Atmospheric Water Budget Research Articles

GTWS-MLrec: global terrestrial water storage reconstruction by machine learning from 1940 to present

Abstract. Terrestrial water storage (TWS) includes all forms of water stored on and below the land surface, and is a key determinant of global water and energy budgets. However, TWS data from measurements by the Gravity Recovery and Climate Experiment (GRACE) satellite mission are only available from 2002, limiting global and regional understanding of the long-term trends and variabilities in the terrestrial water cycle under climate change. This study presents long-term (i.e., 1940–2022) and relatively high-resolution (i.e., 0.25∘) monthly time series of TWS anomalies over the global land surface. The reconstruction is achieved by using a set of machine learning models with a large number of predictors, including climatic and hydrological variables, land use/land cover data, and vegetation indicators (e.g., leaf area index). The outcome, machine-learning-reconstructed TWS estimates (i.e., GTWS-MLrec), fits well with the GRACE/GRACE-FO measurements, showing high correlation coefficients and low biases in the GRACE era. We also evaluate GTWS-MLrec with other independent products such as the land–ocean mass budget, atmospheric and terrestrial water budget in 341 large river basins, and streamflow measurements at 10 168 gauges. The results show that our proposed GTWS-MLrec performs overall as well as, or is more reliable than, previous TWS datasets. Moreover, our reconstructions successfully reproduce the consequences of climate variability such as strong El Niño events. The GTWS-MLrec dataset consists of three reconstructions based on (a) mascons of the Jet Propulsion Laboratory of the California Institute of Technology, the Center for Space Research at the University of Texas at Austin, and the Goddard Space Flight Center of NASA; (b) three detrended and de-seasonalized reconstructions; and (c) six global average TWS series over land areas, both with and without Greenland and Antarctica. Along with its extensive attributes, GTWS_MLrec can support a wide range of geoscience applications such as better understanding the global water budget, constraining and evaluating hydrological models, climate-carbon coupling, and water resources management. GTWS-MLrec is available on Zenodo through https://doi.org/10.5281/zenodo.10040927 (Yin, 2023).

Cloud Microphysical Processes and Atmospheric Water Budget during the 20 July 2021 Extreme Precipitation Event in Zhengzhou, China

Cloud Microphysical Processes and Atmospheric Water Budget during the 20 July 2021 Extreme Precipitation Event in Zhengzhou, China

Changes in the surface and atmospheric water budget due to projected Amazon deforestation: Lessons from a fully coupled model simulation

The Amazon forest has a complex interaction with climate at different spatial and temporal scales. This means that alterations in land use could modify the regional water cycle, including the surface and atmospheric water budget. However, little is known about how these changes occur seasonally and in a spatially distributed manner in the most vulnerable regions, such as the southern Amazon. In this study, the local to regional effects of future Amazon deforestation on the surface and atmospheric water budget components are investigated by twin numerical experiments using the Regional Earth System Model of the ‘Institute Pierre Simone Laplace’ (RegIPSL) for 19 yr (2001–2019). The results show that significant changes in precipitation and actual evapotranspiration in the southern Amazon (south of 5°S) are associated with surrounding areas with a deforested ratio higher than 40%. During the onset of the wet season (September-November) the largest changes in convective processes are manifested by opposite atmospheric dynamic in adjacent regions (dipole), associated with. This dynamic is associated with wind orientation and the different sizes of the straight corridors of continuous deforestation (pathways). The dipole manifests itself as a suppression of convection in the upwind sector, while convection increases in the downwind sector of the deforestation pathway. For medium-sized deforestation pathways (∼350 km) convection changes are related to dynamic processes (decrease in surface roughness). In large-sized pathways (∼500 km) the mechanisms causing convective changes are combined, dynamic and thermal (increase in surface temperature). In deforested regions there is an average increase of terrestrial water storage dynamics and runoff ∼10 times higher than in non-deforested regions. Furthermore, the atmosphere becomes ∼8 times drier in deforested regions than in non-deforested regions. Our findings indicate a new perspective regarding a comprehensive modeling approach to understand potential changes in the surface and atmospheric water cycle in different regions of Amazonia and in different seasons due to future deforestation and thus provide new insights into their spatial and temporal variability at sub-regional scales.

The role of external and local atmospheric moisture fluxes in the interannual variability of peak summer precipitation over the northern fringe of the East Asian summer monsoon

On the northern fringe of the East Asian summer monsoon (NFEASM), both external atmospheric moisture transport and local evaporation are important moisture sources of moisture that feed peak summer precipitation, but their relative importance in regulating the precipitation variability remains unclear. This study uses the atmospheric water budget analysis to investigate the contributions of external and local atmospheric moisture fluxes to the interannual variability of peak summer (July and August) precipitation over the NFEASM between 1980 and 2015. The results show that, compared with the net atmospheric moisture flux (i.e., moisture flux convergence, MFC), although climatologically evaporation is of the same magnitude as precipitation, its standard deviation is much smaller than that of precipitation and MFC. With respect to moisture conservation, the atmospheric moisture budget indicates that the interannual variability in summer precipitation is derived primarily from changes in MFC. Moreover, the closer correlation between MFC and precipitation than between MFC and evaporation also implies that the variability of summer precipitation over the NFEASM is controlled mainly by fluctuations in the external atmospheric moisture fluxes, particularly by the moisture transport from the southwest, which is closely linked to the anticyclonic anomalous circulation over eastern China. In addition, although the westerly does not bring substantial moisture, its meridional movement can change the upper-level zonal wind divergence pattern, thereby affecting peak summer precipitation over the NFEASM.

Predicting Inundation Dynamics and Hydroperiods of Small, Isolated Wetlands Using a Machine Learning Approach

The duration of inundation or saturation (i.e., hydroperiod) controls many wetland functions. In particular, it is a key determinant of whether a wetland will provide suitable breeding habitat for amphibians and other taxa that often have specific hydrologic requirements. Yet, scientists and land managers often are challenged by a lack of sufficient monitoring data to enable the understanding of the wetting and drying dynamics of small depressional wetlands. In this study, we present and evaluate an approach to predict daily inundation dynamics using a large wetland water-level dataset and a random forest algorithm. We relied on predictor variables that described characteristics of basin morphology of each wetland and atmospheric water budget estimates over various antecedent periods. These predictor variables were derived from datasets available over the conterminous United States making this approach potentially extendable to other locations. Model performance was evaluated using two metrics, median hydroperiod and the proportion of correctly classified days. We found that models performed well overall with a median balanced accuracy of 83% on validation data. Median hydroperiod was predicted most accurately for wetlands that were infrequently inundated and least accurate for permanent wetlands. The proportion of inundated days was predicted most accurately in permanent wetlands (99%) followed by frequently inundated wetlands (98%) and infrequently inundated wetlands (93%). This modeling approach provided accurate estimates of inundation and could be useful in other depressional wetlands where the primary water flux occurs with the atmosphere and basin morphology is a critical control on wetland inundation and hydroperiods.

Quantifying the Impact of Land Use and Land Cover Change on Moisture Recycling With Convection‐Permitting WRF‐Tagging Modeling in the Agro‐Pastoral Ecotone of Northern China

AbstractLand use and land cover change (LUCC) can influence the regional atmospheric water budget. In this study, the Weather Research and Forecasting model embedded with evapotranspiration (ET)‐tagging (WRF‐tagging) is used to investigate the atmospheric pathways of ET as well as where and to what extent ET returns as precipitation (P) in the agro‐pastoral ecotone of northern China (APENC). First, we updated the default land use and vegetation indices in the WRF‐tagging with high‐resolution and real‐time datasets. WRF‐tagging modeling reproduces the spatial distribution of P and ET reasonably after updating surface characteristics. Second, we analyzed and quantified the contribution of ET to atmospheric moisture and regional P in the APENC. The water vapor originating as ET is advected in the atmosphere below 600 hPa to hundreds of kilometers by the prevailing winds. Moisture recycling shows that 5.83% of P comes from local ET during the growing season in the core region of the APENC. Furthermore, to quantify the impact of LUCC on moisture recycling, we designed two different vegetation scenarios (Afforestation and Degradation) by changing land use and vegetation indices in the model. Results show that the precipitation recycling ratio increased to 6.31% in the Afforestation scenario, and decreased to 5.19% in the Degradation scenario, demonstrating the non‐neglectable positive feedback of vegetation on P. An analysis of land surface‐precipitation feedback processes indicates that the LUCC‐induced change in precipitation efficiency dominates P changes. Our findings highlight the importance of LUCC on local and regional moisture recycling in the APENC.

Recent Increase of Spring Precipitation over the Three-River Headwaters Region—Water Budget Analysis Based on Global Reanalysis (ERA5) and ET-Tagging Extended Regional Climate Modeling

Abstract Precipitation change is critical for the Three-River Headwaters (TRH) region, which serves downstream communities in East Asia. The spring (March–May) precipitation over the TRH region shows an increasing trend from 1979 to 2018, as revealed by a Chinese gridded precipitation product (CN05.1). However, the physical processes responsible for this precipitation change are still unclear. This study investigated the characteristics of spring precipitation and the water budget over the TRH region using the ERA5 global reanalysis and the Weather Research and Forecast (WRF) Model. The WRF version employed in this study includes online calculations of the atmospheric water budget and an evapotranspiration (ET) tagging procedure to trace evapotranspired water in the atmosphere. Both ERA5 and WRF reproduce the spring precipitation increase. Moreover, WRFD02 (with a 3-km domain) reduces the wet bias by around 60% and 77% compared to WRFD01 (9 km) and ERA5 (30 km). Both ERA5 and WRF demonstrate that the increase of spring precipitation is dominated by moisture convergence, especially the atmospheric water fluxes from the southern boundary. The enhanced moisture inflow is sustained by enhanced mass flux while the enhanced moisture outflow is sustained by increased moisture. The ET-tagging results further demonstrate the weakened precipitation recycling process because of the significant increase of precipitation produced by external moisture. Compared to ERA5, the reduced wet bias with WRF is attributed to a better spatial resolution of orographic barrier effects, which reduce the southerly water fluxes. The results highlight the potential of regional climate downscaling to better represent the atmospheric water budget in complex terrain.

Representation of Atmospheric Water Budget and Uncertainty Quantification of Future Changes in CMIP6 for the Seven U.S. National Climate Assessment Regions

Abstract Observation-based climate model evaluation and future projections help policymakers in developing action plans for efficient management of water resources and mitigation of the impacts of hazardous extremes. Apart from this socioeconomic importance, the scientific value cannot be overstated, especially in light of the upcoming Fifth U.S. National Climate Assessment (NCA) report. In this study, we evaluate the realism of hydroclimate variability in the historical simulations of a suite of coupled general circulation models (CGCMs) participating in the fifth and sixth phases of the Coupled Model Intercomparison Project (CMIP5 and CMIP6). Our results demonstrate systematic biases in the simulated seasonal precipitation—most prominently, wet bias over the mountainous western United States in winter, and dry bias over the U.S. central plains in summer. A distinctive feature of this work is our focus on the examination of the atmospheric water budget, in particular the relative importance of remote and local contributions—convergence of moisture fluxes and local land surface processes (evapotranspiration) respectively—in helping produce precipitation. This diagnosis reveals that the leading contribution of the remote influence in winter is overestimated by the CMIP6 multimodel mean (MMM), whereas the local influence, which is more influential in summer, is underestimated. Our results aid in understanding the drivers of seasonal precipitation over the United States, where precipitation will likely increase by the end of the century but with significant model disagreement for the summer and fall. In support of ongoing NCA efforts, our study aims to contribute a comprehensive, regional-level analysis of the moisture budget and emphasizes the importance of realistically simulating its major components in CGCMs.

Large‐Scale Afforestation Enhances Precipitation by Intensifying the Atmospheric Water Cycle Over the Chinese Loess Plateau

AbstractAfforestation is an appropriate approach to control soil erosion, but consumes extra water resources. It also exerts feedbacks on local precipitation, affecting the water availability for water‐limited areas. The Chinese Loess Plateau (LP) has implemented the world's largest afforestation program to mitigate severe soil erosion. However, it remains unclear how the atmospheric water cycle responds to large‐scale afforestation under climate change. Here we show that afforestation elevates precipitation in rainy season by intensifying the atmospheric water cycle over the LP. Results show the upward trend of vegetation coverage fraction increased by 3.15% decade−1 and climatological precipitation increased by 54.62 mm after launching the large‐scale afforestation in 1999. Such afforestation also enhanced evapotranspiration by 22.56 mm. We found the moisture inflow and outflow continuously decreased, but more atmospheric moisture was retained since the rate of decline of inflow was less than that of outflow. Using a dynamic precipitation recycling method, we explored changes in precipitation recycling and components of the atmospheric water budget. The precipitation recycling ratio increased from 9.16 ± 0.35 to 10.18 ± 0.28% after the afforestation. Both external and internal branches of the atmospheric water cycle have been strengthened, and their contributions to the increased precipitation are 84.93% and 15.07%, respectively. The afforestation caused a more humid atmosphere, heightened soil moisture‐vegetation‐precipitation feedback, stronger moisture convergence, and more clouds; these changes favored precipitation generation. This study advances the understanding of how afforestation affects regional climate from a precipitation recycling perspective, further assisting decision‐makers to establish sustainable afforestation strategies.

Examining the Regional Co-Variability of the Atmospheric Water and Energy Imbalances in Different Model Configurations-Linking Clouds and Circulation.

Clouds are a key player in the global climate system, affecting the atmospheric water and energy budgets, and they are strongly coupled to the large‐scale atmospheric circulation. Here, we examine the co‐variability of the atmospheric energy and water budget imbalances in three different global model configurations–radiative‐convective equilibrium, aqua‐planet, and global simulations with land. The gradual increase in the level of complexity of the model configuration enables an investigation of the effects of rotation, meridional temperature gradient, land‐sea contrast, and seasonal cycle on the co‐variability of the water and energy imbalances. We demonstrate how this co‐variability is linked to both the large‐scale tropical atmospheric circulation and to cloud properties. Hence, we propose a co‐variability‐based framework that connects cloud properties to the large‐scale tropical circulation and climate system and is directly linked to the top‐down constrains on the system—the water and energy budgets. In addition, we examine how the water and energy budget imbalances co‐variability depends on the temporal averaging scale, and explain its dependency on how stationary the circulation is in the different model configurations. Finally, we demonstrate the effect of an idealized global warming and convective aggregation on this co‐variability.

The Effects of Soil Representation in WRF–CLM on the Atmospheric Moisture Budget

Abstract Soil hydrophysical properties are necessary components in weather and climate simulation, yet the parameter inaccuracies may introduce considerable uncertainty in the representation of surface water and energy fluxes. This study uses seasonal coupled simulations to examine the uncertainties in the North American atmospheric water cycle that result from the use of different soil datasets. Two soil datasets are considered: the State Soil Geographic dataset (STATSGO) from the U.S. Department of Agriculture and the Global Soil Dataset for Earth System Modeling (GSDE) from Beijing Normal University. Two simulations are conducted from 1 June to 31 August 2016–18 using the Weather Research and Forecasting (WRF) Model coupled with the Community Land Model (CLM) version 4 and applying each soil dataset. It is found that changes in soil texture lead to statistically significant differences in daily mean surface water and energy fluxes. The boundary layer thermodynamic structure responds to these changes in surface fluxes resulting in differences in mean CAPE and CIN, leading to conditions that are less conducive for precipitation. The soil-texture-related surface fluxes instigate dynamic responses as well. Low-level wind fields are altered, resulting in differences in the associated vertically integrated moisture fluxes and in vertically integrated moisture flux convergence in the same regions. Through land–atmosphere interactions, it is shown that soil parameters can affect each component of the atmospheric water budget.

Attribution of Dry and Wet Climatic Changes over Central Asia

Abstract Central Asia (CA; 35°–55°N, 55°–90°E) has been experiencing a significant warming trend during the past five decades, which has been accompanied by intensified local hydrological changes. Accurate identification of variations in hydroclimatic conditions and understanding the driving mechanisms are of great importance for water resource management. Here, we attempted to quantify dry/wet variations by using precipitation minus evapotranspiration (P − E) and attributed the variations based on the atmosphere and surface water balances. Our results indicated that the dry season became drier while the wet season became wetter in CA for 1982–2019. The land surface water budget revealed precipitation (96.84%) and vapor pressure deficit (2.26%) as the primary contributing factors for the wet season. For the dry season, precipitation (95.43%), net radiation (3.51%), and vapor pressure deficit (−2.64%) were dominant factors. From the perspective of the atmospheric water budget, net inflow moisture flux was enhanced by a rate of 72.85 kg m−1 s−1 in the wet season, which was mainly transported from midwestern Eurasia. The increase in precipitation induced by the external cycle was 11.93 mm (6 months)−1. In contrast, the drying trend during the dry season was measured by a decrease in the net inflow moisture flux (74.41 kg m−1 s−1) and reduced external moisture from midwestern Eurasia. An increase in precipitation during the dry season can be attributed to an enhancement in local evapotranspiration, accompanied by a 4.69% increase in the recycling ratio. The compounding enhancements between wet and dry seasons ultimately contribute to an increasing frequency of both droughts and floods.

Impacts of Variations in Caspian Sea Surface Area on Catchment‐Scale and Large‐Scale Climate

AbstractThe Caspian Sea (CS) is the largest inland lake in the world. Large variations in sea level and surface area occurred in the past and are projected for the future. The potential impacts on regional and large‐scale hydroclimate are not well understood. Here, we examine the impact of CS area on climate within its catchment and across the northern hemisphere, for the first time with a fully coupled climate model. The Community Earth System Model (CESM1.2.2) is used to simulate the climate of four scenarios: (a) larger than present CS area, (b) current area, (c) smaller than present area, and (d) no‐CS scenario. The results reveal large changes in the regional atmospheric water budget. Evaporation (e) over the sea increases with increasing area, while precipitation (P) increases over the south‐west CS with increasing area. P‐E over the CS catchment decreases as CS surface area increases, indicating a dominant negative lake‐evaporation feedback. A larger CS reduces summer surface air temperatures and increases winter temperatures. The impacts extend eastwards, where summer precipitation is enhanced over central Asia and the north‐western Pacific experiences warming with reduced winter sea ice. Our results also indicate weakening of the 500‐hPa troughs over the northern Pacific with larger CS area. We find a thermal response triggers a southward shift of the upper troposphere jet stream during summer. Our findings establish that changing CS area results in climate impacts of such scope that CS area variations should be incorporated into climate model simulations, including palaeo and future scenarios.

Identifying drivers of streamflow extremes in West Africa to inform a nonstationary prediction model

West Africa exhibits decadal patterns in the behaviour of droughts and floods, creating challenges for effective water resources management. Proposed drivers of prolonged shifts in hydrological extremes include the impacts of land-cover change and climate variability in the region. However, while future land-degradation or land-use are highly unpredictable, recent studies suggest that prolonged periods of high-flows or increasing flood occurrences could be predicted by monitoring sea-surface temperature (SST) anomalies in the different ocean basins. In this study, we thus examine: i) what ocean basins would be the most suitable for future seamless flood-prediction systems; ii) how these ocean basins affect high-flow extremes (hereafter referred as extreme streamflow); and iii) how to integrate such nonstationary information in flood risk modelling. We first use relative importance analysis to identify the main SST drivers modulating hydrological conditions at both interannual and decadal timescales. At interannual timescales, Pacific Niño (ENSO), tropical Indian Ocean (TIO) and eastern Mediterranean (EMED) constitute the main climatic controls of extreme streamflow over West Africa, while the SST variability in the North and tropical Atlantic, as well as decadal variations of TIO and EMED are the main climatic controls at decadal timescales. Using regression analysis, we then suggest that these SST drivers impact hydrological extremes through shifts in the latitudinal location and the strength of the Intertropical Convergence Zone (ITCZ) and the Walker circulation, impacting the West African Monsoon, especially the zonal and meridional atmospheric water budget. Finally, a nonstationary extreme model, with climate information capturing regional circulation patterns, reveals that EMED SST is the best predictor for nonstationary streamflow extremes, particularly across the Sahel. Predictability skill is, however, much higher at the decadal timescale, and over the Senegal than the Niger catchment. This might be due to stronger impacts of land-use (-cover) and/or catchment properties (e.g. the Inner Delta) on the Niger River flow. Overall, a nonstationary framework for floods can also be applied to drought risk assessment, contributing to water regulation plans and hazard prevention, over West Africa and potentially other parts of the world.

Atmospheric water budget associated with a local heavy precipitation event near the Central Urban Area of Beijing Metropolitan Region

An isolated storm-triggered heavy precipitation event near the Central Urban Area (CUA) of Beijing on 9 August 2011 was simulated using a cloud-scale simulation. The atmospheric water budgets in both the initiation area (TA area) and the heavy rainfall region over the CUA (UAS area) associated with the storm were investigated using the three-dimensional (3D) precipitation equation, respectively. The main results showed that the moisture-related rate (QWV) largely offset the hydrometer-related rate (QCM) in both areas, which is different from the previous studies on topographic rainfall and tropical cyclone rainfall. The magnitudes of the precipitation equation related terms were generally more prominent in the UAS area than the TA area, followed by heavier precipitation rate (PS) in the UAS area, due to stronger upward motion contributed by the mature of the system in the former area. Moreover, the initiation, development and movement of the storm also resulted in different vertical dynamic structures in the two areas. And the differences of vertical dynamic structures and their evolutions triggered different water vapor and hydrometeor budgets in these two contiguous areas. Analysis of vertical profiles of hydrometeors in both areas further confirmed the above conclusions.

Boundary condition and oceanic impacts on the atmospheric water balance in limited area climate model ensembles

Regional climate models (RCMs) are indispensable in climate research, albeit often characterized by biased terrestrial precipitation and water budgets. This study identifies excess oceanic evaporation, in conjunction with the RCMs’ boundary conditions, as drivers contributing to these biases in RCMs with forced sea surface temperatures in a CORDEX RCM ensemble over Europe. The RCMs are relaxed to the prescribed lateral boundary conditions originating from a global model, effectively matching the driving model's overall atmospheric moisture flux divergence. As a consequence, excess oceanic evaporation results in positive precipitation biases over land due to forced internal recycling of moisture to maintain the overall flux divergence prescribed by the boundary conditions. This systematic behaviour is shown through an analysis of long-term atmospheric water budgets and atmospheric moisture exchange between oceanic and continental areas in a multi-model ensemble.

Groundwater age of spring discharges under changing permafrost conditions: the Khangai Mountains in central Mongolia

Obtaining a better understanding of groundwater dynamics in permafrost zones is a critical issue in permafrost hydrology. This includes assessing the impacts of climate change on permafrost thaw and ground ice-melt. Both permafrost thaw and ground ice-melt can be related to groundwater discharges (i.e. spring discharges), and spring water is an important local water resource; accordingly, changes in these processes can have large impacts on local people and their subsistence activities. To detect permafrost thaw and ground ice-melt in the permafrost zone of Mongolia, groundwater ages of several spring discharges were determined using two transient tracers: tritium (3H) and chlorofluorocarbons (CFCs). Spring water samples were collected seasonally from 2015 to 2019 at seven spring sites around the Khangai Mountains in central Mongolia. The sites included two thermokarst landscapes on the northern and southern sides of the mountains. The 3H and CFC concentrations in the spring water in the thermokarst landscapes were very low, especially on the southern side of the mountains, and the estimated mean groundwater age for these sites was older than that for the other sampled springs. Consequently, the young water ratios of the thermokarst sites were lower than those for the other springs. This ratio, however, showed a gradual increase with time, which indicates that recently recharged rainwater began to contribute to the spring discharge at the thermokarst sites. An atmospheric water budget analysis indicated that net recharge from modern and recent precipitation to shallow groundwater in the summer season was almost zero on the southern side of the mountains. Thus, we inferred that the spring water at the thermokarst sites on the southern side of the mountains contained large amounts of ground ice-melt water.

Atmospheric driving mechanisms of extreme precipitation events in July of 2017 and 2018 in western Japan

The occurrence of extreme precipitation events is now a serious concern in recent years in Japan. This study explores the atmospheric driving mechanisms of two extreme precipitation events occurred during 5–6 July 2017 and 5–8 July 2018 over western Japan. We identified that the atmospheric transport of large amounts of moisture and wind streams with wind speed of minimum 15 m s−1 from south of Japan towards north on the days before these torrential precipitation events are mainly responsible for the July 2017 and July 2018 floods over western Japan. However, the contributions from the moisture advections (both vertical and horizontal) to the atmospheric water budget plays key roles to intensify the precipitations during the said torrential events. We also find that the prominent moisture flux convergence and well-developed moist conditions mainly maintain these heavy precipitation events over the downpour affected area. Our overall analysis suggests that the atmospheric factors driving to all these two heavy precipitation events are qualitatively robust and vital to explain the mechanism of extreme precipitations.

Assessing changes in the atmospheric water budget as drivers for precipitation change over two CORDEX-CORE domains

This study evaluates the projected changes in the atmospheric water budget and precipitation under the RCP8.5 scenario over two CORDEX-CORE domains: South America (SAM) and Europe (EUR). An ensemble of five twenty-first century projections with the Regional Climate Model version 4 (RegCM4) and their driving Global Climate Models (GCMs) are analyzed in terms of the atmospheric water budget terms (precipitation, P; evapotranspiration, ET; and moisture flux convergence, C). Special focus is on four subregions: Amazon (AMZ), La Plata basin (LPB), Mid-Europe (ME) and Eastern Europe (EA). The precipitation change signal in SAM presents a dipole pattern, i.e. drier conditions in AMZ and wetter conditions in LPB. Over the two European regions a seasonality is evident, with an increase of ~ 25% in precipitation for DJF and a decrease of ~ 35% in JJA. The atmospheric water budget drivers of precipitation change vary by region and season. For example, in DJF the main drivers are related to the large-scale moisture flux convergence, while in JJA over the AMZ atmospheric moisture flux convergence plays only a minor role and local processes dominate. For JJA in the GCMs the high values of the residual term do not allow us to assess which mechanisms drive the precipitation change signal over the AMZ and LPB, respectively. Same conclusions are found for the RegCM4 JJA simulations over the LPB and EA. This points to the importance of the spatial resolution of climate simulations and the role of parameterization schemes in climate models. Our work illustrates the usefulness of analyzing regional water budgets for a better understanding of precipitation change patterns around our globe.

Constraint on precipitation response to climate change by combination of atmospheric energy and water budgets

Global mean precipitation is expected to increase with increasing temperatures, a process which is fairly well understood. In contrast, local precipitation changes, which are key for society and ecosystems, demonstrate a large spread in predictions by climate models, can be of both signs and have much larger magnitude than the global mean change. Previously, two top-down approaches to constrain precipitation changes were proposed, using either the atmospheric water or energy budget. Here, using an ensemble of 27 climate models, we study the relative importance of these two budgetary constraints and present analysis of the spatial scales at which they hold. We show that specific geographical locations are more constrained by either one of the budgets and that the combination of water and energy budgets provides a significantly stronger constraint on the spatial scale of precipitation changes under anthropogenic climate change (on average about 3000 km, above which changes in precipitation approach the global mean change). These results could also provide an objective way to define the scale of ‘regional’ climate change.