Search

This paper provides an updated analysis of observed changes in extreme precipitation using high-quality station data up to 2018. We examine changes in extreme precipitation represented by annual maxima of 1-day (Rx1day) and 5-day (Rx5day) precipitation accumulations at different spatial scales and attempt to address whether the signal in extreme precipitation has strengthened with several years of additional observations. Extreme precipitation has increased at about two-thirds of stations and the percentage of stations with significantly increasing trends is significantly larger than that can be expected by chance for the globe, continents including Asia, Europe, and North America, and regions including central North America, eastern North America, northern Central America, northern Europe, the Russian Far East, eastern central Asia, and East Asia. The percentage of stations with significantly decreasing trends is not different from that expected by chance. Fitting extreme precipitation to generalized extreme value distributions with global mean surface temperature (GMST) as a covariate reaffirms the statistically significant connections between extreme precipitation and temperature. The global median sensitivity, percentage change in extreme precipitation per 1 K increase in GMST is 6.6% (5.1% to 8.2%; 5%–95% confidence interval) for Rx1day and is slightly smaller at 5.7% (5.0% to 8.0%) for Rx5day. The comparison of results based on observations ending in 2018 with those from data ending in 2000–09 shows a consistent median rate of increase, but a larger percentage of stations with statistically significant increasing trends, indicating an increase in the detectability of extreme precipitation intensification, likely due to the use of longer records. [ABSTRACT FROM AUTHOR]

This paper describes the development and analysis of an objective climatology of warm and cold fronts over North America from 1979 to 2018. Fronts are detected by a convolutional neural network (CNN), trained to emulate fronts drawn by human meteorologists. Predictors for the CNN are surface and 850-hPa fields of temperature, specific humidity, and vector wind from the ERA5 reanalysis. Gridded probabilities from the CNN are converted to 2D frontal regions, which are used to create the climatology. Overall, warm and cold fronts are most common in the Pacific and Atlantic cyclone tracks and the lee of the Rockies. In contrast with prior research, we find that the activity of warm and cold fronts is significantly modulated by the phase and intensity of El Niño–Southern Oscillation. The influence of El Niño is significant for winter warm fronts, winter cold fronts, and spring cold fronts, with activity decreasing over the continental United States and shifting northward with the Pacific and Atlantic cyclone tracks. Long-term trends are generally not significant, although we find a poleward shift in frontal activity during the winter and spring, consistent with prior research. We also identify a number of regional patterns, such as a significant long-term increase in warm fronts in the eastern tropical Pacific Ocean, which are characterized almost entirely by moisture gradients rather than temperature gradients. [ABSTRACT FROM AUTHOR]

The assumption of a stationary global signal linked to El Niño–Southern Oscillation (ENSO) events is often used in paleo-ENSO proxy data interpretation. This paper attempts to investigate whether the assumption is valid during the last glacial maximum (LGM) over the region 60°S–90°N, 60°E−60°W. Using four models within phase 3 of the Paleoclimate Modeling Intercomparison Project framework that well reproduce ENSO-induced variabilities, differences from the preindustrial period to LGM in the ENSO-related sea surface temperature pattern and its impacts are investigated. Compared to the preindustrial period, the ENSO impacts are revealed to weaken and shift eastward during the LGM. According to multimodel medians, ENSO impacts on precipitation and near-surface air temperature are attenuated over most regions of concern, with percentage changes in both parameters averaging −21% for the whole region; the ENSO-induced Pacific–North America (PNA) teleconnection pattern is weakened, manifested by the 41% diminished center over the North Pacific and the almost vanished activity centers over the continent. Spatially, there is a zonal contraction of 13° for the sea surface warming of ENSO, as well as eastward migration over 10° for the ENSO-induced positive precipitation anomaly center over the tropical Pacific and the PNA teleconnection pattern outside the tropics. The aforementioned changes are linked to the altered climatic background during the LGM, which features a 16° eastward shift for the Pacific Walker circulation rising branch and a weakened waveguide in the midlatitudes. The results suggest that the hypothesis of stationary ENSO impacts should be applied cautiously to the past. [ABSTRACT FROM AUTHOR]

The wintertime Pacific–North American (PNA) teleconnection pattern has previously been shown to influence springtime snow conditions over portions of North America. This paper develops a more complete physical understanding of this linkage across the continent, using a recently released long-term, continental-scale gridded North American snow depth dataset and the 40-yr European Centre for Medium-Range Weather Forecasts Re-Analysis data. An empirical orthogonal function–based filtering process is used to identify and isolate the interannual snow depth variations associated with PNA. Then linear and partial correlations are employed to investigate the physical mechanisms that link winter PNA with spring snow depth. In the positive phase of PNA, the enhanced PNA pressure centers lead to warmer temperatures over northwestern North America and less precipitation at midlatitudes. The temperature and precipitation pathways act independently and in distinct geographical regions, and together they serve to reduce winter snow depth across much of North America. Winter anomalies in the snow depth field then tend to persist into spring. Dynamic mechanisms responsible for the PNA-influenced North American precipitation and temperature anomalies, involving moisture transport and cold air intrusions, are confirmed in this study and also extended to continental snow depth anomalies. [ABSTRACT FROM AUTHOR]

An important goal of the Climate Variability and Predictability (CLIVAR) research on the American monsoon systems is to determine the sources and limits of predictability of warm season precipitation, with emphasis on weekly to interannual time scales. This paper reviews recent progress in the understanding of the American monsoon systems and identifies some of the future challenges that remain to improve warm season climate prediction. Much of the recent progress is derived from complementary international programs in North and South America, namely, the North American Monsoon Experiment (NAME) and the Monsoon Experiment South America (MESA), with the following common objectives: 1) to understand the key components of the American monsoon systems and their variability, 2) to determine the role of these systems in the global water cycle, 3) to improve observational datasets, and 4) to improve simulation and monthly-to-seasonal prediction of the monsoons and regional water resources. Among the recent observational advances highlighted in this paper are new insights into moisture transport processes, description of the structure and variability of the South American low-level jet, and resolution of the diurnal cycle of precipitation in the core monsoon regions. NAME and MESA are also driving major efforts in model development and hydrologic applications. Incorporated into the postfield phases of these projects are assessments of atmosphere–land surface interactions and model-based climate predictability experiments. As CLIVAR research on American monsoon systems evolves, a unified view of the climatic processes modulating continental warm season precipitation is beginning to emerge. [ABSTRACT FROM AUTHOR]

Two questions are addressed in this paper: whether ENSO can be adequately characterized by simple, seasonally invariant indices and whether the time series of a single component-SST or OLR-provides a sufficiently complete representation of ENSO for the purpose of quantifying U.S. climate impacts. Here, ENSO is defined as the leading mode of seasonally varying canonical correlation analysis (CCA) between anomalies of tropical Pacific SST and outgoing longwave radiation (OLR). The CCA reveals that the strongest regions of coupling are mostly invariant as a function of season and correspond to an OLR region located in the central Pacific Ocean (CP-OLR) and an SST region in the eastern Pacific that coincides with the Niño-3 region. In a linear context, the authors explore whether the use of a combined index of these SST and OLR regions explains additional variance of North American temperature and precipitation anomalies beyond that described by using a single index alone. Certain seasons and regions benefit from the use of a combined index. In particular, a combined index describes more variability in winter/spring precipitation and summer temperature. [ABSTRACT FROM AUTHOR]

Future Arctic sea ice loss has a known impact on Arctic amplification (AA) and mean atmospheric circulation. Furthermore, several studies have shown it leads to a decreased variance in temperature over North America. In this study, we analyze results from two fully coupled Community Earth System Model (CESM) Whole Atmosphere Community Climate Model (WACCM4) simulations with sea ice nudged to either the ensemble mean of WACCM historical runs averaged over the 1980–99 period for the control (CTL) or projected RCP8.5 values over the 2080–99 period for the experiment (EXP). Dominant large-scale meteorological patterns (LSMPs) are then identified using self-organizing maps applied to winter daily 500-hPa geopotential height anomalies ( Z 500 ′ ) over North America. We investigate how sea ice loss (EXP − CTL) impacts the frequency of these LSMPs and, through composite analysis, the sensible weather associated with them. We find differences in LSMP frequency but no change in residency time, indicating there is no stagnation of the flow with sea ice loss. Sea ice loss also acts to de-amplify and/or shift the Z 500 ′ that characterize these LSMPs and their associated anomalies in potential temperature at 850 hPa. Impacts on precipitation anomalies are more localized and consistent with changes in anomalous sea level pressure. With this LSMP framework we provide new mechanistic insights, demonstrating a role for thermodynamic, dynamic, and diabatic processes in sea ice impacts on atmospheric variability. Understanding these processes from a synoptic perspective is critical as some LSMPs play an outsized role in producing the mean response to Arctic sea ice loss. Significance Statement: The goal of this study is to understand how future Arctic sea ice loss might impact daily weather patterns over North America. We use a global climate model to produce one set of simulations where sea ice is similar to present conditions and another that represents conditions at the end of the twenty-first century. Daily patterns in large-scale circulation at roughly 5.5 km in altitude are then identified using a machine learning method. We find that sea ice loss tends to de-amplify these patterns and their associated impacts on temperature nearer the surface. Our methodology allows us to probe more deeply into the mechanisms responsible for these changes, which provides a new way to understand how sea ice loss can impact the daily weather we experience. [ABSTRACT FROM AUTHOR]

The mid-Pliocene (approximately 3.3–3.0 Ma) was one of the past geological warm periods. Since this past warmer climate was in many respects comparable to near future warming projections, how the regional monsoonal rainfall changed during the mid-Pliocene is an important scientific and socioeconomic concern. Based on phase 2 of the Pliocene Model Intercomparison Project (PlioMIP2), this work examines the simulated changes of Sahel summer rainfall during the mid-Pliocene. The results show the considerable intermodel uncertainty of the simulated mid-Pliocene Sahel rainfall changes in the PlioMIP2 multimodel ensemble, which is due to the uncertainties of both the simulated dynamic and thermodynamic responses to this past warmer climate. In particular, we find that the intermodel spread in the simulated northern North American warming is a major source of the uncertainty of the mid-Pliocene Sahel summer rainfall changes through two processes. One is a direct dynamic process: a stronger warming over northern North America could enhance the meridional temperature gradient between the extratropical and tropical regions, inducing an interhemisphere energy imbalance of the atmosphere. This could lead to a northward shift of the intertropical convergence zone, strengthening the Western African summer monsoon (WASM) circulation and Sahel summer rainfall. Another is an indirect thermodynamic process: the strengthened WASM circulation could further induce anomalous moisture convergence over the Sahel region, increasing local atmospheric moisture at the low-level troposphere, in favor of a wetter Sahel. Our results suggest that an improved warming simulation over northern North America is essential for the hydrological cycle simulation around the Sahel in the mid-Pliocene warmer climate. Significance Statement: The Sahel summer rainfall change in a global warmer climate is a widespread scientific and socioeconomic issue because of its important impacts on regional agriculture, ecosystems, food security, water resources, and even cultural environment. However, the present study identifies a nonnegligible intermodel uncertainty of the simulated Sahel rainfall changes during the mid-Pliocene (one of the most recent geological warm periods in Earth's history) in the Pliocene Model Intercomparison Project phase 2 (PlioMIP2) multimodel ensemble. In particular, such an intermodel uncertainty of the simulated Sahel rainfall changes during the mid-Pliocene is attributed to that of the simulated northern North America warming via both the direct dynamic process and the indirect thermodynamic process. This is quite different from the uncertainty source of near-future projections of Sahel summer rainfall changes. The present results improve our understanding of the underlying physics of the hydrological cycle change around the Sahel region in the mid-Pliocene warmer climate, with implications for the future projections of regional monsoonal rainfall. [ABSTRACT FROM AUTHOR]

Key mechanisms important for the simulation and better understanding of the precipitation of the North American monsoon (NAM) were analyzed in this paper. Three experiments with the Providing Regional Climates for Impacts Studies (PRECIS) regional climate model, the Hadley Centre Regional Model version 3P (HadRM3P), driven by different boundary conditions were carried out. After a detailed analysis of the moisture and low-level winds derived from the models, the authors conclude that the Gulf of Mexico (GoM) moisture and the Great Plains low-level jet (GPLLJ) play an important role in the northern portion of the NAM. Moreover, the realistic simulation of these features is necessary for a better simulation of precipitation in the NAM. Previous works suggest that the influence of moisture from the GoM in Arizona--New Mexico (AZNM) takes place primarily via the middle- and upper-tropospheric flow (above 700 mb). However, it is shown here that if the GoM does not supply enough moisture and the GPLLJ at lower levels (below 700 mb) does not reach the AZNM region, then a dry westerly flow dominates that area and the summer precipitation is below normal. The implications of these findings for studies of climate change are demonstrated with the analysis of two general circulation models (GCMs) commonly used for climate change prediction, which are shown not to reproduce correctly the GPLLJ intensity nor the moisture in the GoM. This implies that the precipitation in AZNM would not be correctly represented by a regional model driven by these GCMs. [ABSTRACT FROM AUTHOR]

A large number of water- and climate-related applications, such as drought monitoring, are based on spaceborne-derived relationships between land surface temperature (LST) and the normalized difference vegetation index (NDVI). The majority of these applications rely on the existence of a negative slope between the two variables, as identified in site- and time-specific studies. The current paper investigates the generality of the LST–NDVI relationship over a wide range of moisture and climatic/radiation regimes encountered over the North American continent (up to 60°N) during the summer growing season (April–September). Information on LST and NDVI was obtained from long-term (21 years) datasets acquired with the Advanced Very High Resolution Radiometer (AVHRR). It was found that when water is the limiting factor for vegetation growth (the typical situation for low latitudes of the study area and during the midseason), the LST–NDVI correlation is negative. However, when energy is the limiting factor for vegetation growth (in higher latitudes and elevations, especially at the beginning of the growing season), a positive correlation exists between LST and NDVI. Multiple regression analysis revealed that during the beginning and the end of the growing season, solar radiation is the predominant factor driving the correlation between LST and NDVI, whereas other biophysical variables play a lesser role. Air temperature is the primary factor in midsummer. It is concluded that there is a need to use empirical LST–NDVI relationships with caution and to restrict their application to drought monitoring to areas and periods where negative correlations are observed, namely, to conditions when water—not energy—is the primary factor limiting vegetation growth. [ABSTRACT FROM AUTHOR]

The seasonal rainfall over the U.S. central plains features a late-spring maximum. A spring–fall annual mode revealed from the empirical orthogonal function analysis on rainfall delineates a maximum center over the central plains that coincides with the large late-spring rainfall. This paper examines the large-scale dynamical and hydrological processes in forming the rainfall center. The NCEP–Department of Energy (DOE) reanalysis 2 data reveal that the baroclinic structure of the continental-scale circulation during late spring (May and June) induces a vertically out-of-phase divergent circulation forming strong convergence of water vapor flux over the central plains. Such circulation features generate concentrated convective activity in this region. The upper-level anticyclone development with the North American monsoon in July replaces the late-spring baroclinic structure and, in turn, reduces the convective activity. The Great Plains low-level jet (LLJ) plays a role in the downscaling process that connects the continental-scale circulation to rainfall. The LLJ coupled with approaching baroclinic waves leads to stronger moisture convergence in the central plains than that occurring under the upper-level anticyclone. The former type of the LLJ occurs most frequently in late spring and contributes to more than 60% of the rainfall. During midsummer (July and August), such a coupling is hindered by the well-developed upper-level anticyclone, subsequently decreasing the rainfall. [ABSTRACT FROM AUTHOR]

In support of the 2004 North American Monsoon Experiment (NAME) field campaign, NOAA established and maintained a field site about 100 km north of Mazatlán, Mexico, consisting of wind profilers, precipitation profilers, surface upward–downward-looking radiometers, and a 10-m meteorological tower to observe the environment within the North American monsoon. Three objectives of this NOAA project are discussed in this paper: 1) to observe the vertical structure of precipitating cloud systems as they passed over the NOAA profiler site, 2) to estimate the vertical air motion and the raindrop size distribution from near the surface to just below the melting layer, and 3) to better understand the microphysical processes associated with stratiform rain containing well-defined radar bright bands. To provide a climatological context for the profiler observations at the field site, the profiler reflectivity distributions were compared with Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) reflectivity distributions from the 2004 season over the NAME domain as well as from the 1998–2005 seasons. This analysis places the NAME 2004 observations into the context of other monsoon seasons. It also provides a basis for evaluating the representativeness of the structure of the precipitation systems sampled at this location. The number of rain events observed by the TRMM PR is dependent on geography; the land region, which includes portions of the Sierra Madre Occidental, has more events than the coast and gulf regions. Conversely, from this study it is found that the frequencies of occurrence of stratiform rain and reflectivity profiles with radar bright bands are mostly independent of region. The analysis also revealed that the reflectivity distribution at each height has more year-to-year variability than region-to-region variability. These findings suggest that in cases with a well-defined bright band, the vertical profile of the reflectivity relative to the height of the bright band is similar over the gulf, coast, and land regions. [ABSTRACT FROM AUTHOR]

The question of the impact of the Atlantic on North American (NA) seasonal prediction skill and predictability is examined. Basic material is collected from the literature, a review of seasonal forecast procedures in Canada and the United States, and some fresh calculations using the NCEP–NCAR reanalysis data. The general impression is one of low predictability (due to the Atlantic) for seasonal mean surface temperature and precipitation over NA. Predictability may be slightly better in the Caribbean and the (sub)tropical Americas, even for precipitation. The NAO is widely seen as an agent making the Atlantic influence felt in NA. While the NAO is well established in most months, its prediction skill is limited. Year-round evidence for an equatorially displaced version of the NAO (named ED_NAO) carrying a good fraction of the variance is also found. In general the predictability from the Pacific is thought to dominate over that from the Atlantic sector, which explains the minimal number of reported Atmospheric Model Intercomparison Project (AMIP) runs that explore Atlantic-only impacts. Caveats are noted as to the question of the influence of a single predictor in a nonlinear environment with many predictors. Skill of a new one-tier global coupled atmosphere–ocean model system at NCEP is reviewed; limited skill is found in midlatitudes and there is modest predictability to look forward to. There are several signs of enthusiasm in the community about using “trends” (low-frequency variations): (a) seasonal forecast tools include persistence of last 10 years’ averaged anomaly (relative to the official 30-yr climatology), (b) hurricane forecasts are based largely on recognizing a global multidecadal mode (which is similar to an Atlantic trend mode in SST), and (c) two recent papers, one empirical and one modeling, giving equal roles to the (North) Pacific and Atlantic in “explaining” variations in drought frequency over NA on a 20 yr or longer time scale during the twentieth century. [ABSTRACT FROM AUTHOR]

The extent to which wintertime North American surface temperature can be specified based on simultaneous sea surface temperature (SST) is quantified for the period 1982–98. The term specification indicates that the predictor and predictands are not lagged in time, as would be the case for true prediction. Four state-of-the-art general circulation models (GCMs) and linear empirical models with predictors derived from observations and dynamical models are considered. Predictors are derived from model hindcasts using principal component analysis (PCA), canonical correlation analysis (CCA), and discriminant analysis. The last technique has appeared in the climate literature, but its use in the present context appears new. A distinguishing feature of this paper is that several methods and models are compared in a common framework. The specification skill of GCMs for the period 1982–98 is statistically significant in the northwestern region near Washington State, British Columbia, and central Canada, with some local correlations exceeding 0.6. The specification skill of GCMs is comparable to, or better than, the skill of the best empirical model for the particular 17-yr period examined. No single specification strategy was found to improve the model hindcast skill in all cases. Predictors derived from discriminant analysis generally lead to larger skill than predictors based on PCA or CCA. The signal-to-noise ratio varies greatly among models and appears to be, if anything, inversely related to the specification skill when discriminants are used as predictors. Predictors based on 500-hPa geopotential height can lead to specification skill at least as good as predictors based on land surface temperature. Evidence is presented for the existence of at least two distinct dynamically predictable components of land surface temperature arising from two distinct “flavors” of SST anomalies associated with El Niño and La Niña. [ABSTRACT FROM AUTHOR]

The purpose of this paper is to study the influence of tropical sea surface temperature (SST) on the midlatitude circulation regime behavior in the Pacific–North American region. Toward this end, a cluster analysis has been applied to 55-member ensembles of winter seasonal simulations of the Center for Ocean–Land–Atmosphere Studies general circulation model for 18 winters. The ensemble members for each winter utilize the same prescribed, observed weekly varying SST for that winter. The cluster analysis includes all fluctuations with time scales longer than 10 days except for the ensemble mean seasonal cycle. Using a partitioning algorithm separately applied to each winter's ensemble, clusters are found in the 200-hPa height field that are signicant (vis-à-vis a suitable Gaussian background), reproducible (in half-length datasets), and consistent (with clusters obtained from the 200-hPa u wind) for all winters except the strong El Niño events of 1982/83, 1986/87, and 1997/98. One cluster found consistently in many winters, consisting of a strong ridge over the Alaskan region and a trough over central North America, is quite similar to the Alaskan pattern identified from observations as being particularly difficult to predict and that occurs preferentially during La Niña events. Two other clusters found in many winters have no observational counterparts. A regime that is very similar to the seasonal mean response to cold tropical Pacific SSTs is seen during several La Niña winters. A strong negative correlation between a measure of the strength of the clustering and the Niño-3 SST index is found. That this correlation is as strong as the correlation between the seasonal mean response and the same SST index indicates that the El Niño–Southern Oscillation–related SSTs affect the regime structure of intraseasonal flow as strongly as they do the mean state. [ABSTRACT FROM AUTHOR]

The impacts of the Madden–Julian oscillation (MJO) on the subseasonal-to-seasonal (S2S) prediction in the Northern Hemisphere extratropics are examined using the reforecasts from the S2S Project and Subseasonal Experiment Project (SubX). When forecasts are initialized during an active MJO, extratropical prediction skill becomes significantly higher at 3–4-week windows compared to inactive MJO. Such prediction skill improvement is evident in the 500-hPa geopotential height over the Pacific–North America region and the North Atlantic and in surface temperature over North America, especially when the model is initialized during the MJO phases 6–7 and 8–1. However, the extratropical prediction skill is not modulated by the MJO phases 2–3 and 4–5. This phase dependency is likely determined by the arrival time of the MJO at the Maritime Continent (MC) barrier that substantially enhances the MJO amplitude error. This result suggests that only MJO phases whose convection lies east of the MC are a source of wintertime S2S predictability in the extratropics. [ABSTRACT FROM AUTHOR]

Principal component analysis (PCA) is a widely used technique to identify modes of low-frequency variability of atmospheric circulation and their spatial changes. However, it turns out that PCA is highly sensitive to the period analyzed and the length of the time window used. Its results can vary considerably if the period is shifted by even 1 year. We present temporal variability of modes from the late nineteenth century using moving PCA of winter (DJF) monthly mean 500-hPa height anomalies for 20–50-yr moving periods with 1-yr step. We employ the congruence coefficient to compare spatial patterns of the modes and identify their substantial changes. Shorter moving periods are more susceptible to sudden fluctuations in mode patterns from one period to the next, while longer periods yield more stable results. We strongly recommend applying a moving PCA to detect spatial changes in modes of low-frequency variability, as it unveils any hidden sudden changes in the modes. These changes can be influenced by many aspects, such as data quality, sampling variability, and length of the analyzed period. Spatial patterns of the Atlantic–European modes are more stable across ensemble members than those over the Pacific and North America, especially before the 1920s. During this period, North Atlantic and European modes explain more variance in the ensemble mean than in ensemble members, while the reverse holds for Pacific and North American modes. In data-sparse regions, modes in ensemble members exhibit greater variability. The process of averaging then leads to weaker modes in the ensemble mean, explaining less variance compared to ensemble members. [ABSTRACT FROM AUTHOR]

In this study, we analyze drivers of non–El Niño–Southern Oscillation (ENSO) precipitation variability in the Southwest United States (SWUS) and the influence of the atmospheric basic state, using atmosphere-only and ocean–atmosphere coupled simulations from the Community Earth System Model version 2 (CESM2) large ensemble. A cluster analysis identifies three main wave trains associated with non-ENSO SWUS precipitation in the experiments: a meridional ENSO-type wave train, an arching Pacific–North American-type (PNA) wave train, and a circumglobal zonal wave train. The zonal wave train cluster frequency differs between models and ENSO phase, with decreased frequency during El Niño and the coupled runs, and increased frequency during La Niña and the atmosphere-only runs. This is consistent with an El Niño–like bias of the atmospheric circulation in the coupled model, with strengthened subtropical westerlies in the central and eastern North Pacific that cause a retraction of the waveguide in the midlatitude eastern North Pacific. As such, zonal wave trains from the East Asian jet stream (EAJS) are more likely to be diverted southward in the east Pacific in the coupled large ensemble, with a consequently smaller role in driving SWUS precipitation variability. This study illustrates the need to reduce model biases in the background flow, particularly relating to the jet stream, in order to accurately capture the role of large-scale teleconnections in driving SWUS precipitation variability and improve future forecasting capabilities. [ABSTRACT FROM AUTHOR]

Climate model projections of atmospheric circulation patterns, their frequency, and associated temperature and precipitation anomalies under a high-end global warming scenario are assessed over the Pacific Northwest of North America for the final three decades of the twenty-first century. Model simulations are from phase 6 of the Coupled Model Intercomparison Project (CMIP6) and circulation patterns are identified using the self-organizing maps (SOMs) approach, applied to 500-hPa geopotential height (Z500) anomalies. Overall, the range of projected circulation patterns is similar to that in the current climate, especially in winter, whereas in summer the models project a general reduction in the magnitude of Z500 anomalies. Significant changes in pattern frequencies are also projected in summer, with an overall decrease in the frequency of patterns with large Z500 anomalies. In winter, patterns historically associated with anomalously cold weather in northern latitudes are projected to warm the most, and in summer the largest temperature increases are projected over inland areas. Precipitation is found to increase across all seasons and most SOM patterns. However, some summer patterns that are associated with above-average precipitation in the current climate are projected to become significantly drier by the end of the century. [ABSTRACT FROM AUTHOR]

Extratropical cyclones (ETCs) are a common source of natural hazards, from heavy rain to high winds, and the direction and speed of ETC propagation influence where impacts occur and for how long. Eighteen models from phase 6 of the Coupled Model Intercomparison Project (CMIP6) are used to examine the response of Northern Hemisphere ETC propagation to global warming. In winter, simulations show that ETCs become slower over North America and the Arctic but faster over the Pacific Ocean and part of Europe. In summer, storm propagation becomes slightly slower throughout much of the midlatitudes (308-608N). Trends in both seasons relate closely to the impact of global warming on upper-level (250 hPa) winds and the 850-250-hPa thickness gradient. Wherever local thickness gradients weaken in the future, ETCs travel more slowly; conversely, wherever they strengthen, ETCs travel more quickly. In contrast to past work, we find that winter storm propagation becomes more zonal over the Pacific and Atlantic Oceans, which may link to decreased atmospheric blocking and less-sinuous flow at 500 hPa. The importance of model projections of the 850-250-hPa thickness gradient for meridionality of ETC propagation remains uncertain for these regions. However, for North America, models that project stronger thickness gradients also project less-sinuous flow and more-zonal ETC propagation. Overall, this work highlights strong regional variation in how the speed and direction of ETC propagation, and the upper-level circulation patterns that govern them, respond to continued warming. [ABSTRACT FROM AUTHOR]

Weather regimes defined through cluster analysis concisely categorize the anomalous regional circulation pattern on any given day. Owing to their persistence and low dimensionality, regimes are increasingly used in subseasonal-to-seasonal prediction and in analysis of climate variability and change. However, a limitation of existing regime classifications for North America is their seasonal dependence, with most existing studies defining regimes for winter only. Here, we normalize the seasonal cycle in daily geopotential height variance and use empirical orthogonal function analysis combined with k-means clustering to define a new set of year-round North American weather regimes: the Pacific Trough, Pacific Ridge, Alaskan Ridge, and Greenland High regimes. We additionally define a "No Regime" state to represent conditions close to climatology. To demonstrate the robustness of the classification, a thorough assessment of the sensitivity of the clustering solution to various methodological choices is provided. The median persistence of all four regimes, obtained without imposing a persistence criterion, is found to be one week, approximately 3 times longer than the median persistence of the No Regime state. Regime-associated temperature and precipitation anomalies are reported, together with the relationship between the regimes and modes of climate variability. We also quantify historical trends in the frequency of the regimes since 1979, finding a decrease in the annual frequency of the Pacific Trough regime and an increase in the summertime frequency of the Greenland High regime. This study serves as a foundation for the future use of these regimes in a variety of weather and climate applications. [ABSTRACT FROM AUTHOR]

Explosive cyclones (ECs), defined as extratropical cyclones that experience normalized pressure drops of at least 24 hPa in 24 h, are impactful weather events in the North Atlantic sector, but year-to-year changes in the frequency and impacts of these storms are sizeable. To analyze the sources of this interannual variability, we track cases of ECs and dissect them into two spatial groups: those that formed near the east coast of North America (coastal) and those in the north central Atlantic (high latitude). The frequency of high-latitude ECs is strongly correlated with the North Atlantic Oscillation, a well-known feature, whereas coastal EC frequency is statistically linked with an atmospheric wave train emanating from the North Pacific in the last 30 years. This wave train pattern of alternating high and low pressure is associated with heightened upper-level divergence and Eady growth rates along the east coast of North America, likely resulting in a stronger correspondence between the atmospheric wave train and coastal EC frequency. Using coupled model experiments, we show that the tropical and North Pacific oceans are an important factor for this atmospheric wave train and the subsequent enhancement of seasonal baroclinicity in the North Atlantic. [ABSTRACT FROM AUTHOR]

The predictability of temperatures in North America is of great importance for local agriculture and human health. In autumn (SON), the temperature in North America is correlated with ENSO, but its predictive skill is limited. Here, we show that spring (MAM) sea surface temperature (SST) anomalies in the southwest Pacific (SWP) exhibit a higher correlation with autumn temperature in North America (r = 0.73) than ENSO. This cross-seasonal and cross-hemispheric relationship is established via the western tropical Pacific (WTP) region. The spring SWP SST anomalies show a cross-hemispheric propagation embedded in the southerly monsoonal flow through the wind–evaporation–SST feedback, which sustains the progression of SST anomalies toward the WTP in autumn. The AGCM simulations from multimodels show that active convection in the WTP caused by SST warming stimulate a Rossby wave train propagating downward to North America, where it is governed by an anomalous high with increased atmospheric thickness and tropospheric temperature. Consequently, the longwave radiative heating over North America is enhanced, raising the surface air temperature. These results indicate that the SWP SST is a useful predictor of North American temperature 6 months in advance through the cross-hemispheric influence. A model based on the spring SWP SST and preceding winter ENSO (Niño-3.4) shows a high predictive skill for the autumn temperature anomalies in North America. Significance Statement: Seasonal predictions of surface temperature are important for agricultural decision-making, disaster prevention, and mitigation. Over the western Pacific, associated with the seasonal evolution of ITCZ, there is a strong northward progression of SST anomaly signals generated in the southwest Pacific. This study finds that this cross-hemispheric SST propagation can significantly impact the autumn surface temperature over central North America through the atmospheric bridge. A statistical model incorporating southwest Pacific SST for spring is constructed to predict the North American autumn surface temperature and exhibits high consistency with observations. This improves our understanding of the interhemispheric interactions at seasonal time scales and the seasonal predictability of the North American climate. [ABSTRACT FROM AUTHOR]

This paper describes the results of an analysis of trends in short duration (1--7 days) extreme precipitation events that have a recurrence interval of 1 yr or longer for stations in the United States and Canada. This definition of extreme precipitation was chosen because such events are highly correlated with hydrologic flooding in some U.S. regions. The dominant temporal characteristic of a national event composite index is significant low-frequency variability. There were lengthy periods of a below-average number of events in the 1930s and 1950s and an above-average number of events in the early 1940s, early 1980s, and 1990s. Regional variations often differ substantially from the national composite. A simple linear analysis indicates that the overall trend covering the period 1931--96 has been upward at a highly statistically significant rate over the southwest United States and in a broad region from the central Great Plains across the middle Mississippi River and southern Great Lakes basins. The national trend for the United States is upward at a rate of 3% decade 21 for the period 1931--96. While the annual trend for Canada is upward for the period 1951--93, it is not statistically significant. Although the high statistical significance of the results is partially a consequence of the low frequency during the 1930s and 1950s located in the first half of the record, the latter half of the record exhibits an upward trend nearly identical to the entire record. However, an analysis of a 101-yr record of midwestern stations shows that heavy precipitation event frequencies around the turn of the twentieth century (1896--1906) were higher than for other periods of comparable length, except for 1986--96. Although data were not available in digital form to extend the analysis back to 1896 for the entire United States, the midwestern analysis shows that interpretation of the recent upward trends must account for the possibility of significant... [ABSTRACT FROM AUTHOR]

In a companion paper, Y. Liu and R. Avissar analyzed the features of persistence in the land--atmosphere system simulated with the National Center for Atmospheric Research Community Climate Model Version 2 coupled with the Biosphere--Atmosphere Transfer Scheme (CCM2--BATS). To interpret the results obtained in that study, a fourth-order land--atmosphere analytical model is developed and used to investigate the timescales of disturbances in the land--atmosphere system, and the major parameters and processes affecting them. This analytical model has four damping timescales, namely seasonal, monthly, weekly, and daily. It is found that the seasonal scale is caused by self-feedback of soil moisture, and its length increases significantly due to the interactions between soil moisture and the other system variables. A sensitivity analysis performed with the Fourier amplitude sensitivity test indicates that the seasonal timescale is mostly affected by the physical param-eters related to hydrological processes (namely, evaporation, runoff, and soil moisture diffusion), while the thermal characteristics of the land--atmosphere system mostly affect the monthly timescale. Thus, the results of this analytical study indicate that the persistence obtained in the CCM2--BATS simulation is an inherent property of the land--atmosphere system. They also emphasize the importance of soil moisture disturbances on persistence in the climatic system. [ABSTRACT FROM AUTHOR]

The transport of water vapor through the Mackenzie River basin, a typical high-latitude river basin, is examined for the period from August to October 1994. The spatial and temporal variability in the transport is considered with both objectively analyzed fields and radiosonde data. Previous studies of the high-latitude water vapor have made use of radiosonde data and have been able to document some features of annual cycle of water vapor transport. These studies have left unresolved many important aspects of moisture transport processes. In particular, detailed information as to the spatial and temporal variation of the transport has not been fully documented or understood. In order to address these important issues, the authors make use of the objectively analyzed fields from the European Centre for Medium-Range Weather Forecasts to study the high-latitude transport of water vapor. This paper presents findings regarding the transport of water vapor over northern parts of North America. It is shown that the transport is highly variable in time with transient synoptic-scale disturbances being responsible for much of the transport. The prospect of using the objectively analyzed fields to determine the spatial structure of humidity fluxes and the evaporation-- precipitation field in data-sparse high-latitude regions is discussed. The results obtained with the objectively analyzed fields are compared with those obtained directly from radiosonde data for stations in and around the basin. The influence that the local land topography has on the regional water vapor balance is also discussed. [ABSTRACT FROM AUTHOR]

El Niño–Southern Oscillation (ENSO) is the strongest interannual signature in the tropical air–sea system and can affect global atmospheric variables, but ENSO's climatic impact on land surface variables such as skin temperature, snow cover, and soil moisture that can serve as seasonal climate predictors remains relatively little known. Here we examine ENSO's impact on the three land surface variables in Northern Hemisphere extratropics by regression analysis, using a combination of ERA5 reanalysis, GLDAS, satellite-based observations, and CESM2 simulations. Our results show that during El Niño winters anomalous land surface warming occurs in Northern Hemisphere midlatitudes, accompanied by snow cover reduction, especially in northern North America and eastern Europe, while anomalous cooling occurs in southern North America and the Tibetan Plateau, accompanied by increased snow cover. Meanwhile, increased soil moisture is observed in southern North America, central Asia, and southeast China. Further analysis indicates that atmospheric moisture processes dominate the formation of the land surface anomalies, for which the changes in water vapor and precipitation induced by the ENSO-related large-scale atmospheric teleconnection are critical. The anomalous land surface warming in midlatitudes mainly results from the increased downward longwave radiation due to the increase of water vapor, whereas the physical pathway causing water vapor anomalies is different over North America and Eurasia. Controlled by ENSO-induced changes in atmospheric circulation and moisture transport, anomalous precipitation explains most of the snow cover and soil moisture anomalies, which play a certain role in shaping the skin temperature anomalies in some regions through snow–albedo feedback and evaporation, respectively. [ABSTRACT FROM AUTHOR]

Current models for spatial extremes are concerned with the joint upper (or lower) tail of the distribution at two or more locations. Such models cannot account for teleconnection patterns of 2-m surface air temperature (T2m) in North America, where very low temperatures in the contiguous United States may coincide with very high temperatures in Alaska in the wintertime. This dependence between warm and cold extremes motivates the need for a model with opposite-tail dependence in spatial extremes. This work develops a statistical modeling framework that has flexible behavior in all four pairings of high and low extremes at pairs of locations. In particular, we use a mixture of rotations of common Archimedean copulas to capture various combinations of four-corner tail dependence. We study teleconnected T2m extremes using ERA5 of daily average 2-m temperature during the boreal winter. The estimated mixture model quantifies the strength of opposite-tail dependence between warm temperatures in Alaska and cold temperatures in the midlatitudes of North America, as well as the reverse pattern. These dependence patterns are shown to correspond to blocked and zonal patterns of midtropospheric flow. This analysis extends the classical notion of correlation-based teleconnections to considering dependence in higher quantiles. [ABSTRACT FROM AUTHOR]

Extreme near-surface wind speeds in cities can have major societal impacts but are not well represented in climate models. Despite this, large-scale dynamics in the free troposphere, which models resolve better, could provide reliable constraints on local extreme winds. This study identifies synoptic circulations associated with midlatitude extreme wind events and assesses how resolution affects their representation in analysis products and a climate model framework. Composites of reanalysis (ERA5) sea level pressure and upper-tropospheric winds during observed extreme wind events reveal distinct circulation structures for each quadrant of the surface-wind rose. Enhanced resolution of the analysis product (ERA5 versus the higher-resolution ECMWF Operational Analysis) reduced wind speed biases but has little impact on capturing occurrences of wind extremes seen in station observations. Composite circulations for surface wind extremes in a climate model (CESM) skillfully reproduce circulations found in reanalysis. Regional refinement of CESM over a region centered on southern Ontario, Canada, using variable resolution (VR-CESM) improves representation of surface ageostrophic circulations and the strength of vertical coupling between upper-level and near-surface winds. We thus can distinguish situations for which regional refinement (dynamical downscaling) is necessary for realistic representation of the large-scale atmospheric circulations associated with extreme winds, from situations where the coarse resolution of standard GCMs is sufficient. [ABSTRACT FROM AUTHOR]

Recent studies propose that the Asian--Bering--North American (ABNA) teleconnection is a distinct atmospheric pattern that is related to Eurasian and North American winter climate besides the Pacific--North America (PNA) pattern, while its origin remains elusive. This study investigates the interannual variability of the ABNA during the past 42 winters (1979-2020) and the associated prior surface boundary forcings. The ABNA explains coherent surface air temperature changes in northern Asia, eastern Siberia--Alaska, and eastern North America, even after removing the impacts of the PNA, the Arctic Oscillation, the North Atlantic Oscillation, and the North Pacific Oscillation. Surface boundary conditions linked to the ABNA could be traced back to a Eurasian snow cover dipole pattern (ESCDP) and a Maritime Continent sea surface temperature anomaly (MCSST) in November. The ESCDP leads to a displacement of the Arctic stratospheric polar vortex via troposphere--stratosphere coupling. The anomalous polar vortex propagates downward in the following winter and generates the tropospheric ABNA pattern. The MCSST induces a diabatic heating anomaly, which is associated with a tropical western Pacific precipitation anomaly (TWPP) in winter. The TWPP excites a poleward Rossby wave train that propagates across the North Pacific and directly strengthens the ABNA. The above physical processes can be well reproduced by a linear baroclinic model (LBM). Based on the ESCDP and MCSST predictors, an empirical model is established and shows a promising prediction skill of the ABNA during the hindcast period. This can provide a useful strategy for seasonal prediction of winter climate in the Northern Hemisphere extratropics. [ABSTRACT FROM AUTHOR]

The impact of tropical Pacific sea surface temperature (SST) biases on the deterministic skill of the Unified Forecast System (UFS) coupled model Prototype 5 is evaluated during weeks 1–4 of the forecast. The evaluation is limited to the contiguous United States (CONUS) and two seasons: boreal summer (June–September) and winter (December–March). The tropical SST in the UFS model is warmer than in observations and bias patterns show seasonal dependence especially in the central and western Pacific. During boreal summer, the bias is located north of the equator whereas in winter, the bias is located in the Southern Hemisphere. A regression analysis indicates a significant relationship between these SST biases and the biases in the surface temperature and precipitation over the CONUS along with midtroposphere large-scale circulation and North Pacific storm-track activity. The SST biases affect the biases in other fields from week 1 of the forecast and the impact becomes stronger as the lead time increases to week 4. The impact of SST biases on the biases in other fields show a qualitative relationship to the patterns of forecast errors of the fields. [ABSTRACT FROM AUTHOR]

Wintertime cold air outbreaks are periods of extreme cold, often persisting for several days and spanning hundreds of kilometers or more. They are commonly associated with intrusions of cold polar air into the midlatitudes, but it is unclear whether the air mass's initial temperature in the Arctic or its cooling as it travels is the determining factor in producing a cold air outbreak. By calculating air parcel trajectories for a preindustrial climate model scenario, we study the role of the origin and evolution of air masses traveling over sea ice and land and resulting in wintertime cold air outbreaks over central North America. We find that not all Arctic air masses result in a cold air outbreak when advected into the midlatitudes. We compare trajectories that originate in the Arctic and result in cold air outbreaks to those that also originate in the Arctic but lead to median temperatures when advected into the midlatitudes. While about one-third of the midlatitude temperature difference can be accounted for by the initial height and temperature in the Arctic, the other two-thirds are a result of differences in diabatic heating and cooling as the air masses travel. Vertical mixing of cold surface air into the air mass while it travels dominates the diabatic cooling and contributes to the cold events. Air masses leading to cold air outbreaks experience more negative sensible heat flux from the underlying surface, suggesting that preconditioning to establish a cold surface is key to producing cold air outbreaks. Significance Statement: Wintertime cold air outbreaks can cause temperatures to plummet tens of degrees below freezing over the northern United States, with the potential to damage agriculture, infrastructure, and human health. Accurate predictions under climate change could help mitigate these effects, but there is disagreement over whether cold air outbreaks have declined in line with the already-observed global warming trend or persisted in spite of it. Focusing on cold air outbreaks that originate from the Arctic, we find that there must be additional cooling of the traveling air mass by mixing with very cold surface air as it moves south over North America in order to result in a cold outbreak. [ABSTRACT FROM AUTHOR]

Teleconnection patterns associated with the Madden–Julian oscillation (MJO) and El Niño–Southern Oscillation (ENSO) impact weather and climate phenomena in the Pacific–North American region and beyond, and therefore accurately simulating these teleconnections is of importance for seasonal and subseasonal forecasts. Systematic biases in boreal midwinter ENSO and MJO teleconnections are found in eight subseasonal to seasonal (S2S) forecast models over the Pacific–North America region. All models simulate an anomalous 500-hPa geopotential height response that is too weak. This overly weak response is associated with overly weak subtropical upper-level convergence and a too-weak Rossby wave source in most models, and in several models there is also a biased subtropical Pacific jet, which affects the propagation of Rossby waves. In addition to this overly weak response, all models also simulate ENSO teleconnections that reach too far poleward toward Alaska and northeastern Russia. The net effect is that these models likely underestimate the impacts associated with the MJO and ENSO over western North America, and suffer from a reduction in skill from what could be achieved. [ABSTRACT FROM AUTHOR]

Previous work has shown that anthropogenic aerosol (AA) forcing drives a strengthening in the Atlantic meridional overturning circulation (AMOC) in CMIP6 historical simulations over 1850–1985, but the mechanisms have not been fully understood. Across CMIP6 models, it is shown that there is a strong correlation between surface heat loss over the subpolar North Atlantic (SPNA) and the forced strengthening of the AMOC. Despite the link to AA forcing, the AMOC response is not strongly related to the contribution of anomalous downwelling surface shortwave radiation to SPNA heat loss. Rather, the spread in AMOC response is primarily due to the spread in turbulent heat loss. We hypothesize that turbulent heat loss is larger in models with strong AA forcing because the air advected over the ocean is colder and drier, in turn because of greater AA-forced cooling over the continents upwind, especially North America. The strengthening of the AMOC also feeds back on itself positively in two distinct ways: by raising the sea surface temperature and hence further increasing turbulent heat loss in the SPNA, and by increasing the sea surface density across the SPNA due to increased northward transport of saline water. A comparison of key indices suggests that the AMOC response in models with strong AA forcing is not likely to be consistent with observations. [ABSTRACT FROM AUTHOR]

Even though winter land–sea thermal contrast (LSC) is expected to undergo a strong weakening in the future warmer climate, its effects have been poorly investigated. Here we run a set of idealized winter simulations featuring reduced LSC in the Northern Hemisphere (NH) extratropics, or in individual extratropical sectors of the NH (Atlantic and Pacific), using an intermediate-complexity atmospheric general circulation model. Reduced LSC is obtained by imposing a warming of surface land temperatures in East Asia and North America. For similar warming intensities over the two regions, the response of the model to East Asia forcing is significantly stronger and dominates the response to the sum of the two forcing patterns. We find that the LSC reduction causes a weakening and poleward shift of the midlatitude jet streams, and a strong interference with zonal wavenumbers 1 and 2. In particular, East Asian warming reduces the amplitude of waves 1 and 2, producing a strengthening of the stratospheric vortex, while a weaker vortex due to a moderate amplification of wave 1 is detected when warming North America. Eventually, stratospheric signals propagate downward in the troposphere affecting the midlatitude winter NH even remotely from the forcing. In this work we pinpoint some mechanisms by which weakened winter LSC influences the NH extratropical circulation: the results may become useful to interpret the response to long-term projections displaying reduced LSC along with other climate change forcing patterns. [ABSTRACT FROM AUTHOR]

During summer, persistent positive anomalies (PPAs) of midtropospheric geopotential heights in North America are often associated with extreme weather, including heatwaves. We evaluate the link between prolonged summertime PPAs in 500-hPa geopotential heights and wildfire activity across western North America and examine temporal trends in PPA characteristics. On average, 17% of May–September days experience PPA events over the study domain. Large fires (burned area > 500 ha) were 7 times as likely to start during a PPA, with approximately 40% of these fires' ignitions coincident with PPA events. A positive correlation exists between the fraction of May–September PPA days and burned area for most of the study domain. Additionally, the presence of a PPA exerts greater influence on fire ignition and burned area in higher latitudes than lower latitudes of western North America. We find a statistically significant expansion in the spatial extent of PPA events during 1979–2020. The observed expansion of the PPAs is likely due to thermodynamic changes in midlatitude synoptic patterns. These findings may improve our understanding of the connections between PPA events and wildfires in western North America, enhance the short-term predictability of wildfire events, and have important implications for increased fire risk in a warming climate. Significance Statement: Persistent positive anomalies (PPAs) of the upper air atmospheric flow, a slow progression of planetary waves, are synoptic-scale patterns that cause heatwaves and contribute to wildfire activity. We seek to understand how these events relate to fire weather and fire activity over western North America. The presence of PPA events increases the likelihood of fire ignition by a factor of 7, with higher likelihood over northern regions. The mean area of the PPA events has grown significantly in recent decades, exposing larger areas and populations to increased fire risks. These results improve our understanding of the connections between upper air atmospheric patterns and wildfires, signal how it may change in future warmer climate and scenarios, and enhance the near-future predictability of fire events in this region. [ABSTRACT FROM AUTHOR]

Atmospheric rivers (ARs) are long and narrow bands of intense water vapor transport that often induce heavy precipitation and flooding along the west coast of North America. Previous studies demonstrate that the Madden–Julian oscillation (MJO) contributes to the predictability of AR activity on a subseasonal time scale. However, individual AR responses vary widely following the same phase of MJO. Here we investigate 96 MJO events following phase 3 (convection over the Indian Ocean) and analyze the differences between events that brought large-scale ARs to the entire Pacific Northwest coastal region and those that did not. The MJO events with ARs tend to stay longer at phase 3 than those without ARs. We use linear regression to isolate the extratropical signals linearly related to the MJO and explore how the residual fields differ between the two groups. The linearly dependent signal shows slow-moving planetary-scale water vapor transport across the North Pacific. The residual field exhibits a contrasting extratropical low-frequency (>10 days) pattern in the Gulf of Alaska resembling the Pacific–North American (PNA) pattern: a trough for events with ARs and a ridge for events without ARs. This low-frequency variability alters the Pacific waveguide such that, for MJO events with ARs, baroclinic waves are directed into the Pacific Northwest with an orientation that favors anomalous positive IVT. For MJO events without ARs, the ridge strengthens large-scale anticyclonic flow over the North Pacific and prevents moisture access to the Pacific Northwest. [ABSTRACT FROM AUTHOR]

Observational evidence shows changes to North American weather regime occurrence depending on the strength of the lower-stratospheric polar vortex. However, it is not yet clear how this occurs or to what extent an improved stratospheric forecast would change regime predictions. Here we analyze four North American regimes at 500 hPa, constructed in principal component (PC) space. We consider both the location of the regimes in PC space and the linear regression between each PC and the lower-stratospheric zonal-mean winds, yielding a theory of which regime transitions are likely to occur due to changes in the lower stratosphere. Using a set of OpenIFS simulations, we then test the effect of relaxing the polar stratosphere to ERA-Interim on subseasonal regime predictions. The model start dates are selected based on particularly poor subseasonal regime predictions in the European Centre for Medium-Range Weather Forecasts CY43R3 hindcasts. While the results show only a modest improvement to the number of accurate regime predictions, there is a substantial reduction in Euclidean distance error in PC space. The average movement of the forecasts within PC space is found to be consistent with expectation for moderate-to-large lower-stratospheric zonal wind perturbations. Overall, our results provide a framework for interpreting the stratospheric influence on North American regime behavior. The results can be applied to subseasonal forecasts to understand how stratospheric uncertainty may affect regime predictions, and to diagnose which regime forecast errors are likely to be related to stratospheric errors. Significance Statement: Predicting the weather several weeks ahead is a major challenge with large potential benefits to society. The strength of the circulation more than 10 km above the Arctic during winter (i.e., the polar vortex) is one source of predictability. This study investigates how forecast error and uncertainty in the polar vortex can impact predictions of large-scale weather patterns called "regimes" over North America. Through statistical analysis of observations and experiments with a weather forecast model, we develop an understanding of which regime changes are more likely to be due to changes in the polar vortex. The results will help forecasters and researchers understand the contribution of the stratosphere to changes in weather patterns, and in assessing and improving weather forecast models. [ABSTRACT FROM AUTHOR]

The frequency of atmospheric blocking has been largely underestimated by general circulation models (GCMs) participating in the Coupled Model Intercomparison Project (CMIP). Errors in the onset, persistence, barotropicity, geographical preference, seasonality, intensity, and moving speed of global blocking were diagnosed in 10 Geophysical Fluid Dynamics Laboratory (GFDL) GCMs for recent CMIP5 and CMIP6 using a detection approach that combines zonal eddies and the reversal of zonal winds. The blocking frequency, similar at 500 and 250 hPa, is underestimated by 50% in the Atlantic–Europe region during December–February but is overestimated by 60% in the Pacific–North America region during that season and by 70% in the southwest Pacific during July–August. These blocking biases at 500 hPa were investigated in the five CMIP6 models that showed improvements over the CMIP5 versions. The Atlantic–Europe underestimate corresponds to lower instantaneous blocking rates, lower persistent blocking rates, and higher persistent stationary ridge rates; the number of blocks with a duration of 4–5 days is only 40%–65% of that in observations. In contrast, the overestimate consists of excessive blocks with a duration longer than 12 days in the Pacific–North America and up to twice as many 4–6-day events in the southwest Pacific. Simulated December–February blocks up to 12 days in the Pacific–North America region tend to be stronger and to move more slowly than those in observations. Diagnostic sensitivity tests indicated that the zonal mean and zonal eddy components of the mean state play a key role, as replacing each with that of observations substantially reduced many of the outstanding biases in these GCMs. [ABSTRACT FROM AUTHOR]

This study shows that the frequency of North American summertime (June–August) heat extremes is skillfully predicted several months in advance in the newly developed Geophysical Fluid Dynamics Laboratory (GFDL) Seamless System for Prediction and Earth System Research (SPEAR) seasonal forecast system. Using a statistical optimization method, the average predictability time, we identify three large-scale components of the frequency of North American summer heat extremes that are predictable with significant correlation skill. One component, which is related to a secular warming trend, shows a continent-wide increase in the frequency of summer heat extremes and is highly predictable at least 9 months in advance. This trend component is likely a response to external radiative forcing. The second component is largely driven by the sea surface temperatures in the North Pacific and North Atlantic and is significantly correlated with the central U.S. soil moisture. The second component shows largest loadings over the central United States and is significantly predictable 9 months in advance. The third component, which is related to the central Pacific El Niño, displays a dipole structure over North America and is predictable up to 4 months in advance. Potential implications for advancing seasonal predictions of North American summertime heat extremes are discussed. [ABSTRACT FROM AUTHOR]

Atmospheric rivers (ARs) originating near the Kuroshio Extension and the Hawaiian Islands and making landfall onto the west coast of North America in the North Pacific in the boreal winter season (October–March) are detected and tracked using ERA5 reanalysis (2000–19), and are classified as Kuroshio Extension (KE) and Pineapple Express (PE) ARs, respectively. Compared with KE ARs, PE ARs are longer and wider with higher intensity and shorter duration. Although the total occurrence of PE ARs is lower, the occurrence of extreme ARs is substantially higher than KE ARs. PE (KE) ARs are oriented more meridionally (zonally) with more equatorward (poleward) landfalling positions and associated precipitation. The genesis, development, and decay of KE and PE ARs and their relationships with extratropical cyclones (ECs) are investigated. Along- and cross-section analyses show that PE ARs are associated with stronger, deeper low pressure systems with closer tropical connections. Compared with KE ARs, PE ARs originate from well-developed ECs with stronger southward intrusion of cold fronts, forming closer to the ECs' centers along the sharp temperature/pressure gradient zone. They are accompanied by enhanced and deeper vertical motion and stronger low-level wind. The intensity difference between KE and PE ARs is largely determined by the orientation and the strengths of temperature/pressure gradients of associated ECs rather than the intensity of associated ECs themselves. Furthermore, the evolution of ARs and ECs is not always synchronized, suggesting complicated AR and EC interactions that require further investigations. [ABSTRACT FROM AUTHOR]

Temporal clustering of extreme precipitation (TCEP) at subseasonal time scales often results in major impacts on humans and ecosystems. Assessment and mitigation of the risk of such events requires characterization of their weather/climate drivers and their spatial dependence. Here, we introduce a regionalization method that identifies coherent regions in which the likelihood of subseasonal TCEP exhibits similar dependence to large-scale dynamics. We apply this method to each season in the Northern Hemisphere using ERA5 reanalysis data. The analysis yields spatially coherent regions, primarily at high latitudes and along the eastern margins of ocean basins. We analyze the large-scale and synoptic conditions associated with TCEP in several of the identified regions, in light of three key ingredients: lifting, moisture availability, and persistence in synoptic conditions. We find that TCEP is often directly related to distinct cyclone and blocking frequency anomalies and upper-level wave patterns. Blocking and associated Rossby wave breaking are particularly relevant at high latitudes and midlatitudes. At upper levels, meridional wave patterns dominate; however, in western Europe and parts of North America, TCEP is sometimes associated with zonally extended wave patterns. The flow features associated with TCEP in the eastern Pacific and eastern Atlantic Oceans exhibit similarities. For some regions, moisture flux anomalies are present during clustering episodes whereas in others forced lifting alone is sufficient to trigger heavy precipitation. Our results provide new information on the dynamics and spatial dependence of TCEP that may be relevant for the subseasonal prediction of clustering episodes. [ABSTRACT FROM AUTHOR]

Future changes in boreal winter MJO teleconnections over the Pacific–North America (PNA) region are examined in 15 Coupled Model Intercomparison Project phase 6 models (CMIP6s) under SSP585 (i.e., Shared Socioeconomic Pathway 5 following approximately the representative concentration pathway RCP8.5) scenarios. The most robust and significant change is an eastward extension (∼4° eastward for the multimodel mean) of MJO teleconnections in the North Pacific. Other projected changes in MJO teleconnections include a northward extension, more consistent patterns between different MJO events, stronger amplitude, and shorter persistence; however, these changes are more uncertain and less significant with a large intra- and intermodel spread. Mechanisms of the eastward teleconnection extension are investigated by comparing impacts of the future MJO and basic state changes on the anomalous Rossby wave source (RWS) and teleconnection pathways with a linear baroclinic model (LBM). The eastward extended jet in the future plays a more important role than the eastward-extended MJO in influencing the east–west position of MJO teleconnections. It leads to more eastward teleconnection propagation along the jet due to the eastward extension of turning latitudes before they propagate into North America. MJO teleconnections thus are positioned 2.9° more eastward in the North Pacific in the LBM. The eastward extended MJO, on the other hand, helps to generate a more eastward-extended RWS. However, negligible change is found in the east–west position of MJO teleconnections (only 0.3° more eastward in the LBM) excited from this RWS without the jet impacts. The above results suggest the dominant role of the jet change in influencing future MJO teleconnection position by altering their propagation pathways. [ABSTRACT FROM AUTHOR]

The mechanisms of model-projected atmospheric moisture budget change across North America are examined in simulations conducted with 22 models from phase 5 of the Coupled Model Intercomparison Project. Modern-day model budgets are validated against the European Centre for Medium-Range Weather Forecasts Interim Re-Analysis. In the winter half year transient eddies converge moisture across the continent while the mean flow wets the west from central California northward and dries the southwest. In the summer half year there is widespread mean flow moisture divergence across the west and convergence over the Great Plains that is offset by transient eddy divergence. In the winter half year the models project drying for the southwest and wetting to the north. Changes in the mean flow moisture convergence are largely responsible across the west but intensified transient eddy moisture convergence wets the northeast. In the summer half year widespread declines in precipitation minus evaporation ( P − E) are supported by mean flow moisture divergence across the west and transient eddy divergence in the Great Plains. The changes in mean flow convergence are related to increases in specific humidity but also depend on changes in the mean flow including increased low-level divergence in the U.S. Southwest and a zonally varying wave that wets the North American west and east coasts in winter and dries the U.S. Southwest. Increased transient eddy fluxes occur even as low-level eddy activity weakens and arise from strengthened humidity gradients. A full explanation of North American hydroclimate changes will require explanation of mean and transient circulation changes and the coupling between the moisture and circulation fields. [ABSTRACT FROM AUTHOR]

This study investigates the characteristics and climate impacts of the quasi-biweekly oscillation (QBWO) over the western North Pacific (WNP) in boreal winter based on observational and reanalysis data and numerical experiments with a simplified model. The wintertime convection over the WNP is dominated by significant biweekly variability with a 10–20-day period, which explains about 66% of the intraseasonal variability. Its leading mode on the biweekly time scale is a northwestward-propagating convection dipole over the WNP, which oscillates over a period of about 12 days. When the convection-active center of this QBWO is located to the east of the Philippines, it can generate an anticyclonic vorticity source to the south of Japan via inducing upper-tropospheric divergence and excite a Rossby wave train propagating toward North America along the Pacific rim. The resultant lower-tropospheric circulation facilitates cold advection and leads to cold anomalies over central North America in the following week. This result highlights a cause–effect relationship between the WNP convection and the North American climate on the quasi-biweekly time scale and may provide some prediction potential for the North American climate. Significance Statement: This study establishes a cause–effect relationship between the wintertime western North Pacific convection and the central North American air temperature on the quasi-biweekly time scale. In boreal winter, the convection over the western North Pacific oscillates significantly with a 10–20-day period. When the convection is active, it can disturb the atmosphere to the south of Japan and excite a midlatitude Rossby wave train. The latter propagates along the North Pacific rim and leads to cold spells over central North America within one week. This information connects the climate variability across the Pacific and provides an additional subseasonal-to-seasonal prediction potential for the North American winter climate. [ABSTRACT FROM AUTHOR]

The approximately century-long instrumental record of precipitation over land reflects a single sampling of internal variability. Thus, the spatiotemporal evolution of the observations is only one realization of "what could have occurred" given the same climate system and boundary conditions but different initial conditions. While climate models can be used to produce initial-condition large ensembles that explicitly sample different sequences of internal variability, an analogous approach is not possible for the real world. Here, we explore the use of a statistical model for monthly precipitation to generate synthetic ensembles based on a single record. When tested within the context of the NCAR Community Earth System Model version 1 Large Ensemble (CESM1-LE), we find that the synthetic ensemble can closely reproduce the spatiotemporal statistics of variability and trends in winter precipitation over the extended contiguous United States and that it is difficult to infer the climate change signal in a single record given the magnitude of the variability. We additionally create a synthetic ensemble based on the Global Precipitation Climatology Centre (GPCC) dataset, termed the GPCC-synth-LE; comparison of the GPCC-synth-LE with the CESM1-based ensembles reveals differences in the spatial structures and magnitudes of variability, highlighting the advantages of an observationally based ensemble. We finally use the GPCC-synth-LE to analyze three water resource metrics in the upper Colorado River basin: frequency of dry, wet, and whiplash years. Thirty-one-year "climatologies" in the GPCC-synth-LE can differ by over 20% in these key water resource metrics due to sampling of internal variability, and individual ensemble members in the GPCC-synth-LE can exhibit large near-monotonic trends over the course of the last century due to sampling of internal variability alone. [ABSTRACT FROM AUTHOR]

The present study investigates the intraseasonal oscillations over the North Pacific during summer based on the ERA-Interim reanalysis dataset. It is shown that the main component of intraseasonal variations in meridional wind is dominated by 10–30-day variability. Zonally oriented wave trains are identified over the North Pacific at this band, with a zonal wavenumber 6. The wave trains exhibit an equivalent-barotropic structure, with the maximum amplitude in the upper troposphere, and are manifested as quasi-stationary Rossby waves with the energy dispersing eastward. The wave trains do not show a phase-locking feature; that is, they have no preferred geographical locations in the zonal direction. Furthermore, energy analyses suggest that the intraseasonal waves gain energy through baroclinic energy conversion, while the barotropic energy conversion plays a negligible role. The present results have implications for better understanding and forecasting weather and climate in North America, since the intraseasonal waves over the North Pacific may act as precursory signals for extreme events occurring over North America. [ABSTRACT FROM AUTHOR]

This study presents the ability of seasonal forecastmodels to represent the observedmidlatitude teleconnection associated with El Niño-Southern Oscillation (ENSO) events over the North American region for the winter months of December, January, and February. Further, the impacts of the associated errors on regional forecast performance for winter temperatures are evaluated, with a focus on 1-month-lead-time forecasts. In most models, there exists a strong linear relationship of temperature anomalies with ENSO, and, thus, a clear anomaly sign separation between both ENSOphases persists throughout the winter, whereas linear relationships are weak in observations. This leads to a difference in the temperature forecast performance between the two ENSOphases. Forecast verification scores show that the winter-season warming events during El Niño in northern North America are more correctly forecast in the models than the cooling events during La Niña and that the winter-season cooling events during El Niño in southern North America are also more correctly forecast in the models than warming events during LaNiña. One possible reason for this result is that the remote atmospheric teleconnection pattern in the models is almost linear or symmetric between the El Niño and La Niña phases. The strong linear atmospheric teleconnection appears to be associated with the models' failure in simulating the westward shift of the tropical Pacific Ocean rainfall response for the La Niña phase as compared with that for the El Niño phase, which is attributed to the warmer central tropical Pacific in themodels. This study highlights that understanding howthe predictive performance of climatemodels varies according to El Niño orLaNiña phases is very important when utilizing predictive information from seasonal forecastmodels. [ABSTRACT FROM AUTHOR]

A new regime index is constructed to capture the seasonal development of the stratospheric polar vortex in the northern winter, based on the standard deviation of Ertel's potential vorticity in the upper stratosphere in November–December. The narrow-jet flow regime is characterized by a polar vortex that is more confined to high latitudes in the early winter upper stratosphere. This upper-level vortex configuration is more susceptible to the disturbances of upward propagating planetary-scale Rossby waves; the stratospheric polar vortex thus weakens earlier and is vertically shallower. The wide-jet flow regime is characterized by a broader-than-average polar vortex that extends further into the subtropics in the early winter upper stratosphere. The polar night jet then gradually strengthens, moves poleward, and penetrates deep into the lowermost stratosphere, with a sharply defined polar vortex edge due to more frequent Rossby wave breaking. Composite difference analyses show that the wide- and narrow-jet regimes, defined in the uppermost stratosphere in November–December, lead to different circulation anomalies of the lower stratosphere and the troposphere in January–February, offering the potential for improved predictability of subseasonal to seasonal forecasts up to two months ahead. The lower-tropospheric responses in January–February are zonally asymmetric. The narrow-jet regime projects most strongly over the North Atlantic, with an equatorward-shifted and/or broader midlatitude westerly jet. The wide-jet-regime response is characterized by a weakened midlatitude westerly jet over the North Pacific. The two flow regimes also differ in their impacts on the storm track over western Europe and the east coast of North America, which may have implications for extreme weather events in those regions. [ABSTRACT FROM AUTHOR]

In this study, we use analogue method and convolutional neural networks (CNNs) to assess the potential predictability of extreme precipitation occurrence based on large-scale meteorological patterns (LSMPs) for the winter (DJF) of ‘‘Pacific Coast California’’ region (PCCA) and the summer (JJA) of the midwestern United States (MWST). We evaluate the LSMPs constructed with a large set of variables at multiple atmospheric levels and quantify the prediction skill with a variety of complementary performance measures. Our results suggest that LSMPs provide useful predictability of daily extreme precipitation occurrence and its interannual variability over both regions. The 14-yr (2006–19) independent forecast shows Gilbert skill scores (GSS) in PCCA ranging from 0.06 to 0.32 across 24 CNN schemes and from 0.16 to 0.26 across four analogue schemes, in contrast from 0.1 to 0.24 and from 0.1 to 0.14 in MWST. Overall, CNN is shown to be more powerful in extracting the relevant features associated with extreme precipitation from the LSMPs than analogue method, with several single-variate CNN schemes achieving more skillful prediction than the best multivariate analogue scheme in PCCA and more than half of CNN schemes in MWST. Nevertheless, both methods highlight that the integrated vapor transport (IVT, or its zonal and meridional components) enables higher skills than other atmospheric variables over both regions. Warm-season extreme precipitation in MWST presents a forecast challenge with overall lower prediction skill than in PCCA, attributed to the weak synoptic-scale forcing in summer. [ABSTRACT FROM AUTHOR]