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China's Losses Plateau (LP) is one of the ecologically vulnerable and the most severe soil erosion regions. Thus, knowing spatiotemporal changes in evapotranspiration (ET) and its components (soil evaporation, E; transpiration, T; and vegetation interception evaporation, EI) and revealing the underlying mechanisms are vital for ecosystem and water resources sustainability for this region. Here, we investigate the spatiotemporal changes in ET and its components and then quantify the impacts of climate variables (i.e., precipitation, radiation, temperature, and relative humidity) and vegetation dynamics (e.g., land use/cover changes [LUCC] and changes in leaf area index [LAI]) on their annual trends, by using a process‐based terrestrial ecosystem model and a joint‐solution method with multiple sensitivity numerical experiments. Results show that over 67% of the study region experienced significant (p < 0.05) increases in annual ET, T, and EI, with regional average rises of 4.05, 3.67, and 0.74 mm·year−1, respectively. However, there are significant (p < 0.05) decreases in regional mean E of 0.38 mm·year−1, and the negative trend covers 35.8% of the study area. E, T, and EI changes dominate the annual ET trends over 11.8%, 87.3%, and 0.9% of the study area, respectively. Attribution analyses highlight the increased LAI as the critical factor governing these trends across most of the LP (>58%). At the same time, precipitation and LUCC play a more dominant role in the remaining areas. This study emphasizes the spatial heterogeneity in the drivers of changes in ET and its components and highlights the critical role of vegetation dynamics. These findings provide valuable insights for understanding the ET processes and guiding sustainable water resource management in the LP. [ABSTRACT FROM AUTHOR]

Climate extremes, such as heatwaves and droughts, significantly impact terrestrial ecosystems. This study investigates the influence of compound hot–dry (CHD) events on vegetation productivity in northern East Asia. Four of the most widespread CHD events occurring during the summer from 2003 to 2019 were selected as the focus of this research. We first verified the performance of the Community Land Model version 5 (CLM5) in the region and then conducted factor-controlled experiments using CLM5 to assess the effects of different climate factors on gross primary productivity (GPP) changes during CHD events. Our results show that vegetation productivity exhibits greater sensitivity to CHD events within the transitional climatic zone (TCZ) than in other affected areas. In grassland areas within the TCZ, precipitation deficit is the primary factor leading to the decrease in GPP (explaining 56%–90% of GPP anomalies), while high temperatures serve as a secondary detrimental factor (explaining 13%–32% of GPP anomalies). In high-latitude forests outside the TCZ, high temperature has a more significant impact on suppressing GPP, while the decrease in soil moisture has a synchronously negligible impact on GPP. There are differences in the effects of high solar radiation on grasslands and woodlands during CHD events. It was observed that high radiation benefits trees by increasing the maximum carboxylation rate (Vcmax) and maximum electron transport rate (Jmax), as well as enhancing photosynthesis, but has a negligible impact on grasses. Furthermore, this study highlights the potential for compound events to impact vegetation productivity more than expected from individual events due to confounding nonlinear effects between meteorological factors. More than 10% of the negative anomalies in GPP during two CHD events in 2017 and 2010 were attributed to these nonlinear effects. These research findings are significant for understanding ecosystem responses to climate extremes and their influence on carbon cycling in terrestrial ecosystems. They can also contribute to more precisely evaluating and predicting carbon dynamics in these regions. [ABSTRACT FROM AUTHOR]

As the theoretical upper bound of evapotranspiration (ET) or water use by ecosystems, potential ET (PET) has always been widely used as a variable linking a variety of disciplines, such as climatology, ecology, hydrology, and agronomy. However, substantial uncertainties exist in the current PET methods (e.g., empiric models and single-layer models) and datasets because of unrealistic configurations of land surface and unreasonable parameterizations. Therefore, this study comprehensively considered interspecific differences in various vegetation-related parameters (e.g., plant stomatal resistance and CO 2 effects on stomatal resistance) to calibrate and parametrize the Shuttleworth–Wallace (SW) model for forests, shrubland, grassland, and cropland. We derived the parameters using identified daily ET observations with no water stress (i.e., PET) at 96 eddy covariance (EC) sites across the globe. Model validations suggest that the calibrated model could be transferable from known observations to any location. Based on four popular meteorological datasets, relatively realistic canopy height, time-varying land use or land cover, and the leaf area index, we generated a global 5 km ensemble mean monthly PET dataset that includes two components of potential transpiration (PT) and soil evaporation (PE) for the 1982–2015 time period. Using this new dataset, the climatological characteristics of PET partitioning and the spatiotemporal changes in PET, PE, and PT were investigated. The global mean annual PET was 1198.96 mm with PT/PET of 41 % and PE/PET of 59 %, controlled moreover by PT and PE of over 41 % and 59 % of the globe, respectively. Globally, the annual PET and PT significantly (p<0.05) increase by 1.26 and 1.27 mm yr -1 over the last 34 years, followed by a slight decrease in the annual PE. Overall, the annual PET changes over 53 % of the globe could be attributed to PT, and the rest to PE. The new PET dataset may be used by academic communities and various agencies to conduct climatological analyses, hydrological modeling, drought studies, agricultural water management, and biodiversity conservation. The dataset is available at 10.11888/Terre.tpdc.300193 (Sun et al., 2023). [ABSTRACT FROM AUTHOR]

Using the 43‐station soil moisture (SM) at a depth of 0–10 cm over eastern China, the near‐surface (about 0–5 cm) SM products from satellite missions including the level‐2 product of Chinese FengYun 3C (FY3C), level‐2 neural network product of the European Soil Moisture and Ocean Salinity (SMOS) and level‐4 product of the US Soil Moisture Active Passive (SMAP) were evaluated and compared during summers of 2015–2018. Thus, features of those products can be identified for their further application of climate study over eastern China. Large diversity is found among the satellite and field SM in terms of spatial distribution. This disagreement may cause the poor performance of the relationship between spatial coefficients of variation (CV) and mean SM. Compared with the field SM, the FY3C SM has smaller bias than the other satellite products. FY3C also performs better than SMOS in terms of the root‐mean‐square error (RMSE) and unbiased RMSE (ubRMSE) but has the smallest correlation coefficient (R). The SMAP product is generally the best among the three products in terms of RMSE, ubRMSE and R. However, a good performance in those metrics does not guarantee the same results on various time scales. On subseasonal time scales, the R in FY3C is the smallest among the three products, and the SMAP product has the largest R, but its amplitudes of the subseasonal variations are much smaller than the field observations. This indicates that when the SMAP products are applied for the analysis on subseasonal SM–atmosphere interactions, the effects of SM may be underestimated. On 10–30 days and above 60 days, dry period tends to have large spatial CV but this phenomenon is weak in all the satellite products. On the other hand, dry area tends to have large temporal CV on the four time scales, and this relationship is the strongest in SMAP but the weakest in FY3C. Therefore, there are large uncertainties of variability among different satellite SM products on subseasonal time scales over eastern China. Besides seasonal and overall performance, more attention is called to the variations on different time scales. [ABSTRACT FROM AUTHOR]

Intensified droughts have been weakening global vegetation productivity, yet how the sensitivity of vegetation productivity to drought changes over time is not well known. Here, using the simulated long‐term gross primary production (GPP) with an improved two‐leaf light use efficiency model and the Standardized Precipitation Evapotranspiration Index (SPEI), we studied the sensitivity of global vegetation productivity to drought, quantified by the corresponding time scale of SPEI with strongest drought impact on GPP, and analyzed the changes in the sensitivity over two time periods (1993–2005 and 2006–2018). Compared to the first period, droughts were more widespread and severer around the world in the second period, as evidenced by increased drought range (increased by 4.43%) and intensity (SPEI03 decreased by 103%). Globally, the area with significant correlation between GPP and SPEI increased by 25.53%, the impact intensity increased by 14.75%, and the drought sensitivity of GPP enhanced by 13.76%; the changing directions were pretty similar across various vegetation types, mostly showing an increasing trend. Moreover, the vegetation in regions with consistently decreasing moisture was affected by drought most strongly and experienced the greatest change in the sensitivity of GPP to drought (enhanced by 10.99%), indicating that the arid and semi‐arid ecosystems should be considered as a research priority in the future. Our results reveal strengthened drought sensitivity of global vegetation productivity in recent decades across various ecosystems and climate transition regions, which could improve our understanding on the behavior and fate of terrestrial ecosystems in the changing climate. Plain Language Summary: Drought is one of the key factors that weaken vegetation productivity, but there is a lack of research on the changes in vegetation sensitivity to drought at the global scale. Based on long‐term gross primary productivity (GPP) simulated with an improved two‐leaf light use efficiency model and the standardized precipitation evapotranspiration index (SPEI), we studied the changes in vegetation GPP sensitivity to drought by comparing the time scale of SPEI with strongest impact of drought on GPP over two time periods (1993–2005 and 2006–2018). The extent, intensity, and frequency of droughts have increased in the last three decades. Globally, the area and intensity of drought effect on vegetation increased and the sensitivity of GPP to drought enhanced, occurring in most vegetation types. In addition, the increase in vegetation sensitivity to drought was the strongest in regions with persistent decreasing moisture, implying the need to focus on the impacts of drought on arid and semi‐arid ecosystems. This study can deepen our insights into the response of vegetation to climate change. Key Points: Droughts have become more widespread and severer around the world during the recent decadesDrought sensitivity of vegetation gross primary productivity was enhanced globally and across most vegetation typesThe sensitivity increased most strongly in the regions with persistently decreasing water availability [ABSTRACT FROM AUTHOR]

Droughts and floods are extreme events that have tremendous socioeconomic impact. Many studies have investigated their possible variations under the effects of climate changes, while their intraseasonal‐to‐seasonal characteristics have received less attention. Based on observation‐constrained monthly soil moisture (SM) datasets since 1980, we analysed the spatiotemporal characteristics of global SM at the intraseasonal‐to‐seasonal time scales and the associated influencing factors. The results were then used to evaluate the performance of simulations by Coupled Model Intercomparison Project Phase 6 (CMIP6) models. It is found that the frequencies of extreme wet events are slightly higher than those of extreme dry events, but their spatial distributions are similar and are both affected by precipitation variability. Extreme events tend to have longer durations than nonextreme events, and their global mean durations are 4–5 months. Globally, dry events persist longer than wet events. Maximum SM anomalies are strongly affected by earlier precipitation and this effect is stronger in a transitional climate. The onset and peak times of SM anomalies in a year occur most frequently near the peak time of precipitation rather than that of SM. Approximately half of CMIP6 models overestimate the durations of both dry and wet events and approximately one third of models only underestimate wet events durations. Different versions of the same model produce similar event durations. The findings of this study enhance understanding of the intraseasonal‐to‐seasonal variabilities of global droughts and floods and could provide guidance for future study of land–atmosphere interactions and prediction of extreme events. [ABSTRACT FROM AUTHOR]

Based on the normalized difference vegetation index (NDVI) and empirical orthogonal function analysis, a "northeast‐southwest" dipole pattern of spring vegetation in mid‐high latitude Asia was detected. This pattern was revealed to be associated with the autumn sea ice concentration (SIC) anomalies in the Barents‐Laptev Seas on the interannual variability. Increased autumn SIC over the Barents‐Laptev Seas tends to increase spring NDVI over the west of Lake Baikal and decrease spring NDVI in the Russian Far East. Further analyses indicated that the sea surface temperature (SST) anomalies persisting from winter to spring over the Northeast Atlantic and the Northwest Pacific play an important role in such a relationship. Increased autumn SIC over the Barents‐Laptev Seas is associated with a teleconnection pattern over the mid‐high latitudes in the following winter, accompanied by anomalous anticyclonic circulations over the Northeast Atlantic and the Northwest Pacific. Such changes in the large‐scale circulations induce downward net heat flux anomalies over the Northeast Atlantic and the Northwest Pacific, thereby contributing to the warming of SST which may persist to spring and in turn influence the atmospheric circulations. The Northeast Atlantic SST warming in spring may evoke a downstream wave train and cause positive geopotential height anomalies over the west of Lake Baikal, which increases local temperature and hence the vegetation. The Northwest Pacific SST warming in spring may lead to negative geopotential height anomalies over the Russian Far East through a meridional wave train, consequently resulting in a decrease in local temperature and hence vegetation. Plain Language Summary: The complex relationship between the climate and vegetation dynamics has been receiving a great deal of research attention. While much is known about how spring vegetation is controlled by the basic conditions such as temperature and precipitation, few studies have examined the response of the vegetation to Arctic sea ice. Our results reveal that the "northeast‐southwest" dipole pattern of spring vegetation in mid‐high latitude Asia is closely related to the preceding autumn sea ice concentration in the Barents‐Laptev Seas. The sea surface temperature anomalies persisting from winter to spring over the Northeast Atlantic and the Northwest Pacific play an important role in bridging such a relationship. These findings contribute to a better understanding of the change in spring vegetation over mid‐high latitude Asia. Key Points: A "northeast‐southwest" dipole pattern of spring vegetation is detected over mid‐high latitude AsiaThe spring vegetation dipole pattern is linked to the preceding autumn sea ice variation in the Barents‐Laptev SeasThe sea surface temperatures in the Northeast Atlantic and Northwest Pacific play an important role in bridging such a lag linkage [ABSTRACT FROM AUTHOR]

This study systematically assessed the performance of the Integrated Multi‐satellitE Retrievals (IMERG) for Global Precipitation Measurement V06, including the near‐real‐time "Late Run" (IMERG‐L) and the post‐real‐time "Final Run" (IMERG‐F), over Zhejiang Province (ZJP), China. The evaluation was conducted at daily and hourly timescales for a full year and for each season, based on dense rain gauge observations and continuous and categorical validation statistics. For the full year and for each season, IMERG‐F outperformed IMERG‐L in representing the spatial pattern of multiyear mean precipitation. For regional mean of ZJP, IMERG‐F and IMERG‐L overestimated the daily/hourly precipitation for the full year by 6.51 and 4.98%, respectively. Among seasons, the regional mean relative biases for IMERG‐F were between 5.65 and 8.63%; however, for IMERG‐L, they exhibited notable variations with a maximum of 11.09% in fall and a minimum of 0 in spring. Bias composition suggested that the regional mean overestimations were largely due to false bias for the full year and for each season, except in winter, wherein it was due to hit bias. Spatially, the biases for the full year and for each season commonly arose from false and hit biases at daily timescale, and from false and miss biases at hourly timescale. Based on the remaining continuous metrics (i.e., root‐mean‐square‐error [RMSE], correlation coefficient [CC], and Kling–Gupta Efficiency [KGE]) and all categorical metrics, the IMERG daily/hourly performance was acceptable on regional and grid scales throughout the year and in all seasons. From a region‐average perspective, IMERG‐F outperformed IMERG‐L according to CC, RMSE, and KGE, but both products showed the same performance overall based on all categorical metrics; most grids also share these characteristics. This study provides a valuable reference for IMERG developers to improve product accuracy from the perspective of the final postprocessing step and for potential users in ZJP. [ABSTRACT FROM AUTHOR]

Indochina is one of the key areas affecting the East Asian summer monsoon and its thermal condition can modulate the prevailing wind and water vapour transport, especially in the early stages of establishment of the summer monsoon. Previous studies emphasized the climatic effect of the seasonal‐averaged soil moisture (SM), but the subseasonal effects of land surface processes over Indochina are not clear yet. This study investigated the subseasonal effect of SM in Indochina on precipitation in southern China (SC) during May and June together with its relevant mechanism based on both statistical analysis and numerical experiments. Results show that increased SM in Indochina in May is closely associated with increased local (Indochina) precipitation and suppressed non‐local (SC) precipitation in June. The positive SM anomaly over Indochina can persist from May to June, cooling the atmosphere and increasing the specific humidity in the lower troposphere. Meanwhile, the potentially unstable lower troposphere and the ascending motion over Indochina result in strengthened upward moisture advection and condensational heating, which are conducive to forming an abnormal cyclonic circulation and increased precipitation over Indochina. To the northeast, an easterly wind anomaly appears in SC, leading to weakened moisture transport and decreased precipitation. When the SM decreases over Indochina, the opposite results are obtained. Moreover, through increasing and decreasing SM in Indochina in May, numerical experiments showed similar results to those of reanalysis data and further indicated that the moist and thermal processes of the SM anomaly over Indochina play distinct roles in affecting the atmosphere and regional precipitation. The moisture process mainly influences local precipitation, whereas the thermal process can change the precipitation non‐locally. This study highlights the significant local and non‐local impacts of SM in Indochina and could contribute to understanding the physical mechanisms of SM effects. [ABSTRACT FROM AUTHOR]

In the context of global warming, meteorological disasters occur more frequently in various regions which exert increasing influences on human life. Snow disasters are some of the natural disasters that most seriously affect the development of husbandry on the Qinghai–Tibetan Plateau (QTP), so it is necessary to explore their spatio-temporal variations and perform comprehensive risk assessment. Based on the daily snow depth data set in China, obtained by inversion of satellite remote sensing data, the spatio-temporal variation characteristics of snow disasters on the QTP from 1980 to 2019 were studied. The regional difference in the comprehensive risks of snow disasters for the husbandry on the QTP was evaluated from four perspectives, i.e., the risk of hazard factors, sensitivity of hazard-inducing environments, vulnerability of hazard-affected bodies, and disaster prevention and mitigation capacity. The farmer and pastoralist well-being (FPWB) index in five typical regions was constructed to discuss the possible influences of snow disasters on the FPWB since the 21st century. Results show that, in the last 40 years, the frequency, duration, average snow depth, and grade of snow disasters on the QTP all exhibited significant interannual and interdecadal variabilities, and they also displayed a declining long-term trend. The comprehensive risk of snow disasters for the husbandry on the QTP is low in the north while high in the south. The high-risk zone accounts for 1.54% of the total and is mainly located in Kashgar City in the north-western end of the QTP; the sub-high-risk and medium-risk zones are mainly found in the south of the plateau and are distributed in a tripole pattern, separately covering 15.96% and 16.32% of the total area of the plateau; the north of the plateau mainly belongs to low-risk and sub-low-risk zones, which separately account for 43.06% and 23.12% of the total area of the plateau. Since the beginning of the 21st century, the FPWB in five typical regions, namely, Kashgar (I), Shigatse (II), Nagqu (III), Qamdo (IV), and Yushu (V), has been increasing, while the risk of snow disasters has gradually decreased. Every 1% decrease in the risk of snow disasters corresponded to 0.186%, 0.768%, 0.378%, 0.109%, and 0.03% increases in the FPWB index in the five regions. Snow disasters affect FPWB mainly by directly or indirectly damaging material resources (livestock inventories and meat production) and social and financial resources. [ABSTRACT FROM AUTHOR]

Given the key roles of the Indo–China Peninsula (ICP) in weather and climate systems, hydrometeorology, and ecology, the annual and monthly changes in the Food and Agriculture Organization‐56 Penman–Monteith reference evapotranspiration (ET0), which was calculated based on the Climatic Research Unit datasets, were investigated in ICP during 1961–2017. The annual ICP ET0 significantly (p <.05) increased, with different increasing tendencies in most months. In particular, larger and more significant (p <.05) ET0 values were found during October–December. The annual and monthly ET0 changes showed evident spatial differences, characterized by increases in more than 50% of the ICP area except for decreases in around 70% of that area during March–May. A sensitivity experiment‐based separation method was utilized to evaluate the contribution of each influential factor, and the corresponding determinants were identified by comparing the contributions. Results showed that the annual ICP ET0 increase was attributed to the increased vapour pressure deficit (Vpd). However, the annual determinants varied spatially, with net solar radiation (Rn) in the southern region of ICP, wind speed (Wnd) in the northeast, and Vpd in the remaining regions. The monthly ICP determinant was Wnd in January, March–May and December, and Vpd for the remaining months. Despite different spatial patterns of monthly dominants, Vpd and Wnd were the determinants with the most extensive distributions over ICP (>75% of ICP in total). The results of this study can significantly fulfil the research gap regarding the ICP ET0 changes and the underlying mechanisms. Meanwhile, this study provides fundamental and necessary information for protecting biodiversity and understanding hydrometeorological extreme events, thus promoting specific measures to sustain the ICP development. [ABSTRACT FROM AUTHOR]