Soil Moisture Precipitation Feedback Research Articles

Weaker land–atmosphere coupling in global storm-resolving simulation

The debate on the sign of the soil moisture-precipitation feedback remains open. On the one hand, studies using global coarse-resolution climate models have found strong positive feedback. However, such models cannot represent convection explicitly. On the other hand, studies using km-scale regional climate models and explicit convection have reported negative feedback. Yet, the large-scale circulation is prescribed in such models. This study revisits the soil moisture-precipitation feedback using global, coupled simulations conducted for 1 y with explicit convection and compares the results to coarse-resolution simulations with parameterized convection. We find significant differences in a majority of points with feedback that is weaker and dominantly negative with explicit convection. The model with explicit convection is more often in a wet regime and prefers the triggering of convection over dry soil in the presence of soil moisture heterogeneity, in contrast to the coarse-resolution model. Further analysis indicates that the feedback not only between soil moisture and evapotranspiration but also between evapotranspiration and precipitation is weaker, in better agreement with observations. Our findings suggest that coarse-resolution models may not be well suited to study aspects of climate change over land such as changes in droughts and heatwaves.

Soil moisture precipitation feedbacks in the Eastern European Alpine region in convection-permitting climate simulations.

A novel convection permitting modelling framework that combines a pseudo-global warming approach with continuously forced deep soil moisture from prescribed perturbation storylines is applied in the Eastern European Alpine region and parts of the Pannonian Basin to investigate soil moisture precipitation (SMP) feedbacks on summertime precipitation and the feedbacks' role under changed climate conditions. A set of 1-year convection-permitting (3 km horizontal grid spacing) soil moisture sensitivity simulations with the regional climate model of the Consortium for Small-Scale Modelling in Climate Mode are conducted. In order to account for global warming, end-of-the-century climate change effects from four global climate models, projecting the greenhouse gas concentration scenario RCP 8.5, are imprinted. The simulations reveal that (1) the locations of precipitation events are highly sensitive to soil moisture modifications while intensities and the internal structure of precipitation events are nearly unaffected and (2) high precipitation intensities are more likely in combinations with positive temporal but distinctive (either strong positive or strong negative) spatial SMP coupling. Low precipitation intensities are in favour of combinations of negative temporal and positive spatial coupling. The analyses suggest that soil moisture at a given time acts as a guiding field for the location of the next precipitation event. Interestingly, this behaviour is independent of climate change, although the coupling strength's increase is 1.5-1.7 times larger than expected from linear climate change scaling when climate becomes 50% dryer. Finally, it is found that (1) local deviations in the climate change signal of summertime precipitation in the range of up to ±40% are caused by uncertainty in deep soil moisture in the range of ±10% and (2) these local deviations in the climate change signal are dominated by soil moisture uncertainty in future climate conditions.

Soil moisture–precipitation feedbacks in pre‐ and post‐monsoon landfalling tropical cyclones in Bay of Bengal

AbstractThe Bay of Bengal (BoB) experiences an average of three to four tropical cyclones (TCs) annually. The high population density of surrounding countries often leads to disastrous consequences when a TC makes landfall. As a result, it is critical to understand the evolution and intensity of rainfall associated with a TC that originates in the BoB. In this study, we examine the impact of initial soil moisture (SM) conditions on the TC track, TC recycled precipitation, and other TC variables using the Weather Research and Forecasting (WRF) model upgraded with Eulerian water‐tagging capabilities. We simulated pre‐monsoon TCs Amphan, Titli, Viyaru and post‐monsoon cyclones Phailin, Titli and Helen originating in the BoB. We conducted sensitivity experiments with dry and wet initial SM conditions to determine the impact of initial SM changes on TCs. We also generated four control simulations for each TC by changing the initial time to assess the effect of internal model variability. Our results indicate that initial SM conditions impact TC more than the internal model variability. We find that changes in the initial SM affect the latent heat flux, which influences the temperature and the synoptic wind pattern over the entire domain, resulting in changes in the TC properties. We find the feedback of SM to TC precipitation (quantified as recycled precipitation) is stronger as the TC approaches the landfall. The post‐landfall recycling ratio for pre‐monsoon TCs is approximately 5%–10%, but is around 20%–30% for post‐monsoon TCs. We observe that the Viyaru, Titli and Helen TC tracks are more sensitive to the initial SM conditions compared to the other three TCs. In addition to SM, we find that factors such as proximity to land, and TC intensity also have a role in determining the quantity of recycled precipitation for a TC.

Diagnosing the compound seasonal soil moisture-hydroclimate interaction regime on the Tibetan Plateau using multi-high-resolution reanalysis products and one regional climate model

Land-atmosphere energy and moisture exchanges exert great impacts on local and regional climate. However, high uncertainties exist in the recent land–atmosphere interactions due to scarce observations and difficulties in modeling at high elevations and cold regions. This study applied multiple high-resolution reanalysis products (ERA5-land, GLDAS Noah and CLSM products) and one regional climate model, RegCM4, to diagnose the interaction pattern and strength of seasonal soil moisture and hydroclimate on the Tibetan Plateau (TP) using a conditional correlation coefficient method and the global land–atmosphere coupling experimental modeling approach. A compound aggregation method is applied to recognize hot spots with strong soil moisture-hydroclimate interactions among multiple data. As a result, the Changtang Plateau in the inner TP, the sources of the Yellow, Yangtze, Mekong, Salween, and Lancang Rivers and part of the Brahmaputra River basin in the south-southeastern TP are diagnosed with strong land–atmosphere interactions in most seasons. In summer, the coupling strength is stronger, and the covered area is much wider and spatially continuous as the climate turns warm. All applied data indicate a positive dominant soil moisture-precipitation feedback, and a negative soil moisture-temperature feedback at the hot spots. Meanwhile, the soil moisture-runoff feedback is strong and positive at most parts of the TP, especially at the hot spots and in summer. Evapotranspiration acts as a positive linkage in the soil moisture-precipitation-temperature interactions, while the nexus of soil moisture, evapotranspiration and runoff is complicated. This study contributes to understanding local land-hydroclimate interactions in the high elevation and cold climate of the TP. Additionally, the found the proposed compound aggregation method efficient for compound studies.

Impacts of combined microphysical and land-surface uncertainties on convective clouds and precipitation in different weather regimes

Abstract. To reduce the underdispersion of precipitation in convective-scale ensemble prediction systems, we investigate the relevance of microphysical and land-surface uncertainties for convective-scale predictability. We use three different initial soil moisture fields and study the response of convective precipitation to varying cloud condensation nuclei (CCN) concentrations and different shape parameters of the cloud droplet size distribution (CDSD) by applying a novel combined-perturbation strategy. Using the new ICOsahedral Non-hydrostatic (ICON) model, we construct a 60-member ensemble for cases with summertime convection under weak and strong synoptic-scale forcing over central Europe. We find a systematic positive soil moisture–precipitation feedback for all cases, regardless of the type of synoptic forcing, and a stronger response of precipitation to different CCN concentrations and shape parameters for weak forcing than for strong forcing. While the days with weak forcing show a systematic decrease in precipitation with increasing aerosol loading, days with strong forcing also show nonsystematic responses for some values of the shape parameters. The large magnitudes of precipitation deviations compared to a reference simulation ranging between −23 % and +18 % demonstrate that the uncertainties investigated here and, in particular, their collective effect are highly relevant for quantitative precipitation forecasting of summertime convection in central Europe. A rainwater budget analysis is used to identify the dominating source and sink terms and their response to the uncertainties applied in this study. Results also show a dominating cold-rain process for all cases and a strong but mostly nonsystematic impact on the release of latent heat, which is considered to be the prime mechanism for the upscale growth of small errors affecting the predictability of convective systems. The combined ensemble spread when accounting for all three uncertainties lies in the same range as the ones from an operational convective-scale ensemble prediction system with 20 members determined in previous studies. This indicates that the combination of different perturbations used in our study may be suitable for ensemble forecasting and that this method should be evaluated against other sources of uncertainty.

How morning soil moisture conditions influence afternoon precipitation events in South America

AbstractThe land–atmosphere interactions play an important role in the South American climate system. Previous studies have explored the coupling between soil moisture (SM), surface heat fluxes and atmospheric variables such as temperature and precipitation; however, the SM–precipitation feedback is still debated, especially at the diurnal scale. We computed three diurnal local coupling diagnostics between spatial, temporal and heterogeneity morning SM anomalies and the occurrence of afternoon precipitation events. We analyse South America in the period October–March 1983–2012 with the ERA5 reanalysis and the RCA4 regional climate model. Two 30‐year climate simulations are performed: a control and an uncoupled simulation where the SM is prescribed with daily climatological values, limiting the SM–atmosphere interaction. Comparing both simulations we isolate the effect of SM variability, allowing us to confirm that the diagnostics are indeed showing the contribution of the SM–precipitation coupling. We test different methods of calculating the morning SM anomalies and observe that all diagnostics show some methodological sensitivity, especially the spatial and temporal diagnostics. Despite the differences, in eastern Brazil we find a preference for afternoon precipitation to develop when the soil is wetter and heterogeneous, over points that are wetter than their surroundings. Towards southeastern South America, there is a spatial and temporal preference for drier or average conditions, depending on the method, with heterogeneity preference, and the same is observed in southwestern Amazonia in RCA4. Ultimately, it is important that future studies disentangle the spatiotemporal coupling mechanisms that may act simultaneously into its distinct components to avoid erroneous assumptions and contradictory results.

Identification of Soil Moisture–Precipitation Feedback Based on Temporal Information Partitioning Networks

AbstractThe underlying mechanisms by which soil moisture might affect precipitation are essential for weather prediction and climate change projection. Process‐based models that are capable of providing physical explanation are often tripped in concerns about model uncertainty in structure, data, and parameters, etc. The information theory has provided a new paradigm to explain the feedback system. This study focused on to identify the soil moisture–precipitation feedback based on direct long‐term observations using an information‐based method, Temporal Information Partitioning Networks (TIPNets). Normalized transfer entropy was proposed to describe feedback strength. In comparison with Granger causality and correlation, the TIPNets method was independent of parameterizations and spatiotemporal resolution effects, also elucidate information‐theoretic insights. The results in the case study of Illinois, indicated that soil moisture–precipitation feedback existed and was significant during May to mid‐July. The bidirectional dominant lags of 3–10 and 6–17 days were both shorter in summer. Areas with strong feedback were located in south‐central Illinois. Besides, the wooded grassland coverage was the most related land use type to feedback strength, which could be one kind of the positive feedback mechanism in Illinois.

The role of mid‐tropospheric moistening and land‐surface wetting in the progression of the 2016 Indian monsoon

AbstractAccurately predicting the Indian monsoon is limited by inadequate understanding of the underlying processes, which feed into systematic model biases. Here we aim to understand the dynamic and thermodynamic features associated with the progression of the monsoon, using 2016 as a representative year, with the help of convection‐permitting simulations of the Met Office Unified Model. Simulations are carried out in a 4 km resolution limited‐area model, nested within a coarser global model. Two major processes thought to influence the northwestward progression of the monsoon are: (a) the interaction between the low‐level monsoon flow and a mid‐tropospheric dry‐air intrusion from the northwest, and (b) land–atmosphere interactions. We find that the 4 km limited‐area model simulates the mid‐tropospheric moistening that erodes the northwesterly dry intrusion, pushing the northern limit of moist convection northwestwards. The surface soil moisture also plays a major role at the leading edge of the monsoon progression. The heavy rains associated with the local onset wet the soil, reducing the sensitivity of surface fluxes to soil moisture and weakening the land influence on further progression of monsoon rains. The 4 km model is tested with an alternative land‐surface configuration to explore its sensitivity to land‐surface processes. We find that the choice of soil and vegetation ancillaries affects the time‐scales of soil moisture–precipitation feedback and the timing of diurnal convection, thereby affecting the local onset. We further compare these simulations with a parametrized convection run at 17 km resolution to isolate the effects of convective parametrization and resolution. The model with explicit convection better simulates the dynamic and thermodynamic features associated with the progression of the monsoon.

Early warm-season mesoscale convective systems dominate soil moisture–precipitation feedback for summer rainfall in central United States

Land-atmosphere interactions play an important role in summer rainfall in the central United States, where mesoscale convective systems (MCSs) contribute to 30 to 70% of warm-season precipitation. Previous studies of soil moisture-precipitation feedbacks focused on the total precipitation, confounding the distinct roles of rainfall from different convective storm types. Here, we investigate the soil moisture-precipitation feedbacks associated with MCS and non-MCS rainfall and their surface hydrological footprints using a unique combination of these rainfall events in observations and land surface simulations with numerical tracers to quantify soil moisture sourced from MCS and non-MCS rainfall. We find that early warm-season (April to June) MCS rainfall, which is characterized by higher intensity and larger area per storm, produces coherent mesoscale spatial heterogeneity in soil moisture that is important for initiating summer (July) afternoon rainfall dominated by non-MCS events. On the other hand, soil moisture sourced from both early warm-season MCS and non-MCS rainfall contributes to lower-level atmospheric moistening favorable for upscale growth of MCSs at night. However, soil moisture sourced from MCS rainfall contributes to July MCS rainfall with a longer lead time because with higher intensity, MCS rainfall percolates into deeper soil that has a longer memory. Therefore, early warm-season MCS rainfall dominates soil moisture-precipitation feedback. This motivates future studies to examine the contribution of early warm-season MCS rainfall and associated soil moisture anomalies to predictability of summer rainfall in the major agricultural region of the central United States and other continental regions frequented by MCSs.

Is the soil moisture precipitation feedback enhanced by heterogeneity and dry soils? A comparative study

AbstractThe interaction between the land surface and the atmosphere is a crucial driver of atmospheric processes. Soil moisture and precipitation are key components in this feedback. Both variables are intertwined in a cycle, that is, the soil moisture – precipitation feedback for which involved processes and interactions are still discussed. In this study the soil moisture – precipitation feedback is compared for the sempiternal humid Ammer catchment in Southern Germany and for the semiarid to subhumid Sissili catchment in West Africa during the warm season, using precipitation datasets from the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS), from the German Weather Service (REGNIE) and simulation datasets from the Weather Research and Forecasting (WRF) model and the hydrologically enhanced WRF‐Hydro model. WRF and WRF‐Hydro differ by their representation of terrestrial water flow. With this setup we want to investigate the strength, sign and variables involved in the soil moisture – precipitation feedback for these two regions. The normalized model spread between the two simulation results shows linkages between precipitation variability and diagnostic variables surface fluxes, moisture flux convergence above the surface and convective available potential energy in both study regions. The soil moisture – precipitation feedback is evaluated with a classification of soil moisture spatial heterogeneity based on the strength of the soil moisture gradients. This allows us to assess the impact of soil moisture anomalies on surface fluxes, moisture flux convergence, convective available potential energy and precipitation. In both regions the amount of precipitation generally increases with soil moisture spatial heterogeneity. For the Ammer region the soil moisture – precipitation feedback has a weak negative sign with more rain near drier patches while it has a positive signal for the Sissili region with more rain over wetter patches. At least for the observed moderate soil moisture values and the spatial scale of the Ammer region, the spatial variability of soil moisture is more important for surface‐atmosphere interactions than the actual soil moisture content. Overall, we found that soil moisture heterogeneity can greatly affect the soil moisture – precipitation feedback.

Mechanisms of European summer drying under climate change

AbstractThe geography of Europe as a continental landmass, located between the arid Sahara and the cold high latitudes (both are dry in terms of absolute humidity), dictates the reliance during summer of Southern Europe (south of 45°N) on stored water from winter and spring, and of Northwestern Europe on a small concentrated low-level moisture jet from the North Atlantic. In a recent study, we explained the projected winter precipitation decline over the Mediterranean under climate change as due to shifts in upper tropospheric stationary waves and to the regional-scale land-water warming contrast. Here, based on the analysis of observations and output from Coupled Model Intercomparison Project phase 5 models,we expand this theory further, documenting howthe winter precipitation decline expands into Southern Europe during spring, dictated by similar dynamical mechanisms, depleting soil moisture and setting the stage for drier summers via soil moisture-precipitation feedbacks. Over Northwestern Europe, an anomalous anticyclonic circulation west of the British Isles displaces the low-level moisture jet northwards, limiting moisture supply, and reducing low-level relative humidity (RH) and rainfall. Finally, we discuss how this comprehensive perspective of European summer climate change can help better understand the variations across model projections, and pave the way for their reduction.

Changing summer precipitation variability in the Alpine region: on the role of scale dependent atmospheric drivers

Summer precipitation totals in the Alpine Region do not exhibit a systematic trend over the last 120 years. However, we find significant low frequency periodicity of interannual variability which occurs in synchronization with a dominant two-phase state of the atmospheric circulation over the Alps. Enhanced meridional flow increases precipitation variability through positive soil moisture precipitation feedbacks on the regional scale, whereas enhanced zonal flow results in less variability through constant moisture flow from the Atlantic and suppressed feedbacks with the land surface. The dominant state of the atmospheric circulation over the Alps in these periods appears to be steered by zonal sea surface temperature gradients in the mid-latitude North Atlantic. The strength and the location of the westerlies in the mid-latitude Atlantic play an important role in the physical mechanisms linking atmosphere and oceanic temperature gradients and the meridional/zonal circulation characteristics.

The Continental-Scale Soil-Moisture Precipitation Feedback in Europe with Parameterized and Explicit Convection

AbstractSoil moisture atmosphere interactions are key elements of the regional climate system. There is a well-founded hope that a more accurate representation of the soil moisture-precipitation feedback would improve the simulation of summer precipitation on daily to seasonal, to climate time scales. However, uncertainties have persistently remained as the simulated feedback is strongly sensitive to the model representation of deep convection. Here we assess the feedback representation using a GPU-accelerated version of the regional climate model COSMO. We simulate and compare the impact of continental-scale springtime soil-moisture anomalies on summer precipitation at convection-resolving (2.2 km) and convection-parameterizing resolution (12 km). We conduct re-analysis-driven simulations of 10 summer seasons (1999-2008) in continental Europe. While both simulations qualitatively agree on a positive sign of soil moisture-induced precipitation, they strongly differ in precipitation frequency: When convection is parameterized, wetter soil predominantly leads to more frequent precipitation events, and when convection is treated explicitly, they primarily become more intense. The results indicate that the sensitivity to soil moisture is stronger with parameterized convection, suggesting that the land surface-atmosphere coupling may be overestimated. In addition, the feedback’s sensitivity in complex terrain is assessed for soil perturbations of different horizontal scales. The convection-resolving simulations confirm a negative feedback for sub-continental soil moisture anomalies, which manifests itself in a local decrease of wet-hour frequency. However, the intensity feedback reinforces precipitation events at the same time (positive feedback). The two processes are represented differently in simulations with explicit and parameterized convection, explaining much of the difference between the two simulations.

Understanding the Distinct Impacts of MCS and Non-MCS Rainfall on the Surface Water Balance in the Central United States Using a Numerical Water-Tagging Technique

ABSTRACTWarm-season rainfall associated with mesoscale convective systems (MCSs) in the central United States is characterized by higher intensity and nocturnal timing compared to rainfall from non-MCS systems, suggesting their potentially different footprints on the land surface. To differentiate the impacts of MCS and non-MCS rainfall on the surface water balance, a water tracer tool embedded in the Noah land surface model with multiparameterization options (WT-Noah-MP) is used to numerically “tag” water from MCS and non-MCS rainfall separately during April–August (1997–2018) and track their transit in the terrestrial system. From the water-tagging results, over 50% of warm-season rainfall leaves the surface–subsurface system through evapotranspiration by the end of August, but non-MCS rainfall contributes a larger fraction. However, MCS rainfall plays a more important role in generating surface runoff. These differences are mostly attributed to the rainfall intensity differences. The higher-intensity MCS rainfall tends to produce more surface runoff through infiltration excess flow and drives a deeper penetration of the rainwater into the soil. Over 70% of the top 10th percentile runoff is contributed by MCS rainfall, demonstrating its important contribution to local flooding. In contrast, lower-intensity non-MCS rainfall resides mostly in the top layer and contributes more to evapotranspiration through soil evaporation. Diurnal timing of rainfall has negligible effects on the flux partitioning for both MCS and non-MCS rainfall. Differences in soil moisture profiles for MCS and non-MCS rainfall and the resultant evapotranspiration suggest differences in their roles in soil moisture–precipitation feedbacks and ecohydrology.

Seasonal variability of soil moisture-precipitation feedbacks over India

Soil moisture plays a significant role in partitioning surface energy fluxes into latent and sensible heat components and is fundamental for process level understanding of land-atmosphere interactions. Realistic simulations of such interactions by models are constrained due to intrinsic model assumptions. This study examines convective triggering based on soil moisture by employing a framework of coupling diagnostics called Convective triggering potential (CTP) and humidity index (HILow) to classify land regions into various feedback regimes for each season between 2005 and 2015. Results show that atmospherically controlled cases prevail in most of the regions for all seasons. Temporal regime probability values (TRP) suggested a dominant wet regime in southern India and a dominant dry regime in central and western India. Precipitation events triggered in wet advantage conditions were found to have larger accumulations than similar events triggered in dry advantage conditions for all the seasons. This study highlights separate seasonal regime classification and emphasizes on how potential regime hotspots vary for each season.

A sensitivity study on the response of convection initiation to in situ soil moisture in the central United States

Soil moisture can affect precipitation, however there is significant debate about the sign and strength of land–atmosphere coupling. This may be due to the differences regarding the selection of data sources, the presence of atmospheric persistence, and the spatial and temporal scales of the analysis. This study is a sensitivity analysis that quantifies how each of these factors influences land–atmosphere coupling in the central United States from 2005 to 2007. Four different sources of soil moisture are used to represent soil moisture: in situ measurements and three satellite products. The Thunderstorm Observation by Radar (ThOR) algorithm is used to identify convective events. The results show that warm-season afternoon convection initiates preferentially over dry soil, if in situ measurements are used. However, when satellite data are used the sign and strength of the soil moisture-precipitation coupling varies depending on which satellite dataset is used. This demonstrates that evaluations of land–atmosphere coupling strength are sensitive to the source of soil moisture. Our results also show that accounting for atmospheric persistence tends to weaken apparent land–atmosphere coupling. Changing the spatial scale of the analysis can also influence the sign and coupling strength. Analyses that are performed at a coarser spatial resolution tend to indicate a wet preference because they do not capture the local negative feedbacks. This study demonstrates that contradictions in the literature regarding the sign and strength of soil moisture-precipitation feedbacks can be partly attributed to differences in datasets, methods and scale of the analysis.

Disentangling Drivers of Meteorological Droughts in the European Greater Alpine Region During the Last Two Centuries.

This study investigates the atmospheric drivers of severe precipitation deficits in the Greater Alpine Region during the last 210 years utilizing a daily atmospheric circulation type reconstruction. Precipitation deficit tends to be higher during periods with more frequent anticyclonic (dry) and less frequent cyclonic (wet) circulation types, as would be expected. However, circulation characteristics are not the main drivers of summer precipitation deficit. Dry soils in the warm season tend to limit precipitation, which is particularly the case for circulation types that are sensitive to a soil moisture‐precipitation feedback. This mechanism is of specific relevance in explaining the major drought decades of the 1860s and 1940s. Both episodes show large negative precipitation anomalies in spring followed by increasing frequencies of circulation types sensitive to soil moisture precipitation feedbacks. The dry springs of the 1860s were likely caused by circulation characteristics that were quite different from those of recent decades as a consequence of the large spatial extent of Arctic sea ice at the end of the Little Ice Age. On the other hand, the dry springs of the 1940s developed under a persistent positive pressure anomaly across Western and Central Europe, triggered by positive sea surface temperatures in the western subtropical Atlantic.

Relative impact of aerosol, soil moisture, and orography perturbations on deep convection

Abstract. The predictability of deep moist convection depends on many factors, such as the synoptic-scale flow, the geographical region (i.e., the presence of mountains), and land surface–atmosphere as well as aerosol–cloud interactions. This study addresses all these factors by investigating the relative impact of orography, soil moisture, and aerosols on precipitation over Germany in different weather regimes. To this end, we conduct numerical sensitivity studies with the COnsortium for Small-sale MOdelling (COSMO) model at high spatial resolution (500 m grid spacing) for 6 days with weak and strong synoptic forcing. The numerical experiments consist of (i) successive smoothing of topographical features, (ii) systematic changes in the initial soil moisture fields (spatially homogeneous increase/decrease, horizontal uniform soil moisture, different realizations of dry/wet patches), and (iii) different assumptions about the ambient aerosol concentration (spatially homogeneous and heterogeneous fields). Our results show that the impact of these perturbations on precipitation is on average higher for weak than for strong synoptic forcing. Soil moisture and aerosols are each responsible for the maximum precipitation response for three of the cases, while the sensitivity to terrain forcing always shows the smallest spread. For the majority of the analyzed cases, the model produces a positive soil moisture–precipitation feedback when averaged over the entire model domain. Furthermore, the amount of soil moisture affects precipitation more strongly than its spatial distribution. The precipitation response to changes in the CCN concentration is more complex and case dependent. The smoothing of terrain shows weaker impacts on days with strong synoptic forcing because surface fluxes are less important and orographic ascent is still simulated reasonably well, despite missing fine-scale orographic features. We apply an object-based characterization to identify whether and how the perturbations affect the structure, location, timing, and intensity of precipitation. These diagnostics reveal that the structure component, comparing the size and shape of precipitating objects to the reference simulation, is on average highest in the soil moisture and aerosol simulations, often due to changes in the maximum precipitation amounts. This indicates that the dominant mechanisms for convection initiation remain but that precipitation amounts depend on the strength of the trigger mechanisms. Location and amplitude parameters both vary over a much smaller range. Still, the temporal evolution of the amplitude component correlates well with the rain rate. Our results suggest that for quantitative precipitation forecasting, both aerosols and soil moisture are of similar importance and that their inclusion in convective-scale ensemble forecasting containing classical sources of uncertainty should be assessed in the future.

Land–atmosphere feedbacks exacerbate concurrent soil drought and atmospheric aridity

Compound extremes such as cooccurring soil drought (low soil moisture) and atmospheric aridity (high vapor pressure deficit) can be disastrous for natural and societal systems. Soil drought and atmospheric aridity are 2 main physiological stressors driving widespread vegetation mortality and reduced terrestrial carbon uptake. Here, we empirically demonstrate that strong negative coupling between soil moisture and vapor pressure deficit occurs globally, indicating high probability of cooccurring soil drought and atmospheric aridity. Using the Global Land Atmosphere Coupling Experiment (GLACE)-CMIP5 experiment, we further show that concurrent soil drought and atmospheric aridity are greatly exacerbated by land-atmosphere feedbacks. The feedback of soil drought on the atmosphere is largely responsible for enabling atmospheric aridity extremes. In addition, the soil moisture-precipitation feedback acts to amplify precipitation and soil moisture deficits in most regions. CMIP5 models further show that the frequency of concurrent soil drought and atmospheric aridity enhanced by land-atmosphere feedbacks is projected to increase in the 21st century. Importantly, land-atmosphere feedbacks will greatly increase the intensity of both soil drought and atmospheric aridity beyond that expected from changes in mean climate alone.

On the uniformity of rainfall distribution over India

Understanding response of temporal distribution, timing, frequency and amount of high and low intensity rainfall to warming is important in water resources management. In this paper, Relative Entropy is used to investigate the spatial variability and change in uniformity of rainfall distribution over India. Temporal trends in atmospheric temperature can alter the frequency and amount of high and low intensity rainfall events, which influence the uniformity of rainfall distribution. The study is divided into two time periods, 1951–1980 and 1981–2010 based on time trend in annual mean temperature. The sensitivity of rainfall uniformity and high and low intensity rainfall events to annual mean temperature and the degree of coherence between them are investigated. The uniformity of rainfall distribution shows a significant spatial variability. Significant changes are observed in both the amount and timing of rainfall across India. A significant association between rainfall uniformity and low intensity of rainfall is observed in the recent past over a larger aerial extent compared to the distant past. It is concluded that rise in temperature modifies both high and low intensity rainfall events, thus altering the uniformity in rainfall distribution. A regionally varied strength of coherence between rainfall uniformity and high and low intensity rainfall is observed which may be due to regionally dependent soil moisture-precipitation feedbacks.