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Present study investigates the characteristics and factors of summer drought variations over Asia during 1950–2020 using 3-month Standardized Precipitation Evapotranspiration Index (SPEI03) in July. The leading mode of Asian summer drought variations exhibits a roughly north–south contrasting distribution across 30° N with dominant interannual variability. The interannual variation of the leading mode is associated with both precipitation and temperature. In comparison, the contribution of precipitation is larger in the eastern part of the mid-latitude Asia. The Asian summer drought variations subject to both individual and combined impacts of preceding winter equatorial central-eastern Pacific (ECEP) sea surface temperature (SST) anomalies and concurrent North Atlantic (NA) tripole SST anomalies. Preceding ECEP SST anomalies induce anomalous vertical motion and precipitation over the mid-latitude Asia through large-scale divergence and convergence in previous winter and spring. The resulted soil moisture anomalies persist to summer and are conducive to anomalous summer precipitation through evaporation. The accompanying changes in cloud-radiation, surface longwave radiation and sensible heat flux induce temperature and evapotranspiration anomalies. The NA tripole SST anomalies induce anomalous vorticity forcing over the western mid-latitude NA. This contributes to a wave train that propagates from the NA to East Asia and affects wind and vertical motion over the mid-latitude Asia. [ABSTRACT FROM AUTHOR]

Soil moisture (SM) is a key component of the Earth's climate system. Accurate prediction of SM is essential for understanding and predicting short-term climate variability. While Sea Surface Temperature (SST) has been shown to improve SM prediction, the pathways of its impact and the underlying physical mechanisms are not yet fully understood. This study aims to assess the leading influence of the preceding December–February [DJF (− 1)] North Tropical Atlantic (NTA) SST on the following September–November (SON) Northeastern Eurasia (NEE) SM. Our analysis reveals a significant cross-seasonal influence of NTA SST on NEE SM, with a 9-month lead time (r = 0.57). To investigate the physical mechanisms underlying this relationship, we employ both observational data and model simulation. The results suggest that the warming of DJF (− 1) NTA SST persists into June–August (JJA), triggering Rossby waves propagating eastward from the North Atlantic to the Eurasia, which forms an anomalous cyclone over NEE. The cyclone leads to lowered barometric pressure, enhanced upward movement of air currents, and anomalous southerly winds bringing abundant water moisture supply. The precipitation over NEE increases correspondingly, leading to positive SM anomalies in JJA. The positive feedback between SM and precipitation contributes to the persistence of SM anomalies to subsequent SON season. Our findings provide new insights into the physical mechanisms by which NTA SST impact SON SM and improve the predictability of SON SM in NEE. [ABSTRACT FROM AUTHOR]

Latent heat released during orographic precipitation over the Western Ghat (WG) Mountain drives the Indian Summer Monsoon. Instrumental data record a considerable spatiotemporal variation of rainfall amount along the mountain. Although Indian teak (Tectona grandis LF) samples from WG have been used earlier for reconstructing past monsoon rainfall, the effect of rainfall variation on the annual ring growth pattern along the mountain has not been extensively studied yet. To address this issue, tree-ring width data series from three locations—Dahanu (1763 -1985), Nagerhole (1703–2016), and Tekkedy (1785–2003) are presented in this study. The locations are situated along WG from north to south. Monthly mean rainfall data obtained from the nearest observatories show a decreasing (increasing) rainfall amount from north to south during summer monsoon (pre and post-monsoon). We obtain a significant positive correlation between ring width indices and monsoon rainfall and a negative correlation with summer (especially May) temperature suggesting a contrasting response of summer temperature and monsoon rain on teak growth. The correlation between rainfall and ring width varies from southern to northern WG (both in significance level and the number of months with significant correlation). While the southernmost location exhibits positive (significant) correlations for both pre and summer monsoon months, the correlations are found for only two summer monsoonal months in the northernmost location. This spatial correlation trend reflects the variation of the pre-monsoon to monsoon rainfall ratio observed in our study locations. This observation is further substantiated by soil moisture-ring width relationship. Furthermore, our study shows that ring width indices respond to a variation of western equatorial Pacific sea surface temperature and vapor pressure deficit. Our study, therefore, suggests that the Indian teak samples can be used for understanding regional and seasonal scale rainfall/soil moisture variation along the WG and teleconnection studies. [ABSTRACT FROM AUTHOR]

Seasonal prediction of summer precipitation over eastern China is closely linked to the East Asian monsoon circulation, which is largely affected by the El Niño-Southern Oscillation (ENSO). In this study, results show that spring soil moisture (SM) over the Indo-China peninsula (ICP) could be a reliable seasonal predictor for eastern China summer precipitation under non-ENSO conditions. When springtime SM anomalies are present over the ICP, they trigger a structured response in summertime precipitation over most of eastern China. The resultant south-to-north, tri-polar configuration of precipitation anomalies has a tendency to yield increased (decreased) precipitation in the Yangtze River basin and decreased (increased) in South and North China with a drier (wetter) spring soil condition in the ICP. The analyses show that ENSO exerts a powerful control on the East Asian circulation system in the ENSO-decaying summer. In the case of ENSO forcing, the seasonal predictability of the ICP spring SM for eastern China summer precipitation is suppressed. However, in the absence of the influence of ENSO sea surface temperature anomalies from the preceding winter, the SM anomalies over the ICP induce abnormal local heating and a consequent geopotential height response owing to its sustained control on local temperature, which could, in turn, lead to abnormal eastern China summer precipitation by affecting the East Asian summer monsoon circulation. The present findings provide a better understanding of the complexity of summer climate predictability over eastern China, which is of potential significance for improving the livelihood of the people. [ABSTRACT FROM AUTHOR]

Soil moisture is one of the essential climate variables with a potential impact on local climate variability. Despite the importance of soil moisture, studies on soil moisture characteristics in Ethiopia are less documented. In this study, the spatiotemporal variability of Ethiopian soil moisture (SM) has been characterized, and its local and remote influential driving factors are investigated. An empirical orthogonal function (EOF) and KMeans clustering algorithm have been employed to classify the large domain into homogeneous zones. Complex maximum covariance analysis (CMCA) is applied to evaluate the covariability between SM and selected local and remote variables such as rainfall (RF), evapotranspiration (ET), and sea surface temperature (SST). Inter-comparison among SM datasets highlight that the FLDAS dataset better depicts the country's SM spatial and temporal distribution (i.e., a correlation coefficient r = 0.95 , r m s d = 0.04 m 3 m - 3 with observations). Results also indicate that regions located in northeastern Ethiopia are drier irrespective of the season (JJAS, MAM, and OND) considered. In contrast, the western part of the country consistently depicted a wetter condition in all seasons. During summer (JJAS), the soil moisture variability is characterized by a strong east–west spatial contrast. The highest and lowest soil moisture values were observed across the country's central western and eastern parts, respectively. Furthermore, analyses indicate that interannual variability of SM is dictated substantially by RF, though the impact on some regions is weaker. It is also found that ET likely drives the SM in the eastern part of Ethiopia due to a higher atmospheric moisture demand that ultimately invokes changes in surface humidity and rainfall. A composite analysis based on the extreme five wettest and driest SM years revealed a similar spatial distribution of wet SM with positive anomalies of RF across the country and ET over the southern regions. Remote SSTs are also found to have a significant influence on SM distribution. In particular, equatorial central Pacific and western Indian oceans SST anomalies are predominant factors for spatiotemporal SM variations over the country. Major global oceanic indices: Oceanic Nino Index (ONI), Indian Ocean Dipole (IOD), Pacific warm pool (PACWARMPOOL), and Pacific Decadal Oscillations (PDO) are found to be closely associated with the SM anomalies in various parts of the country. The associationship between these remote SST anomalies and local soil moisture is via large-scale atmospheric circulations that are linked to regional factors such as precipitation and temperature anomalies. [ABSTRACT FROM AUTHOR]

Terrestrial ecosystems are fully coupled with the climate. The planet has been greening owing to the increased vegetation growth in response to the changing atmosphere, which in turn has feedback on the climate. Greening has slowed down the rise in global land-surface air temperature mainly through a coincident increase of evapotranspiration and precipitation in wet regions. In dry regions, greening intensifies the decrease in soil moisture induced by greening-enhanced transpiration. Uncertain, however, is how the climate effects of greening in semi-arid lands might differ for variable wet and dry conditions. Here, we focus on the biosphere–atmosphere interactions in Australia by modeling the perturbation of vegetation changes under various states of sea surface temperature (SST), including the climatology mean, El Niño, and La Niña conditions. For the dry conditions of El Niño, greening exacerbates water stress and largely depletes the soil moisture, while for the wet conditions of La Niña, greening-enhanced evapotranspiration and precipitation resupply the soil moisture. For the normal conditions using the climatology mean SST, a small decrease in soil moisture occurs but with large spatial contrast because of heterogeneous changes of evapotranspiration and precipitation induced by greening. We emphasize that the alternating dry and wet conditions modulated by the large-scale climate variability are vital to understanding the response of climate to greening. Furthermore, vegetation-based warming mitigation policies need to be cautious when inferring distinct climate effects associated with greening. [ABSTRACT FROM AUTHOR]

Summer 2010 saw two simultaneous extremes linked by an atmospheric wave train: a record-breaking heatwave in Russia and severe floods in Pakistan. Here, we study this wave event using a large ensemble climate model experiment. First, we show that the circulation in 2010 reflected a recurrent wave train connecting the heatwave and flooding events. Second, we show that the occurrence of the wave train is favored by three drivers: (1) 2010 sea surface temperature anomalies increase the probability of this wave train by a factor 2-to-4 relative to the model's climatology, (2) early-summer soil moisture deficit in Russia not only increases the probability of local heatwaves, but also enhances rainfall extremes over Pakistan by forcing an atmospheric wave response, and (3) high-latitude land warming favors wave-train occurrence and therefore rainfall and heat extremes. These findings highlight the complexity and synergistic interactions between different drivers, reconciling some seemingly contradictory results from previous studies. [ABSTRACT FROM AUTHOR]

The single variable-dependent drought cannot adequately define the onset and withdrawal characteristics of the droughts. A Multivariate Standardised Drought Index (MSDI) is developed in the present study, based on precipitation and soil moisture using bivariate copula function. Reconnaissance Trivariate Drought Index (RTDI) is also developed combining precipitation, soil moisture and evapotranspiration. MSDI and RTDI represent meteorological and agricultural droughts by linking the climate status in an effective way. The best fitted copulas obtained for bivariate and trivariate analyses are Frank and Student's t copulas respectively. The two drought indices are developed and tested to study the onset and withdrawal characteristics of drought and their trends. Cross-wavelet analysis (CWA) is performed to identify the substantial effect of large-scale climate anomalies on the derived drought indices. The large-scale climate factors like sea surface temperature (SST), Multivariate ENSO Index (MEI), Southern Oscillation Index (SOI), Indian Ocean Dipole (IOD) and Indian summer monsoon rainfall (ISMR) are considered in this study. ENSO, IOD and ISMR showed significant influences on the drought variability. The 3-month MSDI is significantly influenced by ISMR while SST showed a significant teleconnection with RTDI-3. The SST showed a strong influence on both 6-month MSDI and 6-month RTDI. This study is robust and reliable for future drought assessment and will provide a great platform to develop warning criteria on onset and termination of droughts. [ABSTRACT FROM AUTHOR]

Projected changes in near-surface relative humidity (RH) remain highly model-dependent over land and may have been underestimated by the former generation global climate models. Here the focus in on the recent CNRM-CM6-1 model, which shows an enhanced land surface drying in response to quadrupled atmospheric CO2 compared to its CNRM-CM5 predecessor. Atmosphere-only experiments with prescribed sea surface temperature (SST) are used to decompose the simulated RH changes into separate responses to uniform SST warming, pattern of SST anomalies, changes in sea-ice concentration, as well as direct radiative and physiological CO2 effects. Results show that the strong drying simulated by CNRM-CM6-1 is due to both fast CO2 effects and a SST-mediated response. The enhanced drying compared to CNRM-CM5 is partly due to the introduction of the physiological CO2 effect that was not accounted for in CNRM-CM5. The global ocean warming also contributes to the RH decline over land, in reasonable agreement with the moisture advection mechanism proposed by earlier studies which however does not fully capture the contrasted RH response between the two CNRM models. The SST anomaly pattern is a significant driver of changes in RH humidity at the regional scale, which are partly explained by changes in atmospheric circulation. The improved land surface model may also contribute to a stronger soil moisture feedback in CNRM-CM6-1, which can amplify the surface aridity induced by global warming and, thereby, lead to a non-linear response of RH. [ABSTRACT FROM AUTHOR]

Soil moisture is a key variable of the land surface and its variations are an important issue in climate studies. In this study, we employed the Community Earth System Model (CESM) for 20 ensemble member simulations of the 50-year period from 1965 to 2014 and used canonical correlation analysis (CCA) and multiple regression to analyze the spatiotemporal characteristics of soil moisture predictability. The effects of soil moisture persistence and sea surface temperature (SST) as an external forcing on its predictability were analyzed. Results show that the soil moisture predictability due to its persistence is 1–2 months and considering SST as an external forcing can significantly increase its predictability. Regions that exhibit a significant increase in predictability are mainly tropical regions, North America and Western Asia during winter and spring. In tropical regions, SST increases the predictability of soil moisture by influencing the local surface temperature and precipitation. In other regions, the effects of SST on wind speed, cloud cover, and surface evaporation also contribute significantly to the increase in soil moisture predictability. The results were validated through the analysis based on soil moisture data from land data assimilation system and observed precipitation. [ABSTRACT FROM AUTHOR]

The effects of spring soil moisture over the vast region from the lower and middle reaches of the Yangtze River valley to North China (YRNC) and El Niño on the East Asian summer monsoon (EASM) and precipitation in eastern China, as well as the relevant mechanisms, are investigated using the modified atmospheric model ECHAM5 coupled with the Common Land Model. These models are the atmospheric and land components of the climate system model developed at the Chinese Academy of Meteorological Sciences (CAMS-CSM). The simulations show that both soil moisture anomalies in eastern China and El Niño sea surface temperature (SST) anomalies have significant influences on the EASM, with the effect of soil moisture being slightly greater than that of the El Niño. However, the impacts of soil moisture on EASM and rainfall in eastern China are markedly different from those of the El Niño. Wetter (drier) soil over the YRNC corresponds to less (more) precipitation over northern and southeastern China, and more (less) precipitation over the Yangtze River basin and northeastern China, as well as a strengthened (weakened) and westward-shifted (eastward-shifted) West Pacific Subtropical High and a deepened (shallower) East Asian trough, representing a weakened (strengthened) EASM pattern. During El Niño developing summers, an anomalous anticyclone extends from northeastern to northern China, and an anomalous cyclone occupies the middle and lower reaches of the Yangtze River and southern China. Concurrently, the West Pacific Subtropical High is anomalously weaker than normal. As a result, rainfall anomalously increases over the lower reaches of the Yangtze River and southern China, and decreases over northern and northeastern China. In El Niño decaying summers, there is an anomalous cyclone over northeastern China and an anomalous anticyclone over southern China. The convergence of southerly airflow and northerly winds leads to enhanced rainfall around northern China and the middle reaches of the Yangtze River, and reduced rainfall over other regions. [ABSTRACT FROM AUTHOR]

The ERA-Interim (1979–2016) and National Center for Environmental Prediction (NCEP) (1958–2016) reanalysis data are applied in an empirical orthogonal function (EOF) decomposition of the summer zonal wind anomaly in the upper troposphere (at 200 hPa) over Asia. Consistent spatio-temporal modes are derived from the two datasets on different time scales, with the first three dominant modes representing the principal features of the summer Asian subtropical westerly jet (ASWJ). The first and third modes respectively describe the meridional position deviation and the overall strength variations of ASWJ, and both exhibit zonally symmetric distributions, which have been extensively investigated. The second mode describes a zonally asymmetric distribution of the jet over Asia, which reflects coordinated variations in the upstream and downstream systems and has not yet been systematically studied. In this study, we focus on the analysis of the second mode of ASWJ. The observation results show that the second mode is closely related to external forcing factors as well as the large-scale circulation at mid-high latitudes. Through the interaction of the preceding North Atlantic sea surface temperature (SST), the simultaneous soil moisture, and the atmospheric circulation that propagates zonally via the waveguide effect of the jet, the ocean–land–atmosphere coupled system can produce coordinating impacts on the variability of ASWJ. These results aid in a more complete and comprehensive understanding of the physical characteristics of the summer westerly jet and provide a new perspective for the study of the variability of ASWJ. [ABSTRACT FROM AUTHOR]

Ensembles of numerical forecasts based on perturbed initial conditions have long been used to improve estimates of both weather and climate forecasts. The Goddard Earth Observing System (GEOS) Atmosphere–Ocean General Circulation Model, Version 5 (GEOS-5 AOGCM) Seasonal-to-Interannual Forecast System has been used routinely by the GMAO since 2008, the current version since 2012. A coupled reanalysis starting in 1980 provides the initial conditions for the 9-month experimental forecasts. Once a month, sea surface temperature from a suite of 11 ensemble forecasts is contributed to the North American Multi-Model Ensemble (NMME) consensus project, which compares and distributes seasonal forecasts of ENSO events. Since June 2013, GEOS-5 forecasts of the Arctic sea-ice distribution were provided to the Sea-Ice Outlook project. The seasonal forecast output data includes surface fields, atmospheric and ocean fields, as well as sea ice thickness and area, and soil moisture variables. The current paper aims to document the characteristics of the GEOS-5 seasonal forecast system and to highlight forecast biases and skills of selected variables (sea surface temperature, air temperature at 2 m, precipitation and sea ice extent) to be used as a benchmark for the future GMAO seasonal forecast systems and to facilitate comparison with other global seasonal forecast systems. [ABSTRACT FROM AUTHOR]

Ensuring stable crop yield increases to meet rising demand is an important issue globally, particularly when accounting for climate change. In this study, using observations, reanalysis datasets, and the Hodrick and Prescott filter method, we find that changes in a distinct pattern of Indian Ocean–Pacific five-pole (IPFP) SST (sea surface temperature) are strongly linked to the ensuing year's winter wheat climatic yield (the part of yield that fluctuation caused by climatic factors change) in the North China Plain (NCP), which is the main production region of winter wheat in China. Here we define a normalized IPFP index (IPFPI) and demonstrate that the autumn IPFPI (1948–2014) is well correlated with the ensuing year's winter wheat climatic yield (1949–2015), particularly for October (r = 0.69; n = 67; P < 0.001). A composite analysis shows that the October IPFP is correlated with sowing-period and emergence-period climate factors in the NCP. When the October IPFP is in a positive phase, the atmosphere geopotential height fields and water vapor flux are bebefitial to rainfall formation in NCP, and the precipitation and soil moisture are higher in NCP and benefit winter wheat growth, thus increasing the climatic yield. In addition, accumulated rainfall and soil water content might influence winter wheat growth from sowing and emergence (autumn) to the returning green stage (following spring). [ABSTRACT FROM AUTHOR]

Extreme weather events such as heat waves and floods are damaging to society and their contribution to future climate impacts is expected to be large. Such extremes are often related to persistent local weather conditions. Weather persistence is linked to sea surface temperatures, soil-moisture (especially in summer) and large-scale circulation patterns and these factors can alter under past and future climate change. Though persistence is a key characteristic for extreme weather events, to date the climatology and potential changes in persistence have only been poorly documented. Here, we present a systematic analysis of temperature persistence for the northern hemisphere land area. We define persistence as the length of consecutive warm or cold days and use spatial clustering techniques to create regional persistence distributions. We find that persistence is longest in the Arctic and shortest in the mid-latitudes. Parameterizations of the regional persistence distributions show that they are characterized by an exponential decay with a drop in the decay rate for very persistent events, implying that feedback mechanisms are important in prolonging these events. For the mid-latitudes, we find that persistence in summer has increased over the past 60 years. The changes are particularly pronounced for prolonged events suggesting a lengthening in the duration of heat waves. [ABSTRACT FROM AUTHOR]

Soil Moisture and Ocean Salinity (SMOS) Level 3 (L3) sea surface salinity (SSS) products are provided by the Barcelona Expert Centre (BEC). Strong biases were observed on the SMOS SSS products, thus the data from the Centre Aval de Traitement des Données SMOS (CATDS) were adjusted for biases using a large-scale correction derived from observed differences between the SMOS SSS and World Ocean Atlas (WOA) climatology data. However, this large-scale correction method is not suitable for correcting the large gradient of salinity biases. Here, we present a method for the correction of SSS regional bias of the monthly L3 products. Based on the stable characteristics of the large SSS biases from month to month in some regions, corrected SMOS SSS maps can be obtained from the monthly mean values after removing the regional biases. The accuracy of the SMOS SSS measurements is greatly improved, especially near the coastline, at high latitudes, and in some open ocean regions. The SMOS and ISAS SSS data are also compared with Aquarius SSS to verify the corrected SMOS SSS data. The correction method presented here only corrects annual mean biases. The measurement accuracy of the SSS may be improved by considering the influence of atmospheric and ocean circulation in different seasons and years. [ABSTRACT FROM AUTHOR]

We analyze the local and remote impacts of climate change on the hydroclimate of the Amazon and La Plata basins of South America (SA) in an ensemble of four 21st century projections (1970-2100, RCP8.5 scenario) with the regional climate model RegCM4 driven by the HadGEM, GFDL and MPI global climate models (GCMs) over the SA CORDEX domain. Two RegCM4 configurations are used, one employing the CLM land surface and the Emanuel convective schemes, and one using the BATS land surface and Grell (over land) convection schemes. First, we find considerable sensitivity of the precipitation change signal to both the driving GCM and the RegCM4 physics schemes (with the latter even greater than the first), highlighting the pronounced uncertainty of regional projections over the region. However, some improvements in the simulation of the annual cycle of precipitation over the Amazon and La Plata basins is found when using RegCM4, and some consistent change signals across the experiments are found. One is a tendency towards an extension of the dry season over central SA deriving from a late onset and an early retreat of the SA monsoon. The second is a dipolar response consisting of reduced precipitation over the broad Amazon and Central Brazil region and increased precipitation over the La Plata basin and central Argentina. An analysis of the relative influence on the change signal of local soil-moisture feedbacks and remote effects of Sea Surface Temperature (SST) over the Niño 3.4 region indicates that the former is prevalent over the Amazon basin while the latter dominates over the La Plata Basin. Also, the soil moisture feedback has a larger role in RegCM4 than in the GCMs. [ABSTRACT FROM AUTHOR]

This study uses experiments with an atmospheric general circulation model (AGCM) to address the role of the oceans and the effect of land-atmosphere coupling on the predictability of summertime rainfall over northern Argentina focusing on interdecadal time scales during 1901-2006. Ensembles of experiments where the AGCM is forced with historical sea surface temperature (SST) in the global, Pacific and tropical-North Atlantic domains are used. The role of land-atmosphere interaction is assessed comparing the output of simulations with active and climatological soil moisture. A maximum covariance analysis between precipitation and SST reveals the impact of the Pacific Decadal Oscillation, the Atlantic Multidecadal Oscillation and the equatorial-tropical South Atlantic on rainfall over northern Argentina. Model simulations further show that while the dominant influence comes from the Pacific basin, the Atlantic influence can explain a large transition from dry to wet decades over northern Argentina during the beginning of the 1970s. Analysis of anomalies before and after the transition reveals an upper level anticyclonic circulation off the Patagonian coast with barotropic structure. This circulation enhances the moisture transport and convergence in northern Argentina and, together with enhanced evaporation, increased the rainfall after 1970. The SST pattern is dominated by cold conditions in the equatorial Atlantic and warm eastern Pacific and South Atlantic. We also found that land-atmosphere interaction leads to a representation of the long term rainfall evolution over northern Argentina that is closer to the observed one. Moreover, it leads to a smaller dispersion among ensemble members, thus resulting in a larger signal-to-noise ratio. [ABSTRACT FROM AUTHOR]

Based on numerical experiments using the NCAR CAM3-CLM3 models, this paper examines the impact of soil moisture, vegetation, and sea surface temperature (SST) on the inter-annual variability of climate over land. For each element, two experiments are carried out, with the inter-annual variability preserved in one experiment and eliminated in the other. Differences in the standard deviation of the precipitation and air temperature at the inter-annual time scale are used to quantify the impacts from soil moisture dynamics, vegetation dynamics, and oceanic forcing. The impact of oceanic forcing is mainly limited to the Tropics, with the strongest signal in the equatorial zone, and moisture convergence is the key linkage between SST forcing and tropical precipitation. Soil moisture plays a significant role in climate variability during the rainy seasons of all semi-arid regions (which is consistent with many previous studies), and during the dry seasons of the humid Amazon. Evapotranspiration is identified as the main mechanism linking precipitation variability to soil moisture. Amazon is the only region where vegetation dynamics has a significant influence on precipitation variability. However, the impact of vegetation dynamics on temperature is strong over the US Great Plains in all four seasons and in the Amazon region during the dry and dry-to-wet transition seasons. [ABSTRACT FROM AUTHOR]

Droughts and floods are the two most costly climate disasters over China. However, our ability to predict droughts and floods is limited by poor understanding of the atmospheric response to long memory climate drivers such as sea surface temperature and soil moisture. In this study, we investigate soil moisture feedbacks on summer droughts and floods over eastern China for the 1998 and 1999 cases using the Weather Research and Forecasting (WRF) model simulations. Soil moisture climatology, derived from a 20-year-long control run, is used to replace soil moisture evolution in uncoupled simulations for 1998 and 1999 summers. Eastern China experienced severe floods during the summer of 1998, while 1999 summer is characterized by a “southern flood and northern drought” pattern. The WRF model generally simulates relatively well the droughts and floods in the two summers. It is found that land-atmosphere coupling contributes substantially to both droughts and floods over northern China while it plays a relatively small role in precipitation anomalies over southern China. Our findings suggest that soil moisture memory help contribute skill to seasonal prediction of droughts and floods over northern China. [ABSTRACT FROM AUTHOR]