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Groundwater and climate interact in a two-way manner. Precipitation ultimately controls groundwater recharge and, conversely, groundwater may influence climate through evapotranspiration. Yet very few global climate models or Earth system models actually simulate groundwater flows. And while the expected impacts of climate change on groundwater resources are the subject of a growing concern, global-scale groundwater–climate feedbacks have received very little attention so far. Here we show that the integration of unconfined aquifers in a global climate model can regionally affect the climate change signal on temperatures and precipitation. We assess the impact of groundwater under preindustrial and 4xCO2 conditions (after climate stabilization). In both cases, we find that groundwater has a cooling and a wetting effect in certain regions of the world. In eastern Europe, both these impacts are stronger in the warmer climate (4xCO2 forcing) where the presence of groundwater reduces the frequency of summer heatwaves by 40%, compared to a 15% reduction in the preindustrial world. This work constitutes one of the very first global assessments of the potential feedbacks of groundwater on climate change. Our results support the idea that groundwater should be represented in global climate models and Earth system models, as it does indeed play an active role in the climate system. [ABSTRACT FROM AUTHOR]

The Tibetan Plateau (TP) exerts strong powerful thermal forcing, which plays a vital role in influencing weather–climate variations in Asia and even the Northern Hemisphere. However, the causes of thermal variation over the TP have not been fully revealed. Here, the role of winter soil moisture (SM) in subsequent summer thermal anomalies on the TP was investigated through multisource datasets for the period 1979–2014. Results indicate a significant positive relationship (r = 0.52) between winter SM and subsequent summer-mean surface air temperature (SAT). Further investigations show that more (less) winter SM results in abundant (deficient) atmospheric water vapor in subsequent summer owing to its persistence. Furthermore, Earth’s surface energy budget equation confirms that strengthened (weakened) surface downward longwave radiation caused by increased (decreased) water vapor is the dominant factor leading to SAT variations, even more significant for nocturnal SAT. The winter SM–atmospheric temperature positive relationship can extend from the surface to 200 hPa over the TP. In addition, the enhanced (weakened) atmospheric latent heat release associated with increased (decreased) water vapor content may be another important factor contributing to changes in atmospheric temperatures over the TP. Therefore, our results contribute to a better understanding of the effect of land–surface processes on thermal anomalies over the TP. Significance Statement Understanding the causes of thermal anomalies over the Tibetan Plateau (TP) is crucial for weather and climate variations, but the role of winter soil moisture (SM) in subsequent summer thermal effects is largely unknown. This study investigated the relationship between winter SM and thermal anomalies in subsequent summers on the TP. Results show that the above (below)-normal winter SM will cause warm (cold) atmospheric temperatures in the subsequent summer. The above (below)-normal winter SM anomalies bring increased (decreased) atmospheric water vapor in summer owing to its persistence, resulting in strengthened (weakened) downward longwave radiation and atmospheric latent heat release to heat (cool) the atmosphere. [ABSTRACT FROM AUTHOR]

Standardized precipitation index (SPI) is one of the frequently used meteorological drought indices. However, the time-varying characteristics observed in the historical precipitation data questions the reliability of SPI and motivated the development of nonstationary SPI. To overcome some of the limitations in the existing nonstationary drought indices, a new framework for drought index is proposed, incorporating the temporal dynamics in the precipitation. The proposed drought index is developed by coupling the joint deficit index with the extended time sliding window–based nonstationary modeling (TSW-NSM). The proposed nonstationary joint deficit index (NJDI) detects the signature of nonstationarity in the distribution parameter and models both long-term (i.e., trend) and short-term (i.e., step-change) temporal dynamics of distribution parameters. The efficacy of NJDI is demonstrated by employing it to identify the meteorological drought-prone areas over India. The changes observed in the distribution parameter of rainfall series reveal an increasing number of dry days in recent decades all over India, except the northeast. Comparison of NJDI and stationary joint deficit index (JDI) reveals that JDI overestimates drought when frequent severe dry events are clustered and underestimates when these events are scattered, which indicates that the traditional index is biased toward the lowest magnitude of precipitation while classifying the drought. Moreover, NJDI could closely capture historical droughts and their spatial variations, thereby reflecting the temporal dynamics of rainfall series and the changes in the pattern of dry events over India. NJDI proves to be a potentially reliable index for drought monitoring in a nonstationary climate. Significance Statement: Drought is one of the most severe natural disasters and is expected to intensify under a warming climate. There has been progress on developing newer methodologies to characterize drought severity under the changing climate. However, some limitations remain in capturing the temporal changes of the precipitation, especially the nonstationarity in variance (rapid increases in extreme precipitation versus the average precipitation). We propose an extension to the time sliding window approach to capture the nonstationarity in variance and mean while incorporating short-term (step-change) and long-term (trend) temporal dynamics. We apply the methodology to a subcontinent-sized heterogeneous country of India with gridded rainfall dataset (0.25° × 0.25°, 1901–2013) from the India Meteorological Department. We find that the majority of grids exhibit negative and positive trends in shape and scale parameters, respectively, which ultimately leads to an increase in the number of drier events, whereas a contradictory pattern is exhibited in the northwest Indian region (decrease in the number of dry days). The proposed index gives a potential framework for drought monitoring under the changing climate and can be extended to develop a multivariate nonstationary joint deficit index by incorporating other hydrological variables (e.g., soil moisture, diurnal temperature range, streamflow). [ABSTRACT FROM AUTHOR]

Drought is a major natural hazard with far-reaching social, economic, and environmental impacts whose characteristics are highly interdependent across different spatial and temporal scales. Traditional global warming impact assessments on drought at the global scale have, however, taken into account only one drought characteristic at a time, likely leading to an underestimation of the overall impact. Here, we perform a trivariate analysis of changes in drought conditions at 1.5°, 2°, and 3°C global warming levels using 25 CMIP6 GCMs. Drought properties are characterized by the Standardized Soil Moisture Index (SSI). The future joint return periods of droughts historically associated with 10-, 20-, and 30-yr return periods are computed under the warming levels using copula functions considering drought duration, peak, and severity. Our comparative assessments of global warming impact on drought properties between univariate and trivariate analyses corroborate the substantial underestimation of the impact by the univariate analysis. The trivariate analysis shows that around 63%–91% of the global land will be subject to more recurrent droughts, while the percentage of the land reduces to 41%–56% for the univariate analysis. The difference between the univariate and trivariate analyses enlarges with global warming levels and the extremity of drought events. Based on the trivariate analysis, a 30-yr drought would become at least threefold more recurrent in 11%, 15%, and 20% of the global land at 1.5°, 2°, and 3°C warming levels, respectively, but the univariate analysis could not reach such large increases in drought conditions. [ABSTRACT FROM AUTHOR]

Extreme weather events are triggered by atmospheric circulation patterns and shaped by slower components, including soil moisture and sea surface temperature, and by the background climate. This separation of factors is exploited by the storyline approach in which an atmospheric model is nudged toward the observed dynamics using different climate boundary conditions to explore their influence. The storyline approach disregards uncertain climatic changes in the frequency and intensity of dynamical conditions, focusing instead on the thermodynamic influence of climate on extreme events. Here we demonstrate an advanced storyline approach that employs a coupled climate model (AWI-CM-1-1-MR) in which the large-scale free-troposphere dynamics are nudged toward ERA5 data. Five-member ensembles are run for present-day (2017–19), preindustrial, +2-K, and +4-K climates branching off from CMIP6 historical and scenario simulations of the same model. In contrast to previous studies, which employed atmosphere-only models, feedbacks between extreme events and the ocean and sea ice state, and the dependence of such feedbacks on the climate, are consistently simulated. Our setup is capable of reproducing observed anomalies of relevant unconstrained parameters, including near-surface temperature, cloud cover, soil moisture, sea surface temperature, and sea ice concentration. Focusing on the July 2019 European heat wave, we find that the strongest warming amplification expands from southern to central Europe over the course of the twenty-first century. The warming reaches up to 10 K in the 4-K-warmer climate, suggesting that an analogous event would entail peak temperatures around 50°C in central Europe. Significance Statement: This work explores a new storyline method to determine the impact of climate change on specific recent extreme events. The observed evolution of the large-scale atmospheric circulation is imposed in a coupled climate model. Variations in climate parameters, including ocean temperatures and sea ice, are well reproduced. By varying the background climate, including CO2 concentrations, it is demonstrated how the July 2019 European heat wave could have evolved in preindustrial times and in warmer climates. For example, up to 10°C warmer peak temperatures could occur in central Europe in a 4°C warmer climate. The method should be explored for other types of extreme events and has the potential to make climate change more tangible and to inform adaptation measures. [ABSTRACT FROM AUTHOR]

Drought is projected to become more severe and widespread as global warming continues in the twenty-first century, but hydroclimatic changes and their drivers are not well examined in the latest projections from phase 6 of the Coupled Model Intercomparison Project (CMIP6). Here, precipitation (P), evapotranspiration (E), soil moisture (SM), and runoff (R) from 25 CMIP6 models, together with self-calibrated Palmer drought severity index with Penman–Monteith potential evapotranspiration (scPDSIpm), are analyzed to quantify hydroclimatic and drought changes in the twenty-first century and the underlying causes. Results confirm consistent drying in these hydroclimatic metrics across most of the Americas (including the Amazon), Europe and the Mediterranean region, southern Africa, and Australia, although the drying magnitude differs, with the drying being more severe and widespread in surface SM than in total SM. Global drought frequency based on surface SM and scPDSIpm increases by ∼25%–100% (50%–200%) under the SSP2-4.5 (SSP5-8.5) scenario in the twenty-first century together with large increases in drought duration and areas, which result from a decrease in the mean and flattening of the probability distribution functions of SM and scPDSIpm, while the R-based drought changes are relatively small. Changes in both P and E contribute to the SM change, whereas scPDSIpm decreases result from ubiquitous PET increases and P decreases over subtropical areas. The R changes are determined primarily by P changes, while the PET change explains most of the E increase. Intermodel spreads in surface SM and R changes are large, leading to large uncertainties in the drought projections. SIGNIFICANCE STATEMENT: Drought may become more severe and widespread under greenhouse gas (GHG)-induced global warming in the twenty-first century based on model projections. However, there are still large uncertainties in projected future drought changes, especially regarding the extent to which drought changes depend on drought indices and the future emissions scenarios analyzed. The latest projections from CMIP6 models reaffirm the widespread drying and increases in agricultural drought by up to 200% over most of the Americas (including the Amazon), Europe and the Mediterranean region, southern Africa, Southeast Asia, and Australia under moderate-to-high emissions scenarios in the twenty-first century, despite large uncertainties in individual projections partly due to internal variability. Ubiquitous increases in atmospheric demand for moisture under rising temperatures and precipitation decreases over many subtropical regions are the main driver of the projected drying and drought increases. [ABSTRACT FROM AUTHOR]

Future projections of precipitation change over tropical land are often enhanced by vegetation responses to CO2 forcing in Earth system models. Projected decreases in rainfall over the Amazon basin and increases over the Maritime Continent are both stronger when plant physiological changes are modeled than if these changes are neglected, but the reasons for this amplification remain unclear. The responses of vegetation to increasing CO2 levels are complex and uncertain, including possible decreases in stomatal conductance and increases in leaf area index due to CO2 fertilization. Our results from an idealized atmospheric general circulation model show that the amplification of rainfall changes occurs even when we use a simplified vegetation parameterization based solely on CO2-driven decreases in stomatal conductance, indicating that this mechanism plays a key role in complex model projections. Based on simulations with rectangular continents we find that reducing terrestrial evaporation to zero with increasing CO2 notably leads to enhanced rainfall over a narrow island. Strong heating and ascent over the island trigger moisture advection from the surrounding ocean. In contrast, over larger continents rainfall depends on continental evaporation. Simulations with two rectangular continents representing South America and Africa reveal that the stronger decrease in rainfall over the Amazon basin seen in Earth system models is due to a combination of local and remote effects, which are fundamentally connected to South America's size and its location with respect to Africa. The response of tropical rainfall to changes in evapotranspiration is thus connected to size and configuration of the continents. [ABSTRACT FROM AUTHOR]

Variability in soil moisture has implications for regional terrestrial environments under a warming climate. This paper focuses on the spatiotemporal variability in the intra-annual persistence of soil moisture in China using the fifthgeneration reanalysis dataset by the European Centre for Medium-Range Weather Forecasts for the period 1979-2018. The results show that in China, the mean intra-annual persistence in the humid to arid zones increased from 60 to 115 days in the lower layer but decreased from 19 to 13 days and from 25 to 14 days in the upper and root layers, respectively. However, these changes were strongly attenuated in extremely dry and wet regions due to the scarcity of soil moisture anomalies. Large changes in persistence occurred in the lower soil layer in dryland areas, with a mean difference of up to 40 days between the 2010s and the 1980s. Overall increasing trends dominated the large-scale spatial features, despite regional decreases in the eastern arid zone and the North and Northeast China plains. In the root layer, the two plains experienced an expanded decrease while on the Tibetan Plateau it was dominated by decadal variability. These contrasting changes between the lower and root layers along the periphery of the transition zone was a reflection of the enhanced soil hydrological cycle in the root layer. The enhanced persistence in drylands lower layer is an indication of the intensified impacts of soil moisture anomalies (e.g., droughts) on terrestrial water cycle. These findings may help the understanding of climate change impacts on terrestrial environments. [ABSTRACT FROM AUTHOR]

This study investigates the trend in destructive potential of landfalling tropical cyclones (TCs) in terms of power dissipation index (PDI) over mainland China in the period of 1980–2018. Results show that both the accumulated PDI and averaged PDI after landfall show significant increasing trends. The increasing trends are found to be contributed primarily by the increasing mean duration of TCs over land and the increasing TC intensity at landfall. Further analyses indicate that the increase in landfalling TC intensity prior to and at landfall, the decrease in intensity weakening rate after landfall, and the northward shift of landfalling TC track density all contribute to the longer duration of TCs after landfall. Moreover, the conducive large-scale conditions, such as the increases in coastal sea surface temperature and land surface temperature and soil moisture, the decrease in low-level vertical wind shear, and the increase in upper-level divergence, are all favorable for intense landfalling TCs and their survival after landfall, thus contributing to the increasing destructive potential of landfalling TCs over China. [ABSTRACT FROM AUTHOR]

Understanding vulnerabilities of continental precipitation to changing climatic conditions is of critical importance to society at large. Terrestrial precipitation is fed by moisture originating as evaporation from oceans and from recycling of water evaporated from continental sources. In this study, continental precipitation and evaporation recycling processes in the Earth system model GFDL-ESM2G are shown to be consistent with estimates from two different reanalysis products. The GFDL-ESM2G simulations of historical and future climate also show that values of continental moisture recycling ratios were systematically higher in the past and will be lower in the future. Global mean recycling ratios decrease 2%–3% with each degree of temperature increase, indicating the increased importance of oceanic evaporation for continental precipitation. Theoretical arguments for recycling changes stem from increasing atmospheric temperatures and evaporative demand that drive increases in evaporation over oceans that are more rapid than those over land as a result of terrestrial soil moisture limitations. Simulated recycling changes are demonstrated to be consistent with these theoretical arguments. A simple prototype describing this theory effectively captures the zonal mean behavior of GFDL-ESM2G. Implications of such behavior are particularly serious in rain-fed agricultural regions where crop yields will become increasingly soil moisture limited. [ABSTRACT FROM AUTHOR]

In the mid-twentieth century (1948–57), North America experienced a severe drought forced by cold tropical Pacific sea surface temperatures (SSTs). If these SSTs recurred, it would likely cause another drought, but in a world substantially warmer than the one in which the original event took place. We use a 20-member ensemble of the GISS climate model to investigate the drought impacts of a repetition of the mid-twentieth-century SST anomalies in a significantly warmer world. Using observed SSTs and mid-twentieth-century forcings (Hist-DRGHT), the ensemble reproduces the observed precipitation deficits during the cold season (October–March) across the Southwest, southern plains, and Mexico and during the warm season (April–September) in the southern plains and the Southeast. Under analogous SST forcing and enhanced warming (Fut-DRGHT, ≈3 K above preindustrial), cold season precipitation deficits are ameliorated in the Southwest and southern plains and intensified in the Southeast, whereas during the warm season precipitation deficits are enhanced across North America. This occurs primarily from greenhouse gas–forced trends in mean precipitation, rather than changes in SST teleconnections. Cold season runoff deficits in Fut-DRGHT are significantly amplified over the Southeast, but otherwise similar to Hist-DRGHT over the Southwest and southern plains. In the warm season, however, runoff and soil moisture deficits during Fut-DRGHT are significantly amplified across the southern United States, a consequence of enhanced precipitation deficits and increased evaporative losses due to warming. Our study highlights how internal variability and greenhouse gas–forced trends in hydroclimate are likely to interact over North America, including how changes in both precipitation and evaporative demand will affect future drought. [ABSTRACT FROM AUTHOR]

An integrated picture of the future changes in the water cycle is provided focusing on the global land monsoon (GLM) region, based on multimodel projections under the representative concentration pathway 8.5 (RCP8.5) from phase 5 of the Coupled Model Intercomparison Project (CMIP5). We investigate the reservoirs (e.g., precipitable water, soil moisture) and water fluxes (e.g., precipitation P, evaporation E, precipitation minus evaporation P − E, and total runoff) of the water cycle. The projected intensification of the water cycle with global warming in the GLM region is reflected in robust increases in annual-mean P (multimodel median response of 0.81% K−1), E (0.57% K−1), P − E (1.58% K−1), and total runoff (2.08% K−1). Both surface (−0.83% K−1) and total soil moisture (−0.26% K−1) decrease as a result of increasing evaporative demand. Regionally, the Northern Hemispheric (NH) African, South Asian, and East Asian monsoon regions would experience an intensified water cycle, as measured by the coherent increases in P, P − E, and runoff, while the NH American monsoon region would experience a weakened water cycle. Changes in the monthly fields are more remarkable and robust than in the annual mean. An enhanced annual cycle (by ~3%–5% K−1) with a phase delay from the current climate in P, P − E, and runoff is projected, featuring an intensified water cycle in the wet season while little changes or slight weakening in the dry season. The increased seasonality and drier soils throughout the year imply increasing flood and drought risks and agricultural yields reduction. Limiting global warming to 1.5°C, the low warming target set by the Paris Agreement, could robustly reduce additional hydrological risks from increased seasonality as compared to higher warming thresholds. [ABSTRACT FROM AUTHOR]

Because of the interactive margin between the East Asian summer monsoon and westerly circulation, summer rainfall in northern China (NC) exhibits high variability. By employing reanalysis data and geostationary satellite data from the Fengyun-2G (FY-2G) satellite and using the linear baroclinic model (LBM) and Hybrid Single-Particle Lagrangian Integrated Trajectory model, this study suggests a tripole pattern in summer rainfall over NC and the Indian subcontinent (IS) that is related to the Indian summer monsoon. The distributions of atmospheric circulation indicate three teleconnections: one is from the IS via the Indo-China Peninsula (ICP) and NC, enhancing the Pacific–Japan (PJ) pattern; another is from the IS via west-central Asia and NC, arousing a Eurasian wave pattern; and the third is an IS–TP–NC pattern via the Tibetan Plateau (TP). Those teleconnections modulate vorticity and atmospheric stability over NC. In addition, along with the circulation distribution related to those teleconnections, two pathways of moisture transport related to the IS rainfall are suggested, except for moisture transport via the Bay of Bengal: one is from the Indo-Pacific to NC due to enhancing cyclones over the Indo-Pacific and a PJ-like pattern; and another is from the IS to NC via the TP within the midtroposphere, which modulates midtroposphere moisture fluxes and atmospheric stability over NC. Both teleconnections and moisture transport result in anomalous rainfall over NC. This study reveals a new mechanism and pathway of the Indian summer monsoon impacting NC rainfall, possibly explaining the reason behind the high variability in NC rainfall. [ABSTRACT FROM AUTHOR]

Soil moisture anomalies within the root zone (roughly, soil depths down to ~0.4 m) typically persist only a few months. Consequently, land surface–related climate predictability research has often focused on subseasonal to seasonal time scales. However, in this study of multidecadal in situ datasets and land data assimilation products, we find that root zone soil moisture anomalies can recur several or more seasons after they were initiated, indicating potential interannual predictability. Lead–lag correlations show that this recurrence often happens during one fixed season and also seems related to the greater memory of soil moisture anomalies within the layer beneath the root zone, with memory on the order of several months to over a year. That is, in some seasons, notably spring and summer when the vertical soil water potential gradient reverses sign throughout much of North America, deeper soil moisture anomalies appear to return to the surface, thereby restoring an earlier root zone anomaly that had decayed. We call this process "reemergence," in analogy with a similar seasonally varying process (with different underlying physics) providing winter-to-winter memory to the extratropical ocean surface layer. Pronounced spatial and seasonal dependence of soil moisture reemergence is found that is frequently, but not always, robust across datasets. Also, some of its aspects appear sensitive to spatial and temporal sampling, especially within the shorter available in situ datasets, and to precipitation variability. Like its namesake, soil moisture reemergence may enhance interannual-to-decadal variability, notably of droughts. Its detailed physics and role within the climate system, however, remain to be understood. [ABSTRACT FROM AUTHOR]

Soilmoisture-atmosphere coupling is a key process underlying climate variability and change over land. The control of soil moisture (SM) on evapotranspiration (ET) is a necessary condition for soil moisture to feed back onto surface climate. Here we investigate how this control manifests itself across simulations from the CMIP5 ensemble, using correlation analysis focusing on the interannual (summertime) time scale. Analysis of CMIP5 historical simulations indicates significantmodel diversity in SM-ET coupling in terms of patterns and magnitude. We investigate the relationship of this spread with differences in background simulated climate. Mean precipitation is found to be an important driver of model spread in SM-ET coupling but does not explain all of the differences, presumably because ofmodel differences in the treatment of land hydrology. Compared to observations, some land regions appear consistently biased dry and thus likely overly soil moisture-limited. Because of ET feedbacks on air temperature, differences in SM-ET coupling induce model uncertainties across the CMIP5 ensemble in mean surface temperature and variability.We explore the relationships between model uncertainties in SM-ET coupling and climate projections. In particular over mid-to-high-latitude continental regions of the Northern Hemisphere but also in parts of the tropics, models that are more soilmoisture-limited in the present tend to warm more in future projections, because they project less increase in ET and (in midlatitudes) greater increase in incoming solar radiation. Soil moisture-atmosphere processes thus contribute to the relationship observed across models between summertime present-day simulated climate and future warming projections over land. [ABSTRACT FROM AUTHOR]

Leaf area index (LAI) is increasing throughout the globe, implying Earth greening. Global modeling studies support this contention, yet satellite observations and model simulations have never been directly compared. Here, for the first time, a coupled land–climate model was used to quantify the potential impact of the satellite-observed Earth greening over the past 30 years on the terrestrial water cycle. The global LAI enhancement of 8% between the early 1980s and the early 2010s is modeled to have caused increases of 12.0 ± 2.4 mm yr−1 in evapotranspiration and 12.1 ± 2.7 mm yr−1 in precipitation—about 55% ± 25% and 28% ± 6% of the observed increases in land evapotranspiration and precipitation, respectively. In wet regions, the greening did not significantly decrease runoff and soil moisture because it intensified moisture recycling through a coincident increase of evapotranspiration and precipitation. But in dry regions, including the Sahel, west Asia, northern India, the western United States, and the Mediterranean coast, the greening was modeled to significantly decrease soil moisture through its coupling with the atmospheric water cycle. This modeled soil moisture response, however, might have biases resulting from the precipitation biases in the model. For example, the model dry bias might have underestimated the soil moisture response in the observed dry area (e.g., the Sahel and northern India) given that the modeled soil moisture is near the wilting point. Thus, an accurate representation of precipitation and its feedbacks in Earth system models is essential for simulations and predictions of how soil moisture responds to LAI changes, and therefore how the terrestrial water cycle responds to climate change. [ABSTRACT FROM AUTHOR]

Short-term climate prediction based on a regional climate dynamical model heavily depends on atmospheric forcing and initial soil moisture state. In this study, the Weather Research and Forecasting (WRF) Model with different nudging schemes is used for approximate 2-yr simulations for investigating the importance of soil variables in seasonal temperature and precipitation simulations. The results show that the improvement of seasonal climate simulation (precipitation and air temperature) is more evident in the experiment of assimilating both soil and atmospheric variables than that in the experiments of assimilating atmospheric variables only. Further investigation of the impact of indirectly assimilating soil moisture on precipitation prediction with an indirect soil nudging (ISN) scheme shows that the precipitation reproducibility in summer is better than that in winter, and the effect of ISN is particularly prominent in the region where seasonal precipitation exceeds 200 mm. Moreover, statistical results also illustrate that initial soil moisture plays a crucial role in seasonal precipitation forecasts because of its slowly evolving nature, and its effect is more distinct in semiarid and semihumid regions than in arid and humid regions. The effects of indirectly assimilating soil moisture on precipitation can last two and three months in semiarid and semihumid areas, respectively. [ABSTRACT FROM AUTHOR]

Soil moisture-atmosphere interactions play a key role in modulating climate variability and extremes. This study investigates how soil moisture-atmosphere coupling may affect future extreme events, particularly the role of projected soil moisture in modulating the frequency and maximum duration of hot spells over North America, using the fifth-generation Canadian Regional Climate Model (CRCM5). With this objective, CRCM5 simulations, driven by two coupled general circulation models (MPI-ESM and CanESM2), are performed with and without soil moisture-atmosphere interactions for current (1981-2010) and future (2071-2100) climates over North America, for representative concentration pathways (RCPs) 4.5 and 8.5. Analysis indicates that, in future climate, the soil moisture-temperature coupling regions, located over the Great Plains in the current climate, will expand farther north, including large parts of central Canada. Results also indicate that soil moisture-atmosphere interactions will play an important role in modulating temperature extremes in the future by contributing more than 50% to the projected increase in hot-spell days over the southern Great Plains and parts of central Canada, especially for the RCP4.5 scenario. This higher contribution of soil moisture-atmosphere interactions to the future increases in hot-spell days for RCP4.5 is related to the fact that the projected decrease in soil moisture caused the soil to remain in a transitional regime between wet and dry state that is conducive to soil moisture-atmosphere coupling. For the RCP8.5 scenario, on the other hand, the future projected soil state over the southern United States and northern Mexico is too dry to have an impact on evapotranspiration and therefore on temperature. [ABSTRACT FROM AUTHOR]

The impacts of sea surface temperature (SST) anomalies and anthropogenic greenhouse gases on the likelihood of extreme drought occurring in the central United States in the year 2012 were investigated using large-ensemble simulations from a global atmospheric climate model. Two sets of experiments were conducted. In the first, the simulated hydroclimate of 2012 was compared to a baseline period (1986-2014) to investigate the impact of SSTs. In the second, the hydroclimate in a world with 2012-level anthropogenic forcing was compared to five 'counterfactual' versions of a 2012 world under preindustrial forcing. SST anomalies in 2012 increased the simulated likelihood of an extreme summer precipitation deficit (e.g., the deficit with a 2% exceedance probability) by a factor of 5. The likelihood of an extreme summer soil moisture deficit increased by a similar amount, due in great part to a large spring soil moisture deficit carrying over into summer. An anthropogenic impact on precipitation was detectable in the simulations, doubling the likelihood of what would have been a rainfall deficit with a 2% exceedance probability under preindustrial-level forcings. Despite this reduction in rainfall, summer soil moisture during extreme drought was essentially unaffected by anthropogenic forcing because of 1) evapotranspiration declining roughly one-to-one with a decrease in precipitation due to severe water supply constraint and despite higher evaporative demand and 2) a decrease in stomatal conductance, and therefore a decrease in potential transpiration, with higher atmospheric CO2 concentrations. [ABSTRACT FROM AUTHOR]

A case study is presented using the northeast United States to evaluate information contained in the monthly mean annual cycle that has yet to be exploited. This research documents the performance and projections for the northeast United States from a suite of 16 climate models in the archive of phase 5 of the Coupled Model Intercomparison Project (CMIP5) from the World Climate Research Programme (WCRP). Analysis is performed for the late twentieth-century monthly mean annual cycle and changes in the late twenty-first century. A weak seasonality in temperature and a strong seasonality in precipitation changes are found. The seasonality of changes is distinct from the mean annual cycles, such that temperature increases are largest in midwinter (December-February) and late summer [July-September (JAS)]. Precipitation increases peak in late winter-early spring (February-April), associated with increased moisture convergence and a more active storm track, and exhibit greatest model disagreement in late summer (JAS) when the models suggest weak divergence and a westward extension of the Atlantic subtropical anticyclone. The late summer-early fall maximum in temperature and late winter-early spring maximum in precipitation changes have not been seen previously in annual or seasonal mean analyses. Yet there is model agreement in these results, indicating that there is important information in the annual cycle for understanding the changes in the physical climate system and for evaluating impacts and adaptation strategies. It is argued that improved understanding of seasonal transitions has potential to increase confidence in projections, and to provide additional information of use to the impacts and decision-maker communities. [ABSTRACT FROM AUTHOR]

The current California drought has cast a heavy burden on statewide agriculture and water resources, further exacerbated by concurrent extreme high temperatures. Furthermore, industrial-era global radiative forcing brings into question the role of long-term climate change with regard to California drought. How has human-induced climate change affected California drought risk? Here, observations and model experimentation are applied to characterize this drought employing metrics that synthesize drought duration, cumulative precipitation deficit, and soil moisture depletion. The model simulations show that increases in radiative forcing since the late nineteenth century induce both increased annual precipitation and increased surface temperature over California, consistent with prior model studies and with observed long-term change. As a result, there is no material difference in the frequency of droughts defined using bivariate indicators of precipitation and near-surface (10 cm) soil moisture, because shallow soil moisture responds most sensitively to increased evaporation driven by warming, which compensates the increase in the precipitation. However, when using soil moisture within a deep root zone layer (1 m) as covariate, droughts become less frequent because deep soil moisture responds most sensitively to increased precipitation. The results illustrate the different land surface responses to anthropogenic forcing that are relevant for near-surface moisture exchange and for root zone moisture availability. The latter is especially relevant for agricultural impacts as the deep layer dictates moisture availability for plants, trees, and many crops. The results thus indicate that the net effect of climate change has made agricultural drought less likely and that the current severe impacts of drought on California's agriculture have not been substantially caused by long-term climate changes. [ABSTRACT FROM AUTHOR]

Previous studies on the response of the South Asian summer monsoon to the direct radiative forcing caused by anthropogenic absorbing aerosols have emphasized the role of premonsoonal aerosol forcing. This study examines the roles of aerosol forcing in both pre- and postonset periods using the Community Earth System Model, version 1.0.4, with the Community Atmosphere Model, version 4. Simulations were perturbed by model-derived radiative forcing applied (i) only during the premonsoonal period (May-June), (ii) only during the monsoonal period (July-August), and (iii) throughout both periods. Soil water storage is found to retain the effects of premonsoonal forcing into succeeding months, resulting in monsoonal central India drying. Monsoonal forcing is found to dry all of India through local responses. Large-scale responses, such as the meridional rotation of monsoon jet during June and its weakening during July-August, are significant only when aerosol forcing is present throughout both premonsoonal and monsoonal periods. Monsoon responses to premonsoonal forcing by the model-derived 'realistic' distribution versus a uniform wide-area distribution were compared. Both simulations exhibit central India drying in June. June precipitation over northwestern India (increase) and southwestern India (decrease) is significantly changed under realistic but not under wide-area forcing. Finally, the same aerosol forcing is found to dry or moisten the July-August period following the warm or cool phase of the simulations' ENSO-like internal variability. The selection of years used for analysis may affect the precipitation response obtained, but the overall effect seems to be an increase in rainfall variance over northwest and southwest India. [ABSTRACT FROM AUTHOR]

Potential biases in tree-ring reconstructed Palmer drought severity index (PDSI) are evaluated using Thornthwaite (TH), Penman-Monteith (PM), and self-calibrating Penman-Monteith (SC) PDSI in three diverse regions of the United States and tree-ring chronologies from the North American drought atlas (NADA). Minimal differences are found between the three PDSI reconstructions and all compare favorably to independently reconstructed Thornthwaite-based PDSI from the NADA. Reconstructions are bridged with model-derived PDSI_TH and PDSI_PM, which both closely track modeled soil moisture (near surface and full column) during the twentieth century. Differences between modeled moisture-balance metrics only emerge in twenty-first-century projections. These differences confirm the tendency of PDSI_TH to overestimate drying when temperatures exceed the range of the normalization interval; the more physical accounting of PDSI_PM compares well with modeled soil moisture in the projection interval. Remaining regional differences in the secular behavior of projected soil moisture and PDSI_PM are interpreted in terms of underlying physical processes and temporal sampling. Results demonstrate the continued utility of PDSI as a metric of surface moisture balance while additionally providing two recommendations for future work: 1) PDSI_PM (or similar moisture-balance metrics) compare well to modeled soil moisture and are an appropriate means of representing soil-moisture balance in model simulations and 2) although PDSI_PM is more physically appropriate than PDSI_TH, the latter metric does not bias tree-ring reconstructions of past hydroclimate variability and, as such, reconstructions targeting PDSI_TH can be used with confidence in data-model comparisons. These recommendations and the collective results of this study thus provide a framework for comparing hydroclimate variability within paleoclimatic, observational, and modeled data. [ABSTRACT FROM AUTHOR]

Widespread negative correlations between summertime-mean temperatures and precipitation over land regions are a well-known feature of terrestrial climate. This behavior has generally been interpreted in the context of soil moisture-atmosphere coupling, with soil moisture deficits associated with reduced rainfall leading to enhanced surface sensible heating and higher surface temperature. The present study revisits the genesis of these negative temperature-precipitation correlations using simulations from the Global Land-Atmosphere Coupling Experiment-phase 5 of the Coupled Model Intercomparison Project (GLACE-CMIP5) multimodel experiment. The analyses are based on simulations with five climate models, which were integrated with prescribed (noninteractive) and with interactive soil moisture over the period 1950-2100. While the results presented here generally confirm the interpretation that negative correlations between seasonal temperature and precipitation arise through the direct control of soil moisture on surface heat flux partitioning, the presence of widespread negative correlations when soil moisture-atmosphere interactions are artificially removed in at least two out of five models suggests that atmospheric processes, in addition to land surface processes, contribute to the observed negative temperature-precipitation correlation. On longer time scales, the negative correlation between precipitation and temperature is shown to have implications for the projection of climate change impacts on near-surface climate: in all models, in the regions of strongest temperature-precipitation anticorrelation on interannual time scales, long-term regional warming is modulated to a large extent by the regional response of precipitation to climate change, with precipitation increases (decreases) being associated with minimum (maximum) warming. This correspondence appears to arise largely as the result of soil moisture-atmosphere interactions. [ABSTRACT FROM AUTHOR]

Atmospheric circulation patterns occurring on the warmest 10% of summer days for a region of Europe severely impacted by the 2003 heatwave have been identified using a perturbed parameter ensemble of regional high-resolution climate model simulations for the recent past. Changes in the frequency and duration of these circulation types, driven by the simulations following a moderate transient pathway of anthropogenic emissions, are then shown for the period 2070 to 2100. Increases in the future probability of hot days are then attributed separately to changes in the frequency and temperature intensity of the circulation types. Changes in temperature intensity are found to have an effect 2 to 3 times larger than in frequency. The authors then consider how model uncertainty in changes of future temperature within circulation patterns compares to the uncertainty irrespective of circulation, in an attempt to exclude contributions to the overall uncertainty arising from changes in circulation. Within individual patterns, the range of meteorological physical processes may be narrower. However, no reduction in uncertainty was found when single patterns were considered. Contributions to the lack of narrowing from circulation-type duration, model vegetation root depth and changes in cloud cover, pressure gradient, and continental-scale warming are subsequently examined using relationships between changes in surface latent heat and temperature. Vegetation root depth is found to be the greatest contributor to the temperature uncertainty. [ABSTRACT FROM AUTHOR]

The climate system model of the National Center for Atmospheric Research is used to examine the predictability arising from the land surface initialization of seasonal climate ensemble forecasts in current, preindustrial, and projected future settings. Predictability is defined in terms of the model's ability to predict its own interannual variability. Predictability from the land surface in this model is relatively weak compared to estimates from other climate models but has much of the same spatial and temporal structure found in previous studies. Several factors appear to contribute to the weakness, including a low correlation between surface fluxes and subsurface soil moisture, less soil moisture memory (lagged autocorrelation) than other models or observations, and relative insensitivity of the atmospheric boundary layer to surface flux variations. Furthermore, subseasonal cyclical behavior in plant phenology for tropical grasses introduces spurious unrealistic predictability at low latitudes during dry seasons. Despite these shortcomings, intriguing changes in predictability are found. Areas of historical land use change appear to have experienced changes in predictability, particularly where agriculture expanded dramatically into the Great Plains of North America, increasing land-driven predictability there. In a warming future climate, land-atmosphere coupling strength generally increases, but added predictability does not always follow; many other factors modulate land-driven predictability. [ABSTRACT FROM AUTHOR]

Long-term changes in land-atmosphere interactions during spring and summer are examined over North America. A suite of models from phase 5 of the Coupled Model Intercomparison Project simulating preindustrial, historical, and severe future climate change scenarios are examined for changes in soil moisture, surface fluxes, atmospheric boundary layer characteristics, and metrics of land-atmosphere coupling. Simulations of changes from preindustrial to modern conditions show warming brings stronger surface fluxes at high latitudes, while subtropical regions of North America respond with drier conditions. There is a clear anthropogenic aerosol response in midlatitudes that reduces surface radiation and heat fluxes, leading to shallower boundary layers and lower cloud base. Over the Great Plains, the signal does not reflect a purely radiatively forced response, showing evidence that the expansion of agriculture may have offset the aerosol impacts on the surface energy and water cycle. Future changes show soils are projected to dry across North America, even though precipitation increases north of a line that retreats poleward from spring to summer. Latent heat flux also has a north-south dipole of change, increasing north and decreasing south of a line that also moves northward with the changing season. Metrics of land-atmosphere feedback increase over most of the continent but are strongest where latent heat flux increases in the same location and season where precipitation decreases. Combined with broadly elevated cloud bases and deeper boundary layers, land-atmosphere interactions are projected to become more important in the future with possible consequences for seasonal climate prediction. [ABSTRACT FROM AUTHOR]

Simulated hydroclimate variability in millennium-length forced transient and control simulations from the ECHAM and the global Hamburg Ocean Primitive Equation (ECHO-G) coupled atmosphere-ocean general circulation model (AOGCM) is analyzed and compared to 1000 years of reconstructed Palmer drought severity index (PDSI) variability from the North American Drought Atlas (NADA). The ability of the model to simulate megadroughts in the North American southwest is evaluated. (NASW: 25°-42.5°N, 125°-105°W). Megadroughts in the ECHO-G AOGCM are found to be similar in duration and magnitude to those estimated from the NADA. The droughts in the forced simulation are not, however, temporally synchronous with those in the paleoclimate record, nor are there significant differences between the drought features simulated in the forced and control runs. These results indicate that model-simulated megadroughts can result from internal variability of the modeled climate system rather than as a response to changes in exogenous forcings. Although the ECHO-G AOGCM is capable of simulating megadroughts through persistent La Niña-like conditions in the tropical Pacific, other mechanisms can produce similarly extreme NASW moisture anomalies in the model. In particular, the lack of low-frequency coherence between NASW soil moisture and simulated modes of climate variability like the El Niño-Southern Oscillation, Pacific decadal oscillation, and Atlantic multidecadal oscillation during identified drought periods suggests that stochastic atmospheric variability can contribute significantly to the occurrence of simulated megadroughts in the NASW. These findings indicate that either an expanded paradigm is needed to understand multidecadal hydroclimate variability in the NASW or AOGCMs may incorrectly simulate the strength and/or dynamics of the connection between NASW hydroclimate variability and the tropical Pacific. [ABSTRACT FROM AUTHOR]

A process-based, semianalytic prototype model for understanding large-scale land-atmosphere coupling is developed here. The metric for quantifying the coupling is the sensitivity of precipitation P to soil moisture W, . For a range of prototype parameters typical of conditions found over tropical or summertime continents, the sensitivity measure exhibits a broad minimum at intermediate soil moisture values. This minimum is attributed to a trade-off between evaporation (or evapotranspiration) E and large-scale moisture convergence across the range of soil moisture states. For water-limited, low soil moisture conditions, is dominated by evaporative sensitivity , reflecting high potential evaporation Ep arising from relatively warm surface conditions and a moisture-deficient atmospheric column under dry surface conditions. By contrast, under high soil moisture (or energy limited) conditions, becomes slightly negative as Ep decreases. However, because convergence and precipitation increase strongly with decreasing (drying) moisture advection, while soil moisture slowly saturates, is large. Variation of key parameters is shown to impact the magnitude of , for example, increasing the time scale for deep convective adjustment lowers at a given W, especially on the moist side of the profile where convergence dominates. While the prototype's applicability for direct quantitative comparison with either observations or models is clearly limited, it nonetheless demonstrates how the complex interplay of surface turbulent and column radiative fluxes, deep convection, and horizontal and vertical moisture transport influences the coupling of the land surface and atmosphere that may be expected to occur in either more realistic models or observations. [ABSTRACT FROM AUTHOR]

This study examines the sensitivity of the global climate to land surface processes (LSP) using an atmospheric general circulation model both uncoupled (with prescribed SSTs) and coupled to an oceanic general circulation model. The emphasis is on the interactive soil moisture and vegetation biophysical processes, which have first-order influence on the surface energy and water budgets. The sensitivity to those processes is represented by the differences between model simulations, in which two land surface schemes are considered: 1) a simple land scheme that specifies surface albedo and soil moisture availability and 2) the Simplified Simple Biosphere Model (SSiB), which allows for consideration of interactive soil moisture and vegetation biophysical process. Observational datasets are also employed to assess the extent to which results are realistic. The mean state sensitivity to different LSP is stronger in the coupled mode, especially in the tropical Pacific. Furthermore, the seasonal cycle of SSTs in the equatorial Pacific, as well as the ENSO frequency, amplitude, and locking to the seasonal cycle of SSTs, is significantly modified and more realistic with SSiB. This outstanding sensitivity of the atmosphere-ocean system develops through changes in the intensity of equatorial Pacific trades modified by convection over land. The results further demonstrate that the direct impact of land-atmosphere interactions on the tropical climate is modified by feedbacks associated with perturbed oceanic conditions ('indirect effect' of LSP). The magnitude of such an indirect effect is strong enough to suggest that comprehensive studies on the importance of LSP on the global climate have to be made in a system that allows for atmosphere-ocean interactions. [ABSTRACT FROM AUTHOR]

Changes in the area of Australia experiencing concurrent temperature and rainfall extremes are investigated through the use of two combined indices. The indices describe variations between the fraction of land area experiencing extreme cold and dry or hot and wet conditions. There is a high level of agreement between the variations and trends of the indices from 1957 to 2008 when computed using (i) a spatially complete gridded dataset without rigorous quality control checks and (ii) spatially incomplete high-quality station datasets with rigorous quality control checks. Australian extremes are examined starting from 1911, which is the first time a broad-scale assessment of Australian temperature extremes has been performed prior to 1957. Over the whole country, the results show an increase in the extent of hot and wet extremes and a decrease in the extent of cold and dry extremes annually and during all seasons from 1911 to 2008 at a rate of between 1%% and 2%% decade−−1. These trends mostly stem from changes in tropical regions during summer and spring. There are relationships between the extent of extreme maximum temperatures, precipitation, and soil moisture on interannual and decadal time scales that are similar to the relationships exhibited by variations of the means. However, the trends from 1911 to 2008 and from 1957 to 2008 are not consistent with these relationships, providing evidence that the processes causing the interannual variations and those causing the longer-term trends are different. [ABSTRACT FROM AUTHOR]

The Global Land–Atmosphere Coupling Experiment (GLACE) built a framework to estimate the strength of the land–atmosphere interaction across many weather and climate models. Within this framework, GLACE-type experiments are performed with a single atmospheric model coupled to three different land models. The precipitation time series is decomposed into three frequency bands to investigate the large-scale connection between external forcing, precipitation variability and predictability, and land–atmosphere coupling strength. It is found that coupling to different land models or prescribing subsurface soil moisture does not change the global pattern of precipitation predictability and variability too much. However, the regional impact of soil moisture can be highlighted by calculating the land–atmosphere coupling strength, which shows very different patterns for the three models. The estimated precipitation predictability and land–atmosphere coupling strength is mainly associated with the low-frequency component of precipitation (periods beyond 3 weeks). Based on these findings, the land–atmosphere coupling strength is conceptually decomposed into the impact of low-frequency external forcing and the impact of soil moisture. Because most models participating in GLACE have overestimated the low-frequency component of precipitation, a calibration to the GLACE-estimated land–atmosphere coupling strength is performed. The calibrated coupling strength is generally weaker, but the global pattern does not change much. This study provides an important clarification of land–atmosphere coupling strength and increases the understanding of the land–atmosphere interaction. [ABSTRACT FROM AUTHOR]

The probabilistic modal response of vegetation to stochastic precipitation variability is studied in a conceptual climate–ecosystem model. It is found that vegetation can exhibit bimodality in a monostable climate–ecosystem under strong rainfall variability and with soil moisture memory comparable with that of the vegetation. The bimodality of vegetation is generated by a convolution of a nonlinear vegetation response and a colored stochastic noise. The nonlinear vegetation response is such that vegetation becomes insensitive to precipitation variability near either end state (green or desert), providing the potential for two preferred modes. The long memory of soil moisture allows the vegetation to respond to a slow stochastic forcing such that the vegetation tends to grow toward its equilibrium states. The implication of the noise-induced bimodality to abrupt changes in the climate–ecosystem is also discussed. [ABSTRACT FROM AUTHOR]

Climate model simulations consistently show that surface temperature over land increases more rapidly than over sea in response to greenhouse gas forcing. The enhanced warming over land is not simply a transient effect caused by the land–sea contrast in heat capacities, since it is also present in equilibrium conditions. This paper elucidates the transient adjustment processes over time scales of days to weeks of the surface and tropospheric climate in response to a doubling of CO2 and to changes in sea surface temperature (SST), imposed separately and together, using ensembles of experiments with an atmospheric general circulation model. These adjustment processes can be grouped into three stages: immediate response of the troposphere and surface processes (day 1), fast adjustment of surface processes (days 2–5), and adjustment of the whole troposphere (days 6–20). Some land surface warming in response to doubled CO2 (with unchanged SSTs) occurs immediately because of increased downward longwave radiation. Increased CO2 also leads to reduced plant stomatal resistance and hence restricted evaporation, which increases land surface warming in the first day. Rapid reductions in cloud amount lead in the next few days to increased downward shortwave radiation and further warming, which spreads upward from the surface, and by day 5 the surface and tropospheric response is statistically consistent with the equilibrium value. Land surface warming in response to imposed SST change (with unchanged CO2) is slower. Tropospheric warming is advected inland from the sea, and over land it occurs at all levels together rather than spreading upward from the surface. The atmospheric response to prescribed SST change in about 20 days is statistically consistent with the equilibrium value, and the warming is largest in the upper troposphere over both land and sea. The land surface warming involves reduction of cloud cover and increased downward shortwave radiation, as in the experiment with CO2 change, but in this case it is due to the restriction of moisture supply to the land (indicated by reduced soil moisture), whereas in the CO2 forcing experiment it is due to restricted evaporation despite increased moisture supply (indicated by increased soil moisture). The warming over land in response to SST change is greater than over the sea and is the dominant contribution to the land–sea warming contrast under enhanced CO2 forcing. [ABSTRACT FROM AUTHOR]

Numerous modeling studies have shown that soil moisture anomalies in later spring have a significant effect on the summer rainfall anomalies in North America. On the other hand, the role of soil moisture in forming monsoonal precipitation in East Asia has not been identified. This study attempts to clarify the importance of soil moisture on the summer rainfall in late spring in East Asia. The National Centers for Environmental Prediction (NCEP) Regional Spectral Model (RSM) is utilized for 3-month (June–August) simulations in 1998 (above-normal precipitation year) and 1997 (below-normal precipitation year). Initial and boundary conditions are derived from the NCEP–Department of Energy (DOE) reanalysis. The control run uses the initial soil moisture from the reanalysis, whereas it is set as a saturation and wilting point for “wet” and “dry” experiments, respectively. The impact of soil moisture anomalies on the simulated summer rainfall in East Asia is not significant. The change in precipitation between the wet and dry experiments is about 10%. A conflict between the local feedback of soil moisture and a change in large-scale circulations associated with the summertime monsoonal circulation in East Asia can be attributed as a reason for this anomaly. It is found that enhanced (suppressed) evaporation from the soil to the atmosphere in wet (dry) initial soil moisture reduces (increases) the land–sea contrast between East Asia and the Pacific Ocean, leading to a weakened sensitivity of the monsoonal circulations to the initial soil moisture. It can be concluded that the impact of the initial soil moisture is significant on the dynamic circulation in East Asia. [ABSTRACT FROM AUTHOR]

A 10 000-yr unforced simulation with the Commonwealth Scientific and Industrial Research Organisation (CSIRO) Mark 2 coupled global climatic model has been used to investigate the occurrence of heat waves over the globe. Results are presented for both seasonal (summer mean) and daily heat waves. Geographical distributions of the occurrence rates of these heat waves are shown for various magnitudes of surface temperature anomalies. The heat waves have specific geographical preferences with regions where relatively frequent, intense, and long-lasting heat waves occur. Time series over all 10 000 yr of the heat waves for the selected model grid boxes illustrate the differing temporal variabilities at these locations, as well as identifying the occurrences of extreme heat waves. To this end, the observed European heat wave of 2003 was simulated remarkably well in its overall characteristics; it occurs once in this simulation. Heat waves for various continental locations are shown to occur as isolated spatial and temporal events, and not as part of larger-scale systems over continental-size domains, suggesting stochastic forcing as a contributor to the initiation of the heat waves. Regional plots of selected heat waves at monthly intervals illustrated the considerable spatial variability, progression, and variation in the intensity of the heat waves. Comparison of year-long daily surface temperature anomalies for heat-wave years for simulated and observed conditions at individual model grid boxes indicated substantial agreement, while spatial plots permitted the progress of a short-term heat wave over the United States to be followed. Multidecadal time series plots of intense heat waves also showed basic similarities between the simulation and observations, despite the brevity of the latter. The simulated time series suggest that more extreme heat waves than currently are observed, owing to the brevity of the observations, may be a possibility as a consequence solely of natural variability. An examination of the physical processes associated with a heat wave showed mutually consistent climatic relationships, such that a heat wave was associated with reduced rainfall and consequently reduced soil moisture content, evaporation, and cloud cover, and increased insolation at the surface. These combined changes created the surface temperature increase intrinsic to the heat wave. All heat waves examined for different regions experienced negative rainfall anomalies prior to a heat wave. The cause of these rainfall anomalies was not readily apparent. While an ENSO influence on heat waves is shown to exist in the simulation, not all ENSO events produce heat waves, suggesting that stochastic influences may determine when a major heat wave occurs in conjunction with these events. The limitations of the adequacy of the model ENSO may, however, have had an influence in this regard. [ABSTRACT FROM AUTHOR]

Outputs from two ensembles of atmospheric model simulations for 1951–98 define the influence of “realistic” land surface wetness on seasonal precipitation predictability in boreal summer. The ensembles consist of one forced with observed sea surface temperatures (SSTs) and the other forced with realistic land surface wetness as well as SSTs. Predictability was determined from correlations between the time series of simulated and observed precipitation. The ratio of forced variance to total variance determined potential predictability. Predictability occurred over some land areas adjacent to tropical oceans without land wetness forcing. On the other hand, because of the chaotic nature of the atmosphere, considerable parts of the land areas of the globe did not even show potential predictability with both land wetness and SST forcings. The use of land wetness forcing enhanced predictability over semiarid regions. Such semiarid regions are generally characterized by a negative correlation between fluxes of latent heat and sensible heat from the land surface, and are “water-regulating” areas where soil moisture plays a governing role in land–atmosphere interactions. Actual seasonal prediction may be possible in these regions if slowly varying surface conditions can be estimated in advance. In contrast, some land regions (e.g., south of the Sahel, the Amazon, and Indochina) showed little predictability despite high potential predictability. These regions are mostly characterized by a positive correlation between the surface fluxes, and are “radiation-regulating” areas where the atmosphere plays a leading role. Improvements in predictability for these regions may require further improvements in model physics. [ABSTRACT FROM AUTHOR]

A statistical model based on canonical correlation analysis (CCA) was used to explore climatic associations and predictability of June–August (JJA) maximum and minimum surface air temperatures (Tmax and Tmin) as well as the frequency of Tmax daily extremes (Tmax90) in the central and western United States (west of 90°W). Explanatory variables are monthly and seasonal Pacific Ocean SST (PSST) and the Climate Division Palmer Drought Severity Index (PDSI) during 1950–2001. Although there is a positive correlation between Tmax and Tmin, the two variables exhibit somewhat different patterns and dynamics. Both exhibit their lowest levels of variability in summer, but that of Tmax is greater than Tmin. The predictability of Tmax is mainly associated with local effects related to previous soil moisture conditions at short range (one month to one season), with PSST providing a secondary influence. Predictability of Tmin is more strongly influenced by large-scale (PSST) patterns, with PDSI acting as a short-range predictive influence. For both predictand variables (Tmax and Tmin), the PDSI influence falls off markedly at time leads beyond a few months, but a PSST influence remains for at least two seasons. The maximum predictive skill for JJA Tmin, Tmax, and Tmax90 is from May PSST and PDSI. Importantly, skills evaluated for various seasons and time leads undergo a seasonal cycle that has maximum levels in summer. At the seasonal time frame, summer Tmax prediction skills are greatest in the Midwest, northern and central California, Arizona, and Utah. Similar results were found for Tmax90. In contrast, Tmin skill is spread over most of the western region, except for clusters of low skill in the northern Midwest and southern Montana, Idaho, and northern Arizona. [ABSTRACT FROM AUTHOR]

Observed vegetation feedbacks on temperature and precipitation are assessed across the United States using satellite-based fraction of photosynthetically active radiation (FPAR) and monthly climate data for the period of 1982–2000. This study represents the first attempt to spatially quantify the observed local impact of vegetation on temperature and precipitation over the United States for all months and by season. Lead–lag correlations and feedback parameters are computed to determine the regions where vegetation substantially impacts the atmosphere and to quantify this forcing. Temperature imposes a significant instantaneous forcing on FPAR, while precipitation's impact on FPAR is greatest at one-month lead, particularly across the prairie. An increase in vegetation raises the surface air temperature by absorbing additional radiation and, in some cases, masking the high albedo of snow cover. Vegetation generally exhibits a positive forcing on temperature, strongest in spring and particularly across the northern states. The local impact of FPAR on precipitation appears to be spatially inhomogeneous and relatively weak, potentially due to the atmospheric transport of transpired water. The computed feedback parameters can be used to evaluate vegetation–climate interactions simulated by models with dynamic vegetation. [ABSTRACT FROM AUTHOR]

The ensemble rainfall forecasts over the Sahel for July–September (JAS) from the NCEP Coupled Forecast System (CFS) were evaluated for the period 1981–2002. The comparison with the gauge-based precipitation analysis indicates that the predicted Sahel rainfall is light and exhibits little interannual variability. The rain belt is shifted about 4° southward. One major source of rainfall errors comes from the erroneous sea surface temperature (SST) forecasts. The systematic SST error pattern has positive errors in the North Pacific and the North Atlantic and negative errors in the tropical Pacific and the southern oceans. It resembles the decadal SST mode, which has a significant influence on rainfall over the Sahel. Because the systematic SST errors were not corrected during the forecasts, persistent errors serve as an additional forcing to the atmosphere. The second source of error is from the soil moisture feedback, which contributes to the southward shift of rainfall and dryness over West Africa. This was demonstrated by the comparison between simulations (SIMs) and the Atmospheric Model Intercomparison Project (AMIP) run. Both are forced with observed SSTs. The SIMs initialized at the end of June have realistic soil moisture and do not show the southward shift of rainfall. The AMIP, which predicts soil moisture, maintains the dryness through the summer over the Sahel. For AMIP, the decreased rainfall is contributed by the decreased evaporation (E) due to the dry soil and the shift of the large temperature gradients southward. In response, the African easterly jet (AEJ) shifts southward. Since this jet is the primary source of energy for the African waves and their associated mesoscale convective systems, these too shift southward. This negative feedback contributes to increased dryness over the Sahel. [ABSTRACT FROM AUTHOR]

A workshop on enhancing climate change indices in South America was held in Maceió, Brazil, in August 2004. Scientists from eight southern countries brought daily climatological data from their region for a meticulous assessment of data quality and homogeneity, and for the preparation of climate change indices that can be used for analyses of changes in climate extremes. This study presents an examination of the trends over 1960–2000 in the indices of daily temperature extremes. The results indicate no consistent changes in the indices based on daily maximum temperature while significant trends were found in the indices based on daily minimum temperature. Significant increasing trends in the percentage of warm nights and decreasing trends in the percentage of cold nights were observed at many stations. It seems that this warming is mostly due to more warm nights and fewer cold nights during the summer (December–February) and fall (March–May). The stations with significant trends appear to be located closer to the west and east coasts of South America. [ABSTRACT FROM AUTHOR]

Previous studies show that the climatological precipitation over South America, particularly the Nordeste region, is influenced by the presence of the African continent. Here the influence of African topography and surface wetness on the Atlantic marine ITCZ (AMI) and South American precipitation are investigated. Cross-equatorial flow over the Atlantic Ocean introduced by north–south asymmetry in surface conditions over Africa shifts the AMI in the direction of the flow. African topography, for example, introduces an anomalous high over the southern Atlantic Ocean and a low to the north. This results in a northward migration of the AMI and dry conditions over the Nordeste region. The implications of this process on variability are then studied by analyzing the response of the AMI to soil moisture anomalies over tropical Africa. Northerly flow induced by equatorially asymmetric perturbations in soil moisture over northern tropical Africa shifts the AMI southward, increasing the climatological precipitation over northeastern South America. Flow associated with an equatorially symmetric perturbation in soil moisture, however, has a very weak cross-equatorial component and very weak influence on the AMI and South American precipitation. The sensitivity of the AMI to soil moisture perturbations over certain regions of Africa can possibly improve the skill of prediction. [ABSTRACT FROM AUTHOR]

Interannual variations of Australian climate are strongly linked to the El Niño-Southern Oscillation (ENSO) phenomenon. However, the impact of other mechanisms on prediction, such as atmosphere-land surface interactions, has been less frequently investigated. Here, the impact of soil moisture variability on interannual climate variability and predictability is examined using the Bureau of Meteorology Research Centre atmospheric general circulation model. Two sets of experiments are run, each with five different initial conditions. In the first set of experiments, soil moisture is free to vary in response to atmospheric forcing in each experiment according to a set of simple prognostic equations. A potential predictability index is computed as the ratio of the model's internal variability to its external forced variability. This estimates the level of predictability obtained assuming perfect knowledge of future ocean surface temperatures. A second set of five experiments with prescribed soil moisture is performed. A comparison between these two sets of experiments reveals that fluctuations of soil moisture increase the persistence, the variance, and the potential predictability of surface temperature and rainfall. The interrelationship between these two variables is also strongly dependent upon the soil water content. Results are particularly marked over Australia in this model. A novel feature of this study is the focus on the effectiveness of ENSO-based statistical seasonal forecasting over Australia. Forecasting skill is shown to be crucially dependent upon soil moisture variability over the continent. In fact, surface temperature forecasts in this manner are not possible without soil moisture variability. This result suggests that a better representation of land-surface interaction has the potential to increase the skill of seasonal prediction schemes. [ABSTRACT FROM AUTHOR]

Month-long integrations with a regional climate model covering Europe and the Northern Atlantic are utilized to study the sensitivity of the summertime European precipitation climate with respect to the continental-scale soil moisture content. Experiments are conducted for July 1990 and 1993. For each of the two months, the control experiment with the initial soil water distribution derived from the operational ECMWF analysis is compared against two sensitivity experiments with dry and wet initial soil moisture distributions. The results demonstrate that summertime European precipitation climate in a belt ;1000 km wide between the wet Atlantic and the dry Mediterranean climate heavily depends upon the soil moisture content. In this belt, changes in monthly mean precipitation amount to about half of the changes in mean evapotranspiration. Budget analysis of water substance over selected subdomains demonstrate that the simulated sensitivity cannot be interpreted with the classical recycling mechanism, that is, the surplus of precipitation that falls over wet (as compared to dry) soils does not directly derive from evapotranspiration. Rather, the surplus of precipitation primarily originates from water vapor extracted from the ambient atmospheric flow. Thus, the soil--precipitation feedback must rely on some indirect mechanism, whereby wet soils increase the efficiency of convective precipitation processes. In order to isolate the physical mechanisms underlying the soil--precipitation feedback, a detailed analysis including an investigation of the mean diurnal cycle throughout the integration period is performed. The key elements of the feedback are the following. First, wet soils (small Bowen ratios) imply the buildup of a comparatively shallow boundary layer. The surface fluxes of heat and moisture are thus concentrated into a comparatively small volume of air, leading to the buildup of high values of low-level moist entropy, thereby providing a... [ABSTRACT FROM AUTHOR]