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Cold weather disruptions Despite the rapid warming that is the cardinal signature of global climate change, especially in the Arctic, where temperatures are rising much more than elsewhere in the world, the United States and other regions of the Northern Hemisphere have experienced a conspicuous and increasingly frequent number of episodes of extremely cold winter weather over the past four decades. Cohen et al . combined observations and models to demonstrate that Arctic change is likely an important cause of a chain of processes involving what they call a stratospheric polar vortex disruption, which ultimately results in periods of extreme cold in northern midlatitudes (see the Perspective by Coumou). —HJS

A k-means clustering method is applied to daily ERA5 500-hPa heights, sea level pressure, and 850-hPa winds, 1979–2008, to identify characteristic weather types (WTs) for September–November for the northeast United States. The resulting WTs are analyzed in terms of structure, frequency of occurrence, typical progressions, precipitation and temperature characteristics, and relation to teleconnections. The WTs are used to make a daily circulation-based distinction between early and late autumn and consider shifts in seasonality. Seven WTs are identified for the autumn season, representing a range of trough and ridge patterns. The largest average values of precipitation and greatest likelihood of extremes occur in the Midwestern Trough and Atlantic Ridge patterns. The greatest likelihood of extreme temperatures occurs in the Northeast Ridge. Some WTs are strongly associated with the phase of the North Atlantic Oscillation and Pacific–North America pattern, with frequency of occurrence for several WTs changing by more than a factor of 2. The two most common progressions between the WTs are one most frequent in September, Mid-Atlantic Trough to Northeast Ridge to Mid-Atlantic Trough, and one most frequent in mid-October–November, Midwestern Trough to Northeast Trough to Midwestern Trough. This seasonality allows for a daily WT-based distinction between early and late season. A preliminary trend analysis indicates an increase in early season WTs later in the season and a decrease in late season WTs earlier in the season; that is, a shift toward a longer period of warm season patterns and a shorter, delayed period of cold season patterns.

The ability of six CMIP6 models to reproduce the observed cold season teleconnection between tropical Indo-Pacific sea surface temperatures (SSTs) and precipitation in Southwest Asia, the coastal Middle East (CME), and Northern Pakistan and India (NPI) is examined. The 1979-2014 period is analyzed, to maximize observations over both the tropical ocean and the regions. Nine historical simulations for the same period are examined for each model, to account for the internal variability of the coupled system. The teleconnection is examined in terms of SSTs, precipitation, 200 hPa geopotential heights, and derived quantities.All the models capture some of the broadest features of the teleconnections, but there is a wide range in the ability of the models to reproduce the magnitude and details. The differences appear related to both the models’ ability to capture the details of the tropical variability, including the position and strength of the precipitation anomalies in the Indo-west Pacific, as well as the models’ ability to accurately propagate the tropically-forced response into the region. The teleconnections to the CME and NPI regions on the eastern and western margins, respectively, of the strongest signal are very similar in structure and have similar results, except that the models’ ability to reproduce the strength and details of the teleconnection is even more limited, consistent with their marginal locations and known influence of other modes of variability. For all three areas, the wide range in model ability to capture the leading teleconnection suggests caution in interpreting climate regional projections.

The Coupled Model Intercomparison Project Phase 6 (CMIP6) dataset is used to examine projected changes in temperature and precipitation over the United States (U.S.), Central America and the Caribbean. The changes are computed using an ensemble of 31 models for three future time slices (2021–2040, 2041–2060, and 2080–2099) relative to the reference period (1995–2014) under three Shared Socioeconomic Pathways (SSPs; SSP1-2.6, SSP2-4.5, and SSP5-8.5). The CMIP6 ensemble reproduces the observed annual cycle and distribution of mean annual temperature and precipitation with biases between − 0.93 and 1.27 °C and − 37.90 to 58.45%, respectively, for most of the region. However, modeled precipitation is too large over the western and Midwestern U.S. during winter and spring and over the North American monsoon region in summer, while too small over southern Central America. Temperature is projected to increase over the entire domain under all three SSPs, by as much as 6 °C under SSP5-8.5, and with more pronounced increases in the northern latitudes over the regions that receive snow in the present climate. Annual precipitation projections for the end of the twenty-frst century have more uncertainty, as expected, and exhibit a meridional dipole-like pattern, with precipitation increasing by 10–30% over much of the U.S. and decreasing by 10–40% over Central America and the Caribbean, especially over the monsoon region. Seasonally, precipitation over the eastern and central subregions is projected to increase during winter and spring and decrease during summer and autumn. Over the monsoon region and Central America, precipitation is projected to decrease in all seasons except autumn. The analysis was repeated on a subset of 9 models with the best performance in the reference period; however, no signifcant diference was found, suggesting that model bias is not strongly infuencing the projections. Universidad de Costa Rica/[805-B9-454]/UCR/Costa Rica National Science Foundation/[AGS-1849654]/NSF/Estados Unidos National Science Foundation/[AGS-1623912]/NSF/Estados Unidos Department of Energy/[2316‐T849‐08]/DOE/Estados Unidos National Oceanic and Atmospheric Administration/[2316‐T849‐08]/NOAA/Estados Unidos UCR::Vicerrectoría de Investigación::Unidades de Investigación::Ciencias Básicas::Centro de Investigaciones Geofísicas (CIGEFI) UCR::Vicerrectoría de Investigación::Unidades de Investigación::Ciencias Básicas::Centro de Investigación en Ciencias del Mar y Limnología (CIMAR)

Historical simulations from 14 models participating in phase 5 of the Coupled Model Intercomparison Project (CMIP5) are evaluated for their ability to reproduce observed precipitation in the northeastern United States and its associated circulation, with particular emphasis on extreme (top 1%) precipitation. The models are compared to observations in terms of the spatial variations of extreme precipitation, seasonal cycles of precipitation and extreme precipitation frequency and intensity, and extreme precipitation circulation regimes. The circulation regimes are identified using k-means clustering of 500-hPa geopotential heights on extreme precipitation days, in both observations and in the models. While all models capture an observed northwest-to-southeast gradient of precipitation intensity (reflected in the top 1% threshold), there are substantial differences from observations in the magnitude of the gradient. These differences tend to be more substantial for lower-resolution models. However, regardless of resolution, and despite a bias toward too-frequent precipitation, many of the models capture the seasonality of observed daily precipitation intensity, and the approximate magnitude and seasonality of observed extreme precipitation intensity. Many of the simulated extreme precipitation circulation patterns are visually similar to the set of observed patterns. However, the location and magnitude of specific troughs and ridges within the patterns, as well as the seasonality of the patterns, may differ substantially from the observed corresponding patterns. A series of metrics is developed based on the observed regional characteristics to facilitate comparison between models.

Sixteen historical simulations (1950–2014) from phase 6 of the Coupled Model Intercomparison Project (CMIP6) are compared to Northeast U.S. observed precipitation and extreme precipitation–related synoptic circulation. A set of metrics based on the regional climate is used to assess how realistically the models simulate the observed distribution and seasonality of extreme precipitation, as well as the synoptic patterns associated with extreme precipitation. These patterns are determined byk-means typing of 500-hPa geopotential heights on extreme precipitation days (top 1% of days with precipitation). The metrics are formulated to evaluate the models’ extreme precipitation spatial variations, seasonal frequency, and intensity; and for circulation, the fit to observed patterns, pattern seasonality, and pattern location of extreme precipitation. Based on the metrics, the models vary considerably in their ability to simulate different aspects of regional precipitation, and a realistic simulation of the seasonality and distribution of precipitation does not necessarily correspond to a realistic simulation of the circulation patterns (reflecting the underlying dynamics of the precipitation), and vice versa. This highlights the importance of assessing both precipitation and its associated circulation. While the models vary in their ability to reproduce observed results, in general the higher-resolution models score higher in terms of the metrics. Most models produce more frequent precipitation than that for observations, but capture the seasonality of precipitation intensity well, and capture at least several of the key characteristics of extreme precipitation–related circulation. These results do not appear to reflect a substantial improvement over a similar analysis of selected CMIP5 models.

The socioeconomic stability of the Central Asian Republics in the Amu Darya watershed is sensitive to drought. Activities related to agriculture employ a large fraction of the population and are responsible for at least one-fifth of the gross domestic products of Afghanistan, Tajikistan, and Turkmenistan. Toward building a predictive understanding that may be applied to drought early warning practices, the characteristics, precursors and potential predictability of agricultural drought in the Amu Darya watershed are examined in a large ensemble of Community Earth System Model version 1 simulations during 1920–2019. Agricultural drought is examined over Upper and Lower regions of the Amu Darya watershed, which have different mean hydroclimates, and is defined by 1-m soil moisture deficits lasting three or more months. The likelihood of drought onset and demise is phase-locked with the seasonal cycle of precipitation of each region, but with some notable differences. For the Upper region, drought onset and demise are three times more likely to occur during Autumn and Spring than other seasons. For the Lower region, drought onset and demise are three times more likely to occur during November–April than during Summer. Precipitation anomalies drive drought onset and demise during the climatological wet periods of both regions while temperatures play a smaller role. The probability of drought onset and demise is modulated by La Nina and El Nino, which control the interannual variability of precipitation over the Central Asian Republics during their wet seasons, indicating that the state of the El Nino Southern Oscillation serves as a key predictor of agricultural drought phase changes.

Globally, thermodynamics explains an increase in atmospheric water vapor with warming of around 7%/°C near to the surface. In contrast, global precipitation and evaporation are constrained by the Earth's energy balance to increase at ∼2-3%/°C. However, this rate of increase is suppressed by rapid atmospheric adjustments in response to greenhouse gases and absorbing aerosols that directly alter the atmospheric energy budget. Rapid adjustments to forcings, cooling effects from scattering aerosol, and observational uncertainty can explain why observed global precipitation responses are currently difficult to detect but are expected to emerge and accelerate as warming increases and aerosol forcing diminishes. Precipitation increases with warming are expected to be smaller over land than ocean due to limitations on moisture convergence, exacerbated by feedbacks and affected by rapid adjustments. Thermodynamic increases in atmospheric moisture fluxes amplify wet and dry events, driving an intensification of precipitation extremes. The rate of intensification can deviate from a simple thermodynamic response due to in-storm and larger-scale feedback processes, while changes in large-scale dynamics and catchment characteristics further modulate the frequency of flooding in response to precipitation increases. Changes in atmospheric circulation in response to radiative forcing and evolving surface temperature patterns are capable of dominating water cycle changes in some regions. Moreover, the direct impact of human activities on the water cycle through water abstraction, irrigation, and land use change is already a significant component of regional water cycle change and is expected to further increase in importance as water demand grows with global population.

Global and national climate assessments are comprehensive, authoritative sources of information about observed and projected climate changes and their impacts on society. These assessments follow well-known, accepted procedures to create credible, legitimate, salient sources of information for policy- and decision-making, build capacity for action, and educate the public. While there is a great deal of research on assessments at global and national scales, there is little research or guidance for assessment at the U.S. state scale. To address the need for guidance for state climate assessments (SCAs), the authors combined insights from the literature, firsthand experience with four SCAs, and interviews with individuals involved in 10 other SCAs to identify challenges, draw lessons, and point out future research needs to guide SCAs. SCAs are challenged by sparseness of literature and data, insufficient support for ongoing assessment, short time lines, limited funding, and surprisingly, little deliberate effort to address legitimacy as a concern. Lessons learned suggest SCAs should consider credibility, legitimacy, and salience as core criteria; happen at regular intervals; identify assessment scope, resource allocation, and trade-offs between generation of new knowledge, engagement, and communication up front; and leverage boundary organizations. Future research should build on ongoing efforts to advance assessments, examine the effectiveness of different SCA approaches, and seek to inform both broad and specific guidance for SCAs.

This paper surveys the current state of knowledge regarding large-scale meteorological patterns (LSMPs) associated with short-duration (less than 1 week) extreme precipitation events over North America. In contrast to teleconnections, which are typically defined based on the characteristic spatial variations of a meteorological field or on the remote circulation response to a known forcing, LSMPs are defined relative to the occurrence of a specific phenomenon—here, extreme precipitation—and with an emphasis on the synoptic scales that have a primary influence in individual events, have medium-range weather predictability, and are well-resolved in both weather and climate models. For the LSMP relationship with extreme precipitation, we consider the previous literature with respect to definitions and data, dynamical mechanisms, model representation, and climate change trends. There is considerable uncertainty in identifying extremes based on existing observational precipitation data and some limitations in analyzing the associated LSMPs in reanalysis data. Many different definitions of “extreme” are in use, making it difficult to directly compare different studies. Dynamically, several types of meteorological systems—extratropical cyclones, tropical cyclones, mesoscale convective systems, and mesohighs—and several mechanisms—fronts, atmospheric rivers, and orographic ascent—have been shown to be important aspects of extreme precipitation LSMPs. The extreme precipitation is often realized through mesoscale processes organized, enhanced, or triggered by the LSMP. Understanding of model representation, trends, and projections for LSMPs is at an early stage, although some promising analysis techniques have been identified and the LSMP perspective is useful for evaluating the model dynamics associated with extremes.

Hydrometeorological links to high streamflow events (HSFEs), 1950–2014, for the Mystic and Charles watersheds in the Metro Boston region of Massachusetts are examined. HSFEs are defined as one or more continuous days of streamflow above the mean annual maxima for a selected gauge in each basin. There are notable differences in the HSFEs for these two basins. HSFEs last from 1 to 3 days in the Mystic basin, while HSFEs for the Charles can last from 3 to 9 days. The majority of Mystic HSFEs are immediately preceded by extreme precipitation (occurring within 24 h), while only half of those for the Charles are preceded by extreme precipitation (in this case occurring 2–5 days earlier). While extreme precipitation events are often linked to HSFEs, other factors are often necessary in generating high streamflow, particularly for the Charles, as more than 50% of HSFEs occur at times when streamflow, soil moisture, and total precipitation are statistically above average for a period of at least 2 weeks before the HSFE. Approximately 52% and 80% of HSFEs occur from February to June for the Mystic and Charles, respectively, and these HSFEs are frequently linked to the passage of strong coastal lows, which produce extreme precipitation in the form of both rain and snow. For these coastal lows, Mystic HSFEs are linked to a strong moisture feed along the Massachusetts coastline and intense precipitation, while Charles HSFEs are linked to strong cyclones located off the Mid-Atlantic and longer-duration precipitation.

The spatial and temporal evolution of Middle East and southwest Asia (MESW) precipitation characteristics and the associated atmospheric circulation during times in which tropical eastern Indian Ocean precipitation is either enhanced or reduced associated with the Madden–Julian oscillation (MJO) is assessed. Using multiple estimates of both the observed precipitation and the MJO during 1981–2016, the evolution of MESW precipitation characteristics throughout November–April is examined in terms of monthly precipitation accumulation on precipitation days, the number of precipitation days, and the number of extreme precipitation days. MJO phases 2–4, during which eastern Indian Ocean precipitation is enhanced, and MJO phases 6–8, during which eastern Indian Ocean precipitation is reduced, are related, with significant decreases and increases in the number of precipitation days across MESW, respectively. The patterns of precipitation-day changes between MJO phases undergo noteworthy spatial and temporal evolutions across the boreal cold season that are influenced by the interaction between Rossby wave forcing by the MJO and seasonal changes in both the upper-level jet and moisture over the region. During December–January, the changes in precipitation days are found primarily over northern MESW, while during February–March, the changes in precipitation days are found primarily over southern MESW. Although the results identify an important sensitivity in the number of precipitation days over the MESW related to the MJO, the same sensitivity is not apparent in terms of the number of extreme precipitation days and, in particular, the amount of precipitation on a precipitation day.

The sensitivity of southwest Asia (25°–40°N, 40°–70°E) precipitation during the November–April rainy season to four types of El Niño–Southern Oscillation (ENSO) events, eastern Pacific (EP) and central Pacific (CP) El Niño and La Niña, is assessed using an ensemble of atmospheric model simulations forced by 1979–2015 boundary conditions. Sensitivity is assessed in terms of 1) the spread of precipitation across the ensemble members around the ensemble mean, 2) the probability of precipitation falling into the upper and lower terciles of the historical distribution, and 3) the relationship between the tropical atmosphere and southwest Asia precipitation during ENSO. During CP La Niña, the magnitude of the below-average mean precipitation exceeds the magnitude of the precipitation spread, thereby conditioning the probability of lower-tercile southwest Asia precipitation to greater than 70%. By contrast, EP La Niña does not alter the odds of southwest Asia precipitation terciles, as the magnitude of the near-zero mean precipitation is overwhelmed by the magnitude of the precipitation spread. EP and CP El Niño similarly result in above-average mean precipitation whose magnitude approaches the magnitude of the precipitation spread, thereby conditioning the probability of upper-tercile southwest Asia precipitation to around 50% region-wide. However, the notable effect of the precipitation spread during El Niño allows for a 20%–30% probability that the regional precipitation falls into the lower tercile. ENSO types simultaneously modify the probability of eastern Indian Ocean precipitation and southwest Asia precipitation, supporting the hypothesis that the tropical eastern Indian Ocean atmosphere serves as the medium by which ENSO forcing is communicated to southwest Asia.

Patterns of daily large-scale circulation associated with Northeast US extreme precipitation are identified using both k-means clustering (KMC) and Self-Organizing Maps (SOM) applied to tropopause height. The tropopause height provides a compact representation of the upper-tropospheric potential vorticity, which is closely related to the overall evolution and intensity of weather systems. Extreme precipitation is defined as the top 1% of daily wet-day observations at 35 Northeast stations, 1979–2008. KMC is applied on extreme precipitation days only, while the SOM algorithm is applied to all days in order to place the extreme results into the overall context of patterns for all days. Six tropopause patterns are identified through KMC for extreme day precipitation: a summertime tropopause ridge, a summertime shallow trough/ridge, a summertime shallow eastern US trough, a deeper wintertime eastern US trough, and two versions of a deep cold-weather trough located across the east-central US. Thirty SOM patterns for all days are identified. Results for all days show that 6 SOM patterns account for almost half of the extreme days, although extreme precipitation occurs in all SOM patterns. The same SOM patterns associated with extreme precipitation also routinely produce non-extreme precipitation; however, on extreme precipitation days the troughs, on average, are deeper and the downstream ridges more pronounced. Analysis of other fields associated with the large-scale patterns show various degrees of anomalously strong moisture transport preceding, and upward motion during, extreme precipitation events.

While a strong influence on cold season southwest Asia precipitation by Pacific sea surface temperatures (SSTs) has been previously established, the scarcity of southwest Asia precipitation observations prior to 1960 renders the region’s long-term precipitation history largely unknown. Here a large ensemble of atmospheric model simulations forced by observed time-varying boundary conditions for 1901–2012 is used to examine the long-term sensitivity of November–April southwest Asia precipitation to Pacific SSTs. It is first established that the models are able to reproduce the key features of regional variability during the best-observed 1960–2005 period and then the pre-1960 variability is investigated using the model simulations. During the 1960–2005 period, both the mean precipitation and the two leading modes of precipitation variability during November–April are reasonably simulated by the atmospheric models, which include the previously identified relationships with El Niño–Southern Oscillation (ENSO) and the multidecadal warming of Indo-Pacific SSTs. Over the full 1901–2012 period, there are notable variations in precipitation and in the strength of the SST influence. A long-term drying of the region is associated with the Indo-Pacific warming, with a nearly 10% reduction in westernmost southwest Asia precipitation during 1938–2012. The influence of ENSO on southwest Asia precipitation varied in strength throughout the period: strong prior to the 1950s, weak between 1950 and 1980, and strongest after the 1980s. These variations were not antisymmetric between ENSO phases. El Niño was persistently related with anomalously wet conditions throughout 1901–2012, whereas La Niña was not closely linked to precipitation anomalies prior to the 1970s but has been associated with exceptionally dry conditions thereafter.

This study examines U.S. Northeast daily precipitation and extreme precipitation characteristics for the 1979–2008 period, focusing on daily station data. Seasonal and spatial distribution, time scale, and relation to large-scale factors are examined. Both parametric and nonparametric extreme definitions are considered, and the top 1% of wet days is chosen as a balance between sample size and emphasis on tail distribution. The seasonal cycle of daily precipitation exhibits two distinct subregions: inland stations characterized by frequent precipitation that peaks in summer and coastal stations characterized by less frequent but more intense precipitation that peaks in late spring as well as early fall. For both subregions, the frequency of extreme precipitation is greatest in the warm season, while the intensity of extreme precipitation shows no distinct seasonal cycle. The majority of Northeast precipitation occurs as isolated 1-day events, while most extreme precipitation occurs on a single day embedded in 2–5-day precipitation events. On these extreme days, examination of hourly data shows that 3 h or less account for approximately 50% of daily accumulation. Northeast station precipitation extremes are not particularly spatially cohesive: over 50% of extreme events occur at single stations only, and 90% occur at only 1–3 stations concurrently. The majority of extreme days (75%–100%) are related to extratropical storms, except during September, when more than 50% of extremes are related to tropical storms. Storm tracks on extreme days are farther southwest and more clustered than for all storm-related precipitation days.

Southwest Asia, defined as the region containing the countries of Afghanistan, Iran, Iraq, and Pakistan, is water scarce and receives nearly 75% of its annual rainfall during the boreal cold season of November–April. The forcing of southwest Asia precipitation has been previously examined for the entire boreal cold season from the perspective of climate variability originating over the Atlantic and tropical Indo-Pacific Oceans. This study examines the intermonthly differences in precipitation variability over southwest Asia and the atmospheric conditions directly responsible in forcing monthly November–April precipitation. Seasonally averaged November–April precipitation over southwest Asia is significantly correlated with sea surface temperature (SST) patterns consistent with Pacific decadal variability (PDV), El Niño–Southern Oscillation (ENSO), and the long-term change of global SST (LT). In contrast, the precipitation variability during the individual months of November–April is unrelated and is correlated with SST signatures that include PDV, ENSO, and LT in different combinations. Despite strong intermonthly differences in precipitation variability during November–April over southwest Asia, similar atmospheric circulations, highlighted by a stationary equivalent barotropic Rossby wave centered over Iraq, force the monthly spatial distributions of precipitation. Tropospheric flow on the eastern side of the equivalent barotropic Rossby wave modifies the flux of moisture and advects the mean meridional temperature gradient, resulting in temperature advection that is balanced by vertical motions over southwest Asia. The forcing of monthly southwest Asia precipitation by equivalent barotropic Rossby waves is different from the forcing by baroclinic Rossby waves associated with tropically forced–only modes of climate variability.

Southwestern Asia, defined here as the domain bounded by 20°–40°N and 40°–70°E, which includes the nations of Iraq, Iran, Afghanistan, and Pakistan, is a water-stressed and semiarid region that receives roughly 75% of its annual rainfall during November–April. The November–April climate of southwestern Asia is strongly influenced by tropical Indo-Pacific variability on intraseasonal and interannual time scales, much of which can be attributed to sea surface temperature (SST) variations. The influences of lower-frequency SST variability on southwestern Asia climate during November–April Pacific decadal SST (PDSST) variability and the long-term trend in SST (LTSST) is examined. The U.S. Climate Variability and Predictability Program (CLIVAR) Drought Working Group forced global atmospheric climate models with PDSST and LTSST patterns, identified using empirical orthogonal functions, to show the steady atmospheric response to these modes of decadal to multidecadal SST variability. During November–April, LTSST forces an anticyclone over southwestern Asia, which results in reduced precipitation and increases in surface temperature. The precipitation and tropospheric circulation influences of LTSST are corroborated by independent observed precipitation and circulation datasets during 1901–2004. The decadal variations of southwestern Asia precipitation may be forced by PDSST variability, with two of the three models indicating that the cold phase of PDSST forces an anticyclone and precipitation reductions. However, there are intermodel circulation variations to PDSST that influence subregional precipitation patterns over the Middle East, southwestern Asia, and subtropical Asia. Changes in wintertime temperature and precipitation over southwestern Asia forced by LTSST and PDSST imply important changes to the land surface hydrology during the spring and summer.

The Arctic region has warmed more than twice as fast as the global average-a phenomenon known as Arctic amplification. The rapid Arctic warming has contributed to dramatic melting of Arctic sea ice and spring snow cover, at a pace greater than that simulated by climate models. These profound changes to the Arctic system have coincided with a period of ostensibly more frequent extreme weather events across the Northern Hemisphere mid-latitudes, including severe winters. The possibility of a link between Arctic change and mid-latitude weather has spurred research activities that reveal three potential dynamical pathways linking Arctic amplification to mid-latitude weather: changes in storm tracks, the jet stream, and planetary waves and their associated energy propagation. Through changes in these key atmospheric features, it is possible, in principle, for sea ice and snow cover to jointly influence mid-latitude weather. However, because of incomplete knowledge of how high-latitude climate change influences these phenomena, combined with sparse and short data records, and imperfect models, large uncertainties regarding the magnitude of such an influence remain. We conclude that improved process understanding, sustained and additional Arctic observations, and better coordinated modelling studies will be needed to advance our understanding of the influences on mid-latitude weather and extreme events.

Previous research has linked wintertime Arctic Oscillation (AO) variability to indices of Siberian snow cover and upward wave activity flux in the preceding fall season. Here, daily data are used to examine the surface and tropospheric processes that occur as the link between snow cover and upward forcing into the stratosphere develops. October Eurasian mean snow cover is found to be significantly related to sea level pressure (SLP) and to lower-stratosphere (100 hPa) meridional heat flux. Analysis of daily SLP and 100-hPa heat flux shows that in years with high October snow, the SLP is significantly higher from approximately 1 November to 15 December, and the 100-hPa heat flux is significantly increased with a two-week lag, from approximately 15 November to 31 December. During November–December, there are periods with upward wave activity flux extending coherently from the surface to the stratosphere, and these events occur nearly twice as often in high snow years compared to low snow years. The vertical structure of these events is a westward-tilting pattern of high eddy heights, with the largest normalized anomalies near the surface in the same region as the snow and SLP changes. These results suggest that high SLP develops in response to the snow cover and this higher pressure, in turn, provides part of the structure of a surface-to-stratosphere wave activity flux event, thus making full events more likely. Implications for improved winter forecasts exist through recognition of these precursor signals.

The differences in tropical Pacific sea surface temperature (SST) expressions of El Nino-Southern Oscillation (ENSO) events of the same phase have been linked with different global atmospheric circulation patterns. This study examines the dynamical forcing of precipitation during October–December (OND) and March–May (MAM) over East Africa and during December–March (DJFM) over Central-Southwest Asia for 1950–2010 associated with four tropical Pacific SST patterns characteristic of La Nina events, the cold phase of ENSO. The self-organizing map method along with a statistical distinguishability test was used to isolate La Nina events, and seasonal precipitation forcing was investigated in terms of the tropical overturning circulation and thermodynamic and moisture budgets. Recent La Nina events with strong opposing SST anomalies between the central and western Pacific Ocean (phases 3 and 4), force the strongest global circulation modifications and drought over the Northwest Indian Ocean Rim. Over East Africa during MAM and OND, subsidence is forced by an enhanced tropical overturning circulation and precipitation reductions are exacerbated by increases in moisture flux divergence. Over Central-Southwest Asia during DJFM, the thermodynamic forcing of subsidence is primarily responsible for precipitation reductions, with moisture flux divergence acting as a secondary mechanism to reduce precipitation. Eastern Pacific La Nina events in the absence of west Pacific SST anomalies (phases 1 and 2), are associated with weaker global teleconnections, particularly over the Indian Ocean Rim. The weak regional teleconnections result in statistically insignificant precipitation modifications over East Africa and Central-Southwest Asia.

The El Nino–Southern Oscillation (ENSO) is the leading mode of interannual variability, with global impacts on weather and climate that have seasonal predictability. Research on the link between interannual ENSO variability and the leading mode of intraseasonal variability, the Madden–Julian oscillation (MJO), has focused mainly on the role of MJO initiating or terminating ENSO. We use observational analysis and modeling to show that the MJO has an important simultaneous link to ENSO: strong MJO activity significantly weakens the atmospheric branch of ENSO. For weak MJO conditions relative to strong MJO conditions, the average magnitude of ENSO-associated tropical precipitation anomalies increases by 63%, and the strength of hemispheric teleconnections increases by 58%. Since the MJO has predictability beyond three weeks, the relationships shown here suggest that there may be subseasonal predictability of the ENSO teleconnections to continental circulation and precipitation.

Deep tropical convection over the Indian Ocean leads to intense diabatic heating, a main driver of the climate system. The Northern Hemisphere circulation and precipitation associated with intraseasonal and seasonal-to-interannual components of the leading pattern of Indian Ocean convection are investigated for November–April 1979–2008. The leading pattern of Indian Ocean convection is separated into intraseasonal and seasonal-to-interannual components by filtering an index of outgoing longwave radiation at 33–105 days and greater than 105 days, yielding Madden–Julian oscillation (MJO)- and El Niño–Southern Oscillation (ENSO)-influenced patterns, respectively. Observations and barotropic Rossby wave ray tracing experiments suggest that Indian Ocean convection can influence the ENSO-related hemispheric teleconnection pattern in addition to the regional Asian teleconnection. Equivalent barotropic circulation anomalies throughout the Northern Hemisphere subtropics are associated with both seasonal-to-interannual Indian Ocean convection and ENSO. The hemispheric teleconnection associated with seasonal-to-interannual Indian Ocean convection is investigated with ray tracing, which suggests that forcing over the Indian Ocean can propagate eastward across the hemisphere and back to Asia. The relationship between the seasonal-to-interannual component of Indian Ocean convection and ENSO is investigated in terms of a gradient in sea surface temperatures (SST) over the equatorial western Pacific Ocean. When the western Pacific SST gradient is strong during ENSO, strong Maritime Continent precipitation extends further westward into the Indian Ocean, which is accompanied by enhanced tropospheric Asian circulation, similar to the seasonal-to-interannual component of Indian Ocean convection. Analysis of the three strongest interannual convection seasons shows that the strong Indian Ocean pattern of ENSO can dominate individual seasons.

[1] The North American monsoon is accompanied by large-scale changes in circulation and precipitation over much of Mexico and the United States during summer. Here, the influence of the North American monsoon is analyzed in terms of midlevel changes to the thermodynamic energy equation, circulation, and precipitation associated with the monsoon onset in northwest Mexico, for the 1948–2004 period. In addition to the well-known strong increase in rising motion over the core region of the monsoon during the onset, there is also a decrease in upward motion over the northern Baja California Peninsula and into the southwest United States, directly in the path of monsoon development. This area of decreased vertical motion is linked to cold advection caused by the onset itself, as the Gill-Matsuno response to the monsoon precipitation thermodynamically interacts with the mean circulation. It is in this sense that we propose that the monsoon is self-limiting.

Northern Hemisphere circulations differ considerably between individual El Nino-Southern Oscillation events due to internal atmospheric variability and variation in the zonal location of sea surface temperature forcing over the tropical Pacific Ocean. This study examines the similarities between recent Northern Hemisphere droughts associated with La Nina events and anomalously warm tropical west Pacific sea surface temperatures during 1988–1989, 1998–2000, 2007–2008 and 2010–2011 in terms of the hemispheric-scale circulations and the regional forcing of precipitation over North America and Asia during the cold season of November through April. The continental precipitation reductions associated with recent central Pacific La Nina events were most severe over North America, eastern Africa, the Middle East and southwest Asia. High pressure dominated the entire Northern Hemisphere mid-latitudes and weakened and displaced storm tracks northward over North America into central Canada. Regionally over North America and Asia, the position of anomalous circulations within the zonal band of mid-latitude high pressure varied between each La Nina event. Over the northwestern and southeastern United States and southern Asia, the interactions of anomalous circulations resulted in consistent regional temperature advection, which was subsequently balanced by similar precipitation-modifying vertical motions. Over the central and northeastern United States, the spatial variation of anomalous circulations resulted in modest inter-seasonal temperature advection variations, which were balanced by varying vertical motion and precipitation patterns. Over the Middle East and eastern Africa, the divergence of moisture and the advection of dry air due to anomalous circulations enhanced each of the droughts.

The leading pattern of precipitation for the Indian Ocean, one of the most intense areas of rainfall on the globe, is calculated for November–April 1979–2008. The associated regional circulation and thermodynamic forcing of precipitation over Asia are examined at both intraseasonal and interannual time scales. The leading pattern is determined using both empirical orthogonal function analysis of monthly precipitation data and a closely related index of daily outgoing longwave radiation filtered into intraseasonal (33–105 days) and interannual (greater than 105 days) components. The leading pattern has a maximum in the tropical eastern Indian Ocean, and is closely associated with the Madden–Julian oscillation at intraseasonal time scales and related to the El Niño–Southern Oscillation at interannual time scales. Both time scales are associated with baroclinic Gill–Matsuno-like circulation responses extending over southern Asia, but the interannual component also has a strong equivalent barotropic circulation. Thermodynamically, both time scales are associated with cold temperature advection and subsidence over southwest Asia, with advection of the mean temperature by the anomalous wind more important at lower and midlevels and advection of the anomalous temperature by the mean wind more important at upper levels. For individual months, the intraseasonal variability can overwhelm the interannual variability. Enhanced Indian Ocean convection persisted for almost the entire 2007/08 season in association with severe drought over southwest Asia, but a strong intraseasonal signal in January 2008 reversed the pattern, resulting in damaging floods in the midst of drought.

The regional influence of the Indian monsoon onset is examined though observational analysis focusing on the Rodwell–Hoskins “monsoon-desert” hypothesis, which proposes that the strong diabatic heating associated with the monsoon produces a Gill-like Rossby wave response that thermodynamically interacts with the midlatitude westerly jet to produce subsidence and reduced rainfall to the west of the monsoon. Here, the authors analyze this proposed mechanism in terms of changes to the thermodynamic energy equation, regional circulation, and precipitation between the 10-day periods before and after the monsoon onset, for all onset dates in the 1958–2000 period. A Rossby-like response to the monsoon onset is clear in the observational data and is associated with horizontal temperature advection at midlevels as the westerlies intersect the warm temperature anomalies of the Rossby wave. Analysis of the thermodynamic equation verifies that the horizontal temperature advection is indeed balanced by subsidence over areas of North Africa, the Mediterranean, and the Middle East, and there is an associated decrease in precipitation over those regions. Despite the increased subsidence, diabatic heating changes are small in these regions so diabatic enhancement does not appear to be a primary factor in the response to the onset. This analysis also shows that the same processes that favor subsidence to the west of the monsoon also force rising motion over northern India and appear to be an important factor for the inland development of the monsoon. Comparison of strong and weak onsets further validates these relationships.

The links between daily ozone levels in Southern California and atmospheric circulation at regional and large scales are examined for July–September 1994–2001. The monitoring station in Pasadena is used as the primary basis for ozone analysis; comparison with other stations validates its representativeness for Southern California. Comparing the 10% of highest-ozone days with the 10% of lowest-ozone days for Pasadena reveals a large regional difference in 700-hPa vertical velocity over Southern California, consistent with changes to the ventilation and depth of the boundary layer. Analysis of the associated changes in midlevel (500 hPa) circulation reveals near-continental-scale differences, with very large modifications in the strength and position of the North American anticyclone. These links between daily ozone levels and regional and large-scale atmospheric circulation features suggest the potential for using currently available medium-range weather forecasts in ozone prediction.

While there is growing evidence that the main contribution to trends in U.S. precipitation occurs during fall, most studies of seasonal precipitation have focused on winter or summer. Here, the leading mode of fall precipitation variability over North America is isolated from multiple data sources and connected to a hemispheric-scale circulation pattern. Over North America, the leading mode of fall precipitation variability in both station-based and satellite-blended data is a tripole that links fall precipitation anomalies in southern Alaska, the central United States, and eastern Canada. This mode is part of a larger pattern of alternating wet and dry anomalies stretching from the western Pacific to the North Atlantic. Dynamically, the precipitation anomalies are closely associated with changes to regional-scale moisture transport that are, in turn, linked to two independently identified hemispheric-scale wave patterns that are one-quarter wavelength out of phase (i.e., in quadrature) and resemble the circumglobal teleconnection.

The warming trend in global surface temperatures over the last 40 yr is clear and consistent with anthropogenic increases in greenhouse gases. Over the last 2 decades, this trend appears to have accelerated. In contrast to this general behavior, however, here it is shown that trends during the boreal cold months in the recent period have developed a marked asymmetry between early winter and late winter for the Northern Hemisphere, with vigorous warming in October–December followed by a reversal to a neutral/cold trend in January–March. This observed asymmetry in the cold half of the boreal year is linked to a two-way stratosphere–troposphere interaction, which is strongest in the Northern Hemisphere during late winter and is related to variability in Eurasian land surface conditions during autumn. This link has been demonstrated for year-to-year variability and used to improve seasonal time-scale winter forecasts; here, this coupling is shown to strongly modulate the warming trend, with implications for decadal-scale temperature projections.

Warm season river flows in central Asia, which play an important role in local water resources and agriculture, are shown to be closely related to the regional-scale climate variability of the preceding cold season. The peak river flows occur in the warm season (April–August) and are highly correlated with the regional patterns of precipitation, moisture transport, and jet-level winds of the preceding cold season (November–March), demonstrating the importance of regional-scale variability in determining the snowpack that eventually drives the rivers. This regional variability is, in turn, strongly linked to large-scale climate variability and tropical sea surface temperatures (SSTs), with the circulation anomalies influencing precipitation through changes in moisture transport. The leading pattern of regional climate variability, as resolved in the operationally updated NCEP–NCAR reanalysis, can be used to make a skillful seasonal forecast for individual river flow stations. This ability to make predictions based on regional-scale climate data is of particular use in this data-sparse area of the world. The river flow is considered in terms of 24 stations in Uzbekistan and Tajikistan available for 1950–85, with two additional stations available for 1958–2003. These stations encompass the headwaters of the Amu Darya and Syr Darya, two of the main rivers of central Asia and the primary feeders of the catastrophically shrinking Aral Sea. Canonical correlation analysis (CCA) is used to forecast April–August flows based on the period 1950–85; cross-validated correlations exceed 0.5 for 10 of the stations, with a maximum of 0.71. Skill remains high even after 1985 for two stations withheld from the CCA: the correlation for 1986–2002 for the Syr Darya at Chinaz is 0.71, and the correlation for the Amu Darya at Kerki is 0.77. The forecast is also correlated to the normalized difference vegetation index (NDVI); maximum values exceed 0.8 at 8-km resolution, confirming the strong connection between hydrology and growing season vegetation in the region and further validating the forecast methodology.

Since 1980, the number of undernourished people in eastern and southern Africa has more than doubled. Rural development stalled and rural poverty expanded during the 1990s. Population growth remains very high, and declining per-capita agricultural capacity retards progress toward Millennium Development goals. Analyses of in situ station data and satellite observations of precipitation have identified another problematic trend: main growing-season rainfall receipts have diminished by ≈15% in food-insecure countries clustered along the western rim of the Indian Ocean. Occurring during the main growing seasons in poor countries dependent on rain-fed agriculture, these declines are societally dangerous. Will they persist or intensify? Tracing moisture deficits upstream to an anthropogenically warming Indian Ocean leads us to conclude that further rainfall declines are likely. We present analyses suggesting that warming in the central Indian Ocean disrupts onshore moisture transports, reducing continental rainfall. Thus, late 20th-century anthropogenic Indian Ocean warming has probably already produced societally dangerous climate change by creating drought and social disruption in some of the world's most fragile food economies. We quantify the potential impacts of the observed precipitation and agricultural capacity trends by modeling “millions of undernourished people” as a function of rainfall, population, cultivated area, seed, and fertilizer use. Persistence of current tendencies may result in a 50% increase in undernourished people by 2030. On the other hand, modest increases in per-capita agricultural productivity could more than offset the observed precipitation declines. Investing in agricultural development can help mitigate climate change while decreasing rural poverty and vulnerability.

A diagnostic of Northern Hemisphere winter extratropical stratosphere–troposphere interactions is presented to facilitate the study of stratosphere–troposphere coupling and to examine what might influence these interactions. The diagnostic is a multivariate EOF combining lower-stratospheric planetary wave activity flux in December with sea level pressure in January. This EOF analysis captures a strong linkage between the vertical component of lower-stratospheric wave activity over Eurasia and the subsequent development of hemisphere-wide surface circulation anomalies, which are strongly related to the Arctic Oscillation. Wintertime stratosphere–troposphere events picked out by this diagnostic often have a precursor in autumn: years with large October snow extent over Eurasia feature strong wintertime upward-propagating planetary wave pulses, a weaker wintertime polar vortex, and high geopotential heights in the wintertime polar troposphere. This provides further evidence for predictability of wintertime circulation based on autumnal snow extent over Eurasia. These results also raise the question of how the atmosphere will respond to a modified snow cover in a changing climate.

The dynamics and recent and possible future changes of the June–September rainfall associated with the North American Monsoon (NAM) are reviewed in this chapter. Our analysis as well as previous analyses of the trend in June–September precipitation from 1948 until 2010 indicate significant precipitation increases over New Mexico and the core NAM region, and significant precipitation decreases over southwest Mexico. The trends in June–September precipitation have been forced by anomalous cyclonic circulation centered at 15°N latitude over the eastern Pacific Ocean. The anomalous cyclonic circulation is responsible for changes in the flux of moisture and the divergence of moisture flux within the core NAM region. Future climate projections using the Coupled Model Intercomparison Project Phase 5 (CMIP5) models, as part of the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report (AR5), support the observed analyses of a later shift in the monsoon season in the presence of increased greenhouse gas concentrations in the atmosphere under the RCP8.5 scenario. The CMIP5 models under the RCP8.5 scenario predict significant NAM-related rainfall decreases during June and July and predict significant NAM-related rainfall increases during September and October.

Analysis of daily observations shows that wintertime (November–April) precipitation over Southwest Asia is modulated by Madden–Julian oscillation (MJO) activity in the eastern Indian Ocean, with strength comparable to the interannual variability. Daily outgoing longwave radiation (OLR) for 1979–2001 is used to provide a long and consistent, but indirect, estimate of precipitation, and daily records from 13 stations in Afghanistan reporting at least 50% of the time for 1979–85 are used to provide direct, but shorter and irregularly reported, precipitation data. In the station data, for the average of all available stations, there is a 23% increase in daily precipitation relative to the mean when the phase of the MJO is negative (suppressed tropical convection in the eastern Indian Ocean), and a corresponding decrease when the MJO is positive. The distribution of extremes is also affected such that the 10 wettest days all occur during the negative MJO phase. The longer record of OLR data indicates that the effect of the MJO is quite consistent from year to year, with the anomalies averaged over Southwest Asia more negative (indicating more rain) for the negative phase of the MJO for each of the 22 yr in the record. Additionally, in 9 of the 22 yr the average influence of the MJO is larger than the interannual variability (e.g., the relationship results in anomalously wet periods even in dry years and vice versa). Examination of NCEP–NCAR reanalysis data shows that the MJO modifies both the local jet structure and, through changes to the thermodynamic balance, the vertical motion field over Southwest Asia, consistent with the observed modulation of the associated synoptic precipitation. A simple persistence scheme for forecasting the sign of the MJO suggests that the modulation of Southwest Asia precipitation may be predictable for 3-week periods. Finally, analysis of changes in storm evolution in Southwest Asia due to the influence of the MJO shows a large difference in strength as the storms move over Afghanistan, with apparent relevance for the flooding event of 12–13 April 2002.

The North Atlantic Oscillation (NAO) and the closely related Arctic Oscillation (AO) strongly affect Northern Hemisphere (NH) surface temperatures with patterns reported similar to the global warming trend. The NAO and AO were in a positive trend for much of the 1970s and 1980s with historic highs in the early 1990s, and it has been suggested that they contributed significantly to the global warming signal. The trends in standard indices of the AO, NAO, and NH average surface temperature for December–February, 1950–2004, and the associated patterns in surface temperature anomalies are examined. Also analyzed are factors previously identified as relating to the NAO, AO, and their positive trend: North Atlantic sea surface temperatures (SSTs), Indo–Pacific warm pool SSTs, stratospheric circulation, and Eurasian snow cover. Recently, the NAO and AO indices have been decreasing; when these data are included, the overall trends for the past 30 years are weak to nonexistent and are strongly dependent on the choice of start and end date. In clear distinction, the wintertime hemispheric warming trend has been vigorous and consistent throughout the entire period. When considered for the whole hemisphere, the NAO/AO patterns can also be distinguished from the trend pattern. Thus the December–February warming trend may be distinguished from the AO and NAO in terms of the strength, consistency, and pattern of the trend. These results are insensitive to choice of index or dataset. While the NAO and AO may contribute to hemispheric and regional warming for multiyear periods, these differences suggest that the large-scale features of the global warming trend over the last 30 years are unrelated to the AO and NAO. The related factors may also be clearly distinguished, with warm pool SSTs linked to the warming trend, while the others are linked to the NAO and AO.

Severe drought is a notable feature of the hydrology of central Southwest (CSW) Asia. Although studies have linked the region's interannual precipitation variability to remote forcings that include East Asia jet stream variability and western Pacific tropical convection, atmospheric general circulation models (GCMs) forced by observed sea-surface temperatures demonstrate little skill in simulating interannual precipitation variability in this region. Here, statistical methods of correcting systematic errors in GCM simulations of CSW Asia precipitation are investigated. Canonical correlation analysis is used to identify model fields related to observed precipitation anomaly patterns. These relationships are then used to predict observed precipitation anomalies. This approach is applied to the ECHAM 4.5 GCM using regional precipitation, upper-level winds and western Pacific tropical precipitation as predictors of observed CSW Asia precipitation anomalies. The statistical corrections improve the GCM precipitation simulations, resulting in modest, but statistically significant, cross-validated skill in simulating CSW Asia precipitation anomalies. Applying the procedure to hindcasts with persisted sea-surface temperatures gives lower, but statistically significant, precipitation correlations in the region along the Hindu Kush mountain range. Copyright © 2003 Royal Meteorological Society

Severe drought over the past three years (1998‐2001), in combination with the effects of protracted sociopolitical disruption, has led to widespread famine affecting over 60 million people in central and southwest (CSW) Asia. Here both a regional and a large-scale mode of climate variability are documented that, together, suggest a possible forcing mechanism for the drought. During the boreal cold season, an inverse relationship exists between precipitation anomalies in the eastern Indian Ocean and CSW Asia. Suppression of precipitation over CSW Asia is consistent with interaction between local synoptic storms and wave energy generated by enhanced tropical rainfall in the eastern Indian Ocean. This regional out-of-phase precipitation relationship is

Two distinct low-frequency fluctuations are suggested from a joint frequency domain analysis of the Pacific Ocean (30°S-60°N) sea surface temperature (SST) and sea level pressure (SLP). The lowest frequency signal reveals a spatially coherent interdecadal evolution, In-phase SST and SLP anomalies are found along the subarctic frontal zone (SAFZ). It is symmetric about the equator, with tropical SST anomalies peaking near 15° latitudes in the eastern Pacific. The other low-frequency signal reveals a spatially coherent decadal evolution. It is primarily a low-latitude phenomenon. Tropical SST anomalies peak in the central equatorial ocean with evidence of atmospheric teleconnections. These interdecadal and decadal signals join the ENSO and quasi-biennial signals in determining dominant patterns of Pacific Ocean natural climate variability. Relative phasing and location of the SST and SLP anomalies for the decadal, ENSO, and the quasi-biennial signals, are similar to one another but significantly different from that of the interdecadal signal.

The relationship between the three primary modes of Pacific sea surface temperature (SST) variability—the El Nino–Southern Oscillation (ENSO), the Pacific decadal oscillation, and the North Pacific mode—and U.S. warm season hydroclimate is examined. In addition to precipitation, drought and stream flow data are analyzed to provide a comprehensive picture of the lower-frequency components of hydrologic variability. ENSO and the two decadal modes are extracted from a single unfiltered analysis, allowing a direct intercomparison of the modal structures and continental linkages. Both decadal modes have signals in the North Pacific, but the North Pacific mode captures most of the local variability. A summertime U.S. hydroclimatic signal is associated with all three SST modes, with the linkages of the two decadal modes comparable in strength to that of ENSO. The three SST variability modes also appear to play a significant role in long-term U.S. drought events. In particular, the northeastern drought o...

The two leading patterns of Pacific decadal sea surface temperature (SST) variability are strongly linked to large-scale patterns of warm-season drought and streamflow in the United States, recent analysis shows. The predictive potential of this link may contribute to the development of warm-season hydroclimate forecasts in the United States. Understanding of low-frequency variations in drought and streamflow would be important for both agriculture and water resources management. The two leading patterns are what we call the Pacific Decadal Oscillation (PDO) and the North Pacific mode. Their link with drought and streamflow patterns was notably expressed in the 1960s when severe drought in the northeast (the 1962–66 “Northeastern” drought) and exceptional positive SST anomalies in the North Pacific Ocean (Figures 1a, 1b) both occurred. Analysis of upper tropospheric circulation anomalies showed the North Pacific to be a source region of wave activity affecting the drought area in these summers. The anomalous circulation was vertically coherent and opposed the climatological low-level moisture inflow over the eastern United States associated with the western extension of the Bermuda High.

A dynamically oriented description of the North American summer monsoon system, which encompasses the Mexican monsoon and the associated large-scale circulation over the continental United States, is provided by developing an evolution climatology of the precipitation, tropospheric circulation, moisture fluxes, diabatic heating, convective environment, and the adjoining basin SSTs. A distinguishing aspect of this study is the amount of independent data analyzed, such as the newly available European Centre for Medium-Range Weather Forecasts (ECMWF) reanalyses, the National Centers for Environmental Prediction (NCEP) reanalyses, both satellite-derived and station data–based precipitation estimates, and the heating diagnosed from both reanalyses. This also provides a preliminary evaluation and comparison of the newly available NCEP and ECMWF reanalyses at the regional level, including the model-generated precipitation and heating distributions. The principal findings are the following. The accompani...

Global climate models (GCMs) are the fundamental drivers of regional climate-change projections (IPCC 2007). GCMs allow us to characterize changes in atmospheric circulation associated with human causes at global and continental scales. However, because of the planetary scope of the GCMs, their resolution, or level of detail, is somewhat coarse. A typical GCM grid spacing is about 62 miles (100 km) or greater, which is inadequate for creating projections and evaluating impacts of climate change at a regional scale. Thus, a “downscaling” procedure is needed to provide finer spatial detail of the model results.