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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.

Northeastern US heat waves have usually been considered in terms of a single circulation pattern, the high-pressure circulation typical of most heat waves occurring in other parts of the world. However, k-means clustering analysis from 1980–2018 shows there are four distinct patterns of Northeast heat wave daily circulation, each of which has its own seasonality, heat-producing mechanisms (associated moisture, subsidence, and temperature advection), and impact on electricity demand. Monthly analysis shows statistically-significant positive trends occur in late summer for two of the patterns and early summer for a third pattern, while the fourth pattern shows a statistically significant negative trend in early summer. These results demonstrate that heat waves in a particular geographic area can be initiated and maintained by a variety of mechanisms, resulting in heat wave types with distinct impacts and potential links to climate change, and that pattern analysis is an effective tool to distinguish these differences.

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.

The January 2022 Hunga Tonga-Hunga Ha'apai eruption was one of the most explosive volcanic events of the modern era(1,2), producing a vertical plume that peaked more than 50 km above the Earth(3). The initial explosion and subsequent plume triggered atmospheric waves that propagated around the world multiple times(4). A global-scale wave response of this magnitude from a single source has not previously been observed. Here we show the details of this response, using a comprehensive set of satellite and ground-based observations to quantify it from surface to ionosphere. A broad spectrum of waves was triggered by the initial explosion, including Lamb waves(5,6) propagating at phase speeds of 318.2 +/- 6 m s(-1) at surface level and between 308 +/- 5 to 319 +/- 4 m s(-1) in the stratosphere, and gravity waves(7) propagating at 238 +/- 3 to 269 +/- 3 m s(-1) in the stratosphere. Gravity waves at sub-ionospheric heights have not previously been observed propagating at this speed or over the whole Earth from a single source(8,9). Latent heat release from the plume remained the most significant individual gravity wave source worldwide for more than 12 h, producing circular wavefronts visible across the Pacific basin in satellite observations. A single source dominating such a large region is also unique in the observational record. The Hunga Tonga eruption represents a key natural experiment in how the atmosphere responds to a sudden point-source-driven state change, which will be of use for improving weather and climate models. Royal Society University Research Fellowship [UF160545]; NERC [NE/S00985X/1]; NASA Heliophysics DRIVE Science Center [80NSSC20K0628]; NERC Fellowship [NE/P006450/1]; European Research Council (ERC) under the European Union [742909]; NASA AIM Small Explorer Program [NAS5-03132] Published version C.J.W. is supported by a Royal Society University Research Fellowship, reference no. UF160545. C.J.W. and N.P.H. are supported by NERC grant no. NE/S00985X/1. M.J.A. and C.E.R. were supported by a NASA Heliophysics DRIVE Science Center (grant no. 80NSSC20K0628). C.N.M. was supported by NERC Fellowship NE/P006450/1 for work underpinning this research. C.C. and M.B. received funding from the European Research Council (ERC) under the European Union's Horizon 2020 and innovation programme (grant agreement no. 742909, IASI-FT advanced ERC grant). J.C. was supported by the NASA AIM Small Explorer Program, contract no. NAS5-03132. The Australian Institute of Marine Sciences, the Australian Bureau of Meteorology and the Tongan Met Office are thanked for provision of surface station pressure data. We thank I. Krisch, N. Kaifler and B. Kaifler (all at the DLR, Oberpfaffenhofen, Germany) for assistance with preliminary data analysis, A. Boynard (LATMOS, Paris, France) for providing the H2O IASI data, S. Proud (RAL) for correcting some details of the geostationary imager measurements and E. Gryspeerdt (Imperial College, London, UK) for independent confirmation of the Lamb wave trigger time.

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.

The extratropical stratosphere in boreal winter is characterized by a strong circumpolar westerly jet, confining the coldest temperatures at high latitudes. The jet, referred to as the stratospheric polar vortex, is predominantly zonal and centered around the pole; however, it does exhibit large variability in wind speed and location. Previous studies showed that a weak stratospheric polar vortex can lead to cold-air outbreaks in the midlatitudes, but the exact relationships and mechanisms are unclear. Particularly, it is unclear whether stratospheric variability has contributed to the observed anomalous cooling trends in midlatitude Eurasia. Using hierarchical clustering, we show that over the last 37 years, the frequency of weak vortex states in mid- to late winter (January and February) has increased, which was accompanied by subsequent cold extremes in midlatitude Eurasia. For this region, 60% of the observed cooling in the era of Arctic amplification, that is, since 1990, can be explained by the increased frequency of weak stratospheric polar vortex states, a number that increases to almost 80% when El Niño–Southern Oscillation (ENSO) variability is included as well.

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.

Previous work has identified six large-scale meteorological patterns (LSMPs) of dynamic tropopause height associated with extreme precipitation over the Northeast US, with extreme precipitation defined as the top 1% of daily station precipitation. Here, we examine the three-dimensional structure of the tropopause LSMPs in terms of circulation and factors relevant to precipitation, including moisture, stability, and synoptic mechanisms associated with lifting. Within each pattern, the link between the different factors and extreme precipitation is further investigated by comparing the relative strength of the factors between days with and without the occurrence of extreme precipitation. The six tropopause LSMPs include two ridge patterns, two eastern US troughs, and two troughs centered over the Ohio Valley, with a strong seasonality associated with each pattern. Extreme precipitation in the ridge patterns is associated with both convective mechanisms (instability combined with moisture transport from the Great Lakes and Western Atlantic) and synoptic forcing related to Great Lakes storm tracks and embedded shortwaves. Extreme precipitation associated with eastern US troughs involves intense southerly moisture transport and strong quasi-geostrophic forcing of vertical velocity. Ohio Valley troughs are associated with warm fronts and intense warm conveyor belts that deliver large amounts of moisture ahead of storms, but little direct quasi-geostrophic forcing. Factors that show the largest difference between days with and without extreme precipitation include integrated moisture transport, low-level moisture convergence, warm conveyor belts, and quasi-geostrophic forcing, with the relative importance varying between patterns.

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.

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 method of k-means cluster analysis is applied to U.S. wintertime daily 850-hPa winds across the Northeast. The resulting weather patterns are analyzed in terms of duration, station, gridded precipitation, storm tracks, and climate teleconnections. Five distinct weather patterns are identified. Weather type (WT) 1 is characterized by a ridge over the western Atlantic and positive precipitation anomalies as far north as the Great Lakes; WT2, by a trough along the eastern United States and positive precipitation anomalies into southern New England; WT3, by a trough over the western Atlantic and negative precipitation anomalies along much of the U.S. East Coast; WT4, by a trough east of Newfoundland and negative precipitation anomalies along parts of the U.S. East Coast; and WT5, by a broad, shallow trough over southeastern Canada and negative precipitation anomalies over the entire U.S. East Coast. WT5 and WT1 are the most persistent, while WT2 typically progresses quickly to WT3 and then to WT4. Based on mean station precipitation in the northeastern United States, most precipitation occurs in WT2 and WT3, with the least in WT1 and WT4. Extreme precipitation occurs most frequently in WT2. Storm tracks show that WT2 and WT3 are associated with coastal storms, while WT2 is also associated with Great Lakes storms. Teleconnections are linked with a change in WT frequency by more than a factor of 2 in several cases: for the North Atlantic Oscillation (NAO) in WT1 and WT4 and for the Pacific–North American (PNA) pattern in WT1 and WT3.

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.