Search

Hydrologic, land surface, and other environmental models require meteorological input data--for example, precipitation and temperature to estimate discharge and soil moisture. In a hindcast these data are usually provided by [...]

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]

Despite the key importance of soil moisture-evapotranspiration (ET) coupling in the climate system, limited availability of soil moisture and ET observations poses a major impediment for investigation of this coupling regarding spatiotemporal characteristics and potential modifications under climate change. To better understand and quantify soil moisture-ET coupling and relevant processes, this study takes advantage of in situ soil moisture observations from the U.S. Climate Reference Network (USCRN) for the time period of 2010-17 and a satellite-derived version of the evapotranspiration stress index (ESI), which represents anomalies in a normalized ratio of actual to reference ET. The analyses reveal strong seasonality and regional characteristics of the ESI-land surface interactions across the United States, with the strongest control of soil moisture on the ESI found in the southern Great Plains during spring, and in the north-central United States, the northern Great Plains, and the Pacific Northwest during summer. In drier climate regions such as the northern Great Plains and north-central United States, soil moisture control on the ESI is confined to surface soil layers, with subsurface soil moisture passively responding to changes in the ESI. The soil moisture-ESI interaction is more uniform between surface and subsurface soils in wetter regions with higher vegetation cover. These results provide a benchmark for simulation of soil moisture-ET coupling and are useful for projection of associated climate processes in the future. [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]

The article presents a study investigating the role of anthropogenic climate change on extreme weather events in northeast China in 2017. Depicted are results of histogram and probability density functions (PDFs) of temperature and precipitation extremes. The research by Yuan et al. on soil moisture and temperature analysis is mentioned.

The design of reclamation soil covers at oil sands mines in northern Alberta, Canada, has been conventionally based on the calibration of soil–vegetation–atmosphere transfer (SVAT) models against field monitoring observations collected over several years, followed by simulations of long-term performance using historical climate data. This paper evaluates the long-term water balances for reclamation covers on two oil sands landforms and three natural coarse-textured forest soil profiles using both historical climate data and future climate projections. Twenty-first century daily precipitation and temperature data from CanESM2 were downscaled based on three representative concentration pathways (RCPs) employing a stochastic weather generator [Long Ashton Research Station Weather Generator (LARS-WG)]. Relative humidity, wind speed, and net radiation were downscaled using the delta change method. Downscaled precipitation and estimated potential evapotranspiration were used as inputs to simulate soil water dynamics using physically based models. Probability distributions of growing season (April–October) actual evapotranspiration (AET) and net percolation (NP) for the baseline and future periods show that AET and NP at all sites are expected to increase throughout the twenty-first century regardless of RCP, time period, and soil profile. Greater increases in AET and NP are projected toward the end of the twenty-first century. The increases in future NP at the two reclamation covers are larger (as a percentage increase) than at most of the natural sites. Increases in NP will result in greater water yield to surface water and may accelerate the rate at which chemical constituents contained within mine waste are released to downstream receptors, suggesting these potential changes need to be considered in mine closure designs. [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]

Land–atmosphere (L-A) interactions are a main driver of Earth’s surface water and energy budgets; as such, they modulate near-surface climate, including clouds and precipitation, and can influence the persistence of extremes such as drought. Despite their importance, the representation of L-A interactions in weather and climate models remains poorly constrained, as they involve a complex set of processes that are difficult to observe in nature. In addition, a complete understanding of L-A processes requires interdisciplinary expertise and approaches that transcend traditional research paradigms and communities. To address these issues, the international Global Energy and Water Exchanges project (GEWEX) Global Land–Atmosphere System Study (GLASS) panel has supported “L-A coupling” as one of its core themes for well over a decade. Under this initiative, several successful land surface and global climate modeling projects have identified hot spots of L-A coupling and helped quantify the role of land surface states in weather and climate predictability. GLASS formed the Local Land–Atmosphere Coupling (LoCo) project and working group to examine L-A interactions at the process level, focusing on understanding and quantifying these processes in nature and evaluating them in models. LoCo has produced an array of L-A coupling metrics for different applications and scales and has motivated a growing number of young scientists from around the world. This article provides an overview of the LoCo effort, including metric and model applications, along with scientific and programmatic developments and challenges. [ABSTRACT FROM AUTHOR]

Precipitation is affected by soil moisture spatial variability. However, this variability is not well represented in atmospheric models that do not consider soil moisture transport as a three-dimensional process. This study investigates the sensitivity of precipitation to the uncertainty in the representation of terrestrial water flow. The tools used for this investigation are the Weather Research and Forecasting (WRF) Model and its hydrologically enhanced version, WRF-Hydro, applied over central Europe during April-October 2008. The model grid is convection permitting, with a horizontal spacing of 2.8 km. The WRF-Hydro subgrid employs a 280-m resolution to resolve lateral terrestrial water flow. A WRF/WRF-Hydro ensemble is constructed by modifying the parameter controlling the partitioning between surface runoff and infiltration and by varying the planetary boundary layer (PBL) scheme. This ensemble represents terrestrial water flow uncertainty originating from the consideration of resolved lateral flow, terrestrial water flow uncertainty in the vertical direction, and turbulence parameterization uncertainty. The uncertainty of terrestrial water flow noticeably increases the normalized ensemble spread of daily precipitation where topography is moderate, surface flux spatial variability is high, and the weather regime is dominated by local processes. The adjusted continuous ranked probability score shows that the PBL uncertainty improves the skill of an ensemble subset in reproducing daily precipitation from the E-OBS observational product by 16%-20%. In comparison to WRF, WRF-Hydro improves this skill by 0.4%-0.7%. The reproduction of observed daily discharge with Nash-Sutcliffe model efficiency coefficients generally above 0.3 demonstrates the potential of WRF-Hydro in hydrological science. [ABSTRACT FROM AUTHOR]

In this study, a microwave-based multisatellite merged product released from the European Space Agency's Climate Change Initiative (ESA CCI) and two model-based simulations from the Community Land Model 4.5 (CLM4.5) and Global Land Data Assimilation System (GLDAS) were used to investigate interannual variations and trends of soil moisture in China between 1979 and 2010. They were also evaluated using in situ observations from the nationwide agrometeorological network. These three datasets show consistent drying trends for surface soil moisture in northeastern and central China, as well the eastern portion of Inner Mongolia, and wetting trends in the Tibetan Plateau, which are also identified by in situ observations. Trends in the root-zone soil moisture are in line with those of surface soil moisture seen in the CLM4.5 and GLDAS simulations obtained from most areas in China (78%-88%), except for northwestern China and southwest of the Tibetan Plateau. Moreover, the drying trend intensifies with increasing soil depth. Taking the in situ measurements as reference, it is found that ESA CCI has better accuracy in identifying the significant drying trends while CLM4.5 and GLDAS capture wetting trends better. Compared to temperature, precipitation is the primary factor responsible for these trends, which controls the direction of soil moisture changes, while increasing temperatures can also enhance soil drying during periods of decreased precipitation. [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]

This paper proposes a heat-wave definition for Bangladesh that could be used to trigger preparedness measures in a heat early warning system (HEWS) and explores the climate mechanisms associated with heat waves. A HEWS requires a definition of heat waves that is both related to human health outcomes and forecastable. No such definition has been developed for Bangladesh. Using a generalized additive regression model, a heat-wave definition is proposed that requires elevated minimum and maximum daily temperatures over the 95th percentile for 3 consecutive days, confirming the importance of nighttime conditions for health impacts. By this definition, death rates increase by about 20% during heat waves; this result can be used as an argument for public-health interventions to prevent heat-related deaths. Furthermore, predictability of these heat waves exists from weather to seasonal time scales, offering opportunities for a range of preparedness measures. Heat waves are associated with an absence of normal premonsoonal rainfall brought about by anomalously strong low-level westerly winds and weak southerlies, detectable up to approximately 10 days in advance. This circulation pattern occurs over a background of drier-than-normal conditions, with below-average soil moisture and precipitation throughout the heat-wave season from April to June. Low soil moisture increases the odds of heat-wave occurrence for 10-30 days, indicating that subseasonal forecasts of heat-wave risk may be possible by monitoring soil-moisture conditions. [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]

Watershed flooding is a function of meteorological and hydrologic catchment conditions. Climate change is anticipated to affect air temperature and precipitation patterns such as altered total precipitation, increased intensity, and shorter event durations in the northeastern United States. While significant work has been done to estimate future meteorological conditions, much is currently unknown about future changes to distributions of hydrologic state variables. High-resolution hydrologic simulations of Fall Creek (Tompkins County, New York), a small temperate watershed (324 km2) with seasonal snowmelt, are performed to evaluate future climate change impacts on flood hydrology. The effects of hydrologic state and environmental variables on river flood stage are isolated and the importance of groundwater elevation, unsaturated soil moisture, snowpack, and air temperature is demonstrated. It is shown that the temporal persistence of these hydrologic state variables allows for an influence on watershed flood hydrology for up to 20 days. Finally, six hypothetical climate change forcing scenarios are simulated to estimate the influence of catchment conditions on the watershed runoff response. The possibility of drier summers and wetter springs with a reduced winter snowpack in the Northeast is also simulated. These hydrologic changes influence flood discharge in the opposite direction as climate effects because of a reduced snowpack accumulation and melt time. Strong hydrologic state influence on flood discharge may be most attributable to increased air temperature and decreased precipitation. Hydrologic state variables may change both the location and shape of seasonal flood discharge distributions despite expected consistency in the shape of precipitation statistic distributions. [ABSTRACT FROM AUTHOR]

A new land surface scheme has been developed at Environment and Climate Change Canada (ECCC) to provide surface fluxes of momentum, heat, and moisture for the Global Environmental Multiscale (GEM) atmospheric model. In this study, the performance of the Soil, Vegetation, and Snow (SVS) scheme in estimating the surface and root-zone soil moisture is evaluated against the Interactions between Soil, Biosphere, and Atmosphere (ISBA) scheme currently used operationally at ECCC within GEM for numerical weather prediction. In addition, the sensitivity of SVS soil moisture results to soil texture and vegetation data sources (type and fractional coverage) has been explored. The performance of SVS and ISBA was assessed against a large set of in situ observations as well as the brightness temperature data from the Soil Moisture Ocean Salinity (SMOS) satellite over North America. The results indicate that SVS estimates the time evolution of soil moisture more accurately, and compared to ISBA, results in higher correlations with observations and reduced errors. The sensitivity tests carried out during this study revealed that the SVS soil moisture results are not affected significantly by the soil texture data from different sources. The vegetation data source, however, has a major impact on the soil moisture results predicted by SVS, and accurate specification of vegetation characteristics is therefore crucial for accurate soil moisture prediction. [ABSTRACT FROM AUTHOR]

This paper presents a detailed analysis of how future climate change may affect water availability in a typical arid endorheic river basin, the Heihe River basin (HRB), in northwest China. The analysis is based on the improved Soil Water Assessment Tool (SWAT), which is calibrated and validated with historical streamflow data from the upper HRB and is used to predict future hydrological responses. Six general circulation models (GCMs), under two emission scenarios (RCP4.5 and RCP8.5), are downscaled to construct future climate change scenarios. The results suggest that the climate of the upper HRB will likely become warmer and wetter in the near future (2021-50), with the largest increase in precipitation occurring in the summer. Correspondingly, the basinwide evapotranspiration, snowmelt, and runoff are projected to increase over the same period. The mean temperature in the near future is projected to rise, relative to the recent 30 years (1981-2010), by 1.2°-1.7°C under scenario RCP4.5 and by 1.4°-2.1°C under scenario RCP8.5. The mean precipitation is projected to increase by 10.0%-16.6% under scenario RCP4.5, and by 10.5%-22.0% under scenario RCP8.5. The mean values of evapotranspiration, snowmelt, and runoff are expected to increase by 14.2%, 4.3%, and 11.4%, respectively, under scenario RCP4.5 and to increase by 18.7%, 5.8%, and 12.8%, respectively, under scenario RCP8.5. Though the model simulations forecast an increase in streamflows in the headwater region of the HRB, future water availability varies significantly over space and time. The findings of this study will help to frame more effective water management strategies for the HRB under changing climatic conditions. [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]

A single-model 16-member ensemble is used to investigate how external model factors can affect model performance. Ensemble members are constructed with the land surface model (LSM) Joint UK Land Environment Simulator (JULES), with different choices of meteorological forcing [in situ, NCEP Climate Forecast System Reanalysis (CFSR)/CFSv2, or Water and Global Change (WATCH) Forcing Data ERA-Interim (WFDEI)] and ancillary datasets (in situ or remotely sensed), and with four time step modes. Effects of temporal averaging are investigated by comparing the hourly, daily, monthly, and seasonal ensemble performance against snow depth and water equivalent, soil temperature and moisture, and latent and sensible heat fluxes from one forest site and one clearing in the boreal ecozone of Finnish Lapland. Results show that meteorological data are the largest source of uncertainty; differences in ancillary data have little effect on model results. Although generally informative and representative, aggregated performance metrics fail to identify 'right results for the wrong reasons'; to do so, scrutinizing of time series and of interactions between variables is necessary. Temporal averaging over longer intervals improves metrics-with the notable exception of bias, which increases-by reducing the effects of internal data and model variability on model response. Model evaluation during shoulder seasons (fall minus spring) identifies weaknesses in the reanalyses datasets that conventional seasonal performance (winter minus summer) neglects. In view of the importance of snow on the range of results obtained with the same model, let alone identical simulations using different temporal averaging, it is recommended that systematic evaluation, quantification of errors, and uncertainties in snow-covered regions be incorporated in future efforts to standardize evaluation methods of LSMs. [ABSTRACT FROM AUTHOR]

Soil moisture observations from seven observational networks (spanning portions of seven states) with different biome and climate conditions were used in this study to evaluate multimodel simulated soil moisture products. The four land surface models, including Noah, Mosaic, Sacramento soil moisture accounting (SAC), and the Variable Infiltration Capacity model (VIC), were run within phase 2 of the North American Land Data Assimilation System (NLDAS-2), with a ⅛° spatial resolution and hourly temporal resolution. Hundreds of sites in Alabama, Colorado, Michigan, Nebraska, Oklahoma, West Texas, and Utah were used to evaluate simulated soil moisture in the 0-10-, 10-40-, and 40-100-cm soil layers. Soil moisture was spatially averaged in each state to reduce noise. In general, the four models captured broad features (e.g., seasonal variation) of soil moisture variations in all three soil layers in seven states, except for the 10-40-cm soil layer in West Texas and the 40-100-cm soil layer in Alabama, where the anomaly correlations are weak. Overall, Mosaic, SAC, and the ensemble mean have the highest simulation skill and VIC has the lowest simulation skill. The results show that Noah and VIC are wetter than the observations while Mosaic and SAC are drier than the observations, mostly likely because of systematic errors in model evapotranspiration. [ABSTRACT FROM AUTHOR]

Land-atmosphere coupling can strongly affect climate and climate extremes. Estimates of land-atmosphere coupling vary considerably between climate models, between different measures used to define coupling, and between the present and the future. The Australian Community Climate and Earth-System Simulator, version 1.3b (ACCESS1.3b), is used to derive and examine previously used measures of coupling strength. These include the GLACE-1 coupling measure derived on seasonal time scales; a similar measure defined using multiyear simulations; and four other measures of different complexity and data requirements, including measures that can be derived from standard model runs and observations. The ACCESS1.3b land-atmosphere coupling strength is comparable to other climate models. The coupling strength in the Southern Hemisphere summer is larger compared to the Northern Hemisphere summer and is dominated by a strong signal in the tropics and subtropics. The land-atmosphere coupling measures agree on the location of very strong land-atmosphere coupling but show differences in the spatial extent of these regions. However, the investigated measures show disagreement in weaker coupled regions, and some regions are only identified by a single measure as strongly coupled. In future projections the soil moisture trend is crucial in generating regions of strong land-atmosphere coupling, and the results suggest an expansion of coupling 'hot spots.' It is concluded that great care needs to be taken in using different measures of coupling strength and shown that several measures that can be easily derived lead to inconsistent conclusions with more computationally expensive measures designed to measure coupling strength. [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]

In the spring and early summer of 2011, the Assiniboine River basin in Canada experienced an extreme flood that was unprecedented in terms of duration and severity. The flood had significant socioeconomic impacts and caused over $1 billion (Canadian dollars) in damage. Contrary to what one might expect for such an extreme flood, individual precipitation events before and during the 2011 flood were not extreme; instead, it was the cumulative impact and timing of precipitation events going back to the summer of 2010 that played a key role in the 2011 flood. The summer and fall of 2010 were exceptionally wet, resulting in above-normal soil moisture levels at the time of freeze-up. This was followed by record high snow water equivalent values in March and April 2011. Cold temperatures in March delayed the spring melt, resulting in the above-average spring freshet occurring close to the onset of heavy rains in May and June. The large-scale atmospheric flow during May and June 2011 favored increased cyclone activity in the region, which produced an anomalously large number of heavy rainfall events over the basin. All of these factors combined generated extreme flooding. Japanese 55-year Reanalysis Project (JRA-55) data are used to quantify the relative importance of snowmelt and spring precipitation in contributing to the unprecedented flood and to demonstrate how the 2011 flood was unique compared to previous floods. This study can be used to validate and improve flood forecasting techniques over this important basin; the findings also raise important questions regarding floods in a changing climate over basins that experience pluvial and nival flooding. [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]

Over recent decades Europe has experienced heavy floods, with major consequences for thousands of people and billions of euros worth of damage. In particular, the summer of 2013 flood in central Europe showed how vulnerable modern society is to hydrological extremes and emphasized once more the need for improved forecast methods of such extreme climatic events. Based on a multiple linear regression model, it is shown here that 55% of the June 2013 Elbe River extreme discharge could have been predicted using May precipitation, soil moisture, and sea level pressure. Moreover, the model was able to predict more than 75% of the total Elbe River discharge for June 2013 (in terms of magnitude) by also incorporating the amount of precipitation recorded during the days prior to the flood, but the predicted discharge for the June 2013 event was still underestimated by 25%. Given that all predictors used in the model are available at the end of each month, the forecast scheme can be used to predict extreme events and to provide early warnings for upcoming floods. The forecast methodology could be relevant for other rivers also, depending on their location and their climatic background. [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]

Changes in precipitation, air temperature, and model-simulated soil moisture were examined for the observed (1950-2008) and projected (2010-99) climate for the sowing period of Kharif and Rabi [KHARIF_SOW (May-July) and RABI_SOW (October-December)] and the entire Kharif and Rabi [KHARIF (May-October) and RABI (October-April)] crop-growing periods in India. During the KHARIF_SOW and KHARIF periods, precipitation declined significantly in the Gangetic Plain, which in turn resulted in declines in soil moisture. Statistically significant warming trends were noticed as all-India-averaged air temperature increased by 0.40°, 0.90°, and 0.70°C in the KHARIF, RABI_SOW, and RABI periods, respectively, during 1950-2008. Frequency and areal extent of soil moisture-based droughts increased substantially during the latter half (1980-2008) of the observed period. Under the projected climate (2010-99), precipitation, air temperature, and soil moisture are projected to increase in all four crop-growing seasons. In the projected climate, all-India ensemble mean precipitation, air temperature, and soil moisture are projected to increase up to 39% (RABI_SOW period), 2.3°C, and 5.3%, respectively, in the crop-growing periods. While projected changes in air temperature are robust across India, robust increases in precipitation and soil moisture are projected to occur in the end-term (2070-99) climate. Frequency and areal extents of soil moisture-based severe, extreme, and exceptional droughts are projected to increase in the near- (2010-39) and midterm (2040-69) climate in the majority of crop-growing seasons in India. However, frequency and areal extent of droughts during the crop-growing period are projected to decline in the end-term climate in the entire crop-growing period because of projected increases in the monsoon season precipitation. [ABSTRACT FROM AUTHOR]

Moderate Resolution Imaging Spectroradiometer (MODIS)-derived vegetation fraction data were used to update the boundary conditions of the advanced research Weather Research and Forecasting (WRF) Model to assess the influence of realistic vegetation cover on climate simulations in southeast Australia for the period 2000-08. Results show that modeled air temperature was improved when MODIS data were incorporated, while precipitation changes little with only a small decrease in the bias. Air temperature changes in different seasons reflect the variability of vegetation cover well, while precipitation changes have a more complicated relationship to changes in vegetation fraction. Both MODIS and climatology-based simulation experiments capture the overall precipitation changes, indicating that precipitation is dominated by the large-scale circulation, with local vegetation changes contributing variations around these. Simulated feedbacks between vegetation fraction, soil moisture, and drought over southeast Australia were also investigated. Results indicate that vegetation fraction changes lag precipitation reductions by 6-8 months in nonarid regions. With the onset of the 2002 drought, a potential fast physical mechanism was found to play a positive role in the soil moisture-precipitation feedback, while a slow biological mechanism provides a negative feedback in the soil moisture-precipitation interaction on a longer time scale. That is, in the short term, a reduction in soil moisture leads to a reduction in the convective potential and, hence, precipitation, further reducing the soil moisture. If low levels of soil moisture persist long enough, reductions in vegetation cover and vigor occur, reducing the evapotranspiration and thus reducing the soil moisture decreases and dampening the fast physical feedback. Importantly, it was observed that these feedbacks are both space and time dependent. [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]

Hourly surface temperature differences between Dallas-Fort Worth, Texas, metropolitan and rural sites have been used to calculate the urban heat island from 2001 to 2011. The heat island peaked after sunset and was particularly strong during the drought and heat wave in July 2011, reaching a single-day instantaneous maximum value of 5.4°C and a monthly mean maximum of 3.4°C, as compared with the 2001-11 July average of 2.4°C. This severe drought caused faster warming of rural locations relative to the metropolitan area in the morning as a result of lower soil moisture content, which led to an average negative heat island in July 2011 of −2.3°C at 1100 central standard time. The ground-based assessment of canopy air temperature at screening level has been supported by a remotely sensed surface estimate from the Moderate Resolution Imaging Spectroradiometer (MODIS) on board the Terra satellite, highlighting a dual-peak maximum heat island in the major city centers of Dallas and Fort Worth. Both ground-based and remotely sensed spatial analyses of the maximum heat island indicate a northwest shift, the result of southeast winds in July 2011 of ~2 m s−1 on average. There was an overall positive trend in the urban heat island of 0.14°C decade−1 in the Dallas-Fort Worth metropolitan area from 2001 to 2011, due to rapid urbanization. Superimposed on this trend are significant interannual and decadal variations that influence the urban climate. [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]

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]

Data from 15 models of phase 5 of the Coupled Model Intercomparison Project (CMIP5) for preindustrial, historical, and future climate change experiments are examined for consensus changes in land surface variables, fluxes, and metrics relevant to land-atmosphere interactions. Consensus changes in soil moisture and latent heat fluxes for past-to-present and present-to-future periods are consistent with CMIP3 simulations, showing a general drying trend over land (less soil moisture, less evaporation) over most of the globe, with the notable exception of high northern latitudes during winter. Sensible heat flux and net radiation declined from preindustrial times to current conditions according to the multimodel consensus, mainly due to increasing aerosols, but that trend reverses abruptly in the future projection. No broad trends are found in soil moisture memory except for reductions during boreal winter associated with high-latitude warming and diminution of frozen soils. Land-atmosphere coupling is projected to increase in the future across most of the globe, meaning a greater control by soil moisture variations on surface fluxes and the lower troposphere. There is also a strong consensus for a deepening atmospheric boundary layer and diminished gradients across the entrainment zone at the top of the boundary layer, indicating that the land surface feedback on the atmosphere should become stronger both in absolute terms and relative to the influence of the conditions of the free atmosphere. Coupled with the trend toward greater hydrologic extremes such as severe droughts, the land surface seems likely to play a greater role in amplifying both extremes and trends in climate on subseasonal and longer time scales. [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]

Positive soil moisture-precipitation feedbacks can intensify heat and prolong drought under conditions of precipitation deficit. Adequate representation of these processes in regional climate models is, therefore, important for extended weather forecasts, seasonal drought analysis, and downscaled climate change projections. This paper presents the first application of the NASA Unified Weather Research and Forecasting Model (NU-WRF) to simulation of seasonal drought. Simulations of the 2006 southern Great Plains drought performed with and without soil moisture memory indicate that local soil moisture feedbacks had the potential to concentrate precipitation in wet areas relative to dry areas in summer drought months. Introduction of a simple dynamic surface albedo scheme that models albedo as a function of soil moisture intensified the simulated feedback pattern at local scale-dry, brighter areas received even less precipitation while wet, whereas darker areas received more-but did not significantly change the total amount of precipitation simulated across the drought-affected region. This soil-moisture-mediated albedo land-atmosphere coupling pathway is structurally excluded from standard versions of WRF. [ABSTRACT FROM AUTHOR]

The atmospheric moisture budget and surface interactions for the southern Great Plains are evaluated for contrasting May-June periods (1998, 2002, 2006, and 2007) as background for the Cloud and Land Surface Interaction Campaign (CLASIC) of (wet) 7-30 June 2007. Budget components [flux divergence (MFD), storage change (dPW), and inflow (IF/ A)] are estimated from North American Regional Reanalysis data. Precipitation ( P) is calculated from NCEP daily gridded data, evapotranspiration ( E) is obtained as moisture budget equation residual, and the recycling ratio ( PE/ P) is estimated using a new equation. Regional averages are presented for months and five daily P categories. Monthly budget results show that E and E − P are strongly positively related to P; E − P generally is positive and balanced by positive MFD that results from its horizontal velocity divergence component (HD, positive) exceeding its horizontal advection component (HA, negative). An exception is 2007 (CLASIC), when E − P and MFD are negative and supported primarily by negative HA. These overall monthly results characterize low P days (≤0.6 mm), including for nonanomalous 2007, but weaken as daily P approaches 4 mm. In contrast, for 4 < P ≤ 8 mm day−1 E − P and MFD are moderately negative and balanced largely by negative HD except in 2007 (negative HA). This overall pattern was accentuated (including for nonanomalous 2007) when daily P > 8 mm. Daily P E/ P ratios are small and of limited range, with P category averages 0.15-0.19. Ratios for 2007 are above average only for daily P ≤ 4 mm. CLASIC wetness principally resulted from distinctive MFD characteristics. Solar radiation, soil moisture, and crop status/yield information document surface interactions. [ABSTRACT FROM AUTHOR]

This study examines the land-atmosphere coupling strength during summer over subregions of the United States based on observations [Climate Prediction Center (CPC)-Variable Infiltration Capacity (VIC)], reanalysis data [North American Regional Reanalysis (NARR) and NCEP Climate Forecast System Reanalysis (CFSR)], and models [Community Atmosphere Model, version 3 (CAM3)-Community Land Model, version 3 (CLM3) and CAM4-CLM4]. The probability density function of conditioned correlation between soil moisture and subsequent precipitation or surface temperature during the years of large precipitation anomalies is used as a measure for the coupling strength. There are three major findings: 1) among the eight subregions (classified by land cover types), the transition zone Great Plains (and, to a lesser extent, the Midwest and Southeast) are identified as hot spots for strong land-atmosphere coupling; 2) soil moisture-precipitation coupling is weaker than soil moisture-surface temperature coupling; and 3) the coupling strength is stronger in observational and reanalysis products than in the models examined, especially in CAM4-CLM4. The conditioned correlation analysis also indicates that the coupling strength in CAM4-CLM4 is weaker than in CAM3-CLM3, which is further supported by Global Land-Atmosphere Coupling Experiments1 (GLACE1)-type experiments and attributed to changes in CAM rather than modifications in CLM. Contrary to suggestions in previous studies, CAM-CLM models do not seem to overestimate the land-atmosphere coupling strength. [ABSTRACT FROM AUTHOR]

Anthropogenic activities have been significantly perturbing global freshwater flows and groundwater reserves. Despite numerous advances in the development of land surface models (LSMs) and global terrestrial hydrological models (GHMs), relatively few studies have attempted to simulate the impacts of anthropogenic activities on the terrestrial water cycle using the framework of LSMs. From the comparison of simulated terrestrial water storage with the Gravity Recovery and Climate Experiment (GRACE) satellite observations it is found that a process-based LSM, the Minimal Advanced Treatments of Surface Interaction and Runoff (MATSIRO), outperforms the bucket-model-based GHM called H08 in simulating hydrologic variables, particularly in water-limited regions. Therefore, the water regulation modules of H08 are incorporated into MATSIRO. Further, a new irrigation scheme based on the soil moisture deficit is developed. Incorporation of anthropogenic water regulation modules significantly improves river discharge simulation in the heavily regulated global river basins. Simulated irrigation water withdrawal for the year 2000 (2462 km3 yr−1) agrees well with the estimates provided by the Food and Agriculture Organization (FAO). Results indicate that irrigation changes surface energy balance, causing a maximum increase of ~50 W m−2 in latent heat flux averaged over June-August. Moreover, unsustainable anthropogenic water use in 2000 is estimated to be ~450 km3 yr−1, which corresponds well with documented records of groundwater overdraft, representing an encouraging improvement over the previous modeling studies. Globally, unsustainable water use accounts for ~40%% of blue water used for irrigation. The representation of anthropogenic activities in MATSIRO makes the model a suitable tool for assessing potential anthropogenic impacts on global water resources and hydrology. [ABSTRACT FROM AUTHOR]

Land surface model experiments are used to quantify, for a number of U.S. river basins, the contributions (isolated and combined) of soil moisture and snowpack initialization to the skill of seasonal streamflow forecasts at multiple leads and for different start dates. Snow initialization has a major impact on skill during the spring melting season. Soil moisture initialization has a smaller but still statistically significant impact during this season, and in other seasons, its contribution to skill dominates. Realistic soil moisture initialization can contribute to skill at long leads (over 6 months) for certain basins and seasons. Skill levels in all seasons are found to be related to the ratio of initial total water storage (soil water plus snow) variance to the forecast period precipitation variance, allowing estimates of the potential for skill in areas outside the verification basins. [ABSTRACT FROM AUTHOR]

A revised framework for the analysis of soil moisture memory characteristics of climate models and observational data is derived from the approach proposed by Koster and Suarez. The resulting equation allows the expression of the month-to-month soil moisture autocorrelation as a function of 1) the initial soil moisture variability, 2) the (atmospheric) forcing variability over the considered time period, 3) the correlation between initial soil moisture and subsequent forcing, 4) the sensitivity of evaporation to soil moisture, and 5) the sensitivity of runoff to soil moisture. A specific new feature is the disentangling of the roles of initial soil moisture variability and forcing variability, which were both (for the latter indirectly) contributing to the seasonality term of the original formulation. In addition, a version of the framework entirely based on explicit equations for the underlying relationships (i.e., independent of soil moisture statistics at the following time step) is proposed. The validity of the derived equation is exemplified with atmospheric general circulation model (AGCM) simulations from the Global Land-Atmosphere Coupling Experiment (GLACE). [ABSTRACT FROM AUTHOR]

Linkages between the terrestrial ecosystem and precipitation play a critical role in regulating regional weather and climate. These linkages can manifest themselves as positive or negative feedback loops, which may either favor or inhibit the triggering and intensity of thunderstorms. Although the Canadian Prairies terrestrial system has been identified as having the potential to exert a detectable influence on convective precipitation during the warm season, little work has been done in this area using in situ observations. The authors present findings from a novel study designed to explore linkages between the normalized difference vegetation index (NDVI) and lightning duration (DUR) from the Canadian Lightning Detection Network for 38 census agricultural regions (CARs) on the Canadian Prairies. Statistics Canada divides the prairie agricultural zone into CARs (polygons of varying size and shape) for the purpose of calculating agricultural statistics. Here, DUR is used as a proxy for thunderstorm activity. Statistical analyses were undertaken for 38 CARs for summers [June--August (JJA)] between 1999 and 2008. Specifically, coefficients of determination were calculated between pairs of standardized anomalies of DUR and NDVI by season and by month. Correlations were also calculated for CARs grouped by size and/or magnitude of the NDVI anomalies. The main findings are as follows: 1) JJA lightning activity is overwhelmingly below average within larger dry areas (i.e., areas with below-average NDVI); that is, the linkages between NDVI and DUR increased significantly as both the area and magnitude of the dry anomaly increased. 2) In contrast, CARs with above-average NDVI did not consistently experience above-average lightning activity, regardless of the CAR size. 3) The lower threshold for the length scale of the dry anomalies required to affect the boundary layer sufficiently to reduce lightning activity was found to be approximately 150 km (~18 000 km2). 4) The authors'' analysis suggests that the surface-convection feedback appears to be a real phenomenon, in which drought tends to perpetuate drought with respect to convective storms and associated rainfall, within the limits found in 1) and 3). [ABSTRACT FROM AUTHOR]