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Past work has shown that a land surface model's (LSM) implicit (not explicitly coded) relationships between soil moisture and both evapotranspiration (ET) and runoff largely determine the LSM's hydrological behavior. Here we estimate the relationships that appear to be operating in the real world and compare them to those of the LSM component of a state-of-the-art Earth system model (ESM). The two sets of relationships are determined by calibrating them within a simple water balance model (WBM): once using stream gauge observations from small, unregulated rivers over the eastern half of the United States, and once using the runoffs generated by the LSM as part of a state-of-the-art atmospheric reanalysis. Hydrological simulations and subseasonal hydrological forecasts performed with the two calibrated versions of the WBM provide two key results. First, the version calibrated to the LSM-generated runoffs does successfully reproduce, to first order, the hydrological behavior of the full LSM within its ESM environment. Second, of the two WBM versions, the one calibrated to the observations reproduces more accurately a broad collection of fully independent streamflow observations as well as a similarly broad collection of in situ soil moisture measurements. Taken together, the two results suggest that the observations-calibrated ET and runoff efficiency functions do successfully represent, at least to some degree, soil moisture controls over hydrological variability in nature and can serve as potentially useful targets for further LSM development. Significance Statement: For all their complexity, and for all the work that underlies their development, the land surface model components of Earth system models may be suboptimal in fundamental yet unstudied ways. Here we estimate how the joint control of soil moisture over evapotranspiration and runoff processes in nature differs from that built implicitly into a state-of-the-art land model. Validation exercises demonstrate how this difference appears to lead to reduced accuracy in the land model's simulation and forecasting of such hydrological variables as streamflow and soil moisture. Our results indicate that the relationships estimated for nature could serve as a potentially valuable target for further land model development. [ABSTRACT FROM AUTHOR]

For ∼100 years, the continental patterns of avian migration in North America have been described in the context of three or four primary flyways. This spatial compartmentalization often fails to adequately reflect a critical characterization of migration—phenology. This shortcoming has been partly due to the lack of reliable continental-scale data, a gap filled by our current study. Here, we leveraged unique radar-based data quantifying migration phenology and used an objective regionalization approach to introduce a new spatial framework that reflects interannual variability. Therefore, the resulting spatial classification is intrinsically different from the "flyway concept." We identified two regions with distinct interannual variability of spring migration across the contiguous United States. This data-driven framework enabled us to explore the climatic cues affecting the interannual variability of migration phenology, "specific to each region" across North America. For example, our "two-region" approach allowed us to identify an east–west dipole pattern in migratory behavior linked to atmospheric Rossby waves. Also, we revealed that migration movements over the western United States were inversely related to interannual and low-frequency variability of regional temperature. A similar link, but weaker and only for interannual variability, was evident for the eastern region. However, this region was more strongly tied to climate teleconnections, particularly to the east Pacific–North Pacific (EP–NP) pattern. The results suggest that oceanic forcing in the tropical Pacific—through a chain of processes including Rossby wave trains—controls the climatic conditions, associated with bird migration over the eastern United States. Our spatial platform would facilitate better understanding of the mechanisms responsible for broadscale migration phenology and its potential future changes. [ABSTRACT FROM AUTHOR]

Soil moisture (W) helps control evapotranspiration (ET), and ET variations can in turn have a distinct impact on 2-m air temperature (T2M), given that increases in evaporative cooling encourage reduced temperatures. Soil moisture is accordingly linked to T2M, and realistic soil moisture initialization has, in previous studies, been shown to improve the skill of subseasonal T2M forecasts. The relationship between soil moisture and evapotranspiration, however, is distinctly nonlinear, with ET tending to increase with soil moisture in drier conditions and to be insensitive to soil moisture variations in wetter conditions. Here, through an extensive analysis of subseasonal forecasts produced with a state-of-the-art seasonal forecast system, this nonlinearity is shown to imprint itself on T2M forecast error in the conterminous United States in two unique ways: (i) the T2M forecast bias (relative to independent observations) induced by a negative precipitation bias tends to be larger for dry initializations, and (ii) on average, the unbiased root-mean-square error (ubRMSE) tends to be larger for dry initializations. Such findings can aid in the identification of forecasts of opportunity; taken a step further, they suggest a pathway for improving bias correction and uncertainty estimation in subseasonal T2M forecasts by conditioning each on initial soil moisture state. Significance Statement: Not all forecasts are created equal. Even before a given forecast is produced, the nature of its initial conditions may indicate that it will prove more accurate than corresponding forecasts started at other times. We address here how the character of the soil moisture at the beginning of a forecast may provide such information. We find that under certain conditions, when the initial state of the soil is wet, the bias in the forecast is reduced and, to a lesser extent, the random error in the forecast is also reduced. Knowing ahead of time when to put more trust into a forecast should be of substantial benefit to forecast end-users. [ABSTRACT FROM AUTHOR]

Heat waves are extreme climate events that have the potential to cause immense stress on human health, agriculture, and energy systems, so understanding the processes leading to their onset is crucial. There is no single accepted definition for heat waves, but they are generally described as a sustained amount of time over which temperature exceeds a local threshold. Multiple different temperature variables are potentially relevant, because high values of both daily maximum and minimum temperatures can be detrimental to human health. In this study, we focus explicitly on the different mechanisms associated with summertime heat waves manifested during daytime hours versus nighttime hours over the contiguous United States. Heat waves are examined using the National Aeronautics and Space Administration Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2). Over 1980–2018, the increase in the number of heat-wave days per summer was generally stronger for nighttime heat-wave days than for daytime heat-wave days, with localized regions of significant positive trends. Processes linked with daytime and nighttime heat waves are identified through composite analysis of precipitation, soil moisture, clouds, humidity, and fluxes of heat and moisture. Daytime heat waves are associated with dry conditions, reduced cloud cover, and increased sensible heating. Mechanisms leading to nighttime heat waves differ regionally across the United States, but they are typically associated with increased clouds, humidity, and/or low-level temperature advection. In the midwestern United States, enhanced moisture is transported from the Gulf of Mexico during nighttime heat waves. [ABSTRACT FROM AUTHOR]

This study examines the causes and predictability of the spring 2011 U.S. extreme weather using the Modern-Era Retrospective Analysis for Research and Applications (MERRA) and Goddard Earth Observing System Model, version 5, (GEOS-5) atmospheric general circulation model simulations. The focus is on assessing the impact on precipitation of sea surface temperature (SST) anomalies, land conditions, and large-scale atmospheric modes of variability. A key result is that the April record-breaking precipitation in the Ohio River valley was primarily the result of the unforced development of a positive North Atlantic Oscillation (NAO)-like mode of variability with unusually large amplitude, limiting the predictability of the precipitation in that region at 1-month leads. SST forcing (La Niña conditions) contributed to the broader continental-scale pattern of precipitation anomalies, producing drying in the southern plains and weak wet anomalies in the northeast, while the impact of realistic initial North American land conditions was to enhance precipitation in the upper Midwest and produce deficits in the Southeast. It was further found that 1) the 1 March atmospheric initial condition was the primary source of the ensemble mean precipitation response over the eastern United States in April (well beyond the limit of weather predictability), suggesting an influence on the initial state of the previous SST forcing and/or tropospheric-stratospheric coupling linked to an unusually persistent and cold polar vortex; and 2) stationary wave model experiments suggest that the SST-forced base state for April enhanced the amplitude of the NAO response compared to that of the climatological state, though the impact is modest and can be of either sign. [ABSTRACT FROM AUTHOR]

The variability of Atlantic tropical cyclones (TCs) associated with El Niño-Southern Oscillation (ENSO) in model simulations is assessed and compared with observations. The model experiments are 28-yr simulations forced with the observed sea surface temperature from 1982 to 2009. The simulations were coordinated by the U.S. Climate Variability and Predictability Research Program (CLIVAR) Hurricane Working Group and conducted with five global climate models (GCMs) with a total of 16 ensemble members. The model performance is evaluated based on both individual model ensemble means and multimodel ensemble mean. The latter has the highest anomaly correlation (0.86) for the interannual variability of TCs. Previous observational studies show a strong association between ENSO and Atlantic TC activity, as well as distinctions during eastern Pacific (EP) and central Pacific (CP) El Niño events. The analysis of track density and TC origin indicates that each model has different mean biases. Overall, the GCMs simulate the variability of Atlantic TCs well with weaker activity during EP El Niño and stronger activity during La Niña. For CP El Niño, there is a slight increase in the number of TCs as compared with EP El Niño. However, the spatial distribution of track density and TC origin is less consistent among the models. Particularly, there is no indication of increasing TC activity over the U.S. southeast coastal region during CP El Niño as in observations. The difference between the models and observations is likely due to the bias of the models in response to the shift of tropical heating associated with CP El Niño, as well as the model bias in the mean circulation. [ABSTRACT FROM AUTHOR]

This study compares the extreme heat and drought that developed over the United States in 2011 and 2012 with a focus on the role of sea surface temperature (SST) forcing. Experiments with the NASA Goddard Earth Observing System, version 5 (GEOS-5), atmospheric general circulation model show that the winter/spring response over the United States to the Pacific SST is remarkably similar for the two years despite substantial differences in the tropical Pacific SST. As such, the pronounced winter and early spring temperature differences between the two years (warmth confined to the south in 2011 and covering much of the continent in 2012) primarily reflect differences in the contributions from the Atlantic and Indian Oceans, with both acting to cool the east and upper Midwest during 2011, while during 2012 the Indian Ocean reinforced the Pacific-driven, continental-wide warming and the Atlantic played a less important role. During late spring and summer of 2011, the tropical Pacific SST forced a continued warming and drying over the southern United States, though considerably weaker than observed. Nevertheless, the observed 2011 anomalies fall well within the model's intraensemble spread. In contrast, the observed rapid development of intense heat and drying over the central United States during June and July 2012 falls on the margins of the model's intraensemble spread, with the response to the SST giving little indication that 2012 would produce record-breaking precipitation deficits and heat. A diagnosis of the 2012 observed circulation anomalies shows that the most extreme heat and drought was tied to the development of a stationary Rossby wave and an associated anomalous upper-tropospheric high maintained by weather transients. [ABSTRACT FROM AUTHOR]

Weather and climate extremes have been varying and changing on many different time scales. In recent decades, heat waves have generally become more frequent across the United States, while cold waves have been decreasing. While this is in keeping with expectations in a warming climate, it turns out that decadal variations in the number of U.S. heat and cold waves do not correlate well with the observed U.S. warming during the last century. Annual peak flow data reveal that river flooding trends on the century scale do not show uniform changes across the country. While flood magnitudes in the Southwest have been decreasing, flood magnitudes in the Northeast and north-central United States have been increasing. Confounding the analysis of trends in river flooding is multiyear and even multidecadal variability likely caused by both large-scale atmospheric circulation changes and basin-scale "memory" in the form of soil moisture. Droughts also have long-term trends as well as multiyear and decadal variability. Instrumental data indicate that the Dust Bowl of the 1930s and the drought in the 1950s were the most significant twentieth-century droughts in the United States, while tree ring data indicate that the megadroughts over the twelfth century exceeded anything in the twentieth century in both spatial extent and duration. The state of knowledge of the factors that cause heat waves, cold waves, floods, and drought to change is fairly good with heat waves being the best understood. [ABSTRACT FROM AUTHOR]

An initialization strategy, tailored to the prediction of the Madden-Julian oscillation (MJO), is evaluated using the Goddard Earth Observing System Model, version 5 (GEOS-5), coupled general circulation model (CGCM). The approach is based on the empirical singular vectors (ESVs) of a reduced-space statistically determined linear approximation of the full nonlinear CGCM. The initial ESV, extracted using 10 years (1990-99) of boreal winter hindcast data, has zonal wind anomalies over the western Indian Ocean, while the final ESV (at a forecast lead time of 10 days) reflects a propagation of the zonal wind anomalies to the east over the Maritime Continent-an evolution that is characteristic of the MJO. A new set of ensemble hindcasts are produced for the boreal winter season from 1990 to 1999 in which the leading ESV provides the initial perturbations. The results are compared with those from a set of control hindcasts generated using random perturbations. It is shown that the ESV-based predictions have a systematically higher bivariate correlation skill in predicting the MJO compared to those using the random perturbations. Furthermore, the improvement in the skill depends on the phase of the MJO. The ESV is particularly effective in increasing the forecast skill during those phases of the MJO in which the control has low skill (with correlations increasing by as much as 0.2 at 20-25-day lead times), as well as during those times in which the MJO is weak. [ABSTRACT FROM AUTHOR]

This study examines the cause of the extreme snowstorm activity along the U.S. East Coast during the winter of 2009/10 with a focus on the role of sea surface temperature (SST) anomalies. The study employs the Goddard Earth Observing System, version 5 (GEOS-5) atmospheric general circulation model (AGCM) run at high resolution and forced with specified observed or idealized SST. Comparisons are made with the winter of 1999/2000, a period that is characterized by SST anomalies that are largely of opposite sign. When forced with observed SSTs, the AGCM response consists of a band of enhanced storminess extending from the central subtropical North Pacific, across the southern United States, across the North Atlantic, and across southern Eurasia, with reduced storminess to the north of these regions. Positive precipitation and cold temperature anomalies occur over the eastern United States, reflecting a propensity for enhanced snowstorm activity. Additional idealized SST experiments show that the anomalies over the United States are, to a large extent, driven by the ENSO-related Pacific SST. The North Atlantic SSTs contribute to the cooler temperatures along the East Coast of the United States, while the Indian Ocean SSTs act primarily to warm the central part of the country. It is further shown that the observed upper-tropospheric height anomalies have a large noise (unforced) component over the Northern Hemisphere, represented over the North Atlantic by a North Atlantic Oscillation (NAO)-like structure. The signal-to-noise ratios of the temperature and precipitation fields nevertheless indicate a potential for predicting the unusual storm activity along the U.S. East Coast several months in advance. [ABSTRACT FROM AUTHOR]

This study examines the nature of boreal summer subseasonal atmospheric variability based on the new NASA Modern-Era Retrospective Analysis for Research and Applications (MERRA) for the period 1979-2010. An analysis of the June, July, and August subseasonal 250-hPa meridional υυ-wind anomalies shows distinct Rossby wave-like structures that appear to be guided by the mean jets. On monthly subseasonal time scales, the leading waves [the first 10 rotated empirical orthogonal functions (REOFs) of the 250-hPa υυ wind] explain about 50%% of the Northern Hemisphere υυ-wind variability and account for more than 30%% (60%%) of the precipitation (surface temperature) variability over a number of regions of the northern middle and high latitudes, including the U.S. northern Great Plains, parts of Canada, Europe, and Russia. The first REOF in particular consists of a Rossby wave that extends across northern Eurasia where it is a dominant contributor to monthly surface temperature and precipitation variability and played an important role in the 2003 European and 2010 Russian heat waves. While primarily subseasonal in nature, the Rossby waves can at times have a substantial seasonal mean component. This is exemplified by REOF 4, which played a major role in the development of the most intense anomalies of the U.S. 1988 drought (during June) and the 1993 flooding (during July), though differed in the latter event by also making an important contribution to the seasonal mean anomalies. A stationary wave model (SWM) is used to reproduce some of the basic features of the observed waves and provide insight into the nature of the forcing. In particular, the responses to a set of idealized forcing functions are used to map the optimal forcing patterns of the leading waves. Also, experiments to reproduce the observed waves with the SWM using MERRA-based estimates of the forcing indicate that the wave forcing is dominated by submonthly vorticity transients. [ABSTRACT FROM AUTHOR]

The Modern-Era Retrospective Analysis for Research and Applications (MERRA) was undertaken by NASA''s Global Modeling and Assimilation Office with two primary objectives: to place observations from NASA''s Earth Observing System satellites into a climate context and to improve upon the hydrologic cycle represented in earlier generations of reanalyses. Focusing on the satellite era, from 1979 to the present, MERRA has achieved its goals with significant improvements in precipitation and water vapor climatology. Here, a brief overview of the system and some aspects of its performance, including quality assessment diagnostics from innovation and residual statistics, is given. By comparing MERRA with other updated reanalyses [the interim version of the next ECMWF Re-Analysis (ERA-Interim) and the Climate Forecast System Reanalysis (CFSR)], advances made in this new generation of reanalyses, as well as remaining deficiencies, are identified. Although there is little difference between the new reanalyses in many aspects of climate variability, substantial differences remain in poorly constrained quantities such as precipitation and surface fluxes. These differences, due to variations both in the models and in the analysis techniques, are an important measure of the uncertainty in reanalysis products. It is also found that all reanalyses are still quite sensitive to observing system changes. Dealing with this sensitivity remains the most pressing challenge for the next generation of reanalyses. Production has now caught up to the current period and MERRA is being continued as a near-real-time climate analysis. The output is available online through the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). [ABSTRACT FROM AUTHOR]

This study uses the NASA Seasonal-to-Interannual Prediction Project (NSIPP-1) AGCM to investigate the physical mechanisms by which the leading patterns of annual mean SST variability impact U.S. precipitation. The focus is on a cold Pacific pattern and a warm Atlantic pattern that exert significant drought conditions over the U.S. continent. The precipitation response to the cold Pacific is characterized by persistent deficits over the Great Plains that peak in summer with a secondary peak in spring, and weakly pluvial conditions in summer over the Southeast (SE). The precipitation response to the warm Atlantic is dominated by persistent deficits over the Great Plains with the maximum deficit occurring in late summer. The precipitation response to the warm Atlantic is overall similar to the response to the cold Pacific with, however, considerably weaker amplitude. An analysis of the atmospheric moisture budget combined with a stationary wave model diagnosis of the associated atmospheric circulation anomalies is conducted to investigate mechanisms of the precipitation responses. A key result is that, while the cold Pacific and warm Atlantic are two spatially distinct SST patterns, they nevertheless produce similar diabatic heating anomalies over the Gulf of Mexico during the warm season. In the case of the Atlantic forcing, the heating anomalies are a direct response to the SST anomalies, whereas in the case of Pacific forcing they are a secondary response to circulation anomalies forced from the tropical Pacific. The diabatic heating anomalies in both cases force an anomalous low-level cyclonic flow over the Gulf of Mexico that leads to reduced moisture transport into the central United States and increased moisture transport into the eastern United States. The precipitation deficits over the Great Plains in both cases are greatly amplified by the strong soil moisture feedback in the NSIPP-1 AGCM. In contrast, the response over the SE to the cold Pacific during spring is primarily associated with an upper-tropospheric high anomaly over the southern United States that is remotely forced by tropical Pacific diabatic heating anomalies, leading to greatly reduced stationary moisture flux convergences and anomalous subsidence in that region. Moderately reduced evaporation and weakened transient moisture flux convergences play secondary roles. It is only during spring that these three terms are all negative and constructively contribute to produce the maximum dry response in spring. The above findings based on the NSIPP-1 AGCM are generally consistent with observations, as well as with four other AGCMs included in the U.S. Climate Variability and Predictability (CLIVAR) project. [ABSTRACT FROM AUTHOR]

The U.S. Climate Variability and Predictability (U.S. CLIVAR) Drought Working Group (DWG) recently performed a series of experiments in which a number of AGCMs were forced with different leading patterns of global SST variability. These experiments provide a unique opportunity to examine how different SST regimes affect temperature over the continental United States. Herein, the focus is on a particular aspect of June–August (JJA) near-surface air temperature: the temperature during relatively dry years for a given SST regime. For most of the models participating in the DWG experiments, a cold Pacific produces greater warming in the central United States during relatively dry years than a warm Pacific does for the following two separate reasons: (i) the cold Pacific leads on average, across all years, to drier conditions, and (ii) the particular evaporation regime induced by the cold Pacific enhances the impact of evaporation feedback on temperature, that is, the sensitivity of temperature to within-climate variations in moisture availability. These results are supported, to a large extent, by the observational record. [ABSTRACT FROM AUTHOR]

The U.S. Climate Variability and Predictability (CLIVAR) working group on drought recently initiated a series of global climate model simulations forced with idealized SST anomaly patterns, designed to address a number of uncertainties regarding the impact of SST forcing and the role of land–atmosphere feedbacks on regional drought. The runs were carried out with five different atmospheric general circulation models (AGCMs) and one coupled atmosphere–ocean model in which the model was continuously nudged to the imposed SST forcing. This paper provides an overview of the experiments and some initial results focusing on the responses to the leading patterns of annual mean SST variability consisting of a Pacific El Niño–Southern Oscillation (ENSO)-like pattern, a pattern that resembles the Atlantic multidecadal oscillation (AMO), and a global trend pattern. One of the key findings is that all of the AGCMs produce broadly similar (though different in detail) precipitation responses to the Pacific forcing pattern, with a cold Pacific leading to reduced precipitation and a warm Pacific leading to enhanced precipitation over most of the United States. While the response to the Atlantic pattern is less robust, there is general agreement among the models that the largest precipitation response over the United States tends to occur when the two oceans have anomalies of opposite signs. Further highlights of the response over the United States to the Pacific forcing include precipitation signal-to-noise ratios that peak in spring, and surface temperature signal-to-noise ratios that are both lower and show less agreement among the models than those found for the precipitation response. The response to the positive SST trend forcing pattern is an overall surface warming over the world’s land areas, with substantial regional variations that are in part reproduced in runs forced with a globally uniform SST trend forcing. The precipitation response to the trend forcing is weak in all of the models. It is hoped that these early results, as well as those reported in the other contributions to this special issue on drought, will serve to stimulate further analysis of these simulations, as well as suggest new research on the physical mechanisms contributing to hydroclimatic variability and change throughout the world. [ABSTRACT FROM AUTHOR]

The observed climate trends over the United States during 1950–2000 exhibit distinct seasonality and regionality. The surface air temperature exhibits a warming trend during winter, spring, and early summer and a modest countrywide cooling trend in late summer and fall, with the strongest warming occurring over the northern United States in spring. Precipitation trends are positive in all seasons, with the largest trend occurring over the central and southern United States in fall. This study investigates the causes of the seasonality and regionality of those trends, with a focus on the cooling and wetting trends in the central United States during late summer and fall. In particular, the authors examine the link between the seasonality and regionality of the climate trends over the United States and the leading patterns of sea surface temperature (SST) variability, including a global warming (GW) pattern and a Pacific decadal variability (PDV) pattern. A series of idealized atmospheric general circulation model (AGCM) experiments were performed forced by SST trends associated with these leading SST patterns, as well as the residual trend pattern (obtained by removing the GW and PDV contributions). The results show that the observed seasonal and spatial variations of the climate trends over the United States are to a large extent explained by changes in SST. Among the leading patterns of SST variability, the PDV pattern plays a prominent role in producing both the seasonality and regionality of the climate trends over the United States. In particular, it is the main contributor to the apparent cooling and wetting trends over the central United States. The residual SST trend, a manifestation of phase changes of the Atlantic multidecadal SST variation during 1950–2000, also exerts influences that show strong seasonality with important contributions to the central U.S. temperature and precipitation during the summer and fall seasons. In contrast, the response over the United States to the GW SST pattern is an overall warming with little seasonality or regional variation. These results highlight the important contributions of decadal and multidecadal variability in the Pacific and Atlantic in explaining the observed seasonality and regionality of the climate trends over the United States during the period of 1950–2000. [ABSTRACT FROM AUTHOR]

This study examines the predictability of seasonal mean Great Plains precipitation using an ensemble of century-long atmospheric general circulation model (AGCM) simulations forced with observed sea surface temperatures (SSTs). The results show that the predictability (intraensemble spread) of the precipitation response to SST forcing varies on interannual and longer time scales. In particular, this study finds that pluvial conditions are more predictable (have less intraensemble spread) than drought conditions. This rather unexpected result is examined in the context of the physical mechanisms that impact precipitation in the Great Plains. These mechanisms include El Niño–Southern Oscillation’s impact on the planetary waves and hence the Pacific storm track (primarily during the cold season), the role of Atlantic SSTs in forcing changes in the Bermuda high and low-level moisture flux into the continent (primarily during the warm season), and soil moisture feedbacks (primarily during the warm season). It is found that the changes in predictability are primarily driven by changes in the strength of the land–atmosphere coupling, such that under dry conditions a given change in soil moisture produces a larger change in evaporation and hence precipitation than the same change in soil moisture would produce under wet soil conditions. The above changes in predictability are associated with a negatively skewed distribution in the seasonal mean precipitation during the warm season—a result that is not inconsistent with the observations. [ABSTRACT FROM AUTHOR]

In this study the authors examine the impact of El Niño–Southern Oscillation (ENSO) on precipitation events over the continental United States using 49 winters (1949/50–1997/98) of daily precipitation observations and NCEP–NCAR reanalyses. The results are compared with those from an ensemble of nine atmospheric general circulation model (AGCM) simulations forced with observed SST for the same time period. Empirical orthogonal functions (EOFs) of the daily precipitation fields together with compositing techniques are used to identify and characterize the weather systems that dominate the winter precipitation variability. The time series of the principal components (PCs) associated with the leading EOFs are analyzed using generalized extreme value (GEV) distributions to quantify the impact of ENSO on the intensity of extreme precipitation events. The six leading EOFs of the observations are associated with major winter storm systems and account for more than 50% of the daily precipitation variability along the West Coast and over much of the eastern part of the country. Two of the leading EOFs (designated GC for Gulf Coast and EC for East Coast) together represent cyclones that develop in the Gulf of Mexico and occasionally move and/or redevelop along the East Coast producing large amounts of precipitation over much of the southern and eastern United States. Three of the leading EOFs represent storms that hit different sections of the West Coast (designated SW for Southwest coast, WC for the central West Coast, and NW for northwest coast), while another represents storms that affect the Midwest (designated by MW). The winter maxima of several of the leading PCs are significantly impacted by ENSO such that extreme GC, EC, and SW storms that occur on average only once every 20 years (20-yr storms) would occur on average in half that time under sustained El Niño conditions. In contrast, under La Niña conditions, 20-yr GC and EC storms would occur on average about once in 30 years, while there is little impact of La Niña on the intensity of the SW storms. The leading EOFs from the model simulations and their connections to ENSO are for the most part quite realistic. The model, in particular, does very well in simulating the impact of ENSO on the intensity of EC and GC storms. The main model discrepancies are the lack of SW storms and an overall underestimate of the daily precipitation variance. [ABSTRACT FROM AUTHOR]

The article describes the creation of a drought early warning system called The National Integrated Drought Information System (NIDIS) by the Western Governors' Association and the U.S. National Oceanic and Atmospheric Administration (NOAA). The main goal of NIDIS is to reduce the impact of drought with the system's improved monitoring and forecasting capabilities. NOAA has been tasked to handle the implementation of the system. Moreover, it will facilitate the coordination and program delivery across interagency, intergovernmental and private sector for the establishment of an integrated federal drought research program.

Summer simulations over the contiguous United States and Mexico with the Regional Atmospheric Modeling System (RAMS) dynamically downscaling the NCEP–NCAR Reanalysis I for the period 1950–2002 (described in Part I of the study) are evaluated with respect to the three dominant modes of global SST. Two of these modes are associated with the statistically significant, naturally occurring interannual and interdecadal variability in the Pacific. The remaining mode corresponds to the recent warming of tropical sea surface temperatures. Time-evolving teleconnections associated with Pacific SSTs delay or accelerate the evolution of the North American monsoon. At the period of maximum teleconnectivity in late June and early July, there is an opposite relationship between precipitation in the core monsoon region and the central United States. Use of a regional climate model (RCM) is essential to capture this variability because of its representation of the diurnal cycle of convective rainfall. The RCM also captures the observed long-term changes in Mexican summer rainfall and suggests that these changes are due in part to the recent increase in eastern Pacific SST off the Mexican coast. To establish the physical linkage to remote SST forcing, additional RAMS seasonal weather prediction mode simulations were performed and these results are briefly discussed. In order for RCMs to be successful in a seasonal weather prediction mode for the summer season, it is required that the GCM provide a reasonable representation of the teleconnections and have a climatology that is comparable to a global atmospheric reanalysis. [ABSTRACT FROM AUTHOR]

The diurnal cycle of warm-season rainfall over the continental United States and northern Mexico is analyzed in three global atmospheric general circulation models (AGCMs) from NCEP, GFDL, and the NASA Global Modeling Assimilation Office (GMAO). The results for each model are based on an ensemble of five summer simulations forced with climatological sea surface temperatures. Although the overall patterns of time-mean (summer) rainfall and low-level winds are reasonably well simulated, all three models exhibit substantial regional deficiencies that appear to be related to problems with the diurnal cycle. Especially prominent are the discrepancies in the diurnal cycle of precipitation over the eastern slopes of the Rocky Mountains and adjacent Great Plains, including the failure to adequately capture the observed nocturnal peak. Moreover, the observed late afternoon–early evening eastward propagation of convection from the mountains into the Great Plains is not adequately simulated, contributing to the deficiencies in the diurnal cycle in the Great Plains. In the southeast United States, the models show a general tendency to rain in the early afternoon—several hours earlier than observed. Over the North American monsoon region in the southwest United States and northern Mexico, the phase of the broad-scale diurnal convection appears to be reasonably well simulated, though the coarse resolution of the runs precludes the simulation of key regional phenomena. All three models employ deep convection schemes that assume fundamentally the same buoyancy closure based on simplified versions of the Arakawa–Schubert scheme. Nevertheless, substantial differences between the models in the diurnal cycle of convection highlight the important differences in their implementations and interactions with the boundary layer scheme. An analysis of local diurnal variations of convective available potential energy (CAPE) shows an overall tendency for an afternoon peak—a feature well simulated by the models. The simulated diurnal cycle of rainfall is in phase with the local CAPE variation over the southeast United States and the Rocky Mountains where the local surface boundary forcing is important in regulating the diurnal cycle of convection. On the other hand, the simulated diurnal cycle of rainfall tends to be too strongly tied to CAPE over the Great Plains, where the observed precipitation and CAPE are out of phase, implying that free atmospheric large-scale forcing plays a more important role than surface heat fluxes in initiating or inhibiting convection. [ABSTRACT FROM AUTHOR]

This study examines the sensitivity of the North American warm season diurnal cycle of precipitation to changes in horizontal resolution in three atmospheric general circulation models, with a primary focus on how the parameterized moist processes respond to improved resolution of topography and associated local/regional circulations on the diurnal time scale. It is found that increasing resolution (from approximately 2° to ½° in latitude–longitude) has a mixed impact on the simulated diurnal cycle of precipitation. Higher resolution generally improves the initiation and downslope propagation of moist convection over the Rockies and the adjacent Great Plains. The propagating signals, however, do not extend beyond the slope region, thereby likely contributing to a dry bias in the Great Plains. Similar improvements in the propagating signals are also found in the diurnal cycle over the North American monsoon region as the models begin to resolve the Gulf of California and the surrounding steep terrain. In general, the phase of the diurnal cycle of precipitation improves with increasing resolution, though not always monotonically. Nevertheless, large errors in both the phase and amplitude of the diurnal cycle in precipitation remain even at the highest resolution considered here. These errors tend to be associated with unrealistically strong coupling of the convection to the surface heating and suggest that improved simulations of the diurnal cycle of precipitation require further improvements in the parameterizations of moist convection processes. [ABSTRACT FROM AUTHOR]

During the 1930s, the United States experienced one of the most devastating droughts of the past century. The drought affected almost two-thirds of the country and parts of Mexico and Canada and was infamous for the numerous dust storms that occurred in the southern Great Plains. In this study, we present model results that indicate that the drought was caused by anomalous tropical sea surface temperatures during that decade and that interactions between the atmosphere and the land surface increased its severity. We also contrast the 1930s drought with other North American droughts of the 20th century. [ABSTRACT FROM AUTHOR]

This study examines the predictability of seasonal means during boreal summer. The results are based on ensembles of June–July–August (JJA) simulations (started in mid-May) carried out with the NASA Seasonal-to-Interannual Prediction Project (NSIPP-1) atmospheric general circulation model (AGCM) forced with observed sea surface temperatures (SSTs) and sea ice for the years 1980–99. It is found that the predictability of the JJA extratropical height field is primarily in the zonal-mean component of the response to the SST anomalies. This contrasts with the cold season (January–February–March) when the predictability of seasonal means in the boreal extratropics is primarily in the wave component of the El Niño–Southern Oscillation (ENSO) response. Two patterns dominate the interannual variability of the ensemble mean JJA zonal-mean height field. One has maximum variance in the tropical/subtropical upper troposphere, while the other has substantial variance in the midlatitudes of both hemispheres. Both are symmetric with respect to the equator. A regression analysis shows that the tropical/subtropical pattern is associated with SST anomalies in the far eastern tropical Pacific and the Indian Ocean, while the midlatitude pattern is associated with SST anomalies in the tropical Pacific just east of the date line. The two leading zonal height patterns are reproduced in model runs forced with the two leading JJA SST patterns of variability. A comparison with observations shows a signature of the midlatitude pattern that is consistent with the occurrence of dry and wet summers over the United States. It is hypothesized that both patterns, while imposing only weak constraints on extratropical warm season continental-scale climates, may play a role in the predilection for drought or pluvial conditions. [ABSTRACT FROM AUTHOR]

Focuses on a study which examined precipitation recycling over the central United States (U.S.) using the Goddard Earth Observing System Data Assimilation System (GEOS-1 DAS) of the U.S. National Aeronautics and Space Administration. Information on the GEOS-1 DAS and the bulk diagnostic recycling model; Regional hydrological behavior in the U.S.; Issues in diagnostic recycling.

Subseasonal variations in warm-season (May--August) precipitation over the central and eastern United States are shown to be strongly linked to variations in the moisture entering the continent from the Gulf of Mexico within a longitudinally confined "channel" (referred to here as the Texas corridor or TC). These variations reflect the development of low-level southerly wind maxima (or jets) on a number of different timescales in association with distinct subcontinental and larger-scale phenomena. On the diurnal timescale, the TC moisture flux variations are tied to the development of the Great Plains low-level jet. The composite nighttime anomalies are characterized by a strong southerly moisture flux covering northeast Mexico and the southern Great Plains, and enhanced boundary layer convergence and precipitation over much of the upper Great Plains. The strongest jets tend to be associated with an anomalous surface low over the Great Plains, reflecting a predilection for periods when midlatitude weather systems are positioned to produce enhanced southerly flow over this region. On subsynoptic (2--4 days) timescales the TC moisture flux variations are associated with the development and evolution of a warm-season lee cyclone. These systems, which are most prevalent during the early part of the warm season (May and June), form over the central Great Plains in association with an upper-level shortwave and enhanced upper-tropospheric cross-mountain westerly flow. A low-level southerly wind maximum or jet develops underneath and perpendicular to the advancing edge of enhanced midtropospheric westerlies. The clash of anomalous southerly moisture flux and a deep intrusion of anomalous northerly low-level winds results in enhanced precipitation eventually stretching from Texas to the Great Lakes. On synoptic (4--8 days) timescales the TC moisture flux variations are associated with the propagation and intensification of a warm-season mid-latitude... [ABSTRACT FROM AUTHOR]