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In this paper, we introduce a novel strategy to robustly diagnose the onset and demise of the rainy season using daily observed rainfall over seven specific regions across Australia, as demarcated by the Natural Resource Management (NRM) agency of Australia. The methodology lies in developing an ensemble spread of the diagnosed onset and demise from randomly perturbing the observed daily time series of rainfall at synoptic scales to obtain a measure of the uncertainty of the diagnosis. Our results indicate that the spread of the ensemble in the diagnosis of the onset and demise dates of the rainy season is higher in the subtropical region than the tropical region. Secular change of earlier onset, later demise, longer length, and wetter season are also identified in many of these regions. The influence of the PDO at decadal scale, ENSO and Indian Ocean dipole at interannual scale, and MJO at intraseasonal scale also reveals significant influence on the evolution of the rainy season over these regions in Australia. Most important, the covariability of the onset date with the length of the season and seasonal rainfall anomaly of the season is highlighted as a valuable relationship that can be exploited for real-time monitoring and providing an outlook of the forthcoming rainy season, which could serve some of the NRM regions. Significance Statement: We document the rainfall variability during the rainy season over tropical, subtropical, and semiarid regions of Australia and relate them to modes of climate variability spanning from intraseasonal to secular time scales. The study highlights the varied influence of the modes of climate variability on various aspects of the evolution of the rainy season, such as its onset and demise dates and the seasonal rainfall anomaly over these Australian regions. The study uses 114 years of data and shows that the variations in the length of the rainy season and its seasonal rainfall anomaly are strongly dictated by variations of rainy-season onset date. This provides a quick seasonal outlook of the forthcoming rainy season by just monitoring the onset-date evolution in these regions. [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]

The systematic bias of the estimated average temperature using daily Tmax and Tmin records relative to the standard average temperature of four time-equidistant observations and its effect on the estimated trend of long-term temperature change have not been well understood. This paper attempts to evaluate the systematic bias across mainland China using the daily data of national observational stations. The results revealed that the positive bias of annual mean temperature was large, reaching 0.58°C nationally on average; regional average bias was lowest in the northwest arid region and highest in the Qinghai–Tibetan Plateau; the bias was low in spring and summer and high in autumn and winter, reaching its lowest point in mid- and late May and highest point in early November. Furthermore, the bias showed a significant upward trend in the past 50 years, with a rising rate of 0.021°C (10 yr)−1, accounting for about 12% of the overall warming as estimated from the data of the observational network; the largest positive trend bias was found in the northwest arid region, while the east monsoon region experienced the smallest change; the most remarkable increase of the bias occurred after early 1990s. These results indicate that the customarily applied method to calculate daily and monthly mean temperature using Tmax and Tmin significantly overestimates the climatological mean and the long-term trend of surface air temperature in mainland China. [ABSTRACT FROM AUTHOR]

Exposure to weather extremes, such as heatwaves, can cause discomfort, harm, or death in grazing cattle in pastures. While the Australian Bureau of Meteorology issues sheep graziers alerts when there is an exposure risk to chill for livestock, there is no equivalent alert for heat stress for Australian cattle. Before any such alert system can be developed, a robust assessment and comparison of relevant cattle thermal stress indices is required. This study evaluates and compares the multiyear climatology of three cattle thermal heat stress indices across Australia in the warm season months (October–March). The same indices are then used to assess historical Australian heat events where cattle died from heat exposure. These events are based off official records and survey responses from northern Australian graziers. In the seven historical heat events studied, high relative humidity combined with low wind speeds, or high solar exposure combined with high surface temperatures, exacerbated the impact of heat stress on cattle. In the two historic events where multiple compounding weather factors combined (e.g., high humidity, low winds, and high solar exposure), the cattle mortality levels were significantly high. These events were characterized by rainy conditions followed by a rapid warming, meaning cattle were likely unable to acclimatize to such dramatic temperature changes. This study highlights the need for using more than one thermal stress index when verifying cattle heat stress events and, importantly, calls for further research on standardizing the risk classifications of these thermal indices for cattle in Australia's variable climate. Significance Statement: Cattle across Australia's northern tropical and semiarid regions often experience extreme hot and humid conditions in the summer months, which increases the risk of heat stress. This is the first study of its kind to evaluate observations of cattle heat stress across Australia using indices that describe the combined effects of solar exposure, wind speed, relative humidity, and surface temperatures. These cattle heat stress indices can be used to evaluate historical cattle mortality events in feedlots and in grazed pastures. This study lays the groundwork for the development of Australian-wide cattle heat stress forecast products on the 7-day to multiweek time scales. [ABSTRACT FROM AUTHOR]

The long-range transport of bioaerosols by dust events significantly impacts ecological and meteorological networks of the atmosphere, biosphere, and anthroposphere. Bioaerosols not only cause significant public health risks, but also act as efficient ice nuclei for inducing cloud formation and precipitation in the hydrological cycle. To establish risk management for bioaerosol impacts on the Earth system, a large-scale investigation of bioaerosols must be performed under different environmental conditions. For this purpose, a Dust–Bioaerosol (DuBi) field campaign was conducted to investigate the distribution of bioaerosols by collecting ∼950 samples at 39 sites across East Asia from 2016 to 2021. Concentrations and community structures of bioaerosols were further analyzed using fluorescence microscopic observations and high-throughput DNA sequencing, and these factors were compared to environmental factors, such as PM10 and aridity. The results indicated that microbial concentrations at dryland sites were statistically higher than those at humid sites, while the microbe-to-total-particle ratio was statistically lower in drylands than in humid regions. Microbial cells per microgram of PM10 decreased when PM10 increased. The proportion of airborne particles at each site did not vary substantially with season. The richness and diversity of airborne bacteria were significantly higher in drylands than in semiarid regions, while the community structures were stable among all sampling sites. The DuBi field campaign improves our understanding of bioaerosol characteristic variations along the dust transport pathway in East Asia and the changes of bioaerosols under the trend of climate warming, supporting the efforts to reduce public health risks. SIGNIFICANCE STATEMENT: We first conducted large-scale Dust–Bioaerosol (DuBi) field observations in East Asia from 2016 to 2021. We used unified sampling and analysis methods to collect 950 samples at 39 sites and analyzed bioaerosols' concentration and community structure. This study aims to find the relationship between bioaerosols with atmospheric particles and aridity, which fills gaps in the field. These results improve our understanding of bioaerosols' impacts on ecological and meteorological networks of the atmosphere, biosphere, and anthroposphere. The comprehensive observations will promote prediction of bioaerosol change under the trend of climate warming, supporting the efforts to reduce global climate, ecological security, and public health risks in the future. [ABSTRACT FROM AUTHOR]

Land surface–atmosphere interactions are a key component of climate modeling. They are particularly critical to understand and anticipate the climate and the water resources over the semiarid and arid North African regions. This study uses in situ observations to assess the ability of the IPSL-CM global climate model to simulate the land–atmosphere interactions over the Moroccan semiarid plains. A specific configuration with a grid refinement over the Haouz Plain, near Marrakech, and nudging outside Morocco has been performed to properly assess the model's performances. To ensure reliable model–observation comparisons despite the fact that station measurements are not representative of a mesh-size area, we carried out experiments with adapted vegetation properties. Results show that the CMIP6 version of the model's physics represents the near-surface climate over the Haouz Plain reasonably well. Nonetheless, the simulation exhibits a nocturnal warm bias, and the wind speed is overestimated in tree-covered meshes and underestimated in the wheat-covered region. Further sensitivity experiments reveal that LAI-dependent parameterization of roughness length leads to a strong surface wind drag and to underestimated land surface atmosphere thermal coupling. Setting the roughness heights to the observed values improves the wind speed and, to a lesser extent, the nocturnal temperature. A low bias in latent heat flux and soil moisture coinciding with a pronounced diurnal warm bias at the surface is still present in our simulations. Including a first-order irrigation parameterization yields more realistic simulated evapotranspiration flux and daytime skin surface temperatures. This result raises the importance of accounting for the irrigation process in present and future climate simulations over Moroccan agricultural areas. [ABSTRACT FROM AUTHOR]

Scarcity or unavailability of precipitation observation creates difficulties in hydrologic modeling of mountainous sections of the arid region of northwest China (34°-50°N, 72°-107°E). Tropical Rainfall Measuring Mission (TRMM) precipitation products may be a potential substitute, but they should be evaluated and corrected with ground observation data before application. In this paper, two TRMM Multisatellite Precipitation Analysis (TMPA) precipitation products were evaluated by gauge observations, using indices such as frequency bias index, probability of detection, false alarm ratio, relative mean bias, Nash-Sutcliffe efficiency, and correlation coefficient. Terrain variables were extracted from a digital elevation model, and their rotated principal components were determined to establish a stepwise regression model to adjust TMPA precipitation. Additionally, a back-propagation (BP) neural network was established to correct TMPA precipitation. The results showed that TMPA had an unsatisfactory detection ability in the study area for both precipitation occurrence and amount. TMPA precipitation corrected by a stepwise regression method showed some improvement, but only the results for TRMM 3B43 on a subregion scale were acceptable. The BP neural network method showed better results than the stepwise regression method, and both TRMM 3B42 and TRMM 3B43 corrected by the former method on a subregion scale could be acceptable. Both methods were spatial-scale dependent and showed better results on a subregion scale than on a larger scale. [ABSTRACT FROM AUTHOR]

Climate change impact on a groundwater-dependent small urban town has been investigated in the semiarid hard rock aquifer in southern India. A distributed groundwater model was used to simulate the groundwater levels in the study region for the projected future rainfall (2012-32) obtained from a general circulation model (GCM) to estimate the impacts of climate change and management practices on groundwater system. Management practices were based on the human-induced changes on the urban infrastructure such as reduced recharge from the lakes, reduced recharge from water and wastewater utility due to an operational and functioning underground drainage system, and additional water extracted by the water utility for domestic purposes. An assessment of impacts on the groundwater levels was carried out by calibrating a groundwater model using comprehensive data gathered during the period 2008-11 and then simulating the future groundwater level changes using rainfall from six GCMs [Institute of Numerical Mathematics Coupled Model, version 3.0 (INM-CM.3.0); L'Institut Pierre-Simon Laplace Coupled Model, version 4 (IPSL-CM4); Model for Interdisciplinary Research on Climate, version 3.2 (MIROC3.2); ECHAM and the global Hamburg Ocean Primitive Equation (ECHO-G); Hadley Centre Coupled Model, version 3 (HadCM3); and Hadley Centre Global Environment Model, version 1 (HadGEM1)] that were found to show good correlation to the historical rainfall in the study area. The model results for the present condition indicate that the annual average discharge (sum of pumping and natural groundwater outflow) was marginally or moderately higher at various locations than the recharge and further the recharge is aided from the recharge from the lakes. Model simulations showed that groundwater levels were vulnerable to the GCM rainfall and a scenario of moderate reduction in recharge from lakes. Hence, it is important to sustain the induced recharge from lakes by ensuring that sufficient runoff water flows to these lakes. [ABSTRACT FROM AUTHOR]

Hydrological processes in most semiarid regions on Earth have been changing under the impacts of climate change, human activities, or combinations of the two. This paper first presents a trend analysis of the spatiotemporal changes in water resources and then diagnoses their underlying atmospheric and socio-economic causes over 10 catchments in the Laoha basin, a typical semiarid zone of northeast China. The impacts of climate variability and human activities on streamflow change were quantitatively evaluated by the VIC (Variable Infiltration Capacity) model. First, results indicate that six out of the 10 studied catch-ments have statistically significant downward trends in annual streamflow; however, there is no significant change of annual precipitation for all catchments. Two abrupt changes of annual streamflow at 1979 and 1998 are identified for the four largest catchments. Second, the Laoha basin generally experienced three evident dry-wet pattern switches during the past 50 years. Furthermore, this basin is currently suffering from unprecedented water shortages. Large-scale climate variability has affected the local natural hy-drologie system. Third, quantitative evaluation shows human activities were the main driving factors for the streamflow reduction with contributions of approximately 90% for the whole basin. A significant in-crease in irrigated area, which inevitably resulted in tremendous agricultural water consumption, is the foremost culprit contributing to the dramatic runoff reduction, especially at midstream and downstream of the Laoha basin. This study is expected to enable policymakers and stakeholders to make well-informed, short-term practice decisions and better plan long-term water resource and ecoenvironment management strategies. [ABSTRACT FROM AUTHOR]

The majority of the world's population growth to 2050 is projected to occur in the tropics. Hence, there is a serious need for robust methods for undertaking water resource assessments to underpin the sustainable management of water in tropical regions. This paper describes the largest and most comprehensive assessment of the future impacts of runoff undertaken in a tropical region using conceptual rainfall-runoff models (RRMs). Five conceptual RRMs were calibrated using data from 115 streamflow gauging stations, and model parameters were regionalized using a combination of spatial proximity and catchment similarity. Future rainfall and evapotranspiration projections (denoted here as GCMES) were transformed to catchment-scale variables by empirically scaling (ES) the historical climate series, informed by 15 global climate models (GCMs), to reflect a 1°C increase in global average surface air temperature. Using the best-performing RRM ensemble, approximately half the GCMES used resulted in a spatially averaged increase in mean annual runoff (by up to 29%%) and half resulted in a decrease (by up to 26%%). However, ~70%% of the GCMES resulted in a difference of within ±5%% of the historical rainfall (1930-2007). The range in modeled impact on runoff, as estimated by five RRMs (for individual GCMES), was compared to the range in modeled runoff using 15 GCMES (for individual RRMs). For mid- to high runoff metrics, better predictions will come from improved GCMES projections. A new finding of this study is that in the wet-dry tropics, for extremely large runoff events and low flows, improvements are needed in both GCMES and rainfall-runoff modeling. [ABSTRACT FROM AUTHOR]

Parameterization of turbulent flux from bare-soil and undercanopy surfaces is imperative for modeling land–atmosphere interactions in arid and semiarid regions, where flux from the ground is dominant or comparable to canopy-sourced flux. This paper presents the major characteristics of turbulent flux transfers over seven bare-soil surfaces. These sites are located in arid, semiarid, and semihumid regions in Asia and represent a variety of conditions for aerodynamic roughness length (z0m; from <1 to 10 mm) and sensible heat flux (from -50 to 400 W m-2). For each site, parameter kB-1 [=ln(z0m/z0h), where z0h is the thermal roughness length] exhibits clear diurnal variations with higher values during the day and lower values at night. Mean values of z0h for the individual sites do not change significantly with z0m, resulting in kB-1 increasing with z0m, and thus the momentum transfer coefficient increases faster than the heat transfer coefficient with z0m. The term kB-1 often becomes negative at night for relatively smooth surfaces (z0m ∼ 1 mm), indicating that the widely accepted excess resistance for heat transfer can be negative, which cannot be explained by current theories for aerodynamically rough surfaces. Last, several kB-1 schemes are evaluated using the same datasets. The results indicate that a scheme that can reproduce the diurnal variation of kB-1 generally performs better than schemes that cannot. [ABSTRACT FROM AUTHOR]

Detailed information on the spatial and temporal characteristics of precipitation intensity from the mountainous region of northwest Mexico has, until recently, been lacking. As part of the 2004 North American Monsoon Experiment (NAME) enhanced observing period (EOP) surface rain gauge networks along with weather radar and orbiting satellites were employed to observe precipitation in a manner heretofore unprecedented for this semiarid region. The NAME Event Rain gauge Network (NERN), which has been in operation since 2002, contributed to this effort. Building on previous work, this paper presents analyses on the spatial and temporal characteristics of precipitation intensity as observed by NERN gauges. Analyses from the 2004 EOP are compared with the 2002–04 period and with long-term gauge observations. It was found that total precipitation from July to August of 2004 was similar in spatial extent and magnitude to the long-term average, though substantially wetter than 2003. Statistical analyses of precipitation intensity data from the NERN reveal that large precipitation events at hourly and daily time scales are restricted to coastal and low-elevation areas west of the Sierra Madre Occidental. At 10-min time scales, maximum intensity values equal to those at low elevations could be observed at higher elevations though they were comparatively infrequent. It is also shown that the inclusion of NERN observations in existing operational analyses helps to correct significant biases, which, on the seasonal time scale, are of similar magnitude as the interannual variability in precipitation in key headwater regions of northwest Mexico. [ABSTRACT FROM AUTHOR]

Regional precipitation recycling may constitute a feedback mechanism affecting soil moisture memory and the persistence of anomalously dry or wet states. Bulk methods, which estimate recycling based on time-averaged variables, have been applied on a global basis, but these methods may underestimate recycling by neglecting the effects of correlated transients. A back-trajectory method identifies the evaporative sources of vapor contributing to precipitation events by tracing air motion backward in time through the analysis grid of a data-assimilating numerical model. The back-trajectory method has been applied to several large regions; in this paper it is extended to all global land areas for 1979–2003. Meteorological information (wind vectors, humidity, surface pressure, and evaporation) are taken from the NCEP–Department of Energy (DOE) reanalysis, and a hybrid 3-hourly precipitation dataset is produced to establish the termini of the trajectories. The effect of grid size on the recycling fraction is removed using an empirical power-law relationship; this allows comparison among any land areas on a latitude–longitude grid. Recycling ratios are computed on a monthly basis for a 25-yr period. The annual and seasonal averages are consistent with previous estimates in terms of spatial patterns, but the trajectory method generally gives higher estimates of recycling than a bulk method, using compatible spatial scales. High northern latitude regions show the largest amplitude in the annual cycle of recycling, with maxima in late spring/early summer. Amplitudes in arid regions are small in absolute terms, but large relative to their mean values. Regions with strong interannual variability in recycling do not correspond directly to regions with strong intra-annual variability. The average recycling ratio at a spatial scale of 105 km2 for all land areas of the globe is 4.5%; on a global basis, recycling shows a weak positive trend over the 25 yr, driven largely by increases at high northern latitudes. [ABSTRACT FROM AUTHOR]

Because land surface emissivity (ℇ) has not been reliably measured, global climate model (GCM) land surface schemes conventionally set this parameter as simply constant, for example, 1 as in the National Oceanic and Atmospheric Administration (NOAA) National Centers for Environmental Prediction (NCEP) model, and 0.96 for bare soil as in the National Center for Atmospheric Research (NCAR) Community Land Model version 2 (CLM2). This is the so-called constant-emissivity assumption. Accurate broadband emissivity data are needed as model inputs to better simulate the land surface climate. It is demonstrated in this paper that the assumption of the constant emissivity induces errors in modeling the surface energy budget, especially over large arid and semiarid areas where ℇ is far smaller than unity. One feasible solution to this problem is to apply the satellite-based broadband emissivity into land surface models. The Moderate Resolution Imaging Spectroradiometer (MODIS) instrument has routinely measured spectral emissivities (ℇλ) in six thermal infrared bands. The empirical regression equations have been developed in this study to convert these spectral emissivities to broadband emissivity (ℇ) required by land surface models. The observed emissivity data show strong seasonality and land-cover dependence. Specifically, emissivity depends on surface-cover type, soil moisture content, soil organic composition, vegetation density, and structure. For example, broadband ℇ is usually around 0.96–0.98 for densely vegetated areas [(leaf area index) LAI > 2], but it can be lower than 0.90 for bare soils (e.g., desert). To examine the impact of variable surface broadband emissivity, sensitivity studies were conducted using offline CLM2 and coupled NCAR Community Atmosphere Models, CAM2–CLM2. These sensitivity studies illustrate that large impacts of surface ℇ occur over deserts, with changes up to 1°–2°C in ground temperature, surface skin temperature, and 2-m surface air temperature, as well as evident changes in sensible and latent heat fluxes. [ABSTRACT FROM AUTHOR]

The area–time integral (ATI) method has previously been successfully used to estimate the area-averaged rain-rate distribution and the rainfall volume over an area from radar or from satellite infrared (IR) data. In most cases, the method was implemented over regions or test areas with an assumed homogeneous climatic character, that is, without a strong spatial variation of the rain regime throughout the test area. In the present paper, the behavior of the ATI method is discussed for a test area displaying two strong gradients of the cumulative annual rainfall: one meridional, at the transition between regions having, respectively, a desertic and an equatorial climate and the other zonal, at the transition between land and sea. The studied area is divided into four subtest areas (north, south, land, and sea) over which the ATI computation is applied separately. The linear coefficient relating the radar-observed area-averaged rain rate and the fractional area where the rain is higher than a threshold calculated over the four subtest areas is found to be almost constant, in agreement with the ergodic character of the rain-rate distribution observed in this region. Similarly, the linear coefficient relating the rain volume over the subtest areas to the IR satellite-derived ATI, a parameter analogous to the Geostationary Operational Environmental Satellite (GOES) Precipitation Index (GPI), is found to be very steady, with a mean value of 3.02 mm h-1 and a coefficient of variation of only 8%. These coefficients, as well as the underlying dynamic and microphysical processes, do not seem significantly influenced by the climatic character, even at a short space scale, in the studied area. The ratio of radar rain areas to cloud areas is, notably, almost constant. For a brightness temperature of 235 K, the ratio of the cloud area to rain area is around 1.68. [ABSTRACT FROM AUTHOR]

This paper examines observational evidence of a positive feedback between the land surface and rainfall in semiarid conditions. The novelty of the work lies in the length scale of study, investigating interactions between soil moisture patterns and deep convection at scales of less than 20 km. The feedback mechanism was proposed in a previous study to explain the development of an anomalous rainfall gradient in the West African Sahel. The aim here is to assess whether such rainfall persistence occurs elsewhere in the region. Convective-scale rainfall patterns are examined using two years of observations from a dense rain gauge network in southwest Niger. Rainfall differences are analyzed between neighboring gauges separated by 7.5-15 km. Under certain surface conditions, a positive correlation between daily and antecedent rainfall differences is established. These circumstances arise when previous storm patterns have modified local evaporation rates. Rainfall gradients in subsequent events tend to persist, reinforcing soil moisture patterns. The effect appears to be most pronounced in mature, large-scale storms. The widespread occurrence of persistence in the dataset provides strong observational evidence of a surface feedback mechanism, with surface-induced low-level humidity anomalies locally enhancing convection in passing storms. Several rainfall patterns that persist for a month are identified. These patterns are linked to surface processes and the frequency of storm passage. [ABSTRACT FROM AUTHOR]

The major tributary of the lower Colorado River, the Gila River, is a critical source of water for human and natural environments in the southwestern United States. Warmer and drier than the upper Colorado River basin, with less snow and a bimodal precipitation regime, the Gila River is controlled by a set of climatic conditions that is different from the controls on upper Colorado River flow. Unlike the Colorado River at Lees Ferry in Arizona, the upper Gila River and major Gila River tributaries, the Salt and Verde Rivers, do not yet reflect significant declines in annual streamflow, despite warming trends. Annual streamflow is dominated by cool-season precipitation, but the monsoon influence is discernable as well, variable across the basin and complicated by an inverse relationship with cool-season precipitation in the Salt and Verde River basins. Major multiyear streamflow droughts in these two basins have frequently been accompanied by wet monsoons, suggesting that monsoon precipitation may partially offset the impacts of a dry cool season. While statistically significant trends in annual streamflow are not evident, decreases in autumn and spring streamflow reflect warming temperatures and some decreases in spring precipitation. Because climatic controls vary with topography and the influence of the monsoon, the impact of warming on streamflow in the three subbasins is somewhat variable. However, given relationships between climate and streamflow, current trends in hydroclimate, and projections for the future, it would be prudent to expect declines in Gila River water supplies in the coming decades. Significance Statement: This research investigates the climatic controls on the Gila River and its major tributaries, the Verde and Salt Rivers, to gain insights on how trends in climate may impact future water supply. The Gila River is the major tributary of the lower Colorado River, but, unlike the situation for the upper Colorado River, no significant decreasing trends in annual streamflow are evident despite warming temperatures. Climate–streamflow relationships are more complex in this part of the Colorado River basin, and several factors may be buffering streamflow to the impact of warming. However, given the key climatic controls on streamflow, current and emerging trends in climate, and projections for the future, declines in streamflow should be expected in the future. [ABSTRACT FROM AUTHOR]

Uncertainty in the calculation of a standardized precipitation index (SPI) attracted growing concerns in the hydrometeorology research community in the last decade. This issue is addressed in the present study from the perspective of candidate probability distributions, the data record length, the cumulative time scale, and the selection of a reference period with the bootstrap and Monte Carlo methods using daily precipitation data observed in four climate regions across China. The impacts of the uncertainty in an SPI calculation on drought assessment are also investigated. Results show that the gamma distribution is optimal in describing the cumulative precipitation in China; among the four time scales investigated in the present study (i.e., 10, 20, 30, and 90 days), the minimal time scale appropriate for SPI calculation is 20 days for the humid region, 30 days for the semihumid/semiarid region and Tibetan Plateau (mostly its eastern part), and 90 days for the arid region. The uncertainty in SPI calculation decreases with the increase of time scale and record length, essentially as a consequence of the decrease of the confidence interval width of gamma distribution parameters with the increase of time scale and record length. But there is little improvement for the parameter estimation with record length longer than 70 years. There is greater uncertainty for high absolute SPI values than for small ones; consequently, there is greater uncertainty in assessing extreme droughts than moderate droughts. Reference period selection has large impacts on drought assessment, especially in the context of climate change. The uncertainty of the SPI calculation has large impacts on categorizing droughts, but no impact on assessing the temporal features of drought variation. Significance Statement: The standardized precipitation index (SPI) is the most commonly used drought index over the world for drought assessment, but there are several issues not well recognized in its application, such as the uncertainty resulting from the choice of time scales, the record length, and the reference period for its calculation. A comprehensive evaluation of these issues will be helpful for better interpreting SPI values for drought assessments, especially in the context of climate change. [ABSTRACT FROM AUTHOR]

Comparison and quantification of different uncertainties of future climate change involved in the modeling of a hydrological system are highly important for both hydrological modelers and policy-makers. However, few studies have accurately estimated the relative importance of different sources of uncertainty at different spatiotemporal scales. Here, a hierarchical sensitivity analysis framework (HSAF) incorporated with a variance-based global sensitivity analysis is developed to quantify the spatiotemporal contributions of different uncertainties in hydrological impacts of climate change in two different climatic (humid and semiarid) basins in China. The uncertainty sources include three emission scenarios (ESs), 20 global climate models (GCs), three hydrological models (HMs), and the associated sensitive hydrological parameters (PAs) screened and sampled by the Morris and Latin hypercube sampling methods, respectively. The results indicate that the overall trend of uncertainty is PA > HM > GC > ES, but their uncertainties have discrepancies in projections of different hydrological variables. The HM uncertainty in annual and monthly discharge projections is generally larger than the PA uncertainty in the humid basin than semiarid basin. The PA has greater uncertainty in extreme hydrological event (annual peak discharge) projections than in annual discharge projections for both basins (particularly for the humid basin), but contributes larger uncertainty to annual and monthly discharge projections in the semiarid basin than humid basin. The GC contributes larger uncertainty in all the hydrological variables projections in the humid basin than semiarid basin, while the ES uncertainty is rather limited in both basins. Overall, our results suggest there is greater spatiotemporal variability of hydrological uncertainty in more arid regions. [ABSTRACT FROM AUTHOR]

One of the critical components in understanding the climate system is the interaction between the land and the atmosphere. Whereas previous studies on land–atmosphere coupling mostly focus on its spatial hotspots, we explore the temporal evolution of land surface coupling strength (LCS) during a large-scale flood event in a semiarid region in northern Australia. The LCS indicates the relationship between soil moisture and latent heat flux, and the spatiotemporal variability in precipitation and soil water strongly affects the variability of LCS. The LCS is usually positive in the semiarid climate, where evapotranspiration (ET) occurs under the soil moisture–limited regime and thus increases with soil moisture. However, our analyses of combined land surface modeling and observational datasets show high temporal variability of LCS in the course of the extreme flood event followed by a drying period. The wet regions transferred the ET regime from the soil moisture–limited to the transition section, weakening the linear growth of ET with soil moisture, which resulted in the decline of LCS. The LCS remained weak until the flood retreated and the soil water approached the prestorm average state. Such temporal variation of the LCS has important implications for realistic parameterization of the land–atmosphere coupling and consequently improving subseasonal to seasonal climate forecast. [ABSTRACT FROM AUTHOR]

Snow fraction has a direct impact on water resources in arid regions. The selection of proper methods for estimating snow fraction is thus essential. Two temperature-based and two humidity-based approaches to discriminate precipitation phase were evaluated using daily meteorological observations over the past six decades in Xinjiang in arid northwest China. The main findings included that 1) the finest discrimination was achieved by the wet-bulb temperature (Tw) method whereas the single temperature threshold at 0°C produces the poorest result; the performances of the Dai and humidity-dependent empirical method (TRH) methods were between them, with slightly lower error using the Dai method. Also, the Tw method is the least sensitive to regional heterogeneity and less affected by distinct changes in elevation; the other three methods, however, are biased mostly toward underestimating snow and show larger variations due to the regional discrepancies. Careful adjustment of snow discrimination thresholds based on the local properties of observation spots is needed for these methods. 2) Despite widespread warming, snow fraction perturbations in Xinjiang are characterized mainly by insignificant changes plus pronounced reductions at high mountain sites. Proxy drivers of such changes can be better explained by considering the hydrothermal diversity and changing climatic factors. Across the wetter subregions, snowfall has been significantly increasing, and the positive impact of which on snow fraction was hindered by significant warming, particularly in winter, and summer rainfall; across the drier subregions, however, insignificant change in snow fraction corresponds to a slow and insignificant increase in snowfall joined by the negative impacts of significant winter warming and summer rainfall. [ABSTRACT FROM AUTHOR]

Central Asia is a semiarid to arid region that is sensitive to hydrological changes. We use the Community Atmosphere Model, version 5 (CAM5), equipped with a water-tagging capability, to investigate the major moisture sources for climatological precipitation and its long-term trends over central Asia. Europe, the North Atlantic Ocean, and local evaporation, which explain 33.2% ± 1.5%, 23.0% ± 2.5%, and 19.4% ± 2.2% of the precipitation, respectively, are identified as the most dominant moisture sources for northern central Asia (NCA). For precipitation over southern central Asia (SCA), Europe, the North Atlantic, and local evaporation contribute 25.4% ± 2.7%, 18.0% ± 1.7%, and 14.7% 6 1.9%, respectively. In addition, the contributions of South Asia (8.6% ± 1.7%) and the Indian Ocean (9.5% ± 2.0%) are also substantial for SCA. Modulated by the seasonal meridional shift in the subtropical westerly jet, moisture originating from the low and midlatitudes is important in winter, spring, and autumn, whereas northern Europe contributes more to summer precipitation. Wealso explain the observed drying trends over southeastern central Asia in spring and overNCAin summer during 1956-2005. The drying trend over southeastern central Asia in spring is mainly due to the decrease in local evaporation and weakened moisture fluxes from the Arabian Peninsula and Arabian Sea associated with the warming of the western Pacific Ocean. The drying trend over NCA in summer can be attributed to a decrease in local evaporation and reduced moisture from northern Europe that is due to the southward shift of the subtropical westerly jet. [ABSTRACT FROM AUTHOR]

A thorough evaluation of the Weather Research and Forecasting (WRF) Model is conducted over the United Arab Emirates, for the period September 2017–August 2018. Two simulations are performed: one with the default model settings (control run), and another one (experiment) with an improved representation of soil texture and land use land cover (LULC). The model predictions are evaluated against observations at 35 weather stations, radiosonde profiles at the coastal Abu Dhabi International Airport, and surface fluxes from eddy-covariance measurements at the inland city of Al Ain. It is found that WRF's cold temperature bias, also present in the forcing data and seen almost exclusively at night, is reduced when the surface and soil properties are updated, by as much as 3.5 K. This arises from the expansion of the urban areas, and the replacement of loamy regions with sand, which has a higher thermal inertia. However, the model continues to overestimate the strength of the near-surface wind at all stations and seasons, typically by 0.5–1.5 m s−1. It is concluded that the albedo of barren/sparsely vegetated regions in WRF (0.380) is higher than that inferred from eddy-covariance observations (0.340), which can also explain the referred cold bias. At the Abu Dhabi site, even though soil texture and LULC are not changed, there is a small but positive effect on the predicted vertical profiles of temperature, humidity, and horizontal wind speed, mostly between 950 and 750 hPa, possibly because of differences in vertical mixing. [ABSTRACT FROM AUTHOR]

Using tree-ring data of Pinus sylvestris var. mongolica from the Hulun Buir region in northeast China, 12 annual runoff series of the Hailar River spanning the past 202-216 years were established for the first time; these included 11 branches and one for the entire basin. These reconstructions, which could explain 29.4%-52.7% of the total variance for the measured runoffs during 1956-2006, performed well in statistical verification tests. In the whole basin's reconstruction of 212 years, 34 extreme drought years (16.0%) and 41 extreme pluvial years (19.3%) were identified; 4 of the 10 most extreme years occurred after 1980. The consistent cycle and correlation revealed that the Hailar runoff had a teleconnection with the El Niño-Southern Oscillation (ENSO). The sharply increasing variance at the end of the reconstruction, accompanied by the increasing intensity of short cycles (4-8 years), indicated that runoff variability in the Hailar River basin has enhanced in the late twentieth century. This is verified by the drastic fluctuations in water level and area of rivers and lakes, and the frequent shift of natural land cover types in the Hulun Buir area in recent decades. The intensified runoff variability can be connected with the concurrently enhanced ENSO activity. Our study is the first to identify the intensification of recent runoff variability in the semiarid to arid region in northeast China from a long-term perspective. With projected enhancement of ENSO activity, the Hailar River basin will face the increased risk of extreme hydrological events. [ABSTRACT FROM AUTHOR]

Evaporation is a principal factor in the hydrological cycle and energy exchange; however, estimations of evaporation include large uncertainties. In this study, a modified estimation of evaporation based on empirical linearly simplified Penman evaporation (PES) is proposed, soil moisture and precipitation are used to correct the land surface evaporation estimation, and the temporal and spatial characteristics of the corrected evaporation (CE) are investigated globally. The results show that CE is strong at low latitudes and weak at high latitudes. CE has obvious seasonal variation, ranging from 0.2 to 4.0 mm day−1; CE is prominent in summer but feeble in winter. Compared to PES, CE is generally weaker in most regions, especially in arid regions, with differences of more than 9 mm day−1. CE agrees well with evaporation derived from FLUXNET-Model Tree Ensemble (FLUXNET-MTE), MERRA, and GLDAS. In general, the root-mean-square error (RMSE) between annual CE and FLUXNET-MTE is less than 0.2 mm day−1, and CE is about 5%–10% less than the evaporation of FLUXNET-MTE. In the arid regions, the maximum CE almost occurs in the month with the strongest precipitation; in the tropical regions, soil moisture enhances CE only when precipitation is less. In the context of global temperature rise, PES always shows an apparent increasing trend due to the water supply is not considered; however, CE decreases in western Asia, the western United States, the Amazon basin, and Central Africa, but weakly increases in the other study regions from 1984 to 2013. This study provides a method for estimating evaporation considering more restrictive factors on evaporation. [ABSTRACT FROM AUTHOR]

Drought is a prominent climatic hazard in the south-central United States. Drought severity is frequently classified using the categories established by the U.S. Drought Monitor (USDM). This study evaluates whether the thresholds for the standardized precipitation index (SPI) used by the USDM accurately classify drought severity. This study uses the SPI based on PRISM precipitation data from 1900 to 2015 to evaluate drought severity in Texas, Oklahoma, and Kansas. The results show that the fixed SPI thresholds for the USDM drought categories may lead to a systematic underestimation of drought severity in arid regions. To address this issue, objective drought thresholds were developed at each location by fitting a cumulative distribution function at each location to ensure that the observed frequency of drought in each severity category (D0–D4) matched the theoretical expectations of the USDM. This approach reduces the systematic biases in drought severity across the western portion of the study region. Therefore, we recommend developing objective drought thresholds for each location and SPI time scale (e.g., 1, 3, and 6 months). This method can be used to develop objective drought thresholds for any drought index and climate region of interest. [ABSTRACT FROM AUTHOR]

While CMIP5 models robustly project drying of the subtropics and more precipitation in the tropics and subpolar latitudes by the end of the century, the magnitude of these changes in precipitation varies widely across models: for example, some models simulate no drying in the eastern Mediterranean while others simulate more than a 50% reduction in precipitation relative to the model-simulated present-day value. Furthermore, the factors leading to changes in local subtropical precipitation remain unclear. The importance of zonal-mean changes in atmospheric structure for local precipitation changes is explored in 42 CMIP5 models. It is found that up to half of the local intermodel spread over the Mediterranean, northern Mexico, East Asia, southern Africa, southern Australia, and southern South America is related to the intermodel spread in large-scale processes such as the magnitude of globally averaged surface temperature increases, Hadley cell widening, polar amplification, stabilization of the tropical upper troposphere, or changes in the polar stratosphere.Globally averaged surface temperature increases account for intermodel spread in land subtropical drying in the Southern Hemisphere but are not important for land drying adjacent to the Mediterranean. The factors associated with drying over the eastern Mediterranean and westernMediterranean differ, with stabilization of the tropical upper troposphere being a crucial factor for the former only. Differences in precipitation between the western and eastern Mediterranean are also evident on interannual time scales. In contrast, the global factors examined here are unimportant over most of the United States, and more generally over the interior of continents. Much of the rest of the spread can be explained by variations in local relative humidity, a proxy also for zonally asymmetric circulation and thermodynamic changes. [ABSTRACT FROM AUTHOR]

Evaporation plays an extremely important role in determining summertime surface temperature variability over land. Observations show the relationship between evaporation and soil moisture generally conforms to the Budyko "two regime" framework; namely, that evaporation is limited by available soil moisture in dry climates and by radiation in wet climates. This framework has led climate models to different parameterizations of the relationship between evaporation and soil moisture in wet and dry regions. We have developed the Simple Land–Atmosphere Model (SLAM) as a tool for studying land–atmosphere interaction in general, and summertime temperature variability in particular. We use the SLAM to show that a negative feedback between evaporation and surface temperature gives rise to the two apparent evaporation "regimes" and provide analytic solutions for evaporative cooling anomalies that demonstrate the nonlinear impact of soil moisture perturbations. Stemming from the temperature dependence of vapor pressure deficit, the feedback we identify has important implications for how transitions between wet and dry land surfaces may impact temperature variability as the climate warms. We also elucidate the impacts of surface moisture and insolation perturbations on latent and sensible heat fluxes and on surface temperature variability. [ABSTRACT FROM AUTHOR]

A series of idealized prescribed soil moisture experiments is performed with the atmosphere/land stand-alone configuration of the Community Earth System Model, version 1, in an effort to find sources of predictability for high-impact stationary wave anomalies observed in recent boreal summers. We arbitrarily prescribe soil water to have a zero value at selected domains in the continental United States and run 100-member ensembles to examine the monthly and seasonal mean response. Contrary to the lack of a substantial response in the boreal winter, the summertime circulation response is robust, consistent, and circumglobal. While the stationary wave response over the North America and North Atlantic sectors can be well explained by the reaction of a linear dynamical system to heating anomalies caused by the imposed dry land surface, nonlinear processes involving synoptic eddies play a crucial role in forming the remote response in Eurasia and the North Pacific Ocean. A number of other possible factors contributing to the circulation responses are also discussed. Overall, the experiments suggest that, in the boreal summer, soil moisture may contribute to the predictability of high-impact stationary wave events, which can impact regions that are great distances from these source regions. [ABSTRACT FROM AUTHOR]

Flash flooding in the arid/semiarid southwestern United States is frequently associated with convective rainfall during the North American monsoon. In this study, we examine flood-producing storms in central Arizona based on analyses of dense rain gauge observations and stream gauging records as well as North American Regional Reanalysis fields. Our storm catalog consists of 102 storm events during the period of 1988-2014. Synoptic conditions for flood-producing storms are characterized based on principal component analyses. Four dominant synoptic modes are identified, with the first two modes explaining approximately 50% of the variance of the 500-hPa geopotential height. The transitional synoptic pattern from the North American monsoon regime to midlatitude systems is a critical large-scale feature for extreme rainfall and flooding in central Arizona. Contrasting spatial rainfall organizations and storm environment under the four synoptic modes highlights the role of interactions among synoptic conditions, mesoscale processes, and complex terrains in determining space-time variability of convective activities and flash flood hazards in central Arizona. We characterize structure and evolution properties of flood-producing storms based on storm tracking algorithms and 3D radar reflectivity. Fast-moving storm elements can be important ingredients for flash floods in the arid/semiarid southwestern United States. Contrasting storm properties for cloudburst storms highlight the wide spectrum of convective intensities for extreme rain rates in the arid/semiarid southwestern United States and exhibit comparable vertical structures to their counterparts in the eastern United States. [ABSTRACT FROM AUTHOR]

Evapotranspiration (ET) estimation is important for water management decision tools. In this study, different ET data with varying resolution, accuracy, and functionality were reviewed over a semiarid, data-sparse region in southern Iran. Study results showed that the widely used reanalysis and Moderate Resolution Imaging Spectroradiometer (MODIS) datasets have relatively high uncertainty and underestimated ET over the sparse heterogeneous landscape. On the other hand, fine-resolution ET datasets using Landsat imagery with Mapping Evapotranspiration at High Resolution with Internalized Calibration (METRIC) and Surface Energy Balance System (SEBS) algorithms, yielded high accuracy. Evaluation of METRIC and SEBS models in estimating seasonal crop water use showed a mean absolute error of 5% and 13%, respectively. The Satellite Application Facility on Climate Monitoring (CMSAF) data were used as radiation input to the models and were found to be a representative data source with daily average RMSE of 70 W m−2. An average crop coefficient Kc was estimated for the region and was obtained as 0.77. The study proposes and applies a hybrid framework that uses reference ET from simple diagnostic models (such as the REF-ET tool) and calculates actual ET by using the satellite-derived regionally and locally representative Kc values. The ET estimates generated with the framework were regionally representative and required low computational resources. The study findings have the potential to provide practical guidance to local farmers and water managers to generate useful and usable decision-making tools, especially for ET assessments in the study region and other data-sparse areas. [ABSTRACT FROM AUTHOR]

While vapor condensation in arid and semiarid areas has garnered much attention, such information is scarce for humid crop production areas such as rice fields. In a water-saving irrigation (WSI) rice field, high-precision weighed microlysimeters allowed the direct and independent quantification of condensation over plants (Cc) and soil (Cs) through mass balance calculations. The occurrence frequency and rate of Cc generally exceeded that of Cs. Predominantly occurring between sunset and sunrise, particularly between 0400 and 0500 local time, Cc showed an overall maximum rate of 0.096 mm h−1. In contrast, Cs was highest between 0100 and 1100 local time and showed an overall maximum rate of 0.044 mm h−1. The occurrence of Cc, unlike that of Cs, required a surface temperature lower than the ambient temperature or dewpoint. Of 65 rain-free days, Cc and Cs occurred on 60 and 33 days, respectively. Seasonal Cc, Cs, and Cc + Cs were estimated as 32.3, 3.1, and 35.4 mm, respectively, and their contributions to seasonal rice transpiration T, evaporation E, and evapotranspiration (ET) were 9.5%, 1.6%, and 6.7%, respectively. The seasonal Cc + Cs was similar in magnitude to a routine irrigation quota and accounted for 10.8% of rainfall and 14.4% of irrigation in the WSI rice field. Therefore, vapor condensation in rice fields in a subtropical monsoon climate is an important component of the hydrological cycle and cannot be ignored when tabulating the field water balance, calculating field water consumption, or in irrigation scheduling. [ABSTRACT FROM AUTHOR]

Rainfall in the Levant drylands is scarce but can potentially generate high-magnitude flash floods. Rainstorms are caused by distinct synoptic-scale circulation patterns: Mediterranean cyclone (MC), active Red Sea trough (ARST), and subtropical jet stream (STJ) disturbances, also termed tropical plumes (TPs). The unique spatiotemporal characteristics of rainstorms and floods for each circulation pattern were identified. Meteorological reanalyses, quantitative precipitation estimates from weather radars, hydrological data, and indicators of geomorphic changes from remote sensing imagery were used to characterize the chain of hydrometeorological processes leading to distinct flood patterns in the region. Significant differences in the hydrometeorology of these three flood-producing synoptic systems were identified: MC storms draw moisture from the Mediterranean and generate moderate rainfall in the northern part of the region. ARST and TP storms transfer large amounts of moisture from the south, which is converted to rainfall in the hyperarid southernmost parts of the Levant. ARST rainfall is local and intense, whereas TP rainfall is widespread and prolonged due to high precipitation efficiency and large-scale forcing. Thus, TP rainfall generates high-magnitude floods in the largest catchments; integration of numerous basins leads to sediment feeding from the south into the Dead Sea, exhibited in large sediment plumes. Anecdotal observations of the channel with the largest catchment in the region (Nahal HaArava) indicate that TP floods account for noticeable geomorphic changes in the channel. It provides insights into past intervals of increased flash flood frequency characterized by episodes of marked hydrogeomorphic work; such an increase is especially expected during intervals of southerly situated and southwesterly oriented STJs. [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]

The 2011-16 California drought illustrates that drought-prone areas do not always experience relief once a favorable phase of El Niño-Southern Oscillation (ENSO) returns. In the twenty-first century, such an expectation is unrealistic in regions where global warming induces an increase in terrestrial aridity larger than the changes in aridity driven by ENSO variability. This premise is also flawed in areas where precipitation supply cannot offset the global warming-induced increase in evaporative demand. Here, atmosphere-only experiments are analyzed to identify land regions where aridity is currently sensitive to ENSO and where projected future changes in mean aridity exceed the range caused by ENSO variability. Insights into the drivers of these changes in aridity are obtained using simulations with the incremental addition of three different factors to the current climate: ocean warming, vegetation response to elevated CO2 levels, and intensified CO2 radiative forcing. The effect of ocean warming overwhelms the range of ENSO-driven temperature variability worldwide, increasing potential evapotranspiration (PET) in most ENSO-sensitive regions. Additionally, about 39% of the regions currently sensitive to ENSO will likely receive less precipitation in the future, independent of the ENSO phase. Consequently aridity increases in 67%-72% of the ENSO-sensitive area. When both radiative and physiological effects are considered, the area affected by arid conditions rises to 75%-79% when using PET-derived measures of aridity, but declines to 41% when an aridity indicator for total soil moisture is employed. This reduction mainly occurs because plant stomatal resistance increases under enhanced CO2 concentrations, resulting in improved plant water-use efficiency, and hence reduced evapotranspiration and soil desiccation. Imposing CO2-invariant stomatal resistance may overestimate future drying in PET-derived indices. [ABSTRACT FROM AUTHOR]

The authors suggest an approach to analyze the effects of small-scale afforestation on the surrounding climate of a large heterogenic area. While simple statistics have difficulty identifying the effect, here a well-known eigenvector technique is used to overcome several specific challenges that result from a limited research region, complex topography, and multiple atmospheric circulation patterns. This approach is applied to investigate the influence of the isolated Yatir forest, at the north edge of Israel's Negev Desert. It was found that this forest does influence the daily climate, primarily seen in the main pattern of the empirical orthogonal function (EOF) of temperature and humidity. The EOF explains 93% and 80%, respectively, of the total variance in the data. Although the Yatir forest is small, it is significant in regulating the climate in the nearby surroundings, as it is located in a sharp transition area toward an arid climate. The results are presented as maps of correlation and regression between the normalized principal component time series of each pattern as well as other time series of the raw data and spatially interpolated data stations. Analysis of short-term campaign measurements around the Yatir forest supports the EOF results, and shows the forest's influence to the south, mainly during nighttime when the forest becomes cooler than its surroundings. Overall, results suggest that in areas of transition to semiarid climates, forests regulate the surrounding surface air temperature and humidity fields. Wind analysis based on a complex EOF technique reveals the pattern of the daily cycle of surface wind over the region. [ABSTRACT FROM AUTHOR]

Arid extratropical Asia (AEA) is bisected at the wetter Tian Shan (a northern offshoot of the Tibetan Plateau) into east and west deserts, each with unique climatological characteristics. The east deserts (~35°-55°N, ~75°-115°E) have a summer precipitation maximum, and the west deserts (~35°-55°N, ~45°-75°E) have a winter-spring precipitation maximum. A new high-resolution (50 km atmosphere-land) global coupled climate model is run with the Tian Shan removed to determine whether these mountains are responsible for the climatological east-west differentiation of AEA. Multicentennial simulations for the Control and NoTianshan runs highlight statistically significant effects of the Tian Shan. Overall, the Tian Shan are found to enhance the precipitation seasonality gradient across AEA, mostly through altering the east deserts. The Tian Shan dramatically change the precipitation seasonality of the Taklimakan Desert directly to its east (the driest part of AEA) by blocking west winter precipitation, enhancing subsidence over this region, and increasing east summer precipitation. The Tian Shan increase east summer precipitation through two mechanisms: 1) orographic precipitation, which is greatest on the eastern edge of the Tian Shan in summer, and 2) remote enhancement of the East Asian summer monsoon through alteration of the larger-scale seasonal mean atmospheric circulation. The decrease in east winter precipitation also generates remote warming of the Altai and Kunlun Shan, mountains northeast and southeast of the Tian Shan, respectively, due to reduction of snow cover and corresponding albedo decrease. [ABSTRACT FROM AUTHOR]

Precipitation and soil moisture are rigorously measured or estimated from a variety of sources. Here, 22 precipitation and 23 soil moisture products are evaluated against long-term daily observed precipitation (Pobs) and July-September daily observationally constrained soil moisture (SM) datasets over a densely monitored 150 km2 watershed in southeastern Arizona, United States. Gauge-radar precipitation products perform best, followed by reanalysis and satellite products, and the median correlations of annual precipitation from these three categories with Pobs are 0.83, 0.68, and 0.46, respectively. Precipitation results from phase 5 of the Coupled Model Intercomparison Project (CMIP5) are the worst, including an overestimate of cold season precipitation and a lack of significant correlation of annual precipitation with Pobs from all (except one) models. Satellite soil moisture products perform best, followed by land data assimilation systems and reanalyses, and the CMIP5 results are the worst. For instance, the median unbiased root-mean-square difference (RMSD) values of July-September soil moisture compared with SM are 0.0070, 0.011, 0.014, and 0.029 m3 m−3 for these four product categories, respectively. All 17 (except 3) precipitation [17 (except 2) soil moisture] products with at least 20 years of data agree with Pobs (SM) without significant trends. The uncertainties associated with the scale mismatch between Pobs and coarser-resolution products are addressed using two 4-km gauge-radar precipitation products, and their impact on the results presented in this study is overall small. These results identify strengths and weaknesses of each product for future improvement; they also emphasize the importance of using multiple gauge-radar and satellite products along with their uncertainties in evaluating reanalyses and models. [ABSTRACT FROM AUTHOR]

Arid and semiarid lowland areas of central Asia are largely dependent on fluvial water originating from the Tian Shan. Mountain glaciers contribute significantly to runoff, particularly in summer. With global warming, the total glacier area in the Kunma Like River catchment declined by 13.2% during 1990-2007. For future water resources, it is essential to quantify the responses of hydrologic processes to both climate change and shrinking glaciers in glacierized catchments, such as the headwaters of the Tarim River. Thus, a degree-day glacier melt algorithm was integrated into the macroscale hydrologic Variable Infiltration Capacity model (VIC). Good results were obtained for monthly runoff simulations in the Kunma Like River catchment, which suggest that the extended VIC has acceptable performance. Because of increased precipitation and air temperature, annual runoff in the catchment has increased by about 4.07 × 108 m3 decade−1 during 1984/85-2006/07. Under the assumption of the same climatic conditions, sensitivity analyses indicated that annual and summer river runoff volumes would decrease by 9.3% and 10.4%, respectively, for reductions in glacier area of 13.2%. The variation coefficient of annual runoff also increased because of shrinking glaciers. Runoff scenarios for warmer future climate and various deglaciation situations suggest that reductions in glacier area by >30% will likely produce less meltwater in summer and river runoff will decline. Consequently, the annual total discharge of the Kunma Like River is projected to decrease by 2.8%-19.4% in the 2050s scenario because of glacier shrinking. [ABSTRACT FROM AUTHOR]

The aridity of a terrestrial climate is often quantified using the dimensionless ratio of annual precipitation ( P) to annual potential evapotranspiration (PET). In this study, the climatological patterns and greenhouse warming responses of terrestrial P, Penman-Monteith PET, and are compared among 16 modern global climate models. The large-scale climatological values and implied biome types often disagree widely among models, with large systematic differences from observational estimates. In addition, the PET climatologies often differ by several tens of percent when computed using monthly versus 3-hourly inputs. With greenhouse warming, land P does not systematically increase or decrease, except at high latitudes. Therefore, because of moderate, ubiquitous PET increases, decreases (drying) are much more widespread than increases (wetting) in the tropics, subtropics, and midlatitudes in most models, confirming and expanding on earlier findings. The PET increases are also somewhat sensitive to the time resolution of the inputs, although not as systematically as for the PET climatologies. The changes in the balance between P and PET are also quantified using an alternative aridity index, the ratio , which has a one-to-one but nonlinear correspondence with . It is argued that the magnitudes of changes are more uniformly relevant than the magnitudes of changes, which tend to be much higher in wetter regions. The ratio and its changes are also found to be excellent statistical predictors of the land surface evaporative fraction and its changes. [ABSTRACT FROM AUTHOR]

The challenges of monitoring and forecasting flash-flood-producing storm events in data-sparse and arid regions are explored using the Weather Research and Forecasting (WRF) Model (version 3.5) in conjunction with a range of available satellite, in situ, and reanalysis data. Here, we focus on characterizing the initial synoptic features and examining the impact of model parameterization and resolution on the reproduction of a number of flood-producing rainfall events that occurred over the western Saudi Arabian city of Jeddah. Analysis from the European Centre for Medium-Range Weather Forecasts (ECMWF) interim reanalysis (ERA-Interim) data suggests that mesoscale convective systems associated with strong moisture convergence ahead of a trough were the major initial features for the occurrence of these intense rain events. The WRF Model was able to simulate the heavy rainfall, with driving convective processes well characterized by a high-resolution cloud-resolving model. The use of higher (1 km vs 5 km) resolution along the Jeddah coastline favors the simulation of local convective systems and adds value to the simulation of heavy rainfall, especially for deep-convection-related extreme values. At the 5-km resolution, corresponding to an intermediate study domain, simulation without a cumulus scheme led to the formation of deeper convective systems and enhanced rainfall around Jeddah, illustrating the need for careful model scheme selection in this transition resolution. In analysis of multiple nested WRF simulations (25, 5, and 1 km), localized volume and intensity of heavy rainfall together with the duration of rainstorms within the Jeddah catchment area were captured reasonably well, although there was evidence of some displacements of rainstorm events. [ABSTRACT FROM AUTHOR]

Water managers across the United States face the need to make informed policy decisions regarding long-term impacts of climate change on water resources. To provide a scientifically informed basis for this, the evolution of important components of the basin-scale water balance through the end of the twenty-first century is estimated. Bias-corrected and spatially downscaled climate projections, from phase 3 of the Coupled Model Intercomparison Project (CMIP3) of the World Climate Research Programme, were used to drive a spatially distributed Variable Infiltration Capacity (VIC) model of hydrologic processes in the Salt-Verde basin in the southwestern United States. From the suite of CMIP3 models, the authors select a five-model subset, including three that best reproduce the historical climatology for the study region, plus two others to represent wetter and drier than model average conditions, so as to represent the range of GCM prediction uncertainty. For each GCM, data for three emission scenarios (A1B, A2, and B1) were used to drive the hydrologic model into the future. The projections of this model ensemble indicate a statistically significant 25% decrease in streamflow by the end of the twenty-first century. The primary cause for this change is due to projected decreases in winter precipitation accompanied by significant (temperature driven) reductions in storage of snow and increased winter evaporation. The results show that water management in central Arizona is highly likely to be impacted by changes in regional climate. [ABSTRACT FROM AUTHOR]

This study analyzed uncertainties and correlations over the United States among four ensemble-mean North American Land Data Assimilation System (NLDAS) percentile-based drought indices derived from monthly mean evapotranspiration ET, total runoff Q, top 1-m soil moisture SM1, and total column soil moisture SMT. The results show that the uncertainty is smallest for SM1, largest for SMT, and moderate for ET and Q. The strongest correlation is between SM1 and SMT, and the weakest correlation is between ET and Q. The correlation between ET and SM1 (SMT) is strongest in arid-semiarid regions, and the correlation between Q and SM1 (SMT) is strongest in more humid regions in the Pacific Northwest and the Southeast. Drought frequency analysis shows that SM1 has the most frequent drought occurrence, followed by SMT, Q, and ET. The study compared the NLDAS drought indices (a research product) with the U.S. Drought Monitor (USDM; an operational product) in terms of drought area percentage derived from each product. It proposes an optimal blend of NLDAS drought indices by searching for weights for each index that minimizes the RMSE between NLDAS and USDM drought area percentage for a 10-yr period (2000-09) with a cross validation. It reconstructed a 30-yr (1980-2009) Objective Blended NLDAS Drought Index (OBNDI) and monthly drought percentage. Overall, the OBNDI performs the best with the smallest RMSE, followed by SM1 and SMT. It should be noted that the contribution to OBNDI from different variables varies with region. So a single formula is probably not the best representation of a blended index. The representation of a blended index using the multiple formulas will be addressed in a future study. [ABSTRACT FROM AUTHOR]

Weather Research and Forecasting Model forecasts over the Great Salt Lake Desert erroneously underpredict nocturnal cooling over the sparsely vegetated silt loam soil area of Dugway Proving Ground in northern Utah, with a mean positive bias error in temperature at 2 m AGL of 3.4°C in the early morning [1200 UTC (0500 LST)]. Positive early-morning bias errors also exist in nearby sandy loam soil areas. These biases are related to the improper initialization of soil moisture and parameterization of soil thermal conductivity in silt loam and sandy loam soils. Forecasts of 2-m temperature can be improved by initializing with observed soil moisture and by replacing Johansen's 1975 parameterization of soil thermal conductivity in the Noah land surface model with that proposed by McCumber and Pielke in 1981 for silt loam and sandy loam soils. Case studies illustrate that this change can dramatically reduce nighttime warm biases in 2-m temperature over silt loam and sandy loam soils, with the greatest improvement during periods of low soil moisture. Predicted ground heat flux, soil thermal conductivity, near-surface radiative fluxes, and low-level thermal profiles also more closely match observations. Similar results are anticipated in other dryland regions with analogous soil types, sparse vegetation, and low soil moisture. [ABSTRACT FROM AUTHOR]

Drier future conditions are projected for the arid southwest of North America, increasing the chances of the region experiencing severe and prolonged drought. To examine the mechanisms of decadal variability, 47 global climate model historical simulations performed for phase 5 of the Coupled Model Intercomparison Project (CMIP5) were assessed. On average, the CMIP5 models have higher climatological precipitation over the past century in southwestern North America than current instrumental or reanalysis products. The timing of the winter peak in climatological precipitation over California and Nevada is accurately represented. Models with resolutions coarser than 2° show a larger spread in the location and strength of the North American monsoon ridge and subsequent summer precipitation, in comparison with the higher-resolution models. Less than 20% of decadal variability in wintertime precipitation over California is associated with North Pacific sea surface temperature anomalies, a larger proportion than is associated with the tropical forcing but not sufficient for making decadal drought predictions. North American monsoon precipitation is strongly associated with local land temperatures on interannual-to-decadal time scales attributable to evaporative cooling and radiation changes driven by varying cloud cover. Soil moisture in Texas and Oklahoma in April is shown to be positively correlated with monsoon precipitation for the following summer, indicating a potential source of nonoceanic interseasonal persistence in southwestern North American hydroclimate. To make meaningful decadal predictions in the future, it is likely that forecasting will move away from sea surface temperature-driven anomaly patterns, and focus on land surface processes, which can allow persistence of precipitation anomalies via feedbacks. [ABSTRACT FROM AUTHOR]

In this study, a Lagrangian particle dispersion model, Flexible Particle (FLEXPART), is employed to simulate the trajectories of global air parcels during 2000-09 with the purpose of revealing the moisture sources of the semiarid grasslands of China, especially on precipitation days. Based on land-cover and precipitation data, two areas of semiarid grasslands are identified: one in North China and one in the Tibetan Plateau. Using the FLEXPART simulation results, air parcels reaching these two target regions are traced back for 10 days to examine their temporal variations in position (longitude, latitude, and altitude) and specific humidity. The moisture sources of these semiarid grasslands are discussed for different precipitation categories. Moreover, the contributions of different moisture sources to the precipitation in the target regions are computed and compared. The results indicate that the moisture released in the target regions is substantially from the Eurasian continent, in both summer and winter. During May-September, the southern and eastern adjacent land areas seem to be the main moisture sources of rainfall in the grasslands of North China, while the Eurasian continent on the north and west tends to be the predominant contributor to the rainfall over the grasslands of the eastern Tibetan Plateau. During October-April, moistures released in both target regions principally originate from the Eurasian continent on the north and west. Overall, although the moisture uptake over oceanic sources is also considerable, most released moisture over the target regions is from the Eurasian continent throughout the year, while little of the contribution of oceanic sources is due to great loss of moisture en route. [ABSTRACT FROM AUTHOR]

The reliability of predictions from climate and weather models is linked to an adequate representation of the land surface processes. To evaluate performance and to improve predictions, land surface models are calibrated against observed data. Despite an extensive literature describing methods of land surface model calibration, few studies have applied a calibration method for semiarid natural vegetation, especially for the semiarid northeast of Brazil, which presents caatinga as its natural vegetation. Caatinga is a highly dynamic ecosystem with the physics at the land surface-atmosphere interface still poorly understood. Therefore, in this study a multiobjective hierarchical method, which provides means to estimate optimal values of the model parameters through calibration, is evaluated. This method is applied to caatinga by using the Integrated Biosphere Simulator (IBIS). Results demonstrated that the calibrated set of vegetation parameters produced a considerably different energy balance from the default parameters. In general, the model was able to simulate the partition of the available energy into sensible and latent heat fluxes when the calibrated parameters were used. The IBIS model was not able to capture short-term, intense changes in latent heat flux from a dry condition to a wetter condition, however, even when the new set of calibrated parameters was used. Therefore, the parameter optimization may not be sufficient if processes are missing or misrepresented. This study is one of the first to understand the physics at the land surface-atmosphere interface in the caatinga ecosystem and to evaluate the ability of the IBIS model to represent the biophysical interactions in this important ecosystem. [ABSTRACT FROM AUTHOR]

Accurate prediction of evapotranspiration E depends upon representative characterization of meteorological conditions in the boundary layer. Drag and bulk transfer coefficient schemes for estimating aerodynamic resistance to vapor transfer were compared over a semiarid natural woodland ecosystem in central Australia. Aerodynamic resistance was overestimated from the drag coefficient, resulting in limited E at intermediate values of vapor pressure deficit. Large vertical humidity gradients were present during the summer, causing divergence between momentum and vapor transport within and above the canopy surface. Because of intermittency in growth of the summer-active, rain-dependent understory and physiological responses of the canopy, leaf resistance varied from less than 50 s m−1 to greater than 106 s m−1, in which the particularly large values were obtained from inversion of drag coefficient resistance. Soil moisture limitations further contributed to divergence between actual and reference E. Unsurprisingly, inclusion of site-specific meteorological (e.g., vertical humidity gradients) and hydrological (e.g., soil moisture content) information improved the accuracy of predicting E when applying Penman-Monteith analysis. These results apply regardless of canopy layering (i.e., even when the understory was not present) wherever atmospheric humidity gradients develop and are thus not restricted to two-layer canopies in semiarid regions. [ABSTRACT FROM AUTHOR]

Estimating evapotranspiration using the complementary relationship can serve as a proxy to more sophisticated physically based approaches and can be used to better understand water and energy budget feedbacks. The authors investigated the existence of complementarity between actual evapotranspiration (ET) and potential ET (ET p) over natural vegetation in semiarid desert ecosystems of southern Idaho using only the forcing data and simulated fluxes obtained from Noah land surface model (LSM) and North American Regional Reanalysis (NARR) data. To mitigate the paucity of long-term meteorological data, the Noah LSM-simulated fluxes and the NARR forcing data were used in the advection-aridity (AA) model to derive the complementary relationship (CR) for the sagebrush and cheatgrass ecosystems. When soil moisture was a limiting factor for ET, the CR was stable and asymmetric, with b values of 2.43 and 1.43 for sagebrush and cheatgrass, respectively. Higher b values contributed to decreased ET and increased ET p, and as a result ET from the sagebrush community was less compared to that of cheatgrass. Validation of the derived CR showed that correlations between daily ET from the Noah LSM and CR-based ET were 0.76 and 0.80 for sagebrush and cheatgrass, respectively, while the root-mean-square errors were 0.53 and 0.61 mm day−1. [ABSTRACT FROM AUTHOR]

The rain gauge network associated with the Walnut Gulch Experimental Watershed (WGEW) in southeastern Arizona provides a unique opportunity for direct comparisons of in situ measurements and satellite-based instantaneous rain rate estimates like those from the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR). The WGEW network is the densest rain gauge network in the PR coverage area for watersheds greater than 10 km2. It consists of 88 weighing rain gauges within a 149-km2 area. On average, approximately 10 gauges can be found in each PR field of view (~5-km diameter). All gauges are very well synchronized with 1-min reporting intervals. This allows generating very-high-temporal-resolution rain rate fields and obtaining accurate estimates of the area-average rain rate for the entire watershed and for a single PR field of view. In this study, instantaneous rain rate fields from the PR and the spatially interpolated gauge measurements (on a 100 m × 100 m grid, updated every 1 min) are compared for all TRMM overpasses in which the PR recorded rain within the WGEW boundaries (25 overpasses during 1999-2010). The results indicate very good agreement between the fields with low bias values (<10%) and high correlation coefficients, especially for the near-nadir cases (>0.9). The correlation is high at overpass time but the peak occurs several minutes after the overpass, which can be explained by the fact that it takes several minutes for the raindrops to reach the gauge from the time they are observed by the PR. The correlation improves with the new version of the TRMM algorithm (V7). The study includes assessment of the accuracy of the reference products. [ABSTRACT FROM AUTHOR]