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This paper examines hydrological variability and its changes in two different versions of a coupled ocean–atmosphere general circulation model developed at the National Oceanic and Atmospheric Administration/Geophysical Fluid Dynamics Laboratory and forced with estimates of future increases of greenhouse gas and aerosol concentrations. This paper is the second part, documenting potential changes in variability as greenhouse gases increase. The variance changes are examined using an ensemble of 8 transient integrations for an older model version and 10 transient integrations for a newer model. Monthly and annual data are used to compute the mean and variance changes. Emphasis is placed on computing and analyzing the variance changes for the middle of the twenty-first century and compared with those found in the respective control integrations. The hydrologic cycle intensifies because of the increase of greenhouse gases. In general, precipitation variance increases in most places. This is the case virtually everywhere the mean precipitation rate increases and many places where the precipitation decreases. The precipitation rate variance decreases in the subtropics, where the mean precipitation rate also decreases. The increased precipitation rate and variance, in middle to higher latitudes during late fall, winter, and early spring leads to increased runoff and its variance during that period. On the other hand, the variance changes of soil moisture are more complicated, because soil moisture has both a lower and upper bound that tends to reduce its fluctuations. This is particularly true in middle to higher latitudes during winter and spring, when the soil moisture is close to its saturation value at many locations. Therefore, changes in its variance are limited. Soil moisture variance change is positive during the summer, when the mean soil moisture decreases and is close to the middle of its allowable range. In middle to high northern latitudes, an increase in runoff and its variance during late winter and spring plus the decrease in soil moisture and its variance during summer lend support to the hypothesis stated in other publications that a warmer climate can cause an increasing frequency of both excessive discharge and drier events, depending on season and latitude. [ABSTRACT FROM AUTHOR]

Recently the National Aeronautics and Space Administration (NASA) Tropical Rainfall Measuring Mission (TRMM) project office made available a new product called the convective–stratiform heating (CSH). These are the datasets for vertical profiles of diabatic heating rates (the apparent heat source). These observed estimates of heating are obtained from the TRMM satellite’s microwave radiances and the precipitation radar. The importance of such datasets for defining the vertical distribution of heating was largely the initiative of Dr. W.-K. Tao from NASA’s Goddard Laboratory. The need to examine how well some of the current cumulus parameterization schemes perform toward describing the amplitude and the three-dimensional distributions of heating is addressed in this paper. Three versions of the Florida State University (FSU) global atmospheric model are run that utilize different versions of cumulus parameterization schemes; namely, modified Kuo parameterization, simple Arakawa–Schubert parameterization, and Zhang–McFarlane parameterization. The Kuo-type scheme used here relies on moisture convergence and tends to overestimate the rainfall generally compared to the TRMM estimates. The other schemes used here show only a slight overestimate of rain rates compared to TRMM; those invoke mass fluxes that are less stringent in this regard in defining cloud volumes. The mass flux schemes do carry out a total moisture budget for a vertical column model and include all components of the moisture budget and are not limited to the horizontal convergence of moisture. The authors carry out a numerical experimentation that includes over a hundred experiments from each of these models; these experiments differ only in their use of the cumulus parameterization. The rest of the model physics, resolution, and initial states are kept the same for each set of 117 forecasts. The strategy for this experimentation follows the authors’ previous studies with the FSU multimodel superensemble. This includes a 100-day training and a 17-day forecast phase, both of which include a large number of forecast experiments. The training phase provides a useful statistical database for tagging the systematic errors of the respective models. The forecast phase is designed to minimize the collective bias errors of these member models. In these forecasts the authors also include the ensemble mean and the multimodel superensemble. In this paper the authors examine model errors in their representations of the heating (amplitude, vertical level of maximum, and the geographical distributions). The main message of this study is that some cumulus parameterization schemes overestimate the amplitude of heating, whereas others carry lower values. The models also exhibit large errors in the placement of the vertical level of maximum heating. Some significant errors were also found in the geographical distributions of heating. The ensemble mean largely mimics the model features and also carries some large errors. The superensemble is more selective in reducing the three-dimensional collective bias errors of the models and provides the best short range forecasts, through hour 60, for the heating. This study shows that it is possible to diagnose some of the modeling errors in the heating for individual member models and that information can be important for correcting such features. [ABSTRACT FROM AUTHOR]

The relative contributions of locally evapotranspired (i.e., recycled) moisture versus externally advected water vapor for the growing-season precipitation of the U.S. Corn Belt and surrounding areas (1.23 × 106 km2) are estimated in this paper. Four May–August seasons with highly contrasting precipitation and crop yields (1975, 1976, 1979, and 1988) are investigated. A simple recycling equation—developed from the traditional atmospheric moisture budget and involving regional evapotranspiration and atmospheric water vapor inflow—is applied on daily, monthly, and seasonal time scales. Several atmospheric moisture budget components {moisture flux divergence [MFD], storage change [or change in precipitable water (dPW)], and inflow [IF]} are evaluated for 24-h periods using standard finite difference and line integral methods applied to objectively analyzed U.S. and Canadian rawinsonde data (50-hPa vertical resolution, surface to 300 hPa) for 0000 and 1200 UTC. Daily area-averaged precipitation (P) totals are derived from approximately 600 evenly distributed (but ungridded) recording rain gauges. Evapotranspiration (E) is estimated as the residual of the moisture budget equation for 24-h periods; values compare favorably with the few existing observations. Traditional budget results show the following: E is weakly related to P on monthly and seasonal time scales; there is surprising interannual constancy of seasonal E cycles and averages given the large variation in resulting crop yields; and monthly and seasonal variability of the export of the E - P surplus is determined largely by the horizontal velocity divergence component of MFD. New recycling analyses suggest that the contribution of local E to P (i.e., PE/P) is relatively small and remarkably consistent (largely 0.19–0.24) for monthly and seasonal periods, despite large P and crop yield variations. However, the monthly/seasonal averaging process is found to completely mask a striking decrease of daily PE/P (from approximately 0.30 to 0.15) with increasing P from 0 to 8 mm day-1. Unique and detailed analyses of P-stratified daily moisture budget results provide key insights into apparent contradictions between daily and monthly/seasonal recycling and related results and concomitant interannual variability, especially for the very dry 1988 season. Interpretation is facilitated by the use of modeled daily global radiation values, measured (instantaneous) and modeled (monthly) soil moisture, United States Department of Agriculture (USDA) crop yield estimates, and satellite normalized difference vegetation index (NDVI) imagery. This paper shows that land–atmosphere interactions are intimately involved in pronounced seasonal climate anomalies for the world's richest agricultural region, but apparently with considerable complexity that includes plant behavior, solar radiation forcing, and challenging time-scale interrelations. [ABSTRACT FROM AUTHOR]

This paper describes a publicly available, long-term (1915-2011), hydrologically consistent dataset for the conterminous United States, intended to aid in studies of water and energy exchanges at the land surface. These data are gridded at a spatial resolution of latitude/longitude and are derived from daily temperature and precipitation observations from approximately 20 000 NOAA Cooperative Observer (COOP) stations. The available meteorological data include temperature, precipitation, and wind, as well as derived humidity and downwelling solar and infrared radiation estimated via algorithms that index these quantities to the daily mean temperature, temperature range, and precipitation, and disaggregate them to 3-hourly time steps. Furthermore, the authors employ the variable infiltration capacity (VIC) model to produce 3-hourly estimates of soil moisture, snow water equivalent, discharge, and surface heat fluxes. Relative to an earlier similar dataset by Maurer and others, the improved dataset has 1) extended the period of analysis (1915-2011 versus 1950-2000), 2) increased the spatial resolution from ⅛° to , and 3) used an updated version of VIC. The previous dataset has been widely used in water and energy budget studies, climate change assessments, drought reconstructions, and for many other purposes. It is anticipated that the spatial refinement and temporal extension will be of interest to a wide cross section of the scientific community. [ABSTRACT FROM AUTHOR]

Numerical models have long predicted that the deforestation of the Amazon would lead to large regional changes in precipitation and temperature, but the extratropical effects of deforestation have been a matter of controversy. This paper investigates the simulated impacts of deforestation on the northwest United States December-February climate. Integrations are carried out using the Ocean-Land-Atmosphere Model (OLAM), here run as a variable-resolution atmospheric GCM, configured with three alternative horizontal grid meshes: 1) 25-km characteristic length scale (CLS) over the United States, 50-km CLS over the Andes and Amazon, and 200-km CLS in the far-field; 2) 50-km CLS over the United States, 50-km CLS over the Andes and Amazon, and 200-km CLS in the far-field; and 3) 200-km CLS globally. In the high-resolution simulations, deforestation causes a redistribution of precipitation within the Amazon, accompanied by vorticity and thermal anomalies. These anomalies set up Rossby waves that propagate into the extratropics and impact western North America. Ultimately, Amazon deforestation results in 10%-20% precipitation reductions for the coastal northwest United States and the Sierra Nevada. Snowpack in the Sierra Nevada experiences declines of up to 50%. However, in the coarse-resolution simulations, this mechanism is not resolved and precipitation is not reduced in the northwest United States. These results highlight the need for adequate model resolution in modeling the impacts of Amazon deforestation. It is concluded that the deforestation of the Amazon can act as a driver of regional climate change in the extratropics, including areas of the western United States that are agriculturally important. [ABSTRACT FROM AUTHOR]

In this paper, the authors evaluate the significance of multidecadal trends in seasonal-mean summertime precipitation and precipitation characteristics over the southwestern United States using stochastic, chain-dependent daily rainfall models. Unlike annual-mean precipitation, trends during the summertime monsoon, covering the period 1931–2000, indicate an overall increase in seasonal precipitation, the number of rainfall events, and the coverage of rainfall events in peripheral regions north of the “core” monsoon area of Arizona and western New Mexico. In addition, there is an increasing trend in intense storm activity and a decreasing trend in extreme dry-spell lengths. Over other regions of the domain, there are no discernible trends found in any of the observed characteristics. These trends are robust to the choice of start dates and, in the case of seasonal-mean precipitation, appear to persist into the current century. [ABSTRACT FROM AUTHOR]

A disproportionate increase in precipitation coming from intense rain events, in the situation of general warming (thus, an extension of the vegetation period with intensive transpiration), and an insignificant change in total precipitation could lead to an increase in the frequency of a potentially serious type of extreme events: prolonged periods without precipitation (even when the mean seasonal rainfall totals increase). This paper investigates whether this development is already occurring during the past several decades over the conterminous United States, for the same period when changes in frequency of intense precipitation events are being observed. Lengthy strings of “dry” days without sizeable (>1.0 mm) precipitation were assessed only during the warm season (defined as a period when mean daily temperature is above the 5°C threshold) when water is intensively used for transpiration and prolonged periods without sizable rainfall represent a hazard for terrestrial ecosystem’s health and agriculture. During the past four decades, the mean duration of prolonged dry episodes (1 month or longer in the eastern United States and 2 months or longer in the southwestern United States) has significantly increased. As a consequence the return period of 1-month-long dry episodes over the eastern United States has reduced more than twofold from 15 to 6–7 yr. The longer average duration of dry episodes has occurred during a relatively wet period across the country but is not observed over the northwestern United States. [ABSTRACT FROM AUTHOR]

The Commonwealth Scientific and Industrial Research Organisation (CSIRO) Mark 2 global coupled climatic model has been used to generate a 10 000-yr simulation of “present” climate. The resultant dataset has been used to investigate a number of aspects of extremes associated with annual mean rainfall. Multimillennial time series of normalized rainfall amounts for selected points are used to highlight secular variability, spatial variations, and the differences between pluvial and drought conditions. Global distributions are also presented for selected rainfall characteristics, including the frequency of occurrence of specified rainfall anomalies with annual durations, the frequency of occurrence of 5-yr sequences of specified rainfall anomalies, and the maximum and minimum normalized rainfall amounts attained in the simulation. Such features cannot be obtained from observations because of their limited duration. A case study is also made of a megadrought over the southwestern United States, together with an analysis of the associated causal mechanisms. Given the exclusion of all external forcing from the model, it is concluded that the extreme annual mean rainfall extremes presented in the paper are attributable to stochastic events. [ABSTRACT FROM AUTHOR]

An efficient method for precipitation recycling calculations based on the general bulk recycling model is developed and applied to the Amazon basin region. The results are compared with the estimates provided by simplified recycling models, and with the estimations obtained in other studies. Then the numerical procedure is adjusted to the modified recycling model incorporating some effects of incomplete vertical mixing of water in the tropospheric column as described in Part I of this paper. The modified numerical model is applied to the Amazon basin region and the results are compared with those from the unmodified model. It is seen from the results that the effects related to an incomplete vertical mixing produce significant changes in the level and distribution of precipitation recycling over the Amazon basin. The general changes in the recycling patterns occurring as a result of modifications include a significant increase in the contribution of recycled water to precipitation in the eastern part of the region and weakening continental recycling gradients. The regional recycling ratio values for the Amazon basin estimated by the modified model are significantly higher than the values provided by the unmodified model. The results of application of the models to several other regions on the globe are described in short. In particular, a comparison of the results with the estimates by the modified Budyko model is made for different regions, and it is found that the modified Budyko's model estimates are, in general, closer to the modified model numerical results than it was for the unmodified models. The results for precipitation recycling over the central United States are presented in more detail. For this region, the information on the degree of incomplete vertical mixing available from the GCM tracer transport modeling results has been used in the modified model calculations. It has been found that, as distinct from the Amazon basin, the effects related to an incomplete vertical mixing do not produce significant changes in the level and distribution of precipitation recycling over the central United States. [ABSTRACT FROM AUTHOR]

In this paper, the authors analyze simulations of present and future climates in the western United States performed with four regional climate models (RCMs) nested within two global ocean–atmosphere climate models. The primary goal here is to assess the range of regional climate responses to increased greenhouse gases in available RCM simulations. The four RCMs used different geographical domains, different increased greenhouse gas scenarios for future-climate simulations, and (in some cases) different lateral boundary conditions. For simulations of the present climate, RCM results are compared to observations and to results of the GCM that provided lateral boundary conditions to the RCM. For future-climate (increased greenhouse gas) simulations, RCM results are compared to each other and to results of the driving GCMs. When results are spatially averaged over the western United States, it is found that the results of each RCM closely follow those of the driving GCM in the same region in both present and future climates. This is true even though the study area is in some cases a small fraction of the RCM domain. Precipitation responses predicted by the RCMs in many regions are not statistically significant compared to interannual variability. Where the predicted precipitation responses are statistically significant, they are positive. The models agree that near-surface temperatures will increase, but do not agree on the spatial pattern of this increase. The four RCMs produce very different estimates of water content of snow in the present climate, and of the change in this water content in response to increased greenhouse gases. [ABSTRACT FROM AUTHOR]

The poor relationship between what climatologists, hydrologists, and other physical scientists call floods, and those floods that actually cause damage to life or property, has limited what can be reliably said about the causes of observed trends in damaging floods. It further limits what can be said about future impacts of floods on society based on predicted changes in the global hydrological cycle. This paper presents a conceptual framework for the systematic assessment of the factors that condition observed trends in flood damage. Using the framework, it assesses the role that variability in precipitation has in damaging flooding in the United States at national and regional levels. Three different measures of flood damage--absolute, per capita, and per unit wealth--each lead to different conclusions about the nature of the flood problem. At a national level, of the 10 precipitation measures examined in this study, the ones most closely related to flood damage are the number of 2-day heavy rainfall events and the number of wet days. Heavy rainfall events are defined relative to a measure of average rainfall in each area, not as absolute thresholds. The study indicates that the growth in recent decades in total damage is related to both climate factors and societal factors: increased damage is associated with increased precipitation and with increasing population and wealth. At the regional level, this study reports a stronger relationship between precipitation measures and flood damage, and indicates that different measures of precip-itation are most closely related to damage in different regions. This study suggests that climate plays an important, but by no means determining, role in the growth in damaging floods in the United States in recent decades. [ABSTRACT FROM AUTHOR]

The paper presents an analysis of the dependence of summertime daily maximum temperature on antecedent soil moisture using daily surface observations from a selection of stations in the contiguous United States and daily time series of soil moisture computed with a simple local water balance model. The computed soil moisture time series are offered as an alternative to Palmer's soil moisture anomaly (Z) index, the Palmer Drought Severity Index (PDSI), and other such time series. In contrast to other water balance models that have been designed for the computation of soil moisture time series, the model herein is driven by daily rather than monthly data, uses the Priestley-Taylor method in lieu of Thornthwaite's method to calculate potential evapotranspiration, allows for runoff during dry periods as well as when soil moisture is not at field capacity, includes a crude scheme for taking into account the effects of snowmelt on the water balance, and permits geographical variations in soil water capacity. The Priestley-Taylor method is considered to yield more realistic estimates of evapo-transpiration than Thornthwaite's method since it accounts for net radiation and represents a special case of the widely used Penman-Monteith method. Total runoff is parameterized according to the Variable Infiltration Capacity model. Based on a comparison with soil moisture measurements at Peoria, Illinois, the model appears to simulate the variability of soil moisture anomalies (W[sup']) reasonably well. Analysis of the relationship between W[sup'] and daily maximum temperatures (T[submax]) shows that in the central and eastern United States during the summer, the entire frequency distribution of standardized T[submax] is shifted toward higher values following a 'low-W[sup']' day (i.e., a day on which W[sup'] falls into the bottom quartile of its frequency distribution). The shift is most pronounced at the high end of the temperature distribution, indicating that as the... [ABSTRACT FROM AUTHOR]

Tropical cyclones (TCs) are an important source of precipitation for much of the eastern United States. However, our understanding of the spatiotemporal variability of tropical cyclone precipitation (TCP) and the connections to large-scale atmospheric circulation is limited by irregularly distributed rain gauges and short records of satellite measurements. To address this, we developed a new gridded (0.25° × 0.25°) publicly available dataset of TCP (1948–2015; Tropical Cyclone Precipitation Dataset, or TCPDat) using TC tracks to identify TCP within an existing gridded precipitation dataset. TCPDat was used to characterize total June–November TCP and percentage contribution to total June–November precipitation. TCP totals and contributions had maxima on the Louisiana, North Carolina, and Texas coasts, substantially decreasing farther inland at rates of approximately 6.2–6.7 mm km−1. Few statistically significant trends were discovered in either TCP totals or percentage contribution. TCP is positively related to an index of the position and strength of the western flank of the North Atlantic subtropical high (NASH), with the strongest correlations concentrated in the southeastern United States. Weaker inverse correlations between TCP and El Niño–Southern Oscillation are seen throughout the study site. Ultimately, spatial variations of TCP are more closely linked to variations in the NASH flank position or strength than to the ENSO index. The TCP dataset developed in this study is an important step in understanding hurricane–climate interactions and the impacts of TCs on communities, water resources, and ecosystems in the eastern United States. [ABSTRACT FROM AUTHOR]

Analyzing a set of ensemble seasonal reforecasts for 1958-2017 using CFSv2, we evaluate the predictive skill of the U.S. seasonal mean precipitation and examine its sources of predictability. Our analysis is for each of the three periods of 1958-78, 1979-99, and 2000-17, corresponding to the positive phase of the Pacific decadal oscillation (PDO) during 1979-99 and negative ones before and after. The ensemble reforecasts at two-month lead reproduce the spatial distribution of winter precipitation trends throughout the 60 years and the continental-scale increase of summer precipitation since 2000. The predicted signalto- noise (S/N) ratio also reveals greater predictability in the post-1979 period than during 1958-78. A maximized S/N ratio EOF analysis is applied to the ensemble seasonal precipitation predictions. In winter and spring, the most predictable patterns feature a north--south dipole throughout United States. The summer and fall patterns are dominated by the anomalies in central and southern United States, respectively. In verification with observations, the winter--spring patterns are more skillful. ENSO influences on these predictable patterns are most dominant in winter and spring, but other oceanic factors also play an active role during summer and fall. The multidecadal change of the U.S. precipitation predictability is attributable to the low-frequency modulation of the ENSO predictability and the influences of other major climate modes. PDO can be a dominant factor associated with enhanced prediction skill in 1979-99 and reduced skill in 1958-78. Since the 2000s, the forcing from the SST anomalies in the tropical North Atlantic with opposite sign to those in the tropical Pacific becomes a significant factor for the U.S. summer precipitation prediction. [ABSTRACT FROM AUTHOR]

Extratropical regional-scale extreme precipitation events (EPEs) are usually associated with certain synoptic perturbations superimposed on slow-varying background circulations. These perturbations induce a dynamically forced ascent that destabilizes the atmospheric stratification and stimulates deep convection, which further drives the perturbation by releasing latent heat. This study identifies the characteristics of large-scale perturbations associated with summer EPEs in two representative regions, East China (ECN) and the southeastern United States (SUS), and analyzes the roles of dynamic forcings and diabatic heating using the quasigeostrophic omega equation. Composites of 39 events in each region show that the upper-level absolute vorticity advection and tropospheric warm advection promote dynamically forced ascent in EPEs, and the moisture advection premoistens the local environment. The background circulation and synoptic perturbations in ECN and the SUS have significant differences. The background vorticity, temperature, and moisture advection form the quasi-steady mei-yu front in ECN, which provides favorable conditions for heavy rainfall. In the SUS, weaker background ascents are forced mainly through vorticity advection. In the synoptic scale, the EPEs in ECN are triggered by short-wavelength wave trains, and in the SUS the EPEs are triggered by longer wavelength potential vorticity intrusions. Although the amplitudes of the dynamically forced ascent in the two regions are similar, diabatic heating contributes much more to the vertical motion in ECN than the SUS, which indicates that there is stronger diabatic heating feedback there. The stronger diabatic heating feedback in ECN appears to be due to stronger moisture advection, convective environments with more humidity, and stronger coupling between convection and large-scale dynamics. [ABSTRACT FROM AUTHOR]

A correction to the article "Characterizing large-scale meteorological patterns and associated temperature and precipitation extremes over the northwestern United States using self-organizing maps," which appeared in a previous issue of the periodical, is presented.

The spatial extent of an extreme precipitation event can be important for a basin's hydrologic response and subsequent flood risk, and may yield insights into underlying atmospheric processes. Using a relaxed movingneighborhood approach, we develop indicator semivariograms based on precipitation records from the Global Historical Climatology Network-Daily (GHCN-D) station network to directly quantify the climatological length scales of extreme daily precipitation over the United States during 1965-2014. We find that the length scales of extreme (90th percentile) daily precipitation events vary both regionally and seasonally. Over the eastern half of the United States, daily extreme precipitation length scales reach 400 km during the winter months, but are approximately half as large during the summer months. The Northwest region, on the other hand, exhibits little seasonal variation, with extreme precipitation length scales of approximately 150 km throughout the year. By leveraging in situ station measurements, our study avoids some of the uncertainties associated with satellite or interpolated precipitation data, and provides the longest climatological assessment of length scales of extreme daily precipitation over the United States to date. Although the length scales that we calculate can be sensitive to station density, neighborhood size, and neighborhood relaxation, we find that the interregional and interseasonal differences in length scales are relatively robust. Our method could be extended to quantify changes in the spatial extent of extreme daily precipitation in the recent past, and to investigate the underlying causes of any changes that are detected. [ABSTRACT FROM AUTHOR]

The net surface water budget, precipitation minus evaporation (P = E), shows a clear seasonal cycle in the U.S. Southwest with a net gain of surface water (positive P = E) in the cold half of the year (October-March) and a net loss of water (negative P = E) in the warm half (April-September), with June and July being the driest months of the year. There is a significant shift of the summer drying toward earlier in the year under a CO2 warming scenario, resulting in substantial spring drying (March-May) of the U.S. Southwest from the near-term future to the end of the current century, with gradually increasing magnitude. While the spring drying has been identified in previous studies, its mechanism has not been fully addressed. Using moisture budget analysis, it was found that the drying is mainly due to decreased mean moisture convergence, partially compensated by the increase in transient eddy moisture flux convergence. The decreased mean moisture convergence is further separated into components as a result of changes in circulation (dynamic changes) and changes in atmospheric moisture content (thermodynamic changes). The drying is found to be dominated by the thermodynamic-driven changes in column-averaged moisture convergence, mainly due to increased dry zonal advection caused by the climatological land-ocean thermal contrast, rather than by the well-known "dry get drier" mechanism. Furthermore, the enhanced dry advection in the warming climate is dominated by the robust zonal mean atmospheric warming, leading to equally robust spring drying in the southwestern United States. [ABSTRACT FROM AUTHOR]

Regional patterns of extreme precipitation events occurring over the continental United States are identified via hierarchical cluster analysis of observed daily precipitation for the period 1950-2005. Six canonical extreme precipitation patterns (EPPs) are isolated for the boreal warm season and five for the cool season. The large-scale meteorological pattern (LMP) inducing each EPP is identified and used to create a 'base function' for evaluating a climate model's potential for accurately representing the different patterns of precipitation extremes. A parallel analysis of the Community Climate System Model, version 4 (CCSM4), reveals that the CCSM4 successfully captures the main U.S. EPPs for both the warm and cool seasons, albeit with varying degrees of accuracy. The model's skill in simulating each EPP tends to be positively correlated with its capability in representing the associated LMP. Model bias in the occurrence frequency of a governing LMP is directly related to the frequency bias in the corresponding EPP. In addition, however, discrepancies are found between the CCSM4's representation of LMPs and EPPs over regions such as the western United States and Midwest, where topographic precipitation influences and organized convection are prominent, respectively. In these cases, the model representation of finer-scale physical processes appears to be at least equally important compared to the LMPs in driving the occurrence of extreme precipitation. [ABSTRACT FROM AUTHOR]

Climate models robustly imply that some significant change in precipitation patterns will occur. Models consistently project that the intensity of individual precipitation events increases by approximately 6%-7% K−1, following the increase in atmospheric water content, but that total precipitation increases by a lesser amount (1%-2% K−1 in the global average in transient runs). Some other aspect of precipitation events must then change to compensate for this difference. The authors develop a new methodology for identifying individual rainstorms and studying their physical characteristics-including starting location, intensity, spatial extent, duration, and trajectory-that allows identifying that compensating mechanism. This technique is applied to precipitation over the contiguous United States from both radar-based data products and high-resolution model runs simulating 80 years of business-as-usual warming. In the model study the dominant compensating mechanism is a reduction of storm size. In summer, rainstorms become more intense but smaller; in winter, rainstorm shrinkage still dominates, but storms also become less numerous and shorter duration. These results imply that flood impacts from climate change will be less severe than would be expected from changes in precipitation intensity alone. However, these projected changes are smaller than model-observation biases, implying that the best means of incorporating them into impact assessments is via 'data-driven simulations' that apply model-projected changes to observational data. The authors therefore develop a simulation algorithm that statistically describes model changes in precipitation characteristics and adjusts data accordingly, and they show that, especially for summertime precipitation, it outperforms simulation approaches that do not include spatial information. [ABSTRACT FROM AUTHOR]

Time series of U.S. daily heavy precipitation (95th percentile) are analyzed to determine factors responsible for regionality and seasonality in their 1979-2013 trends. For annual conditions, contiguous U.S. trends have been characterized by increases in precipitation associated with heavy daily events across the northern United States and decreases across the southern United States. Diagnosis of climate simulations (CCSM4 and CAM4) reveals that the evolution of observed sea surface temperatures (SSTs) was a more important factor influencing these trends than boundary condition changes linked to external radiative forcing alone. Since 1979, the latter induces widespread, but mostly weak, increases in precipitation associated with heavy daily events. The former induces a meridional pattern of northern U.S. increases and southern U.S. decreases as observed, the magnitude of which closely aligns with observed changes, especially over the south and far west. Analysis of model ensemble spread reveals that appreciable 35-yr trends in heavy daily precipitation can occur in the absence of forcing, thereby limiting detection of the weak anthropogenic influence at regional scales. Analysis of the seasonality in heavy daily precipitation trends supports physical arguments that their changes during 1979-2013 have been intimately linked to internal decadal ocean variability and less so to human-induced climate change. Most of the southern U.S. decrease has occurred during the cold season that has been dynamically driven by an atmospheric circulation reminiscent of teleconnections linked to cold tropical eastern Pacific SSTs. Most of the northeastern U.S. increase has been a warm season phenomenon, the immediate cause for which remains unresolved. [ABSTRACT FROM AUTHOR]

Changes in extreme temperatures, heat waves, and heavy rainfall events have adverse effects on human health, air quality, and water resources. With aerosol-only (AER) and greenhouse gas-only (GHG) simulations from 1860 to 2005 in the GFDL CM3 chemistry-climate model, aerosol-induced versus greenhouse gas-induced changes in temperature (summer) and precipitation (all seasons) extremes over the United States are investigated. Small changes in these extremes in the all forcing simulations reflect cancellations between the effects of increasing anthropogenic aerosols and greenhouse gases. In AER, extreme high temperatures and the number of days with temperatures above the 90th percentile decline over most of the United States. The strongest response occurs in the western United States (−2.0°C and −14 days, regionally averaged) and the weakest response occurs in the southeastern United States (−0.6°C and −4.8 days). An opposite-signed response pattern occurs in GHG (+2.3°C and +11.5 days over the western United States and +1.6°C and +7.2 days over the southeastern United States). The similar spatial response patterns in AER versus GHG suggest a preferred regional mode of response that is largely independent of the type of forcing. Extreme precipitation over the eastern United States decreases in AER, particularly in winter, and increases over the eastern and central United States in GHG, particularly in spring. Over the twenty-first century under the representative concentration pathway 8.5 (RCP8.5) emissions scenario, the patterns of extreme temperature and precipitation associated with greenhouse gas forcing dominate. [ABSTRACT FROM AUTHOR]

Projections of modeled precipitation ( P) change in global warming scenarios demonstrate marked intermodel disagreement at regional scales. Empirical orthogonal functions (EOFs) and maximum covariance analysis (MCA) are used to diagnose spatial patterns of disagreement in the simulated climatology and end-of-century P changes in phase 5 of the Coupled Model Intercomparison Project (CMIP5) archive. The term principal uncertainty pattern (PUP) is used for any robust mode calculated when applying these techniques to a multimodel ensemble. For selected domains in the tropics, leading PUPs highlight features at the margins of convection zones and in the Pacific cold tongue. The midlatitude Pacific storm track is emphasized given its relevance to wintertime P projections over western North America. The first storm-track PUP identifies a sensitive region of disagreement in P increases over the eastern midlatitude Pacific where the storm track terminates, related to uncertainty in an eastward extension of the climatological jet. The second PUP portrays uncertainty in a zonally asymmetric meridional shift of storm-track P, related to uncertainty in the extent of a poleward jet shift in the western Pacific. Both modes appear to arise primarily from intermodel differences in the response to radiative forcing, distinct from sampling of internal variability. The leading storm-track PUPs for P and zonal wind change exhibit similarities to the leading uncertainty patterns for the historical climatology, indicating important and parallel sensitivities in the eastern Pacific storm-track terminus region. However, expansion coefficients for climatological uncertainties tend to be weakly correlated with those for end-of-century change. [ABSTRACT FROM AUTHOR]

This study demonstrates the relationship between the Pacific-North American (PNA) teleconnection pattern and the Great Plains low-level jet (GPLLJ). The negative phase of the PNA, which is associated with lower heights over the Great Plains and ridging in the southeastern United States, enhances the GPLLJ by increasing the pressure gradient within the GPLLJ on 6-hourly to monthly time scales. Strong GPLLJ events predominantly occur when the PNA is negative. Warm-season strong GPLLJ events with a very negative PNA (<−1) are associated with more persistent, longer wavelength planetary waves that increase the duration of GPLLJ events and enhance precipitation over the north central United States. When one considers the greatest 5-day north central U.S. precipitation events, a large majority occur when the PNA is negative, with most exhibiting a very negative PNA. Stronger moisture transport during heavy rainfall events with a very negative PNA decreases the precipitation of locally derived moisture compared to events with a very positive PNA. The PNA becomes negative 2-12 days before heavy rainfall events and is very negative within two weeks of 78% of heavy rainfall events in the north central United States, a finding that could be used to improve medium-range forecasts of heavy rainfall events. [ABSTRACT FROM AUTHOR]

Using weather station data, the parameters of a stationary stochastic weather model (SSWM) for daily precipitation over the contiguous United States are estimated. By construct, the model exactly captures the variance component of seasonal precipitation characteristics (intensity, occurrence, and total amount) arising from high-frequency variance. By comparing the variance of the lower-frequency accumulations (on the order of months) between the SSWM and the original measurements, potential predictability (PP) is estimated. Decomposing the variability into contributions from occurrence and intensity allows one to establish two contributing sources of total PP. Aggregated occurrence is found to have higher PP than either intensity or the seasonal total precipitation, and occurrence and intensity are found to interfere destructively when convolved into seasonal totals. It is recommended that efforts aimed at forecasting seasonal precipitation or attributing climate variability to particular processes should analyze occurrence and intensity separately to maximize signal-to-noise ratios. Significant geographical and seasonal variations exist in all PP components. [ABSTRACT FROM AUTHOR]

This work discusses the land surface-atmosphere interactions during the severe drought of 2008 in southern South America, which was among the most severe in the last 50 years in terms of both intensity and extent. Once precipitation returned to normal values, it took about two months for the soil moisture content and vegetation to recover. The land surface effects were examined by contrasting long-term simulations using a consistent set of satellite-derived annually varying land surface biophysical properties against simulations using the conventional land-cover types in the Weather Research and Forecasting Model-Noah land surface model (WRF-Noah). The new land-cover dataset is based on ecosystem functional properties that capture changes in vegetation status due to climate anomalies and land-use changes. The results show that the use of realistic information of vegetation states enhances the model performance, reducing the precipitation biases over the drought region and over areas of excessive precipitation. The precipitation bias reductions are attributed to the corresponding changes in greenness fraction, leaf area index, stomatal resistance, and surface roughness. The temperature simulation shows a generalized increase, which is attributable to a lower vegetation greenness and a doubling of the stomatal resistance that reduces the evapotranspiration rate. The increase of temperature has a beneficial effect toward the eastern part of the domain with a notable reduction of the bias, but not over the central region where the bias is increased. The overall results suggest that an improved representation of the surface processes may contribute to improving the predictive skill of the model system. [ABSTRACT FROM AUTHOR]

In this work the authors investigate possible changes in the intensity of rainfall events associated with tropical cyclones (TCs) under idealized forcing scenarios, including a uniformly warmer climate, with a special focus on landfalling storms. A new set of experiments designed within the U.S. Climate Variability and Predictability (CLIVAR) Hurricane Working Group allows disentangling the relative role of changes in atmospheric carbon dioxide from that played by sea surface temperature (SST) in changing the amount of precipitation associated with TCs in a warmer world. Compared to the present-day simulation, an increase in TC precipitation was found under the scenarios involving SST increases. On the other hand, in a CO2-doubling-only scenario, the changes in TC rainfall are small and it was found that, on average, TC rainfall tends to decrease compared to the present-day climate. The results of this study highlight the contribution of landfalling TCs to the projected increase in the precipitation changes affecting the tropical coastal regions. [ABSTRACT FROM AUTHOR]

In previous work the authors demonstrated an empirical relation, in the form of an index, between U.S. monthly tornado activity and monthly averaged environmental parameters. Here a detailed comparison is made between the index and reported tornado activity. The index is a function of two environmental parameters taken from the North American Regional Reanalysis: convective precipitation (cPrcp) and storm relative helicity (SRH). Additional environmental parameters are considered for inclusion in the index, among them convective available potential energy, but their inclusion does not significantly improve the overall climatological performance of the index. The aggregate climatological dependence of reported monthly U.S. tornado numbers on cPrcp and SRH is well described by the index, although it fails to capture nonsupercell and cool season tornadoes. The contributions of the two environmental parameters to the index annual cycle and spatial distribution are examined with the seasonality of cPrcp (maximum during summer) relative to SRH (maximum in winter) accounting for the index peak value in May. The spatial distribution of SRH establishes the central U.S. 'tornado alley' of the index, while the spatial distribution of cPrcp enhances index values in the South and Southeast and suppresses them west of the Rockies and over elevation. At the scale of the NOAA climate regions, the largest deficiency of the index climatology occurs over the central region where the index peak in spring is too low and where the late summer drop-off in the reported number of tornadoes is poorly captured. This index deficiency is related to its sensitivity to SRH, and increasing the index sensitivity to SRH improves the representation of the annual cycle in this region. The ability of the index to represent the interannual variability of the monthly number of U.S. tornadoes can be ascribed during most times of the year to interannual variations of cPrcp rather than of SRH. However, both factors are important during the peak spring period. The index shows some skill in representing the interannual variability of monthly tornado numbers at the scale of NOAA climate regions. [ABSTRACT FROM AUTHOR]

The recent sequence of extreme hydrological events across the eastern United States (e.g., Hurricane Irene in August 2011, Tropical Storm Lee in September 2011, and Hurricane Sandy in October 2012), which led to unprecedented flooding including in various parts in the study region, the Catskill Mountains, and Hudson River Valley in southern New York State, have raised the question of whether the frequency of extreme events across the region is changing. In this study variations in the frequency of extreme precipitation and streamflow events available from historical records are analyzed. This study finds that there has been a marked increase in the frequency of warm season (June-October) extreme hydrologic events during the last two decades, with an accelerated rate of increase since the mid-1990s. The most recent decade has the highest frequency of extreme warm season events in the last 100 years across the study region. No such trend is observed between November and May; in fact the frequency of 4-day extreme precipitation events during the cold period has declined during the last two decades. [ABSTRACT FROM AUTHOR]

A generalizable method is presented for establishing the potential predictability for seasonal precipitation occurrence using rain gauge data. This method provides an observationally based upper limit for potential predictability for 774 weather stations in the contiguous United States. It is found that the potentially predictable fraction varies seasonally and spatially, and that on average 30% of year-to-year seasonal variability is potentially explained by predictable climate processes. Potential predictability is generally highest in winter, appears to be enhanced by orography and land surface coupling, and is lowest (stochastic variance is highest) along the Pacific coast. These results depict 'hot' spots of climate variability, for use in guiding regional climate forecasting and in uncovering processes driving climate. Identified 'cold' spots are equally useful in guiding future studies as predictable climate signals in these areas will likely be undetectable. [ABSTRACT FROM AUTHOR]

There is a long history of debate on the usefulness of climate model-based seasonal hydroclimatic forecasts as compared to ensemble streamflow prediction (ESP). In this study, the authors use NCEP's operational forecast system, the Climate Forecast System version 2 (CFSv2), and its previous version, CFSv1, to investigate the value of climate models by conducting a set of 27-yr seasonal hydroclimatic hindcasts over the conterminous United States (CONUS). Through Bayesian downscaling, climate models have higher squared correlation R2 and smaller error than ESP for monthly precipitation, and the forecasts conditional on ENSO have further improvements over southern basins out to 4 months. Verification of streamflow forecasts over 1734 U.S. Geological Survey (USGS) gauges shows that CFSv2 has moderately smaller error than ESP, but all three approaches have limited added skill against climatology beyond 1 month because of overforecasting or underdispersion errors. Using a postprocessor, 60%-70% of probabilistic streamflow forecasts are more skillful than climatology. All three approaches have plausible predictions of soil moisture drought frequency over the central United States out to 6 months, and climate models provide better results over the central and eastern United States. The R2 of drought extent is higher for arid basins and for the forecasts initiated during dry seasons, but significant improvements from CFSv2 occur in different seasons for different basins. The R2 of drought severity accumulated over CONUS is higher during winter, and climate models present added value, especially at long leads. This study indicates that climate models can provide better seasonal hydroclimatic forecasts than ESP through appropriate downscaling procedures, but significant improvements are dependent on the variables, seasons, and regions. [ABSTRACT FROM AUTHOR]

To assess the influence of Atlantic tropical cyclones (TCs) on the eastern U.S. drought regime, the Variable Infiltration Capacity (VIC) land surface hydrologic model was run over the eastern United States forced by the North American Land Data Assimilation System phase 2 (NLDAS-2) analysis with and without TC-related precipitation for the period 1980-2007. A drought was defined in terms of soil moisture as a prolonged period below a percentile threshold. Different duration droughts were analyzed-short term (longer than 30 days) and long term (longer than 90 days)-as well as different drought severities corresponding to the 10th, 15th, and 20th percentiles of soil moisture depth. With TCs, droughts are shorter in duration and of a lesser spatial extent. Tropical cyclones variously impact soil moisture droughts via late drought initiation, weakened drought intensity, and early drought recovery. At regional scales, TCs decreased the average duration of moderately severe short-term and long-term droughts by less than 4 (10% of average drought duration per year) and more than 5 (15%) days yr−1, respectively. Also, they removed at least two short-term and one long-term drought events over 50% of the study region. Despite the damage inflicted directly by TCs, they play a crucial role in the alleviation and removal of drought for some years and seasons, with important implications for water resources and agriculture. [ABSTRACT FROM AUTHOR]

Evidence for spatially coherent, but different, U.S. summer precipitation and surface air temperature anomalies during the evolving phase and during the summers following the peak phase of the winter El Niño is presented. The spatial patterns during the decaying phase of El Niño are distinctive from patterns in the preceding summer when El Niño is in its evolving phase, that is, the traditional 'simultaneous' composite patterns associated with El Niño. The analysis of a multimodel ensemble of global atmospheric models forced by observed sea surface temperature further confirms that the differences in the U.S. summer precipitation and surface temperature anomalies between the developing and decaying phases of El Niño are a result of the atmospheric response to tropical warm SST anomalies that are shifted eastward and are confined east of 120°W during the decaying phase of El Niño. Given the distinctive pattern, and relatively large amplitude of these anomalies during the decaying phase of El Niño, the results may have implications for the seasonal prediction of U.S. summer precipitation and temperature following winter El Niños. [ABSTRACT FROM AUTHOR]

Long-term (1901-2002) diurnal temperature range (DTR) data are evaluated to examine their spatial and temporal variability across the United States; the early century origin of the DTR declines; and the relative regional contributions to DTR variability among cloud cover, precipitation, soil moisture, and atmosphere/ocean teleconnections. Rotated principal component analysis (RPCA) of the Climatic Research Unit (CRU) Time Series (TS) 2.1 dataset identifies five regions of unique spatial U.S. DTR variability. RPCA creates regional orthogonal indices of cloud cover, soil moisture, precipitation, and the teleconnections used subsequently in stepwise multiple linear regression to examine their regional impact on DTR, maximum temperature (Tmax), and minimum temperature (Tmin). The southwestern United States has the smallest DTR and cloud cover trends as both Tmax and Tmin increase over the century. The Tmin increases are the primary influence on DTR trend in other regions, except in the south-central United States, where downward Tmax trend largely affects its DTR decline. The Tmax and DTR tend to both exhibit simultaneous decadal variations during unusually wet and dry periods in response to cloud cover, soil moisture, and precipitation variability. The widely reported post-1950 DTR decline began regionally at various times ranging from around 1910 to the 1950s. Cloud cover alone accounts for up to 63.2% of regional annual DTR variability, with cloud cover trends driving DTR in northern states. Cloud cover, soil moisture, precipitation, and atmospheric/oceanic teleconnection indices account for up to 80.0% of regional variance over 1901-2002 (75.4% in detrended data), although the latter only account for small portions of this variability. [ABSTRACT FROM AUTHOR]

This study uses an empirical downscaling method based on self-organizing maps (SOMs) to produce high-resolution, downscaled precipitation projections over the state of Pennsylvania in the mid-Atlantic region of the United States for the future period 2046-65. To examine the sensitivity of precipitation change to the water vapor increase brought by global warming, the authors test the following two approaches to downscaling: one uses the specific humidity in the downscaling algorithm and the other does not. Application of the downscaling procedure to the general circulation model (GCM) projections reveals changes in the relative occupancy, but not the fundamental nature, of the simulated synoptic circulation states. Both downscaling approaches predict increases in annual and winter precipitation, consistent in sign with the 'raw' output from the GCMs but considerably smaller in magnitude. For summer precipitation, larger discrepancies are seen between raw and downscaled GCM projections, with a substantial dependence on the downscaling version used (downscaled precipitation changes employing specific humidity are smaller than those without it). Application of downscaling generally reduces the inter-GCM uncertainties, suggesting that some of the spread among models in the raw projected precipitation may result from differences in precipitation parameterization schemes rather than fundamentally different climate responses. Projected changes in the North Atlantic Oscillation (NAO) are found to be significantly related to changes in winter precipitation in the downscaled results, but not for the raw GCM results, suggesting that the downscaling more effectively captures the influence of climate dynamics on projected changes in winter precipitation. [ABSTRACT FROM AUTHOR]

The spatial-intensity variability of extreme precipitation over the contiguous United States (CONUS) during boreal winter and relationships with the Madden-Julian oscillation (MJO) are investigated. Daily gridded precipitation is used to define two types of contiguous regions of extreme precipitation (CREPs): the intensity and spatial extent exceeding the 75th and 90th percentiles of frequency distributions. Extreme precipitation occurs twice as frequently when the MJO is active than inactive. Joint probabilities of the fractional area of CONUS sectors when the MJO is active are 2.0-2.5 higher than probabilities during inactive days for both 75th and 90th percentile CREPs (similar for the intensity of CREPs). Probabilities of the fractional area of 75th percentile CREPs when the MJO is active in neutral ENSO are higher than during warm or cold ENSO. Joint probabilities of the fractional area during MJO and warm ENSO are higher than MJO and cold ENSO and statistically significant over southern sectors. Results are similar for joint probabilities of intensity exceedance and MJO activity in warm and cold ENSO phases. Proportions of 75th and 90th percentile CREPs for each sector and phase of the MJO are predominantly large when MJO convective signals are over the central Indian Ocean or western Pacific. Probabilities of the fractional area of 90th percentile CREPs conditioned on MJO phases, however, do not show clear predominance. This indicates that the MJO is not the sole player in the occurrences of CREPs. Last, this study concludes that probabilities of the fractional area and intensity of 75th and 90th percentile CREPs in the CONUS do not depend on the amplitude of the MJO. [ABSTRACT FROM AUTHOR]

Observations from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations ( CALIPSO) and CloudSat satellites are used to evaluate clouds and precipitation in the ECHAM5 general circulation model. Active lidar and radar instruments on board CALIPSO and CloudSat allow the vertical distribution of clouds and their optical properties to be studied on a global scale. To evaluate the clouds modeled by ECHAM5 with CALIPSO and CloudSat, the lidar and radar satellite simulators of the Cloud Feedback Model Intercomparison Project's Observation Simulator Package are used. Comparison of ECHAM5 with CALIPSO and CloudSat found large-scale features resolved by the model, such as the Hadley circulation, are captured well. The lidar simulator demonstrated ECHAM5 overestimates the amount of high-level clouds, particularly optically thin clouds. High-altitude clouds in ECHAM5 consistently produced greater lidar scattering ratios compared with CALIPSO. Consequently, the lidar signal in ECHAM5 frequently attenuated high in the atmosphere. The large scattering ratios were due to an underestimation of effective ice crystal radii in ECHAM5. Doubling the effective ice crystal radii improved the scattering ratios and frequency of attenuation. Additionally, doubling the effective ice crystal radii improved the detection of ECHAM5's highest-level clouds by the radar simulator, in better agreement with CloudSat. ECHAM5 was also shown to significantly underestimate midlevel clouds and (sub)tropical low-level clouds. The low-level clouds produced were consistently perceived by the lidar simulator as too optically thick. The radar simulator demonstrated ECHAM5 overestimates the frequency of precipitation, yet underestimates its intensity compared with CloudSat observations. These findings imply compensating mechanisms in ECHAM5 balance out the radiative imbalance caused by incorrect optical properties of clouds and consistently large hydrometeors in the atmosphere. [ABSTRACT FROM AUTHOR]

This study uses a statistical downscaling method based on self-organizing maps (SOMs) to produce high-resolution, downscaled precipitation estimates over the state of Pennsylvania in the mid-Atlantic region of the United States. The SOMs approach derives a transfer function between large-scale mean atmospheric states and local meteorological variables (daily point precipitation values) of interest. First, the SOM was trained using seven coarsely resolved atmospheric variables from the National Centers for Environmental Prediction (NCEP) reanalysis dataset to model observed daily precipitation data from 17 stations across Pennsylvania for the period 1979-2005. Employing the same coarsely resolved variables from nine general circulation model (GCM) simulations taken from the historical analysis of the Coupled Model Intercomparison Project, phase 3 (CMIP3), the trained SOM was subsequently applied to simulate daily precipitation at the same 17 sites for the period 1961-2000. The SOM analysis indicates that the nine model simulations exhibit similar synoptic-scale features to the (NCEP) observations over the 1979-2007 training interval. An analysis of the sea level pressure signatures and the precipitation distribution corresponding to the trained SOM shows that it is effective in differentiating characteristic synoptic circulation patterns and associated precipitation. The downscaling approach provides a faithful reproduction of the observed probability distributions and temporal characteristics of precipitation on both daily and monthly time scales. The downscaled precipitation field shows significant improvement over the raw GCM precipitation fields with regard to observed average monthly precipitation amounts, average monthly number of rainy days, and standard deviations of monthly precipitation amounts, although certain caveats are noted. [ABSTRACT FROM AUTHOR]

This study examines the characteristics of cold-season (November-March) daily precipitation over the contiguous United States during active periods of the Madden-Julian oscillation (MJO). A large response in the precipitation rate anomaly is found over the eastern United States when MJO-related enhanced tropical convection is moving through the far western to central Pacific (conventionally known as phases 5, 6, and 7 of the MJO). Positive anomalies occur in the region of the eastern Mississippi River basin, and negative anomalies occur in the Southeast. The relative stability of this pattern throughout the three phases suggests that they can be considered together. During phases 5-7, the central United States has a daily precipitation rate between 110%% and 150%% of normal, while the precipitation rate over much of Florida is less than 70%% of normal. Much of the lower Mississippi River basin region receives somewhat more frequent daily precipitation during MJO phases 5-7, but a greater increase is found in the daily precipitation intensity, suggesting more intense storms. On the other hand, Florida has substantially fewer daily precipitation events, with a smaller decrease in the intensity. To understand the atmospheric mechanisms related to the above shifts in daily precipitation, elements of the atmospheric circulation were examined. Positive moisture flux convergence anomalies, which have been linked to increased precipitation rate and intensity, are found in the region of increased precipitation rate during MJO phases 5-7. During those phases, the North American jet stream is shifted northward, likely leading to a higher incidence of storms over the lower Mississippi River basin and fewer storms over Florida. This is supported by the fact that the storm track also shows increased activity over the central United States during MJO phases 5-7. [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]

In this study, the Weather Research and Forecasting (WRF) model is employed as a nested regional climate model to dynamically downscale output from the National Center for Atmospheric Research''s (NCAR''s) Community Climate System Model (CCSM) version 3 and the National Centers for Environmental Prediction (NCEP)--NCAR global reanalysis (NNRP). The latter is used for verification of late-twentieth-century climate simulations from the WRF. This analysis finds that the WRF is able to produce precipitation that is more realistic than that from its driving systems (the CCSM and NNRP). It also diagnoses potential issues with and differences between all of the simulations completed. Specifically, the magnitude of heavy 6-h average precipitation events, the frequency distribution, and the diurnal cycle of precipitation over the central United States are greatly improved. Projections from the WRF for late-twenty-first-century precipitation show decreases in average May--August (MJJA) precipitation, but increases in the intensity of both heavy precipitation events and rain in general when it does fall. A decrease in the number of 6-h periods with rainfall accounts for the overall decrease in average precipitation. The WRF also shows an increase in the frequency of very heavy to extreme 6-h average events, but a decrease in the frequency of all events lighter than those over the central United States. Overall, projections from this study suggest an increase in the frequency of both floods and droughts during the warm season in the central United States. [ABSTRACT FROM AUTHOR]

The northern Rocky Mountains (NRMs) are a critical headwaters region with the majority of water resources originating from mountain snowpack. Observations showing declines in western U.S. snowpack have implications for water resources and biophysical processes in high-mountain environments. This study investigates oceanic and atmospheric controls underlying changes in timing, variability, and trends documented across the entire hydroclimatic-monitoring system within critical NRM watersheds. Analyses were conducted using records from 25 snow telemetry (SNOTEL) stations, 148 1 April snow course records, stream gauge records from 14 relatively unimpaired rivers, and 37 valley meteorological stations. Over the past four decades, midelevation SNOTEL records show a tendency toward decreased snowpack with peak snow water equivalent (SWE) arriving and melting out earlier. Temperature records show significant seasonal and annual decreases in the number of frost days (days ≤≤0°°C) and changes in spring minimum temperatures that correspond with atmospheric circulation changes and surface--albedo feedbacks in March and April. Warmer spring temperatures coupled with increases in mean and variance of spring precipitation correspond strongly to earlier snowmeltout, an increased number of snow-free days, and observed changes in streamflow timing and discharge. The majority of the variability in peak and total annual snowpack and streamflow, however, is explained by season-dependent interannual-to-interdecadal changes in atmospheric circulation associated with Pacific Ocean sea surface temperatures. Over recent decades, increased spring precipitation appears to be buffering NRM total annual streamflow from what would otherwise be greater snow-related declines in hydrologic yield. Results have important implications for ecosystems, water resources, and long-lead-forecasting capabilities. [ABSTRACT FROM AUTHOR]

The recent analysis of Rossow et al. used a clustering technique to derive six tropical weather states (WS) based on mesoscale cloud-type patterns and documented the spatial distribution of those WS and the modes of variability of the convective WS in the tropical western Pacific. In this study, the global tropics are separated into 30°° ×× 30°° regions, and a clustering algorithm is applied to the regional WS frequency distributions to derive the dominant modes of weather state variability (or the climate state variability) in each region. The results show that the whole tropical atmosphere oscillates between a convectively active and a convectively suppressed regime with the exception of the eastern parts of the two ocean basins, where the oscillation is between a stratocumulus and a trade cumulus regime. The dominant mode of both those oscillations is the seasonal cycle with the exception of the eastern Indian and western--central Pacific region, where El Niño frequencies dominate. The transitions between the convectively active and suppressed regimes produce longwave (LW) and shortwave (SW) top-of-atmosphere (TOA) radiative differences that are of opposite sign and of similar magnitude, being of order 20--30 W m−−2 over ocean and 10--20 W m−−2 over land and thus producing an overall balance in the TOA radiative budget. The precipitation differences between the convectively active and suppressed regimes are found to be of order 2.5--3 mm day−−1 over ocean and 1--2.4 mm day−−1 over land. Finally, the transitions between the stratocumulus and shallow cumulus regimes produce noticeable TOA SW differences of order 10--20 W m−−2 and very small TOA LW and precipitation differences. The potential climate feedback implications of the regime radiation and precipitation differences are discussed. [ABSTRACT FROM AUTHOR]

This study investigates a decadal climate shift over East Asia in winter, focusing on the changes in hydrological cycle as well as large-scale circulation using the National Centers for Environmental Prediction (NCEP) Regional Spectral Model (RSM). The RSM is forced by perfect boundary conditions for winter (December-February) from 1979 to 2007. Analyses for two separate periods (1979-87 and 1999-2007) are performed to investigate the regional climate model's ability to simulate climate change in precipitation as well as large-scale circulation. The RSM reproduces differences in large-scale features associated with winter climate change over East Asia when the winter monsoon is modulated on decadal time scales with its weakening pattern observed since the late 1980s. The model adequately reproduces a weakening of the Siberian high and shallowness of the Aleutian low in the lower troposphere and a weakened East Asian coastal trough and East Asian jet in the upper troposphere during 1999-2007, as compared to the first nine winters of 1979-87. Conversely, the decadal shift in precipitation is not well reproduced by the model. The model is capable of reproducing the power spectrum of daily precipitation with maxima at 8.5 days and 45 days in 1979-87, whereas widely spread peaks in 1999-2007 are not captured. The increase of precipitation due to parameterized convection is prominent. This study shows that the dynamical numerical model has a limited capability to reproduce the wintertime hydrological climate over East Asia associated with global warming in recent years. [ABSTRACT FROM AUTHOR]

Data from observations and the Intergovernmental Panel on Climate Change (IPCC) twentieth-century climate change model [phase 3 of the Coupled Model Intercomparison Project (CMIP3)] simulations were analyzed to examine the decadal changes of the impact of ENSO on air temperature Tair and precipitation P over the United States. The comparison of composites for the early period (1915–60) and the recent period (1962–2006) indicates that cooling (warming) over the south and warming (cooling) over the north during ENSO warm (cold) winters have been weakening. The ENSO influence on winter P over the Southwest is strengthening, while the impact on P over the Ohio Valley is weakening for the recent decades. These differences are not due to the long-term trends in Tair or P; they are attributed to the occurrence of the central Pacific (CPAC) ENSO events in the recent years. The CPAC ENSO differs from the canonical eastern Pacific (EPAC) ENSO. The EPAC ENSO has a sea surface temperature anomaly (SSTA) maximum in the eastern Pacific. Enhanced convection extends from the date line to the eastern Pacific, with negative anomalies in the western Pacific. The atmospheric responses resemble a tropical Northern Hemisphere pattern. The wave train is consistent with the north–south Tair contrast over North America during the EPAC ENSO winters. The CPAC ENSO has enhanced convection in the central Pacific. The atmospheric responses show a Pacific–North American pattern. It is consistent with west–east contrast in Tair and more rainfall over the Southwest during the CPAC ENSO winters. [ABSTRACT FROM AUTHOR]

The present study assesses the potential of the U.S. Climate Variability and Predictability (CLIVAR) Drought Working Group (DWG) models in simulating interannual precipitation variability over North America, especially the Great Plains. It also provides targets for the idealized DWG model experiments investigating drought origin. The century-long Atmospheric Model Intercomparison Project (AMIP) simulations produced by version 3.5 of NCAR’s Community Atmosphere Model (CAM3.5), the Lamont-Doherty Earth Observatory’s Community Climate Model (CCM3), and NASA’s Seasonal-to-Interannual Prediction Project (NSIPP-1) atmospheric models are analyzed; CCM3 and NSIPP-1 models have 16- and 14-ensemble simulations, respectively, while CAM3.5 only has 1. The standard deviation of summer precipitation is different in AMIP simulations. The maximum over the central United States seen in observations is placed farther to the west in simulations. Over the central plains the models exhibit modest skill in simulating low-frequency precipitation variability, a Palmer drought severity index proxy. The presence of a linear trend increases correlations in the period 1950–99 when compared with those for the whole century. The SST links of the Great Plains drought index have features in common with observations over both the Pacific and Atlantic Oceans. Interestingly, summer-to-fall precipitation regressions of the warm Trend, cold Pacific, and warm Atlantic modes of annual mean SST variability (used in forcing the DWG idealized model experiments) tend to dry the southwestern, midwestern, and southeastern regions of the United States in the observations and, to a lesser extent, in the simulations. The similarity of the idealized SST-forced droughts in DWG modeling experiments with AMIP precipitation regressions of the corresponding SST principal components, evident especially in the case of the cold Pacific pattern, suggests that the routinely conducted AMIP simulations could have served as an effective proxy for the more elaborated suite of DWG modeling experiments. [ABSTRACT FROM AUTHOR]

Case studies have shown that heavy precipitation events and rapid cyclogenesis in the extratropics can be fueled by moist and warm tropical air masses. Often the tropical moisture export (TME) occurs through a longitudinally confined region in the subtropics. Here a comprehensive climatological analysis of TME is constructed on the basis of seven-day forward trajectories started daily from the tropical lower troposphere using 6-hourly 40-yr ECMWF Re-Analysis (ERA-40) data from the 23-year period 1979–2001. The objective TME identification procedure retains only those trajectories that reach a water vapor flux of at least 100 g kg-1 m s-1 somewhere north of 35°N. The results show four distinct activity maxima with different seasonal behavior: (i) The “pineapple express,” which connects tropical moisture sources near Hawaii with precipitation near the North American west coast, has a marked activity maximum in boreal winter. (ii) TME over the west Pacific is largest in summer, partly related to the East Asian monsoon and the mei-yu–baiu front. This region alone is responsible for a large portion of TME across 35°N. (iii) The narrow activity maximum over the Great Plains of North America is rooted over the Gulf of Mexico and the Caribbean Sea and has a clear maximum in summer and spring. (iv) TME over the western North Atlantic shows the smallest annual cycle with a maximum in winter and autumn. The interannual variability of (i) and (iv) is significantly modulated by El Niño. Over the African–European–Asian region, high orographic barriers impede TME. A typical TME trajectory evolution is poleward and quasi-horizontal in the subtropics and then more eastward and upward in the southern midlatitudes, where TME contributes up to 60% to climatological precipitation. The TME dataset presented here can serve as a basis for future studies on extreme events. [ABSTRACT FROM AUTHOR]

This study examines the seasonal characteristics of daily precipitation over the United States using the North American Regional Reanalysis (NARR). To help understand the physical mechanisms that contribute to changes in the characteristics of daily precipitation, vertically integrated moisture flux convergence (MFC) and precipitable water were included in the study. First, an analysis of the NARR precipitation was carried out because while observed precipitation is indirectly assimilated in the system, differences exist. The NARR mean seasonal amount is very close to that of observations throughout the year, although NARR exhibits a slight systematic bias toward more-frequent, lighter precipitation. Particularly during summer, the precipitation intensity and the probability distribution function (PDF) indicate that NARR somewhat underestimates extremes and overestimates lighter events in the eastern half of the United States. The intensity and PDF of moisture flux convergence exhibit a strong similarity to those of precipitation, suggesting a link between strong MFC and precipitation extremes. On the other hand, the relationship between the precipitable water and precipitation PDFs is weaker, based on the lack of agreement of their gamma distribution parameters. The dependence of the precipitation PDF on the lower-frequency modulation of ENSO was examined. During El Niño winters, the Southwest and central United States, Gulf of Mexico region, and southeastern coast have greater precipitation intensity and extremes than during La Niña, and the Ohio River and Red River basins have lower intensity and fewer extreme events. During summer, the northern Rocky Mountains receive higher intensity precipitation with more extreme events. Most areas where the change in the daily mean precipitation between ENSO phases is large have greater shifts in the extreme tail of the PDF. The ENSO-related response of moisture flux convergence is similar to that of precipitation. ENSO-related shifts in the precipitation PDF do not appear to have a strong relationship to the shifts in precipitable water. [ABSTRACT FROM AUTHOR]

Relationships between transient upper-tropospheric troughs and warm season convective activity over the southwest United States and northern Mexico are explored. Analysis of geopotential height and vorticity fields from the North American Regional Reanalysis and cloud-to-ground lightning data indicates that the passage of mobile inverted troughs (IVs) significantly enhances convection when it coincides with the peak diurnal cycle (1800–0900 UTC) over the North American monsoon (NAM) region. The preferred tracks of IVs during early summer are related to the dominant modes of Pacific sea surface temperature (SST) variability. When La Niña–like (El Niño–like) conditions prevail in the tropical Pacific and the eastern North Pacific has a horseshoe-shaped negative (positive) SST anomaly, IVs preferentially track farther north (south) and are slightly (typically one IV) more (less) numerous. These results point to the important role that synoptic-scale disturbances play in modulating the diurnal cycle of precipitation over the NAM region and the significant impact that the statistically supported low-frequency Pacific SST anomalies exert on the occurrence and track of these synoptic transients. [ABSTRACT FROM AUTHOR]