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Air–sea heat flux is one of the most important factors that affects ocean circulation, weather, and climate. Satellite remote sensing could serve as an important supplement to the sparse in situ observations for heat flux estimations. In this study, we analyze the uncertainty of the turbulent heat fluxes derived from wind speed measured by the Cyclone Global Navigation Satellite System (CYGNSS) over the global tropical oceans at different time scales. In terms of spatial distribution, there is large uncertainty (approximately 50 to 85 W·m−2 in the RMSE) near the equator in the western Pacific Ocean, the Arabian Sea, the Bay of Bengal, and near the Gulf of Guinea. The turbulent heat fluxes are in agreement with the buoys in representing the intraseasonal and seasonal variability, but more specific regional validations are needed for revealing the synoptic and sub-synoptic phenomena and the diurnal cycle. The uncertainty of the CYGNSS wind speed contributes approximately 50–57% to the uncertainty of the estimation of turbulent heat fluxes at the frequency band with a typical period of 3–7 days. In addition, the input sea surface temperature, rather than the wind speed, results in differences in the estimation of the monthly mean turbulent heat fluxes in the tropical Atlantic Ocean based on the COARE 3.5 algorithm. In conclusion, although the CYGNSS-derived turbulent heat fluxes are basically in good agreement with the in situ observations, our analysis highlights the importance of considering the limitations of these datasets, particularly in high wind speed conditions and for higher-frequency variations, including at synoptic, sub-synoptic, and diurnal time scales.

Forests can buffer the understory against temperature extremes often creating cooler microclimates during warm summer days compared to temperatures outside the forest. The buffering of maximum temperatures in the understory results from a combination of canopy shading and air cooling through soil water evaporation and plant transpiration. Therefore, buffering capacity of forests depends on canopy cover and soil moisture content, which are increasingly threatened by more frequent and severe canopy disturbances and soil droughts. The extent to which this buffering will be maintained in future conditions is unclear due to the lack of understanding about the relationship between soil moisture and air temperature buffering in interaction with canopy cover and topographic settings. We explored how soil moisture variability affects temperature offsets between outside and inside the forest on a daily basis, using temperature and soil moisture data from 57 sites in temperate broadleaved forests in Central Europe over four climatically different summer seasons. Daily maximum temperatures in forest understories were on average 2°C cooler than outside temperatures. The buffering of understory temperatures was more effective when soil moisture was higher, and the offsets were more sensitive to soil moisture on sites with drier soils and on sun-exposed slopes with high topographic heat load. Based on these results, it can be expected that, in a warmer climate with longer dry periods, the soil-water limitation of forest buffering will become more prevalent and will likely lead to changes in understory communities. Our results support the inclusion of soil moisture in models and predictions of forest microclimate, understory biodiversity and tree regeneration, aiming to provide a more precise estimate of the effects of climate change., This research was funded by FORMAS [project 2021-01993 to CG], the Czech Science Foundation [projects GACR 20-28119S and GACR 23-06614S] and the Czech Academy of Sciences [project RVO 67985939]. We thank everyone helping with the data collection.

The micrometeorological elements, radiation budget, and surface energy distribution at four sites with land cover types of vegetable, orchard, maize, and desert in the Heihe River basin (HRB) from June 2012 to September 2012 are compared to investigate the differences in the land–atmosphere interaction between different surface types and the biophysical effects of land use and land cover change on surface temperature. The desert site has the highest soil surface temperature during both daytime and nighttime. The strongest cooling effects of maize, orchard, and vegetable are −20.43, −19.35, and −16.42 K, respectively, during daytime, and the average cooling effects are −1.38, −2.52, and −0.93 K, respectively, at nighttime. The differences in the surface cooling effects of the non-desert sites relative to the desert are attributed to the differences in albedo and incoming shortwave radiation, emissivity and incoming longwave radiation, sensible heat flux, latent heat flux, and soil surface heat flux, according to the direct decomposed temperature metric theory. The radiation terms have negative feedbacks on the cooling effects in the non-desert sites. Latent heat flux plays a key role in the differences in the surface temperature among the four sites during both daytime and nighttime, and the soil surface heat flux is also a main factor at night.

The unique tropical storm (TS) Deliwe (2014) occurred in the northern Mozambique Channel on 17 January 2014 and turned right during its whole life cycle, moving south along the west coast of Madagascar Island. During the development of the TS, the anticyclonic eddies in the Mozambique Channel had an important influence on the intensity and track of Deliwe, which existed for months. In this study, multisource reanalysis, conductivity temperature depth (CTD) and Argo buoy data were used to investigate the mechanism of dynamics. The results showed that the anticyclonic eddies in the Mozambique Channel were a major cause of Deliwe strengthening, weakening and then deflection to the right. On 17 January, the maximum latent heat flux of anticyclonic eddy W1 reached 103.1 w/m2. After Deliwe passed, the tropical cyclone heat potential (TCHP) of anticyclonic eddy W1 was significantly reduced by 3 kJ/cm2. The mixed layer of anticyclonic eddy W1 was deeper than the surrounding waters, supporting the development of Deliwe. As the TS intensity decreased, the low-pressure center of 500 hPa moved above anticyclonic eddy W2, and the westerly wind belt moved northward to form a westerly trough of low pressure, which caused the TS to keep turning right and formed a unique TS track. This study provides a new understanding of the influence of marine anticyclonic eddies on the development of tropical cyclones (TCs) in the Mozambique channel.

Through precipitation retention and evaporation (by both interception and transpiration), woodlands play a significant role in the global moisture cycle. Evaporation is the largest, but at the same time, the most difficult flux to observe in a woodland. Accounting for woodland evaporation is important for hydrological modelling for the efficient development and management of water resources. Assessing evaporation is a challenging undertaking that involves the use of a wide range of equipment and requires skilled personnel. Much work has been conducted on assessing evaporation in agricultural crops. Even satellite data-based models are largely structured to assess evaporation in agricultural crops to the exclusion of understanding evaporation dynamics in natural woodlands, especially in African ecosystems. However, evaporation in woodland surfaces accounts for a significant portion of the water cycle over the terrestrial land mass. Understanding the characteristics of woodland ecosystem evaporation like interception and transpiration, is key to monitoring climate impact on woodland ecosystems, which is important for hydrological modelling and the management of water resources at various scales. One of the key aspects to enable this understanding is the knowledge of woodland phenological interaction with climate variables and the seasonal environmental regimes. “Vegetation phenology” refers to the periodic biological life cycle events of plants, such as leaf flushing and senescence, and corresponding temporal changes in vegetation canopy cover. Solar radiation, temperature and water availability (i.e., rainfall and soil moisture) are some of the key environmental variables that influence plant phenology. The attributes of woodland phenology, solar radiation, temperature and water availability differ across the diverse ecosystems globally, therefore, requires better understanding at a more local or regional level. Yet, evaporation of natural woodlands, especially in African ecosystems, with respect to phenological phases, are poorly characterised. This is largely because phenological studies have mainly focused on northern mid-latitude regions to the exclusion of other regions like the miombo of southern Africa. For increasing the predictive power of hydrological models, it is important to account for the interaction of woodland phenology with climate variables over the seasons and to characterise evaporation. This thesis aims at understanding the miombo woodland evaporation as a consequence of the vegetation phenological interaction with environmental and hydrological variables across seasons. Based on information in public domain, this study is the first independent field observation data-based characterisation of actual evaporation of the miombo woodland. The miombo is a heterogeneous woodland of the genus Brachystegia with the dominant species in the study location being Bauhinia petersenia, Brachystegia longifolia, Brachystegia boehmii, Brachystegia speciformis, Jubenerdia paninculata, Pericopsis angolensis, Uapaca kirkiana and Uapaca sansibarica. Unique phenological attributes are the simultaneous leaf fall, leaf flush and leaf colour changes that normally occur in the dry season between May and October. Most miombo woodland species are broad leaved and have developed dry season coping mechanisms such as deep rooting (capacity to access deep soil moisture and ground water) and vegetation water storage. The canopy closure is varied across the miombo woodland strata and is influenced by several factors including rainfall, soil type, soil moisture and nutrients, species diversity and temperature. These phenological attributes are species dependent, with varied response to phenological stimuli. This study sought to answer the question on the role of the phenology of the miombo woodland in the evaporation dynamics. The thesis also endeavoured to show how phenology, potentially, affects satellite-based evaporation estimates of the miombo woodland. The Luangwa Basin in southern Africa, a largely miombo woodland covered basin, was used as the study area. This basin was chosen because it is located in both the dry miombo woodland and wet miombo woodland in the Zambezian miombo woodland which is the largest strata of the miombo woodland. Furthermore, the Luangwa Basin is located in Zambia which is described as the country possibly with the highest diversity of trees and is said to be the centre of endemism for Brachystegia, with 17 species. To answer the questions on the importance of the phenology of the miombo woodland on the evaporation dynamics, the study used a coupled approach by applying both satellite data and field observations. Phenological changes of the miombo woodland across seasons were assessed using satellite-based data, the normalised difference vegetation index (NDVI) and leaf area index (LAI). Satellite-based data, land surface temperature (LST) and normalised difference infrared index (NDII), were used as proxies for climate variables canopy temperature and canopy vegetation water content. Point scale field estimates of evaporation across three different phenophases of the miombo woodland were obtained using the Bowen ratio distributed temperature sensing (BR-DTS) system. By measuring profiles of air temperature and wet bulb temperature, the evaporation could be estimated via the Bowen ratio method (BR-DTS). Six satellite-based evaporation estimates were compared across different phenophases of the miombo woodland. This was meant to observe the phenophases in which significant diferences in the trend and magnitude of satellite-based evaporation estimates occured. The general water balance approach was used to assess annual actual evaporation at basin scale. Consequently, satellite-based evaporation estimates were compared to the BR-DTS-based evaporation estimates at point scale and the water balance-based evaporation at basin scale. Results, based on satellite data, show that the phenology of the miombo woodland, i.e., changes in woodland canopy cover and photosynthetic activities, have a season-dependent correlation with climate variables. Woodland canopy cover, across phenophases and seasons, appear to be more influenced rather by water than temperature. This may explain the particular species-dependent buffering mechanisms during water limited conditions i.e., leaf shedding, deep rooting systems with access to ground water, and the vegetation water storage mechanisms. In agreement with available literature in public domain it appears there is little variation in canopy cover/closure (i.e., proxied by LAI) in wet miombo woodland in the dry season. At the wet miombo woodland site in Mpika, Zambia, the BR-DTS observations showed that, across the different phenophases, the actual evaporation trend and magnitude appeared to be more associated with the available energy than the changes in the woodland canopy cover. Further analysis showed that the net radiation has a greater influence on actual evaporation as it accounted for more variations in the actual evaporation compared to the changes in the woodland canopy cover (i.e., NDVI). The energy partitioning showed that available energy expenditure varied with phenological season. In the green down phenophase during the cool dry season the available energy was largely partitioned as sensible heat flux. As the temperature and net radiation begun to increase in the early dormant phenophase during the late cool dry season (July August) the available energy appeared to be equally partitioned between sensible and latent heat flux. In the late dormant phenophase during the early warm pre-rainy season (i.e., September) available energy was largely partitioned as latent heat flux. In the green-up phenophase during the late pre-warm rainy season (i.e., October) and early rainy season (i.e., November to December) the avialable energy was largely partitioned as latent heat flux. During the rain days the available energy appeard to be equally partition between latent and sensible heat flux. It appears that as the net radiation and canopy cover increased the available energy was largely partitioned as latent heat flux during the dry season. A remarkable observation was the continued rising trend of actual evaporation even during the lowest woodland canopy cover period in August and September. The rising trend in actual evaporation during the dry season may be due to the developed dry season water stress buffering mechanism such as deep rooting with access to moisture in deep soils and possibly access to ground water. The trend of the BR-DTS-based actual evaporation of the miombo woodland in the dry season points to the interaction between hydro-climate variables (i.e., precipitation linked soil moisture and net radiation) and the plant phenology. When compared to field observations, at point scale, all satellite-based evaporation estimates underestimated actual evaporation of a wet miombo woodland in the dry season and part of the early rainy season. Substantial underestimations were in the dormant and the green-up phenophases. Additionally, except for the WaPOR, the trends of all other satellite-based evaporation estimates differed from that of field observations. Plausible explanations for the behaviour (trend and magnitude) of satellite-based evaporation estimates in the dry season include the non-integration of soil moisture directly into the modelling of transpiration and the optimisation of the rooting depth. For instance, the use of proxies such as the NDVI and LST for soil moisture in surface energy balance models, such as SSEBop, results in uncertainities as the proxies are unable to take into account other factors that influence the sensible heat flux. In MOD16 the use of relative humidity and vapour pressure difference as proxies for soil moisture may be a source of uncertainty in estimating transpiration. On the other hand it has been observed that direct integration of soil moisture in the MOD16 algorithm appeared to improve the accuracy of actual evaporation estimates. This may explain why the WaPOR which integrate soil moisture stress in the algorithm appeared to have a smilar trend to field observations and also had higher estimates of actual evaporation compared to the other satellite-based evaporation estimates. It has also been shown that optimising the rooting depth improves the accuracy of transpiration estimates in vegetation with a dry season. Most miombo woodland species are deep rooting with access to deep soil moisture and potentially groundwater. Therefore, direct integration of soil moisture into the algorithms for the satellite-based evaporation estimates and optimising the rooting depth is likely to improve the accuracy of actual evaporation estimates for the miombo woodland.The phenophase-based comparison at pixel scale in dry miombo woodland and wet miombo woodland and at the Luangwa Basin miombo woodland scale showed similar results. In all three scenarios substantially high coefficients of variation in actual evaporation estimates among satellite-based evaporation estimates were observed in the water limited, high temperature and low woodland canopy cover conditions in the dormant phenophase. The coefficients of variation in actual evaporation estimates were also substantially high in the green-up phenophase at the boundary between the dry season and the rainy season. The lowest coefficients of variation in actual evaporation estimates were observed in water abundant, high temperature, high leaf chlorophyll content and high woodland canopy cover during the maturity/peak phenophase. The high coefficients of variation in actual evaporation estimates, among satellite-based evaporation estimates, in the dormant and green-up phenophases, points to the challenge of estimating the actual evaporation of the miombo woodland in the dry season and early rainy season. The same scenario emerged as was observed at point scale, with reference to field observations, in which satellite-based evaporation estimates which directly integrate soil moisture in their algorithm appeared to have higher estimates of actual evaporation in the dormant phenophase in the dry season. For instance, the FLEX-Topo and WaPOR integrate soil moisture in their algorithms. Compared to each other the FLEX-Topo and WaPOR appeared to have no statistically significant (p-value > 0.5) differences in their trends and mean estimates of actual evaporation in the dormant phenophase in the dry season. Compared to the FLEX-Topo and WaPOR the other four satellite-based evaporation estimates, GLEAM, MOD16, SSEBop and TerraClimate showed statisticantly significant (p-value < 0.05) differences in the trend and mean estimates of actual evaporation in the dormant phenophase in the dry season. Considering the canopy phenology and the associated physiological adaptation of the miombo woodland plants in the dry season, it appears that the direct integration of the soil moisture in the algorithms and optimising the rooting depth is likely to improve the accuracy of the satellite-based evaporation estimates. In the maturity/peak phenophase(s) during the mid-rainy season, compared to other satellite-based evaporation estimates, the MOD16 appeared to have significantly (p-value < 0.05) higher estimates of actual evaporation. The plausible explanation for this observation could be that the interception module of MOD16 is more responsive to the miombo woodland phenology. The wet miombo woodland intercepts between 17-20 percent of rainfall annually. Compared to the general annual water balance-based actual evaporation all six satellite-based evaporation estimates underestimated actual evaporation of the Luangwa Basin. The implication of this observation is that satellite-based evaporation estimates likely underestimates evaporation even in non-miombo woodland such as the mopane woodland that are also part of the larger Luangwa Basin vegetation landscape. However, for a comprehensive overview of the performance of the satellite-based evaporation estimates there is need for vegetation type and land-cover type based assessments of actual evaporation for the Luangwa Basin. At both point and basin scale-based assessments, there was a negative linear relationship between the spatial resolution of satellite-based evaporation estimates and the estimated actual evaporation. Satellite-based evaporation estimates with fine spatial resolutions showed lower underestimates compared to those with coarser resolutions. The implication is that the finer the spatial resolution the lower the underestimation. However, at both assessment scales, the linear relationships between the spatial resolutions and the evaporation estimates were statistically insignificant (i.e., p-value > 0.05). The reason for this outcome is exhibited in that some satellite-based evaporation estimates with relatively coarser spatial resolutions, i.e., SSEBop at both point and basin scale and TerraClimate at basin scale, underestimated less compared to MOD16 which had a finer spatial resolution. Furthermore, at basin scale a coarser spatial resolution estimate FLEX-Topo and a finer spatial resolution estimate WaPOR showed similar magnitude of actual evaporation in the dormant phenophase in the dry season. The implication of this observation is that other factors (i.e., heterogeneity in the landscape, model structure, processes and inputs) influence more the estimated actual evaporation rather than the spatial resolutions of the satellite-based evaporation estimates. Consequently, it appears that satellite-based estimates at finer spatial resolution with the structure, processes and inputs that couple canopy transpiration with the root zone storage, taking into account the vertical upward (beyond 2.5 m) and horizontal moisture flux as well as the canopy phenological changes, are likely to provide actual evaporation estimates that reflect actual conditions of the miombo woodland. This is demonstrated by the WaPOR estimates which appears to include these aspects in simulating actual evaporation. The field-based actual evaporation assessments were conducted in the wet miombo woodland. It is possible that the phenological response to changes in hydrological and climate regimes in the drier miombo woodland are different from the observations at the Mpika site. Therefore, there is need for similar observations to be performed in the drier miombo woodland and to compare the results. However, this thesis has demonstrated the importance of understanding and incorporating the canopy phenology and dry season physiological adaptation (i.e., deep rooting) of the miombo woodland in modelling actual evaporation. Additionally, for basins with heterogenous woodland types like the Luangwa, it is important to conduct actual evaporation assessments in the different vegetation types. This is likely to give a more representative understanding of basin scale evaporation dynamics. Nevertheless, this study has provided a foundation on which other studies can build towards a more comprehensive understanding of the actual evaporation dynamics in this unique woodland.

At the surface of the earth, the available radiative energy Rn is distributed between the ground heat flux and the sensible and latent heat fluxes according to the surface energy balance (SEB) equation. In the past decades, most attempts to measure the individual terms of this equation have revealed a non-closure problem, regardless of the site of observation or period of the year. Today, no definitive answer has been provided to this question. In general, it is suspected that the sensible and latent heat fluxes (H and LvE, respectively) that are calculated with the eddy-covariance technique are underestimated. This paper suggests two additional terms that should be considered in the SEB equation, which are based on thermodynamic considerations. They are directly related to H and LvE and appear to be interesting candidates for explaining (at least in part) the non-closure of the SEB. The distribution of the correction between H and LvE varies as a function of the Bowen ratio B. The correction relative to H is dominant for values of B that are greater than 0.2 and represents more than 80% of the total correction for values greater than unity. The impact of these corrections on the SEB closure was tested on a large set of observations from 24 FLUXNET sites around the world with different vegetation types. The closure defect, which is about 17% in the original dataset, is reduced to about 3% with the proposed corrections.

Data assimilation methods have been used to improve the performances of land surface models by integrating remote sensing and in situ measurements. However, the impact of data assimilation on improving the forecast of land surface variables has not been well studied, which is essential for weather and hydrology forecasting. In this study, a multi-pass land data assimilation scheme (MLDAS) based on the Noah-MP model was used to predict short-term land surface variables (e.g., sensible heat fluxes (H), latent heat fluxes (LE), and surface soil moisture (SM)) by jointly assimilating soil moisture, leaf area index (LAI) and solar-induced chlorophyll fluorescence (SIF). The test was conducted at the Mead site during the growing season (1 May to 30 September) in 2003, 2004, and 2005. Four assimilation-prediction scenarios (assimilating for 15 days, 45 days, 75 days, and 105 days from 1 May, then predicting one future month) are adapted to evaluate the influence of assimilation on subsequent prediction against Noah-MP open-loop simulation (OL). On average, MLDAS produces 28.65%, 27.79%, and 19.15% lower root square deviations (RMSD) for daily H, LE, and SM prediction compared to open-loop run, respectively. The influence of assimilation on prediction can reach around 60 days and 100 days for H (LE) and SM, respectively. Our findings indicate that data assimilation can improve the accuracy of land surface variables in a short-term prediction period.

De acuerdo con las proyecciones de los modelos climáticos, se espera a nivel mundial un aumento en la frecuencia e intensidad de las olas de calor. Este estudio analiza, por primera vez, el efecto de los eventos de olas de calor en los flujos de calor latente (LE) y calor sensible (H) en dos lagunas someras: Laguna La Salada (LS - 39°27′ S, 62°42′ W) y Laguna Sauce Grande (SG - 38°57′ S, 61°24′ W). La velocidad y dirección del viento, la humedad relativa, y las diferencias de temperatura entre el aire y el agua determinaron los cambios en LE y H. Los valores diarios de ambas variables fueron altamente fluctuantes. Los valores medios diarios de H variaron entre -309,4 y 200,5 W m-2 y entre -78,6 y 104,8 W m-2 en LS y SG, respectivamente. Los valores medios diarios de LE variaron entre -152 y 463,9 W m-2 y entre -59,2 y 360,1 W m-2 en LS y SG, respectivamente. Ambos flujos disminuyeron con el paso de eventos de olas de calor, presentando una gran amplitud en los valores. En días con olas de calor comparados con días regulares se registraron cambios de hasta 96% en la media diaria de LE y 671% en la media diaria de H en LS y cambios de hasta 25% en la media diaria de LE y 987% en la media diaria de H para SG. Finalmente, se analizó el futuro incremento de la temperatura del aire para ambas lagunas bajo dos escenarios de calentamiento global (RCP 4.5 y RCP 8.5), que permiten deducir mayores amplitudes de cambio en ambos flujos de calor. Estos resultados contribuyen al desarrollo de modelos para lagunas someras, y a las decisiones de manejo de los recursos hídricos en el futuro. According to model projections, increases in the frequency and intensity of heatwaves are expected all over the world. This study analyzed, for the first time, the effect of heatwaves events on long-term surface latent (LE) and sensible heat fluxes (H) from two shallow lakes: La Salada lake (LS-39°27′ S, 62°42′ W) and Sauce Grande lake (SG-38°57′ S, 61°24′ W). The main drivers of LE and H are wind speed and direction, relative humidity, and the difference between air and water temperature. We found that the daily values of both fluxes were highly fluctuating. Mean daily H values ranged between-309.4 to 200.5 W m-2 and-78.6 to 104.8 W m-2 in LS and SG, respectively. LE oscillated between-152 and 463.9 W m-2 and between-59.2 and 360.1 W m-2 in LS and SG, respectively. Both fluxes decreased with the passage of heatwaves events, presenting a high variation in its amplitude. Changes up to 96% in mean daily LE and 671% in mean daily H for LS and up to 25% in LE and 987% in H for SG were accounted in days with heatwaves respect to regular ones. We analyzed the air temperature increase for both lakes under future global warming scenarios (RCP 4.5 y RCP 8.5), expecting higher amplitudes in heat fluxes. These results contribute to the development of lake models, as well as to water resources management in the future. Fil: Alfonso, María Belén. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto Argentino de Oceanografía. Universidad Nacional del Sur. Instituto Argentino de Oceanografía; Argentina Fil: Brendel, Andrea. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto Argentino de Oceanografía. Universidad Nacional del Sur. Instituto Argentino de Oceanografía; Argentina. Universidad Nacional del Sur. Departamento de Agronomía; Argentina Fil: Vitale, Alejandro José. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto Argentino de Oceanografía. Universidad Nacional del Sur. Instituto Argentino de Oceanografía; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras; Argentina Fil: Piccolo, Maria Cintia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto Argentino de Oceanografía. Universidad Nacional del Sur. Instituto Argentino de Oceanografía; Argentina. Universidad Nacional del Sur. Departamento de Geografía y Turismo; Argentina

A reliable thermal-derived method for spatially and temporally continuous latent heat flux (LE) estimates is vital for agricultural water resource management. In this study, we proposed a novel three-source LE model (TSLEM) derived by all-weather thermal infrared (TIR) land surface temperature (LST) to generate all-sky daily LE in mainland China. In this approach, LE was partitioned into the energy fluxes from canopy transpiration, soil evaporation, and interception water evaporation, respectively. Importantly, a new strategy was used to decompose radiational temperature into soil temperature (Ts), canopy temperature (Tc) and interception water temperature (Ti). Then soil evaporation was estimated by Penman-Monteith (PM) equation that parameterizes a soil resistance as a function of the normalized difference temperature index (NDTI) derived from Ts. A simplified MOD16 algorithm framework was used to estimate canopy transpiration and a Priestley-Taylor (PT) model to estimate interception evaporation. The proposed method was validated using 26 eddy covariance (EC) tower sites in mainland China across various vegetation types and applied to generate spatial continuous daily LE in mainland China. The results show that TSLEM accurately yielded daily LE with an average coefficient of determination (R2) of 0.53 (p

Crop evapotranspiration (ET), which is directly related to latent heat flux, is also a key indicator in determining the water status of crops. In order to estimate the latent heat flux, two-source energy balance (TSEB) models have been developed for thermal imagery from satellite platforms. However, because of the coarse resolution of thermal sensors on the satellite, distinguishing soil and vegetation is difficult which complicates the calculation process and introduces errors in latent heat estimates. In this research, high-resolution thermal datasets (0.05 m) and corresponding RGB datasets (0.03 m) were used for calculating crop latent heat flux using an adapted TSEB model. The RGB datasets were used for supervised classification of soil and vegetation, and the classification results were then used to filter the thermal mosaics to separate vegetation and soil temperatures. The vegetation temperature is used for calculating latent heat flux and the results are validated against the ground reference measurements of latent heat using a handheld porometer. The objective of this research is to introduce a workflow including an adapted TSEB model which is customized for high resolution thermal images from unmanned aircraft systems (UAS) to estimate the latent heat flux of row crops in agricultural fields. Nine dates of data collection in 2018 and 2020 have been evaluated and the root mean square error (RMSE) varies between 16 to 106 W/m2 depending on the days after planting (DAP) and the time of measurement for each day. The results indicate that the workflow introduced here is able to provide estimates of instantaneous latent heat flux (evapotranspiration) measurements for row crops in agricultural fields which will enable people to make reliable decisions related to irrigation scheduling.

The extremely severe tropical cyclone Fani (25 April–5 May 2019) unusually sustained high intensity for a prolonged duration over the Bay of Bengal (BoB). A regional coupled atmosphere–ocean model was used to investigate the atmospheric and oceanic conditions and processes responsible for the sustained intensification of the tropical cyclone (TC) Fani. The coupled model simulated the track and intensification/weakening stages of the cyclone reasonably well. A reduction in sea surface temperature (by −2 °C) and an increase in sea surface salinity due to cyclone-induced upwelling and inertial mixing was noticed in both observations and model. The passage of TC Fani over two geostrophic mesoscale warm-core eddies along the cyclone track was found to supply the necessary energy for the intensification of TC Fani. The sea surface height anomaly and tropical cyclone heat potential (TCHP) were higher during TC Fani than other pre-monsoon cyclones in the BoB. The anomalous TCHP in the warm-core eddy zones (i.e., in excess of >160 kJ cm−2) maintained the warm surface temperature and high air–sea heat fluxes. The air–sea latent heat flux and atmospheric wind shear were favourable for the intensification of the cyclone. The atmospheric moist static energy enhanced up to 360 kJ kg−1 with a deep vertical extension in the atmospheric column supporting the further intensification of TC Fani. Therefore, the unusual oceanic TCHP associated with mesoscale eddies, higher latent heat flux, and enhanced moist static energy in the atmosphere contributed to the sustained intensification of TC Fani for a prolonged period in the BoB.

In the case of lakes, evaporation is one of the most significant losses of water and energy. Based on high-frequency eddy-covariance (EC) measurements between May and September of 2019, the offshore heat and water vapor exchanges are evaluated for the large (~600 km2) but shallow (~3.2 m deep) Lake Balaton (Transdanubian region, Hungary). The role of local driving forces of evaporation in different time scales (from 20 min to one month) is explored, such as water surface and air temperatures, humidity, atmospheric stability, net radiation, and energy budget components. EC-derived water vapor roughness lengths and transfer coefficients (Cq) show an apparent intra-seasonal variation. Different energy balance-based evaporation estimation methods (such as the Priestley-Taylor and the Penman-Monteith) confirm this observation. Furthermore, this has suggested the existence of an intra-annual variation in these parameters. This hypothesis is verified using ten years of water balance measurements, from which, as a first step, evaporation rates and, second, transfer coefficients are derived on a monthly scale. Cq is highly reduced in winter months (~1 × 10−3) compared to summer months (~2.5 × 10−3) and strongly correlated with net radiation. The application of time-varying Cq significantly increases the accuracy of evaporation estimation when the Monin-Obukhov similarity theory-based aerodynamic method is applied. The determination coefficient increases to 0.84 compared to 0.52 when a constant Cq is employed.

The Cyclone Global Navigation Satellite System (CYGNSS) mission can measure sea surface wind over tropical oceans with unprecedented temporal resolution and spatial coverage, so as to estimate surface latent and sensible heat fluxes (LHF and SHF). In this paper, the satellite-derived LHF/SHF estimates from CYGNSS are quantitatively evaluated and analyzed by those from the Global Tropical Moored Buoy. Comparisons of the LHF and SHF estimates demonstrate the good performance and reliability of CYGNSS heat flux products during the period of 2017–2022, including CYGNSS Level 2 Ocean Surface Heat Flux Climate Data Record (CDR) Version 1.0 and Version 1.1. Different latent heat characteristics in the tropical oceans are evaluated separately based on each buoy array, suggesting better agreement in the Atlantic for LHF/SHF products. Based on the Coupled Ocean-Atmosphere Response Experiment 3.5 algorithm, the impact of wind speed on the LHF/SHF estimates is analyzed by using the the Science Data Record V3.1 and NOAA V1.2 science wind products. The results show that the performance of satellite-derived wind speed directly affects the accuracy of LHF products, with an improvement of 17% in root-mean-square error over that of LHF CDR V1.0. Especially, in the Indian Ocean, accuracy can be improved by 26.8%. This paper demonstrates that the heat flux estimates along the orbit of the CYGNSS are an important supplement to in situ observational data and will benefit the study of global climate change., This work was supported by the Scientific Research Fund of the Second Institute of Oceanography, MNR, grand no. JB2205, as well as the Innovation Group Project of Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai) (No. 311021004), by the European Space Agency and Ministry of Science and Technology Dragon 5 Cooperation Programme under Grant 58009.

Surface energy budgets are important to the ecohydrology of complex terrain, where land surfaces cycle in and out of shadows creating distinct microclimates. Shading in such environments can help regulate downstream flow over the course of a growing season, but our knowledge on how shadows impact the energy budget and consequently ecohydrology in montane ecosystems is very limited. We investigated the influence of horizon shade on the surface energy fluxes of a subalpine headwater wetland in the Canadian Rocky Mountains during the growing season. During the study, surface insolation decreased by 60% (32% due to evolving horizon shade and 28% from seasonality). The influence of shade on the energy budget varied between two distinct periods: (1) Stable Shade, when horizon shade was constant and reduced sunlight by 2 h per day, and (2) Dynamic Shade, when shade increased and reduced sunlight by 0.18 h more each day, equivalent to a 13% reduction in incoming shortwave radiation and 16% in net radiation. Latent heat flux, the dominant energy flux at our site, varied temporally because of changes in incoming radiation, atmospheric demand, soil moisture and shade. Horizon shade controlled soil moisture at our site by prolonging snowmelt and reducing evapotranspiration in the late growing season, resulting in increased water storage capacity compared to other mountain wetlands. With the mounting risk of climate-change-driven severe spring flooding and late season droughts downstream of mountain headwaters, shaded subalpine wetlands provide important ecohydrological and mitigation services that are worthy of further study and mapping. This will help us better understand and protect mountain and prairie water resources.

The Latent Heat Flux (LE) is an important component of surface water heat transfer and hydrological cycle, and monitoring it is of great value for water resource management and crop water demand estimation. The Heihe River Basin has complex topography, which ensures better variable control in LE analysis. In this paper, the time series analysis and statistics of LE under different underlying surface conditions in summer were carried out by using the eddy correlation observation data in the Heihe River Basin, and the regression factors were analyzed. The results show that when the underlying surface types are greatly different, there are obvious differences in the daily distribution of LE, the daily variation trend of LE and the influencing factors. The range of diurnal distribution of LE in dune, Gobi and desert from −50 W/m2 to 100 W/m2. The diurnal LE distribution of vegetable fields, cornfields and wetlands were about 55% concentrated between −50 W/m2 and 100 W/m2. Temperature and carbon dioxide concentration (CO2) are the dominant factors affecting latent heat flux. Further analysis of temperature and CO2 is carried out by stepwise regression analysis, and multiple regression models are established. In terms of correlation and confidence, the results are better than the single factor fitting, which can better reflect the synergistic effect of temperature and CO2 on LE.

Coastal tidal wetlands are significant and vulnerable aquatic ecosystems. Quantitative remote sensing of biophysical and biochemical properties in coastal tidal wetland habitats through the inversion of physical models has vital practical significance for monitoring ecosystem function, environmental restoration, the global carbon, and nitrogen cycles. The objectives of this research were to map leaf area index (LAI), chlorophyll content, as well as the sensible heat flux, latent heat flux, and productivity in Chongming Dongtan coastal tidal wetland habitats of China and to provide a mapping protocol of biophysical and biochemical properties in Chongming Dongtan wetland for environmental protection and restoration as well as assessment and monitoring. In order to obtain significant information for biodiversity protection and management, a method based on the Soil Canopy Observation of Photosynthesis and Energy fluxes model and lookup table approach has been developed. The results derived from our study contain the reflectance values of Scirpus mariqueter and Phragmites australis spectra are lower than those commonly found for vegetated areas. This may be caused by the dark soil background and low LAI. Moreover, as for the values of latent heat flux (between 120 and 190 W m − 2) and productivity (between 3 and 14 μmol m − 2 s − 1), mudflats are lower than vegetation. However, the values of sensible heat flux (between 140 and 170 W m − 2) of mudflats are higher than that of vegetation.

Coarse spatial resolution sensors play a major role in capturing temporal variation, as satellite images that capture fine spatial scales have a relatively long revisit cycle. The trade-off between the revisit cycle and spatial resolution hinders the access of terrestrial latent heat flux (LE) data with both fine spatial and temporal resolution. In this paper, we firstly investigated the capability of an Extremely Randomized Trees Fusion Model (ERTFM) to reconstruct high spatiotemporal resolution reflectance data from a fusion of the Chinese GaoFen-1 (GF-1) and the Moderate Resolution Imaging Spectroradiometer (MODIS) products. Then, based on the merged reflectance data, we used a Modified-Satellite Priestley–Taylor (MS–PT) algorithm to generate LE products at high spatial and temporal resolutions. Our results illustrated that the ERTFM-based reflectance estimates showed close similarity with observed GF-1 images and the predicted NDVI agreed well with observed NDVI at two corresponding dates (r = 0.76 and 0.86, respectively). In comparison with other four fusion methods, including the widely used spatial and temporal adaptive reflectance fusion model (STARFM) and the enhanced STARFM, ERTFM had the best performance in terms of predicting reflectance (SSIM = 0.91; r = 0.77). Further analysis revealed that LE estimates using ERTFM-based data presented more detailed spatiotemporal characteristics and provided close agreement with site-level LE observations, with an R2 of 0.81 and an RMSE of 19.18 W/m2. Our findings suggest that the ERTFM can be used to improve LE estimation with high frequency and high spatial resolution, meaning that it has great potential to support agricultural monitoring and irrigation management.

Spatial estimates of crop evapotranspiration with high accuracy from the field to watershed scale have become increasingly important for water management, particularly over irrigated agriculture in semiarid regions. Here, we provide a comprehensive assessment on patterns of annual agricultural water use over California's Central Valley, using 30‐m daily evapotranspiration estimates based on Landsat satellite data. A semiempirical Priestley‐Taylor approach was locally optimized and cross‐validated with available field measurements for major crops including alfalfa, almond, citrus, corn, pasture, and rice. The evapotranspiration estimates explained >70% variance in daily measurements from independent sites with an RMSE of 0.88 mm day−1. When aggregated over the Valley, we estimated an average evapotranspiration of 820 ± 290 mm yr−1 in 2014. Agricultural water use varied significantly across and within crop types, with a coefficient of variation ranging from 8% for Rice (1,110 ± 85 mm yr−1) to 59% for Pistachio (592 ± 352 mm yr−1). Total water uses in 2016 increased by 9.6%, as compared to 2014, mostly because of land‐use conversion from fallow/idle land to cropland. Analysis across 134 Groundwater Sustainability Agencies (GSAs) further showed a large variation of agricultural evapotranspiration among and within GSAs, especially for tree crops, e.g., almond evapotranspiration ranging from 339 ± 80 mm yr−1 in Tracy to 1,240 ± 136 mm yr−1 in Tri‐County Water Authority. Continuous monitoring and assessment of the dynamics and spatial heterogeneity of agricultural evapotranspiration provide data‐driven guidance for more effective land use and water planning across scales., Key Points A 30‐m daily evapotranspiration product estimated using regionally optimized approach and Landsat Analysis Ready Data Collection 1Assessment of agricultural consumptive water use over Central Valley provides critical guidance for sustainable groundwater managementLarge variation of water use was found, mostly due to crop diversity, age structure, and physiological factors

The impacts of extreme heat events are amplified in cities due to unique urban thermal properties. Urban greenspace mitigates high temperatures through evapotranspiration and shading; however, quantification of vegetative cooling potential in cities is often limited to simple remote sensing greenness indices or sparse, in situ measurements. Here, we develop a spatially explicit, high-resolution model of urban latent heat flux from vegetation. The model iterates through three core equations that consider urban climatological and physiological characteristics, producing estimates of latent heat flux at 30-m spatial resolution and hourly temporal resolution. We find strong agreement between field observations and model estimates of latent heat flux across a range of ecosystem types, including cities. This model introduces a valuable tool to quantify the spatial heterogeneity of vegetation cooling benefits across the complex landscape of cities at an adequate resolution to inform policies addressing the effects of extreme heat events.

The terrestrial biosphere removes carbon dioxide (CO 2 ) from the atmosphere through photosynthesis and is a major sink for atmospheric pollutants like ozone. It is also the main source of biogenic volatile organic compounds (BVOCs) in the atmosphere. In turn, atmospheric conditions such as temperature, precipitation and photosynthetically active radiation regulate the growth and functioning of plants. The role of some environmental factors like temperature and solar radiation in regulating plant physiological processes are well understood and parameterised in land surface models (LSMs) but others like drought stress and ozone damage are poorly understood and hence poorly represented in LSMs. Yet, these LSMs are integral to climate modelling and climate change mitigation measures as they provide estimates of carbon stored in forests currently and how this will change in future. This thesis seeks to bridge the gap between the latest scientific knowledge about the effects of drought stress and ozone damage on plant physiological processes, and how these stressors are currently modelled. The response of plant isoprene emissions and gas exchange to drought stress and ozone damage was investigated using various model parametrisations, and long-term measurements of isoprene mixing ratios and fluxes, carbon dioxide and water fluxes made in a broad range of forest ecosystems. We find that current isoprene emission models are unable to account for stress-induced isoprene emissions during mild or moderate drought stress leading to underestimation of observed isoprene mixing ratios and fluxes. New methods for modelling isoprene emissions during moderate drought were developed and shown to improve model reproduction of observations. Further, it is shown that both drought stress and ozone damage act to reduce plant productivity and gas exchange. However, the impact of drought stress on vegetation was found to outweigh that of ozone damage at individual forest sites in both present day and future climate scenarios but accounting for the impact of both stress factors provided the best model-observation fit. As global climate changes, abiotic stress factors will become increasingly important in regulating biosphere-atmosphere interactions with potentially negative impacts on plant productivity and hence climate mitigation efforts. These findings highlight the need for more observations, especially in remote and data-sparse regions of the world such as the tropics, to improve understanding of how plants will respond to future stress, and how to better model the impacts.

As climate change progresses, urban areas are increasingly affected by water scarcity and the urban heat island effect. Evapotranspiration (ET) is a crucial component of urban greening initiatives of cities worldwide aimed at mitigating these issues. However, ET estimation methods in urban areas have so far been limited. An expanding number of flux towers in urban environments provide the opportunity to directly measure ET by the eddy covariance method. In this study, we present a novel approach to model urban ET by combining flux footprint modeling, remote sensing and geographic information system (GIS) data, and deep learning and machine learning techniques. This approach facilitates spatio-temporal extrapolation of ET at a half-hourly resolution; we tested this approach with a two-year dataset from two flux towers in Berlin, Germany. The benefit of integrating remote sensing and GIS data into models was investigated by testing four predictor scenarios. Two algorithms (1D convolutional neural networks (CNNs) and random forest (RF)) were compared. The best-performing models were then used to model ET values for the year 2019. The inclusion of GIS data extracted using flux footprints enhanced the predictive accuracy of models, particularly when meteorological data was more limited. The best-performing scenario (meteorological and GIS data) showed an RMSE of 0.0239 mm/h and R2 of 0.840 with RF and an RMSE of 0.0250 mm/h and a R2 of 0.824 with 1D CNN for the more vegetated site. The 2019 ET sum was substantially higher at the site surrounded by more urban greenery (366 mm) than at the inner-city site (223 mm), demonstrating the substantial influence of vegetation on the urban water cycle. The proposed method is highly promising for modeling ET in a heterogeneous urban environment and can support climate change mitigation initiatives of urban areas worldwide.

Evapotranspiration is essential for precise irrigation and water resource management. Previous literature suggested that eddy covariance (EC) systems could directly measure evapotranspiration in agricultural fields. However, the eddy covariance method remains difficult for routine use, due to its high cost, operational complexity, and relatively multifaceted raw data processing. An alternative method is the flux variance (FV) method, which can estimate the sensible heat flux using high-frequency air temperature measurements by fine-wire thermocouples, at relatively low-cost and with less complexity. Additional measurements of the net radiation and soil heat flux permit the extraction of latent heat flux through the energy balance closure equation. This study examined the performance of the FV method and the results were compared against direct eddy covariance measurements. Data were collected from November 2018 to July 2019, covering seasonal variations. Due to the method’s limitation, only the data under unstable conditions were used for the analysis and days with rainfall were omitted. The results showed that the FV-estimated sensible heat flux was in good agreement with that of eddy covariance in the seasons of winter 2018 and summer 2019. The best agreement between the estimated and measured sensible heat fluxes was observed in the summer, with R2 = 0.83, RMSE = 34.97 Wm−2 and RE = 8.20%. The FV extracted latent heat flux was in good agreement with that measured by EC for both seasons. The best result was obtained in the summer, with R2 = 0.92, RMSE = 23.12 Wm−2, and RE = 6.37%. Overall estimations of sensible and latent heat fluxes by the FV method were in close relation with the eddy covariance data.

An accurate and spatially continuous estimation of terrestrial latent heat flux (LE) is fundamental and crucial for the rational utilization of water resources in the Haihe River Basin (HRB). However, the sparsity of flux observation sites hinders the accurate characterization of spatiotemporal LE patterns over the HRB. In this study, we estimated the daily LE across the HRB using the gradient boosting regression tree (GBRT) from global land surface satellite NDVI data, reanalysis data and eddy covariance data. Compared with the random forests (RF) and extra tree regressor (ETR) methods, the GBRT obtains the best results, with R2 = 0.86 and root mean square error (RMSE = 18.1 W/m2. Then, we applied the GBRT algorithm to map the average annual terrestrial LE of the HRB from 2016 to 2018 with a spatial resolution of 0.05°. When compared with the Global Land Surface Satellite (GLASS) and Moderate Resolution Imaging Spectroradiometer (MODIS) LE products, the difference between the terrestrial LE estimated by the GBRT algorithm and the GLASS and MODIS products was less than 20 W/m2 in most areas; thus, the GBRT algorithm was reliable and reasonable for estimating the long-term LE estimation over the HRB.

The Kuroshio and its extension (KE) significantly influences regional climate through meridional heat transport from the tropical ocean. In this study, the observational and reanalysis datasets are used to investigate the impact of the latent heat flux (LHF) over the KE region on downstream rainfall and the underlying mechanism. The result shows a “seesaw” structure in rainfall anomaly, dominating the Western Canada and the southwestern North America with a correlation coefficient of 0.77 between the two modes. In strong LHF years, strengthened LHF favors to enhance precipitation in the Western Canada and reduce that in the southwestern North America. This is primarily associated with an anomalous cyclonic circulation over the KE region, which enhances southwesterly precipitation and latent heating in the middle troposphere. The heating excites an anomalous cyclonic circulation to its west and an anticyclonic circulation to its east, helping to reinforce the existing anomalous cyclonic circulation in turn and form a positive feedback. The conditions associated with La Niña events favor to above processes. To the upper troposphere, the deepened anomalous cyclonic circulation due to enhanced eddy activities and atmospheric baroclinic instability over the KE strengthens subtropical westerly jet stream and thereby extends eastward on the 200 hPa level. Correspondingly, an elongated zonally lower level cyclonic circulation anomaly across the North Pacific leads to a moisture convergence in the Western Canada, which is mainly resulted from the anomalous positive vorticity advection over the left side of the exit region of the jet stream. The opposite circumstance occurs in weak LHF years, presenting an opposed anomalous circulation and rainfall pattern.

O objetivo deste trabalho foi propor uma metodologia para a espacialização dos componentes do Balanço de Energia (BE) a partir do uso conjugado de produtos do sensor MODIS e dados de reanálise ERA Interim e avaliar o desempenho das estimativas geradas pelos modelos OSEB e METRIC nas condições de clima subtropical úmido que predominam no Rio Grande do Sul, Brasil. O período de estudo foi de 3 anos consecutivos, de 2009 a 2011. Os padrões de variação temporal dos componentes do BE foram analisados comparando os valores estimados pelos modelos frente às medidas de referência de uma torre micrometeorológica (rede Sulflux). Para análise de variabilidade espacial foi calculada a evapotranspiração de referência (ETo) em escala local (dados de estações meteorológicas do Instituto Nacional de Meteorologia) e em escala regional (dados de reanálise ERA Interim) e verificada a coerência entre estas estimativas. Após, utilizando somente os pixels em que fluxo de calor sensível representava mais do que 50% do saldo de radiação, foram construídos mapas de correlação entre ETo ERA Interim e fluxo de calor latente. As estimativas dos componentes do BE apresentam coerência, tanto na ordem de magnitude, como na variação ao longo do ano quando comparadas às medidas de referência da torre micrometeorológica. As análises de variabilidade espacial também apresentaram resultados satisfatórios para ambos modelos, porém o modelo METRIC apresentou maior coerência e proporcionou um maior número de datas com resultados consistentes, sendo, assim, indicado como o modelo mais apto para a construção da série temporal. This work aims at proposing a methodology to spatialize the Energy Balance (EB) components from the combined use of MODIS sensor products and ERA-Interim reanalysis data, and to evaluate the performance of the OSEB and METRIC models for estimating EB components in the predominantly humid subtropical climate of Rio Grande do Sul, Brazil. The research was conducted for 3 consecutive years from 2009 to 2011. The temporal variation patterns of the EB components were analyzed by comparing the values estimated by the models against the reference measurements of a micrometeorological tower (Sulflux network). For the spatial variability analysis, reference evapotranspiration (ETo) was calculated at a local scale (data from Weather stations of the National Institute of Meteorology) and a regional scale (ERA-Interim reanalysis data) while the consistency between these estimates was also verified. Afterward, using only the pixels in which the sensible heat flux represented more than 50% of the radiation balance, correlation maps between ETo ERA-Interim and latent heat fluxes were constructed. The estimated BE components are consistent regarding both, the order of magnitude and variation throughout the year, when compared to the reference measurements of the micrometeorological tower. The spatial variability analyses also reveal satisfactory results for both models, however, the METRIC model results showed greater coherence since it provided a greater number of dates with consistent results, thus being indicated as the most suitable model for building the time series.

The Radiative Transfer Model (RTM) is an explicitly resolved three-dimensional multi-reflection radiation model integrated into the PALM modelling system. It is responsible for modelling complex radiative interactions within the urban canopy. It represents a key component in modelling energy transfer inside the urban layer and consequently PALM's ability to provide explicit simulations of the urban canopy at metre-scale resolution. This paper presents RTM version 3.0, which is integrated into the PALM modelling system version 6.0. This version of RTM has been substantially improved over previous versions. A more realistic representation is enabled by the newly simulated processes, e.g. the interaction of longwave radiation with the plant canopy, evapotranspiration and latent heat flux, calculation of mean radiant temperature, and bidirectional interaction with the radiation forcing model. The new version also features novel discretization schemes and algorithms, namely the angular discretization and the azimuthal ray tracing, which offer significantly improved scalability and computational efficiency, enabling larger parallel simulations. It has been successfully tested on a realistic urban scenario with a horizontal size of over 6 million grid points using 8192 parallel processes. © 2021 Pavel Krč et al.

Evaporation (E) is a critical component of the water and energy budget in lake systems yet is challenging to quantify directly and continuously. We examined the magnitude and changes of E and its drivers over Lake Erie-the shallowest and most southern lake of the Laurentian Great Lakes. We deployed two eddy-covariance tower sites in the western Lake Erie Basin-one located nearshore (CB) and one offshore (LI)-from September 2011 through May 2016. Monthly E varied from 5 to 120mm, with maximum E occurring in August-October. The annual E was 635±42 (±SD) mm at CB and 604±32mm at LI. Mean winter (October-March) E was 189±61mm at CB and 178±25mm at LI, accounting for 29.8% and 29.4% of annual E. Mean daily E was 1.8mm during the coldest month (January) and 7.4mm in the warmest month (July). Monthly E exhibited a strong positive linear relationship to the product of wind speed and vapor pressure deficit. Pronounced seasonal patterns in surface energy fluxes were observed with a 2-month lag in E from R n, due to the lake's heat storage. This lag was shorter than reports regarding other Great Lakes. Difference in E between the offshore and nearshore sites reflected within-lake spatial heterogeneity, likely attributable to climatic and bathymetric differences between them. These findings suggest that predictive models need to consider lake-specific heat storage and spatial heterogeneity in order to accurately simulate lake E and its seasonal dynamics.

Human land use intensity affects the surface energy balance by changing the biogeophysical parameters. This study used Moderate Resolution Imaging Spectroradiometer remote sensing data and surface energy balance algorithms to quantify changes in surface energy budgets corresponding to changes in land use in Beijing from 2000 to 2015. Land use was reclassified by considering land use intensity. The difference in the latent heat flux (LE) and net radiation (Rn) (LE&minus, Rn) expressed the warming or cooling effect. The results showed that: (i) The increasing trend of net longwave radiation in Beijing offset the decreasing trend of net shortwave radiation. The Rn changed slightly, while the LE and LE&minus, Rn showed a significant increase of 0.55 and 0.56 W/(m&sup2, ∙year), respectively. The findings indicated that considering only radiative forcing, or even Rn, was not enough to measure the impacts of land use change on the energy budget. (ii) The order of Rn, LE, and LE&minus, Rn values from high to low were natural and seminatural areas, cropland, mixed pixel areas, urban expansion areas, and old urban areas. Compared with natural and seminatural areas, the changing LE&minus, Rn trend in the other four land use types decreased with the increase in human impact intensity, indicating that human activities weakened the positive change trend of LE&minus, Rn and increased the warming effect. (iii) Although the temporal trend of LE increased in Beijing from 2000 to 2015, the effect of Rn on LE&minus, Rn was greater than that of LE, especially in the four land use types affected by human activities. The results for surface temperature in various land use types confirmed this point. This study highlights the energy budget differences of various land use types affected by human activities. It makes an important contribution to understanding the urban heat island effect from a biogeophysical perspective.

Scanlon and Sahu (2008) and Scanlon and Kustas (2010) proposed a source partitioning method (SK10 in the following) to estimate contributions of transpiration, evaporation, photosynthesis, and respiration to H$_2$O and CO$_2$ fluxes obtained by the eddy covariance method. High frequency eddy covariance raw data time series are needed, and the source partitioning is estimated based on separate application of the flux-variance similarity theory to stomatal and non-stomatal components of the regarded fluxes, as well as on additional assumptions on leaf-level water use efficiency (WUE).\\We applied SK10 to data from two test sites (forest and cropland) and analyzed partitioning results depending on various ways to estimate WUE from available data. Also, we conducted large eddy simulations (LES), simulating the turbulent transport of H$_2$O and CO$_2$ for contrasting vertical distributions of the canopy sinks/sources, as well as for varying relative magnitudes of soil sources and canopy sinks/sources. SK10 was applied to the synthetic high frequency data generated by LES and the effects of canopy type, measurement height, given sink-source-distributions, and input of varying WUEs were tested regarding the partitioning performance. SK10 requires that the correlation coefficient between stomatal and non-stomatal scalar fluctuations is determined by the ratio of the transfer efficiencies of these scalar components, an assumption (transfer assumption in the following) that could be tested with the generated LES data.\\The partitioning results of the field sites yielded satisfactory flux fractions, when fair-weather conditions (no precipitation) and a high productive state of the vegetation were present. Further, partitioning performance with regard to soil fluxes increased with crop maturity. Results also showed relatively large dependencies on WUE, where the partitioning factors (median) changed by around -57% and +36%. Measurements of outgoing longwave radiation used for the estimation of foliage temperature and WUE could slightly increase the plausibility of the partitioning results in comparison to soil respiration measurements by decreasing the partitioning factor by up to 42%. The LES-based analysis revealed that for a satisfying performance of SK10, a certain degree of decorrelation of the H$_2$O and CO$_2$ fluctuations (here, |ρ$_{q’c’}$| < 0.975) was needed. This decorrelation is enhanced by a clear separation between soil sources and canopy sinks/sources, and for observations within the roughness sublayer. The expected dependence of the partitioning results on the WUE input could be observed. However, due to violation of the abovementioned transfer assumption, the known true input WUE did not yield the known true input partitioning. This could only be achieved after introducing correction factors for the transfer assumption, which were known however only in the special case of the LES experiments.

In this paper, we address the retrieval of spatially distributed latent heat flux ( &lambda, E) over a tropical dry forest using multi-spectral and thermal unmanned aerial vehicle (UAV) imagery. The study was carried out in the Santa Rosa National Park Environmental Monitoring Super-Site, Costa Rica, in June 2016. The triangle method was used to derive &lambda, E from the UAV imagery and the results were compared to &lambda, E measurements of an eddy covariance system within the coincident eddy flux tower footprint. The tower footprint was derived using a two-dimensional parameterization model for flux footprint prediction. The comparisons with the flux tower measurements showed a mean relative difference of 10.98% with a slight overestimation of the UAV-based flux retrievals by nearly 7.7 Wm &minus, 2 . The results are in good agreement with satellite-based retrievals, as provided by the literature, for which the triangle method was initially developed and mostly used so far. This study proved to be a promising approach for transferring the triangle method to UAV imagery in ecosystems such as tropical dry forests. With the presented approach, new details in spatially distributed latent heat flux estimates at ultra-high resolution are now possible, thereby potentially closing the gap in spatial resolution between satellites and flux towers. Even more, it allows tracing the latent heat flux from single trees at leaf level. Besides, this approach also opens new perspectives for the monitoring of latent heat fluxes in tropical dry forests.

Evaporation (E) is a critical component of the water and energy budget in lake systems yet is challenging to quantify directly and continuously. We examined the magnitude and changes of E and its drivers over Lake Erie—the shallowest and most southern lake of the Laurentian Great Lakes. We deployed two eddy‐covariance tower sites in the western Lake Erie Basin—one located nearshore (CB) and one offshore (LI)—from September 2011 through May 2016. Monthly E varied from 5 to 120 mm, with maximum E occurring in August–October. The annual E was 635 ± 42 (±SD) mm at CB and 604 ± 32 mm at LI. Mean winter (October–March) E was 189 ± 61 mm at CB and 178 ± 25 mm at LI, accounting for 29.8% and 29.4% of annual E. Mean daily E was 1.8 mm during the coldest month (January) and 7.4 mm in the warmest month (July). Monthly E exhibited a strong positive linear relationship to the product of wind speed and vapor pressure deficit. Pronounced seasonal patterns in surface energy fluxes were observed with a 2‐month lag in E from R n, due to the lake's heat storage. This lag was shorter than reports regarding other Great Lakes. Difference in E between the offshore and nearshore sites reflected within‐lake spatial heterogeneity, likely attributable to climatic and bathymetric differences between them. These findings suggest that predictive models need to consider lake‐specific heat storage and spatial heterogeneity in order to accurately simulate lake E and its seasonal dynamics., Key Points The maximum lake evaporation occurred in August–October, with one third in winter over the annual evaporationMonthly evaporation showed a positive linear relationship with vapor pressure deficit and temperature but not correlated with wind speedPronounced seasonal patterns in the surface energy fluxes were observed with a 2‐month lag in evaporation from net radiation

An accurate assessment of evapotranspiration (ET) is crucially needed at the basin scale for studying the hydrological processes and water balance especially from upstream to downstream. In the mountains, this term is poorly understood because of various challenges, including the vegetation complexity, plant diversity, lack of available data and because the in situ direct measurement of ET is difficult in complex terrain. The main objective of this work was to investigate the potential of a Two-Source-Energy-Balance model (TSEB) driven by the Landsat and MODIS data for estimating ET over a complex mountain region. The complexity is associated with the type of the vegetation canopy as well as the changes in topography. For validating purposes, a large-aperture scintillometer (LAS) was set up over a heterogeneous transect of about 1.4 km to measure sensible (H) and latent heat (LE) fluxes. Additionally, two towers of eddy covariance (EC) systems were installed along the LAS transect. First, the model was tested at the local scale against the EC measurements using multi-scale remote sensing (MODIS and Landsat) inputs at the satellite overpasses. The obtained averaged values of the root mean square error (RMSE) and correlation coefficient (R) were about 72.4 Wm−2 and 0.79 and 82.0 Wm−2 and 0.52 for Landsat and MODIS data, respectively. Secondly, the potential of the TSEB model for evaluating the latent heat fluxes at large scale was investigated by aggregating the derived parameters from both satellites based on the LAS footprint. As for the local scale, the comparison of the latent heat fluxes simulated by TSEB driven by Landsat data performed well against those measured by the LAS (R = 0.69, RMSE = 68.0 Wm−2), while slightly more scattering was observed when MODIS products were used (R = 0.38, RMSE = 99.8 Wm−2). Based on the obtained results, it can be concluded that (1) the TSEB model can be fairly used to estimate the evapotranspiration over the mountain regions; and (2) medium- to high-resolution inputs are a better option than coarse-resolution products for describing this kind of complex terrain.

The ECOsystem Space Thermal Radiometer Experiment on the Space Station (ECOSTRESS) was launched to the International Space Station on June 29, 2018 by the National Aeronautics and Space Administration (NASA). The primary scientific focus of ECOSTRESS is on evapotranspiration (ET), which occurs as Level 3 (L3) latent heat flux (LE) data products. This data is generated from the Level 2 Earth Surface Temperature and Emissivity Product (L2_LSTE), along with the atmospheric and ancillary surface data. Here, we provide the first validation (Stage 1, preliminary) of the global product ECOSTRESS clear - sky ET (L3_ET_PT - JPL, Version 6.0) against LE measurements at 82 eddy covariance sites around the world. Overall, the ECOSTRESS ET product performs well against site measurements (instant clear sky / flyover time: r 2 = 0.88; overall bias = 8%; normalized root mean square error, RMSE = 6%) . ET uncertainty was generally constant across climate zones, biome types, and times of day (ECOSTRESS samples the diurnal cycle), although temperate sites are over-represented. ECOSTRESS 70 m high spatial resolution improved correlations by 85% and RMSE by 62%, relative to 1 km pixels. This document serves as a reference for the accuracy of ECOSTRESS L3 ET and the Stage 1 validation status for subsequent science that continues to use this data. Fil: Fisher, Joshua B. California Institute of Technology. Jet Propulsion Laboratory; Estados Unidos Fil: Lee, Brian. California Institute of Technology. Jet Propulsion Laboratory; Estados Unidos Fil: Purdy, Adam J. California Institute of Technology. Jet Propulsion Laboratory; Estados Unidos Fil: Halverson, Gregory H. California Institute of Technology. Jet Propulsion Laboratory; Estados Unidos Fil: Dohlen, Matthew B. California Institute of Technology. Jet Propulsion Laboratory; Estados Unidos Fil: Cawse - Nicholson, Kerry. California Institute of Technology. Jet Propulsion Laboratory; Estados Unidos Fil: Wang, Audrey. California Institute of Technology. Jet Propulsion Laboratory; Estados Unidos Fil: Anderson, Ray G. U.S. Department of Agriculture; Estados Unidos Fil: Aragon, Bruno. King Abdullah University of Science and Technology. Division of Biological and Environmental Science and Engineering. Hydrology, Agriculture and Land Observation Group (HALO); Arabia Saudita Fil: Arain, M. Alfat. McMaster University. School of Geography and Earth Sciences; Canadá Fil: Baldocchi, Dennis D. University of California, Berkeley. Department of Environmental Science, Policy and Management; Estados Unidos Fil: Baker, John M. U.S. Department of Agriculture; Estados Unidos Fil: Barral, Helene. University Montpellier. HydroSciences Montpellier (HSM); Francia Fil: Bernacchi, Carl J. University of Illinois Urbana‐Champaign. Institute for Sustainability, Energy, and Environment and Carl R. Woese Institute for Genomic Biology. Center for Advanced Bioenergy and Bioproducts Innovation; Estados Unidos. U.S. Department of Agriculture, Global Change and Photosynthesis Research Unit; Estados Unidos Fil: Bernhofer, Christian. Technische Universität Dresden, Institute of Hydrology and Meteorology; Alemania Fil: Biraud, Sebastien C. Lawrence Berkeley National Laboratory; Estados Unidos Fil: Bohrer, Gil. Ohio State University. Department of Civil, Environmental and Geodetic Engineering; Estados Unidos Fil: Brunsell, Nathaniel. University of Kansas. Department of Geography and Atmospheric Science; Estados Unidos Fil: Cappelaere, Bernard. University Montpellier. HydroSciences Montpellier (HSM); Francia Fil: Castro - Contreras, Saulo. University of Alberta. Earth and Atmospheric Sciences Department. Centre for Earth Observation Sciences (CEOS); Canadá Fil: Chum, Junghwa. National Institute of Forest Science; Corea del Sur Fil: Conrad, Bryan. University of Kansas. Department of Geography and Atmospheric Science; Estados Unidos Fil: Cremonese, Edoardo. Environmental Protection Agency of Aosta Valley; Italia Fil: Demarty, Jerome. University Montpellier. HydroSciences Montpellier (HSM); Francia Fil: Desai, Ankur R. University of Wisconsin‐Madison. Department of Atmospheric and Oceanic Sciences; Estados Unidos Fil: De Ligne, Anne. University of Liege. TERRA Teaching and Research Centre. Gembloux Agro‐Bio Tech; Bélgica Fil: Foltynova, Lenka. Czech Academy of Sciences. Global Change Research Institute ; República Checa Fil: Goulden, Michael L. University of California Irvine. Department of Earth System Science; Estados Unidos Fil: Griffis, Timothy J. University of Minnesota. Department of Soil, Water, and Climate; Estados Unidos Fil: Grunwald, Thomas. Technische Universität Dresden, Institute of Hydrology and Meteorology; Alemania Fil: Johnson, Mark S. University of British Columbia. Department of Earth, Ocean, and Atmospheric Sciences; Canadá Fil: Kang, Minseok. National Center for AgroMeteorology; Corea del Sur Fil: Kelbe, Dave. Xerra Earth Observation Institute; Nueva Zelanda Fil: Kowalska, Natalia. Czech Academy of Sciences. Global Change Research Institute ; República Checa Fil: Jong - Hwan, Lim. National Institute of Forest Science; Corea del Sur Fil: Mainassara, Ibrahim. University Montpellier. HydroSciences Montpellier (HSM); Francia Fil: McCabe, Matthew F. King Abdullah University of Science and Technology. Division of Biological and Environmental Science and Engineering. Hydrology, Agriculture and Land Observation Group (HALO); Arabia Saudita Fil: Missik, Justine E.C. Washington State University. Department of Civil and Environmental Engineering. Laboratory for Atmospheric Research; Estados Unidos Fil: Mohanty, Binayak P. Texas A&M University. Texas Water Observatory; Estados Unidos Fil: Moore, Caitlin E. University of Illinois Urbana‐Champaign. Institute for Sustainability, Energy, and Environment and Carl R. Woese Institute for Genomic Biology. Center for Advanced Bioenergy and Bioproducts Innovation; Estados Unidos Fil: Morillas, Laura. University of British Columbia. Department of Earth, Ocean, and Atmospheric Sciences; Canadá Fil: Morrison, Ross. Centre for Ecology and Hydrology; Reino Unido Fil: Munger, J. Willians. Harvard University. School of Engineering and Applied Sciences; Estados Unidos Fil: Posse, Gabriela. Instituto Nacional de Tecnología Agropecuaria (INTA). Instituto de Clima y Agua; Argentina Fil: Richardson, Andrew D. Northern Arizona University Center for Ecosystem Science and Society; Estados Unidos Fil: Russell, Eric. S. Washington State University. Department of Civil and Environmental Engineering. Laboratory for Atmospheric Research; Estados Unidos Fil: Ryu, Youngryel. Seoul National University . Department of Landscape Architecture and Rural Systems Engineering; Corea del Sur Fil: Sanchez - Azofeifa, Arturo. University of Alberta. Earth and Atmospheric Sciences Department. Centre for Earth Observation Sciences (CEOS); Canadá Fil: Schmidt, Marius. IInstitute of Bio‐ and Geosciences: Agrosphere (IBG‐3) Forschungszentrum Jülich IBG‐3; Alemania Fil: Schwartz, Efrat. Weizmann Institute of Science. Department of Earth and Planetary Sciences, ; Israel Fil: Sharp, Iain. University of Alberta. Earth and Atmospheric Sciences Department. Centre for Earth Observation Sciences (CEOS); Canadá Fil: Sigut, Ladislav. Czech Academy of Sciences. Global Change Research Institute ; República Checa Fil: Tang, Yao. Georgia Institute of Technology. School of Civil and Environmental Engineering; Estados Unidos Fil: Hulley, Glynn. California Institute of Technology. Jet Propulsion Laboratory; Estados Unidos Fil: Anderson, Martha. U.S. Department of Agriculture‐Agricultural Research Service; Estados Unidos Fil: Hain, Christopher. NASA Marshall Space Flight Center; Estados Unidos Fil: French, Andrew. U.S. Department of Agriculture; Estados Unidos Fil: Wood, Eric. Princeton University. Department of Civil and Environmental Engineering; Estados Unidos Fil: Hook, Simón. California Institute of Technology. Jet Propulsion Laboratory; Estados Unidos

An accurate assessment of evapotranspiration (ET) is crucially needed at the basin scale for studying the hydrological processes and water balance especially from upstream to downstream. In the mountains, this term is poorly understood because of various challenges, including the vegetation complexity, plant diversity, lack of available data and because the in situ direct measurement of ET is difficult in complex terrain. The main objective of this work was to investigate the potential of a Two-Source-Energy-Balance model (TSEB) driven by the Landsat and MODIS data for estimating ET over a complex mountain region. The complexity is associated with the type of the vegetation canopy as well as the changes in topography. For validating purposes, a large-aperture scintillometer (LAS) was set up over a heterogeneous transect of about 1.4 km to measure sensible (H) and latent heat (LE) fluxes. Additionally, two towers of eddy covariance (EC) systems were installed along the LAS transect. First, the model was tested at the local scale against the EC measurements using multi-scale remote sensing (MODIS and Landsat) inputs at the satellite overpasses. The obtained averaged values of the root mean square error (RMSE) and correlation coefficient (R) were about 72.4 Wm−2 and 0.79 and 82.0 Wm−2 and 0.52 for Landsat and MODIS data, respectively. Secondly, the potential of the TSEB model for evaluating the latent heat fluxes at large scale was investigated by aggregating the derived parameters from both satellites based on the LAS footprint. As for the local scale, the comparison of the latent heat fluxes simulated by TSEB driven by Landsat data performed well against those measured by the LAS (R = 0.69, RMSE = 68.0 Wm−2), while slightly more scattering was observed when MODIS products were used (R = 0.38, RMSE = 99.8 Wm−2). Based on the obtained results, it can be concluded that (1) the TSEB model can be fairly used to estimate the evapotranspiration over the mountain regions; and (2) medium- to high-resolution inputs are a better option than coarse-resolution products for describing this kind of complex terrain.

This study evaluated the adequacy of the One-Source Energy Balance (OSEB) and Surface Energy Balance Algorithm for Land (SEBAL) models to estimate evapotranspiration in grain growing areas with humid subtropical climate in Rio Grande do Sul, southern Brazil. The dataset was obtained from a micrometeorological station (Eddy Covariance) and MODIS (Moderate Resolution Imaging Spectroradiometer) products during 84 observation days between 2009 and 2011. The OSEB and SEBAL models were used to estimate the partition of net radiation (Rn) into the components latent heat flux (LE), sensible heat flux (H), and ground heat flux (G) estimated from the MODIS images while the experimental data measured in situ were used to compare the results. Analyses indicated that the Energy Balance (EB) components were estimated from the MODIS images satisfactorily despite the spatial resolution limitations. Furthermore, the SEBAL model estimated the EB components satisfactorily only for summer crops. There are uncertainties associated with determining the hot and cold pixels due to the region humid subtropical climate and the spatial resolution of the sensor used in the other periods. The OSEB model has the lowest errors and the most adequate partitioning of the EB components throughout the year, and therefore, it is the most suitable for the climatic conditions of Rio Grande do Sul.

A method to estimate the sensible heat flux (H) for unstable atmospheric condition requiring measurements taken in half-hourly basis as input and involving the land surface temperature (LST), HLST, was tested over a tall and dense aspen stand. The method avoids the need to estimate the zero-plane displacement and the roughness length for momentum. The net radiation (Rn) and the latent heat flux (λE) dominated the surface energy balance (SEB). Therefore, λE was estimated applying the residual method using HLST as input, λER-LST. The sum of H and λE determined with the eddy covariance (EC) method led to a surface energy imbalance of 20% Rn. Thus, the reference taken for the comparisons were determined forcing the SEB using the EC Bowen ratio (BREB method). For clear sky days, HLST performed close to HBREB. Therefore, it showed potential in the framework of remote sensing because the input requirements are similar to current methods widely used. For cloudy days, HLST scattered HBREB and nearly matched the accumulated sensible hear flux. Regardless of the time basis and cloudiness, λER-LST was close to λEBREB. For all the data, both HLST and λER-LST were not biased and showed, respectively, a mean absolute relative error of 24.5% and 12.5% and an index of agreement of 68.5% and 80%. This work was supported under project RTI2018-098693-B-C31 (Ministerio de Ciencia, Economia y Universidades of Spain). The data was freely downloadable at http://daac.ornl.gov/BOREAS/boreas.shtml (accessed on 28 December 2021). Key R & D Program of Jiangsu Province (BE2021340) and Priority Academic Program Development of Jiangsu Higher Education Institutions (PAPD-2018-87).

The unresolved energy-unclosed problem in micrometeorology refers to the fact that the sum of turbulent fluxes (sensible and latent heat fluxes, Hs and LE) monitored by eddy covariance (EC) methods tends to be lower than the available energy (net radiation (Rn), soil heat flux (G), and heat storage (S)). The lack of energy balance closure (EBC) increases evapotranspiration-measurement uncertainty. Using EC data from Xishuangbanna, a Southeast Asian tropical seasonal rainforest, we analyzed the energy distribution and closure based on micrometeorological features. We found that: (1) the EBC in the rainy season exceeds that in other seasons and that the seasonal moisture content, frictional wind velocity (u*), and LE contribute to the high seasonal variability in EBC; (2) the annual closure is approximately 65%, and energy non-closure is influenced by turbulence intensity and atmospheric stability. When the atmospheric state is unstable to near neutral, u* is greatest, and EBC can reach nearly 80%. (3) energy is mainly allocated to LE, and energy non-closure leads to LE underestimation, especially in the foggy-cool and hot-dry seasons. (4) Heat storage and large time-scale flux effects on EBC were excluded. The causes of energy non-closure in the tropical calm zone need further investigation.

This study aims to statistically describe temporal and spatial variations of sea surface temperature (SST), latent heat flux (LHF), sensible heat flux (SHF), and precipitation rate with typhoon activity over the South China Sea. The correlations of the parameters and their connections with the physical phenomena are clearly presented. This is fundamental to predict a typhoon's intensity and track. The effects were investigated from 1991 to 2011 based on archived data from the National Centers for Environmental Prediction and the National Center for Atmospheric Research (NCEP-NCAR) and the number of typhoons were sourced from the International Best Track Archive for Climate Stewardship (IBTrACS). The results showed that most typhoons occurred in August and September, which was related to high temperature in the summer season and the southwest monsoon in the area. The maximum mean values of SST in May and June were related to the East Asian Monsoon. The average values of LHF were highest in July, and the mean values of SHF were highest in July and August. SHF varied gradually at different months compared with LHF. In addition, the average of precipitation rate was highest in November, which can be related to the northeasterly winter monsoon. The relationships of the aforementioned parameters were obtained using Pearson's correlation analysis. Moreover, the highest and lowest mean values of the parameters in different areas were considered, and their spatial relationships were analyzed.

Made available in DSpace on 2019-10-04T12:42:22Z (GMT). No. of bitstreams: 0 Previous issue date: 2019-10-01 Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Aiming to subsidize the rational water resources management, an R package called agriwater was created in order to obtain the energy balance on the soil and actual evapotranspiration using satellite imagery and agrometeorological data. This package apply the Simple Algorithm for Evapotranspiration Retrieving - SAFER to calculate the evapotranspiration fraction ETr (or ETA ET0-1), actual evapotranspiration (ETA) and latent heat flux (lambda E); the Slob equation calculate the net radiation (R-N); ground heat flux (G) is modeled from R-N; and the sensible heat flux (H) is retrieved as the residue of the energy balance equation. Landsat-8 (with and without thermal bands), Sentinel-2 and MODIS digital images can be used. Results are presented in raster format and can be post-processed by GIS analysis or anothers R procedures. A study case using Sentinel-2 images and agrometeorological data of a semiarid area from Brazil was performed. The requirements and conditions for use of the package are explained. Univ Estadual Paulista, Agron Sci Fac, Rua Jose Barbosa Barros, BR-18610307 Botucatu, SP, Brazil Embrapa Coastal Tablelands, Av Beira Mar 3250, BR-49025040 Aracaju, SE, Brazil Univ Estadual Paulista, Sch Sci & Engn, Rua Domingos Costa Lopes, BR-17602496 Tupa, SP, Brazil Univ Estadual Paulista, Agron Sci Fac, Rua Jose Barbosa Barros, BR-18610307 Botucatu, SP, Brazil Univ Estadual Paulista, Sch Sci & Engn, Rua Domingos Costa Lopes, BR-17602496 Tupa, SP, Brazil CNPq: 143127/2017-9 CNPq: 133715/2019-1

Ocean surface heat fluxes play a significant role in the genesis and evolution of various marine-based atmospheric phenomena, from the synoptic scale down to the microscale. While in-situ measurements from buoys and flux towers will continue to be the standard in regards to surface heat flux estimates, they commonly have significant gaps in temporal and spatial coverage. Previous and current satellite missions have filled these gaps; though they may not observe the fluxes directly, they can measure the variables needed (wind speed, temperature, and humidity) to estimate latent and sensible heat fluxes. However, current remote sensing instruments have their own limitations, such as infrequent coverage, signals attenuated by precipitation, or both. The Cyclone Global Navigation Satellite System (CYGNSS) mission overcomes these limitations over the tropical and subtropical oceans by providing improved coverage in nearly all weather conditions. While CYGNSS (Level 2) primarily estimates surface winds, when coupled with observations or estimates of temperature and humidity from reanalysis data, it can provide estimates of latent and sensible heat fluxes along its orbit. This paper describes the development of the Surface Heat Flux Product for the CYGNSS mission, its current results, and expected improvements and changes in future releases.

Turbulent and radiative exchanges of heat between the ocean and atmosphere (hereafter heat fluxes), ocean surface wind stress, and state variables used to estimate them, are Essential Ocean Variables (EOVs) and Essential Climate Variables (ECVs) influencing weather and climate. This paper describes an observational strategy for producing 3-hourly, 25-km (and an aspirational goal of hourly at 10-km) heat flux and wind stress fields over the global, ice-free ocean with breakthrough 1-day random uncertainty of 15 W m-2 and a bias of less than 5 W m-2. At present this accuracy target is met only at OceanSITES reference station moorings and research vessels (RVs) that follow best practices. To meet these targets globally, in the next decade, satellite-based observations must be optimized for boundary layer measurements of air temperature, humidity, sea surface temperature, and ocean wind stress. In order to tune and validate these satellite measurements, a complementary global in situ flux array, built around an expanded OceanSITES network of time series reference station moorings, is also needed. The array would include 500 - 1000 measurement platforms, including autonomous surface vehicles, moored and drifting buoys, RVs, the existing OceanSITES network of 22 flux sites, and new OceanSITES expanded in 19 key regions. This array would be globally distributed, with 1 - 3 measurement platforms in each nominal 10° by 10° boxes. These improved moisture and temperature profiles and surface data, if assimilated into Numerical Weather Prediction (NWP) models, would lead to better representation of cloud formation processes, improving state variables and surface radiative and turbulent fluxes from these models. The in situ flux array provides globally distributed measurements and metrics for satellite algorithm development, product validation, and for improving satellite-based, NWP and blended flux products. In addition, some of these flux platforms will also measure direct turbulent fluxes, which can be used to improve algorithms for computation of air-sea exchange of heat and momentum in flux products and models. With these improved air-sea fluxes, the ocean’s influence on the atmosphere will be better quantified and lead to improved long-term weather forecasts, seasonal-interannual-decadal climate predictions, and regional climate projections.

The role of wetlands and forests in climate and climate change is usually considered as a part of sequestration system i.e. the source or sink of greenhouse gasses. However, this permanent vegetation is an active factor that, through the process of evapotranspiration directly influences climate. Wet vegetation transforms solar radiation into the latent heat of water vapour. Evapotranspiration is a powerful tool that has, due to phase change of water, a double air-conditioning effect in the landscape. In addition, it reduces thermal gradients, mitigates temperature extremes, close water and mass cycling. Evapotranspiration-condensation processes slow down where there is a lack of water and permanent vegetation. Solar radiation is then transformed into sensible heat. The overheated surface warms the adjacent air layer. Warm air rises turbulently upwards, is capable of absorbing higher amounts of water vapour, which then transmits to higher levels of the atmosphere where condensation occurs. These processes significantly dry out the landscape. The IPCC reports however, do not take into account this direct effect of water and vegetation on climate. The chapter explains the direct function of wetlands and the air-conditioning effect of evapotranspiration, which also illustrates on thermal ground images. Role of forest and wetlands in transport of water from ocean into continents is discussed on literature basis in terms of biotic pump.

Precise estimation of surface-atmosphere exchange is a major challenge in micrometeorology. Previous literature presented the eddy covariance (EC) as the most reliable method for the measurements of such fluxes. Nevertheless, the EC technique is quite expensive and complex, hence other simpler methods are sought. One of these methods is Flux-Variance (FV). The FV method estimates sensible heat flux (H) using high frequency (~10Hz) air temperature measurements by a fine wire thermocouple. Additional measurements of net radiation (Rn) and soil heat flux (G) allow the derivation of latent heat flux (LE) as the residual of the energy balance equation. In this study, the Flux Variance method was investigated, and the results were compared against eddy covariance measurements. The specific goal of the present study was to assess the performance of the FV method for the estimation of surface fluxes along a variable fetch. Experiment was carried out in a tea garden, an EC system measured latent and sensible heat fluxes and five fine-wire thermocouples were installed towards the wind dominant direction at different distances (fetch) of TC1 = 170 m, TC2 = 165 m, TC3 = 160 m, TC4 = 155 m and TC5 = 150 m from the field edge. Footprint analysis was employed to examine the effect of temperature measurement position on the ratio between 90% footprint and measurement height. Results showed a good agreement between FV and EC measurements of sensible heat flux, with all regression coefficients (R2) larger than 0.6, the sensor at 170 m (TC1), nearest to the EC system, had highest R2 = 0.86 and lowest root mean square error (RMSE = 25 Wm&minus, 2). The estimation of LE at TC1 was also in best agreement with eddy covariance, with the highest R2 = 0.90. The FV similarity constant varied along the fetch within the range 2.2&ndash, 2.4.

Corals in the Persian/Arabian Gulf are the most thermally tolerant in the world, but live very near the thresholds of their thermal tolerance. Warming sea temperatures associated with climate change have resulted in numerous coral bleaching events regionally since the mid-1990s, but it has been unclear why unusually warm sea temperatures occur some years but not others. Using a combination of 5 years of observed sea-bottom temperatures at three reef sites and a meteorologically linked hydrodynamic model that extends through the past decade, we show that summer sea-bottom temperatures are tightly linked to regional wind regimes, and that strong ‘shamal’ wind events control the occurrence and severity of bleaching. Sea bottom temperatures were primarily controlled by latent heat flux from wind-driven surface evaporation which exceeded 300 W m-2 during shamal winds, double that of typical breeze conditions. Daily temperature change was highly correlated with wind speed, with breeze winds (5 weeks, while the cooler intervening years (2013–2016) had summers with more frequent and/or strong shamal events which repeatedly cooled temperatures below bleaching thresholds for days to weeks, providing corals temporary respite from thermal stress. Using observed data from 2012 onward and simulated data from 2008 to 2011, we show that the severity of bleaching events over the past decade was linked to both the number of cumulative days above bleaching thresholds (rather than total days, which obfuscates the cooling effects of occasional brief shamal events), as well as to maxima. We show that winds of 4 m s-1 represents a critical threshold for whether or not corals cross bleaching threshold temperatures, and provide simulations to forecast sea-bottom temperature change and recovery times under a range of wind conditions. The role that wind-driven cooling may play on coral reefs globally is discussed.

In this study, the performance of the combined-source variational data assimilation scheme (CS-VDA) is assessed in detail using in situ heat fluxes (i.e. sensible heat (H) and latent heat (LE)) collected at a Eucalypt forest savanna of Northern Australia (Howard Springs). The CS VDA scheme estimates surface turbulent heat fluxes via assimilation of sequences of land surface temperature (LST) and meteorological data into a surface energy balance model and a dynamic model. The main objectives of this paper were to extend previous studies to a semi-arid ecosystem and to evaluate the potential of using global meteorological forcing data (GMD) to drive the CS VDA model (rather than in-situ meteorological observations). In order to study the new errors associated with the use of GMD, the effects on LE of the uncertainty in air temperature and wind speed (the two key meteorological factors that controls the total estimation error) was quantitatively characterized. Using hourly in-situ measurements as inputs, the daily-averaged LE RMSE daily was 54 W/m 2 , which agrees with the errors previously reported in the literature. As expected, replacing local meteorological data with GMD reduces the performance of the LE estimation (GMA: RMSE daily = 82 W/m 2 , GLDAS: RMSE daily = 151 W/m 2 ). However, LE RMSE values at 8-day temporal scale for GMA are RMSE 8-days = 32 W/m 2 , similar to those reported in this area for other models (MODIS (MOD16A2) and Breathing Earth System Simulator (BESS)). The error propagation analysis indicate that the CS VDA model is very sensitive to uncertainties in wind speed measurements. Moreover, there are large discrepancies between in situ and GMD wind speed. These two factors combined can explain the degradation in LE estimations. In this context, our study is a first step towards the characterization of an operational daily LE estimation scheme using hourly LST observations. Fil: Barraza Bernadas, Verónica Daniela. Consejo Nacional de Investigaciónes Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Astronomía y Física del Espacio. - Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Astronomía y Física del Espacio; Argentina Fil: Grings, Francisco Matias. Consejo Nacional de Investigaciónes Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Astronomía y Física del Espacio. - Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Astronomía y Física del Espacio; Argentina Fil: Franco, Mariano Andrés. Consejo Nacional de Investigaciónes Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Astronomía y Física del Espacio. - Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Astronomía y Física del Espacio; Argentina Fil: Douna, Vanesa Mariel. Consejo Nacional de Investigaciónes Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Astronomía y Física del Espacio. - Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Astronomía y Física del Espacio; Argentina Fil: Entekhabi, Dara. Massachusetts Institute of Technology; Estados Unidos Fil: Restrepo Coupe, Natalia. University of Arizona; Estados Unidos. University of Technology of Sydney; Australia Fil: Huete, Alfredo Ramon. University of Arizona; Estados Unidos Fil: Gassmann, María Isabel. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Departamento de Ciencias de la Atmósfera y los Océanos; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina Fil: Roitberg, Esteban Gabriel. Consejo Nacional de Investigaciónes Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Astronomía y Física del Espacio. - Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Astronomía y Física del Espacio; Argentina

Este artículo está sujeto a una licencia CC BY 4.0, Many satellite missions rely on modeling approaches to acquire global or regional evapotranspiration (ET) products. However, a current challenge in ET modeling lies in dealing with sub-pixel heterogeneity, as models often assume homogeneous conditions at the pixel level. This is particularly an issue for heterogeneous landscapes, such as tree-grass ecosystems (TGE). In these areas, while appearing homogeneous at larger spatial scales pertaining to a single land cover type, the separation of the spectral signals of the main landscape features (e.g. trees and grasses) may not be achieved at the conventional satellite sensor resolution (e.g. 10–1000 m). This leads to important heterogeneity within the pixel grid that may not be accounted for in traditional modeling frameworks. This study examined the effect of pixel heterogeneity on ET simulations over a complex TGE in central Spain. High resolution hyperspectral imagery from five airborne campaigns forced the two-source energy balance (TSEB) model at 1.5–1000 m spatial resolutions. Along with this, the sharpened (20 m) and original (1000 m) Sentinels for Evapotranspiration (Sen-ET) products were evaluated over the study site for 2017. Results indicated that TSEB accurately simulated ET (RMSD: ~60 W/m2) when the pixel scale was able to robustly discriminate between grass and tree pixels (, The research received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie SklodowskaCurie TRuStEE project (grant agreement No 721995). It was also funded by Ministerio de Economía y Competitividad through FLUXPEC CGL2012-34383 and SynerTGE CGL2015-G9095-R (MINECO/FEDER, UE) projects. The research infrastructure at the measurement site in Majadas de Ti´etar was partly funded through the Alexander von Humboldt Foundation, ELEMENTAL (CGL 2017-83538-C3-3-R, MINECO-FEDER) and IMAGINA (PROMETEU 2019; Generalitat Valenciana).

Several studies have pointed out the dependence of low‐cloud feedbacks on the strength of the lower‐tropospheric convective mixing. By analyzing a series of single‐column model experiments run by a climate model using two different convective parametrizations, this study elucidates the physical mechanisms through which marine boundary‐layer clouds depend on this mixing in the present‐day climate and under surface warming. An increased lower‐tropospheric convective mixing leads to a reduction of low‐cloud fraction. However, the rate of decrease strongly depends on how the surface latent heat flux couples to the convective mixing and to boundary‐layer cloud radiative effects: (i) on the one hand, the latent heat flux is enhanced by the lower‐tropospheric drying induced by the convective mixing, which damps the reduction of the low‐cloud fraction, (ii) on the other hand, the latent heat flux is reduced as the lower troposphere stabilizes under the effect of reduced low‐cloud radiative cooling, which enhances the reduction of the low‐cloud fraction. The relative importance of these two different processes depends on the closure of the convective parameterization. The convective scheme that favors the coupling between latent heat flux and low‐cloud radiative cooling exhibits a stronger sensitivity of low‐clouds to convective mixing in the present‐day climate, and a stronger low‐cloud feedback in response to surface warming. In this model, the low‐cloud feedback is stronger when the present‐day convective mixing is weaker and when present‐day clouds are shallower and more radiatively active. The implications of these insights for constraining the strength of low‐cloud feedbacks observationally is discussed., Key Points The sensitivity of low clouds to shallow convective mixing depends on turbulence and radiationThe coupling between low‐cloud radiative cooling and surface latent heat flux strengthens the low‐cloud feedbackBy affecting the relative importance of key processes, the closure of shallow convection schemes affects the strength of low‐cloud feedback

Ocean-atmosphere energy exchange is an important factor in the maintenance of oceanic and atmospheric circulation and the regulation of meteorological and climate systems. Oceanic sensible and latent heat fluxes around the Korean Peninsula were determined using satellite-based air-sea variables (wind speed, sea surface temperature, and atmospheric specific humidity and temperature) and the coupled ocean-atmosphere response experiment (COARE) 3.5 bulk algorithm for six years between 2014 and 2019. Seasonal characteristics of the marine heat flux and its short-term fluctuations during summer typhoons were also investigated. air-sea variables were produced through empirical relationships and verified with observational data from marine buoys around the Korean Peninsula. Satellite-derived wind speed, sea surface temperature, atmospheric specific humidity, and air temperature were strongly correlated with buoy data, with R2 values of 0.80, 0.97, 0.90, and 0.91, respectively. Satellite-based sensible and latent heat fluxes around the peninsula were also validated against fluxes calculated from marine buoy data, and displayed low values in summer and higher values in autumn and winter as the difference between air-sea temperature and specific humidity increased. Through analyses of spatio-temporal fluctuations in the oceanic turbulent heat flux and variations in intensities of typhoons, this study assessed the possibility of monitoring air-sea energy exchange using satellite-based ocean turbulent heat fluxes during high-impact weather.

50 Pags.- 2 Tabls.- 10 Figs. The definitive version is available at: https://www.sciencedirect.com/science/journal/03783774, Agricultural engineers, crop physiologists and hydrologists are often forced to deploy instrumentation close to the canopy top to estimate surface eddy fluxes. This is a widely recognized problem either at farm-level or research-level. The eddy covariance (EC) method is grounded on hypothesis, simplifications and relationships valid in the inertial sublayer and alternative methods may require either calibration or inputs that are not commonly available. The present study enables a method that combines similarity, transilient and surface renewal theories in conjunction with the analysis of small eddies (Surface renewal of small eddies, SRSE, method) to estimate the friction velocity and surface fluxes of different scalars (sensible heat, latent heat and carbon dioxide) taking measurements at the canopy top. SRSE minimizes estimation of canopy parameters (only the zero-plane displacement is involved), allows implementing a primary flux quality control and to guide instrumentation deployment. For a mature maize crop, SRSE and EC surface energy balances indicated that EC was slightly more reliable than SRSE during daytime. For unstable cases, the normalized mean absolute error (MAE) to the available net surface energy (ANSE), MAE/ANSE, obtained by the EC and SRSE methods were 9% and 13 %, respectively. For stable cases during the day, 10 % and 11 %, respectively. For stable cases at night SRSE performed better than EC, MAE/ANSE were 23 % and 16 %, respectively. Regardless of the half-hourly eddy flux (including the friction velocity), the EC and SRSE were highly correlated (the minimum coefficient of determination was 0.91) and, in average (for all data) flux of scalars nearly matched including water-use-efficiency. To avoid acquisition of expensive and stringent instrumentation, the closure of the surface energy balance equation was forced to derive affordable approaches to estimate the latent heat flux for different stability cases., This work was supported under projects AGL2013-48728-C2-1-R and RTI2018-098693-B-C31 Ministerio de Economía y Competitividad of Spain.

Evapotranspiration (ET) is one of the least understood components of the hydrological cycle. Its applications are varied, from agricultural, ecological and hydrological monitoring, to control of the evolution of climate change. The goal of this work was to analyze the influence that uncertainties in the estimate of land surface temperature (Ts) can cause on ET estimates by S-SEBI model in the Pampa biome area. Also, the specificities of native grassland of Pampa biome related to energy balance were analyzed. The results indicate that the daily evapotranspiration is higher when the pixel Ts is lower, which also shows the influence of land use on the variability of ET. The results demonstrated that the S-SEBI is less dependent on Ts estimation than other models reported in the literature, such as the SEBS, which not exceed 0.5 mm/day in grasslands. The evapotranspiration variability between forest and grassland were lower than expected, demonstrating that the Pampa biome have in Rio Grande do Sul the same importance that forests regarding to the processes of the hydrological cycle, since it covers 63% of the State.