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Extreme precipitation associated with extratropical cyclones can lead to flooding if cyclones track over land. However, the dynamical mechanisms by which moist air is transported into cyclones is poorly understood. In this paper we analyze airflows within a climatology of cyclones in order to understand how cyclones redistribute moisture stored in the atmosphere. This analysis shows that within a cyclone's warm sector the cyclone-relative airflow is rearwards relative to the cyclone propagation direction. This low-level airflow (termed the feeder airstream) slows down when it reaches the cold front, resulting in moisture flux convergence and the formation of a band of high moisture content. One branch of the feeder airstream turns toward the cyclone center, supplying moisture to the base of the warm conveyor belt where it ascends and precipitation forms. The other branch turns away from the cyclone center exporting moisture from the cyclone. As the cyclone travels, this export results in a filament of high moisture content marking the track of the cyclone (often used to identify atmospheric rivers). We find that both cyclone precipitation and water vapor transport increase when moisture in the feeder airstream increases, thus explaining the link between atmospheric rivers and the precipitation associated with warm conveyor belt ascent. Atmospheric moisture budgets calculated as cyclones pass over fixed domains relative to the cyclone tracks show that continuous evaporation of moisture in the precyclone environment moistens the feeder airstream. Evaporation behind the cold front acts to moisten the atmosphere in the wake of the cyclone passage, potentially preconditioning the environment for subsequent cyclone development. [ABSTRACT FROM AUTHOR]

Models of lake physical processes provide the lower flux boundary conditions for numerical predictions of weather and climate in lake basins. So far, there have been few studies on evaluating lake model performance at the diurnal time scale and against flux observations. The goal of this paper is to evaluate the National Center for Atmospheric Research Community Land Model version 4-Lake, Ice, Snow and Sediment Simulator using the eddy covariance and water temperature data obtained at a subtropical freshwater lake, Lake Taihu, in China. Both observations and model simulations reveal that convective overturning was commonplace at night and timed when water switched from being statically stable to being unstable. By reducing the water thermal diffusivity to 2% of the value calculated with the Henderson-Sellers parameterization, the model was able to reproduce the observed diurnal variations in water surface temperature and in sensible and latent heat fluxes. The small diffusivity suggests that the drag force of the sediment layer in this large (2500 km2) and shallow (2-m depth) lake may be strong, preventing unresolved vertical motions and suppressing wind-induced turbulence. Model results show that a large fraction of the incoming solar radiation energy was stored in the water during the daytime, and the stored energy was diffused upward at night to sustain sensible and latent heat fluxes to the atmosphere. Such a lake-atmosphere energy exchange modulated the local climate at the daily scale in this shallow lake, which is not seen in deep lakes where dominant lake-atmosphere interactions often occur at the seasonal scale. [ABSTRACT FROM AUTHOR]

In this paper, the Weather Research and Forecasting (WRF) Model is used to investigate the sensitivity of precipitation to soil moisture and urban areas in the Netherlands. The average output of a 4-day event during 10-13 May 1999 for which the individual days had similar synoptical forcing is analyzed. Four simulations are conducted to test the impact of soil moisture changes on precipitation. A positive soil moisture-precipitation feedback is found, that is, wet (dry) soils increase (decrease) the amount of precipitation. Three additional experiments are executed, two in which urban areas in the Netherlands are expanded and one where urban areas are completely removed. Expansion of urban areas results in an increase of the sensible heat flux and a deeper planetary boundary layer, similar to reducing soil moisture. Expanding urban areas reduces precipitation over the Netherlands as a whole, but the local response is not clear. Within existing urban areas, mean and maximum temperature increases of 0.4 and 2 K, respectively, are found under an urban coverage scenario for 2040. The ratio of evapotranspiration to precipitation (a measure of the soil moisture-precipitation feedback) in the urbanization experiments is only about one-third (23%) of that in the soil moisture experiments (67%). Triggering of precipitation, on the other hand, is relatively high in the urban expansion experiments. The effects of reduced moisture availability and enhanced triggering in the urban expansion experiments compensate each other, leading to the moderate reduction in precipitation. [ABSTRACT FROM AUTHOR]

The paper presents the incremental improvement of the prediction of the Great Lakes net basin supply (NBS) with the hydrometeorological model Modélisation Environmentale-Surface et Hydrologie (MESH) by increasing the accuracy of the simulated NBS components (overlake precipitation, lake evaporation, and runoff into the lake). This was achieved through a series of experiments with MESH and its parent numerical weather prediction model [the Canadian Global Environmental Multiscale model in its regional configuration (GEM Regional)]. With forcing extracted from operational GEM Regional forecasts, MESH underestimated the NBS in fall and winter. The underestimation increased when the GEM precipitation was replaced with its corrected version provided by the Canadian Precipitation Analysis. This pointed to overestimated lake evaporation and prompted the revision of the parameterization of the surface turbulent fluxes over water used both in MESH and GEM. The revised parameterization was validated against turbulent fluxes measured at a point on Lake Superior. Its use in MESH reduced the lake evaporation and largely corrected the NBS underestimation. However, the Lake Superior NBS became overestimated, signaling an inconsistency between the reduced lake evaporation and the prescribed precipitation. To remove the inconsistency, a new forcing dataset (including precipitation) was generated with the GEM model using the revised flux parameterization. A major NBS simulation improvement was obtained with the new atmospheric forcing reflecting the atmospheric response to the modified surface fluxes over the lakes. Additional improvements resulted by correcting the runoff with a modified snowmelt rate and by insertion of observed streamflows. The study shows that accurate lake evaporation simulation is crucial for accurate NBS prediction. [ABSTRACT FROM AUTHOR]

This paper assesses the performance of the Weather Research and Forecasting Model (WRF) as a tool for multiscale atmospheric simulations. Tests are performed in real and idealized cases with multiple configurations and with resolutions ranging from the mesoscale (gridcell size ~10 km) for the real cases to local scales (gridcell size ~50 m) for both real and idealized cases. All idealized simulations and the finest real-case simulations use the turbulence-resolving large-eddy simulation mode of WRF (WRF-LES). Tests in neutral conditions and with idealized forcing are first performed to assess the model's sensitivity to grid resolutions and subgrid-scale parameterizations and to optimize the setup of the real cases. An increase in horizontal model resolution is found to be more beneficial than an increase in vertical resolution. WRF-LES is then tested, using extensive observational data, in real-world cases over complex terrain through nested simulations in which the mesoscale domains drive the LES domains. Analysis of the mesoscale simulations indicates that the data needed to force the largest simulated domain and to initialize surface parameters have the strongest influence on the results. Similarly, LES model fields are primarily influenced by their mesoscale meteorological forcing. As a result, the nesting of LES models down to a 50-m resolution does not improve all aspects of hydrometeorological predictions. Advantages of using fine-resolution LES are noted at nighttime (under stable conditions) and over heterogeneous surfaces when local properties are required or when resolving small-scale surface features is desirable. [ABSTRACT FROM AUTHOR]

Combination methods estimate the partition of sensible and latent heat fluxes at the surface by combining the surface energy balance equation with the transfer equations for temperature and water vapor in the atmospheric surface layer. This paper presents a diagram that graphically depicts the main assumptions and steps of the method. Potential, apparent potential, and actual evaporation rates are visually explained with the diagram. Using a linearized saturation water content relation, the diagram permits the derivation of many of the combination evaporation results by means of geometrical analysis. The diagram should be helpful in the teaching and understanding of the combination methodology. [ABSTRACT FROM AUTHOR]

The Water and Global Change (WATCH) project evaluation of the terrestrial water cycle involves using land surface models and general hydrological models to assess hydrologically important variables including evaporation, soil moisture, and runoff. Such models require meteorological forcing data, and this paper describes the creation of the WATCH Forcing Data for 1958-2001 based on the 40-yr ECMWF Re-Analysis (ERA-40) and for 1901-57 based on reordered reanalysis data. It also discusses and analyses model-independent estimates of reference crop evaporation. Global average annual cumulative reference crop evaporation was selected as a widely adopted measure of potential evapotranspiration. It exhibits no significant trend from 1979 to 2001 although there are significant long-term increases in global average vapor pressure deficit and concurrent significant decreases in global average net radiation and wind speed. The near-constant global average of annual reference crop evaporation in the late twentieth century masks significant decreases in some regions (e.g., the Murray-Darling basin) with significant increases in others. [ABSTRACT FROM AUTHOR]

As raindrops fall from the cloud base to the ground, evaporation below those clouds affects the rain's isotope ratio, reduces precipitation in arid areas, and impacts the local climate. Therefore, in arid areas with scarce water resources and fragile ecological environments, the below-cloud evaporation is an issue of great concern. Based on 406 event-based precipitation samples collected from nine stations in the Shiyang River basin (SRB) in the northwest arid area, global meteorological water line (GMWL) and local meteorological water line (LMWL) are compared, and the Stewart model is used to study the effect of spatial and temporal variation of below-cloud evaporation on isotope values in different geomorphic units at the SRB. Furthermore, factors influencing below-cloud evaporation are analyzed. The results show that 1) the change of d-excess (Δd) in precipitation at the SRB and the residual ratio of raindrop evaporation (f) vary in time and space. With regard to temporal variation, the intensity of below-cloud evaporation is described by summer < autumn < winter < spring. Regarding spatial variation, the below-cloud evaporation in mountain areas is weaker than in oases and deserts. The intensity of below-cloud evaporation in mountain areas increases with decreasing altitude, and the below-cloud evaporation in oasis and desert areas is affected by local climatic conditions. 2) Below-cloud evaporation is also affected by local transpiration evaporation, especially around reservoirs. Reservoirs increase the relative humidity of the air nearby, weakening below-cloud evaporation. This study deepens our understanding of the water cycle process in arid areas. [ABSTRACT FROM AUTHOR]

"Flash drought" (FD) describes the rapid onset of drought on subseasonal times scales. It is of particular interest for agriculture because it can deplete soil moisture for crop growth in just a few weeks. To better understand the processes causing FD, we evaluate the importance of evaporative demand and precipitation by comparing three different drought indices that estimate this hazard using meteorological and hydrological parameters from the CMIP5 suite of models. We apply the standardized precipitation index (SPI); the evaporative demand drought index (EDDI), derived from evaporative demand E0; and the evaporative stress index (ESI), which connects atmospheric and soil moisture conditions by measuring the ratio of actual and potential evaporation. The results show moderate-to-strong relationships (r2 > 0.5) between drought indices and upper-level soil moisture on daily time scales, especially in drought-prone regions. We find that all indices are able to identify FD in the top 10-cm layer of soil moisture in a similar proportion to that in the models' climatologies. However, there is significant intermodel spread in the characteristics of the FDs identified. This spread is mainly caused by an overestimation of E0, indicating stark differences in the land surface models and coupling in individual CMIP5 models. Of all indices, the SPI provides the highest skill in predicting FD prior to or at the time of onset in soil moisture, while both EDDI and ESI show significantly lower skill. The results highlight that the lack of precipitation is the main contributor to FDs in climate models, with E0 playing a secondary role. Significance Statement: This study is the first to assess the representation of rapidly developing drought, commonly referred to as flash drought, in global coupled climate models. This study elucidates how these models simulate flash drought and how they represent flash drought processes to allow for assessment in a changing climate. The work is also the first to compare the skill of drought indices based on precipitation and evaporative demand E0 for flash drought early detection on a global scale. We show that precipitation deficits are the main contributor to flash drought in climate models, with E0 playing a secondary role. However, an overestimation of E0 in some models causes significant intermodel disagreement, reflecting differences in the representation of land–atmosphere interactions. [ABSTRACT FROM AUTHOR]

To assess the impact of four-dimensional variational (4D-Var) data assimilation on the performance of a land--atmosphere coupled model, the satellite precipitation of the Integrated Multisatellite Retrievals for Global Precipitation Measurement (IMERG) was assimilated into the Weather Research Forecast (WRF) Model, and the WRF was coupled to the hydrological model TOPX. Precipitation and evaporation were both investigated as connecting elements in the coupled model WRF--TOPX. Differing in whether the 4D-Var data assimilation and evaporation were applied, one control experiment and four experiments were performed to simulate a historical flood event that happened in the Wangjiaba watershed in eastern China. The key hydrological variables of precipitation, potential evaporation, soil moisture, and discharge in the studied flood process were evaluated. The results showed that 1) the 4D-Var data assimilation with the IMERG could reduce both the overestimations of the WRF-predicted precipitation and potential evaporation; 2) the applied 4D-Var data assimilation could improve considerably the accuracy of the soil moisture and discharges from the coupled model WRF--TOPX; and 3) evaporation was also an important factor to influence the net precipitation to affect the performance of the coupled land--atmosphere model. With the two connecting elements of precipitation and evaporation, the 4D-Var assimilation based on IMERG could improve the Nash--Sutcliffe coefficient of the coupled model WRF--TOPX from 0.483 to 0.521 at the hourly scale. These investigations can provide important implications for the land--atmosphere coupling with both the precipitation and evaporation and using the 4D-Var data assimilation with IMERG for flood simulation at a large scale. [ABSTRACT FROM AUTHOR]

Evaporation is a principal factor in the hydrological cycle and energy exchange; however, estimations of evaporation include large uncertainties. In this study, a modified estimation of evaporation based on empirical linearly simplified Penman evaporation (PES) is proposed, soil moisture and precipitation are used to correct the land surface evaporation estimation, and the temporal and spatial characteristics of the corrected evaporation (CE) are investigated globally. The results show that CE is strong at low latitudes and weak at high latitudes. CE has obvious seasonal variation, ranging from 0.2 to 4.0 mm day−1; CE is prominent in summer but feeble in winter. Compared to PES, CE is generally weaker in most regions, especially in arid regions, with differences of more than 9 mm day−1. CE agrees well with evaporation derived from FLUXNET-Model Tree Ensemble (FLUXNET-MTE), MERRA, and GLDAS. In general, the root-mean-square error (RMSE) between annual CE and FLUXNET-MTE is less than 0.2 mm day−1, and CE is about 5%–10% less than the evaporation of FLUXNET-MTE. In the arid regions, the maximum CE almost occurs in the month with the strongest precipitation; in the tropical regions, soil moisture enhances CE only when precipitation is less. In the context of global temperature rise, PES always shows an apparent increasing trend due to the water supply is not considered; however, CE decreases in western Asia, the western United States, the Amazon basin, and Central Africa, but weakly increases in the other study regions from 1984 to 2013. This study provides a method for estimating evaporation considering more restrictive factors on evaporation. [ABSTRACT FROM AUTHOR]

Surface heat fluxes are vital to hydrological and environmental studies, but mapping them accurately over a large area remains a problem. In this study, brightness temperature (TB) observations or soil moisture retrievals from the NASA Soil Moisture Active Passive (SMAP) mission and land surface temperature (LST) product from the Geostationary Operational Environmental Satellite (GOES) are assimilated together into a coupled water and heat transfer model to improve surface heat flux estimates. A particle filter is used to assimilate SMAP data, while a particle smoothing method is adopted to assimilate GOES LST time series, correcting for both systematic biases via parameter updating and for short-term error via state updating. One experiment assimilates SMAP TB at horizontal polarization and GOES LST, a second experiment assimilates SMAP TB at vertical polarization and GOES LST, and a third experiment assimilates SMAP soil moisture retrievals along with GOES LST. The aim is to examine if the assimilation of physically consistent TB and LST observations could yield improved surface heat flux estimates. It is demonstrated that all three assimilation experiments improved flux estimates compared to a no-assimilation case. Assimilating TB data tends to produce smaller bias in soil moisture estimates compared to assimilating soil moisture retrievals, but the estimates are influenced by the respective bias correction approaches. Despite the differences in soil moisture estimates, the flux estimates from different assimilation experiments are in general very similar. [ABSTRACT FROM AUTHOR]

The role of shallow unconfined aquifers in supplying water for evapotranspiration (i.e., groundwater evaporation) is investigated in this paper. Recent results from regional land surface modeling have indicated that in shallow water table areas, a large portion of evapotranspiration comes directly from aquifers. However, little field evidence at the regional scale has been reported to support this finding. Using a comprehensive 19-yr (1984–2002) monthly hydrological dataset on soil moisture, water table depth, and streamflow in Illinois, regional recharge to and evaporation from groundwater are estimated by using soil water balance computation. The 19-yr mean groundwater recharge is estimated to be 244 mm yr−1(25% of precipitation), with uncertainty ranging from 202 to 278 mm yr−1. During the summer, the upward capillary flux from the shallow aquifer helps to maintain a high rate of evapotranspiration. Groundwater evaporation (negative groundwater recharge) occurs during the period of July–September, with a total of 31.4 mm (10% of evapotranspiration). Analysis of the relative soil saturation at 11 depths from 0 to 2 m deep supports the dominance of groundwater evaporation across the water table in dry periods. The zero-flux plane separating the recharge zone from the evapotranspiration zone propagates downward from about 70- to 110-cm depth during summer, reflecting the water supply from progressively lower layers for evapotranspiration. Despite its small magnitude, neglecting regional groundwater evaporation in shallow groundwater areas would result in underestimated root-zone soil moisture and hence evapotranspiration by as large as 20% in the dry summer seasons.

While vapor condensation in arid and semiarid areas has garnered much attention, such information is scarce for humid crop production areas such as rice fields. In a water-saving irrigation (WSI) rice field, high-precision weighed microlysimeters allowed the direct and independent quantification of condensation over plants (Cc) and soil (Cs) through mass balance calculations. The occurrence frequency and rate of Cc generally exceeded that of Cs. Predominantly occurring between sunset and sunrise, particularly between 0400 and 0500 local time, Cc showed an overall maximum rate of 0.096 mm h−1. In contrast, Cs was highest between 0100 and 1100 local time and showed an overall maximum rate of 0.044 mm h−1. The occurrence of Cc, unlike that of Cs, required a surface temperature lower than the ambient temperature or dewpoint. Of 65 rain-free days, Cc and Cs occurred on 60 and 33 days, respectively. Seasonal Cc, Cs, and Cc + Cs were estimated as 32.3, 3.1, and 35.4 mm, respectively, and their contributions to seasonal rice transpiration T, evaporation E, and evapotranspiration (ET) were 9.5%, 1.6%, and 6.7%, respectively. The seasonal Cc + Cs was similar in magnitude to a routine irrigation quota and accounted for 10.8% of rainfall and 14.4% of irrigation in the WSI rice field. Therefore, vapor condensation in rice fields in a subtropical monsoon climate is an important component of the hydrological cycle and cannot be ignored when tabulating the field water balance, calculating field water consumption, or in irrigation scheduling. [ABSTRACT FROM AUTHOR]

Precipitation values estimated by radar are assumed to be the amount of precipitation that occurred at the surface, yet this notion is inaccurate. Numerous atmospheric and microphysical processes can alter the precipitation rate between the radar beam elevation and the surface. One such process is evaporation. This study determines the applicability of integrating an evaporation correction scheme for real-time radar-derived mosaicked precipitation rates to reduce quantitative precipitation estimate (QPE) overestimation and to reduce the coverage of false surface precipitation. An evaporation technique previously developed for largescale numerical modeling is applied to Multi-Radar Multi-Sensor (MRMS) precipitation rates through the use of 2D and 3D numerical weather prediction (NWP) atmospheric parameters as well as basic radar properties. Hourly accumulated QPE with evaporation adjustment compared against gauge observations saw an average reduction of the overestimation bias by 57%-76% for rain events and 42%-49% for primarily snow events. The removal of false surface precipitation also reduced the number of hourly gauge observations that were considered as "false zero" observations by 52.1% for rain and 38.2% for snow. Optimum computational efficiency was achieved through the use of simplified equations and hourly 10-km horizontal resolution NWP data. The run time for the evaporation correction algorithm is 6-7 s. [ABSTRACT FROM AUTHOR]

Atmospheric evaporative demand plays a pivotal role in global water and energy budgets, and its change is very important for drought monitoring, irrigation scheduling, and water resource management under a changing environment. Here, future changes of pan evaporation Epan, a measurable indicator for atmospheric evaporative demand, are first projected and attributed over China through a physically based approach, namely, the PenPan model, forced with outputs from 12 state-of-the-art climate models from phase 5 of the Coupled Model Intercomparison Project. An equidistant quantile mapping method was also used to correct the biases in GCMs outputs to reduce uncertainty in Epan projection. The results indicated that Epan would increase during the periods 2021-50 and 2071-2100 relative to the baseline period 1971-2000 under the representative concentration pathway (RCP) 4.5 and 8.5 scenarios, which can mainly be attributed to the projected increase in air temperature and vapor pressure deficit over China. The percentage increase of Epan is relatively larger in eastern China than in western China, which is due to the spatially inconsistent increases in air temperature, net radiation, wind speed, and vapor pressure deficit over China. The widely reported 'pan evaporation paradox' was not well reproduced for the period 1961-2000 in the climate models, before or after bias correction, suggesting discrepancy between observed and modeled trends. With that caveat, it was found that the pan evaporation has been projected to increase at a rate of 117-167 mm yr−1 K−1 (72-80 mm yr−1 K−1) over China using the multiple GCMs under the RCP 4.5 (RCP 8.5) scenario with increased greenhouse gases and the associated warming of the climate system. [ABSTRACT FROM AUTHOR]

Precipitation, soil moisture, and air temperature are the most commonly used climate variables to monitor drought; however, other climatic factors such as solar radiation, wind speed, and humidity can be important drivers in the depletion of soil moisture and evolution and persistence of drought. This work assesses the Evaporative Demand Drought Index (EDDI) at multiple time scales for several hydroclimates as the second part of a two-part study. EDDI and individual evaporative demand components were examined as they relate to the dynamic evolution of flash drought over the central United States, characterization of hydrologic drought over the western United States, and comparison to commonly used drought metrics of the U.S. Drought Monitor (USDM), Standardized Precipitation Index (SPI), Standardized Soil Moisture Index (SSI), and the evaporative stress index (ESI). Two main advantages of EDDI over other drought indices are that it is independent of precipitation (similar to ESI) and it can be decomposed to identify the role individual evaporative drivers have on drought onset and persistence. At short time scales, spatial distributions and time series results illustrate that EDDI often indicates drought onset well in advance of the USDM, SPI, and SSI. Results illustrate the benefits of physically based evaporative demand estimates and demonstrate EDDI's utility and effectiveness in an easy-to-implement agricultural early warning and long-term hydrologic drought-monitoring tool with potential applications in seasonal forecasting and fire-weather monitoring. [ABSTRACT FROM AUTHOR]

Many operational drought indices focus primarily on precipitation and temperature when depicting hydroclimatic anomalies, and this perspective can be augmented by analyses and products that reflect the evaporative dynamics of drought. The linkage between atmospheric evaporative demand E0 and actual evapotranspiration (ET) is leveraged in a new drought index based solely on E0-the Evaporative Demand Drought Index (EDDI). EDDI measures the signal of drought through the response of E0 to surface drying anomalies that result from two distinct land surface-atmosphere interactions: 1) a complementary relationship between E0 and ET that develops under moisture limitations at the land surface, leading to ET declining and increasing E0, as in sustained droughts, and 2) parallel ET and E0 increases arising from increased energy availability that lead to surface moisture limitations, as in flash droughts. To calculate EDDI from E0, a long-term, daily reanalysis of reference ET estimated from the American Society of Civil Engineers (ASCE) standardized reference ET equation using radiation and meteorological variables from the North American Land Data Assimilation System phase 2 (NLDAS-2) is used. EDDI is obtained by deriving empirical probabilities of aggregated E0 depths relative to their climatologic means across a user-specific time period and normalizing these probabilities. Positive EDDI values then indicate drier-than-normal conditions and the potential for drought. EDDI is a physically based, multiscalar drought index that that can serve as an indicator of both flash and sustained droughts, in some hydroclimates offering early warning relative to current operational drought indices. The performance of EDDI is assessed against other commonly used drought metrics across CONUS in Part II. [ABSTRACT FROM AUTHOR]

Reanalyses have the potential to provide meteorological information in areas where few or no traditional observation records are available. The terrestrial branch of the water cycle of CFSR, MERRA, ERA-Interim, and NARR is examined over Quebec, Canada, for the 1979-2008 time period. Precipitation, evaporation, runoff, and water balance are studied using observed precipitation and streamflows, according to three spatial scales: 1) the entire province of Quebec, 2) five regions derived from a climate classification, and 3) 11 river basins. The results reveal that MERRA provides a relatively closed water balance, while a significant residual was found for the other three reanalyses. MERRA and ERA-Interim seem to provide the most reliable precipitation over the province. On the other hand, precipitation from CFSR and NARR do not appear to be particularly reliable, especially over southern Quebec, as they almost systematically showed the highest and the lowest values, respectively. Moreover, the partitioning of precipitation into evaporation and runoff from MERRA and NARR does not agree with what was expected, particularly over southern, central, and eastern Quebec. Despite the weaknesses identified, the ability of reanalyses to reproduce the terrestrial water cycle of the recent past (i.e., 1979-2008) remains globally satisfactory. Nonetheless, their potential to provide reliable information must be validated by comparing reanalyses directly with weather stations, especially in remote areas. [ABSTRACT FROM AUTHOR]

Observations have shown that differences in surface energy fluxes over grasslands and forests are amplified during heat waves. The role of land-atmosphere feedbacks in this process is still uncertain. In this study, a single-column model (SCM) is used to investigate the difference between forest and grassland in their energy response to heat waves. Three simulations for the period 2005-11 were carried out: a control run using vegetation characteristics for Cabauw (the Netherlands), a run where the vegetation is changed to 100% forest, and a run with 100% short grass as vegetation. A surface evaporation tendency equation is used to analyze the impact of the land-atmosphere feedbacks on evapotranspiration and sensible heat release under normal summer and heat wave conditions with excessive shortwave radiation. Land-atmosphere feedbacks modify the contrast in surface energy fluxes between forest and grass, particularly during heat wave conditions. The surface resistance feedback has the largest positive impact, while boundary layer feedbacks generally tend to reduce the contrast. Overall, forests give higher air temperatures and drier atmospheres during heat waves. In offline land surface model simulations, the difference between forest and grassland during heat waves cannot be diagnosed adequately owing to the absence of boundary layer feedbacks. [ABSTRACT FROM AUTHOR]

A quasi-isentropic, back-trajectory scheme is applied to output from the Modern-Era Retrospective Analysis for Research and Applications (MERRA) and a land-only replay with corrected precipitation to estimate surface evaporative sources of moisture supplying precipitation over every ice-free land location for the period 1979-2005. The evaporative source patterns for any location and time period are effectively two-dimensional probability distributions. As such, the evaporative sources for extreme situations like droughts or wet intervals can be compared to the corresponding climatological distributions using the method of relative entropy. Significant differences are found to be common and widespread for droughts, but not wet periods, when monthly data are examined. At pentad temporal resolution, which is more able to isolate floods and situations of atmospheric rivers, values of relative entropy over North America are typically 50%-400% larger than at monthly time scales. Significant differences suggest that moisture transport may be a key factor in precipitation extremes. Where evaporative sources do not change significantly, it implies other local causes may underlie the extreme events. [ABSTRACT FROM AUTHOR]

A novel method is presented to analytically resolve the terrestrial latent heat flux ( λ E) and conductances (boundary layer gB and surface gS) using net radiation ( RN), ground heat flux ( G), air temperature ( Ta), and relative humidity (RH). This method consists of set of equations where the two unknown internal state variables ( gB and gS) were expressed in terms of the known core variables, combining diffusion equations, the Penman-Monteith equation, the Priestley-Taylor equation, and Bouchet's complementary hypothesis. Estimated λ E is validated with the independent eddy covariance λ E observations over Soil Moisture Experiment 2002 (SMEX-02); the Global Energy and Water Cycle Experiment (GEWEX) Continental-Scale International Project (GCIP) selected sites from FLUXNET and tropics eddy flux, representing four climate zones (tropics, subtropics, temperate, and cold); and multiple biomes. The authors find a RMSE of 23.8-54.6 W m−2 for hourly λ E over SMEX-02 and GCIP and 23.8-29.0 W m−2 for monthly λ E over the FLUXNET and tropics. Observational and modeled evidence in the reduction in annual evaporation ( E) pattern on the order of 33% from 1999 to 2006 was found in central Amazonia. Retrieved gS responded to vapor pressure deficit, measured λE, and gross photosynthesis in a theoretically robust behavior. However, the current scheme [Penman-Monteith-Bouchet-Lhomme (PMBL)] showed some overestimation of λ E in limited soil moisture regimes. PMBL provides similar results when compared with another Priestley-Taylor-based λ E estimation approach [Priestley-Taylor-Jet Propulsion Laboratory (PT-JPL)] but with the advantage of having the conductances analytically recovered. [ABSTRACT FROM AUTHOR]

To understand the sources of temporal and spatial variability of atmospheric evaporative demand across the conterminous United States (CONUS), a mean-value, second-moment uncertainty analysis is applied to a spatially distributed dataset of daily synthetic pan evaporation for 1980-2009. This evaporative demand measure is from the 'PenPan' model, which is a combination equation calibrated to mimic observations from U.S. class-A evaporation pans and here driven by six North American Land Data Assimilation System variables: temperature, specific humidity, station pressure, wind speed, and downwelling shortwave and longwave radiation. The variability of evaporative demand is decomposed across various time scales into contributions from these drivers. Contrary to popular expectation and much hydrologic practice, temperature is not always the most significant driver of temporal variability in evaporative demand, particularly at subannual time scales. Instead, depending on the season, one of four drivers (temperature, specific humidity, downwelling shortwave radiation, and wind speed) dominates across different regions of CONUS. Temperature generally dominates in the northern continental interior. This analysis assists land surface modelers in balancing parameter parsimony and physical representativeness. Patterns of dominant drivers are shown to cycle seasonally, with clear implications for modeling evaporative demand in operational hydrology or as a metric of climate change and variability. Depending on the region and season, temperature, specific humidity, downwelling shortwave radiation, and wind speed must together be examined, with downwelling longwave radiation as a secondary input. If any variable may be ignored, it is atmospheric pressure. Parameterizations of evaporative demand based solely on temperature should be avoided at all time scales. [ABSTRACT FROM AUTHOR]

Satellite and gridded meteorological data can be used to estimate evaporation ( E) from land surfaces using simple diagnostic models. Two satellite datasets indicate a positive trend (first time derivative) in global available energy from 1983 to 2006, suggesting that positive trends in evaporation may occur in 'wet' regions where energy supply limits evaporation. However, decadal trends in evaporation estimated from water balances of 110 wet catchments do not match trends in evaporation estimated using three alternative methods: 1) , a model-tree ensemble approach that uses statistical relationships between E measured across the global network of flux stations, meteorological drivers, and remotely sensed fraction of absorbed photosynthetically active radiation; 2) , a Budyko-style hydrometeorological model; and 3) , the Penman-Monteith energy-balance equation coupled with a simple biophysical model for surface conductance. Key model inputs for the estimation of and are remotely sensed radiation and gridded meteorological fields and it is concluded that these data are, as yet, not sufficiently accurate to explain trends in E for wet regions. This provides a significant challenge for satellite-based energy-balance methods. Trends in for 87 'dry' catchments are strongly correlated to trends in precipitation ( R2 == 0.85). These trends were best captured by , which explicitly includes precipitation and available energy as model inputs. [ABSTRACT FROM AUTHOR]

The components of the land surface energy balance respond to periodic incoming radiation forcing with different amplitude and phase characteristics. Evaporative fraction (EF), the ratio of latent heat to available energy at the land surface, supposedly isolates surface control (soil moisture and vegetation) from radiation and turbulent factors. EF is thus supposed to be a diagnostic of the surface energy balance that is constant or self-preserved during daytime. If this holds, EF can be an effective way to estimate surface characteristics from temperature and energy flux measurements. Evidence for EF diurnal self-preservation is based on limited-duration field measurements. The daytime EF self-preservation using both long-term measurements and a model of the soil-vegetation-atmosphere continuum is reexamined here. It is demonstrated that EF is rarely constant and that its temporal power spectrum is wide; thus emphasizing the role of all diurnal frequencies associated with reduced predictability in its daylight response. Oppositely, surface turbulent heat fluxes are characterized by a strong response to the principal daily frequencies (daily and semi-daily) of the solar radiative forcing. It is shown that the phase lag and bias between the turbulent flux components of the surface energy balance are key to the shape of the daytime EF. Therefore, an understanding of the physical factors that affect the phase lag and bias in the response of the components of the surface energy balance to periodic radiative forcing is needed. A linearized model of the soil-vegetation-atmosphere continuum is used that can be solved in terms of harmonics to explore the physical factors that determine the phase characteristics. The dependency of these phase and offsets on environmental parameters-friction velocity, water availability, solar radiation intensity, relative humidity, and boundary layer entrainment-is then analyzed using the model that solves the dynamics of subsurface and atmospheric boundary layer temperatures and heat fluxes in a continuum. Additionally, the asymptotical diurnal lower limit of EF is derived as a function of these surface parameters and shown to be an important indicator of the self-preservation value when the conditions (also identified) for such behavior are present. [ABSTRACT FROM AUTHOR]

River basin managers concerned with maintaining water supplies and mitigating flood risk in the face of climate change are taking outputs from climate models and using them in hydrological models for assessment purposes. While precipitation is the main output used, evaporation is attracting increasing attention because of its significance to the water balance of river basins. Climate models provide estimates of actual evaporation that are consistent with their simplified land surface schemes but do not naturally provide the estimates of potential evaporation (PE) commonly required as input to hydrological models. There are clear advantages in using PE estimates controlled by atmospheric forcings when using stand-alone hydrological models with integral soil-moisture accounting schemes. The atmosphere-land decoupling approximation that PE provides can prove to be of further benefit if it is possible to account for the effect of different, or changing, land cover on PE outside of the climate model. The methods explored here estimate Penman-Monteith PE from vegetated surfaces using outputs from climate models that have an embedded land surface scheme. The land surface scheme enables an examination of the dependence of canopy stomatal resistance on atmospheric composition, and the sensitivity of PE estimates to the choice of canopy resistance values under current and changing climates is demonstrated. The conclusions have practical value for climate change impact studies relating to flood, drought, and water management applications. [ABSTRACT FROM AUTHOR]

Numerous studies have attempted to address the land–precipitation coupling, but scientists’ understanding remains limited and discrepancies still exist from different studies. A new parameter Γ is proposed here to estimate the land–precipitation coupling strength based on the ratio of the covariance between monthly or seasonal precipitation and evaporation anomalies (from their climatological means) over the variance of precipitation anomalies. The Γ value is easy to compute and insensitive to the horizontal scales used; however, it does not provide causality. A relatively high Γ is a necessary—but not sufficient—condition for a relatively strong land–precipitation coupling. A computation of Γ values using two global reanalyses (ECMWF and NCEP), one regional reanalysis [North American Regional Reanalysis (NARR)], and observed precipitation along with Variable Infiltration Capacity (VIC)-derived evaporation data indicates that the land–precipitation coupling is stronger in summer and weaker in winter. The strongest coupling (i.e., hot spots) occurs over the western and central parts of North America, part of the Eurasia midlatitude, and Sahel in boreal summer and over most of Australia, Argentina, and South Africa in austral summer. The Community Climate System Model, version 3 (CCSM3) shows much higher Γ values, consistent with the strong coupling shown by its atmosphere–land coupled components in previous studies. Its overall spatial pattern of Γ values is not affected much over most regions by the doubling of CO2 in CCSM3. The Γ values from the Regional Atmospheric Modeling System (RAMS) are more realistic than those from CCSM3; however, they are still higher than those from observations over North America. [ABSTRACT FROM AUTHOR]