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Precipitation is a critical part of the global hydrological cycle that determines the distribution of water resources. It is also an essential meteorological variable used as input for hydroclimatic models and projections. However, precipitation data frequently lack complete series, especially at daily and sub‐daily precipitation stations, which are usually large, bulky, and complex. To address this, gap filling is commonly used to produce complete hydrometeorological data series without missing values. Several gap‐filling methods have been developed and improved. This study seeks to fill the gaps of 201 daily precipitation time series in Central Italy by localizing the approach used to generate the Serially Complete dataset for the Planet Earth (SC‐Earth). This method combines the outcome of 15 strategies based on four various gap‐filling techniques (quantile mapping, spatial interpolation, machine learning, and multi‐strategy merging). These strategies employ the daily dataset of the neighbouring stations and the matched ERA5 data to estimate missing values at the target stations. Both raw data and the final serially complete station datasets (SCDs) underwent comprehensive quality control. Many accuracy indicators have been utilized to evaluate the performance of the strategies' estimations and the final SCD, such as Correlation Coefficient (CC), Root mean square error (RMSE), Relative bias (Bias %), and Kling‐Gupta efficiency (KGE″). Multi‐strategy merging strategy based on the Modified Kling‐Gupta efficiency (MS1) shows the highest performance as an individual precipitation gap‐filling strategy. However, the machine learning strategy using random forest (ML3) has the most outstanding share in the final estimates among all other strategies. In the end, the temporal–spatial performance of the final SCD is promising and depends on the pattern of the missing values (MV%). The mean values of KGE″, CC, variability (α), and bias term (β) are 0.9, 0.93, 1.064, and 4.98 × 10−7, respectively. [ABSTRACT FROM AUTHOR]

The Thar is the most densely populated desert in the world, which supports diverse ecosystems and human endeavours such as agriculture and socioeconomic activities. Water demand and supply in the Thar play an essential role in regulating the socioeconomic activities of the region. Inland water and precipitation aid the movement of water in the Thar Desert. Precipitation in the Thar is governed by the Indian Summer Monsoon (ISM), during which the winds distribute water vapour to regulate precipitation across the region. Therefore, we analyse the water vapour, its sources and its relation with precipitation using satellite measurements and reanalysis data in the Thar during ISM. Like other regions, a clear seasonal cycle of water vapour is observed in the Thar, with very high values (> 45 kg/m2) during ISM and low in winter (< 15 kg/m2). Evapotranspiration and moisture transport have significant effects on the amount of water vapour during ISM. There is a significant increase in water vapour in the troposphere, with high trends at the surface (0.032 g/kg/year) and small at the tropopause (0.00002 g/kg/year). A significant increase in column water vapour is also estimated in the Thar during ISM, with high trends in the eastern and southern areas, at about 0.15–0.35 kg/m2/year. The rise in water vapour in the Thar can be attributed to the increase in evapotranspiration (0.03–0.07 mm/day/year) and water vapour transport (> 0.5 kg/m/s/year) from the Arabian Sea and Indian Ocean. The rise in water vapour can lead to an increase in precipitation in the Thar, as it shows significant positive trends (0.05–0.1 mm/day/year) in the eastern areas during ISM. The increase in precipitation and water vapour in the arid Thar Desert can have significant implications for the regional environment and agriculture. [ABSTRACT FROM AUTHOR]

Precipitation changes in full response to CO2 increase are widely studied but confidence in future projections remains low. Mechanistic understanding of the direct radiative effect of CO2 on precipitation changes, independent from CO2‐induced SST changes, is therefore necessary. Utilizing global atmospheric models, we identify robust summer precipitation decreases across North America in response to direct CO2 forcing. We find that spatial distribution of CO2 forcing at land surface is likely shaped by climatological distribution of water vapor and clouds. This, coupled with local feedback processes, changes in convection, and moisture supply resulting from CO2‐induced circulation changes, could determine North American hydroclimate changes. In central North America, increasing CO2 may decrease summertime precipitation by warming the surface and inducing dry advection into the region to reduce moisture supply. Meanwhile, for the southwest and the east, CO2‐induced shift of subtropical highs generates wet advection, which might mitigate the drying effect from warming. Plain Language Summary: How precipitation changes in full response to increased CO2 remains unclear. Mechanistic understanding of how increasing CO2 alone changes precipitation can help us better predict future precipitation in full response to CO2 increase. We find that the precipitation responses are much stronger during summer than winter in North America. During summer, precipitation significantly decreases in central North America in response to the direct CO2 radiative effect, while in the southwest and the east, precipitation changes are small. There might be stronger longwave radiation forcing near the surface induced by CO2 increase in arid regions due to weaker masking effect of water vapor and clouds. This, along with local feedbacks, significantly warms the central region. Meanwhile, the direct forcing of CO2 induces northward shifts in subtropical highs, consequently generating anticyclonic anomalies. These wind anomalies result in drier air advected into central North America, leading to moisture divergence and hence reducing moisture supply. The reduced water supply, coupled with the warming, may decrease precipitation in the region. For the southwest and the east, the anticyclonic anomalies cause wetter air advected into the regions and generate moisture convergence, which increases moisture supply and might mitigate the drying effect caused by CO2‐induced warming. Key Points: Robust precipitation decreases during summer in response to CO2 direct radiative effect are identified in central North AmericaClimatology and changes of hydrological environment may collectively modulate the regional CO2 radiative effect on summer precipitationCO2‐induced circulation changes could alter the moisture supply to reshape the regional hydrological cycle [ABSTRACT FROM AUTHOR]

This study investigates the specific circulation anomalies that have sustained the low Antarctic sea ice state since 2016. Firstly, we find a significant strengthening and southward shift in the Ferrel Cell (FC) during 2016–2022, resulting in a marked increase in southward transport of heat and moisture. Secondly, this enhanced FC is closely associated with a stronger mid‐latitude wave pattern. This pattern is zonally asymmetric and greatly amplifies the poleward advections of heat and moisture, leading to the increased downward longwave radiation, more liquid precipitation and sea ice retreat in specific regions, including the western Pacific and Indian Ocean sectors, Ross and northern Weddell Seas. The mechanism deduced from the short‐term period is further supported by the results of 40 ensemble members of simulations. The southward expansion of the FC and sea ice decline are closely linked to La Niña‐like conditions but may also be driven by anthropogenic global warming. Plain Language Summary: Following the sudden decline in 2016, the Antarctic sea ice extent has persisted at historically low levels. In 2023, it reached unprecedented record lows. However, the specific atmospheric circulation anomalies that have sustained the Antarctic sea ice at low levels are still unknown. It is well‐established that the Ferrel Cell, a mid‐latitude atmospheric meridional circulation, plays a pivotal role in the energy exchange between the high‐ and mid‐latitudes. Our findings indicate that the enhanced Ferrel Cell zonally intensified southward transport of heat and moisture over the sea ice regions, which sustains the overall low Antarctic sea ice state. Additionally, in the horizontal plane, the enhanced mid‐latitude wave pattern is responsible for the regional sea ice retreat over the western Pacific sector, Ross Sea, Indian Ocean sector, and northern Weddell Sea, and is also closely associated with the enhanced Ferrel Cell. The effects of the enhanced Ferrel Cell on Antarctic sea ice decline are further supported by the results of large ensemble simulations. Therefore, this study suggests that concurrent with the southward shifting of the Ferrel Cell, the stronger warm and moist air intrusions, and the increased liquid precipitation, restrict the Antarctic sea ice expansion following its sudden decline. Key Points: Since 2016, the low Antarctic sea ice extent has persisted, consistent with heat and moisture accumulation over the sea ice edgesThe Ferrel Cell was enhanced and shifted southward, leading to the increased southward heat/moisture advection, and liquid precipitationThe effects of the enhanced Ferrel Cell on Antarctic sea ice decline are further supported by the results of large ensemble simulations [ABSTRACT FROM AUTHOR]

Precipitation is one of the main components of the hydrological cycle and its precise quantification is fundamental to providing information for the understanding and prediction of physical processes. Precipitation observations based on ground‐based devices (manual and automatic rain gauges) are highly accurate but have limited spatial coverage. On the other hand, remote sensing products cover large areas but with lower accuracy. In this context, this study aims to provide a more accurate monthly precipitation estimating product, with lower latency than other products but without directly relying on field data. The methodology consists of applying a machine learning method (k‐nearest neighbours algorithm) to satellite‐based remote sensing data (IMERG Early Run product) and re‐analysis‐based (MERRA‐2) variables with a particular connection to precipitation. The method was applied over the Brazilian territory, which features a large range of precipitation regimes. This methodology resulted in the development of an adjusted IMERG product (IMERG BraMaL). Compared with the original IMERG products (Early Run and Final Run), IMERG BraMaL has improved the evaluated metrics between ground‐based and satellite data in almost all analyses. For instance, KGE (Kling‐Gupta efficiency) went from lower values (0.70 and 0.82 for Early and Late Run, respectively) to values above 0.86 in the IMERG BraMaL. The adjusted product also presented superior performance statistics compared with other global precipitation products (CHIRPS, PERSIANN‐CDR, and MSWEP). The main advantages of IMERG BraMaL compared with IMERG Final Run are (i) much faster availability to the end‐users; (ii) non‐dependency on any field data, allowing its application in areas where rain gauge data is unavailable or of low quality; (iii) the non‐relationship of errors to local features; and (iv) the much‐improved estimations in regions in Brazil where, historically, satellite‐based products usually underestimate the observed data. [ABSTRACT FROM AUTHOR]

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]

Changes in precipitation and its causes under future warming scenarios in Northwest China are of great concern. Based on the dynamical downscaling results of the Weather Research and Forecasting model (WRF), this study quantitatively identified the contribution of local evaporation and external moisture transport to future precipitation changes in western and eastern Northwest China (WNWC and ENWC) by calculating the precipitation recycling ratio (PRR). The results showed that the WRF could reasonably reproduce the observed spatial and temporal distribution of precipitation and evaporation during the historical reference period of 1985–2014. Under the 1.5 and 2.0°C stabilized warming scenarios from 2071 to 2100, there is a stronger precipitation growth in WNWC than in ENWC, and the PRR generally increases in WNWC and decreases in ENWC. Further analysis indicates that external moisture transport is the dominant contributor to the increased precipitation in all cases with its contribution exceeding 70%, while the difference of precipitation growth in two sub‐regions arises from the summer moisture transport at the southern boundary as the inflow in WNWC and outflow in ENWC. Compared to the negligible contribution of evaporation in ENWC (less than 7%), evaporation contributes more than 23% to the precipitation increase in WNWC under future warming scenarios, which may be related to the strong land‐atmosphere coupling there. Furthermore, an additional warming of 0.5°C leads to an increase in precipitation for both sub‐regions, which is mainly due to the contribution of external moisture transport. Plain Language Summary: In this study, we discuss the relative contributions of evaporation and moisture transport to precipitation changes in Northwest China under 1.5/2.0°C stabilized warming scenarios. With Northwest China (NWC) dividing it into two sub‐regions of western and eastern parts, we find that although the western NWC has less precipitation during the reference period of 1985–2014, the increase in precipitation is about twice that of the eastern NWC under the warming scenarios. The contribution of evaporation to the increased precipitation is greater in the western NWC compared with the reference period, which may indicate the accelerating hydrological cycle in western NWC. Moisture transport is the main contributor to the increase in precipitation and is also the main reason for the difference in precipitation changes between the two sub‐regions, mainly due to differences in summer moisture transport across the southern boundary. This work provides a scientific basis for assessing water resources in Northwest China under future warming scenarios. Key Points: External moisture transport contributes more than 70% of precipitation in Northwest China, both in terms of mean and variabilityContribution of evaporation to the precipitation increase is stronger in western Northwest China, due to its strong land‐atmosphere couplingThe difference in moisture transport between the two regions is mainly due to changes in southern border moisture transport in summer [ABSTRACT FROM AUTHOR]

Global climate change is considered one of the greatest environmental threats in the world. It is expected to significantly change the global hydrological cycle. The two main water cycle components, potential evapotranspiration (PET) and precipitation (P), are closely related to vegetation dynamics. In this study, the partial correlation analysis method was used to analyzed the relationship between Normalized Difference Vegetation Index (NDVI) and climate factors (PET and P) based on grid cells. PET was calculated by FAO-56 Penman-Monteith method. Moreover, we also investigated the NDVI and climate factors in different vegetation cover types. The results showed that grassland, forest and cropland in China were positively correlated with PET and P. The time scales of the maximum partial correlation coefficients between NDVI and PET of grassland vegetation were mostly longer than 5-6 months. These time scales were longer than the time scales related to P. The partial correlation coefficients between NDVI and PET, P of forest vegetation were higher in northern China, whereas the spatial distribution of related time scales was the opposite. The partial correlation coefficients between NDVI and PET, P of forest vegetation were higher in northern China. However, the spatial distribution of related time scales was the opposite. The correlations between NDVI and PET, P of cropland vegetation and the time scales related to PET had clear spatial heterogeneity. The time scale of the correlation between NDVI and P for cropland in the northern China was about 2 months. P had a strong influence on the growth of various types of vegetation in the study area, and grassland vegetation was affected by P over the shortest time scale. We compare and analyze the results of this study with other related studies. These results provide a reference for exploring the dynamic changes in different vegetation types and factors impacting them. [ABSTRACT FROM AUTHOR]

The Asian water tower (AWT) serves as the source of 10 major Asian river systems and supports the lives of ~2 billion people. Obtaining reliable precipitation data over the AWT is a prerequisite for understanding the water cycle within this pivotal region. Here, we quantitatively reveal that the "observed" precipitation over the AWT is considerably underestimated in view of observational evidence from three water cycle components, namely, evapotranspiration, runoff, and accumulated snow. We found that three paradoxes appear if the so-called observed precipitation is corrected, namely, actual evapotranspiration exceeding precipitation, unrealistically high runoff coefficients, and accumulated snow water equivalent exceeding contemporaneous precipitation. We then explain the cause of precipitation underestimation from instrumental error caused by wind-induced gauge undercatch and the representativeness error caused by sparse-uneven gauge density and the complexity of local surface conditions. These findings require us to rethink previous results concerning the water cycle, prompting the study to discuss potential solutions. [ABSTRACT FROM AUTHOR]

A substantial subject for the hydrological cycle, engineers must be able to determine the amount of rainfall in order to design structures and dams that deal with collection, transport and storage runoff. The study provides information on the amount of rainfall (measured in millimeters) that occurred annually from 1991 to 2021 in a single meteorological station in Iraq, specifically Babylon. The distributions of observed frequency are described, and the study attempts to fit three theoretical distributions (Gamma, Log Normal, and Normal) to the data. The distributions and tests chosen for the study play crucial roles in statistical analysis. The Normal distribution, a fundamental pattern in statistics, helps identify common trends in data and is a key part of quality control processes. It is often taught early in statistical education due to its significance in understanding natural variations and environmental factors. The Gamma distribution is widely used in statistics to model time durations for tasks or events. The Log-Normal distribution describes a variable whose logarithm follows a normal distribution. Chi-square test is a statistical method to compare expected and observed outcomes across different categories, commonly employed in survey analysis. The Kolmogorov-Smirnov test compares distributions of two independent samples, useful for evaluating how well a theoretical distribution fits actual data. Researchers use this test under similar conditions as the Chi-square test. The Kolmogorov-Smirnov and Chi-Square and Anderson-Darling indices where, the calculated value of nonparametric test (statistic value) is extract and compared with the tabular value (critical value) based on the significant (α) and degrees of freedom, if the calculated value is less than the tabular value, we accept the null hypothesis (good fit); otherwise, we do not accept the null hypothesis (poor fit). They are used to compare the theoretical distributions to the observed data. The study then focuses on the Intensity-Duration-Frequency (IDF) curves for extreme rainfall values, with durations of 15, 30, and 60 minutes. The results reveal that rainfall intensity decreases as the duration of the storm increases. Additionally, rainfall of a specific duration shows higher intensity if the return period is greater. Gumbel's extreme value distribution, Normal distribution, and Log Normal distribution are used to fit rainfall data with 5, 10, 15, and 50-year return periods. The Excel Software showed that the lognormal, normal, and Gamma probability distributions were the best fit for the data group for all durations. The software estimated the intensities of precipitation for return periods of 5, 10, 15, and 50 years, and the Log Normal distribution presented as the good agreement. [ABSTRACT FROM AUTHOR]

Convergence zones (CZs) are known drivers of precipitation regimes from regional to planetary scales. However, there is a scarcity of accounts of the contribution of CZs to the global precipitation. In this study, we build upon a recently developed Lagrangian diagnostic to attribute precipitation to CZ events in observations and simulations submitted to the Coupled Model Intercomparison Project 6 (CMIP6). Observed CZs are identified using ERA5 reanalysis wind and attributed precipitation from observational products based on satellite estimates and rain gauges. We estimate that approximately 54% (51%–59%, depending on the precipitation product) of global precipitation falls over CZs; in some regions, such as the Intertropical Convergence Zone (ITCZ) and subtropical monsoon regions, this proportion is greater than 60%. All CMIP6 simulations analyzed here attribute about 10% more precipitation to CZ events than what the observations suggest. To investigate this overestimation, we decompose the precipitation error in terms of frequency and intensity of CZ precipitation and find that all models present a substantial positive bias in the frequency of CZ precipitation, suggesting that climate models trigger precipitation too easily in regions of airmass confluence; such positive frequency biases in CZ precipitation help explaining well‐known biases in climate models, such as the double‐ITCZ in the Pacific. We also find that models with better mass conservation present an apportionment of CZ precipitation closest to the observational estimates, demonstrating the relevance of mass conservation in advection schemes. Plain Language Summary: Rain is crucial for human and animal livelihoods. In the Earth's atmosphere, rain often occurs in organized cloud bands of hundreds or thousands of kilometers lengthwise. This type of organized rain is usually denominated as occurring within a convergence zone (CZ). In this study, we use a recently developed method to identify these CZs and apply it to observational data to find out how much of Earth's rain falls in regions under the influence of CZs (approximately 54%). We repeat this exercise in climate model data and find that all models overestimate rain in regions under the influence of CZs by about 10%. Our results point to the importance of CZs for the global hydrological cycle and ways in which climate models need improvement to better simulate CZ rainfall. Key Points: Approximately 54% of global precipitation falls over convergence zonesClimate models overestimate this ratio by approx. 10%Conservative moisture advection schemes seem to alleviate this overestimation [ABSTRACT FROM AUTHOR]

Moisture sources and transport processes play a critical part in hydrological cycle and determine regional precipitation. This paper utilizes the Water Accounting Model‐2layers (WAM‐2layers) and the ERA5 reanalysis data to track the sources of precipitation over the Pearl River Basin (PRB). The contribution of external moisture and the role of local recycling are investigated. The results show that during the period from 1980 to 2020, oceanic sources including the western North Pacific and Indian Oceans serve as the primary moisture sources of precipitation over the PRB. The contributions to total seasonal precipitation are respectively 62.57% in MAM, 54.79% in JJA, 43.70% in SON and 60.88% in DJF. By contrast, the contribution of local recycling is generally below 5.50%. In the dry years of 1994, 1997 and 2001, the contribution of terrestrial sources is about 19.22%; in the wet years of 1989, 2009 and 2011, the contribution is about 16.31%. The summer precipitation anomalies are mainly attributable to moisture anomalies from the Equatorial Indian Ocean in the wet years and from Southeast Asia in the dry years. Furthermore, vertically integrated moisture flux anomalies over the boundaries of the PRB are generally the result of anomalous wind rather than anomalous moisture. In the wet years, low‐pressure systems induce strong cyclonic moisture transports, increasing the PRB precipitation. In the dry years, high‐pressure anomalies over the PRB block the moisture transports from the Indian Ocean and western North Pacific. [ABSTRACT FROM AUTHOR]

Accurate climatic data, especially precipitation measurements, play a critical role in various studies concerning the water cycle, particularly in modeling flood and drought risks. Unfortunately, these datasets often suffer from temporary gaps that are randomly dispersed over time. This study aims to assess the effectiveness of three imputation methods: KNN, MICE, and missForest, in impute missing values in climate series. The evaluation is conducted in two distinct rainfall regimes: the Moulouya basin and the Sous Massa basin. The performance analysis considers the percentage of missing data across the entire dataset. The imputed datasets are used to estimate annual precipitation, which are then subjected to statistical tests to identify potential trends and detect changepoints. The analysis focuses on the precipitation series within the Souss Massa watershed, encompassing 27 rainfall stations. Results indicate that data imputation has a highly positive impact on the study of rainfall series trends and change point detection. The study found that studying trends without data imputation could lead to questionable conclusions. The most significant breakpoints detected in the analyzed rainfall series were in the years 1988, 1991, 1997, 2007, and 2010. The decrease in precipitation at stations showing a downward trend varies between -60 mm and -137 mm using the MICE method, and between -40 mm and 186 mm using the missForest method. [ABSTRACT FROM AUTHOR]

The high latitude Southern Hemisphere (SH) is an important region for Earth's climate. Ocean heat content, cryosphere interactions, Antarctic bottom water development and the cloud‐albedo feedbacks need to be understood to form a complete picture of the climate system. However, the high latitude SH is one of the most under‐observed regions due to its remoteness. The advent of satellites and reanalyses have improved our monitoring of this region. Some previous studies observed an increase in precipitation over the SH high latitudes, however we argue that some of the trends in commonly used data sets may be artifacts. We use regression analysis of trends in precipitation and the Southern Annular Mode to contrast these relationships in satellite and reanalysis products, and to evaluate precipitation over the SH. We suggest that sensor changes and the lack of in situ data available for calibration may be responsible for unusual precipitation patterns especially around 65°S. Plain Language Summary: Many important processes in the Earth's climate occur at high latitudes in the Southern Hemisphere. However, due to its remoteness and inhospitable conditions, scientists have trouble obtaining data for this region. Satellites have helped to provide information about this area but are not well constrained due to a lack of in situ data. Sensor changes and the launch of new satellites means that the data can vary in quality and reliability over time. By comparing precipitation trends over the Southern Hemisphere with known climate patterns, we suggest that an observed increase in precipitation over the Southern Hemisphere high latitudes may be due to variations in the satellite technology rather than a physical increase in precipitation. This is important for understanding the impacts of climate change on Earth's water cycle and heat storage. Key Points: High latitude precipitation trends are likely artifactsSensor changes may be responsible for spurious trends in the Southern OceanSatellite products do not agree on the zonal mean precipitation pattern in the Southern Hemisphere [ABSTRACT FROM AUTHOR]

Shifts in Southern Ocean (SO, 40–85°S) shortwave cloud feedback (SWFB) toward more positive values are the dominant contributor to higher effective climate sensitivity (ECS) in Coupled Model Intercomparison Project Phase 6 (CMIP6) models. To provide an observational constraint on the SO SWFB, we use a simplified physical model to connect SO SWFB with the response of column‐integrated liquid water mass (LWP) to warming and the susceptibility of albedo to LWP in 50 CMIP5 and CMIP6 GCMs. In turn, we predict the responses of SO LWP using a cloud‐controlling factor (CCF) model. The combination of the CCF model and radiative susceptibility explains about 50% of the variance in the GCM‐simulated SWFB in the SO. Observations of SW radiation fluxes, LWP, and CCFs from reanalysis are used to constrain the SO SWFB. Observations suggest a SO LWP increase in response to warming and albedo susceptibility to LWP that is on the lower end relative to GCMs. The overall constraint on the contribution of SO to global mean SWFB is −0.168 to +0.051 W m−2 K−1, relative to −0.277 to +0.270 Wm−2 K−1. In summary, observations suggest SO SWFB is less likely to be as extremely positive as predicted by some CMIP6 GCMs, but more likely to range from moderately negative to weakly positive. Plain Language Summary: Previous studies suggest that SO clouds reflect more sunlight in response to global warming and more strongly cool the planet ‐ a negative shortwave cloud feedback (SWFB). The SO SWFB in the latest generation of global climate models (GCMs) participating in the Coupled Model Intercomparison Project Phase 6 (CMIP6) has shifted toward more positive values, leading to the larger predicted temperature responses to greenhouse gas increases in these GCMs. In this study, we examine if this more positive SWFB is consistent with observations. We connect the effect of SO clouds on reflected sunlight with the predicted response of cloud liquid content to global warming. The linkage between cloud liquid water content and large‐scale meteorology is applied to predict this cloud liquid response. Satellite observations of reflected sunlight, cloud liquid, and observations of large‐scale meteorology are applied to constrain the SO SWFB for 50 CMIP5 and CMIP6 GCMs. The results suggest that SO cloud liquid will increase with warming around the average of predictions of 50 GCMs. Satellite records suggest that SO SWFB is moderately negative to weakly positive, instead of extremely positive or negative as suggested by some GCMs. Key Points: Southern Ocean liquid water path increased over the past two decades due to enhanced moisture convergenceEnhanced moisture convergence contributes to a negative cloud feedback in the Southern OceanAcross global climate models, the sensitivity of upwelling shortwave to cloud opposes the sensitivity of cloud to moisture convergence [ABSTRACT FROM AUTHOR]

Large satellite discrepancies and model biases in representing precipitation over the Southern Ocean (SO) are related directly to the region's limited surface observations of precipitation. To help address this knowledge gap, the study investigated the precipitation characteristics and rain rate retrievals over the remote SO using ship‐borne data of the Ocean Rainfall And Ice‐phase precipitation measurement Network disdrometer (OceanRAIN) and dual‐polarimetric C‐band radar (OceanPOL) aboard the Research Vessel (RV) Investigator in the Austral warm seasons of 2016–2018. Seven distinct synoptic types over the SO were analyzed based on their radar polarimetric signatures, surface precipitation phase, and rain microphysical properties. OceanRAIN observations revealed that the SO precipitation was dominated by drizzle and light rain, with small‐sized raindrops (diameter <1 mm) constituting up to 47% of total accumulation. Precipitation occurred most frequently over the warm sector of extratropical cyclones, while concentrations of large‐sized raindrops (diameter >3 mm) were prominent over synoptic types with colder and more convectively unstable environments. OceanPOL observations complement and extend the surface precipitation properties sampled by OceanRAIN, providing unique information to help characterize the variety of potential precipitation types and associated mechanisms under different synoptic conditions. Raindrop size distributions (DSD) measured with OceanRAIN over the SO were better characterized by analytical DSD forms with two‐shape parameters than single‐shape parameters currently implemented in satellite retrieval algorithms. This study also revised a rainfall retrieval algorithm for C‐band radars to reflect the large amount of small drops and provide improved radar rainfall estimates over the SO. Plain Language Summary: Precipitation is a major component of the hydrologic cycle in high‐latitude regions including the remote Southern Ocean (SO). However, large differences continue to exist among current precipitation products in the region, owing in part to the absence of high‐quality surface observational records suitable for evaluation across a range of temporal and spatial scales. This work uses two instruments aboard the RV Investigator over the Australian sector of the SO in the Austral warm seasons of 2016–2018: the OceanRAIN disdrometer and OceanPOL radar. We found variability in radar features and surface precipitation properties among seven distinct synoptic conditions over the SO. This work also discussed two important findings related to remote sensing retrievals of SO rain. First, we demonstrated why the rainfall retrieval assumptions in satellite algorithms may need to be refined to account for the unique rainfall properties in the SO. Second, we formulated a new set of equations suitable for shipborne C‐band radars in improving rain rate estimates over the region. This work leads toward more accurate, high‐resolution estimates of precipitation over the measurement‐sparse SO to better understand a range of climatological and meteorological processes in the region. Key Points: Different synoptic types across the Southern Ocean exhibit distinctive polarimetric signatures and surface precipitation propertiesSmall raindrops of less than one millimeter contribute up to 47% of total accumulation during the Austral warm seasons over the regionA new formulation for radar rainfall estimates that reflects the large numbers of small drops over the Southern Ocean is proposed [ABSTRACT FROM AUTHOR]

Precipitation is a fundamental component of the water cycle. Satellite‐derived precipitation estimates with high spatial resolution and daily to subdaily temporal resolution become very important in regions with a limited ground‐based measurement network, such as southeastern South America (SESA). This study evaluates the performance of four state‐of‐the‐art satellite products, including IMERG V.06 Final Run, PERSIANN, PERSIANN CCS‐CDR and PDIR‐NOW in representing observed precipitation over SESA during the 2001–2020 period. The ability of each product to represent observed annual and seasonal precipitation patterns was assessed. Statistical and categorical evaluation metrics were used to evaluate the performance of satellite precipitation estimates at monthly and daily timescales. Our results report that IMERG and CCS‐CDR achieve the best performance in estimating observed precipitation patterns at annual and seasonal timescales. While all satellite products effectively identify autumn and spring precipitation patterns, they struggle to represent winter and summer patterns. Notably, all satellite precipitation products have a better agreement with observed precipitation in wetter regions compared to drier regions, as indicated by the spatial distribution of continuous validation metrics. IMERG stands out as the most accurate product, reaching the highest correlation coefficients (0.75 < CC < 0.95) and Kling–Gupta efficiencies (0.65 < KGE < 0.85, rate as good to very good performance). Regarding categorical statistical metrics, IMERG correctly estimates the fraction of observed rainy days (POD > 0.7, CSI > 0.6) and shows the lowest fraction of estimated precipitation events that did not occur. PERSIANN, CCS‐CDR and PDIR‐NOW exhibit lower performances, mainly in drier areas. Moreover, PERSIANN and PDIR‐NOW tend to overestimate observed precipitation in almost the entire SESA region. We expect this validation study will provide greater reliability to satellite precipitation estimates, in order to provide an alternative that complement the scarce observed information available for decision‐making in water management and agricultural planning. [ABSTRACT FROM AUTHOR]

The temporal distribution of precipitation is of great importance in water availability and the hydrological cycle. Existing studies, directly comparing observed and simulated precipitation amount and intensity over different temporal intervals, show that reanalyses overestimate precipitation frequency and underestimate precipitation intensity, and therefore cannot characterize extreme precipitations. In this study, relative values of precipitation (i.e., the cumulative fractions of precipitation on different percentiles of wettest hours or days to the annual total) were used to evaluate ERA5 over China during the warm seasons of from 1979 to 2015. We found that ERA5 well reproduced the relative values of daily precipitation to the annual total, although hourly results were less satisfied. The cumulative fractions at the hourly time scale at the 99th, 95th, and 90th percentiles were 15.2% ± 3.4%, 38.7% ± 6.6%, and 54.5% ± 7.4% for the gauge observations, and 9.0% ± 1.7%, 27.2% ± 4.0%, and 41.5% ± 5.0% for ERA5, respectively. ERA5 had excellent agreement with gauge observations at daily time scales: gauge observations were 13.0% ± 3.4%, 32.1% ± 5.1%, and 47.6% ± 5.7%, compared to 11.5% ± 3.7%, 30.7% ± 7.0%, and 46.0% ± 8.8% for ERA5, respectively. This difference was mainly due to the high frequency of hourly precipitation in the reanalyses, which were cancelled out at the daily scale. Gauge observations at the hourly scale showed an increase cumulative fraction at the 99th, 95th, and 90th percentiles (0.07% ± 0.03% decade−1, 0.15% ± 0.03% decade−1, and 0.17% ± 0.03% decade−1, respectively) from 1979 to 2015, but did not show an obvious trend at the daily scale. These tendencies were underestimated at the hourly scale but overestimated at the daily scale in ERA5. The results helped us to characterize the temporal distributions and variations of precipitation, and to deepen our understanding of hydrological processes and reanalyses performance. [ABSTRACT FROM AUTHOR]

Currently, there is a lack of investigating moisture sources for precipitation over the upstream catchment of the Three Gorges Dam (UCTGD), the world's largest dam. Using the dynamical recycling model (DRM), trajectory frequency method (TFM), and the Climate Forecast System Reanalysis (CFSR), this study quantifies moisture sources and transport paths for UCTGD summer precipitation from 1980 to 2009 based on two categories of sources: region-specific and source-direction. Overall, the land and oceanic sources contribute roughly 63% and 37%, respectively, of the moisture to UCTGD summer precipitation. UCTGD and the Indian Ocean are the most important land and oceanic sources, respectively, in which the southern Indian Ocean with over 10% of moisture contribution was overlooked previously. Under the influence of the Asian monsoon and prevailing westerlies, the land contribution decreases to 57.3% in June, then gradually increases to 68.8%. It is found that for drought years with enhanced southwest monsoon, there is a weakening of the moisture contribution from the C-shaped belt along the Arabian Sea, South Asia, and UCTGD, and vice versa. TFM results show three main moisture transport paths and highlight the importance of moisture from the southwest. Comparison analysis indicates that, generally, sink regions are more affected by land evaporation with their locations more interior to the center of the mainland. Furthermore, correlations between moisture contributions and indices of general circulation and sea surface temperature are investigated, suggesting that these indices affect precipitation by influencing moisture contributions of the subregions. All of these are useful for comprehending the causes of summer UCTGD precipitation. Significance Statement: Quantitative research on the moisture sources of summer precipitation has been implemented for the upstream catchment of the Three Gorges Dam (UCTGD), which is of particular hydrological significance but has not been investigated previously. The dynamical recycling model (DRM)–trajectory frequency method (TFM) approach is used to quantify and interpret the results of the moisture sources both in different specific subregions and directions, which produce more meaningful results than a single method for the areal division of moisture sources. Furthermore, antecedent indices that significantly influence the following moisture contributions of the subregions and then summer UCTGD precipitation are studied in terms of large-scale general circulation indices, which would help our understanding of precipitation forecast for UCTGD. [ABSTRACT FROM AUTHOR]

The study of water vapour sources and water cycle patterns in the Yellow River source region is of great significance for ensuring water resource security in the arid and semi‐arid regions of northern China. We established a precipitation stable isotope observation system in the Yellow River source region for three consecutive years (2020–2022), systematically analysed the spatial and temporal distribution characteristics of precipitation stable isotopes 2H and 18O in the Yellow River source region and their interrelationships with environmental factors and topography, and explored the regional water vapour transport pathways by using the HYSPLIT model and combining with the global reanalysis data. The results show that: (1) the δ18O and δ2H values of precipitation in the Yellow River source region follow the seasonal pattern, with the first half of the year being richer than the second half of the year; (2) the spatial variations of δ18O of precipitation in the Yellow River source region show a low in the southwest and a high in the northeast; (3) the water vapour source in the source area is basically stable, and the complex transport paths and the cross‐effects of the local factors determine the stable isotope characteristics of the water, and the stable isotope characteristics of the water are determined by the cross‐effects of the local factors, because the source of the water vapour and the local factors such as the height will not change significantly in the short term. Since the source of water vapour and local elevation factors will not change significantly in the short term, the precipitation pattern in the source area of the Yellow River can be considered to be basically stable. [ABSTRACT FROM AUTHOR]

Enhancing our understanding of the intricate interplay among hydro‐climatic processes is crucial for a comprehensive assessment of water availability and climate extremes across global land regions. Here, we propose an integrated framework to investigate networks of the global fields of multiple hydrological variables (Precipitation, Evapotranspiration, Soil Moisture). We apply a two‐layer complex network concept to formulate the independent networks of each hydrological variable and their interactions. Intra‐ (Single‐layer) and cross‐ (two‐layer) network coefficients are derived from the formulated hydrological network to quantify the linkage, spatial connection density, and scale for the independent hydrological fields (or variables) and their interactions. The joint distribution of the intra‐network coefficients reveals multiple spatial scales of connectivity for a moderately well‐connected location in case of evapotranspiration and soil moisture. With increasing global mean temperature, spatially synchronized evapotranspiration over such a large scale may lead to multi‐continental droughts and heatwaves. Furthermore, the (cross‐) network coefficients have identified regions acting as "bottlenecks" for moisture flow and the water‐dominated areas with less evaporative actions. The contrasting features of two‐layer network coefficients have provided a qualitative picture of moisture circulation and recirculation over many hydrological hotspot regions, such as the Amazonian basin, Indian subcontinents, and the Sahel region. The derived results can be employed to gain insights into the global water cycle's multiple interacting processes (e.g., land‐atmosphere interactions). Key Points: The bottleneck regions of the precipitation network act like conduits for moisture flowDrought and heatwaves can coevolve on multiple continents through spatially synchronized evapotranspiration and dryingTransitional areas are important hydrologically interactive regions affirming the influence of soil moisture on distant precipitation events [ABSTRACT FROM AUTHOR]

Rainfall, or more generally the precipitation process (flux), is a clear example of chaotic variables resulting from a highly nonlinear dynamical system, the atmosphere, which is represented by a set of physical equations such as the Navier–Stokes equations, energy balances, and the hydrological cycle, among others. As a generalization of the Euclidean (ordinary) measurements, chaotic solutions of these equations are characterized by fractal indices, that is, non-integer values that represent the complexity of variables like the rainfall. However, observed precipitation is measured as an aggregate variable over time; thus, a physical analysis of observed fluxes is very limited. Consequently, this review aims to go through the different approaches used to identify and analyze the complexity of observed precipitation, taking advantage of its geometry footprint. To address the review, it ranges from classical perspectives of fractal-based techniques to new perspectives at temporal and spatial scales as well as for the classification of climatic features, including the monofractal dimension, multifractal approaches, Hurst exponent, Shannon entropy, and time-scaling in intensity–duration–frequency curves. [ABSTRACT FROM AUTHOR]

Observations collected during cold-season precipitation periods at Utquagvik, Alaska and at the multidisciplinary drifting observatory for the study of Arctic climate (MOSAiC) are used to statistically analyze the relations among the atmospheric water cycle parameters including the columnar supercooled liquid and ice amounts (expressed as liquid-water and ice-water paths, i.e., LWP and IWP), the integrated water vapor (IWV) and the near-surface snowfall rate. Data come from radar and radiometer-based retrievals and from optical precipitation sensors. While the correlation between snowfall rate and LWP is rather weak, correlation coefficients between radar-derived snowfall rate and IWP are high (~0.8), which is explained, in part, by the generally low LWP/IWP ratios during significant precipitation. Correlation coefficients between snowfall rate and IWV are moderate (~0.45). Correlations are generally weaker if snowfall is estimated by optical sensors, which is, in part, due to blowing snow. Correlation coefficients between near-surface temperature and snowfall rates are low (r < 0.3). The results from the Alaska and MOSAiC sites are generally similar. These results are not very sensitive to the amount of time averaging (e.g., 15 min averaging versus daily averages). Observationally based relations among the water cycle parameters are informative about atmospheric moisture conversion processes and can be used for model evaluations. [ABSTRACT FROM AUTHOR]

Elevated spring and summer rainfall in the U.S. Midwest is often associated with a strong Great Plains low-level jet (GPLLJ), which transports moist air northward to the region from the Gulf of Mexico. While the intensity of hourly precipitation extremes depends on local moisture availability and vertical velocity, sustained moisture convergence on longer time scales depends on horizontal moisture advection from remote sources. Therefore, the magnitude of moisture convergence in the Midwest depends in part on the humidity in these moisture source regions. Past work has identified the time-mean spatial distribution of moisture sources for the Midwest and studied how this pattern changes in years with anomalous rainfall. Here, using reanalysis products and an Eulerian moisture tracking model, we seek to increase physical understanding of this moisture source variability by linking it to the GPLLJ, which has been studied extensively. We find that on interannual time scales, an anomalously strong GPLLJ is associated with a shift in the distribution of moisture sources from land to ocean, with most of the anomalous moisture transported to—and converged in—the Midwest originating from the Atlantic Ocean. This effect is more pronounced on synoptic time scales, when almost all anomalous moisture transported to the region originates over the ocean. We also show that the observed positive trend in oceanic moisture contribution to the Midwest from 1979 to 2020 is consistent with a strengthening of the GPLLJ over the same period. We conclude by outlining how projected changes in a region's upstream moisture sources may be useful for understanding changes in local precipitation variability. Significance Statement: In this work, we study how the origin of moisture that forms precipitation in the U.S. Midwest covaries with large-scale atmospheric circulation. Our results show that an intensification of the mean winds tends to increase the proportion of total rainfall that originates from the ocean. This analysis may help to constrain future projections of rainfall extremes in the central United States, as projected changes in humidity over the ocean are typically more robust and better understood than those over land. [ABSTRACT FROM AUTHOR]

The hydrological cycle, or water cycle, is one of the most important geochemical cycles on our planet. Normal functioning of its mechanisms (evaporation/evapotranspiration, condensation, and precipitation) is very important for the well-being of human beings. However, the acceleration of the hydrological cycle, mainly due to global warming, is increasing the frequency and intensity of extreme events (floods, droughts, and alterations in water resources) in many regions around the globe. This acceleration or intensification occurs because of rising temperature, which intensifies and speeds up evaporation (probable increase of 5.2%) and precipitation (probable increase of 6.5%); hence this scenario is escalating climate change. According to the datasets retrieved from the Global Land Data Assimilation System (GLDAS) of NASA, rain precipitation rate has shown changes in various regions of the world. Consequently, extreme and frequent events of heavy precipitation, floods, and droughts are also deteriorating the quality of water and preventing recharge of water reservoirs. Although some regions of the world will experience positive outcomes of this scenario in terms of water availability (due to frequent intense precipitation), most of the world’s regions are expected to face the daunting issue of water unavailability, as predicted by many researchers. [ABSTRACT FROM AUTHOR]

Stable isotopic compositions of precipitation (δ18Op, δ2Hp and d‐excessp) and atmospheric vapour (δ18Ov, δ2Hv and d‐excessv) with high spatial–temporal resolution are crucial in revealing hydrologic cycle. Based on the variation characteristics of δ18Op/δ18Ov, δ2Hp/δ2Hv and d‐excessp/d‐excessv in the headwaters of the Shule River (HSR) on hourly and daily scales from June to September 2018, this study analysed the relationships between δ18Op/δ2Hp and δ18Ov/δ2Hv combined with the equilibrium fractionation model, as well as δ18Op/δ18Ov and meteorological factors. The slopes of local meteoric water line (LMWL) and the δ2Hv‐δ18Ov fitting equation were similar (7.96 and 7.94) with both intercepts exceeding 10, reflecting the great contribution of recycling moisture. The values of δ18Ov/δ2Hv were lower than δ18Op/δ2Hp but with consistent variation patterns throughout the period. The equilibrium simulation results suggested that precipitation and atmospheric vapour almost approached isotopic equilibrium state, especially during monsoon intrusion period. Affected by monsoon intrusion, the slopes and intercepts of the LMWLs and the δ2Hv‐δ18Ov fitting equations were smaller than those during non‐monsoon period and d‐excess and δ18O were negatively correlated. Relative humidity had significant negative correlations with δ18Op and δ18Ov in the whole period, however, the positive correlations between δ18Op/δ18Ov and temperature were observed during non‐monsoon and monsoon intrusion period, respectively. Our results demonstrated that precipitation and atmospheric vapour isotopic compositions exhibited consistency under the influence of diverse moisture sources, while more complex relationships were found between δ18Op/δ18Ov and meteorological factors. This research provided evidence for using the isotopic compositions of atmospheric vapour to indicate moisture sources, and can improve understanding of the water cycle and eco‐hydrological process from the perspective of the interaction between water and gas phases of the inland river basin in northwest China. [ABSTRACT FROM AUTHOR]

The streamflow on the Tibetan Plateau (TP) plays an important role in the water supply of Asia's main river basins. To enhance understanding of hydrologic cycle under the pronounced warming over the TP, this study comprehensively investigates the streamflow changes at the upstream of six major rivers (Yellow River, Yalong River, Jinsha River, Lancang River, Nu River, and Yarlung Zangbo River) originating from the TP, and then diagnoses their possible causes by analysing the impacts of climate variability and human activities. Results indicate that these six major rivers studied have generally insignificant increasing trends in annual streamflow during the last half century, except for two stations. The significant increase appears at the Tuotuohe station in the headwater area of Jinsha River, while the dramatic decrease occurs at the Yunjinghong station in the downstream of Lancang River. In terms of climate factors, the six river basins show a distinct warming trend, along with a noticeable increase in precipitation over the central and northern regions. Pan evaporation, wind speed, sunshine duration, and relative humidity have been found to gradually decrease in most areas. As for the Tuotuohe station, both warming‐induced meltwater and increasing precipitation might jointly contribute to the increasing streamflow. But for the Yunjinghong station, the results simulated by the Variable Infiltration Capacity (VIC) model indicate that human activities, especially for the impoundment processes of Xiaowan and Nuozhadu dams, significantly influenced the streamflow, contributing to approximately 69% of the streamflow reduction during 2009–2013. In the context of accelerated global warming, greater attention should be paid to hydrometeorological changes on the TP to offer further insights for the water resources management of the 'Asian Water Tower'. [ABSTRACT FROM AUTHOR]

Evaporation from impervious surfaces plays a vital role in the catchment water cycle. Exploring the spatiotemporal variation patterns and influencing mechanisms of impervious surface evaporation at the catchment scale can improve the understanding and evaluation of the evaporation process. This study downloaded 0.5 m resolution images of the Baiyangdian catchment (BYD) from Google Earth and used deep learning to identify impervious surfaces. This was used to revise impervious surfaces of the China land cover dataset in 1985 and 1990–2020. Potential evaporation (PET) from three types of impervious surfaces (roofs, ground affected or not affected by the building height) was calculated by modifying the parameters of the Penman–Monteith equation, and daily precipitation and water‐storage capacity of impervious surfaces were taken into account to estimate impervious surface evaporation (E). The results showed that E values of the three types of impervious surfaces were between 72.1 and 178.2 mm/year and all exhibited the spatial distribution of high in the northwest and low in the southeast of the BYD in 1980–2020. Compared with that in 1980, in 2020, the cumulative evaporation (EAP) increased by 134.4%. The ratio of EAP to cumulative precipitation ranged from 3.0% to 6.9%, increasing significantly in a fluctuating manner. The increments in precipitation days and impervious surface area played a major role in the increase of EAP, and the decrease in precipitation was the fundamental reason for the increase in the proportion of impervious surface evaporation and water resource pressure in the BYD. Excluding the continuous evaporation from the remaining water can likely lead to underestimating the impervious surface evaporation. This study provides an efficient and reasonable novel approach for calculating impervious surface evaporation in long series and large‐scale catchments. [ABSTRACT FROM AUTHOR]

The Miocene (23.03–5.33 Ma) is recognized as a period with close to modern‐day paleogeography, yet a much warmer climate. With large uncertainties in future hydroclimate projections, Miocene conditions illustrate a potential future analog for the Earth system. A recent opportunistic Miocene Model Intercomparison Project 1 (MioMIP1) focused on synthesizing published Miocene climate simulations and comparing them with available temperature reconstructions. Here, we build on this effort by analyzing the hydrological cycle response to Miocene forcings across early‐to‐middle (E2MMIO; 20.03–11.6 Ma) and middle‐to‐late Miocene (M2LMIO; 11.5–5.33 Ma) simulations with CO2 concentrations ranging from 200 to 850 ppm and providing a model‐data comparison against available precipitation reconstructions. We find global precipitation increases by ∼2.1 and 2.3% per degree of warming for E2MMIO and M2LMIO simulations, respectively. Models generally agree on a wetter than modern‐day tropics; mid and high‐latitude, however, do not agree on the sign of subtropical precipitation changes with warming. Global monsoon analysis suggests most monsoon regions, except the North American Monsoon, experience higher precipitation rates under warmer conditions. Model‐data comparison shows that mean annual precipitation is underestimated by the models regardless of CO2 concentration, particularly in the mid‐ to high‐latitudes. This suggests that the models may not be (a) resolving key processes driving the hydrological cycle response to Miocene boundary conditions and/or (b) other boundary conditions or processes not considered here are critical to reproducing Miocene hydroclimate. This study highlights the challenges in modeling and reconstructing the Miocene hydrological cycle and serves as a baseline for future coordinated MioMIP efforts. Plain Language Summary: This study looks at Earth's hydrological cycle during the Miocene (23–5 million years ago). During this period, the Earth's climate was 3–7°C warmer than today, with carbon dioxide (CO2) estimates ranging between 400 and 850 ppm. Understanding how the hydrological cycle responded during warmer climate conditions can give us insight into what might happen as the Earth gets warmer. We analyzed a suite of Miocene paleoclimate simulations with different CO2 concentrations in the atmosphere and compared them against fossil plant data, which gives an estimate of the average annual rainfall during the period. We found that during the Miocene global rainfall increased by about 2.1%–2.3% for each degree of warming. The models agree that the tropics, mid‐ and high‐latitude, became wetter than they are today but have lower agreement on whether subtropical areas got wetter or drier as they warmed. Compared to proxies, models consistently underestimated how much rain fell in a year, especially in the mid‐ to high‐latitude. This illustrates the challenges in reconstructing the Miocene's hydrological cycle and suggests that the models might not fully capture the range of uncertainties associated with changes in the hydrological cycle due to warming or other factors that differentiated the Miocene. Key Points: A multi‐model comparison of the hydrological cycle in early‐to‐middle and middle‐to‐late Miocene simulations is conductedModels generally agree on wetter than modern tropics, middle and high latitudes, but not on the sign of subtropical precipitation changesModel‐data comparison shows mean annual precipitation is underestimated by the models, particularly in the mid‐ to high‐latitudes [ABSTRACT FROM AUTHOR]

Subsurface water storage is a key component in the water cycle, and China is facing severe issues with water resource shortage. This study estimates the terrestrial water storage (TWS) changes from 2003 to 2017 using a water balance approach over seven large basins in China. The estimated inter‐annual variations and trends in TWS correspond well with those obtained from the Gravity Recovery and Climate Experiment observation. Variance analysis shows that annual precipitation in northern China plays a more important role in controlling annual TWS variability than that in southern China. This increased sensitivity is primarily attributed to the limited availability of water resources and the arid climate conditions prevalent in northern China. Interestingly, actual evapotranspiration is the dominant driver, contributing more than 55% to the declining trend in TWS in two northern basins: Hai River and Yellow River basins, where the leaf area index has strongly increased. Precipitation and evapotranspiration account for over 89% of the TWS trend over basins in northeastern China. Meanwhile, the dominant drivers for TWS in southern China are precipitation (50%–54%) and runoff (33%–41%). Our results suggest that it requires strong ecological conservation actions in order to keep water resources sustainable in northern China. Plain Language Summary: Terrestrial water storage is a vital component of the global hydrological cycle, especially in regions with serious water resource issues, including shortages and disparities in spatiotemporal distribution. This study found that precipitation is the dominant driver of the trends in terrestrial water storage change over southern China. Comparatively, the dominant driver is actual evapotranspiration over northern China, which is caused by the strong increase in the leaf area index in the Hai River and Yellow River basins. Key Points: A water balance and variance analysis approach proposed for terrestrial water storage changes causality analysisPrecipitation has a greater impact on controlling the variability of terrestrial water storage (TWS) in northern China, but it contributes less to the TWS trendVegetation change is a large contributor to the TWS trends in northern basins [ABSTRACT FROM AUTHOR]

Global warming substantially intensifies hydrologic cycles, causing increasing frequency and magnitude of catastrophic floods and droughts. Understanding the patterns and mechanisms of precipitation in historical periods is pivotal for regional disaster prevention and mitigation. Here, we analyzed the daily precipitation of six stations at the Shimantan Reservoir from 1952 to 2013 to examine precipitation characteristics at different time scales. The Mann–Kendall test, moving t-test, and Innovative Polygon Trend Analysis (IPTA) were employed to detect the trends and change points in total precipitation amount, frequency, and duration. Influences of atmospheric circulations on precipitation were then explored via cross-wavelet analysis. Our results showed increased average precipitation and decreased precipitation days annually at the Shimantan Reservoir in the past decades. Specifically, increased seasonal precipitation was only detected in summer, while precipitation days were mainly reduced in winter. There was a noticeable increasing to decreasing transition trend in precipitation from July to August, and a transition from decreasing to increasing from June to July in precipitation days. Summer rainfall was predominantly moderate and light, accompanied by shortening and highly fluctuating rainstorm durations. July exhibited the highest precipitation frequency and always experienced rainstorms. The Arctic Oscillation and East Asian summer monsoon showed positive and negative correlations, respectively, with the changes in precipitation at the Shimantan Reservoir. Our analyses provide a fine-scale portrait of precipitation patterns and mechanisms under a changing climate and benefit regional flood control and sustainable development. [ABSTRACT FROM AUTHOR]

Stable water isotopes are widely recognised as essential tools to trace processes within the hydrological cycle and to disentangle complex phenomena, such as regional–local atmospheric patterns, infer water balances or characterise the aquifer recharge. In this work, we characterised two post-summer precipitation events over the western sector of Sierra de Gádor through the analysis of the rainwater δ18O and δ2H ratios, ionic composition and, complementarily, remote sensing products to define the atmospheric circulation during the rainfall episodes. This information enabled us to discern the moisture source, formation conditions and orographic influence on the rain episodes, and to better define the origin of the groundwater recharge and its dynamics in the study area. Although the samples share a common moisture source (W Mediterranean), they display substantial differences in their isotopic compositions. Such differences are attributable to sub-cloud evaporation processes that mask their Mediterranean origin, and to the strong influence of the orography on the hydrochemical and isotopic characteristics of the rainfall at the local level. The groundwater presents a very stable isotopic content and is strongly depleted in heavy isotopes, evidencing that most of the aquifer recharge takes place at very high altitudes and primarily during winter, when the influence of evaporation is attenuated. [ABSTRACT FROM AUTHOR]

Shipborne observations from the CAPRICORN‐2018 field campaign were used to investigate the characteristics and variability of precipitation across different sectors of an extra‐tropical cyclone on 16 February 2018, over the Southern Ocean (SO). Three distinct time periods—frontal, post‐frontal, and cyclone—were identified during the day. The frontal passage recorded a total accumulation of 1.9 mm, where the precipitation phases were primarily composed of rain (96%), while the cyclone period recorded the largest precipitation (4.0 mm), where the precipitation phases varied with snow (10%), mixed‐phase (40%), and rain (50%). The BASTA radar suggests the freezing level was shallow (∼500 m) with snow present above. The cloud top heights, observed by a C‐band radar, were shallower in the cyclone period, although deeper cloud depths of ∼6 km were sporadically recorded. Increased surface fluxes and a southerly wind direction indicate that cold air advection, was likely the main cause of high precipitation during the cyclone period. A non‐precipitating multi‐layer cloud structure with a geometrically thin (200 m) homogeneous layer of supercooled liquid water (SLW) overlaying shallow boundary layer convection was seen during the post‐frontal period. The ship‐borne observations were used to evaluate Weather Research & Forecasting (WRF) simulations with different microphysics settings. We found the frontal precipitation intensity is well reproduced, but it is underestimated during the cyclone period. This study represents a unique set of observations and highlights the need for understanding how ice processes and potentially horizontal advection contribute to the development of precipitation and convection over the SO. Plain Language Summary: There are still significant differences between current precipitation products over the Southern Ocean (SO). This makes it harder to understand the hydrological cycle and different meteorological processes in the region. In this study, we used the shipborne observations from the Clouds, Aerosols, Precipitation, Radiation, and atmospherIc Composition Over the southeRn oceaN (CAPRICORN) 2018 field campaign to investigate the characteristics and variability of precipitation across different sectors of an extra‐tropical cyclone on 16 February 2018, over the SO. Overall, the frontal passage recorded a total accumulation of 1.9 mm, with 96% of its phases being rain, while the cyclone period recorded the highest precipitation (4.0 mm), with 10% being snow and 40% being mixed. In addition, we made use of the observations to evaluate simulations run with the Weather Research and Forecasting Model (WRF) using a variety of cloud microphysics parameters. We observed that the intensity of the precipitation along the front is reproduced quite well, but that it is significantly underestimated throughout the cyclone period. This work highlights the importance of knowing the role that ice processes and potentially horizontal advection play in the formation of precipitation over the high latitudes of the SO. Key Points: Distinctive characteristics of precipitation across different sectors of an extra‐tropical cyclone are observedLargest precipitation was recorded during the cyclone period where its phases were largely constituted of mixed‐phase and snowWRF reproduced the frontal precipitation intensity, while it is underestimated during the cyclone period [ABSTRACT FROM AUTHOR]

Afghanistan, as a landlocked country located within central and southwestern Asia, has an arid to semi-arid climate. Most of the people are involved in agricultural activities, and a major part of the country's gross domestic product depends on agriculture, but the country has the lowest water storage capacity. Consecutive periods of drought and rapid snowmelt due to climate change have made it more challenging for suitable water resource management practices. This study investigates the historical meteorological drought characteristics across the whole country by employing the Reconnaissance Drought Index for the period 1979–2019 using data from 55 meteorological stations. Trends in precipitation and temperature are also investigated using the Mann-Kendall's and the Sen's slope statistical tests. A four-decadal countrywide drought map is generated. Extreme and severe droughts were observed in 1999 and 2000 across the whole country. Moderate drought events have started to occur with a frequency of 3 to 5 years since 1999. The decadal annual rainfall values in each river basin indicate that rainfall has decreased in the last two decades with a significant decline in 1999-2008. The trends of increase in temperature and decrease in precipitation are indications of rapid climate change in the country, especially in the south, west, and southwest regions. Due to the intensity and frequency of the droughts, river flow rates have decreased; and therefore, there is a need for the upstream and downstream neighboring countries to come to terms with the phenomenon of a new normal in the hydrological cycle and accordingly revise new water sharing treaties. [ABSTRACT FROM AUTHOR]

Reliable quantitative precipitation estimation with a rich spatiotemporal resolution is vital for understanding the Earth's hydrological cycle. Precipitation estimation over land and coastal regions is necessary for addressing the high degree of spatial heterogeneity of water availability and demand, and for resolving the extremes that modulate and amplify hazards such as flooding and landslides. Advancements in computation power along with unique high spatiotemporal and spectral resolution data streams from passive meteorological sensors aboard geosynchronous Earth-orbiting (GEO) and low Earth-orbiting (LEO) satellites offer exciting opportunities to retrieve information about surface precipitation phenomena using data-driven machine learning techniques. In this study, the capabilities of U-Net-like architecture are investigated to map instantaneous, summertime surface precipitation intensity at the spatial resolution of 2 km. The calibrated brightness temperature products from the Global Precipitation Measurement (GPM) Microwave Imager (GMI) radiometer are combined with multispectral images (visible, near-infrared, and infrared bands) from the Advanced Baseline Imager (ABI) aboard the GOES-R satellites as main inputs to the U-Net-like precipitation algorithm. Total precipitable water and 2-m temperature from the Global Forecast System (GFS) model are also used as auxiliary inputs to the model. The results show that the U-Net-like algorithm can capture fine-scale patterns and intensity of surface precipitation at high spatial resolution over stratiform and convective precipitation regimes. The evaluations reveal the potential of extracting relevant, high spatial features over complex surface types such as mountainous regions and coastlines. The algorithm allows users to interpret the inputs' importance and can serve as a starting point for further exploration of precipitation systems within the field of hydrometeorology. [ABSTRACT FROM AUTHOR]

The Arctic is warming faster than anywhere on Earth, and with these warming temperatures, there is likely to be more precipitation falling as rain. This precipitation phase change will have profound impacts on the hydrologic cycle, energy balance, and snow and sea ice mass budgets. Here, we examine the number of rainfall days in the Arctic from three reanalyses, ERA-Interim, ERA5, and MERRA-2, over 1980–2016. We show that the number of rainfall days has increased over this period, predominantly in the autumn and in the North Atlantic and peripheral seas, and the length of the rain season has increased in all reanalyses. This is positively correlated to the number of days with above freezing air temperatures and a lengthening of the warm season. ERA-Interim produces significantly more rainfall days than other reanalyses and CloudSat observations, as well as significantly more rainfall when temperatures are below freezing. Investigation into the cloud microphysics schemes revealed that the scheme employed by ERA-Interim allowed for mixed-phase clouds to form rain at temperatures below freezing following a temperature-dependent phase partitioning function between 250 and 273 K. This simple diagnostic treatment erroneously overestimates rain at temperatures below 273 K and produces unrealistic rainfall compared to ERA5 and MERRA-2. This work highlights the importance of having accurate physics and improving microphysical schemes in models for simulating precipitation in the Arctic and the caution that is warranted for interpreting reanalysis trends. [ABSTRACT FROM AUTHOR]

In the context of climate change, the stakes surrounding water availability are rapidly intensifying. Decomposing and quantifying the effects of climate on discharge allows us to understand their impact on water resources better. We propose a methodology to separate the effect of change in the annual mean of climate variables from the effect of the intra‐annual distribution of precipitation. It combines the Budyko framework with land surface model (LSM) outputs. The LSM is used to reproduce the behavior of 2,134 reconstructed watersheds across Europe between 1902 and 2010, with climate inputs as the only source of change. We fit a one‐parameter approximation of the Budyko framework to the LSM outputs. It accounts for the evolution of the annual mean in precipitation (P) and potential evapotranspiration (PET). We introduce a varying parameter in the equation, representing the effect of long‐term variations in the intra‐annual distribution of P and PET. To better assess the effects of changes in annual means or intra‐annual distribution of P, we construct synthetic forcings fixing one or the other. European results show that the trends in the annual averages of P dominate the trends in discharge due to climate. The second main climate driver is PET, except over the Mediterranean area, where changes in intra‐annual variations of P have a higher impact on discharge than trends in PET. Therefore, the effects of changes in the intra‐annual distribution of climate variables are to be addressed when looking at changes in annual discharge. Plain Language Summary: Water availability is a challenge for all of society. Various competing activities rely on this resource, and its scarcity can lead to social, economic, and environmental conflicts. With climate change, river discharge and, more generally, the full water cycle is impacted. Furthermore, multiple human actions such as dams and irrigation concurrently change the balance of the water cycle over watersheds. To comprehensively understand the dynamics of discharge, it is essential to analyze the potential influence of direct human activities alongside the impacts of natural climatic factors. Models are a way to represent reality with an understanding of the physical phenomena included. They can be used to represent the behavior of watersheds without human intervention. In light of this, we have developed a methodology to highlight the climate factors impacting discharge. Annual discharge changes are driven mainly by changes in annual precipitation over Europe. The increasing temperature leads to an ever‐growing evaporative demand and is the second most impacting factor over most of Europe. However, in the Mediterranean area, where water is more limited, changes in the seasonality of precipitation have a higher impact than changes in the evaporative demand. Key Points: Evaluate the role of climate change on the evolution of the discharge of European riversUsing the Budyko model as a detection tool for changes in hydrological behaviors of watershedsAnalyze the effects of changes in the intra‐annual distribution of precipitation on the evolution of the annual discharge [ABSTRACT FROM AUTHOR]

Precipitation is a major component of the water cycle. Accurate and reliable estimation of precipitation is essential for various applications. Generally, there are three main types of precipitation products: satellite based, reanalysis, and ground measurements from rain gauge stations. Each type has its advantages and disadvantages. Recent efforts have been made to develop various merging methods to improve precipitation estimates by combining multiple precipitation products. This study evaluated for the first time the performance of the random forest-based merging procedure (RF-MEP) method in enhancing the accuracy of daily precipitation estimates in Chongqing city, China with a complex terrain and sparse observational data. The RF-MEP method was used to merge three widely used gridded precipitation products (CHIRPS, ERA5-Land, and GPM IMERG) with ground measurements from a limited number of rain gauge stations to produce the merged precipitation dataset. Eight stations (approximately 70% of the available stations) were used to train the RF-MEP approach, while four stations (30%) were used for independent testing. Various statistical metrics were employed to assess the performance of the merged precipitation dataset and the three existing precipitation products against the ground measurements. Our results demonstrated that the RF-MEP approach significantly enhances the accuracy of daily precipitation estimates, surpassing the performance of the individual precipitation products and two other merging methods (the simple linear regression model and the simple averaging). Among the three existing products, ERA5-Land exhibited the best performance in capturing daily precipitation, followed by GPM IMERG, while CHIRPS performed the worst. Regarding precipitation intensity, all three existing products and the RF-MEP merged dataset performed well in capturing light precipitation events with an intensity of less than 1 mm/day, which accounts for the majority (more than 70%) of occurrences. However, all datasets showed rather poor capability in capturing precipitation events beyond 1 mm/day, with the worst performance observed for extreme heavy precipitation events exceeding 50 mm/day. The RF-MEP approach significantly improves the detection ability for all precipitation intensities, except for the most extreme intensity (>50 mm/day), where only marginal improvement is observed. Analysis of the spatial pattern of precipitation estimates and the temporal bias of daily precipitation estimates further confirms the superior performance of the RF-MEP merged precipitation dataset over the three existing products. [ABSTRACT FROM AUTHOR]

Projecting precipitation changes is essential for researchers to understand climate change impacts on hydrological cycle. This study projected future precipitation over the Hanjiang River Basin (HRB) based on the multimodel ensemble (ME) of six global climate models from Phase 6 of the Coupled Model Intercomparison Project (CMIP6). An ME method using the fusion of four machine learning (ML) algorithms (random forest [RF], K‐nearest neighbors [KNN], extra tree [ET], and gradient boosting decision tree [GBDT]) was proposed in this study. The future precipitation changes were investigated during 2023–2042 (Near‐term), 2043–2062 (Mid‐term), and 2081–2100 (Long‐term) periods, with reference to the base period 1995–2014, under three integrated scenarios (SSP1‐2.6, SSP2‐4.5, and SSP5‐8.5) of the Shared Socioeconomic Pathways (SSPs) and the representative concentration pathways (RCPs). The results show that: (1) the proposed ME method performs better than the ME mean and individual ML algorithms, with a correlation coefficient value reaching 0.88 and Taylor skill score reaching 0.764. (2) The precipitation under SSP5‐8.5 has the largest upward trend with the annual precipitation variation range of −9.27% to 112.84% from 2023 to 2100, followed by SSP2‐4.5 with −30.48% to 44.67%, and the smallest under SSP1‐2.6 with −37.19% to 37.78%, which show a significant trend of humidification over the HRB in the future. (3) The precipitation changes over the HRB are projected to increase over time, with the largest in the Long‐term, followed by Mid‐term, and the smallest in the Near‐term. (4) The northeastern parts of the HRB are projected to experience a large precipitation in the future, and the southeastern parts are smaller. (5) Uncertainties in the projected precipitation over the HRB still exist, which can be reduced by ME. The findings obtained in this study have important implications for hydrological policymakers to make adaptive strategies to reduce the risks of climate change. [ABSTRACT FROM AUTHOR]

Moisture of precipitation originates from terrestrial and oceanic evaporation through atmospheric transport. Understanding the contributions from different moisture sources to precipitation is essential for the hydrologic study. China is the world's third largest country in terms of land area and has contributed 25% of the global net increase in vegetation leaf area since 2000. Thus, it provides a good platform to understand the contributions from different moisture sources to precipitation and how increasing vegetation greenness affects precipitation trends. In this study, we investigated the moisture sources of precipitation and their changes in China during 1980–2018 based on the UTrack moisture recycling data set. We found that 47.3% of the moisture was from oceanic evaporation, and 52.7% was from terrestrial evapotranspiration (ET). For the moisture from terrestrial ET, 33.0% was from vegetation transpiration. The observed annual precipitation showed a significant increasing trend with 2.07 mm/year in China from 1980 to 2018. Increasing moisture from oceanic evaporation contributed the most to the increasing precipitation trend (0.98 mm/year), followed by the increasing moisture from vegetation transpiration (0.72 mm/year) and other terrestrial evaporation (0.37 mm/year). The increasing contribution of vegetation transpiration from China was comparable with that from neighboring countries (0.37 vs. 0.35 mm/year). The increasing moisture from vegetation transpiration could be due to the nationwide afforestation projects in China since 1999. The results provide a reference for understanding changes in precipitation and hydrologic processes. Plain Language Summary: Precipitation plays a crucial role in the water cycle, and changes in precipitation have significant impacts on the water cycle. Understanding the contributions from different moisture sources to precipitation is essential for water resources research. In this study, we found that 47.3% of the precipitation in China originated from oceanic moisture, 33.0% was from vegetation transpiration, and 19.7% was from other terrestrial moisture sources. Increasing moisture from oceanic evaporation contributed the most to the precipitation trend in China, followed by the increasing moisture from vegetation transpiration. The increasing moisture from vegetation transpiration could be due to the nationwide afforestation projects in China since 1999. The results provide a reference for understanding changes in precipitation and contribute to better water resources management. Key Points: For China's precipitation, 47.3% of the moisture was from oceanic evaporation (Eo), and 52.7% was from terrestrial evapotranspirationAnnual precipitation had an increasing trend with 2.07 mm/year, Eo and vegetation transpiration contributed 0.98 and 0.72 mm/year, respectivelyThe increasing moisture from vegetation transpiration could be due to the nationwide afforestation projects since 1999 [ABSTRACT FROM AUTHOR]

Climate change is a pressing issue that is affecting the lives and livelihoods of millions of people across the world. This study investigates the trend analysis and spatial-temporal variations of temperature and precipitation on a monthly, seasonal, and annual basis in Rajasthan state, India, over the past 40 years (1981-2020). The trend analysis of temperature and precipitation were analysed using the Mann-Kendall test at the confidence level of 95%. The magnitude (slope) was determined by using Theil-Sen's slope test. The results of the analysis revealed significant positive and negative trends of temperature and precipitation observed on a monthly, seasonal, and annual basis in all the 33 districts of Rajasthan state. The summer season experienced the maximum average temperature, while the winter season had the minimum. The study also found that the northern and western parts of Rajasthan experience "Mawat" rain during the winter due to cyclones happening in the Mediterranean Sea during that season. The annual average temperature and precipitation were observed to be maximum in the southern part and minimum in the northern and western parts of the state. The findings of this study provide valuable information for the future management of water resources and the likely impact of activities on the hydrologic cycle and natural resources in Rajasthan state. [ABSTRACT FROM AUTHOR]

Unstable hydrological cycles and water resource instability over and around the Tibetan Plateau (TP) are topics of wide concern. The Indian summer monsoon (ISM) is one of the TP's most important moisture sources; as such, its behavior is key to any changes in precipitation and water-related environments. However, there have been relatively few thorough investigations into ISM activities. Here we primarily explore ISM activities using outgoing longwave radiation (OLR) datasets in TP, and precipitation isotopes recorded at Lhasa, for the period 1975–2020. Our major findings are that 1) the ISM onset (retreat date) is between ∼31 May and 19 July (∼8 August–27 September), with ISM duration of ∼40–110 days; 2) significant spatial inhomogeneous patterns are evident in ISM activities, i.e., the western part of our study area experiences earlier ISM onset, delayed retreat, longer duration, and greater intensity and strength, and the inverse is true in the eastern sector of the study area; 3) the ISM activities that dominate the 1975–98 period determine their general patterns over the entire 1975–2020 period, taking into account evident discrepancies in subperiods; and 4) the negative relations between precipitation δ18O and ISM intensity/strength at Lhasa confirm the ISM activities defined using OLR. These results will improve our understanding of hydrological cycles in TP and provide insights into hydrological studies in the "Asian Water Tower" region. Significance Statement: Over the recent decades, the Tibetan Plateau (TP) (Asian Water Tower) has undergone dramatic environmental changes, evinced by the instabilities of hydrological cycles. As one of TP's most important moisture sources, the Indian summer monsoon (ISM) is key to changes in precipitation and water-related environments. To get thorough investigations into ISM activities, we primarily explore ISM activities using outgoing longwave radiation (OLR) datasets in TP and precipitation isotopes at Lhasa. Significant spatial inhomogeneous patterns are evident in ISM activities: the western part experiences earlier ISM onset, delayed retreat, longer duration, and stronger intensity and strength, and the inverse occurs in the eastern sector. These results will improve our understanding of hydrology, meteorology, ecology, and paleoclimate reconstructions in the Asian Water Tower region. [ABSTRACT FROM AUTHOR]

Aquatic ecosystems in arid regions are important habitats for aquatic wildlife and also support species biodiversity. Soda lakes in endorheic drainage basins, so‐called amplifier lakes, are sentinels of climate change and are of scientific significance.Here we present the results of a long‐term study (20 years) of the Torey lakes, Transbaikalia, Russia, including the period from the maximum capacity of the Torey lakes through to aridification, and then to the initial phase of refilling. Our aim was to determine the response of planktonic communities in the lakes to environmental change over this period.We conducted our studies during various parts of the hydrological cycle, including three phases for Lake Zun‐Torey (high [1999, 2003], intermediate [2007, 2011] and low [2014, 2016] water levels) and two phases for Lake Barun‐Torey (high level [1999, 2003] and the initial refilling phase [2014, 2016, 2018, 2020]). Lake Barun‐Torey dried up completely in summer 2009, and since 2013 has been undergoing initial refilling. Lake Zun‐Torey dried up in the autumn of 2017.Temporal variation in planktonic communities differs for each lake. We identified four stages of changes in the planktonic associations during the aridification of Lake Zun‐Torey (the phytoplankton experienced a decrease in abundance and biomass, and was dominated by green algae and diatoms; the zooplankton underwent a decrease in species diversity and an increase in total abundance and biomass, which were caused by an increase in the abundance of some crustacean species) and three stages of changes as the lake level fell and during the initial refilling of Lake Barun‐Torey (the plankton communities increased in species richness and abundance in the transient pools).These results show the complexity of long‐term community dynamics in arid‐zone soda lakes. They have revealed how phytoplankton and zooplankton community diversity and structure can vary with changing environmental conditions and may pass between distinct states related to the stages of the hydroperiod. [ABSTRACT FROM AUTHOR]

The Tibetan Plateau (TP) has become wetter and warmer during the past four decades, which leads to an adjustment in the surface energy budget, characterized by enhanced surface latent heat and weakened surface sensible heat. However, the impacts of these surface energy changes on climate are unclear. In this study, we investigate the atmospheric response to the altered surface energy budget in the monsoon season over the TP using regional climate simulations. The inhibited surface sensible heating weakens the thermal effect of the TP, which further suppresses low-level convergence and upper-level divergence, thereby weakening the water vapor flux convergence over the plateau. The weakening of low-level air humidity by this dynamical response exceeds the supply from the enhanced surface evaporation, causing decreased precipitation (decreasing more in the wet eastern plateau and less in the dry west). Further analyses show that the precipitation frequency increases mainly for light precipitation while decreasing for heavy precipitation. It is thus demonstrated that on the TP, land surface energy–atmosphere interactions can mitigate the rate of precipitation increase, suppress the increase in frequency of heavy precipitation, and weaken the east–west contrast in precipitation amount, through a dynamical mechanism. Overall, land–atmosphere interactions on the TP exert negative feedback to partially offset the accelerated plateau water cycle under a changing climate. [ABSTRACT FROM AUTHOR]

Earth's hydrological cycle is expected to intensify in response to global warming, with a "wet‐gets‐wetter, dry‐gets‐drier" response anticipated over the ocean. Subtropical regions (∼15°–30°N/S) are predicted to become drier, yet proxy evidence from past warm climates suggests these regions may be characterized by wetter conditions. Here we use an integrated data‐modeling approach to reconstruct global and zonal‐mean rainfall patterns during the early Eocene (∼56–48 million years ago). The Deep‐Time Model Intercomparison Project (DeepMIP) model ensemble indicates that the mid‐ (30°–60°N/S) and high‐latitudes (>60°N/S) are characterized by a thermodynamically dominated hydrological response to warming and overall wetter conditions. The tropical band (0°–15°N/S) is also characterized by wetter conditions, with several DeepMIP models simulating narrowing of the Inter‐Tropical Convergence Zone. However, the latter is not evident from the proxy data. The subtropics are characterized by negative precipitation‐evaporation anomalies (i.e., drier conditions) in the DeepMIP models, but there is surprisingly large inter‐model variability in mean annual precipitation (MAP). Intriguingly, we find that models with weaker meridional temperature gradients (e.g., CESM, GFDL) are characterized by a reduction in subtropical moisture divergence, leading to an increase in MAP. These model simulations agree more closely with our new proxy‐derived precipitation reconstructions and other key climate metrics and imply that the early Eocene was characterized by reduced subtropical moisture divergence. If the meridional temperature gradient was even weaker than suggested by those DeepMIP models, circulation‐induced changes may have outcompeted thermodynamic changes, leading to wetter subtropics. This highlights the importance of accurately reconstructing zonal temperature gradients when reconstructing past rainfall patterns. Plain Language Summary: As the world warms, the atmosphere is able to hold more moisture—however, this moisture will not fall evenly across the globe. Some regions are expected to become wetter, whereas other regions will become drier. This is the basis of the familiar paradigm "wet‐gets‐wetter, dry‐gets‐drier" and is largely supported by future model projections. However, evidence from the geological record contradicts this hypothesis and suggests that a warmer world could be characterized by wetter (rather than drier) subtropics. Here, we use an integrated data‐modeling approach to investigate the hydrological response to warming during an ancient warm interval (the early Eocene, 56–48 million years ago). We show that models with weaker latitudinal temperature gradients are characterized by a reduction in subtropical moisture divergence. However, this was not sufficient to induce subtropical wetting. If the meridional temperature gradient was weaker than suggested by the models, circulation‐induced changes may have lead to wetter subtropics. This work shows that the latitudinal temperature gradient is a key factor that influences hydroclimate in the subtropics, especially in past warm climates. Key Points: The early Eocene hydrological cycle in the DeepMIP models is characterized by a "wet‐gets‐wetter, dry‐gets‐drier" responseThe early Eocene exhibits weaker subtropical moisture divergence in simulations with reduced meridional temperature gradientsThis highlights the important role of the meridional temperature gradient when predicting past (and future) rainfall patterns [ABSTRACT FROM AUTHOR]

In the coastal regions of the western United States, atmospheric rivers (ARs) are associated with the largest precipitation generating storms and contribute up to half of annual precipitation, but the impact of ARs on the integrated hydrologic cycle, specifically on groundwater storage and hydrodynamics, is largely unknown. To better explore the hydrologic behavior of AR versus non‐AR event precipitation, we present a novel combination of two water tracking methods (one in the atmosphere and one in the subsurface) to explicitly track the full lifecycle of water parcels generated by ARs. Simulations of northern California's Cosumnes River watershed during the record wet 2017 water year are performed via the coupling of a high‐resolution regional climate model and a land surface‐groundwater model accounting for lateral groundwater flow. Despite ARs contributing more precipitation than non‐AR storms, we find less AR water is preferentially stored in aquifers by year end. Fractionally, ARs result in 300% less snow derived groundwater‐recharged compared to non‐AR precipitation. Rain‐on‐snow (RoS) plays an important role in AR‐driven discharge, where over 50% of total discharge from ARs snow is from RoS events. Finally, despite record‐breaking annual precipitation, simulated groundwater depletion occurs by year end due to estimates of groundwater pumping activities. The results from these simulations serve as a partial analogue of future hydrologic conditions where ARs are expected to intensify and provide a greater fraction of annual precipitation due to climate change. Key Points: A coupled hydrologic model is forced by a regional climate model to examine the role of atmospheric rivers (ARs) on groundwater dynamicsTracking of atmospheric features and subsurface Lagrangian particles is used to follow the full lifecycle of water through a record wet yearThe most significant difference in AR‐sourced precipitation is on the groundwater recharge‐snow relationship [ABSTRACT FROM AUTHOR]

As atmospheric carbon dioxide concentrations rise and climate change becomes more destructive, geoengineering has become a subject of serious consideration. By reflecting a fraction of incoming sunlight, solar geoengineering could cool the planet quickly, but with uncertain effects on regional climatology, particularly hydrological patterns. Here, we review recent work on projected hydrologic outcomes of solar geoengineering, in the context of a robust literature on hydrological responses to climate change. While most approaches to solar geoengineering are expected to weaken the global hydrologic cycle, regional effects will vary based on implementation method and strategy. The literature on the hydrologic outcomes and impacts of geoengineering demonstrates that its implications for human welfare will depend on assumptions about underlying social conditions and objectives of intervention as well as the social lens through which projected effects are interpreted. We conclude with suggestions to reduce decision-relevant uncertainties in this novel field of Earth science inquiry. The expected hydrological effects of reducing insolation are among the most uncertain and consequential impacts of solar geoengineering (SG). Theoretical frameworks from broader climate science can help explain SG's effects on global precipitation, relative humidity, and other aspects of hydroclimate. The state of the knowledge on hydrological impacts of SG is unevenly concentrated among regions. Projected hydrological impacts from SG are scenario dependent and difficult to characterize as either harmful or beneficial. [ABSTRACT FROM AUTHOR]

The response of zonal-mean precipitation minus evaporation (P 2 E) to global warming is investigated using a moist energy balance model (MEBM) with a simple Hadley cell parameterization. The MEBM accurately emulates zonal-mean P 2 E change simulated by a suite of global climate models (GCMs) under greenhouse gas forcing. The MEBM also accounts for most of the intermodel differences in GCM P 2 E change and better emulates GCM P 2 E change when compared to the "wet-gets-wetter, dry-gets-drier" thermodynamic mechanism. The intermodel spread in P 2 E change is attributed to intermodel differences in radiative feedbacks, which account for 60%-70%of the intermodel variance, with smaller contributions from radiative forcing and ocean heat uptake. Isolating the intermodel spread of feedbacks to specific regions shows that tropical feedbacks are the primary source of intermodel spread in zonal-mean P 2 E change. The ability of the MEBM to emulate GCM P 2 E change is further investigated using idealized feedback patterns. A less negative and narrowly peaked feedback pattern near the equator results in more atmospheric heating, which strengthens the Hadley cell circulation in the deep tropics through an enhanced poleward heat flux. This pattern also increases gross moist stability, which weakens the subtropical Hadley cell circulation. These two processes in unison increase P 2 E in the deep tropics, decrease P 2 E in the subtropics, and narrow the intertropical convergence zone. Additionally, a feedback pattern that produces polar-amplified warming partially reduces the poleward moisture flux by weakening the meridional temperature gradient. It is shown that changes to the Hadley cell circulation and the poleward moisture flux are crucial for understanding the pattern of GCM P 2 E change under warming. [ABSTRACT FROM AUTHOR]

Climate changes significantly impact the hydrological cycle. Precipitation is one of the most important atmospheric inputs to the terrestrial hydrologic system, and its variability considerably influences environmental and socioeconomic development. Atmospheric warming intensifies the hydrological cycle, increasing both atmospheric water vapor concentration and global precipitation. The relationship between heavy precipitation and temperature has been extensively investigated in literature. However, the relationship in different percentile ranges has not been thoroughly analyzed. Moreover, a percentile-based regression provides a simple but effective framework for investigation into other factors (precipitation type) affecting this relationship. Herein, a comprehensive investigation is presented on the temperature dependence of daily precipitation in various percentile ranges over the Qinghai–Tibet Plateau. The results show that 1) most stations exhibit a peaklike scaling structure, while the northeast part and south margin of the plateau exhibit monotonic positive and negative scaling structures, respectively. The scaling structure is associated with the precipitation type, and 2) the positive and negative scaling rates exhibit similar spatial patterns, with stronger (weaker) sensitivity in the south (north) part of the plateau. The overall increase rate of daily precipitation with temperature is scaled by Clausius–Clapeyron relationship. 3) The higher percentile of daily precipitation shows a larger positive scaling rate than the lower percentile. 4) The peak-point temperature is closely related to the local temperature, and the regional peak-point temperature is roughly around 10°C. Significance Statement: This study aims to better understand the relationship between precipitation and surface air temperature in various percentile ranges over the Qinghai–Tibet Plateau. This is important because percentile-based regression not only accurately describes the response of precipitation to warming temperature but also provides a simple but effective framework for investigating other factors (precipitation type) that may be affecting this relationship. Furthermore, the sensitivity and peak-point temperature are evaluated and compared among different regions and percentile ranges; this study also attempts to outline their influencing factors. To our knowledge, this study is the first integration of percentile-based analysis of the dependence of daily precipitation on surface air temperature. [ABSTRACT FROM AUTHOR]

The terrestrial water cycle links the soil and atmosphere moisture reservoirs through four fluxes: precipitation, evaporation, runoff, and atmospheric moisture convergence (net import of water vapor to balance runoff). Each of these processes is essential for sustaining human and ecosystem well‐being. Predicting how the water cycle responds to changes in vegetation cover remains a challenge. Recently, changes in plant transpiration across the Amazon basin were shown to be associated disproportionately with changes in rainfall, suggesting that even small declines in transpiration (e.g., from deforestation) would lead to much larger declines in rainfall. Here, constraining these findings by the law of mass conservation, we show that in a sufficiently wet atmosphere, forest transpiration can control atmospheric moisture convergence such that increased transpiration enhances atmospheric moisture import and results in water yield. Conversely, in a sufficiently dry atmosphere increased transpiration reduces atmospheric moisture convergence and water yield. This previously unrecognized dichotomy can explain the otherwise mixed observations of how water yield responds to re‐greening, as we illustrate with examples from China's Loess Plateau. Our analysis indicates that any additional precipitation recycling due to additional vegetation increases precipitation but decreases local water yield and steady‐state runoff. Therefore, in the drier regions/periods and early stages of ecological restoration, the role of vegetation can be confined to precipitation recycling, while once a wetter stage is achieved, additional vegetation enhances atmospheric moisture convergence and water yield. Recent analyses indicate that the latter regime dominates the global response of the terrestrial water cycle to re‐greening. Evaluating the transition between regimes, and recognizing the potential of vegetation for enhancing moisture convergence, are crucial for characterizing the consequences of deforestation as well as for motivating and guiding ecological restoration. [ABSTRACT FROM AUTHOR]