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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.

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.

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.

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.

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.

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.

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.

Drought affects virtually every region of the world, and potential shifts in its character in a changing climate are a major concern. This article presents a synthesis of current understanding of meteorological drought, with a focus on the large-scale controls on precipitation afforded by sea surface temperature (SST) anomalies, land surface feedbacks, and radiative forcings. The synthesis is primarily based on regionally focused articles submitted to the Global Drought Information System (GDIS) collection together with new results from a suite of atmospheric general circulation model experiments intended to integrate those studies into a coherent view of drought worldwide. On interannual time scales, the preeminence of ENSO as a driver of meteorological drought throughout much of the Americas, eastern Asia, Australia, and the Maritime Continent is now well established, whereas in other regions (e.g., Europe, Africa, and India), the response to ENSO is more ephemeral or nonexistent. Northern Eurasia, central Europe, and central and eastern Canada stand out as regions with few SST-forced impacts on precipitation on interannual time scales. Decadal changes in SST appear to be a major factor in the occurrence of long-term drought, as highlighted by apparent impacts on precipitation of the late 1990s “climate shifts” in the Pacific and Atlantic SST. Key remaining research challenges include (i) better quantification of unforced and forced atmospheric variability as well as land–atmosphere feedbacks, (ii) better understanding of the physical basis for the leading modes of climate variability and their predictability, and (iii) quantification of the relative contributions of internal decadal SST variability and forced climate change to long-term drought., The various contributions to this paper were made possible by the support of the host organizations of the coauthors, as noted in the acknowledgments of the contributing Global Drought Information System (GDIS) special collection papers. The GDIS effort is sponsored and supported by the World Climate Research Programme (WCRP: CLIVAR andGEWEX) and various partner organizations including the National Oceanic and Atmospheric Administration (NOAA), the National Aeronautics and Space Administration (NASA), the National Integrated Drought Information System (NIDIS), the World Meteorological Organization (WMO), the U.S. CLIVAR program, the Group on Earth Observations (GEO), the European Commission JointResearch Centre (JRC), the National Science Foundation (NSF), and the European Space Agency (ESA)–European Space Research Institute (ESRIN). Support for the overall development of this synthesis article was provided by NASA’sModeling, Analysis and Prediction Program. The GLDAS-2 data used in this study were acquired as part of the mission of NASA’s Earth Science Division and archived and distributed by the Goddard Earth Sciences (GES) Data and Information Services Center (DISC).

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.

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.

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 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

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...

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...