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Drylands, where the water supplies are scarce relative to the atmospheric moisture demands, occupy approximately half of the area of China. With global warming, the response of atmospheric water cycle is a crucial concern for sustainable development in China's drylands. This study investigates the characteristics of the water cycle in China's drylands during 1980–2019, as well as future projections estimated by the Community Earth System Model (CESM) during 2020–2100. The results show that the air temperature in China's drylands has increased significantly since 1980, especially after 2000, with greater warming in the warm season. Meanwhile, China generally tend to be drier from 1980 to 2019 as a whole, especially in the cold season. Both precipitation (P) and evapotranspiration (E) have increased, but the net effect is that drylands become drier (negative P-E) and wetlands become wetter (positive P-E), respectively. In the future, drylands are projected to become more humid due to increased precipitation, showing a pattern of "western wetter and eastern drier" during 2020–2100. These results could improve understanding of the water cycle and provide some guidance for adapting to climate change in drylands. [ABSTRACT FROM AUTHOR]

Precise estimation of reference evapotranspiration (ETo) is crucial for efficient management of water resources. However, the complex and nonlinear dependence of the ETo on several weather parameters makes its estimation challenging. In this study, artificial neural networks (ANNs) were used to simulate ETo at three diverse stations: Ludhiana, Bathinda, and Faridkot in the Malwa region of Punjab. Different input combinations of weather parameters, represented as (S1-S7) scenarios, were used to test the model against the standard FAO-56 Penman–Monteith (PM) method. The model was judged based on statistical parameters, such as r, R2, MSE, RMSE, NRMSE, and NSE. The results indicate that S1, with maximum number of parameters, performed the best with RMSE (0.154, 0.246, and 0.298) and NSE (0.9933, 0.9849 and 0.9709) values, followed by S2 (Tmax, Tmin, n, u2) in terms of RMSE (0.218, 0.316, and 0.307) and NSE (0.9877, 0.9751, and 0.9699) for Ludhiana, Bathinda, and Faridkot stations, respectively. Scenario S6, consisting of only air temperature and relative humidity, performed the worst among the rest of the scenarios. Moreover, the developed ANN models significantly outperformed conventional empirical models, even when similar input variables were used, demonstrating their superior performance. The ANN models at Ludhiana station performed the best in almost all the scenarios because of the consistent dataset. The inconsistent dataset with higher missing values resulted in comparatively lower performance of the ANN models for the Bathinda and Faridkot stations. The developed ANN model will aid in effective crop planning, irrigation, and water resource management, especially in areas where data availability is constrained. [ABSTRACT FROM AUTHOR]

We evaluated the performance of the Thornthwaite (ThW) method using two gridded climate datasets to estimate monthly average daily potential evapotranspiration (PET). The PET estimated from two gridded series were compared to PET and to reference evapotranspiration (ETo) determined, respectively, through the ThW and Penman-Monteith model parameterized on Food and Agriculture Organization–Irrigation and Drainage paper No 56 (PM-FAO56) using data from weather stations. The PET by ThM was based on monthly air temperature series (1961–2010) from two gridded datasets (Global Historical Climatology Network-GHCN and University of Delaware-UDel) and 21 weather stations of the National Institute of Meteorology (INMET) located in Southeastern Brazil. The ETo PM-FAO56 used monthly climate series (1961–2010) on sunshine duration, air temperature, relative humidity, and wind speed from weather stations of the INMET. The PET estimated using UDel gridded series was better overall performance than the GHCN series. Differences in altitude, latitude, and longitude were the main geographic factors determining the performance of the PET estimates using gridded climate series. Depending on the factors, some locations require bias correction, especially locations more than 10 km away from the grid point. The gridded datasets are an alternative for locations without climatic series data or with low-quality non-continuous data series. [ABSTRACT FROM AUTHOR]

This study estimates the trends in precipitable water vapor (PWV), atmospheric moisture budget (AMB), and the factors influencing them: air temperature, evapotranspiration (ET), convective available potential energy (CAPE), and vertical velocity (Omega) over the Indian subcontinent using ERA5 reanalysis data sets between 1980 and 2020. PWV is examined across three atmospheric layers (1000–850 hPa: lower layer; 850–500 hPa: middle layer; 500–300 hPa: upper layer), and the entire atmospheric column (EAC; 1000–300 hPa). The observed PWV trends exhibit variability within the EAC, ranging from −0.53 to 1.25 mm/decade across the study area, with the middle layer showing the most pronounced variation (–0.44 to 0.83 mm/decade), followed by the lower layer (0.10 to 0.45 mm/decade), and the upper layer (–0.02 to 0.23 mm/decade). These fluctuations in PWV are attributed to changes in air temperature, ET, CAPE, and Omega. This investigation, however, underscores the necessity of delving into the impacts of these influencing factors on PWV using finer resolution data, to enhance our comprehension of its spatial and temporal dynamics in the region. Furthermore, the annual AMB analysis reveals a declining trend in the study region. These findings collectively contribute to the understanding of regional water-energy cycles and the recent shifts in atmospheric dynamics. [ABSTRACT FROM AUTHOR]

Changes are projected for the boreal biome with complex and variable effects on forest vegetation including drought‐induced tree mortality and forest loss. With soil and atmospheric conditions governing drought intensity, specific drivers of trees water stress can be difficult to disentangle across temporal scales. We used wavelet analysis and causality detection to identify potential environmental controls (evapotranspiration, soil moisture, rainfall, vapor pressure deficit, air temperature and photosynthetically active radiation) on daily tree water deficit and on longer periods of tree dehydration in black spruce and tamarack. Daily tree water deficit was controlled by photosynthetically active radiation, vapor pressure deficit, and air temperature, causing greater stand evapotranspiration. Prolonged periods of tree water deficit (multi‐day) were regulated by photosynthetically active radiation and soil moisture. We provide empirical evidence that continued warming and drying will cause short‐term increases in black spruce and tamarack transpiration, but greater drought stress with reduced soil water availability. Plain Language Summary: This research explores how climate change could impact the water stress experienced by black spruce and tamarack trees in the western boreal forest of Canada. We focused on a key measure called "tree water deficit" to understand if the trees were under stress due to insufficient water. We examined how tree water deficit relates to environmental factors such as temperature, sunlight, and soil moisture. The findings revealed that, on a daily basis, factors like sunlight and temperature cause trees to release more water into the air. However, over longer periods (days to weeks), the amount of water in the soil becomes crucial, suggesting that trees might face water stress during dry spells. So, while trees could grow more on hotter, sunnier days, they could also experience water stress and reduced growth if the soil becomes too dry for an extended period. This study helps us grasp how various factors interact to influence tree water stress in the boreal forest, providing insights important for managing these ecosystems in a changing climate. Key Points: A novel approach to determine environmental controls of tree water deficit across time scales with wavelet analysis and Granger causalitySoil moisture emerges as a significant control of tree water deficit in boreal trees at longer scales (multi‐days)Daily productivity gains with warming will be mitigated by decreased soil water availability in longer periods of tree water deficit [ABSTRACT FROM AUTHOR]

Over the last 50 years, global air temperature has increased substantially especially over continents, causing higher rates of evaporative demand that can lead to an increase in drought occurrence and intensity worldwide. The Standardized Precipitation Index (SPI) is a drought index that solely uses precipitation, while the Standardized Precipitation Evapotranspiration Index (SPEI) uses the difference between precipitation and potential evapotranspiration and, therefore, incorporates the impacts of warming more directly. Here, we explore trends in SPI and SPEI, the relationship between SPI and SPEI, and how this relationship varies across different climate types. We find that a majority of the terrestrial surface has positive trends in SPI while most has negative SPEI from 1971 to 2022, a period of consistent global warming. Although the two indices show positive correlation with each other across the globe, we find decreasing correlation across all aridity types from the humid to the hyper-arid regions. The difference of correlation across two recent 26-year periods indicates that humid regions have consistent correlations through time while arid regions experience substantial interdecadal variation. Using a spatially weighted multiple linear regression, we find that SPI and SPEI trends have opposing relationships with temperature trends; specifically, it has a direct relationship with SPI trends and an inverse relationship with SPEI trends. In contrast, both vapor-pressure deficit and incoming solar radiation have an inverse relationship with SPI and a stronger inverse relationship with SPEI. Ongoing increases in temperature and vapor-pressure deficit are likely to cause further decoupling of the two indices worldwide. [ABSTRACT FROM AUTHOR]

Evapotranspiration is the key and predominant component of the water balance in wetlands. Direct evapotranspiration measurements are challenging in wetlands due to their remoteness and high surface water level. This article describes the actual (ETa and reference evapotranspiration (ET0) from a cultivated wet meadow located in the Biebrza National Park - the largest national park in north-east Poland, Central Europe. The data were sourced from a micrometeorological station equipped with an eddy covariance system to measure heat and vapour fluxes and such meteorological elements as radiation balance components, air temperature and humidity. The values of directly measured ETa were presented daily in the context of available energy and ET0. Daily sums of ETa ranged from below 0.2 mm in winter to 6.5 mm in summer. The share of daily sums of ETa in the ET0 usually ranged from 50 to 60%, with extreme values from 10 to 170%. Aside from giving more insight into Biebrza wetlands' functioning, the actual data produced in this study may be used instead of indirect methods, which were used the most in modelling wetlands areas. [ABSTRACT FROM AUTHOR]

This study aims (1) to study the trend and characteristics of average annual air temperature (Tann), annual precipitation (Prann), and annual evapotranspiration (PETann) in Thailand over the present period (1987–2021) and (2) to extract the climate pattern in form of a map using the New Thornthwaite Climate Classification method in Thailand considering the present period. The data were prepared by the Thai Meteorological Department. Data variability, the mean of the data calculation in time series, the homogeneity test of data, and abrupt changes were examined. The trends of each variable were calculated using the Mann–Kendal and Sen's slope test. The results indicated that the high Tann found in Bangkok gradually decreased in the next area. Tann data were heterogeneous with the abrupt change period, and increasing trends were found. Prann values were high in the west side of the southern area and the bottom area of the eastern area; in addition, low rainfall was found in the inner area of the land. Prann data were homogenous with no abrupt change period and slight changes in trends. PETann and %CV spatial distribution were determined for the same pattern of Tann. PETann data were heterogeneous with abrupt change periods and rising trends. The torrid thermal index determined based on the New Thornthwaite Climate Classification results indicated an overall torrid-type climate. A semi-arid climate pattern was found in the small area of the middle of Thailand, and then it shifted toward a moist-type pattern in the next area with an in precipitation. The most climate variability was found to be extreme with the power of temperature changes. [ABSTRACT FROM AUTHOR]

Advection is a prevailing meteorological phenomenon in the arid and semi‐arid environments that directly affects the crop and soil hydrology. It could have a great impact on the rate of standard crop evapotranspiration (ETc) in the irrigated areas. Therefore, it is required to take it into consideration while computing crop water requirement through the physically based meteorological procedures. The objectives of this study are (1) simple modification of the Penman–Monteith (PM) equation in calculation of the grass reference evapotranspiration (ETo) to implement the local advection, (2) comparing the single (Kc) and dual crop coefficient (Kcb) of two quinoa cultivars (Titicaca, and Q5) with and without advection correction and (3) presenting a simple model to calculate the advection factor using the maximum air temperature and mean relative humidity for the future crop growth modelling studies. Both Q5 and Titicaca showed unexpectedly very high ETc and potential transpiration (Tp) as 1568 mm and 1003 mm, and 1156 mm and 829 mm, respectively, due to occurrence of regional advection, whereas very high unrealistic Kc and Kcb values for Q5 revealed the impact of strong local advection and external energy. Therefore, we modified ETo to implement the advection effect through introducing the advection factor, ETc/Rn (Rn is the net radiation), as a function of maximum air temperature and mean relative air humidity during the growing season [ETc/Rn = exp (0.025Tmax – 0.015RHavg)] which resulted in higher ETo values, and consequently lower and more realistic Kc and Kcb. As a result, modified maximum Kc values of 1.14 and 1.55 and the modified maximum Kcb of 0.94 and 1.0 were obtained for Titicaca and Q5 cultivars, respectively. This procedure leads to a more accurate site‐specific Kc estimation and indirectly reliable ETc estimation as a function of advection factor and its multiplication by the non‐modified ETo. Furthermore, for direct estimation of ETc through the PM equation, the coefficients of aerodynamic and canopy resistance components of PM equation were modified for estimation of ETc by the non‐modified Rn, which resulted in accurate estimation of ETc. [ABSTRACT FROM AUTHOR]

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Due to limited direct measurements, regional or global terrestrial evapotranspiration (ET) is generally derived from a combination of meteorological and satellite observations. Although the inhomogeneity of the observed climate data has been widely reported, its impact on the calculated ET has not been adequately quantified. This study aimed to calculate ET using the modified Penman‐Monteith (MPM) model with raw and homogenized meteorological data. Additionally, we compared the calculated ET with those estimates from variable methods (water balance, satellite‐based, and reanalysis) in China and its six major river basins from 1982 to 2020. During the overlapping period of 1997–2018, ET calculated from raw input data decreased slightly at −0.39 mm yr−2 (p = 0.64) in China, whereas homogenized ET showed a significant increasing trend of 0.93 mm yr−2 (p = 0.02), with a better agreement with water balance ET (1.93 mm yr−2, p = 0). Global Land Evaporation Amsterdam Model (GLEAM) and Modern‐Era Retrospective Analysis for Research and Applications, version 2 (MERRA2) could reproduce the increasing trends with 2.08 mm yr−2 (p = 0) and 2.59 mm yr−2 (p = 0). The intercomparison of input variables (solar radiation, relative humidity, wind speed, precipitation, and air temperature) among ET products revealed substantial differences, which can account for the discrepancies in ET estimates. Homogenized ET, GLEAM and MERRA2 exhibited significant increasing trends in China and most river basins from 1982 to 2020. Our findings underscore the importance of utilizing homogenized input data for more accurate ET estimation. Plain Language Summary: Regional or global terrestrial evapotranspiration (ET) is generally derived from a combination of meteorological and satellite observations. Previous studies have highlighted inhomogeneity issues in meteorological observations in China, which can introduce uncertainty to the ET estimated. However, the uncertainty of ET estimates has not been quantified. In this study, we recalculated ET in China using an energy partition model with raw and homogenized meteorological inputs from 1982 to 2020. We also compared ET estimates obtained from different methods (water balance, satellite‐based, and reanalysis) to analyze trends in China and its major river basins over the same period. The study revealed that inhomogeneity in the input data distorted the calculated trends of ET. Key Points: Calculated China's ET using raw and homogenized data in the modified Penman‐Monteith modelImproved ET trend with homogenized data, aligning better with water balance ET over ChinaHomogenized ET exhibits a significant increasing trend of 0.90 mm yr−2 (p = 0) from 1982 to 2020 across China [ABSTRACT FROM AUTHOR]

Altered evaporative demand is a global phenomenon observed over recent decades, however, such change has not been attributed explicitly to specific meteorological drivers, hampering consensus on what has caused such change. Here we investigate exactly how much individual drivers have contributed to long‐term grass‐reference evapotranspiration (ETo) change within conterminous United States (CONUS), with an emphasis on agricultural croplands. Using scenarios that constrain individual drivers i.e., air temperatures (T), relative humidity (RH), solar radiation (Rs), and wind speeds (U2) to their climatologies, we determined their relative contribution toward ETo change at monthly and annual scales. Annual ETo increased by 111 mm, or >2 standard deviations (SD) relative to the 1981–2000 baseline, accompanied by strong increase in Rs (2.7 SD), U2 (2.5 SD), T (1.1 SD), and decreased RH (2.3 SD) in regions that account for one‐third of calories produced in the U.S. Annual ETo increase was attributed primarily to T (relative contribution of 36%), followed by Rs (29%), U2 (18%), and RH (17%) with significant spatial and seasonal variability. During agriculturally critical summer months, Rs was the dominant driver with a 40%–50% relative contribution, and other three drivers were roughly equally important. These findings address demand‐side of agricultural water use and imply long‐term change in crop functions and performance, water security, and planning across aridity gradients. [ABSTRACT FROM AUTHOR]

Reference evapotranspiration (ET0) is a key variable for understanding the water cycle and is essential for managing water resources in arid and semi-arid regions. Employing the high-resolution CRU TS version 4.05 gridded datasets and utilizing a substantial network of 48 meteorological gauging stations, this analysis spans a temporal scope from 1901 to 2018, offering valuable insights into ET0 trends. The results of the Mann-Kendall test show that the majority of stations exhibit a significant upward trend in ET0, with the strongest trends observed in June (Z = 5.58), July (Z = 6.21), and August (Z = 4.42). The magnitude of the trend is found to be faster in the eastern region, with the maximum values observed in May and July. The upward trend in ET0 is significant throughout all seasons and is most notable in summer at southern stations, while in winter, the trend is more prominent at northeastern stations. Annual ET0 trends are highest in the northeastern parts of the South, like Biskra (Z = 8.65), El Oued, and M'sila (Z = 8.54). However, the lowest was observed in Adrar, Tamanrasset, and Ghardaia provinces. Factors such as changes in air temperature, net radiation, wind speed, relative humidity, and land use may influence ET0 levels. These findings provide insights into the changes in water requirements for plants and soil surface evaporation over time, which can have implications for water resource management in Algeria. [ABSTRACT FROM AUTHOR]

In agricultural and hydrological applications, daily reference evapotranspiration (ET) is a key parameter. Based on one, two, and three-day antecedent meteorological parameters including average air temperature (T), sunshine hours (S), average relative humidity (RH), average wind speed (W), and reference evapotranspiration (ET), this study develops a new model framework for estimating daily ET magnitudes. The Long Short-Term Memory (LSTM) model was combined with the Feedforward Neural Network (FFNN) model in order to develop the hybrid approach, which was used to estimate daily ET values at two stations, Babolsar and Bandar Anzali, Iran, between 1990 and 2022. Additionally, 70% of the data in the present study were used for training purposes and 30% for testing purposes. Based on the statistical metrics, the proposed LSTM-FFNN model was benchmarked against the standalone LSTM model. Results from the comparison at Babolsar station indicated that the LSTM-FFNN model performed better than all scenarios with an error of approximately 1 millimeter per day in scenarios 12, 15, and 16. According to the standalone LSTM model, scenarios 5, 8, 11, 15, and 16 had a 1.57 mm/day error rate, and likewise, for the Bandar Anzali station, the combined LSTM-FFNN model performed the best in scenarios 14 and 15 with the lowest error rates (RMSE=0.96 mm/day), while the standalone LSTM model performed better in scenarios 15 and 16. It was found, however, that the proposed LSTM-FFNN model outperformed the standalone LSTM model at both sites. These results suggest that the proposed LSTM-FFNN model is capable of accurately estimating daily ET magnitudes, which may assist in the optimal management of water resources within agriculture. [ABSTRACT FROM AUTHOR]

Evapotranspiration is an important part of the water cycle and influences, for example, water management and agricultural production. The article presents temporal and spatial changes in reference evapotranspiration (ETo) in the growing season (April–September) against the background of climatic conditions in Poland in the years 1966–2020. ETo was calculated using the Penman–Monteith method using data from 37 meteorological stations in the network of the Institute of Meteorology and Water Management‐National Research Institute. For the growing season of April–September, the average sum of ETo for Poland was 529 mm. In terms of spatial distribution, the values were lowest in northern Poland (Kołobrzeg, 480 mm; Lębork, 488 mm) and highest in the central lowlands (Warsaw, 570 mm; Poznań, 566 mm). For individual months, the average sum of ETo ranged from 53 to 63 mm in April and September to 108–112 mm in June and July. In Poland, in the years 1966–2020, ETo showed a statistically significant upward trend of 16.4 mm/10 year. This is the result of, inter alia, statistically significant increases in sunshine duration and air temperature and a decrease in relative humidity (respectively: 62 h/10 year, 0.40°C/10 year and −1%/10 year) during the growing season in Poland. Within the multiyear study period, the maximum ETo values occurred in 2018, reaching values of >700 mm. At that time, Poland was under the influence of very intense anticyclonic circulation. This is confirmed by the relationship between ETo and the anticyclonic circulation index for central Poland, which is statistically significant for the 55 study years. [ABSTRACT FROM AUTHOR]

The skill of the atmospheric reanalysis ERA5 from the European Centre for Medium-Range Weather Forecasts (ECMWF) at simulating upper atmospheric temperature and relative humidity is assessed by using five years of In-service Aircraft for a Global Observing System (IAGOS) observations. IAGOS flight trajectories are used to extract co-located meteorological conditions – temperature, relative humidity, and wind speed – and are compared with the IAGOS measurements. This assess ment is particularly relevant to the study of contrail formation, so focuses on the highly frequented air space that spans the Eastern United States over the North Atlantic and to central Europe. The comparison is performed in terms of mean, median, probability density functions, and a confusion matrix. For temperature a good agreement is identified with a maximum bias of − 0.4 K at the 200 hPa level. Larger biases are found for relative humidity with up to − 5.5 % at the 250 hPa level. To remove the systematic biases, which mostly tend towards too dry and cold, a bias correction method, based on a multivariate quan tile technique, is proposed and applied. After the correction the bias in temperature is reduced to below 0.1 K and in relative humidity to below − 1.5 %. To estimate the representation of contrail occurrence in ERA5, data points from IAGOS as well as corrected and uncorrected data points from ERA5 of temperature and relative humidity are flagged for contrail formation using the Schmidt-Appleman–criterion. In the IAGOS data set 39.2 and 16.9 % of the samples represent conditions for non-persistent contrails and persistent contrails, respectively. The corresponding numbers for original ERA5 analyses are 40.8 and 17.5 %, respectively, indicating good agreement overall. Applying a proposed quantile mapping correction method and removing the biases in temperature and relative humidity has only a small effect on the distributions but leads to an overestima tion of non-persistent contrail occurrence (44.0 %) and underestimation of persistent contrails (16.8 %). Differences in contrail occurrence that remain after the bias correction are traced back to the underling biases in temperature and relative humidity, indicating that ERA5 is either too dry and warm or cold and moist with largest differences at 250 hPa and decreasing with increasing altitude. [ABSTRACT FROM AUTHOR]

We used monthly climatological datasets from the NOAA US Climate Divisional Database to detect long-term trends (1951–2021) in the nine climate divisions of Oklahoma, USA. We applied Hargreaves-Samani method to calculate reference evapotranspiration (ETo) and used 12-month standardized precipitation index to characterize meteorological droughts. Modified Mann-Kendall and Sen's slope non-parametric trend tests were performed to identify significant (p < 0.05) positive and negative trends in maximum, average, and minimum air temperature (Tmax, Tavg, Tmin, respectively), precipitation (P), and ETo on annual and seasonal time scales. Innovative trend analysis and least square regression were used to further support the results. Statistically significant positive trends were observed in annual Tmin in all climate divisions. Statistically significant increasing trends were also observed in Tmin and Tavg on a seasonal scale across different climate divisions whereas significant decreasing trends were observed in summer Tmax. Winter P showed statistically significant increasing trends across Oklahoma. ETo only showed significant decreasing trends in the South Central climate division on an annual basis, and in central and eastern parts of the state during summers. The rate of change in temperature ranged from −0.010 to 0.020 °C/year. The rate of change in P ranged from −0.16 to 3.16 mm/year. while ETo ranged from −0.44 to 0.42 mm/year. These trends have critical implications for agricultural management to cope with potential long-term climate impacts on agricultural production, pests and invasive species, water resources, and soil moisture. [ABSTRACT FROM AUTHOR]

Reference evapotranspiration (ET0) is one important agrometeorological parameter for hydrological studies and climate risk zoning. ET0 calculation by the FAO Penman–Monteith method requires several input data. However, the availability of climate data has been a problem in many places around the world, so the study of scenarios with different combinations of climate data has become essential. The aim of this study was to evaluate the performance of artificial neural network (ANN), random forest (RF), support vector machine (SVM), and multiple linear regression (MLR) approaches to estimate monthly mean ET0 with different input data combinations and scenarios. Three scenarios were evaluated: at the state level, where all climatological stations were used (Scenario I–SI), and at the regional level, where the Minas Gerais state was divided according to the climatic classifications of Thornthwaite (Scenario II–SII) and Köppen (Scenario III–SIII). ANN and RF performed better in ET0 estimation among the models evaluated in the SI, SII, and SIII scenarios with the following data combinations: (i) latitude, longitude, altitude, month, mean, maximum and minimum temperature, and relative humidity and (ii) latitude, longitude, altitude, month, mean temperature, and relative humidity. SVM and MLR models are recommended for all scenarios in situations with limited climatic data where only air temperature and relative humidity data are available. The results and information presented in this study are important for the agricultural chain and water resources in Minas Gerais state. [ABSTRACT FROM AUTHOR]

In the conditions of rising air temperature and changing precipitation regimes in Central Europe and Slovakia over the last two decades, it is necessary to analyse drought, develop high-quality tools for drought detection, and understand its reactions to the emerging drought situation. One of the frequently used meteorological drought indices is the Standardized Precipitation and Evapotranspiration Index (SPEI). Several parameters can be modified in different steps of the calculation process of SPEI. In the article, we analyse the influence of selected adjustable parameters on the index results. Our research has shown that the choice of a statistical distribution (Log-logistic, Pearson III, or Generalized Extreme Value) for fitting water balance can affect the feasibility of calculating distribution parameters (and thus the index) from the provided input data, as well as lead to either underestimation or overestimation of the index. The normality test of SPEI can be used as a tool for the detection and elimination of highly skewed indices and cases when the indices were not well determined by the distribution function. This study demonstrated improved results when using the GEV distribution, despite the common use of the Log-logistic distribution. With the Pearson III distribution, unusually high or low SPEI values (|SPEI| > 6) were detected. [ABSTRACT FROM AUTHOR]

Reference evapotranspiration (ET0) is the first step in calculating crop irrigation demand, and numerous methods have been proposed to estimate this parameter. FAO-56 Penman–Monteith (PM) is the only standard method for defining and calculating ET0. However, it requires radiation, air temperature, atmospheric humidity, and wind speed data, limiting its application in regions where these data are unavailable; therefore, new alternatives are required. This study compared the accuracy of ET0 calculated with the Blaney–Criddle (BC) and Hargreaves–Samani (HS) methods versus PM using information from an automated weather station (AWS) and the NASA-POWER platform (NP) for different periods. The information collected corresponds to Module XII of the Lagunera Region Irrigation District 017, a semi-arid region in the North of Mexico. The HS method underestimated the reference evapotranspiration (ET0) by 5.5% compared to the PM method considering the total ET0 of the study period (26 February to 9 August 2021) and yielded the best fit in the different evaluation periods (daily, 5-day mean, and 5-day cumulative); the latter showed the best values of inferential parameters. The information about maximum and minimum temperatures from the NP platform was suitable for estimating ET0 using the HS equation. This data source is a suitable alternative, particularly in semi-arid regions with limited climatological data from weather stations. [ABSTRACT FROM AUTHOR]

Evapotranspiration (ET) plays an essential role in water balance and ecological environment changes. The Yangtze River Basin (YRB) is a typical monsoon climate zone. Most existing studies on the impact of climatic factors on annual ET have overlooked the seasonal effect. This study quantitatively analyzed the spatiotemporal variation characteristics of ET and its relationship with climatic factors at the annual and monthly scales in the YRB using high−spatial−resolution PML_V2 ET data from 2001 to 2020. Results showed that: (1) the spatiotemporal distribution of the regions with significant correlation between ET and individual climatic factors (i.e., air temperature, solar radiation and precipitation) in the YRB showed obvious cyclical changes in month, and the spatial change pattern is strongly related to the elevation; (2) the area proportion of the dominant climatic factors affecting annual ET in the study area was characterized by solar radiation > specific humidity > precipitation > air temperature > wind speed. However, monthly ET in most areas of the YRB was driven by solar radiation and air temperature, especially in summer and autumn, while ET in spring and winter was mainly driven by solar radiation, air temperature, and specific humidity. [ABSTRACT FROM AUTHOR]

This study presents an alternative approach for computing the Standardized Precipitation Evapotranspiration Index (SPEI). The proposed approach, called the Simplified Standardized Precipitation-Evapotranspiration Index (SSPEI), uses the Box-Cox transformation to normalize water balance anomalies (WBA) and subsequently convert the transformed series into the standard normal distribution (SND) using the Z-score formula. This approach is tested in 45 synoptic stations with varied climates across Iran. The stations' monthly total precipitation and average minimum and maximum air temperatures for 1971–2017 were used to compute the potential evapotranspiration and eventually WBA series needed for SPEI/SSPEI computation. According to the findings, the skewness of the Box-Cox transformed series of almost all the time scales and stations are close to zero. Therefore, the transformed WBA series can be confidentially used for computing SSPEI. The normality of the computed SSPEI series and the SPEI time series computed with the Log-logistics (LLG) and Generalized Extreme Value (GEV) distributions for the studied stations were examined using different normality assessment measures. The computed SSPEI for all the time scales and stations was found to be normally distributed, and the percentage of the SSPEI series with SND was comparable to those of the SPEILLG and SPEIGEV time series. However, SSPEI was superior to SPEILLG and SPEIGEV as it is simple in computation, requires no distribution fitting, and never results in null values due to computation failure, as is common with SPEI. [ABSTRACT FROM AUTHOR]

Significant changes in air temperature and precipitation occurred in Slovakia during the second half of the 20th century and mainly in the first two decades of the 21st century. These changes inuenced potential and actual evapotranspiration, soil moisture, and runoff in Slovakia. The article discusses changes and variability of evapotranspiration in the period 1951-2021 calculated by Budyko's method, which was modified by Tomlain for Slovakia, and due to climate change, the preparation of the evapotranspiration scenarios until the year 2100. The climatic indicator of irrigation, which shows the water's necessity to cover maximum evapotranspiration demands, was also evaluated from 1951 to 2021. We performed the model computation for 26 higher-quality stations in Slovakia. These stations are located in different climatic, especially humid conditions. The input data are air temperature and humidity, cloudiness, number of days with snow cover, and precipitation. The results of measurements and model calculations are presented in detail from stations Hurbanovo, Košice-airport, and Oravská Lesná. Changes in the normal of analysed phenomena between the 1951-1980 and 1991-2020 periods are shown in the table form for 20 selected stations because of limited space. The scenarios of potential evapotranspiration change until 2100, prepared by two regional circulation models (RCM) outputs, are presented at the end of the study. The results confirmed the growth of potential evapotranspiration in 1951-2021 and until 2100, while the actual evapotranspiration depends on soil moisture, which is mainly decreasing. The climatic irrigation index indicates the slightly increasing linear trend in Slovakia from 1951 to 2021. [ABSTRACT FROM AUTHOR]

This study investigated the actual evapotranspiration (AET) and potential evapotranspiration (PET) seasonality, trends, abrupt changes, and driving mechanisms with global sea surface temperature (SST) and atmospheric circulation patterns over Equatorial Africa (EQA) during 1980–2020. The spatiotemporal characteristics of mean ET were computed based on a 40-year average at annual and seasonal scales. The Mann-Kendall statistical test, the Sen slope test, and the Bayesian test were used to analyze trends and detect abrupt changes. The results showed that the mean annual PET (AET) for 1980–2020 was 110 (70) mm. Seasonal mean PET (AET) values were 112 (72) in summer, 110 (85) in autumn, 109 (84) in winter, and 110 (58) in spring. The MK test showed an increasing (decreasing) rate, and the Sen slope identified upward (downward) at a rate of 0.35 (0.05) mm yr−10. The PET and AET abrupt change points were observed to happen in 1995 and 2000. Both dry and wet regions showed observed weak (strong) correlation coefficient values of 0.3 (0.8) between PET/AET and climate factors, but significant spatiotemporal differences existed. Generally, air temperature, soil moisture, and relative humidity best explain ET dynamics rather than precipitation and wind speed. The regional atmospheric circulation patterns are directly linked to ET but vary significantly in space and time. From a policy perspective, these findings may have implications for future water resource management. [ABSTRACT FROM AUTHOR]

It is of great importance to study the changes in reference evapotranspiration (ET0) and the factors that influence it to ensure sustainable and efficient water resource utilization. Daily ET0 data calculated using the Penman–Monteith method from 37 meteorological stations located within Guangdong Province in the humid zone of southern China from 1960 to 2020 were analyzed. The trend analysis and Mann–Kendall test were used to analyze the time series changes in ET0 and major climatic factors (air temperature (T), relative humidity (RH), sunshine duration (SD), and wind speed (u2)) for over 61 years. Sensitivity and contribution analyses were used to evaluate the driving factors of ET0. The main findings of the study are as follows: (1) the trend in average annual ET0 time series in Guangdong slightly increased at a trend rate of 1.61 mm/10a over the past 61 years, with most stations experiencing an increase in ET0. During the same period, air temperature significantly increased, while RH and SD decreased; u2 also decreased. (2) Sensitivity analysis showed that ET0 was more sensitive to RH and T than SD and u2, with ET0 being most sensitive to RH in spring and winter and T in summer and autumn. (3) The contribution analysis showed that T was the dominant factor for ET0 variation in Guangdong, followed by SD. SD was found to be the dominant factor in ET0 changes in areas where the "evaporation paradox" occurred, as well as in spring and summer. The study concludes that the climate in Guangdong became warmer and drier over the past 61 years, and if the current global warming trend continues, it will lead to higher evapotranspiration and drought occurrence in the future. [ABSTRACT FROM AUTHOR]

This study aims to assess the accuracy of the reference evapotranspiration (ET0) estimated by CLDAS, ERA5 reanalysis products, and the quality of reanalysis weather variables required to calculate PM-ET0. For this purpose, the applicability of surface meteorological elements from the ERA5 reanalysis datasets provided by the European Centre for Medium-Range Weather Forecasts (ECMWF), and the second-generation China Meteorological Administration Land Data Assimilation System (CLDASV2.0) datasets are evaluated in China by comparison with local observations from 689 stations reported by the Chinese Meteorological Administration (CMA). Statistics including percent bias (PBias), coefficient of determination (R2), root mean square error (RMSE) and mean absolute error (MAE) are used to check the accuracy. The results show the highest correlation between reanalysis temperature and observations, with a mean R2 of 0.96, 0.90 for the CLDAS maximum and minimum air temperatures, and 0.87, 0.84 for ERA5. For the reanalysis of solar radiation (Rs) and relative humidity (RH), an overestimation trend is shown for Rs and an underestimation trend is shown for RH. For reanalysis of wind speed, a relatively low accuracy is shown. The accuracy of ET0 estimated by the two reanalysis products is acceptable in China, but the spatial and temporal consistency between the CLDAS estimates and site observations is higher, with a mean RMSE R2 of 0.91, 0.82 for CLDAS and 1.42, 0.70 for ERA5, respectively. Moreover, CLDAS reanalysis products are more effective in describing the boundary details of the study area. [ABSTRACT FROM AUTHOR]

Global climate change has emerged as a problem in recent years, and its effects will likely continue to increase in the future. Several scientific studies conducted in the Mediterranean region have demonstrated relatively stationary trends for annual precipitation and significant upward trends for mean annual temperature. These trends present several implications, especially in the Greek islands that serve as major summer tourist destinations where the population is already unable to meet their water demands. The aim of this study is to investigate both long- and short-term variations in temperature and precipitation on three Greek islands in the Mediterranean Sea (Mykonos, Naxos, and Kos). The temperature and rainfall trends, as well as their magnitudes at yearly, seasonal, and monthly time steps, were determined using the non-parametric Mann–Kendall trend test. The Standardized Precipitation Index (SPI) was employed to identify the drought periods. According to the results, precipitation slightly increased (almost stationary) in the three islands, although this rise was not statistically significant. All three islands experienced a sharp and statistically significant increase in their mean annual air temperatures. The region may experience drought episodes as a result of the high temperature increase, which would drastically reduce the amount of water, available for use due to the increased evapotranspiration. For the Mediterranean region, the necessity for a drought management strategy to stop or diminish the severity of drought episodes and their effects has grown into a matter of great concern. It is crucial to take measures and conduct relevant research in order to create the conditions for adaptation and mitigation of climate change consequences and the increased appearance of drought phenomena. [ABSTRACT FROM AUTHOR]

Accurate estimation of evapotranspiration (ET) can be affected by cloud change, while cloud‐induced bias errors in ET change remain poorly understood. Here we evaluated seven ET data sets from satellite microwave and optical models, atmospheric reanalysis and land surface models over East Asia. Results showed that although the data sets estimated ET changes overall well under mild cloud increase, all of them had a systematic overestimation (by 73.8%–159.8%) and deteriorated capability of capturing ET change under heavy cloud increase, especially over dense vegetation with large cloud cover. Overestimated incident solar radiation under clouds contributed to the deteriorated performances of ET. Cloud‐induced change in radiation and its errors played larger role in summer ET change over densely vegetated lands, while those in air temperature and relative humidity were dominant jointly over grass and barren lands. These results can serve as a reference for improving ET models and their forcing inputs under clouds. Plain Language Summary: The change of cloud cover affects terrestrial evapotranspiration (ET), which is a fundamental process in the interaction between land and the atmosphere. ET can be estimated from satellite observations, reanalysis data sets and land surface models. Knowing the cloud‐induced errors in the estimation of ET and its drivers can be very helpful for us to improve the ET modeling under the changing cloud conditions. In this study, we evaluated seven ET data sets and their forcing data from clear sky to cloudy sky conditions over East Asia. We quantified the importance of incident radiation, air temperature and relative humidity inputs in ET data sets under cloudy sky using a machine learning algorithm. Our findings revealed that all ET data sets were overestimated systematically under heavy cloud increase. Cloud‐induced change in radiation was more important over densely vegetated lands, while air temperature and relative humidity played larger roles over grass and barren lands. The result highlights the importance of cloud effects on ET estimations. Key Points: Seven evapotranspiration (ET) data sets from satellite microwave and optical models, reanalysis and land surface models were evaluated under cloud changeAll data sets overestimated the absolute ET values and cloud‐induced changes in ET under heavy cloud increase conditionsSummer ET change under clouds was dominated by radiation in the southern dense vegetation, but by temperature and humidity in grass lands [ABSTRACT FROM AUTHOR]

The climate of Southeastern Europe, where Bosnia and Herzegovina (BiH) and Croatia are located, is changing in line with the global trends. The spatial and seasonal distribution of precipitation is changing, while the temperatures increased 0.4-0.8 oC on average compared to 1961-1990, most notably during summer (1.0-1.2 oC). Depending on the different Representative Concentration Pathway (RCP) scenarios, the temperatures in this area are projected to further increase by 1.7-4.0 °C. In order to understand the effects of climate change on regional water resources, it is important to assess the impacts of these changes on the components of the water balance. The aim of this study was to determine and compare the severity of changes in annual water balance between two climate periods (1961-1990 and 1991-2020). The results indicate that climate change has a different temporal and spatial effect. All areas showed a positive trend in mean air temperature (0.29-0.36 oC per decade), reference evapotranspiration (5.96-32.14 mm per decade) while precipitation, total runoff, amount of snow and actual evapotranspiration vary depending on the location and time period. The key characteristic of the 1991-2020 period compared to 1961-1990 is the greater variation of all components of the water balance. [ABSTRACT FROM AUTHOR]

This article discusses the expected climate changes in Belarus as a result of two types of land transformation—rewetting degraded peatlands and increasing forest cover. The analysis was performed for the growing season (May–September) based on long-term earth remote sensing data, mesoscale modeling of atmospheric processes, and balance calculations using ERA5 reanalysis. It is shown that, as a result of waterlogging, the daytime temperature of the land surface for the southern part of Belarus (below the latitude of Minsk) decreases within 1.5°С due to increased evaporation and, for the northern part, 0.5 increased due to albedo regularity. At night, waterlogging, depending on the soil and climatic conditions, can cause both an increase and decrease a specific value of the land surface temperature (LST) within 1°C. Evapotranspiration due to waterlogging in the northern regions of Belarus decreases and it increases in the southern regions, which is associated with a significant ratio between evaporation and transpiration in these regions. During the afforestation of cropland, the daytime LST of Belarus decreases within 2°C and, at night, increase. The total evapotranspiration for the growing season due to the increase in forest cover reaches 100 mm, and potential (maximum possible) evaporation remains at the same level, which contributes to an increase in soil moisture at an increased amount of atmospheric precipitation. The above changes in the physical characteristics of the land surface as a result of reclamation cause a decrease in the surface air temperature in the reclamated region within 0.4°C and an increase in the amount of atmospheric precipitation within 2% of the climatic normals. At the same time, the maximum in the spatial distribution of secondary precipitation due to western transport shifts to the east relative to the reclaimed region. [ABSTRACT FROM AUTHOR]

Reference evapotranspiration (ETo) is a variable used to characterize the evaporative demand of the atmosphere and its impact on the water balance. During the last decades, significant ETo variabilities have been observed, especially at mid‐latitudes. These variabilities respond mainly to local variations in their physical drivers, such as solar radiation, vapour pressure deficit or wind speed. In this study, the annual and seasonal ETo estimates are generated using the Penman–Monteith method (FAO). Surface weather stations for the Argentine territory and reanalysis data for southern South America of the last four decades (1981–2020) are used. Contributions of both aerodynamic (ETaero) and radiative (ETrad) effects are evaluated to analyse their driving role. Significant positive ETo trends are observed from reanalysis data throughout Argentina, especially on the central east side of the Andes Mountain range with values up to 10 mm·year−1. Most of these ETo changes respond to positive trends in air temperature in the study area, while those in the central Andes also respond to negative trends in dew point temperatures. On the other hand, the increase in energy availability through positive trends in net surface radiation produced a slightly higher ETo in the northern regions of the country. Regional ETo values have shown to be more sensitive to variations in air temperature in the northeastern areas, although changes in humidity and solar radiation could also play a role. In a context of climate change, given that temperature and rainfall are expected to increase in the central and northeastern region of the country and decrease along the eastern side of the Andes Mountains in the coming decades, the characteristics observed over the 1981–2020 period are expected to intensify in the near future. [ABSTRACT FROM AUTHOR]

In this study, the possible climate change impacts on irrigated corn production in the lower Mississippi delta (LMD) region were analyzed. The observed daily maximum and minimum air temperature, wind speed, relative humidity (RH), and precipitation from 1960 to 2018 were used in the analysis. The length of the growing season, evapotranspiration (ET), and crop yield estimates from the precalibrated Root Zone Water Quality Model (RZWQM) were also used. Trend analyses were performed on growing-season averages for temperature, RH, and wind speed; growing-season totals for precipitation and ET; daily values of minimum and maximum temperature; and averages of RH and wind speed at critical corn growth stages. The last day of spring freezing (LDSF) and days with an average daily air temperature Ta of more than 35°C during corn silking were also included in the analysis. The trend analysis was performed using the modified Mann--Kendall test, Pettitt test, and Sen's slope at a significance level of p ≤ 0.05. The results from our study pointed out increases in minimum Ta, increases in the number of days with Ta exceeding 35°C during the corn silking stage, increases in RH and decreases in ET, advancement of the LDSF by 2 weeks, and 8% reductions in corn yield that could be attributed to changes in climate. If the observed trends in climate (climate variability and change) and yield reductions continue in the region, it could be challenging to grow the corn crop in the LMD profitably. [ABSTRACT FROM AUTHOR]

The Bydgoszcz region (Poland) is located in an area with a very high demand for supplementary irrigation during the vegetation period of plants. The projected global warming will bring a rise in the water needs of crops, and thus a further increase in irrigation needs. The goal of the study was an attempt to estimate the water needs of sweet cherry trees in 2021–2050 (forecast period) in the region of Bydgoszcz. The years 1981–2010 were adopted as the reference period. The water needs of sweet cherry trees were calculated on the basis of air temperature using the Treder method, in which water needs are equated with the potential evapotranspiration of a given fruit tree species. It was found that in the growing season of the forecast period, the relative diversity of sweet cherries' water needs was relatively small (7%). The highest variability of monthly water needs was in April, May, and June. The seasonal water needs amounted to 573 mm, with very high monthly water needs noted in July (139 mm) and August (134 mm). A significant trend of the time variability of water needs was calculated only in August. During this month, it is predicted that the water needs will rise by 5 mm in each subsequent decade. These results will be helpful in the design of sweet cherry irrigation treatments. [ABSTRACT FROM AUTHOR]

Carbon and water fluxes in ecosystems are tightly coupled by gas diffusion through stomata. However, carbon–water (C–W) relationships vary largely across time scales, vegetation types, and regions. Subtropical forests in China play an important role in the global carbon and water cycles, yet studies of C–W relationships in this region remain limited. Here, we investigated summer-time C–W relationships in this region at two subtropical sites: the evergreen broadleaved forest at Dinghushan (23.17° N, 112.53° E, 300 m) and the evergreen coniferous forest at Qianyanzhou (26.74° N, 115.06° W, 106 m), using the flux tower data from the FLUXNET2015. The C–W relationship was examined using two measures. The first was daily water use efficiency (WUE), which is the ratio of daily gross primary productivity (GPP) to evapotranspiration (ET). The second was the correlation coefficient (r) of hourly GPP and ET. Our analysis showed that the daily WUE in the two forests ranged over 4–14 mg CO2 per g H2O, higher in the coniferous forest than in the broadleaved forest. The mean values of r for hourly C–W coupling were similar at the two forests, being 0.5–0.6, which suggests asynchronous diurnal variations in GPP and ET. Both daily WUE and r were modulated by meteorological conditions. In general, high radiation, air temperature, and humidity can reduce WUE at both sites. For the broadleaved forest, the most influential factor on WUE was VPD, followed by radiation, while in the coniferous forest, VPD, air temperature, and radiation were almost equally important. For hourly C–W coupling, VPD plays a significant role. The drier the air is, the weaker the coupling in the two forests. The daily WUE and hourly C–W coupling reflect the C–W relationship from different perspectives. Both showed the strongest response to VPD but with different sensitivity. [ABSTRACT FROM AUTHOR]

Lakes are hot spots of carbon cycles in inland aquatic systems. As a vital factor, meteorology, including air temperature, precipitation, wind speed and evapotranspiration, is profoundly affecting or even regulating the wetland-air CO2 exchanges. Compared with some other similar lakes in China, the largest shallow grass-type Baiyangdian Lake (BYDL) acts as a vital CO2 sink on the North China Plain. The purpose of this study is to reveal the effects of meteorology on the process of CO2 flux variation. Based on the method of the eddy covariance, the daily average wetland-air CO2 flux at the BYDL over the monitoring period from April 2019 to November 2020, reached −0.63 μmol m−2 s−1, and the annual average reached −0.71 μmol m−2 s−1 from 12 April 2019 to 12 April 2020. The CO2 sink fluxes varied with the seasons and reached the maximum in summer. Temperature and evapotranspiration are two major driving factors, whose higher values can positively improve the wetland CO2 sinks. Precipitation generally coincides with the CO2 sinks, but the relatively larger summertime precipitation (0.39 m in 2020, compared with that of 0.17 m in 2019) inhibits the CO2 uptakes on longer timescales. A moderate wind speed in the range of 1.6~3.3 m s−1, promoted the CO2 sinks for the shallow grass-type lake. Compared with previous studies at the same or similar wetlands, consistent CO2 sink fluxes are found. Further in this study, the variation trends of CO2 sinks with the changing meteorological factors are revealed for the first time in this type of wetland. Once meteorology is determined under both the anthropogenic and climatic impacts, the evaluation and prediction of the lacustrine carbon cycling could be more precise. Generally, this study will serve as an important data point into the global understanding of lake carbon fluxes. [ABSTRACT FROM AUTHOR]

Reference crop evapotranspiration (ET0) is one of the most important hydroclimatic variables for the hydrologic and crop models, as well as the actual evapotranspiration in the irrigation schedule. The ET0 prediction a few months in advance can be beneficial to the decision-making on the long-term planning in the water management and irrigation communities. In this research, the monthly predictions of ET0 were realized over the Huaihe River basin using the model data of Beijing Climate Center second-Generation Climate Prediction System (BCC_CPSv2), and the surface meteorological observations at 172 stations during 1991 to 2020. The bilinear interpolation and quantile mapping were also selected to downscale and then correct the mean air temperature, net radiation, relative humidity, and wind speed of BCC_CPSv2. The obtained four variables were used to calculate the ET0 predictions using the Penman-Monteith equation. The correlation coefficient (r), Mean Bias Error (MBE), Root Mean Square Error (RMSE), and Mean Absolute Percentage Error (MAPE) were employed to evaluate the ET0 prediction performances of the model, and the four climatic variables before and after correction. Results showed that the mean air temperature, net radiation, and relative humidity from the model were significantly smaller than those from the observations before correction in each month with the RMSE of 1.84℃, 1.70 MJ/(m2 ·d), and 15.79%, respectively. The wind speed was also smaller during March to June, but larger in other months, with the RMSE of 1.39 m/s. Errors in the climatic variables led to the lower ET0 during February to June, and the larger ET0 in January, as well as in July to December, compared with the calculations. The RMSE of ET0 before correction was ranged from 0.11 to 1.70 mm/d for each month, among which was the highest in summer. The larger RMSE exceeding 0.50 mm/d occurred in eastern coastal areas in January and October, while the southwestern mountainous areas presented the higher RMSE exceeding 0.70 mm/d in April and July. The model skills on predicting climatic variables and ET0 were improved effectively by the quantile mapping. The RMSE of air temperature, net radiation, relative humidity, and wind speed decreased to 1.32℃, 0.74 MJ/(m2 ·d), 7.38%, and 0.53 m/s, respectively. Especially, the MAPE of wind speed and net radiation was decreased by more than 19%. The RMSE of ET0 after correction was ranged between 0.05 and 1.22 mm/d for each month, indicating the decrease in 80% of the months. The performances of the model were improved significantly for the eastern coastal areas in January, and the southwest mountainous areas in April, July and October, where the RMSE decreased by more than 0.30 mm/d. Before and after the correction, the net radiation and relative humidity were the primary factors for the ET0 prediction errors in summer half year and winter half year, respectively, due to the larger errors of the model and the higher sensitivity of ET0 to them. A better performance was achieved in the monthly ET0 prediction after the model correction with the error about 10.7%. The finding can provide a strong reference for the water resources management, irrigation schedule planning, and agricultural water demand decision-making. [ABSTRACT FROM AUTHOR]

Actual evapotranspiration (ET) is an essential variable in the hydrological process, linking carbon, water, and energy cycles. Global ET has significantly changed in the warming climate. Although the increasing vapor pressure deficit (VPD) enhances atmospheric water demand due to global warming, it remains unclear how the dynamics of ET are affected. In this study, using multiple datasets, we disentangled the relative contributions of precipitation, net radiation, air temperature (T1), VPD, and wind speed on the annual ET linear trend using an advanced separation method that considers the Budyko framework. We found that the precipitation variability dominantly controls global ET in the dry climates, while the net radiation has substantial control over ET in the tropical regions, and VPD impacts ET trends in the boreal mid-latitude climate. The critical role of VPD in controlling ET trends is particularly emphasized due to its influence in controlling the carbon–water–energy cycle. [ABSTRACT FROM AUTHOR]

Understanding the response of terrestrial ecosystem water use efficiency (WUE) to climate change is critical to accurately represent the carbon‐water cycle processes. However, how WUE dynamics are evolving under seasonal climate variations and biome‐specific characteristics remains still unclear. In this study, we integrated two state‐of‐the‐art retrieval algorithms to estimate gross primary productivity (GPP) and evapotranspiration (ET) from satellite MODIS records. Such metrics served as input to quantify ecosystem WUE, expressed as the ratio of GPP to ET, and explore its dynamics during the dry and wet season from 2001 to 2018 in China's key tropical to subtropical transitional zones, that is, Yunnan Province. Results show large spatial and seasonal variability in WUE over the observational period. During the dry season, the increasing trends in GPP and ET have led to contrasting WUE patterns in forest and non‐forest biomes, leading to positive and negative WUE trends, respectively. During the wet season, the declining trends in GPP occurring in combination with opposite trends in ET, have caused decreasing WUE consistently across all biomes except croplands, likely further modulated by human factors. The observed changes in WUE appear primarily driven by variations in air temperature (Ta) and vapor pressure deficit (VPD) during both dry and wet seasons. Overall, these results contribute to a better understanding of the carbon‐water interplay in tropical‐subtropical transitional zones and provide new insights to improve our capacity to predict the terrestrial ecosystem's response to climate change. Key Points: Terrestrial water use efficiencies (WUEs) show biome‐specific and season‐differential responses to climate changesEvergreen broadleaf forests have more stable water use efficiency across dry and wet seasons than the other biomesDry (wet) season WUE dominantly show positive (negative) trends, mainly caused by change in productivity (evapotranspiration) [ABSTRACT FROM AUTHOR]

Agriculturally used wet grassland sites (WGSs) with shallow water tables are considered to be sites with a special microclimate. Meteorological measurement series, examining the air temperature (Ta) and vapour pressure (VP) in three regions, reveal differences between WGSs and outside the lowland. The results show that the average annual Ta at all three WGSs is significantly lower than in their surrounding area (0.7 to 1.0 K). The differences are minimally larger in the summer half-year than in the winter half-year (1.0 vs. 0.7 K in the Spreewald region, 0.7 vs. 0.6 K in the Havelland region). The differences cannot only be explained by higher evapotranspiration (ET), but are mainly due to the ground heat balance of the sites with shallow water tables and organic soils. The VPs of the WGSs and the surrounding area only differ significantly from each other in the summer months and do not vary as clearly as the Ta. While the VP is higher in the Spreewald wetland than in the surrounding area (+0.05 kPa), it is lower in Paulinenaue than in that surrounding area (−0.04 kPa). The reason for this is different ET due to the different site conditions. [ABSTRACT FROM AUTHOR]

Evapotranspiration is one of the most important hydro-climatological components which directly affects agricultural productions. Therefore, its forecasting is critical for water managers and irrigation planners. In this study, adaptive neuro-fuzzy inference system (ANFIS) model has been hybridized by differential evolution (DE) optimization algorithm as a novel approach to forecast monthly reference evapotranspiration (ET0). Furthermore, this model has been compared with the classic stochastic time series model. For this, the ET0 rates were calculated on a monthly scale during 1995–2018, based on FAO-56 Penman–Monteith equation and meteorological data including minimum air temperature, maximum air temperature, mean air temperature, minimum relative humidity, maximum relative humidity & sunshine duration. The investigation was performed on 6 stations in different climates of Iran, including Bandar Anzali & Ramsar (per-humid), Gharakhil (sub-humid), Shiraz (semi-arid), Ahwaz (arid), and Yazd (extra-arid). The models' performances were evaluated by the criteria percent bias (PB), root mean squared error (RMSE), normalized RMSE (NRMSE), and Nash-Sutcliff (NS) coefficient. Surveys confirm the high capability of the hybrid ANFIS-DE model in monthly ET0 forecasting; so that the DE algorithm was able to improve the accuracy of ANFIS, by 16% on average. Seasonal autoregressive integrated moving average (SARIMA) was the most suitable pattern among the time series stochastic models and superior to its competitors, ANFIS and ANFIS-DE. Consequently, the SARIMA was suggested more appropriate for monthly ET0 forecasting in all the climates, due to its simplicity and parsimony. Comparison between the different climates confirmed that the climate type significantly affects the forecasting accuracies: it's revealed that all the models work better in extra-arid, arid and semi-arid climates, than the humid and per-humid areas. [ABSTRACT FROM AUTHOR]

Precise estimation of reference evapotranspiration (ET0) is of significant importance in hydrologic processes. In this study, a genetic algorithm (GA) optimized back propagation (BP) neural network model was developed to estimate ET0 using different combinations of meteorological data across various climatic zones and seasons in China. Fourteen climatic locations were selected to represent five major climates. Meteorological datasets in 2018–2020, including maximum, minimum and mean air temperature (Tmax, Tmin, Tmean, °C) and diurnal temperature range (∆T, °C), solar radiation (Ra, MJ m−2 d−1), sunshine duration (S, h), relative humidity (RH, %) and wind speed (U2, m s−1), were first subjected to correlation analysis to determine which variables were suitable as input parameters. Datasets in 2018 and 2019 were utilized for training the models, while datasets in 2020 were for testing. Coefficients of determination (r2) of 0.50 and 0.70 were adopted as threshold values for selection of correlated variables to run the models. Results showed that U2 had the least r2 with ET0, followed by ∆T. Tmax had the greatest r2 with ET0, followed by Tmean, Ra and Tmin. GA significantly improved the performance of BP models across different climatic zones, with the accuracy of GABP models significantly higher than that of BP models. GABP0.5 model (input variables based on r2 > 0.50) had the best ET0 estimation performance for different seasons and significantly reduced estimation errors, especially for autumn and winter seasons whose errors were larger with other BP and GABP models. GABP0.5 model using radiation/temperature data is highly recommended as a promising tool for modelling and predicting ET0 in various climatic locations. [ABSTRACT FROM AUTHOR]

Evaluating actual crop evapotranspiration (ETc) variations and their determining factors under changing climates is crucial for agricultural irrigation management and crop productivity improvement in nonhumid regions. This study analyzed the spatiotemporal characteristics and detected the determining factors of ETc for winter wheat and summer maize rotation system from 2000 to 2017 in the North China Plain (NCP), by combining the FAO-56 dual crop coefficient approach with remotely sensed vegetation indices (VIs). The results indicated that daily air temperature increased in varying degrees while wind speed and sunshine hours decreased slightly during the growing season of winter wheat and summer maize over the study period. The trends of relative humidity and effective precipitation varied in crop growing seasons. Based on the validated relationship of dual crop coefficients and VIs, the estimated multi-year average ETc of winter wheat (370.29 ± 31.28 mm) was much higher than summer maize (281.85 ± 20.14 mm), and the rotation cycle was 652.43 ± 27.67 mm. Annual ETc of winter wheat and the rotation cycle increased by 2.96 mm a-1 and 1.77 mm a-1, respectively. However, the ETc of summer maize decreased with distinct spatial variation. Spatially, winter wheat ETc increased significantly in the northeast NCP, covering the Beijing-Tianjin-Hebei areas. Meanwhile, significant increases in summer maize ETc were detected in the southwest NCP. The sensitivity and contribution analysis showed that ETc of winter wheat and summer maize was positively sensitive to temperature, wind speed, and sunshine hours while negatively to relative humidity. Moreover, wind speed and sunshine hours contributed most to changes in ETc (around 20%-40%). [ABSTRACT FROM AUTHOR]

Models relying on limited inputs are very valuable for estimating reference evapotranspiration, and subsequently irrigation doses, but their accuracy can be very dependent from calibration. This study assessed three versions of the Hargreaves-Samani (HS) and the FAO Penman-Monteith (PM) equations to estimate reference evapotranspiration (ET o), relying respectively on three input combinations. Further the six models were adjusted each using different time windows for calculating the calibrating constants, namely global, annual, monthly, fortnightly, and weekly constants, while all the models were calibrated and tested using calculated and lysimeter benchmarks. The models relying on mean air temperature and solar radiation tended to be more accurate than those relying on mean air temperature and relative humidity, while these tended to be more accurate than those relying on air temperature difference, but there might be intra annual exceptions according to the monthly indicators. The errors of the PM estimations were just slightly higher than those of the corresponding HS estimations. The accuracy improvement in the calibrated versions was higher the shorter the time window used for averaging the calibrating parameters. Thus, the application of monthly or, at least, seasonal calibrating constant might be recommended for a suitable correction of the bias. During the year, the estimations presented markedly lower errors and lower differences within models during the summer. The error decrease in the calibrated versions was more marked during the winter. The assessment relying on lysimeter benchmarks provided similar qualitative patterns than the assessment relying on calculated benchmarks, but the corresponding error ranges were higher. Finally, 6 examples were presented for visualizing the effect of the method used to estimate ET o on the corresponding resulting average annual crop water requirements. If irrigation scheduling is based on a soil water balance using crop evapotranspiration estimates, at least, a monthly bias assessment of the ET o estimates in combination with the crop cycle lengths and dates might contribute to infer if crop water requirement infra-estimation trends are identified during crop sensitive stages to water deficit. • The seasonal performance trends of two common non-calibrated ETo equations based on limited inputs were assessed. • The effect of calculating the calibrating constants of the ETo equations using different time windows was assessed. • The effect of using FAO56 PM benchmarks for calibrating and testing was evaluated against lysimeter observations. • The constants of the ETo equations were calibrated relying on calculated and lysimeter observations, and compared. • The effect of the ET o estimation method on the resulting crop water requirements is assessed in 6 crops according to FAO56. [ABSTRACT FROM AUTHOR]

Reference evapotranspiration (ET0) is of great significance in studies of hydrological cycle, agricultural water resources, and hydrometeorology. The present study collected daily meteorological data at 536 meteorological stations in China from 1984 to 2019, calculated daily ET0 using the FAO Penman–Monteith equation, analyzed the spatial distribution and temporal variation characteristics of ET0 and meteorological variables at four different spatial scales (continental, regional, provincial, and local), and discussed the sensitivity of ET0 to the meteorological variables and the contribution rates of the meteorological variables to the ET0 variations. The results showed that ET0 increased at 406 out of the 536 stations (75.7%), with the trends being significant at 65 stations at the 5% significance level, and 147 at the 1% significance level. The slope calculated using Sen's method and linear trend method showed that the annual ET0 at the continental scale increased by approximately 12 mm/decade. Most of the stations showed decreasing trends in relative humidity (Hm), sunshine duration (SD), and wind speed at 2 m height (U2) while increasing trends in the maximum air temperature (Tmax) and minimum air temperature (Tmin). ET0 was most sensitive to Hm (sensitivity coefficient, St = −0.66), followed by Tmax (St = 0.29), SD (St = 0.18), U2 (St = 0.16), and Tmin (St = 0.07). Most of the stations showed increasing trends in St for Hm (56.16%), Tmax (72.95%), Tmin (87.31%), and U2 (90.49%), and decreasing trends for SD (69.78%). The variations in Hm, Tmax, and Tmin increased the ET0 at most of the stations (82.28%, 98.13%, and 69.03%, respectively). The variations in SD and U2 decreased ET0 at most of the stations (66.04% and 56.34%, respectively). Some ET0 characteristics in a few regions can be well described using a single spatial scale. However, most regions exhibited significantly different ET0 characteristics across spatial scales. The results of this project can provide reference for hydrological analysis and agricultural water management under climate change conditions and provide data and information for other hydrology-related applications. [ABSTRACT FROM AUTHOR]

Accurate global terrestrial evapotranspiration (ET) estimation is essential to better understand Earth's energy and water cycles. Although several global ET products exist, recent studies indicate that ET estimates exhibit high uncertainty. With the increasing trend of extreme climate hazards (e.g., droughts and heat waves), accurate ET estimation under extreme conditions remains challenging. To overcome these challenges, we used 3 h and 0.25 ∘ Global Land Data Assimilation System (GLDAS) datasets (net radiation, land surface temperature (LST), and air temperature) and a three-temperature (3T) model, without resistance and parameter calibration, in global terrestrial ET product development. The results demonstrated that the 3T model-based ET product agreed well with both global eddy covariance (EC) observations at daily (root mean square error (RMSE) = 1.1 mm d -1 , N=294058) and monthly (RMSE = 24.9 mm month -1 , N=9632) scales and basin-scale water balance observations (RMSE = 116.0 mm yr -1 , N=34). The 3T model-based global terrestrial ET product was comparable to other common ET products, i.e., MOD16, P-LSH, PML, GLEAM, GLDAS, and Fluxcom, retrieved from various models, but the 3T model performed better under extreme weather conditions in croplands than did the GLDAS, attaining 9.0 %–20 % RMSE reduction. The proposed daily and 0.25 ∘ ET product covering the period of 2001–2020 could provide periodic and large-scale information to support water-cycle-related studies. The dataset is freely available at the Science Data Bank (10.57760/sciencedb.o00014.00001, Xiong et al., 2022). [ABSTRACT FROM AUTHOR]

Evapotranspiration (ET) plays an important role in agricultural water management and crop modeling. The highest mean annual ET values (889–1016 mm) in the United States (US) occur in Florida where there is a combination of ample rainfall (R) and warm air temperatures. Therefore, it is crucial to know the synergistic influence of meteorological variables (MV) on ET variability. This study aims to evaluate how reference evapotranspiration (ET0) over Florida from 2008 to 2018 was influenced by MV using simultaneous changes in all variables. These changes were evaluated interannually, seasonally, monthly, and daily using trend analysis. We used weather information including R, relative humidity (RH), solar radiation (SR), wind, and temperature parameters as well as ET0 from 33 synoptic stations over Florida recorded by the Florida Automated Weather Network (FAWN). Results of this study showed that SR had the strongest positive annual correlation with ET0 for all climate regions over Florida. However, temporal analysis showed that during December and January, temperature was the dominant factor to control variations of ET0 which was highly consistent with anomalies of ET0 and temperature parameters in December. The correlation coefficients between ET0 and RH were negatively higher than −0.6 from May to September, compared to the entire year, where RH was negligible (between −0.1 and −0.2). The significant trend of air and soil temperature, SR, and RH might be considered as an early alarm system for climate variability over Florida. Finally, sensitivity analysis revealed that ET0 changed at least 1% for 16–18% variations of MV in 67% of the weather stations (22 stations); this range (16–18%) can be assigned as an average range to force ET0 to change at least 1% across Florida. The results of this study can be used as a guideline to assess the annual, seasonal, and monthly relationships between the most influential MV and ET0 across Florida, as a source to identify the most sensitive MV in the modeling of ET related studies, and as the base to develop climate-based management plans for agricultural water management. [ABSTRACT FROM AUTHOR]

The climatic changes observed in Poland are manifested by an increase in air temperature, but not an increase in rainfall, which causes an increase in the water needs of plants, and hence the necessity to develop irrigation systems for crops. The aim of this study was to assess the water needs of grapevines in 2021–2050 in the Bydgoszcz region (northern Poland), an area with high requirements for supplementary irrigation. The calculations were based on the expected changes in air temperature according to the climate change scenario for Poland: the 4th Intergovernmental Panel on Climate Change—Special Report on Emissions Scenarios: balanced scenario (A1B). The average monthly temperature in 1981–2010 was used in the calculations. The water needs of grapevines were estimated using the reference evapotranspiration calculated using the Blaney–Criddle equation, and then using the crop coefficient and potential (crop) evapotranspiration. It was found that in 2021–2050, the water needs of grapevines, both during the growing season (May–September) and during the irrigation period (June–August), will increase by 6%. The highest and significant increase in water needs, by 10%, should be expected in August. The estimated increase in water needs of grapevines indicates the need to development sustainable irrigation systems for vineyards in northern Poland. [ABSTRACT FROM AUTHOR]

Evapotranspiration (ET) is a vital part of the global water cycle and is closely related to carbon sequestration. Analysing ET dynamics and their drivers would benefit for improving our understanding of the global water and carbon cycles. Using an eddy covariance (EC) approach, we analysed ET dynamics and their drivers in a temperate mixed forest over northeast China from 2016 to 2017. The results showed that 43.55% of our eddy covariance data passed the quality control. In addition, the energy balance ratio was 0.62, indicating that measurements were reliable. The measured ET showed clear single peak patterns with seasonal and diurnal variations. The daily ET ranged from 0 to 7.75 mm d-1 and the hourly ET ranged from 0 to 0.28 mm h-1. The ranges of hourly ET floated from 0 to 0.05 mm h-1 at non-growing season (November to April) while ranged from 0 to 0.28 mm h-1 at active growing season (May to October). The diurnal ET dynamics during the non-growing season were driven by air temperature (Ta), but were governed by global radiation (Rg) during the active growing season. Leaf area index (LAI) comprehensively reflected the variations of Ta and Rg, and was found to be the primary factor shaping the seasonal dynamics of ET. The annual ET rates were 501.91 ± 5.30 mm year-1 and 554.60 ± 11.24 mm year-1 for 2016 and 2017, respectively. Therefore, energy supply, represented by Ta and Rg, governed ET dynamics in our temperate mixed forest, while variables representing the energy supply affecting ET dynamics differed among seasons and time scales. ET dynamics indicated that a temperate mixed forest is important to the global water cycle. Our results improved our understanding of ET dynamics in the studied region. [ABSTRACT FROM AUTHOR]

Climate change increases the frequency and intensity of heat waves, bringing along multiple adverse impacts on ecosystems, human health, societies, and the economy. Groundwater influences the near surface air temperature evolution through land–atmosphere interactions. Using simplified and shallow groundwater representations, reproducing heat waves in a regional climate model (RCM) is challenging. Currently, RCMs applied over Europe exhibit a warm bias. This study analyzes heat waves over a 13‐year evaluation period, comparing the terrestrial systems modeling platform (TSMP) with an explicit groundwater representation to a EURO‐CORDEX RCM ensemble, the ERA5 reanalysis, and observations. The TSMP multiannual heat wave statistics are consistent with observations and reanalysis data. We attribute the lower absolute deviations of heat wave metrics simulated by TSMP to the improved hydrology including 3D groundwater flow. The findings emphasize the importance of hydrological process representation in RCMs. Plain Language Summary: Heat waves severely impact the ecosystem, society, and the economy. Climate change will amplify these events in the near future, urging a correct representation of heat waves in climate models. Especially during warm and dry periods, there is a strong connection from the groundwater stored in the subsurface through the land surface to the atmosphere. Commonly applied models have a simplified representation of groundwater and cannot establish a correct connection to the atmosphere, simulating too high temperatures over Europe. To show the advantage of a model with a complex groundwater representation, we compare such a model with 12 representative climate models. The results indicate lower deviations from heat wave statistics of observations with the inclusion of complex groundwater. Our findings emphasize the importance of including groundwater dynamics representation in climate models. Key Points: Multiannual heat wave statistics from a regional climate model including groundwater dynamics are consistent with observationsRegional climate models with simplified groundwater representations overestimate observed multiannual heat wave statisticsExplicit groundwater treatment increases the reliability of heat wave simulations with implications for regional climate projections [ABSTRACT FROM AUTHOR]

Accurate global terrestrial evapotranspiration (ET) estimation is essential to better understand Earth's energy and water cycles. Although several global ET products exist, recent studies indicate that ET estimates exhibit high uncertainty. With the increasing trend of extreme climate hazards (e.g., droughts and heat waves), accurate ET estimation under extreme conditions remains challenging. To overcome these challenges, we used 3-hour and 0.25° Global Land Data Assimilation System (GLDAS) datasets (net radiation, land surface temperature (LST), and air temperature) and three-temperature (3T) model, without resistance and parameter calibration, in global terrestrial ET product development. The results demonstrated that the 3T model-based ET product agreed well with both global eddy covariance (EC) tower (root mean square error RMSE) = 24.9 mm month-1) and basin-scale water balance observations (RMSE =116.0 mm yr-1). The 3T model-based global terrestrial ET product was comparable to other common ET products, i.e., MOD16, P-LSH, PML, GLEAM, GLDAS, and Fluxcom, retrieved from various models, but the 3T model performed better under extreme weather conditions in croplands than did the GLDAS, attaining 9.0-20% RMSE reduction. The proposed ET product could provide periodic and large-scale information to support water cycle-related studies. The dataset is freely available at the Science Data Bank. [ABSTRACT FROM AUTHOR]