Search

Understanding the characteristics and variations of heat exchange and evaporation of lakes is important for regional water resource management and sustainable development. Based on eddy covariance measurements over Lake Vanajavesi in southern Finland, characteristics of energy fluxes and cold frontal effects on energy exchange were investigated. The lake acted as a heat sink in spring and summer and a heat source in winter. The latent heat flux reached its minimum value in the morning and peaked in the afternoon. The diurnal variation of sensible heat flux was opposite to that of latent heat flux. Impact factors for the sensible heat flux were mainly the lake-air temperature difference and the product of lake-air temperature difference and wind speed. The latent heat flux was mainly affected by the vapor pressure deficit and the product of vapor pressure deficit and wind speed. The annual mean values of bulk transfer coefficients for momentum, heat, and water vapor were 1.98 × 10−3, 1.62 × 10−3, and 1.31 × 10−3, respectively. Bulk transfer coefficients for heat and water vapor were not equal, indicating that the parameterization of energy exchange in numerical models, where the assumption that the heat coefficient equals the water vapor coefficient needs improvement. During the ice-free season, cold fronts resulted in 28 sensible heat pulses and 17 latent heat pulses, contributing to 50.59% and 34.89% of sensible and latent heat exchange in Lake Vanajavesi. These results indicate that cold fronts significantly impact the surface energy budget and evaporation over lakes. [ABSTRACT FROM AUTHOR]

Mesoscale air–sea interaction, which is active in Western Boundary Currents (WBCs), has a non-negligible effect on mid-latitude climate variability. The analysis and prediction of the mesoscale air–sea interaction rely on high-resolution observation datasets and mesoscale-resolving climate models, which often require long processing times to estimate future changes and have several limitations. Therefore, in this study, we used a newly developed iTransformer model, which integrates mesoscale sea surface temperature anomaly (SSTa) and latent heat flux anomaly (LHFa) coupling coefficient data to predict future changes in SSTa–LHFa coupling. First, we individually trained the model using data corresponding to 1–15 past winters from ERA5 dataset. Thereafter, we used the trained model to predict SSTa–LHFa coupling coefficient for the next 10 winters. Compared with the predictions using only the coupling coefficient, the prediction yields 3.0% relative improvements when SST data were incorporated. The iTransformer model also showed the ability to reproduce the linear trend and mean value of mesoscale SSTa–LHFa coupling coefficients. Furthermore, we chose the optimal input length for each WBC and used the model to predict changes in mesoscale SSTa–LHFa coupling in the future. The results thus obtained were comparable to those obtained using mesoscale-resolving climate models, indicating that the iTransformer model showed satisfactory prediction performance. Therefore, it provides a novel pathway for exploring mesoscale air–sea interaction variations and predicting future climate change. [ABSTRACT FROM AUTHOR]

Lakes represent a vital source of freshwater, accounting for 87% of the Earth’s accessible surface freshwater resources and providing a range of ecosystem services, including water for human consumption. As climate change continues to unfold, understanding the potential evaporative water losses from lakes becomes crucial for effective water management strategies. Here we investigate the impacts of climate change on the evaporation rates of 23 European lakes and reservoirs of varying size during the warm season (July–September). To assess the evaporation trends, we employ a 12-member ensemble of model projections, utilizing three one-dimensional process-based lake models. These lake models were driven by bias-corrected climate simulations from four General Circulation Models (GCMs), considering both a historical (1970–2005) and future (2006–2099) period. Our findings reveal a consistent projection of increased warm-season evaporation across all lakes this century, though the magnitude varies depending on specific factors. By the end of this century (2070–2099), we estimate a 21%, 30% and 42% average increase in evaporation rates in the studied European lakes under RCP (Representative Concentration Pathway) 2.6, 6.0 and 8.5, respectively. Moreover, future projections of the relationship between precipitation (P) and evaporation (E) in the studied lakes, suggest that P-E will decrease this century, likely leading to a deficit in the availability of surface water. The projected increases in evaporation rates underscore the significance of adapting strategic management approaches for European lakes to cope with the far-reaching consequences of climate change. [ABSTRACT FROM AUTHOR]

Irrigation was a critical measure for ensuring stable and increased grain production, and its influence on climate change was significant and could not be overlooked. Investigating the influence of irrigation on the strength of land-atmosphere coupling was essential for enhancing our knowledge of the impact of irrigation on climate change. This study leveraged the ERA5 reanalysis dataset alongside the global irrigation area dataset to perform a quantitative analysis of Coupling Strength Index (CSI) in both densely and reference irrigated areas within China's primary grain-producing regions. The analysis incorporated soil moisture and latent heat flux to explore the impact of irrigation on CSI. First, we applied the commonly used Pettitt test, Buishand test, and SNHT test in the field of agrometeorology to conduct a change-point analysis on the calculated CSI in China's main grain-producing areas. We found that CSI experienced a shift in 1996, changing from a decreasing trend before 1996 to an increasing trend afterward. Then, we explored how irrigation affected CSI by dividing the areas into intensive irrigation regions and reference irrigation regions. The results showed that large-scale irrigation expansion could have altered local climate conditions, significantly impacting CSI. Furthermore, the larger the proportion of irrigated area, the higher the CSI. The greater the difference in the proportion of irrigated area, the greater the difference in CSI. There was a significant difference in CSI values between northern and southern China. Historically, the annual CSI values in the north ranged between −0.008 MJ/m² and 0.009 MJ/m², while in the south, they ranged between −0.018 MJ/m² and −0.007 MJ/m² . The annual CSI in northern China was generally stronger than in southern China, with the northern CSI values being distributed across both positive and negative ranges, whereas the southern CSI values were exclusively in the negative range. The impact of irrigation on CSI intensified with the increase in irrigation area disparity. Irrigation had a significant enhancing effect on the CSI in China's major grain-producing regions. This effect was more pronounced in northern China compared to southern China and was greater in densely irrigated areas than in reference irrigated areas. In recent years, this enhancing effect had been increasing at rates of 0.99×10−4 MJ/m² per year in the north and 2.53×10−4 MJ/m² per year in the south. This trend suggested that China was moving towards a more arid climate. After 1996, the trend in CSI changes for densely irrigated areas in both the north and south had become consistent. However, the trend in CSI changes for reference irrigated areas in the north was higher than in the south. This had resulted in a reduction in the CSI difference between densely and reference irrigated areas in the north, while in the south, this difference had significantly increased. A significant climatic shift occurred around 1996 in East Asia, leading to changes in precipitation and soil moisture trends. This shift caused a decrease in soil moisture in the main grain-producing regions of southern China, transitioning from a "radiation-limited" to a "soil moisture-limited" regime. Consequently, the enhancing effect of irrigation on CSI in southern China's main grain-producing regions increased. Although the overall decrease in soil moisture in China after the 1990s was an indisputable fact, there was still no clear conclusion on the relative contributions of human activities and climate shifts. This study revealed the impact of irrigation on CSI in China's main grainproducing regions, providing scientific references for national food security and climate change adaptation strategies. [ABSTRACT FROM AUTHOR]

Evapotranspiration is a key hydrological process in Brazil's 1,000,000-km2 tropical semiarid Caatinga biome, where monitoring is crucial, but data are scarce. We propose a method to estimate daily actual evapotranspiration (LE) based on the canopy-radiation balance, measuring air and canopy temperatures, relative humidity, wind speed, and global radiation. The method was applied at a location with preserved Caatinga forest [Aiuaba Experimental Basin, daily average net radiation (Rn) of 12 MJ/m2 ] during one hydrological year (2020–2021). The results, which agree with independently performed field measurements, identify the predominance of distinct evaporative processes throughout the year. In the dry season, net radiation is high (16.7 MJ/m2/day), but actual evapotranspiration is negligible (LE/Rn<0.01) because stress due to extremely low soil water content causes leave deciduousness and root shrinkage. Contrastingly, in the rainy season, soil water content increases, leaves recover, and roots expand, enhancing actual evapotranspiration (LE=6 mm/day and LE/Rn=0.89). Thus, in the Caatinga forest, during the dry and transition periods, actual evapotranspiration is ultimately ruled by the soil water content (source-limited), whereas during the rainy season, it is sink-limited (i.e., controlled by atmospheric demand). Practical Applications: The authors developed a new method to assess actual evapotranspiration in forested areas. The actual evapotranspiration, which is fundamental to compute irrigation demand, is also essential to understand the impact of climate change on forests. This is particularly important for drylands, such as the 1,000,000-km2 Brazilian semiarid region, where water is scarce and actual evapotranspiration is high, consuming 70% of the precipitation. The method, which estimates the energy balance on the leaves of forest trees, demands the measurement of only a few variables, such as temperature, air relative humidity, wind speed, and radiation. The equipment to perform the measurement is much cheaper (less than 10%) than that of the reference methods for this kind of study. Therefore, with the same budget, the method can be applied at more locations, increasing the spatial representation of the measurements. The method hereafter presented is especially meant to help semiarid and arid regions, where evapotranspiration is high and monitoring is crucial, but data are often scarce. [ABSTRACT FROM AUTHOR]

Abstract Latent heat flux (LE) is a measure of the water exchange between Earth's surface and atmosphere, also known as evapotranspiration. It is a fundamental component in the Earth's energy budget and hydrological cycle and plays an important role in regulating the weather and climate. Moderate Resolution Imaging Spectroradiometer (MODIS) offers a gap‐filled biophysical product for LE at 8‐day temporal and 500‐meter spatial resolutions. Nonetheless, validation against the in situ eddy covariance measurement reveals significant errors in MODIS LE estimation. Our study integrates ground‐measured, reanalysis and satellite data to predict LE by leveraging the advantage of the data‐driven method. The study draws upon flux data derived from the AsiaFlux database, alongside reanalysis datasets from the Indian Monsoon Data Assimilation and Analysis (IMDAA) and the European Centre for Medium‐Range Weather Forecasts (ERA5) products, as well as biophysical measurements from the MODIS satellite. An analysis of the annual water budget, based on ERA5 precipitation data, highlights net positive water balances across the study sites. By harnessing diverse datasets, we employ various machine learning regression algorithms. We find the support vector regression superior to linear, lasso, random forest, adaptive boosting and gradient boosting algorithms. This study highlights the robustness of support vector regression and accentuates the impact of climatic and environmental conditions on model performance, ultimately contributing to more precise predictions of latent heat flux.

In recent years, there has been a rise in human activities in oceanic areas, making the land–atmosphere interactions over islands a major scientific concern on a global scale. Examining the observation data from offshore areas enables a more comprehensive understanding of the turbulent fluxes in offshore atmospheric environments, patterns of momentum, energy and material exchange between the atmosphere and underlying surface in an oceanic boundary layer, and development of a heterogeneous atmospheric boundary layer. The related findings will assist in developing theoretical models and parameterization schemes to simulate the influence of heterogeneous surfaces on land–atmosphere interactions on the South China Sea Islands. Existing studies on the turbulent fluxes over the South China Sea Islands were mainly conducted on the Nansha Islands, whereas studies on the waters of the South China Sea are scarce. In this study, we used 10 Hz high‐frequency turbulence measurements to calculate the latent and sensible heat fluxes over the South China Sea Islands using the eddy correlation method. These findings were then compared with data from the Dunhuang Gobi, Ordos desert, and Xilingol grassland regions in inland China, along with the observed net radiation and surface heat fluxes. The findings indicate that the energy fluxes over the South China Sea in summer exhibit prominent diurnal variations. The magnitude of either latent or soil heat flux is low, and the net radiation is predominantly transformed into sensible heat flux, which warms the atmosphere. Furthermore, the daily variation curves of sensible and latent heat fluxes are influenced by intermittent turbulence on the islands and reefs, resulting in a less smooth pattern compared with soil heat flux. Although the South China Sea Islands have small land areas and are surrounded by the sea, the land–atmosphere interactions over the underlying surface of this region are similar to those over the underlying surface of grasslands in inland China during summer. The daily mean sensible heat flux on the islands is higher than that in an inland area, and the time lag in its response to sunrise is longer than that in inland areas by approximately 1 h. The overall energy balance ratio is approximately 0.75, c which is in line with the average level, but an energy balance residual of approximately 25% still exists. Furthermore, extreme weather conditions, such as typhoons, can disrupt the diurnal variations of sensible and latent heat fluxes, and the cyclical patterns are subsequently restored. [ABSTRACT FROM AUTHOR]

Tropical cyclones constitute a major risk for coastal communities. To assess their damage potential, accurate predictions of their intensification are needed, which requires a detailed understanding of the evolution of turbulent heat flux (THF). By combining multiple buoy observations along the south-north storm track, we investigated the THF anomalies associated with tropical storm Danas (2019) in the East China Sea (ECS) during its complete life cycle from the intensification stage to the mature stage and finally to its dissipation on land. The storm passage is characterized by strong winds of 10–20 m/s and a sea level pressure below 1 000 hPa, resulting in a substantial enhancement of THF. Latent heat (LH) fluxes are most strongly affected by wind speed, with a gradually increasing contribution of humidity along the trajectory. The relative contributions of wind speed and temperature anomalies to sensible heat (SH) depend on the stability of the boundary layer. Under stable conditions, SH variations are driven by wind speed, while under near-neutral conditions, SH variations are driven by temperature. A comparison of the observed THF and associated variables with outputs from the ERA5 and MERRA2 reanalysis products reveals that the reanalysis products can reproduce the basic evolution and composition of the observed THF. However, under extreme weather conditions, temperature and humidity variations are poorly captured by ERA5 and MERRA2, leading to large LH and SH errors. The differences in the observed and reproduced LH and SH during the passage of Danas amount to 26.1 and 6.6 W/m2 for ERA5, respectively, and to 39.4 and 12.5 W/m2 for MERRA2, respectively. These results demonstrate the need to improve the representation of tropical cyclones in reanalysis products to better predict their intensification process and reduce their damage. [ABSTRACT FROM AUTHOR]

Climate models are useful tools for monthly to decadal prediction of the evolution of climate. This study assesses how CMIP6 models represent soil moisture-latent heat regimes and coupling processes between the land and atmosphere. Metrics considered are terrestrial and atmospheric coupling indices to show the nature and strength of the coupling over Africa, focusing on the March to May (MAM) and June to August (JJA) seasons over East, Central, and West Africa. Characterization of the annual cycle indicates that model biases are highest during the peak of the rainfall season and least during the dry season, while soil moisture biases correspond with rainfall. Models show appreciable sensitivity to regional characteristics; there was model consensus in representing East Africa and the Sahel as regions of limited soil moisture, while major differences were noted in the wet regime over Central Africa. Most CMIP6 models tend to overestimate the strength of the terrestrial and atmospheric coupling pathways over East and Southern Africa. Inter-model differences in coupling indices could be traced to their inter-annual variability rather than the mean biases of the variables considered. These results encourage further advancement of land surface schemes in the next generation of climate models for a better representation of climate over Africa. [ABSTRACT FROM AUTHOR]

The increasing ocean warming due to climate change significantly threatens regional marine ecosystems by raising the frequency and severity of extreme temperature events. This study examines patterns and trends of maximum annual sea surface temperature (Tmax) in the Eastern China Seas from 1985 to 2022. The results show a significant warming trend in Tmax, exceeding the global average, with notable differences between southern and northern regions. The northern Tmax warming rate is faster, with occurrence times significantly advancing, while the southern Tmax warming rate is slower, with occurrence times significantly delayed. The southern Tmax and its timing are closely correlated with the annual maximum air temperature and its timing. In the north, Tmax timing is influenced by latent heat flux (QLH); a significant increase in August QLH inhibits the continued rise of SST, causing Tmax to advance. The study also highlights a significant increase in marine heatwaves at Tmax timing, with higher Tmax indicating a higher occurrence probability. By elucidating these Tmax trends and dynamics, our study enhances understanding of regional climate impacts, supporting targeted conservation efforts and adaptive ecosystem management strategies in the Eastern China Seas. [ABSTRACT FROM AUTHOR]

Sea surface latent and sensible heat fluxes are crucial components of the air-sea energy exchanges that influence the upper-ocean heat content and the marine atmospheric boundary layer. Due to the limited availability of in situ observations, assessing their impact on Arctic weather and climate has mainly been done using data assimilation products and numerical model simulations. The accuracy of the surface fluxes in numerical models are, however, largely unvalidated. Recent deployments of saildrones, remotely piloted uncrewed surface vehicles, can help bridge this data gap of in situ observations. This study represents an initial effort to validate sea surface latent and sensible heat fluxes over the Pacific sub-Arctic open ocean from three commonly used global reanalysis products (NASA MERRA2, ECMWF ERA5, NOAA CFSR2) against observations by saildrones. In general, fluxes from these reanalysis products and saildrone observations agree well, except for CFSR2 sensible heat fluxes, which exhibit systematic negative biases. Sporadic, very large (greater than two observed standard deviations) discrepancies between fluxes from the reanalysis products and observations do occur. These substantial discrepancies in the reanalysis products primarily result from errors in temperature for sensible heat fluxes and errors in both humidity and wind speed for latent heat fluxes. The results from this study suggest that the sea surface latent and sensible heat fluxes from MERRA2 and ERA5 are reliable in representing the mean features of air-sea exchanges in the sub-Arctic region. Nonetheless, their reliability is limited when used for studies of high-frequency variability, such as synoptic weather events. [ABSTRACT FROM AUTHOR]

Copyright of Chinese Journal of Applied Ecology / Yingyong Shengtai Xuebao is the property of Chinese Journal of Applied Ecology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Evapotranspiration (ET) is a major component of the water budget in Bottomland Hardwood Forests (BHFs) and is driven by a complex intertwined suite of meteorological variables. The understanding of these interdependencies leading to seasonal variations in ET is crucial in better informing water resource management in the region. We used structural equation modeling and AIC modeling to analyze drivers of ET using Eddy covariance water flux data collected from a BHF located in the Russel Sage Wildlife Management Area (RSWMA). It consists of mature closed-canopy deciduous hardwood trees with an average canopy height of 27 m. A factor analysis was used to characterize the shared variance among drivers, and a path analysis was used to quantify the independent contributions of individual drivers. In our results, ET and net radiation (Rn) showed similar variability patterns with Vapor Pressure Deficit (VPD) and temperature in the spring, summer, and autumn seasons, while they differed in the winter season. The path analysis showed that Rn has the strongest influence on ET variations via direct and indirect pathways. In deciduous forests like BHFs, our results suggest that ET is more energy dependent during the growing season (spring and summer) and early non-growing season (autumn) and more temperature dependent during the winter season. [ABSTRACT FROM AUTHOR]

In absence of the high-frequency measurements of wind components, sonic temperature and water vapour required by the eddy covariance (EC) method, Monin–Obukhov similarity theory (MOST) is often used to calculate heat fluxes. However, MOST requires assumptions of stability corrections and roughness lengths. In most environments and weather situations, roughness length and stability corrections have high uncertainty. Here, we revisit the modified Bowen-ratio method, which we call C-method, to calculate the latent heat flux over snow. In the absence of high-frequency water vapour measurements, we use sonic anemometer data, which have become much more standard. This method uses the exchange coefficient for sensible heat flux to estimate latent-heat flux. Theory predicts the two exchange coefficients to be equal and the method avoids assuming roughness lengths and stability corrections. We apply this method to two datasets from high mountain (Alps) and polar (Antarctica) environments and compare it with MOST and the three-layer model (3LM). We show that roughness length has a great impact on heat fluxes calculated using MOST and that different calculation methods over snow lead to very different results. Instead, the 3LM leads to good results, in part due to the fact that it avoids roughness length assumptions to calculate heat fluxes. The C-method presented performs overall better or comparable to established MOST with different stability corrections and provides results comparable to the direct EC method. An application of this method is provided for a new station installed in the Pamir mountains. [ABSTRACT FROM AUTHOR]

Investigating latent heat flux (LHF) variations in the western boundary current region is crucial for understanding air–sea interactions. In this study, we examine the LHF trend in the East China Sea Kuroshio Region (ECSKR) from 1959 to 2021 using atmospheric and oceanic reanalysis datasets and find that the LHF has a significant strengthening trend. This strengthening can be attributed to sea surface warming resulting from the advection of sea surface temperatures. More importantly, the LHF trend has an apparent seasonal dependence: the most substantial increasing trend in LHF is observed in spring, while the trends are weak in other seasons. Further analysis illustrates that the anomaly of air–sea humidity difference plays a pivotal role in controlling the seasonal variations in LHF trends. Specifically, as a result of the different responses of the East Asian Trough to global warming across different seasons, during spring, the East Asian Trough significantly deepens, resulting in northerly winds that facilitate the intrusion of dry and cold air into the ECSKR region. This intensifies the humidity difference between the sea and air, promoting the release of oceanic latent heat. These findings can contribute to a better understanding of the surface heat budget balance within western boundary currents. [ABSTRACT FROM AUTHOR]

An accurate and dynamic evaluation of the latent heat flux (LE) of greenhouse crops is imperative for advancing precision irrigation. Previous studies used the Penman-Monteith model to evaluate LE and treated the canopy as a holistic leaf, overlooking the discrepancies in structure and microclimate across canopy vertical sections. This study divided the canopy into a shaded and a sunlit layer in line with the structural characteristics of the tomato canopy and the shift in solar elevation angle β. A full-layer model (PMI) and a semi-layer model (PMT) were established based on the layering difference in the evaluation of canopy resistance (rc) and aerodynamic resistance (ra). Eight models: PMI1, PMI2, PMI3, PMI4, PMT1, PMT2, PMT3, and PMT4, were obtained using meteorological data from 2 m above the ground and 2/3 of the canopy height in 2022 and 2023. The performance was compared with the big leaf model (PMB) and verified based on the LE measured by the lysimeter (LEm). The results indicated that LE had the highest sensitivity to canopy absorbed net radiation during the flowering stage (1≤LAI≤3), while PMI2 and PMI4 overestimated LE with the fitting slopes (LE-LEm) of 1.72 and 1.67 in 2022 and 1.70 and 1.55 in 2023, respectively. PMT3 and PMB underestimated LE; the fitting slopes in two years were both 0.83 and 0.80, respectively; PMI3 with the fitting slopes were 0.99 and 0.96 in two years, respectively. In the picking period (LAI≥5), LE was the most sensitive to vapor pressure deficit (VPD); PMI3 and PMB accurately simulated LE with the fitting slops, both over 0.9 in two years. Therefore, the canopy was layered when evaluating rc while treating it as a unit in evaluating ra, PMI3 showed the best comprehensive performance when simulating LE in different seasons and growth periods using meteorological data at 2 m above the ground.

Using 2‐year platform observations, this study investigates seasonal characteristics of sea land breeze (SLB) and how it influences air‐sea turbulent heat fluxes (THFs) in the coastal areas of East China Sea (ECS) in different seasons. Unlike other SLB studies, this study uses hourly observation on a sea platform to explore SLB's effect on both air‐sea latent heat and sensible heat transferring. The results show that sea wind (SW) does not have an obvious seasonal variation pattern while land wind (LW) is stronger in autumn and winter. The SLB day number shows a clear seasonal variation pattern, which accounts for 38.04% and 18.23% of summertime and wintertime days, reaching its peak and bottom respectively. The latent heat flux (LHF) and sensible heat flux (SHF) are high in autumn and winter while low in summer. The SLB‐contributed LHF and SHF reach peaks in autumn and winter, which are 61.07 and 7.39 W/m2 respectively. The contribution importance of SLB on air‐sea sensible/latent heat transferring is highest in summer while lowest in winter. On SLB days, the SHF decreases significantly by at least about 50% while LHF decreases moderately in all seasons, among which spring witnesses an inversion of sensible heat transferring direction. The warming effect of SLB is mainly responsible for the slump of SHF on SLB days. Multiple factors including relative humidity (RH), background wind field and in situ radiation cause the LHF decrease together, whose changing range varies with season. Plain Language Summary: Sea land breeze (SLB) has a great impact on regional environment and meteorological fields. Turbulent heat flux (THF), including sensible heat flux (SHF) and latent heat flux (LHF), is fundamentally engaged in nearly every atmosphere‐ocean interaction process and undoubtedly serve as an important driving force of global atmospheric and oceanic circulation as well as a sensitive variable when facing global climate change. However, there are few studies relating SLB to the variation of THF in the near coastal region, which is a sensitive‐area to climatic changes under the effects of both natural and human variabilities. In this study, instead of using land‐based data like other SLB studies, we investigate SLB's effects on air‐sea THFs in different seasons based on sea‐based data. We find that SLB's role in transferring air‐sea energy in form of THF is most important in summer among all seasons. The SHF decreases significantly while LHF decreases moderately on SLB days in all four seasons. The warming effect of SLB is mainly responsible for the slump of SHF on SLB days, while the external factors such as background wind field, relative humidity, and in situ radiation are responsible for the LHF decrease on SLB days. Key Points: The peak SLB‐contributed LHF and SHF are 61.1 W/m2 in autumn and 7.4 W/m2 in winter, respectivelyThe SHF decreases significantly while LHF decreases moderately on SLB days in four seasonsThe warming effect of SLB is mainly responsible for the slump of SHF on SLB days [ABSTRACT FROM AUTHOR]

An air-sea interaction field campaign was conducted in September of 2017 within the warm and cold eddy region of the western Northwest Pacific (WNP) (17.5°-20.5°N, 127.5°E-133.5°E). Both near-surface oceanic and atmospheric conditions in addition to ocean heat content (OHC) were examined to better understand the mechanisms governing high heat flux magnitudes responsible for rapidly intensifying tropical cyclones. Observations from this experiment indicate that the latent heat flux (LHF) under modest wind conditions reached 400Wm-2 within the vicinity of a warm eddy, with OHC higher than 100 kJ cm-2 of warm eddy region being 2~3 times as large as that of cold eddy region. These high OHC and a resultant high LHF in the warm eddy, comparable to the magnitude of LHF in the North Equatorial Current, may explain the mechanism of why tropical cyclones over a warm eddy in eddy-rich zones often rapidly intensify in the WNP. A month later typhoon Lan rapidly intensified into a super typhoon, while passing over the boundary region of warm and cold eddies during the observation period. Results from this study illustrate that both the wind-normalized LHF and the difference (Qs-Qa) between the specific humidity at air (Qa) and at the sea surface (Qs), closely correlate with OHC patterns, which suggests that the ocean looks likely to control the spatial pattern of LHF. Overall, both the ocean and weather conditions govern the pattern of specific humidity difference between the air-sea interface, with large OHC over the warm eddy controlling higher Qs and the pattern of Qa depending on the pattern of wind direction. Qa as a factor impacting LHF magnitude is strongly linked to wind direction in the experimental area, that is, the drier northwesterly flow and southeasterly moist wind, resulting in the enhanced contrast of specific humidity at cold eddy region. [ABSTRACT FROM AUTHOR]

The water vapor transport associated with latent heat flux (LE) in the planetary boundary layer (PBL) is critical for the atmospheric hydrological cycle, radiation balance, and cloud formation. The spatiotemporal variability of LE and water vapor mixing ratio (rv) are poorly understood due to the scale‐dependent and nonlinear atmospheric transport responses to land surface heterogeneity. Here, airborne in situ measurements with the wavelet technique are utilized to investigate scale‐dependent relationships among LE, vertical velocity (w) variance (σw2 ${\sigma }_{w}^{2}$), and rv variance (σH2O2 ${\sigma }_{\mathrm{H}2\mathrm{O}}^{2}$) over a heterogeneous surface during the Chequamegon Heterogeneous Ecosystem Energy‐balance Study Enabled by a High‐density Extensive Array of Detectors 2019 (CHEESEHEAD19) field campaign. Our findings reveal distinct scale distributions of LE, σw2 ${\sigma }_{w}^{2}$, and σH2O2 ${\sigma }_{\mathrm{H}2\mathrm{O}}^{2}$ at 100 m height, with a majority scale range of 120 m–4 km in LE, 32 m–2 km in σw2 ${\sigma }_{w}^{2}$, and 200 m–8 km in σH2O2 ${\sigma }_{\mathrm{H}2\mathrm{O}}^{2}$. The scales are classified into three scale ranges, the turbulent scale (8–200 m), large‐eddy scale (200 m–2 km), and mesoscale (2–8 km) to evaluate scale‐resolved LE contributed by σw2 ${\sigma }_{w}^{2}$ and σH2O2 ${\sigma }_{\mathrm{H}2\mathrm{O}}^{2}$. The large‐eddy scale in PBL contributes over 70% of the monthly mean total LE with equal parts (50%) of contributions from σw2 ${\sigma }_{w}^{2}$ and σH2O2 ${\sigma }_{\mathrm{H}2\mathrm{O}}^{2}$. The monthly temporal variations mainly come from the first two major contributing classified scales in LE, σw2 ${\sigma }_{w}^{2}$, and σH2O2 ${\sigma }_{\mathrm{H}2\mathrm{O}}^{2}$. These results confirm the dominant role of the large‐eddy scale in the PBL in the vertical moisture transport from the surface to the PBL, while the mesoscale is shown to contribute an additional ∼20%. This analysis complements published scale‐dependent LE variations, which lack detailed scale‐dependent vertical velocity and moisture information. Plain Language Summary: The vertical water vapor transport in the planetary boundary layer (PBL), and the associated latent heat flux (LE), are critical for the atmospheric hydrological cycle, radiation balance, and cloud formation. However, the vertical moisture transport varies nonlinearly at multiple scales due to the land surface heterogeneity across multiple properties. This study investigates the scale‐resolved impact of water vapor and vertical velocity on LE, using data collected aboard an atmospheric research aircraft flying low above the surface in summer over northern Wisconsin during the CHEESEHEAD19 campaign. This study finds that LE and water vapor variance is largest at the large‐eddy scale in PBL and at the mesoscale. In contrast, vertical velocity variance is primarily present in turbulent and large‐eddy scales in PBL. This study confirms the significant role of the large‐eddy scale in PBL in contributing to the majority of the vertical moisture transport from the surface to the PBL top. These findings provide better insight into the factors influencing LE at different scales. Key Points: The scale‐dependent distribution of latent heat flux, vertical velocity variance, and water vapor variance at 100 m over a heterogeneous surface is describedIn the large‐eddy scale, 70% of total latent heat flux is contributed by 50% of total vertical velocity variance and 50% of total water vapor varianceThe large‐eddy scale contributes most of the vertical moisture transport from the surface to the Planetary Boundary Layer [ABSTRACT FROM AUTHOR]

The exchange of moisture and energy between the land and the atmosphere plays a crucial role in terrestrial hydrological cycle and climate change. However, existing studies on the retrieval of surface water and heat flux tend to overlook the dynamic changes in surface vegetation and atmospheric aerosols, which directly affect surface energy and indirectly alter various meteorological factors, including cloud, precipitation, and temperature. In this study, we assess the machine-learning retrieval method for surface fluxes that takes into account vegetation changes and aerosol effects, using FLUXNET observations and remote sensing data to retrieve latent heat flux (LE) and sensible heat flux (H). We constructed four sets of deep neural network models: (a) The first set considers only meteorological factors, (b) the second set considers meteorological factors and aerosols, (c) the third set considers meteorological factors and vegetation changes, and (d) the fourth set comprehensively considers meteorological factors, aerosols, and vegetation changes. All model performances were evaluated using statistical indicators. ERA5 reanalysis and remote sensing data were used to drive the models and retrieve daily H and LE. The retrieved results were validated against ground observation sites that were not involved in model training or the FLUXCOM product. The results show that the model that considers meteorological factors, aerosols, and vegetation changes has the smallest errors and highest correlation for retrieving H and LE (RH = 0.85, RMSEH = 24.88; RLE = 0.88, RMSELE = 22.25). The ability of the four models varies under different vegetation types. In terms of seasons, the models that consider meteorological factors and vegetation changes, as well as those that comprehensively consider meteorological factors, aerosols, and vegetation changes, perform well in retrieving the surface fluxes. As for spatial distribution, when atmospheric aerosols are present in the region, the model that considers both meteorological factors and aerosols retrieves higher values of H compared to the model that considers only meteorological factors, while the LE values are relatively lower. The model that considers meteorological factors and vegetation changes, as well as the model that comprehensively considers meteorological factors, aerosols, and vegetation changes, retrieves lower values in most regions. Through the validation of independent observation sites and FLUXCOM products, we found that the model, considering meteorological factors, aerosols, and vegetation changes, was generally more accurate in the retrieval of surface fluxes. This study contributes to improving the retrieval and future prediction accuracy of surface fluxes in a changing environment. [ABSTRACT FROM AUTHOR]

Energy partitioning and evapotranspiration (ET) of alpine meadows in permafrost areas are crucial for water cycle on the Qinghai-Tibet Plateau. However, seasonal (freeze–thaw cycle) variations in energy partitioning and ET and their driving factors must be clarified. Therefore, 4-year energy fluxes [i.e. latent heat (LE) and sensible heat (H)] were observed, and bulk parameters [i.e. surface conductance, decoupling coefficient (Ω), and Priestley–Taylor coefficient (α)] were estimated in an alpine meadow in the Qinghai-Tibet Plateau. Mean daily LE (27.45 ± 23.89 W/m2) and H (32.51 ± 16.72 W/m2) accounted for 31.71% and 50.14% of available energy, respectively. More available energy was allocated to LE during the rainfall period, while 67.54 ± 28.44% was allocated to H during the frozen period. H was half the LE during rainfall period and seven times the LE during frozen period due to low soil water content and vegetation coverage during the frozen season. Mean annual ET was 347.34 ± 8.39 mm/year, close to mean annual precipitation. Low mean daily Ω (0.45 ± 0.23) and α (0.60 ± 0.29) throughout the year suggested that ET in the alpine meadow was limited by water availability. However, ET was constrained by available energy because of sufficient water supply from precipitation during rainfall season. In contrast, large differences between ET and precipitation indicated that soil water was supplied via lateral flow from melting upstream glaciers and snow during the transition season. The results suggest that seasonal variations in bulk parameters should be considered when simulating water and energy fluxes in permafrost regions. [ABSTRACT FROM AUTHOR]

The preferred spring development of the Pacific Meridional Mode (PMM) is investigated through a combined observational analysis and modeling approach. A mixed-layer heat budget analysis shows that the PMM experiences its strongest growth two months prior to its mature phase, and the growth is primarily attributed to the surface latent heat flux (LHF) anomaly, via the wind-evaporation-SST (WES) feedback. The spring-fall difference in the LHF anomaly is caused by both the anomalous and seasonal mean wind fields. Idealized atmospheric general circulation model experiments (GCM) show that given the same PMM heating, atmospheric anomalous wind and LHF responses are much stronger in boreal spring than in boreal fall, which favors a greater WES feedback. Experiments with an intermediate air-sea coupled model with specified SST and surface wind mean state demonstrate that a PMM-like SSTA perturbation grows fastest in boreal spring among all seasons, indicating that the tropical mean wind and SST fields in spring are most favorable for the PMM development. Finally, we show that the atmospheric teleconnection between mid-latitude North Pacific and PMM is much more pronounced during the development of PMM in boreal spring than in boreal fall. [ABSTRACT FROM AUTHOR]

Evaporative fraction (EF) is the proportion of latent heat flux in surface net energy and reflects the moisture status of an ecosystem. However, the effects of different meteorological factors and vegetation changes on EF are not known. In this study, 142 flux tower observations were used to analyze the spatial and temporal variations of EF in different vegetation types and to analyze the response of meteorological factors and vegetation changes to EF. The results showed that evergreen broadleaf forests (EBFs) had the highest multiyear mean EF (0.61), while open shrublands (OSH) had the lowest multiyear mean EF (0.32). Areas with higher EF values were generally found in temperate continental, mediterranean, and oceanic climates. Seasonally, EFs were generally high in the northern and southern hemispheres during the summer and relatively low in the spring and autumn. The correlation analysis showed that EF increased significantly with increasing precipitation and leaf area index (LAI) for all six vegetation types. Deciduous broadleaf forests ($R$ = 0.37, RSS = 6.96, and $P < 0.01$) and wetlands ($R$ = 0.26, RSS = 7.03, and $P < 0.01$) showed a significant increasing trend with increasing vapor pressure deficit (VPD), and two vegetation types, grasslands ($R$ = −0.35, RSS = 13.44, and $P < 0.01$), and EBF ($R$ = −0.19, RSS = 3.77, and $P < 0.01$) showed a significant decrease trend with increasing VPD. The monthly mean EF of three vegetation types, grasslands ($R$ = 0.26, RSS = 14.20, and $P < 0.01$), deciduous broadleaf forests ($R$ = 0.34, RSS = 7.11, and $P < 0.01$), and wetlands ($R$ = −0.40, RSS = 6.37, and $P < 0.01$) decreased significantly with increasing wind speed. Our findings provide a scientific basis for assessing surface water conditions and contribute to the understanding of EF interactions with climate and vegetation change. [ABSTRACT FROM AUTHOR]

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.

Introduction In determining the evapotranspiration (ET) of a crop species, factors such as type, crop density, growth stage, climate of the region, physicochemical characteristics and soil fertility, have a significant effect. Therefore, it has a significant complexity. In recent years, new technologies are used to estimate ET, such as surface energy balance algorithm for land (SEBAL), which estimates actual evapotranspiration, using satellite data and some ground data. The purpose of this research is to estimate the actual ET and water requirement of Rosa damascena using SEBAL during three crop growth years in a part of the Shahrekord high plain. Materials and Methods The studied farm with an area of 16.38 ha is located in the Shahrekord plain, Karoun watershed. The remote sensing data included 42 cloud-free images of Landsat 7 and Landsat 8 satellites (2017, 2018, and 2019). The growth period lasted from the beginning of April to the end of November of each crop year. Images were processed in ERDAS Imagine 2015 software for radiometric correction and subsequent calculations using SEBAL algorithm. In order to estimate the actual evapotranspiration, the energy balance equation is used. For this purpose, all energy fluxes such as, Rn: the net incoming radiation flux to the considered surface, H: the sensible heat flux, G0: the soil heat flux and lET: the latent heat flux of evapotranspiration should be taken into account. The first step in the SEBAL process is to calculate the net radiation flux of the Rn. The second, soil heat flux G0 that is the rate of heat capacity in the soil and vegetation resulting from heat conduction or heat energy used to heat or cools the volume of the soil mass. The third is to calculate sensible heat flux (H) is the rate of heat loss to the air by conduction and convection phenomena, which is caused by the thermal difference. In SEBAL process, two "anchor" pixels are used to create boundary conditions for energy balance. These include as "cold (wet)" and "warm (dry)" pixels that are determined in the study area. A cold pixel is selected at the surface of open water or the surface covered by a well-watered alfalfa crop. It is assumed that the temperature of the surface and the temperature of the air near the surface are the same in this pixel. The "warm" pixel is selected in dry agricultural lands and its ET is considered zero. It is necessary for SEBAL model to establishing a linear equation between the surface temperature (Ts) and the air-surface temperature difference (dT) for each pixel using hot (dry) and cold (wet) pixels. Results and Discussion Based on the results of three years of research in a 16.38 hectare Golmohammadi farm in the Shahrekord plain, using the Sabal algorithm and the number of 42 images on the days of Landsat 7 and Landsat 8 satellites passing, as well as using the modified Penman-Mantith-Fao mathematical relationship. It was found that the amount of evaporation and transpiration of hollyhocks in the studied area was on average 1043.8 mm during the growth period. According to the results of other researchers, which have been conducted using lysimeter data and field studies, it necessarily requires higher costs than remote sensing methods. In this research, the ability of the Sabal algorithm (as one of the best remote sensing algorithms) to estimate evaporation And the actual transpiration and determination of the water requirement of the chrysanthemum plant with a low cost and an easy method compared to the results of other researchers, which were done with difficult and expensive lysimetric methods, were proved and it is suitable to be used for other plant species and in other geographical areas. Results showed that actual evapotranspiration value of rose crop (ETC) obtained from the SEBAL during the three years of experiment were 1089.4, 1021.3, and 1020.6 mm per growth period. In the same period, reference crop evapotranspiration (ET0) values were 1214.8, 1100.5, and 1135.5 mm during the growth period, respectively. In other words, average value for ETC was 1043.8 mm in growth period. ConclusionBased on the results of three years of research in a 16.38 hectare Golmohammadi farm in the Shahrekord plain, using the Sabal algorithm and the number of 42 images on the days of Landsat 7 and Landsat 8 satellites passing, as well as using the modified Penman-Mantith-Fao mathematical relationship. It was found that the amount of evaporation and transpiration of hollyhocks in the studied area was on average 1043.8 mm during the growth period. According to the results of other researchers, which have been conducted using lysimeter data and field studies, it necessarily requires higher costs than remote sensing methods. In this research, the ability of the Sabal algorithm (as one of the best remote sensing algorithms) to estimate evaporation And the actual transpiration and determination of the water requirement of the chrysanthemum plant with a low cost and an easy method compared to the results of other researchers, which were done with difficult and expensive lysimetric methods, were proved and it is suitable to be used for other plant species and in other geographical areas.

Wetlands, which are composed of soil, vegetation and water, have sufficient water supply and are sensitive to climate change. This study analyzes the coupling degree between wetlands and atmosphere and discusses the influence of environmental factors (solar radiation and water vapor pressure deficit) on latent heat flux by using the experimental data from the Maduo Observatory of Climate and Environment of the Northwest Institute of Eco-Environment and Resource, CAS and WRF models. The results showed that, during the vegetation growing season, the average value of Ω (decoupling factor) is 0.38 in alpine wetlands, indicating that the coupling between wetlands and atmosphere is poor. Solar radiation is the main factor influencing the latent heat flux in the results of both observation data analysis and model simulation, and solar radiation and water vapor pressure deficit still have the opposite reaction to latent heat flux; when solar radiation increased by 30%, the average daily amount of latent heat flux increased from 5.57 MJ·m−2 to 7.50 MJ·m−2; when water vapor pressure deficit increased by 30%, the average daily amount of latent heat flux decreased to 5.17 MJ·m−2. This study provides a new research approach for the study of the parameterization of latent heat flux and evapotranspiration in the context of global climate change [ABSTRACT FROM AUTHOR]

The statistical characteristics and mechanism of the South Atlantic Ocean Dipole (SAOD) from 1980 to 2021 are analysed using observational datasets. The spatial pattern of the sea surface temperature anomaly (SSTA) during SAOD is a dipole pattern oriented in the northeast‐southwest direction, and the intensity of the SSTA in the northeast pole (NEP) is stronger than that in the southwest pole (SWP). SAOD has a decadal variability of about 12 years during 1980–2007, along with obvious seasonal phase‐locking, with the anomaly pattern developing in boreal spring (March–May), peaking in summer (June–August) and decaying in autumn (September–November). For a positive SAOD event (positive SSTA in the NEP, negative in the SWP), positive SSTA in the NEP grows due to a decrease in wind speed and thus in latent heat flux loss in boreal spring, as well as an increase in shortwave radiation flux from boreal spring to summer. However, southwesterly wind anomalies drive cold water from high latitudes to the SWP in boreal spring and summer, coupled with strong wind speed anomalies enhancing the loss of latent heat flux, which contributes to a negative SSTA in the SWP. In addition, the intensity of the SSTA in the SWP is weaker than that in the NEP because of the contribution of smaller shortwave radiation flux, sensible heat flux and larger mixed layer depth in the SWP in summer. For a negative SAOD mode (negative SSTA in the NEP, positive in the SWP), the wind, shortwave radiation flux, sensible heat flux and mixed layer depth anomalies are the opposite of those under a positive SAOD event. [ABSTRACT FROM AUTHOR]

The seasonal evolution and interannual variability of latent heat flux (LHF) over the tropical Indian Ocean (TIO) region is examined for the period 1980–2019. The seasonal distribution of LHF is dominated by the winter pattern of each hemisphere in the TIO. Climatologically high LHF is mostly confined to the Arabian Sea and Bay of Bengal regions in the north Indian Ocean and the zonal belt between 10oS and 25oS in the south Indian Ocean. Warm and cold phases of El‐Niño Southern Oscillation, Indian Ocean Dipole (IOD), and their co‐occurrence events leave distinct LHF signatures over the TIO. The LHF anomalies during these events are more profound than pure events with enhanced latent heat loss when the La Niña and negative IOD events coincide. The LHF anomalies associated with the wind‐evaporation‐SST feedback is prominent when positive IOD co‐occur with the El‐Niño event. Both the vertical humidity gradient and wind speed changes play substantial roles in driving LHF anomalies during the co‐occurring events of NIOD and La Niña. [ABSTRACT FROM AUTHOR]

The modulation of the leaf energy budget components to maintain optimal leaf temperature are fundamental aspects of plant functioning and survival. Better understanding these aspects becomes increasingly important under a drying and warming climate when cooling through evapotranspiration (E) is suppressed. Combining novel measurements and theoretical estimates, we obtained unusually comprehensive twig‐scale leaf energy budgets under extreme field conditions in droughted (suppressed E) and non‐droughted (enhanced E) plots of a semi‐arid pine forest. Under the same high mid‐summer radiative load, leaf cooling shifted from relying on nearly equal contributions of sensible (H) and latent (LE) energy fluxes in non‐droughted trees to relying almost exclusively on H in droughted ones, with no change in leaf temperature. Relying on our detailed leaf energy budget, we could demonstrate that this is due to a 2× reduction in leaf aerodynamic resistance. This capability for LE‐to‐H shift in leaves of mature Aleppo pine trees under droughted field conditions without increasing leaf temperature is likely a critical factor in the resilience and relatively high productivity of this important Mediterranean tree species under drying conditions. Summary statement: Relying on detailed leaf energy budgets in mature pines, we demonstrate that leaves greatly enhance their sensible heat flux to prevent overheating under drought, which must rely on changes in leaf aerodynamic resistance. This may be a critical factor in the resilience of trees to drying conditions. [ABSTRACT FROM AUTHOR]

Forest ecosystems in the mid-latitudes of the Northern Hemisphere are significantly affected by frequent extreme weather events. How different forest ecosystems respond to these changes is a major challenge. This study aims to assess differences in the response of daily net ecosystem exchange (NEE) of CO2 and latent heat flux (LE) between different boreal and temperate ecosystems and the atmosphere to extreme weather events (e.g., anomalous temperature and precipitation). In order to achieve the main objective of our study, we used available reanalysis data and existing information on turbulent atmospheric fluxes and meteorological parameters from the global and regional FLUXNET databases. The analysis of NEE and LE responses to high/low temperature and precipitation revealed a large diversity of flux responses in temperate and boreal forests, mainly related to forest type, geographic location, regional climate conditions, and plant species composition. During the warm and cold seasons, the extremely high temperatures usually lead to increased CO2 release in all forest types, with the largest response in coniferous forests. The decreasing air temperatures that occur during the warm season mostly lead to higher CO2 uptake, indicating more favorable conditions for photosynthesis at relatively low summer temperatures. The extremely low temperatures in the cold season are not accompanied by significant NEE anomalies. The response of LE to temperature variations does not change significantly throughout the year, with higher temperatures leading to LE increases and lower temperatures leading to LE reductions. The immediate response to heavy precipitation is an increase in CO2 release and a decrease in evaporation. The cumulative effect of heavy precipitations is opposite to the immediate effect in the warm season and results in increased CO2 uptake due to intensified photosynthesis in living plants under sufficient soil moisture conditions. [ABSTRACT FROM AUTHOR]

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.

An experimental site at Obafemi Awolowo University's Teaching and Research Farm, in Ile-Ife, Nigeria, was used to conduct multilevel measurements of meteorological parameters, and turbulent fluxes of sensible and latent heat in the atmospheric surface layer (ASL) between June 1 and July 31, 2016. The framework provided by Monin-Obukhov Similarity Theory (MOST) for estimating the turbulent fluxes of sensible and latent heat through existing empirical flux-profile relationships was employed. The objective of this study was to evaluate the performance of the flux-profile technique based on direct measurements of turbulent fluxes obtained from an eddy covariance (EC) system set up at the same location. The results showed that the diurnal patterns of both sensible and latent heat fluxes estimated from flux-profile technique compared relatively well with the direct measurements of the EC system. Nighttime estimations under stably stratified conditions of the atmosphere strongly correlated (R = 0.98) with the directly measured values. However, during the daytime convective conditions, there were some consistent discrepancies in the performance of the flux-profile technique with errors in some of the estimated fluxes well within the uncertainty range of the EC measurements. For sensible 2 2 heat flux estimates; the coefficient of determination, R (0.71), the mean biased error, MBE (15.1 W/m) and the percentage error determined for the period averaged values of the daytime estimates indicated that the sensible heat flux was only overestimated by up to 20%. On the other hand, a negative MBE 2 2 (-28.2 W/m), weak coefficient of determination,R (0.58)and negative percentage error obtained for the period averaged values of the latent heat flux indicated there is an underestimation of up to 45%. It can be concluded the flux-profile relationships can be employed within certain limits of confidence interval at tropical locations especially for the estimation of sensible heat flux. [ABSTRACT FROM AUTHOR]

The GRAPES (Global/Regional Assimilation and Prediction System) global medium-range ensemble forecast system (GRAPES_GFS) is a new generation numerical weather forecast model developed by the China Meteorological Administration (CMA). However, the forecasts of surface latent heat fluxes and surface air temperature have systematic biases, which affect the forecasts of atmospheric dynamics by modifying the lower boundary conditions and degrading the application of GRAPES_GFS since the 2 m air temperature is one of the key components of weather forecast products. Here, we add a soil resistance term to reduce soil evaporation, which ultimately reduces the positive forecast bias of the land surface latent heat flux. We also reduce the positive forecast bias of the ocean surface latent heat flux by considering the effect of salinity in the calculation of the ocean surface vapor pressure and by adjusting the parameterizations of roughness length for the exchanges in momentum, heat, and moisture between the ocean surface and atmosphere. Moreover, we modify the parameterization of the roughness length for the exchanges in heat and moisture between the land surface and atmosphere to reduce the cold bias of the nighttime 2 m air temperature forecast over areas with lower vegetation height. We also consider the supercooled soil water to reduce the warm forecast bias of the 2 m air temperature over northern China during winter. These modified parameterizations are incorporated into the GRAPES_GFS and show good performance based on a set of evaluation experiments. This paper highlights the importance of the representations of the land/ocean surface and boundary layer processes in the forecasting of surface heat fluxes and 2 m air temperature. [ABSTRACT FROM AUTHOR]

It is well known that the dry/wet boundaries of land surface temperature fractional vegetation coverage (LSTfc) trapezoid framework vary linearly with vegetation coverage (fc). In this study, the theoretical end-members algorithm is modified to continuously estimate the dry/wet end-members under varying vegetation conditions, causing the theoretical dry/wet boundaries to become non-linear. The findings revealed that the non-linear dry/wet boundaries were generally below the conventional linear dry/wet boundaries. Furthermore, the non-linear boundary scheme adopted herein provided better performance in estimating the latent heat flux (LE) and vegetation latent heat flux fraction (LEv/LE) compared to the linear boundary scheme. The parametric schemes of aerodynamic and thermodynamic roughness length and the aerodynamic resistance were the major drivers that result in dry/wet boundaries characteristics being highly non-linear. This study enhanced the physical process description in the LST-fc trapezoid framework and improved the prediction accuracy of regional LE and its components. [ABSTRACT FROM AUTHOR]

The temporal variations of latent heat flux (λET) and its affecting factors vary from seconds to decades, and alter with crop species. Understanding the temporal coherence between λET and its influencing factors across different underlying surfaces is a crucial research topic with practical implications, and can enable better water management. To investigate this, we conducted a study in southern China measuring water and heat fluxes over flooded rice-winter wheat rotation fields from 2017 to 2021. Wavelet transform technology was employed to analyze the spectral properties of λET and its affecting factors. Results showed that the power spectra of λET exhibited different cascade laws for rice and winter wheat. The spectral variabilities of λET occurred at daily and seasonal time scales for both rice and winter wheat, and an additional weekly time-scale for rice. Furthermore, the cospectrum between λET and soil water content (SWC) for rice showed a significant temporal correlation at 2–4 days, indicating the period of water input. We found that the daily λET of both crops changed synchronously with daily net radiation (Rn), and preceded daily vapor pressure deficit (VPD) and air temperature (Ta) by 1.5–2.6 h. The phase angle between λET and Ta was significantly lower for rice (mean = 1.8 h) than winter wheat (mean = 2.3 h). Partial wavelet coherence revealed that Rn, followed by VPD, was the main meteorological factor affecting λET for the rotated flooded rice-winter wheat system at each time scale, especially at the daily time scale. Additionally, the effect of VPD on λET was lower for winter wheat than rice at scales below a month. These findings offered a useful insight into selecting models of λET for varying time scales and promoting better agricultural water management.

Introduction In determining the evapotranspiration (ET) of a crop species, factors such as type, crop density, growth stage, climate of the region, physicochemical characteristics and soil fertility, have a significant effect. Therefore, it has a significant complexity. In recent years, new technologies are used to estimate ET, such as surface energy balance algorithm for land (SEBAL), which estimates actual evapotranspiration, using satellite data and some ground data. The purpose of this research is to estimate the actual ET and water requirement of Rosa damascena using SEBAL during three crop growth years in a part of the Shahrekord high plain. Materials and Methods The studied farm with an area of 16.38 ha is located in the Shahrekord plain, Karoun watershed. The remote sensing data included 42 cloud-free images of Landsat 7 and Landsat 8 satellites (2017, 2018, and 2019). The growth period lasted from the beginning of April to the end of November of each crop year. Images were processed in ERDAS Imagine 2015 software for radiometric correction and subsequent calculations using SEBAL algorithm. In order to estimate the actual evapotranspiration, the energy balance equation is used. For this purpose, all energy fluxes such as, Rn: the net incoming radiation flux to the considered surface, H: the sensible heat flux, G0: the soil heat flux and λET: the latent heat flux of evapotranspiration should be taken into account. The first step in the SEBAL process is to calculate the net radiation flux of the Rn. The second, soil heat flux G0 that is the rate of heat capacity in the soil and vegetation resulting from heat conduction or heat energy used to heat or cools the volume of the soil mass. The third is to calculate sensible heat flux (H) is the rate of heat loss to the air by conduction and convection phenomena, which is caused by the thermal difference. In SEBAL process, two "anchor" pixels are used to create boundary conditions for energy balance. These include as "cold (wet)" and "warm (dry)" pixels that are determined in the study area. A cold pixel is selected at the surface of open water or the surface covered by a well-watered alfalfa crop. It is assumed that the temperature of the surface and the temperature of the air near the surface are the same in this pixel. The "warm" pixel is selected in dry agricultural lands and its ET is considered zero. It is necessary for SEBAL model to establishing a linear equation between the surface temperature (Ts) and the air-surface temperature difference (dT) for each pixel using hot (dry) and cold (wet) pixels. Results and Discussion Based on the results of three years of research in a 16.38 hectare Golmohammadi farm in the Shahrekord plain, using the Sabal algorithm and the number of 42 images on the days of Landsat 7 and Landsat 8 satellites passing, as well as using the modified Penman-Mantith-Fao mathematical relationship. It was found that the amount of evaporation and transpiration of hollyhocks in the studied area was on average 1043.8 mm during the growth period. According to the results of other researchers, which have been conducted using lysimeter data and field studies, it necessarily requires higher costs than remote sensing methods. In this research, the ability of the Sabal algorithm (as one of the best remote sensing algorithms) to estimate evaporation And the actual transpiration and determination of the water requirement of the chrysanthemum plant with a low cost and an easy method compared to the results of other researchers, which were done with difficult and expensive lysimetric methods, were proved and it is suitable to be used for other plant species and in other geographical areas. Results showed that actual evapotranspiration value of rose crop (ETC) obtained from the SEBAL during the three years of experiment were 1089.4, 1021.3, and 1020.6 mm per growth period. In the same period, reference crop evapotranspiration (ET0) values were 1214.8, 1100.5, and 1135.5 mm during the growth period, respectively. In other words, average value for ETC was 1043.8 mm in growth period. Conclusion Based on the results of three years of research in a 16.38 hectare Golmohammadi farm in the Shahrekord plain, using the Sabal algorithm and the number of 42 images on the days of Landsat 7 and Landsat 8 satellites passing, as well as using the modified Penman-Mantith-Fao mathematical relationship. It was found that the amount of evaporation and transpiration of hollyhocks in the studied area was on average 1043.8 mm during the growth period. According to the results of other researchers, which have been conducted using lysimeter data and field studies, it necessarily requires higher costs than remote sensing methods. In this research, the ability of the Sabal algorithm (as one of the best remote sensing algorithms) to estimate evaporation And the actual transpiration and determination of the water requirement of the chrysanthemum plant with a low cost and an easy method compared to the results of other researchers, which were done with difficult and expensive lysimetric methods, were proved and it is suitable to be used for other plant species and in other geographical areas. [ABSTRACT FROM AUTHOR]

Investigating latent heat flux (LHF) variations in the western boundary current region is crucial for understanding air–sea interactions. In this study, we examine the LHF trend in the East China Sea Kuroshio Region (ECSKR) from 1959 to 2021 using atmospheric and oceanic reanalysis datasets and find that the LHF has a significant strengthening trend. This strengthening can be attributed to sea surface warming resulting from the advection of sea surface temperatures. More importantly, the LHF trend has an apparent seasonal dependence: the most substantial increasing trend in LHF is observed in spring, while the trends are weak in other seasons. Further analysis illustrates that the anomaly of air–sea humidity difference plays a pivotal role in controlling the seasonal variations in LHF trends. Specifically, as a result of the different responses of the East Asian Trough to global warming across different seasons, during spring, the East Asian Trough significantly deepens, resulting in northerly winds that facilitate the intrusion of dry and cold air into the ECSKR region. This intensifies the humidity difference between the sea and air, promoting the release of oceanic latent heat. These findings can contribute to a better understanding of the surface heat budget balance within western boundary currents.

Micrometeorology plays a pivotal role in advancing our understanding of agricultural systems by unraveling intricate interactions between climate dynamics and crop performance. This article presents a comprehensive analysis of the literature published on crop micrometeorology and indexed in Scopus database from 2000 to 2023. The query yielded only 146 documents, which were subsequently subjected to analysis using an R-based bibliometric tool to assess annual scientific production trend, document types, citation, and keyword analysis. The results revealed zero growth rate of the topic with an average 47.36 citations and total citation of 6536 in the analysis period. USA dominates the number of publications (28.1%), followed by China (17.8%), Japan (11.6%) and Australia (8.9%). India stood at 10th position with only 8 documents contributing 5.5% of the total publications included in the study. The key domains of current research in the realm of crop micrometeorology identified through bibliometric analysis were evapotranspiration, energy balance, gas emissions, and modelling based studies, which are discussed in details in the article. As climate change and global food security becomes more critical, this analysis highlights the role of micrometeorological works within the realm of climate change and crop studies.

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. [ABSTRACT FROM AUTHOR]

This study aims to find out the variations of central pressure (intensity) of intense tropical cyclones (TCs) with sea surface temperature (SST), mid-tropospheric relative humidity (MRH), mid-tropospheric instability (MI), vertical wind shear (VWS), 200 hPa divergence, and surface latent heat flux (SLHF) during the lifetime of intense TCs, and determine the most crucial parameter which shows the highest correlation with central pressure (intensity). Out of all these parameters, SLHF is highly correlated (R2 = 0.74) with the central pressure of intense TCs. Increase and decrease of SLHF correspond to decrease and increase of TCs central pressure (increase and decrease in TCs intensity). The highest SLHF corresponds to the lowest central pressure (highest intensity). [ABSTRACT FROM AUTHOR]

Tropical forests are characterized by vast biomass, complex structures and mega-biodiversity. However, the adaptation processes of these forests to seasonal water availability are less understood, especially those located in the monsoonal and mountainous regions of tropical Southeast Asia. This study used four representative tropical forests spanning from 2° N to 22° N in continental Southeast Asia to address dry-condition photosynthesis at the seasonal scale. We first provided novel and reliable estimations of ecosystem photosynthesis (gross primary production; GPP) seasonality at all four sites. As expected, both evergreen and deciduous seasonal forests exhibited higher GPPs during the rainy season than during the dry season. A bimodal pattern corresponding to solar radiation occurred in the GPP of the perhumid forest. The surface conductance (G s) was consistently lower both in the dry season and during dry spells (DSPs) than during the wet season and non-dry spells. However, this did not prevent GPP from increasing alongside increasing irradiance in the perhumid forest, suggesting that other ecosystem physiological properties, for example, the light-saturated photosynthetic rate, must have increased, thus surpassing the effect of G s reduction. Thus, perhumid forests could be defined as light-demanding ecosystems with regard to their seasonal dynamics. Seasonal forests are water-stressed ecosystems in the dry season, as shown by the reductions in GPP, G s and related ecosystem physiological properties. At all four forest sites, we observed a lack of consistent adaptive strategy to fit the water seasonality due to the diversity in leaf phenology, soil nutrient availability, root depth and other potential factors. [ABSTRACT FROM AUTHOR]

The land surface layer is an important interface between the ground and atmosphere, and cross-surface ground heat flux (G 0) has a significant impact on land surface energy processes and associated cycles. Therefore, understanding dynamics in G 0 is critical for predicting climate changes and developing adaptation strategies. However, the harsh environment and geographic barriers of the Tibetan Plateau have led to a significant lack of observations and soil samples, ultimately limiting the accuracy and application of G 0 calculations. Here we investigated the changes in G 0 at the BJ station, a typical seasonally frozen ground region of the Tibetan Plateau, through soil sampling and long-term in-situ observations. We used the calorimetric method to minimize reliance on model assumptions, aiming to achieve consistent and broadly applicable results. During the freezing-to-thawing and thawing-to-freezing stages, daytime G 0 decreased while nighttime G 0 increased. Conversely, daytime G 0 increased while nighttime G 0 decreased in the completely thawed and completely frozen stages. In moist conditions, more energy was directed toward soil moisture evaporation and vegetation transpiration, whereas in dry conditions, net radiation primarily increased soil temperature, enhancing G 0. Our results revealed the dynamic changes in G 0 across different environmental conditions and their impact on land-atmosphere interactions, and that climate warming and humidifying will diminish the regulatory capacity of G 0. This study highlights the essential requirement for accurate G 0 to predict future climate changes accurately, emphasizing its importance for researchers focusing on land-atmosphere feedback mechanisms and climate modeling. • The minimum and mean G 0 have been increasing while the maximum G 0 decreasing. • More energy is directed toward latent heat flux under moist and warm conditions. • Net radiation primarily increases soil temperature under dry and warm conditions. • The reduction in daytime G 0 leads to insufficient heat release at night. [ABSTRACT FROM AUTHOR]

Accurate quantification of turbulent heat fluxes [THF, comprising sensible heat flux (SHF) and latent heat flux (LHF)] and Bowen ratio ( β , ratio of SHF and LHF) is essential for understanding the air–sea interaction. However, the biased estimates of SHF and LHF by widely applied bulk aerodynamic models, and the separate estimates of SHF and LHF by data-driven models, both may result in unrealistic β estimates. This study for the first time innovatively proposes a Bowen ratio-informed data-driven model (BrTHF) for coordinating the estimations of THF and β using the multivariate random forest (RF) technique and a combination of eddy covariance flux observations and meteorological and oceanic observations collected from 53 historical cruises. The result shows that the BrTHF model could not only achieve high-accuracy SHF and LHF estimates, but also avoid the outliers of β estimates that were commonly found in un-synergistic RF and well-known Coupled Ocean Atmosphere Response Experiment 3.5 models.

The Amazon basin plays a crucial role in the global hydrological cycle and the climate system. Removal of latent heat from the surface covered by the tropical forest through evapotranspiration is a key process that still requires further research due to the complex nature of the involved processes, lack of observations and different model assumptions. Here we present an assessment of the consistency between different latent heat fluxes datasets through an indirect comparison against the daily amplitude of surface temperature and vegetation status estimated from satellite observations. Our study is based on the hypothesis that the observational satellite data can be used to provide hints on how realistically fluxes are represented in different datasets. Results evidence that datasets diverge inside the basin in both space and time, but it is possible to figure out areas under water-limited conditions, especially around the borders of the basin and some regions over eastern/southeastern Amazonia. In despite of these differences, a clear link between daily amplitude of surface temperature, leaf area index and latent heat flux can be observed over particular areas and seasons, where also correlations reach values closer to −0.98 (0.94) for surface temperature (leaf area index) indicating that satellite observations are suitable for assessing the representation of the partitioning of energy fluxes in models and widely used datasets.

Environmental models are sensitive to inaccuracies in their approximation algorithms, which can bias model simulations and even lead to incorrect concepts. We present two alternatives to the two‐source evapotranspiration (ET) model, which utilize a more accurate approximation of the Clausius‐Clapeyron relation. Model performance was evaluated through a comparison with observed half‐hourly eddy covariance fluxes. Modeled representations of sensible heat dynamics and the limiting behaviors were also evaluated to identify the causes of model inaccuracies. Our analysis shows that the new exponential approximation used here significantly reduces errors that stem from solutions to the energy balance equations. The proposed parallel and series models are both more accurate than the Shuttleworth‐Wallace (SW) model under the conditions evaluated here, but we cannot conclude that the new models are consistently more accurate over a broader range of conditions. The new models can correctly reproduce several theoretical limiting behaviors, whereas the SW model generates conceptually incorrect results for several important limiting cases in which some key conductances approach both zero and infinity. Importantly, these models seriously underestimate the observed latent heat fluxes at night; the major causes of the nighttime model inadequacies are thought to be uncertainties of the estimated conductances and forcing data errors. The central concepts and processes related to new models are described via plots of temperature versus specific humidity to explore the theory behind an ET model. Through these efforts, we anticipate making more reliable ET predictions that will lead to a complete understanding of vegetation–atmosphere interactions. Key Points: We propose two new two‐source energy balance evapotranspiration models that incorporate a new approximation algorithmModel performance is evaluated by comparison with observed fluxes, and model behavior is analyzedThe new models are expressed graphically using a plot of temperature versus specific humidity [ABSTRACT FROM AUTHOR]