Vegetation is an indispensable component of the hydrological cycle, playing a critical role not only in modulating water balance but also in regulating ecohydrological processes within ecosystems. However, the specific contributions and mechanisms by which vegetation affects runoff dynamics in alpine catchments remain poorly understood. In this study, we developed a Budyko framework incorporating glacier effect at hydrological year and established a semi-empirical formula for estimating parameters (ω in the Budyko-Fu equation) based on the Normalized Difference Vegetation Index (NDVI) and climate seasonality. We employed the elasticity method to quantify the impact of vegetation changes on annual runoff in the Southwest Basin (SWB) of China from 2000 to 2020. The results show that the semi-empirical formulas used for annual-scale ω calculation demonstrated significant improvement in runoff estimation incorporating glacier effects. The Yarlung Zangbo River Basin (YZRB) shows the largest annual average improvement in ω (0.85%), followed by the Nu River Basin (NRB, 0.28%), while the Lancang River Basin (LRB) exhibits the smallest improvement (0.07%). Vegetation exerted a statistically significant positive impact on basin runoff (P < 0.001). On average, a 10% increase in NDVI corresponded to a 4.20% increase in runoff. Notably, this effect exhibited clear spatial heterogeneity across the nine sub-basins and generally intensified with increasing aridity. However, this trend may be slightly amplified by input data uncertainties in high mountain areas, and the results should be interpreted cautiously in data-scarce regions. These findings contribute to a more nuanced understanding of vegetation-runoff interactions at the interannual scale in alpine watersheds under global environmental change, providing critical insights for sustainable water resource management in glaciered regions.

Climate extremes exert detrimental influences on the water retention capacity and carbon sequestration functions of forest ecosystems. However, the response mechanisms of carbon-water cycles and their coupling relationships to climate extremes remain unclear. To address these issues, we investigated in an evergreen forest ecosystem located in Southern China, with comprehensive datasets and machine learning (ML) algorithms, where water-use efficiency (WUE) is defined as the ratio of gross primary production (GPP) to evapotranspiration (ET). The spatial-temporal distribution characteristics of GPP, ET, and WUE, as well as their responses to observed extreme weather events (torrential rains, drought, heat wave and cold wave) and climate extreme indices (CEIs) during 1979-2017 were investigated. We evaluated the accuracy of 8 types of ML algorithms in modelling observed GPP and ET, and the extreme gradient boosting model showed the best performance (GPP: R-2 = 0.91-0.98, ET: R-2 = 0.84-0.98). Regionally averaged annual values indicated significant increasing (p < 0.01) trends for GPP (3.28 gC m(-2) a(-2)), ET (0.62 mm a(-2)), and WUE (0.0023 gC m(-2) mm(-1) a(-1)), with mean annual values exhibiting a gradient increase from the northwest to southeast. Across the 21 CEIs, the precipitation-related indices showed positive correlations with GPP and ET, and the warm (cold)-related temperature indices showed positive (negative) correlations with these fluxes. These fluxes were more sensitive to torrential rains and cold wave, during which the response of ET was more immediate, while the negative impact of cold wave on GPP gradually intensified over time. As a result, WUE initially remained stable but then declined sharply during cold period. Overall, the carbon-water fluxes for evergreen forests on Southern China were most likely to exhibit high risk during cold events. Our findings provide valuable references for the response of evergreen forests to climate extremes.

The springtime Arctic Oscillation (AO), a dominant pattern of atmospheric variability in the extra-tropical Northern Hemisphere, influences the subsequent El Ni & ntilde;o-Southern Oscillation (ENSO) by triggering westerly wind bursts over the equatorial western Pacific. It thereby provides a source of predictability of ENSO. However, the influence of AO on ENSO is not stable in time, the causes of which have not been well addressed. This study shows that the AO-ENSO relationship has exhibited multi-decadal variations that are primarily caused by the Atlantic Multidecadal Variability (AMV). During the negative AMV phases, the strengthening of the Pacific center of the AO induces stronger atmospheric and sea surface temperature anomalies in the subtropical North Pacific. Those anomalies generate pronounced westerly wind anomalies over the equatorial western Pacific via air-sea interaction process, leading to a strengthened impact of the spring AO on ENSO. Observations and North Atlantic Pacemaker experiments confirm the AMV impact on the Pacific center of the AO by changing the strength of the Aleutian Low and the polar vortex. This study highlights the importance of AMV as a key factor controlling the impact of AO on ENSO and tropical climate variability.

Water conservation, a critical ecosystem service, is primarily quantified through water retention (WR), which plays a pivotal role in sustainable socio-economic development and water resources management. However, the absence of multi-temporal modeling of land use and climate change impacts on eco-hydrological processes limits the accurate estimation of WR, particularly in humid regions. This study employed the Soil and Water Assessment Tool (SWAT) model coupled with the water balance principle to estimate WR in the source area of the Xin'an River (SXAR) in China from 2009 to 2017. The multi-temporal variations of WR and its response to climate and land use changes were analyzed through scenario-based hydrological simulations. Results indicated that annual WR ranged from 256.4 mm to 412.7 mm, monthly WR varied between 0 mm and 67.6 mm, and peak daily WR coincided with extreme rainfall events. Precipitation and evapotranspiration were identified as the primary factors influencing WR variability at daily and monthly scales. Spatially, higher WR values were observed in the northeastern SXAR, reflecting the influences of land use patterns and topography. Notably, agricultural land exhibited negative WR during summer months due to crop water storage demands. Overall, climate change exerted more immediate effects on WR at shorter timescales, whereas land use change produced longer-term impacts. This study offers valuable theoretical insights into WR mechanisms of response to environmental changes and provides practical guidance for water resources planning and management in humid and sub-humid regions.

Heat storage change (HSC) is a crucial component of lake's thermal energy budget. Conventional temperature profile based models of HSC require location specific parameters such as lakebed topography. Based on the half-order time-derivative formula of heat fluxes, an analytical model was formulated for estimating HSC from water surface temperature and solar radiation without using geography dependent parameters. The proposed model was tested against field measurements at Poyang Lake, a shallow inland lake, which has pronounced seasonal variations in water level and lake area. Our analysis indicates that the model accurately simulates diurnal HSC with a coefficient of determination of 0.94 and a root mean squared error (RMSE) of 77.5 +/- 21.6 Wm-2 for the study period. Larger nighttime RMSE (75.0 +/- 26.8 Wm-2) than the daytime value (55.1 +/- 19.7 W m-2) is attributable to larger measurement errors of nighttime turbulent fluxes. The estimation of HSC independent of temperature profile and lake-specific parameters by the proposed model facilitates remote sensing monitoring the HSC of global water bodies.

Evaluating the differences in evapotranspiration between urban and surrounding non-urban areas (i.e., ∆ET) has critical implications for urban ecological planning and water resources management. However, it is unclear how the magnitude of changes in ∆ET caused by urbanization varies under different climatic conditions in China. Here, using the remotely ET estimates at 1 km spatial resolution, we firstly estimated the magnitude of changes in ∆ET and then quantified the main driving factors influencing variations in ∆ET of 7 national-level urban agglomerations (UAs) across China during 2003-2020. Results showed that all annual ETurban values were smaller than ETnon-urban of 7 UAs, and the absolute ∆ET values of cities in South China were generally higher than those in North China. There is an apparent effect of urbanization on ∆ET increase in Guanzhong Plain City Group, Central Plain UA and Guangdong-Hong Kong-Macao Greater Bay Area (GHKMGBA), while ∆ET decrease in Chengdu-Chongqing City Group and Yangtze River Delta (YRDUA) were primarily due to the climate change. The suppressing effects of temperature and NDVI on ∆ET decrease in YRDUA were enhanced, and the promoting effect of GDP on ∆ET increase in GHKMGBA was weakened. Considering nonstationary features, urbanization appears to heighten extreme ∆ET by 0.83 %, 4.83 % and 10.39 % under 5-year, 20-year, and 50-year return periods over all the 7 UAs, respectively. Collectively, our findings confirm that urbanization is a significant factor that leads to ∆ET increase, and the factors affecting the response of urban water circulation system need to be deeply decomposed.

Extreme climate occurred frequently in subtropical region, which seriously affects carbon and water fluxes such as evapotranspiration (ET) and gross primary productivity (GPP) of terrestrial ecosystems. The process-based biome biogeochemical cycles (Biome-BGC) model is widely used for simulating carbon and water fluxes of forest ecosystems. However, the lack of the interaction information of climate, vegetation and soil, such as the hysteresis effect, canopy stratification on photosynthesis, impedes better simulations of the ecohydrological processes. Here, we tended to improve the simulation accuracy of Biome-BGC model at a subtropical forest on the Xin’an River in Southeastern China by reconstructing the precipitation series, modifying the ET and canopy multilayers modules, and optimizing the parameters. The spatiotemporal patterns of GPP, ET, water use efficiency (WUE) and their response to environmental factors across the Xin’an River Basin from 1982 to 2018 were further explored. The results showed that the improved model performed well, with the determination coefficient, root means square error and mean absolute error being 0.730, 1.522 gC/m2/d and 1.218 gC/m2/d for GPP, 0.857, 1.082 mm/d and 0.838 mm/d for ET, respectively. Basin-averaged GPP, ET and WUE increased during 1982-2018 and these increasing trends were more pronounced during 1999-2018. Significant positive trends of WUE occurred in the northeast corner. The increasing air temperature and precipitation respectively dominated the increase in GPP and ET, the increasing CO2 concentration and NDVI mitigated the negative effect of extreme precipitation on WUE. Given that human activities such as afforestation have effectively reduced the extent of damage to forest ecosystems from extreme precipitation, we highlight an urgent need to formulate adaptation strategies aimed at reducing the risk of extreme climate in humid regions.

Evapotranspiration (ET) partitioning distinguishes the soil evaporation (E) and plant transpiration (T) components and is crucial for understanding the land-atmosphere interactions and ecosystem water budget. However, the mechanism and controls of ET partitioning for subtropical forests in heterogeneous environments remain poorly understood. Here, we present delta 18O and delta 2H of about 1,527 isotope samples including atmospheric water, soil and plant water during different seasons in 2 years of 2020-2021 from a coniferous forest across Southeast China. We used the isotopic mass balance of ecosystem water pools, the Craig-Gordon model and the Keeling-Plot method to partition T from ET (T/ET) and quantify the controls on T/ET. Results indicated that the uncertainty in the T/ET was principally from the soil water evaporation (delta E) value, about 20-30 cm was found to be a reasonable evaporating front depth for estimating delta E in this coniferous forest. T/ET presented a "U" shape diurnal pattern and varied from 66.7% to 89.9%. Isotope-based T/ET in autumn with high temperatures and little rain was higher than those in the summer and winter seasons. Relative humidity (or vapour pressure deficit) dominated the diurnal T/ET variations (relative contributions of > 40%) in summer and autumn, while air temperature and soil water content were the main controls in winter. Our study also showed that delta 18O-derived T/ET was consistent with that of delta 2H, although delta 2H was found to be more stable in ET partitioning, the dual stable isotope approach should be employed in future studies for the uncertainties brought by samplings or measurements. The agreement between the isotope-based T/ET and ET partitioning approach that uses eddy covariance and sap flux data was stronger at midday. These isotope-inferred ET partitioning can inform land surface models and provide more insights into water management in subtropical forests.

Canopy conductance (g(c)) is a crucial parameter in simulating evapotranspiration and modulating water exchange, but its variation mechanism has regional uncertainties and complex environmental co-controls. In addition, the effect of extreme rainfall on g(c) cannot be ignored under the changing climate. Here, we investigated the variation and environmental controls on g(c) and the effect of extreme rainfall events in a Cunninghamia lanceolata forest across the subtropical area of Southern China. In July 2020, an extreme rainstorm hit the source area of the Xin'an River, with the cumulative rainfall on July 7 and 8 reaching 216.6 mm. The thermal diffusion probe method was used to measure the density of sap flow, and the environmental factors such as air temperature (T-a), net solar radiation (R-n) and soil water content (SWC) were monitored during the growing seasons of 2020 and 2021. Ultimately, g(c) obtained by the Penman-Monteith equation was adopted since the result from the K & ouml;stner equation was overestimated. g(c) showed a unimodal curve on the diurnal scale, and this characteristic was more obvious after the extreme rainfall. Daily g(c) appeared a fluctuating pattern with a maximum in summer. g(c) was simultaneously affected by T-a, R-n, water vapour pressure difference (VPD), SWC, among which T-a was the most significant driving factor at both the diurnal and daily timescales. The regulation of T-a, VPD and SWC on g(c) had obvious thresholds, and the most definite response mode was VPD (2020: 1.25 kPa; 2021: 0.95 kPa). SWC and T-a were the dominant factors after the rainfall period, and the promotion effect of VPD on post-rainy days turned to inhibition effect on typical sunny days. These findings will further reveal the water exchange mechanism between atmosphere and vegetation and impacts of environmental factors in subtropical coniferous forests, especially after the extreme rainfall events.

Understanding future variations and trends of heatwave events has critical implications for the ecosystem and human health. However, the diverse metrics of heatwave affect the comparable assessment of heatwave evolution at regional scales. The inadequate consideration of the enhanced warming trend and local antecedent heat conditions at different climate zones undermines the comprehensive understanding of future heatwave changes. Here, we systematically assess variations and trends in duration, frequency, and intensity of heatwave events in China from 1961 to 2100, using historical observations and climate model simulations from Coupled Model Intercomparison Project Phase 6. The increased rates and trends in the duration and frequency are more evident than those in intensity and severe heatwave days. Regionally, the northern and western regions are projected to suffer longer and more frequent consecutive heatwaves, while southern regions are likely at greater risk of severe heatwave days. A comparison among four scenarios shows that the future heatwave characteristics projected by the high forcing Shared Socioeconomic Pathway (SSP5-8.5) exhibit substantial intensification than those in other three experiments, imposing intractable dangers to numerous organisms and ecosystems. Under the SSP1-2.6, the acceleration of all heatwave characteristics is projected to slow down in all regions after 2040. In addition to maximum temperature, temperature advections are projected to contribute to heatwave intensification in western regions. Our results provide a comprehensive assessment of future variations and trends in heatwave events. The comparable future changes across unevenly developed regions are necessary for improving regional adaptive capacity to extreme heat risk.

为适应水利改革发展新要求,须全面提升水利行业人才队伍的素质,其中提升水利类研究生培养的质量是关键路径之一.河海大学以水利类研究生培养为基础,面向行业智慧化新需求,制定水利类研究生招生具体政策与跨学科生源联合选拔机制;以全员、全过程、全方位育人为指导,深化课程改革、推进教材建设,创建分类培养、学制动态调整、本硕博联动贯通的培养模式;将质量监督和激励机制有机结合,构建"大平台—大项目—大团队"与科研激励制度互馈的保障体系;构建基于理论知识、专业素养、创新能力与综合应用能力"四位一体"动态耦联的水利专业研究生培养质量评价体系,以期为水利类研究生的综合素质提升和创新人才培养质量评价体系优化提供依据.

To clarify the variations of water isotopic composition and mechanism underlying their responses to envi-ronmental factors during water transport and conversion in subtropical forest ecosystems in heavy rain periods,we measured the hydrogen and oxygen stable isotopes of typical species in the subtropical evergreen coniferous forest across the source area of Xin'an River during the East Asian rainy season in 2020.Combined with the environmen-tal factors monitored by the eddy covariance measurements of Huangshan Hydrological Station,we analyzed the di-urnal variation of water isotopic compositions(δ18O and δ2H)in different parts(roots,bark,xylem and leaves)of Cunninghamia lanceolata and the correlation between δ18 O and δ2H in leaf water of other dominant species in 2nd-4th July.The main environmental controlling factors of leaf water δ18O and δ2H in different plants were inves-tigated.The results showed that on the diurnal scale,water isotopic compositions of roots,bark,and xylem were similar and changed gently,while the isotopes in leaf water were most enriched and changed dramatically.Influ-enced by the random heavy rainfall,there was no significant consistency in the diurnal variations in δ18O and δ2H from different sources,showing single peak,single valley and fluctuation in each day of 2nd-4th July respectively.By linear regression of leaf water δ18O-δ2H,the slopes of the transpiration line of five dominant species from high to low were as follows:Woodwardia japonica,Camellia sinensis,Glycine max,Cunninghamia,lanceolata,Phyl-lostachys heterocycla,indicating that water isotope fractionation effect was the strongest in Phyllostachys heterocycla and the weakest in Woodwardia japonica.The environmental controlling factors of δ18O and δ2 H were different among the five species.Soil moisture and soil temperature were the dominant factors affecting δ18O and δ2H in leaf water of Cunninghamia lanceolata and Woodwardia japonica,while air temperature and net radiation were the main factors affecting δ18O and δ2H in leaf water of Camellia sinensis and Glycine max.The δ18O and δ2H in leaf water of Phyllostachys heterocycla were strongly correlated with air temperature,relative humidity,soil temperature,soil moisture,and wind speed.The results are helpful to clarify the eco-hydrological process in humid region and pro-vide data support for further establishing isotope hydrological model.

Seasonal variation of vegetation profoundly affects the water cycle. However, the seasonal divergence of evapotranspiration (ET) sensitivity in response to vegetation variations has not been fully understood. Here we derived an analytical solution to examine the impact of seasonal vegetation changes on ET with an extended Budyko framework based on an improved ET algorithm with improved water balance constraints. Results reveal a clear seasonal divergence of ET sensitivity to vegetation coverage changes across climate regimes and biomes. Generally, the high ET sensitivity to vegetation coverage has a clear north-south shift trajectory from spring to winter. For moderate-humid regions (0.7 < aridity index < 1.0), vegetation exhibits higher importance in altering ET in March-September. While for moderate-dry regions (1.0 < aridity index < 1.4), the sensitivity of ET to vegetation changes is the highest in September-November. Moreover, the spatial-temporal pattern of ET sensitivity to seasonal vegetation changes is different between short vegetation cover and forest. Additionally, negative ET sensitivity to vegetation coverage changes was discovered in regions with seasonal precipitation of less than 500 mm and sparse vegetation coverage (predominant land cover types of grassland, scrubland, and savannas). In summary, our study provides an analytical solution to estimate ET sensitivity to seasonal vegetation changes within the extended Budyko framework. The results highlight the difference in hydrological response to vegetation dynamics across seasons and vegetation types.

It has become increasingly important to quantify carbon and water fluxes due to their roles in global warming and climate change, particularly for the agroecosystems. However, the dynamics of carbon and water fluxes have not been clearly recognized in rotation croplands with complex and changeable climate. Here, the variations of net ecosystem productivity (NEP), evapotranspiration (ET) and the water use efficiency (WUE, defined as NEP/ET), and their responses to the environmental factors were investigated in a wheat-maize rotation cropland across the Huaibei Plain of China over 2013–2015. The total average NEP, ET and average WUE respectively were 489.1 gC m-2, 315.8 kgH2O m-2, 4.4 gC kg-1H2O for wheat and 192.5 gC m-2, 249.0 kgH2O m-2, 3.6 gC kg-1H2O for maize, implying that wheat season sequestered more CO2 than maize season. Spring drought and summer flood affected WUE of wheat and maize, respectively. Daily wheat WUE seemed to be more sensitive to changes in photosynthetically active radiation (PAR), vapor pressure deficit (VPD), soil water content (SWC) and canopy conductance (Gc). PAR was the dominant factor controlling diurnal dynamics of NEP and ET, while the opposite effect of VPD on NEP was recognized. NEP increasing with PAR was limited by high VPD, which obviously when VPD exceeded 2 kPa during the maize season. Maize NEP was limited with VPD under high solar radiation (> 500 μmol m-2 s-1). WUEs of wheat and maize were negatively related to SWC and Gc, and the sensitivity of WUE response to SWC and Gc increased with the increase of PAR or VPD range. Sub-diurnal NEP against PAR, VPD or temperature showed clockwise hysteresis but ET against PAR or windspeed showed counter-clockwise hysteresis, and these hystereses were mainly caused by the interplay between evaporative demand and moisture supply, photosynthesis and carbon allocation of the agroecosystems.

采集 2021 年生长季和非生长季新安江源区常绿针叶林土壤-植物-大气多源水样进行氢氧稳定同位素测试,分析不同来源水分同位素组成(δ18O和δ2 H)的差异及变化特征,评估不同季节多水源采样方案(植物不同部位、土壤不同深度)对蒸散发组分区分的影响程度,进而优化我国南方湿润区森林生态系统蒸散组分区分的氢氧稳定同位素采样方案.结果显示:多源水δ18O和δ2H在土壤-植物的水分传输过程中逐渐富集,非生长季较生长季更为富集.植物各部位水分的动力学分馏强度随着同位素不断富集而逐渐增大.河道水与山泉水同位素组成分布较为接近,大气水汽相较于其他水源明显最为贫化.土壤水同位素组成垂向分布主要呈现三种不同的规律:随深度增加而减小、先增大后减小或先减小后增大.浅层土壤水同位素组成变化范围大于深层土壤水,拐点位于 50-90 cm.由植物各部位与土壤的水同位素组成分布特征及其差异可知符合同位素稳态假设的杉木最佳取样部位为韧皮部.比较基于不同深度土壤蒸发水汽同位素组成δE计算得出的T/ET(蒸腾与蒸散发比率),发现生长季T/ET整体变化量为13.46%,低于非生长季21.42%.即土壤取样深度的变化在相对干冷条件下对T/ET的影响较大,推断出适宜杉木林的土壤取样深度约为 20-30 cm.研究成果可为湿润区半湿润区蒸散发组分区分同位素采样方案设计、蒸散发估算模型构建提供科学依据,并为生态系统蒸散发组分分割、植物蒸腾水分溯源研究奠定有效基础.

AimsThe variability of climatic conditions and complexity of underlying surface conditions in the humid regions of southern China have brought difficulties to the measurement and estimation of evapotranspiration.Tree transpiration is the key component of forest evapotranspiration.The monitoring and measurement of sap flow has become the main method to determine transpiration.Cunninghamia lanceolata forest as a representative vegetation in the source area of Xinʼanjiang River, is crucial to soil and water conservation and climate regulation in the area. MethodsIn order to investigate the controlling mechanism of environmental factors on the change of the sap flow rate (J s ) during the growing season of C. lanceolata (April to September 2020), the J s of C. lanceolata were monitored by the sap flow measurement system and environmental observations and soil water content were measured by the meteorological gradient tower in the source area. Important findingsThe J s of C. lanceolata had obvious seasonal variations with the largest in August and the lowest in May.Among the environmental factors, net solar radiation (R n ) and vapor pressure deficit (VPD) were the strongest factors correlating with J s .The results of principal component analysis indicated that the variance contribution rates of the first principal component were 59.1% and 57.9% at the hourly and daily scales, respectively.Furthermore, VPD and R n played a major role in the first principal component and were the main environmental factors affecting the change of the sap flow rate of C. lanceolata in the study area.During the

The Beijing-Tianjin-Hebei (BTH) region has encountered increasingly severe and frequent haze pollution during recent decades. This study reveals that El Nino-Southern Oscillation (ENSO) has distinctive impacts on interannual variations of haze pollution over BTH in early and late winters. The impact of ENSO on the haze pollution over the BTH is strong in early winter, but weak in late winter. In early winter, ENSO-related sea surface temperature anomalies generate double-cell Walker circulation anomalies, with upward motion anomalies over the tropical central-eastern Pacific and tropical Indian Ocean, and downward motion anomalies over the tropical western Pacific. The ascending motion and enhanced atmospheric heating anomalies over the tropical Indian Ocean trigger atmospheric teleconnection propagating from the north Indian Ocean to East Asia, and result in the generation of an anticyclonic anomaly over Northeast Asia. The associated southerly anomalies to the west side lead to more serious haze pollution via reducing surface wind speed and increasing low-level humidity and the thermal inversion. The strong contribution of the Indian Ocean heating anomalies to the formation of the anticyclonic anomaly over Northeast Asia in early winter can be confirmed by atmospheric model numerical experiments. In late winter, vertical motion and precipitation anomalies are weak over the tropical Indian Ocean related to ENSO. As such, ENSO cannot induce a clear anticyclonic anomaly over Northeast Asia via atmospheric teleconnection, and thus has a weak impact on the haze pollution over BTH. Further analysis shows that stronger ENSOinduced atmospheric heating anomalies over the tropical Indian Ocean in early winter are partially due to higher mean SST and precipitation there. SIGNIFICANCE STATEMENT: There exist large discrepancies regarding the contribution of El Nino-Southern Oscillation (ENSO) events to the wintertime haze pollution over North China. Several studies have indicated that ENSO has a weak impact on the haze pollution over North China. However, some studies have argued that ENSO events can exert impacts on the occurrence of haze pollution over North China. In this study, we present evidence to demonstrate that ENSO has distinctive impacts on interannual variations of the haze pollution over the BeijingTianjin-Hebei (BTH) region in North China in early and late winters. Specifically, ENSO has a strong impact on the haze pollution over BTH in early winter, whereas the impact of ENSO on the haze pollution over BTH is fairly weak in late winter. Results of this study could reconcile the discrepancy of previous studies about the impact of ENSO on the haze pollution over North China.

This study reveals a close connection between interannual variation of the Somalia Jet (SMJ) intensity in boreal spring and the northwest-southeast movement of the South Asian High (SAH) in the following summer based on multiple datasets and numerical experiments. It is found that the summer SAH tends to shift northwestward (southeastward) when the preceding spring SMJ is stronger (weaker). There are two ways by which the spring SMJ intensity affects the following summer SAH. One is via modulating sea surface temperature (SST) in the tropical Indian Ocean and the other is through modulating anomalous heating associated with the Indian summer monsoon rainfall. On one hand, increase in the spring SMJ intensity enhances southwesterly monsoon winds and upward latent heat flux and leads to SST decrease in the tropical western Indian Ocean. The tropical western Indian Ocean cooling further leads to a decrease (increase) in upper-level geopotential height to the southeastern (northwestern) side of the SAH, inducing a northwestward movement of the SAH. On the other hand, increase in the spring SMJ intensity strengthens the Indian summer monsoon and enhances rainfall and atmospheric heating over the Indian subcontinent. The enhanced Indian subcontinent heating induces strong upper-level positive geopotential height to the northwestern side of the SAH, contributing to a northwestward shift of the summer SAH. Results of this study indicate that variation of the spring SMJ intensity is an effective predictor in the prediction of the northwest-southeast movement of the SAH in the following summer.

Accurate estimation of global evapotranspiration (ET) is critical to understand the water and energy cycles in the Earth system. Satellite-driven ET algorithms serve as an effective way to estimate the global ET. However, many algorithms have been designed independently of water balance constraints, which potentially limit their ability to estimate ET in water-limited and high interception regions. As ET remains one of the most uncertain terms in the global water budgets, incorporating water balance constraints into algorithms should improve the performance of ET estimates. In this study, we developed a general solution (denoted PEW) based on the proportionality hypothesis to incorporate available water control into the widely used Priestley Taylor-Jet Propulsion Laboratory (PT-JPL) ET algorithm. Simulated performances of the PEW model and PT-JPL algorithm were evaluated against 106 FLUXNET eddy covariance (EC) towers data at the site scale. Meanwhile, model results were compared at the global scale with the means of the widely used ET products. We found that the PEW model has smaller errors than the original PT-JPL algorithm, with the greatest improvements in water-limited regions and areas characterized by the high interception. Moreover, by incorporating the water balance constraints into the ET algorithm, the PEW model has the ability to distinguish variations in ET affected by El Nino-Southern Oscillation. In summary, our study offers a convincing evidence regarding the incorporation of water balance constraints into remote sensing algorithms for more accurately mapping global terrestrial ET with an enhanced understanding of ET variation under climate change. This model is the first of its kind among remote-sensing models to provide global land ET estimation with the proportionality hypothesis-based water balance constraints.

Hysteresis between sub-diurnal actual evaporation (AET) (or one of its components, transpiration) and vapor pressure deficit (VPD) at the species or individual ecosystem level has been extensively studied, but the global variation and seasonal variability of this hysteresis across biomes and climates is yet to be fully explored and the limiting mechanisms remain unclear. We hypothesize that the sub-diurnal AET-VPD hysteresis results from the interplay between evaporative demand and soil moisture supply limitations. To test our hypothesis, we quantify the sub-diurnal AET-VPD hysteresis across a broad range of biomes and climates based on the observations from the 89 FLUXNET sites (703 site-years) across the globe. We find that the magnitude of hysteresis varies with biomes and climates and is mostly attributable to evaporative demand limitation in all ten sampled biomes. In seasonally dry locations, however, low soil moisture availability amplifies the hysteresis during the dry season. Sensitivity analysis using a hydraulic model suggests that most ecosystems exhibiting seasonal drought display a more isohydric behavior during the dry season, while shift toward a more anisohydric response during the wet season. Our findings have important implications for understanding sub-diurnal dynamics between vegetation and its surrounding environment, reducing uncertainties in AET simulation at fine spatial and temporal scales, and improving understanding of the ecosystem response to hydrologic stress.