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Tropical cyclones (TCs) induce substantial upper‐ocean mixing and upwelling, leading to sea surface cooling. In this study, we explore changes in TC‐induced cold wakes along the United States (U.S.) Southeast and Gulf Coasts during 1982–2020. Our study shows a significant increase in TC‐induced sea surface temperature (SST) cooling of about 0.20°C near the U.S. Southeast Coast over this period. However, for the U.S. Gulf Coast, trends in TC‐induced SST cooling are insignificant. Analysis of the large‐scale oceanic environments indicate that the increasing TC‐induced cold wakes near the Southeast coast have been predominantly caused by the cooling of subsurface waters in that region. This upper‐ocean change is attributed to the enhancement of surface pressure gradient across land‐sea boundary and the associated increase in alongshore winds over there. Further analysis with climate models reveals the important role of anthropogenic forcings in driving these changes in the atmospheric circulation response along the U.S. Southeast Coast. Plain Language Summary: Tropical cyclones (TCs) can induce strong mixing in the upper ocean and upwelling of cold, nutrient‐rich water from subsurface to the surface. This process can induce significant sea surface cooling and enhance primary productivity. Utilizing satellite observations, we found evidence that the sea surface cooling associated with TCs has been increasing significantly in the near‐shore regions of United States (U.S.) Southeast Coast. However, corresponding trends in the U.S. Gulf Coast are not significant. Here we show that the enhanced TC‐induced SST cooling along the U.S. Southeast Coast has occurred in response to changes in the atmospheric circulation associated with global warming. These findings shed light on the potential changes in the interactions between TCs and the upper ocean conditions under a non‐stationary climate. Key Points: The tropical cyclone induced sea surface temperature cooling has significantly increased near the U.S. Southeast Coast in recent decadesThe increasing trend in TC‐induced cold wake is primarily attributed to subsurface cooling driven by the change in atmospheric circulationClimate models suggest greenhouse gases are likely responsible for the atmospheric circulation changes [ABSTRACT FROM AUTHOR]

The cool season (November–March) of 2022–2023 was exceptional in the western United States (US), with the highest precipitation totals in ≥128 years in some areas. Recent precipitation extremes and expectations based on thermodynamics motivate us to evaluate the evidence for an anthropogenic intensification of western US cool‐season precipitation to date. Over cool seasons 1951–2023, trends in precipitation totals on the wettest cool‐season days were neutral or negative across the western US, and significantly negative in northern California and parts of the Pacific Northwest, counter to the expected net intensification effect from anthropogenic forcing. Multiple reanalysis data sets indicate a corresponding lack of increase in moisture transports into the western US, suggesting that atmospheric circulation trends over the North Pacific have counteracted the increases in atmospheric moisture expected from warming alone. The lack of precipitation intensification to date is generally consistent with climate model simulations. A large ensemble of 648 simulations from 35 climate models suggests it is too soon to detect anthropogenic intensification of precipitation across much of the western US. In California, the 35‐model median time of emergence for intensification of the wettest days is 2080 under a mid‐level emissions scenario. On the other hand, observed reductions of precipitation extremes in California and the Pacific Northwest are near the lower edge of the large ensemble of simulated trends, calling into question model representation of western US precipitation variability. Plain Language Summary: After warming, one of the best understood climate responses to greenhouse gasses is increased atmospheric moisture (from more evaporation) and resultant storm intensification. Given that hydrological infrastructure and policies are probably more attuned to past climate than future climate, intensified precipitation has important implications for management of flood hazards and water resources. In the western US, the very wet winter of 2023 and the extensive flooding that resulted indicated that this region may be highly vulnerable to increases in precipitation extremes. Are precipitation extremes already intensifying in the western US? We find no evidence for intensified western US winter precipitation thus far. In fact, precipitation intensity actually decreased in northern California and the Pacific Northwest over 1951–2023. In California, most climate models do not project intensified precipitation to become detectable from that region's wide range of natural variability until the 2060s even under heavy greenhouse‐gas emissions. By the end of this century, however, most climate models consistently project the strongest storms to be stronger than they were historically across most or all of the western US. Thus, the lack of precipitation intensification thus far should not dissuade planning for greater precipitation intensity and flood risks. Key Points: Over 1951–2023, precipitation on the wettest cool‐season days did not increase across most of the western US, and even declined in areasIn California, most climate models do not project human‐caused precipitation intensification to become detectable before the 2060sClimate models rarely simulate precipitation intensity to decline as much as it did in northern California and the Pacific Northwest [ABSTRACT FROM AUTHOR]

Predicting future climate change over a region of complex terrain, such as the western United States (US), remains challenging due to the low resolution of global climate models (GCMs). Yet the climate extremes of recent years in this region, such as floods, wildfires, and drought, are likely to intensify further as climate warms, underscoring the need for high-quality and high-resolution predictions. Here, we present an ensemble of dynamically downscaled simulations over the western US from 1980–2100 at 9 km grid spacing, driven by 16 latest-generation GCMs. This dataset is titled the Western US Dynamically Downscaled Dataset (WUS-D3). We describe the challenges of producing WUS-D3, including GCM selection and technical issues, and we evaluate the simulations' realism by comparing historical results to temperature and precipitation observations. The future downscaled climate change signals are shaped in physically credible ways by the regional model's more realistic coastlines and topography. (1) The mean warming signals are heavily influenced by more realistic snowpack. (2) Mean precipitation changes are often consistent with wetting on the windward side of mountain complexes, as warmer, moister air masses are uplifted orographically during precipitation events. (3) There are large fractional precipitation increases on the lee side of mountain complexes, leading to potentially significant changes in water resources and ecology in these arid landscapes. (4) Increases in precipitation extremes are generally larger than in the GCMs, driven by locally intensified atmospheric updrafts tied to sharper, more realistic gradients in topography. (5) Changes in temperature extremes are different from what is expected by a shift in mean temperature and are shaped by local atmospheric dynamics and land surface feedbacks. Because of its high resolution, comprehensiveness, and representation of relevant physical processes, this dataset presents a unique opportunity to evaluate societally relevant future changes in western US climate. [ABSTRACT FROM AUTHOR]

On seasonal time scales, vapor pressure deficit (VPD) is a known predictor of burned area in the southwestern United States ("the Southwest"). VPD increases with atmospheric warming due to the exponential relationship between temperature and saturation vapor pressure. Another control on VPD is specific humidity, such that increases in specific humidity can counteract temperature-driven increases in VPD. Unexpectedly, despite the increased capacity of a warmer atmosphere to hold water vapor, near-surface specific humidity decreased from 1970 to 2019 in much of the Southwest, particularly in spring, summer, and fall. Here, we identify declining near-surface humidity from 1970 to 2019 in the southwestern United States with both reanalysis and in situ station data. Focusing on the interior Southwest in the months preceding the summer forest fire season, we explain the decline in terms of changes in atmospheric circulation and moisture fluxes between the surface and the atmosphere. We find that an early spring decline in precipitation in the interior region induced a decline in soil moisture and evapotranspiration, drying the lower troposphere in summer. This prior season precipitation decline is in turn related to a trend toward a Northern Hemisphere stationary wave pattern. Finally, using fixed humidity scenarios and the observed exponential relationship between VPD and burned forest area, we estimate that with no increase in temperature at all, the humidity decline alone would still lead to nearly one-quarter of the observed VPD-induced increase in burned area over 1984–2019. Significance Statement: Burned forest area has increased significantly in the southwestern United States in recent decades, driven in part by an increase in atmospheric aridity [vapor pressure deficit (VPD)]. Increases in VPD can be caused by a combination of increasing temperature and decreasing specific humidity. As the atmosphere warms with climate change, its capacity to hold moisture increases. Despite this, there is a decrease in near-surface air humidity in the interior southwestern United States over 1970–2019, which during the summer is likely caused by a decline in early spring precipitation leading to limited soil moisture and evaporation in spring and summer. We estimate that this declining humidity alone, without an increase in temperature, would cause about one-quarter of the VPD-induced increase in burned forest area in this region over 1984–2019. [ABSTRACT FROM AUTHOR]

Land surface‐atmosphere coupling and soil moisture memory are shown to combine into a distinct temporal pattern for wildfire incidents across the western United States. We investigate the dynamic interplay of observed soil moisture, vegetation water content, and atmospheric dryness in relation to fuel loading, fire ignition and post‐fire recovery. We find that positive soil moisture anomalies around 5 months before fire ignition increase biomass growth in the subsequent months, thereby shaping fire‐prone vegetation conditions. Then, concurrent decrease in soil moisture, vegetation dehydration, and atmospheric dryness collectively contribute to the occurrence of fire ignition events. This is followed by a rapid recovery in both soil and atmospheric moisture within several weeks after the fire incidents. Our findings provide insights into understanding of wildfire ignition dynamics, supporting fire modeling and enabling improved fire predictions, early warning systems, and mitigation strategies. Plain Language Summary: We find that wildfire are part of a distinct temporal pattern of soil moisture, vegetation water content and atmospheric dryness dynamics that begin about 5 months before the incidents. We analyze anomalies in soil moisture, vegetation water content, vapor pressure deficit and precipitation before and after large wildfires during the warm season across various US climate regions. We document distinct patterns in soil aridity and atmospheric dryness, fuel load, and vegetation dehydration that contribute to the occurrence of wildfires. Our observation‐based analyses show that soil moisture anomalies significantly control the growth of biomass several months before the fire occurrence, which in turn affects the availability of fire fuel. Notable dry anomalies with fuel accumulation in the dry western climate regions are observed approximately 4 to 5 months before the fires, followed by a quick recovery trend several weeks after the fire in wet regions. Our results indicate that in the majority of the climate regions, there are significant dry anomalies preceding the occurrence of wildfires. Understanding the dynamics of these environmental variables can be the basis for improved wildfire hazard predictions and mitigation strategies. Key Points: Wetter‐than‐average soil moisture 4–5 months before wildfires results in increased aboveground biomass accumulationSoil moisture decrease and atmospheric drying after peak biomass lead to dry fuel availability at the time of wildfire ignitionThe temporal pattern is evident in mapped data on soil moisture, vegetation water content and wildfire incidents across western United States [ABSTRACT FROM AUTHOR]

Weather types or weather regimes represent the dominant modes of large‐scale atmospheric circulation patterns and have been used to understand and explain the physical mechanisms of different weather events. While there have been many studies that analyse the changes in extreme climate events through the lenses of weather typing, there is a lack of studies that attribute changes in flood extremes to changes in weather regimes. Here we examine the potential applicability of weather types as predictors of flood extremes. For 4535 streamgages across the conterminous United States, we employ a statistical attribution approach to model the seasonal and annual maximum discharge, utilizing five weather types with distinct synoptic features. Although there are regional patterns in the relationship between weather types and the major climate drivers of flooding, our results show that the frequency of weather types does not provide enough information to model the interannual variability in the magnitude of flood peaks across the conterminous United States. [ABSTRACT FROM AUTHOR]

Predicting future climate change over a region of complex terrain, such as the western United States (U.S.), remains challenging due to the low resolution of global climate models (GCMs). Yet climate extremes of recent years in this region, such as floods, wildfires, and drought, are likely to intensify further as climate warms, underscoring the need for high-quality predictions. Here, we present an ensemble of dynamically downscaled simulations over the western U.S. from 1980-2100 at 9-km grid spacing, driven by sixteen latest-generation GCMs. This dataset is titled the Western U.S. Dynamically Downscaled Dataset (WUS-D3). We describe the challenges of producing WUS-D3, including GCM selection and technical issues, and we evaluate the simulations' realism by comparing historical results to temperature and precipitation observations. The future downscaled climate change signals are shaped in physically credible ways by the regional model's more realistic coastlines and topography: (1) The mean warming signals are heavily influenced by more realistic snowpack. (2) Mean precipitation changes are often consistent with wetting on the windward side of mountain complexes, as warmer, moister air masses are uplifted orographically during precipitation events. (3) There are large fractional precipitation increases on the lee side of mountain complexes, leading to potentially significant changes in water resources and ecology in these arid landscapes. (4) Increases in precipitation extremes are generally larger than in the GCMs, driven intensified local atmospheric updrafts tied to topography. (5) Changes in temperature extremes are different from what is expected by a shift in mean temperature and are shaped by local atmospheric dynamics and land surface feedbacks. Because of its high resolution, comprehensiveness, and representation of relevant physical processes, this dataset presents a unique opportunity to evaluate societally relevant future changes in western U.S. climate. [ABSTRACT FROM AUTHOR]

During the mid‐Holocene (MH: ∼6,000 years Before Present) and Last Interglacial LIG (LIG: ∼129,000–116,000 years Before Present) differences in the seasonal and latitudinal distribution of insolation drove Northern Hemisphere high‐latitude warming comparable to that projected for the end of the 21st century in low emissions scenarios. Paleoclimate proxy records point to distinct but regionally variable hydroclimatic changes during these past warm intervals. However, model simulations have generally disagreed on North American regional moisture patterns during the MH and LIG. To investigate how closely the latest generation of models associated with the Paleoclimate Model Intercomparison Project (PMIP4) reproduces proxy‐inferred moisture patterns during recent warm periods, we compare hydroclimate output from 17 PMIP4 models with newly updated compilations of moisture‐sensitive North American proxy records during the MH and LIG. Agreement is lower for the MH, with models producing wet anomalies across the western United States (US) where most proxies indicate increased aridity relative to the preindustrial period. The models that agree most closely with the LIG proxy compilation display relative wetness in the eastern US and Alaska, and dryness in the northwest and central US. An assessment of atmospheric dynamics using an ensemble of the three LIG simulations that best agree with the proxies suggests that weaker winter North Pacific pressure gradients and steeper summer North Pacific and Atlantic gradients drive LIG precipitation patterns. Our updated compilations and proxy‐model comparisons offer a tool for benchmarking climate models and their performance in simulating climate states that are warmer than present. Plain Language Summary: The mid‐Holocene (MH) and the Last Interglacial (LIG) are the two most recent intervals that were warmer than the preindustrial and so are potentially informative analogs for future emissions scenarios. We compare the newest generation of climate models with North American precipitation patterns indicated by proxy records during the MH and LIG. We find that agreement is lower for the MH, with models producing wet anomalies across the western United States (US) where most records indicate drier conditions. Most LIG simulations show wetter conditions than the preindustrial in Alaska, northern Canada, and the southwestern US, yet the models that agree most closely with the LIG proxies also show wetness in the eastern US and aridity in the Pacific Northwest and central US. Using a subset of the three models that most closely agree with the LIG proxy records, we find that differences in LIG sea level pressure gradients in the North Pacific and North Atlantic Oceans drove shifts in the spatial and seasonal distribution of precipitation across North America. Our approach offers a strategy for assessing how well models simulate past climate during times when it was warmer than modern conditions, which may offer insight into future climate change. Key Points: PMIP4 models agree more closely with moisture‐sensitive North American proxy records during the Last Interglacial than the mid‐HoloceneA subset ensemble of three models maximizes agreement and suggests sea level pressure gradient differences drove Last Interglacial precipitation patternsOur proxy‐model comparisons offer a tool for benchmarking model skill in simulating climate states that are warmer than modern conditions [ABSTRACT FROM AUTHOR]

During the last ice age, the western United States was covered by large lakes, sustained partly by higher levels of precipitation. Increased rainfall was driven by the atmospheric circulation associated with the presence of large North American ice sheets, yet Pleistocene lakes generally reached their highstands not at glacial maximum but during deglaciation. Prior modeling studies, however, showed nearly monotonic drying since the last glacial maximum. Here I show that iTraCE, a new transient climate simulation of the last deglaciation, reproduces a robust peak in winter rainfall over the Great Basin near 16 ka. The simulated peak is driven by a transient strengthening and southward shift of the midlatitude jet. While meltwater forcing is an important driver of changes to the North Pacific Jet, changing orbital conditions and rising atmospheric CO2 also shift the jet south and contribute to wetter conditions over the western US during deglaciation. Plain Language Summary: At the height of the last ice age, the western United States was covered by large lakes such as Lake Bonneville and Lake Lahontan that required more rainfall to be sustained. It is believed that the 3–4 km thick North American ice sheet over Canada acted as an obstacle to the atmospheric flow, forcing storms to be deflected southward over the southwestern US and bringing more winter rain. While wet conditions during glacial maximum are attributable to the presence of a large ice sheet, why does geological evidence indicate that most lakes attained their maximum size not when the ice sheet was at it largest, but rather when the ice sheet was already melting? Here, I use climate simulations to show that other factors, such as changes to Earth's tilt and temperature, in conjunction with changes in ocean circulation, caused a temporary further increase in rainfall that explains lake expansions during the deglaciation. Key Points: Geological evidence indicates many lakes over the western United States reached highstands during the last deglaciationiTraCE, a transient simulation of the last deglaciation, shows wetter conditions at 16 ka than at 20 ka and compares well to proxy evidenceOrbital conditions, rising atmospheric CO2, and meltwater flux all contribute to lake expansions inferred during Heinrich Stadial 1 [ABSTRACT FROM AUTHOR]

Mesoscale convective systems (MCSs) play a key role in regulating variability in the U.S. water and energy cycle. Here a hierarchical dissection of the multiscale forcing of springtime MCSs is carried out through a two-step classification process. Hierarchical clustering is first applied to spatiotemporally evolving upper-tropospheric height fields to reveal large-scale forcing patterns of MCSs. Five distinct forcing patterns (clusters) are identified with three being "remotely forced" and two associated with "local growth." The upper-level troughs associated with these forcing patterns create broad envelopes downstream within which large-scale ascent and MCS genesis tend to occur. Further classification of MCSs based on MCS track locations reveals that local dynamic and thermodynamic forcing determines the precise locations of MCS genesis in the envelope created by large-scale forcing. Specifically, MCSs often occur near surface fronts in warm sectors of surface low pressure systems and are accompanied by low-level kinematic and moisture convergence driven by low-level jets (LLJs). Nearly 50% of spring MCSs are associated with potential instability realized through frontal lifting, and the highest probability of MCS genesis is seen with an environmental CAPE of ∼1400 J kg−1 and CIN of ∼150 J kg−1. The positive trend of the U.S. MCS genesis frequency observed in recent decades is found to be driven by the cluster of MCSs forced at large scale by the Pacific storm track. Regression analysis further suggests that the growing phase of the Pacific decadal oscillation (PDO) modulates the associated MCS large-scale forcing and is ultimately responsible for the positive MCS trend. Significance Statement: The purpose of this study is to provide a systematic classification of multiscale forcing factors triggering mesoscale convective system development over the United States. These storms are very active in spring and often lead to intense rainfall and other weather hazards such as lightning, hail, and tornadoes. They play a key role in the U.S. hydrological cycle and have been occurring more frequently over the past several decades. Our study reveals the detailed characteristics of atmospheric forcing leading to these storms. Such information lays theoretical grounds for designing prediction schemes of warm season severe weather and provides guidance for model development to improve climate models' simulation and long-term projection of these storms. [ABSTRACT FROM AUTHOR]

Extreme heat events are a threat to human health, productivity, and food supply, so understanding their drivers is critical to adaptation and resilience. Anticyclonic circulation and certain quasi-stationary Rossby wave patterns are well known to coincide with heatwaves, and soil moisture deficits amplify extreme heat in some regions. However, the relative roles of these two factors in causing heatwaves is still unclear. Here we use constructed circulation analogs to estimate the contribution of atmospheric circulation to heatwaves in the United States in the Community Earth System Model version 1 (CESM1) preindustrial control simulations. After accounting for the component of the heatwaves explained by circulation, we explore the relationship between the residual temperature anomalies and soil moisture. We find that circulation explains over 85% of heatwave temperature anomalies in the eastern and western United States but only 75%–85% in the central United States. In this region, there is a significant negative correlation between soil moisture the week before the heatwave and the strength of the heatwave that explains additional variance. Further, for the hottest central U.S. heatwaves, positive temperature anomalies and negative soil moisture anomalies are evident over a month before heatwave onset. These results provide evidence that positive land–atmosphere feedbacks may be amplifying heatwaves in the central United States and demonstrate the geographic heterogeneity in the relative importance of the land and atmosphere for heatwave development. Analysis of future circulation and soil moisture in the CESM1 Large Ensemble indicates that, over parts of the United States, both may be trending toward greater heatwave likelihood. [ABSTRACT FROM AUTHOR]

Precipitation is vital for the water‐limited region of the southwestern United States. Coupled Model Intercomparison Project Phase 6 global climate models project 21st century precipitation trends of varying sign for this region, even if forced by an identical anthropogenic emissions scenario. This study investigates the role of the present‐day and future atmospheric circulation in driving the disparity in precipitation trends among models. The wettest model projections are linked to the development of an anomalous mid‐tropospheric trough over the eastern North Pacific Ocean, which depends in part on future unpredictable internal variability. By contrast, future precipitation trends are also linked to models' representation of the present‐day climatological mid‐tropospheric ridge over western North America. Models that fail to properly simulate this ridge in the present‐day climatology are responsible for the most extreme outlier precipitation scenarios for the Southwest for the 21st century: extreme drying in winter and extreme wetting in summer. Plain Language Summary: The southwestern United States contains major population centers and agricultural regions that depend on limited water resources. Computer models used to predict future climate change disagree on how precipitation will change in this region over the 21st century. The goal of this study is to investigate why different models predict different future precipitation changes for this region. The key finding is that how well models simulate the present‐day configuration of the atmospheric jet streams over western North America is closely linked to what they predict for future precipitation change in the Southwest. By excluding models with poor representations of the present‐day jet streams, the range of physically plausible future precipitation scenarios for the Southwest can be narrowed to exclude extreme drying trends during winter and extreme wetting trends during summer. Key Points: Global climate models do not agree on the sign of 21st century precipitation trends for the southwestern United StatesFuture precipitation trends in this region are closely tied to the models' present‐day mid‐tropospheric flow over western North AmericaModels with the most biased present‐day mid‐tropospheric flow project the largest drying trends in winter and wetting trends in summer [ABSTRACT FROM AUTHOR]

Identifying the origins of wintertime climate variations in the Northern Hemisphere requires careful attribution of the role of El Niño–Southern Oscillation (ENSO). For example, Aleutian low variability arises from internal atmospheric dynamics and is remotely forced mainly via ENSO. How ENSO modifies the local sea surface temperature (SST) and North American precipitation responses to Aleutian low variability remains unclear, as teasing out the ENSO signal is difficult. This study utilizes carefully designed coupled model experiments to address this issue. In the absence of ENSO, a deeper Aleutian low drives a positive Pacific decadal oscillation (PDO)-like SST response. However, unlike the observed PDO pattern, a coherent zonal band of turbulent heat flux–driven warm SST anomalies develops throughout the subtropical North Pacific. Furthermore, non-ENSO Aleutian low variability is associated with a large-scale atmospheric circulation pattern confined over the North Pacific and North America and dry precipitation anomalies across the southeastern United States. When ENSO is included in the forcing of Aleutian low variability in the experiments, the ENSO teleconnection modulates the turbulent heat fluxes and damps the subtropical SST anomalies induced by non-ENSO Aleutian low variability. Inclusion of ENSO forcing results in wet precipitation anomalies across the southeastern United States, unlike when the Aleutian low is driven by non-ENSO sources. Hence, we find that the ENSO teleconnection acts to destructively interfere with the subtropical North Pacific SST and southeastern United States precipitation signals associated with non-ENSO Aleutian low variability. [ABSTRACT FROM AUTHOR]

It has been known that the southwestern United States (US) has experienced a drying trend during spring as climate warms. Less is known about the projected increase of summer precipitation in the region and its physical mechanisms. By using climate model simulations and moisture budget analysis, we show that in contrast to the spring, the changes of moisture gradient and wind convergence both cause increasing precipitation during summer. The change of the moisture gradient is featured by larger increase of water vapor along the western coast than inland, thus causing enhanced moisture advection in the future climate. The change of the wind convergence is caused by the maximum jet weakening over the continental US near the latitudes of the region, which leads to enhanced moisture convergence. Plain Language Summary: Precipitation in the southwestern United States (US) is projected to decrease in the spring but increase in the summer under climate warming. It has been known that the spring dry is caused by enhanced zonal drying advection. Here, we performed moisture budget analysis using climate model simulations and found that in contrast to the spring, the moisture gradient change and the wind convergence change both increase the precipitation in the summer. There is more moisture increase along the western coast than inland in the summer. Hence the westerly brings more moisture into the southwestern US and increases precipitation. There is more wind convergence with warming during summer in the southwestern US, which induces more moisture convergence and hence more precipitation. Such wind convergence increase is associated with the maximum jet weakening over land near the southwestern US. Spring drying and summer wetting in the southwestern US demonstrate how different changes of atmospheric dynamics and thermodynamics in different seasons determine the precipitation change. Key Points: Precipitation decreases during spring but increases during summer in the southwestern United States in response to warmingEnhanced zonal moisture advection causes moisture convergence in the summerStronger wind convergence associated with jet weakening is mainly responsible for the summer precipitation increase [ABSTRACT FROM AUTHOR]

Previous studies have identified a recent increase in wildfire activity in the western United States (WUS). However, the extent to which this trend is due to weather pattern changes dominated by natural variability versus anthropogenic warming has been unclear. Using an ensemble constructed flow analogue approach, we have employed observations to estimate vapor pressure deficit (VPD), the leading meteorological variable that controls wildfires, associated with different atmospheric circulation patterns. Our results show that for the period 1979 to 2020, variation in the atmospheric circulation explains, on average, only 32% of the observed VPD trend of 0.48 6 0.25 hPa/decade (95% CI) over the WUS during the warm season (May to September). The remaining 68% of the upward VPD trend is likely due to anthropogenic warming. The ensemble simulations of climate models participating in the sixth phase of the Coupled Model Intercomparison Project suggest that anthropogenic forcing explains an even larger fraction of the observed VPD trend (88%) for the same period and region. These models and observational estimates likely provide a lower and an upper bound on the true impact of anthropogenic warming on the VPD trend over the WUS. During August 2020, when the August Complex "Gigafire" occurred in the WUS, anthropogenic warming likely explains 50% of the unprecedented high VPD anomalies. [ABSTRACT FROM AUTHOR]

Using synoptic classification techniques, synoptic‐scale weather types associated with large exports of dissolved organic carbon and nitrate‐nitrogen in three forested watersheds in the northeastern United States are analyzed. In contrast to Siegert et al. (2021, https://doi.org/10.1029/2020jd033413; Part 1), which details the general synoptic conditions associated with stream chemistry variations, this study focuses on the long‐term frequency, trends, and global‐scale forcing mechanisms of individual, chemistry‐relevant, synoptic types. Nine individual types are identified as the most important to stream chemistry exports in northeastern watersheds during a 2.5‐year period of high‐frequency stream chemistry observation (2014–2016). Streamflow chemistry was the most influenced by Northwest Flow synoptic weather types in Vermont, cold front passages associated with Weak Westerly Flow types in Rhode Island, and Southwest Flow (SWF) types in Maryland. Each type provides unique atmospheric conditions that result in variations in precipitation, and thus chemical signals. From 1948 to 2017, the Arctic and North Atlantic Oscillations greatly influenced the interannual frequency of the analyzed synoptic types. When the indices were positively phased, SWF types were more frequent, while Northwest Flow and Weak Westerly Flow types were less frequent. Long‐term trends in synoptic type frequency are, inpart, due to documented changes in these teleconnection indices toward more positively phased configurations. As the climate continues to change into the 21st century, such associations may continue to drive large changes in synoptic type frequency, and thus watershed hydrology and biogeochemistry in the Northeast region. Key Points: Individual synoptic weather types uniquely influence the export of dissolved organic carbon (DOC) and NO3 solutes in watersheds of the Northeast United StatesThe interannual frequency and precipitation signals of multiple chemistry‐relevant synoptic types exhibit long‐term linear trendsVariations in synoptic type frequency, and thus stream chemistry, are partially forced by teleconnection indices, such as the North Atlantic Oscillation (NAO) [ABSTRACT FROM AUTHOR]

Observed United States trends in the annual maximum 1-day precipitation (RX1day) over the last century consist of 15%–25% increases over the eastern United States (East) and 10% decreases over the far western United States (West). This heterogeneous trend pattern departs from comparatively uniform observed increases in precipitable water over the contiguous United States. Here we use an event attribution framework involving parallel sets of global atmospheric model experiments with and without climate change drivers to explain this spatially diverse pattern of extreme daily precipitation trends. We find that RX1day events in our model ensembles respond to observed historical climate change forcing differently across the United States with 5%–10% intensity increases over the East but no appreciable change over the West. This spatially diverse forced signal is broadly similar among three models used, and is positively correlated with the observed trend pattern. Our analysis of model and observations indicates the lack of appreciable RX1day signals over the West is likely due to dynamical effects of climate change forcing—via a wintertime atmospheric circulation anomaly that suppresses vertical motion over the West—largely cancelling thermodynamic effects of increased water vapor availability. The large magnitude of eastern U.S. RX1day increases is unlikely a symptom of a regional heightened sensitivity to climate change forcing. Instead, our ensemble simulations reveal considerable variability in RX1day trend magnitudes arising from internal atmospheric processes alone, and we argue that the remarkable observed increases over the East has most likely resulted from a superposition of strong internal variability with a moderate climate change signal. Implications for future changes in U.S. extreme daily precipitation are discussed. [ABSTRACT FROM AUTHOR]

Latewood width tree‐ring chronologies from arid‐site conifers in the southwestern United States are correlated with precipitation during portions of the summer monsoon season. The onset date and length of the monsoon season varies across the region, and these regional differences in summer rainfall climatology may impact the strength and timing of the warm season precipitation response of latewood chronologies. The optimal latewood response to summer precipitation is computed on a daily basis using 67 adjusted latewood chronologies (LWa) from the southwestern United States, adjusted to remove correlation with preceding earlywood growth. Most LWa chronologies are significantly correlated with precipitation summed over a period of approximately 4 weeks (29 days) in early summer. This early summer precipitation signal is present in most ponderosa pine chronologies across the study area. It is also evident in Douglas‐fir chronologies, but only from southern Arizona and New Mexico. The Julian date of summer precipitation onset increases from south to north in the instrumental precipitation data for the southwestern United States. The timing of the early summer season precipitation response in most LWa chronologies also tends to occur later in the summer from southeastern Arizona into northern New Mexico and eastern Colorado. Principal components analysis of the LWa chronologies reproduces two of the three most important spatial modes of early summer precipitation covariability seen in the instrumental data. The first PC of LWa is related to the same atmospheric circulation features associated with PC1 of instrumental early summer precipitation, including cyclonic circulation over the southwestern United States and moisture advection from the eastern Pacific. Correlation analyses between antecedent cool season precipitation and early summer rainfall using instrumental and tree‐ring reconstructed precipitation indicates that the tree‐ring data reproduce the multi‐decadal variability in correlation between seasons seen in the instrumental data. [ABSTRACT FROM AUTHOR]

Rapid drought intensification, or flash droughts, is often driven by anomalous atmospheric ridging and can cause severe and complex impacts on water availability and agriculture, but the full range of variability of such events in terms of intensity and frequency is unknown. New tree‐ring reconstructions of May–July mid‐tropospheric ridging and soil moisture anomalies back to 1500 CE in the central United States—a hotspot for flash drought—suggest that over the last five centuries, anomalies in these two variables combined to indicate flash‐drought conditions in ∼17% of years and exceptionally severe flash drought in ∼4% of years, similar to frequencies in recent decades. However, over one‐third of all inferred exceptional flash droughts occurred since 1900, suggesting the 20th century was highly flash‐drought prone. These results may guide future work to diagnose the roles of external, oceanic, and land‐surface forcing of warm‐season atmospheric circulation and hydroclimate over North America. Plain Language Summary: In 2012, the central United States experienced a "flash drought," when rapid soil drying due to persistently low precipitation totals and high temperatures in late spring and summer caused billions of dollars in damages and agricultural losses. Such events are difficult to forecast because flash droughts can develop in a matter of weeks, and only a handful of flash droughts have been observed in recent decades, giving high uncertainty as to their likelihood. Here, we use tree rings to create two independent annual records of central United States soil moisture and the principal atmospheric circulation pattern known to cause flash droughts that extend back to the year 1500. Taken together, these records provide a new five‐century perspective on these crucial components of flash drought and reveal for the first time the long‐term behavior of central United States flash droughts, including frequency and cyclicity of exceptional events. We find that the instrumental record is a good representation of the long‐term likelihood of flash droughts. This apparent agreement with long‐term average conditions is largely by chance; however, as the reconstructions indicate large century‐to‐century variations in flash‐drought frequency and magnitude over the past 500 years. Key Points: We developed tree‐ring reconstructions of central U.S. soil moisture and the atmospheric ridge that causes flash droughts back to 1500 CEObservations capture flash drought's long‐term probability distribution, but reconstructions reveal centennial fluctuations in variabilityCycles in reconstructed atmospheric ridging may aid diagnosis and prediction of flash drought on interannual to decadal time scales [ABSTRACT FROM AUTHOR]

We introduce the idea of simultaneous heavy precipitation events (SHPEs) to understand whether extreme precipitation has a spatial organization manifested as specified tracks or contiguous fields with inherent scaling relationships. For this purpose, we created a database of SHPEs using ground‐based precipitation observations recorded by the daily Global Historical Climatology Network across the conterminous United States during 1900–2014. SHPEs are examined for their seasonality, spatial manifestation, orientation, and areal extent. We quantified the spatial distribution of the centroids and principal axes of SHPEs and their quasi‐elliptical manifestations, azimuthal orientations, and areal extents on the ground. Four seasons, December‐January‐February (DJF), March‐April‐May (MAM), June‐July‐August (JJA), and September‐October‐November (SON) are considered to examine the spatial patterns and associated large‐scale atmospheric circulations. Results indicate that there are 54, 58, 103, and 204 SHPEs in DJF, MAM, JJA, and SON seasons, and their longest stretches range on average between 650 and 1,600, between 850 and 1,500, between 950 and 1,550, and between 750 and 1,450 km, respectively. SHPEs in the DJF, MAM, and JJA seasons occur mostly over the Pacific coast and central and midwestern United States, respectively. The atmospheric circulation patterns and mechanisms of precipitable water vapor and moisture transport in the atmosphere are also discussed in relation to these SHPEs. Power laws explain SHPEs' underlying area scaling behavior in all the four seasons, with stronger evidence in DJF and MAM. A seasonal spatial risk model is developed to predict the likelihood of SHPEs. Quantifying the characteristics of SHPEs and modeling their footprints can improve the projections of flood risk and understanding of damages to interconnected infrastructure systems. Plain Language Summary: We present a new approach to quantify extreme regional precipitation considering the spatial structure of extreme events. Defined as simultaneous heavy precipitation events (SHPEs), they measure the central location, spatial extent, and the orientation of widespread heavy rains on the land. These characteristics are derived for four seasons over the entire 20th and early 21st centuries (115 years). We interpret the features of SHPEs over the Pacific Coast, Midwest, and the Northeastern United States using a combination of atmospheric circulation and moisture transport features. A seasonal spatial risk model is also developed to identify the probability of any region experiencing SHPEs. The framework and findings presented in this study can help in developing improved flood risk management methods by public/private planners and agencies. The database can be used by the Earth system scientists working on extreme events to explore new avenues of research. Key Points: The location, area, and orientation of widespread precipitation extremes (SHPEs) vary seasonally and spatially across the United StatesThe longest stretch of SHPEs range on average between 650 and 1,600 km, and the frequency distribution of their areal extents follows a power lawA combination of a strong upper‐level wave and moisture convergence are the most common elements of the atmosphere required for the SHPEs [ABSTRACT FROM AUTHOR]

The 100th meridian is a conceptual arid‐humid divide that effectively bisects the continent of the United States into the humid east and arid west. Here, we examine the historical and future shifts of the 100th meridian from atmospheric, hydrologic, and agroecological perspectives. We find that the effective arid‐humid divide regarding vegetation greenness and runoff has been moving toward west with a mean shift of 0.73° (1982–2015) and 2.08° (1961–2010), respectively, suggesting decreased agroecological and hydrologic aridity in the region. For future periods, the agroecological divide shows a persistent westward movement, whereas eastward shifts of the 100th meridian are detected from the atmospheric and hydrologic perspectives. Nevertheless, the eastward movements of the atmospheric and hydrologic divide substantially slow down when the vegetation response to elevated atmospheric CO2 is accounted for. This finding demonstrates that CO2 fertilization on vegetation could largely alleviate the warming‐induced drying tendency around the 100th meridian region. Plain Language Summary: The 100th meridian is a conceptual arid‐humid divide in the physical climate and landscape of the central United States continent and has exerted a profound influence on human settlement and agriculture developments. Using climate projections and aridity index, a previous study reported an eastward movement of the 100th meridian, indicating an overall drying trend in the region. Here, we reexamine the historical and future shifts of the 100th meridian from the atmospheric, hydrologic, and agroecological perspectives. We find that the movements of the 100th meridian are strongly modified by the vegetation response to elevated atmospheric CO2 concentration that CO2 fertilization on vegetation could largely alleviate the warming‐induced drying tendency and effectively slows down the eastward movement of the arid‐humid divide. Key Points: Historical and future shifts of the 100th meridian from atmospheric, hydrologic, and agroecological perspectives are assessedObserved hydrologic and agroecological 100th meridian have been moving toward west over the past few decadesProjected agroecological divide moves toward west whereas hydrologic and atmospheric divides move toward east in the coming century [ABSTRACT FROM AUTHOR]

Orographic precipitation gradients (OPG) relating to the increase or decrease in precipitation amount with elevation are not well studied or analyzed except for case examples. A quality controlled daily OPG dataset for the western United States that is based on a linear regression framework of gauge precipitation observations and elevation for a 39-yr time period was created and analyzed to identify spatial and temporal patterns and variability in OPG and some of the drivers of variability on seasonal, annual, interannual, and climatological time scales. Most locations in the western United States experience positive OPG during most of the year, exhibiting an annual cycle with the highest magnitude of OPG in the winter season and lowest magnitude of OPG in the summer season. Coastal locations tend to have OPG with higher magnitude and larger variability in OPG than do interior locations during cool seasons. Empirical orthogonal function analysis identifies two principal components that account for 33% of the variability in a subset of the OPG dataset, and these modes of variability are related to precipitation amount and atmospheric circulation over the Pacific Ocean. Comparison of daily OPG with similarly calculated 3-day and monthly OPG identifies that OPG magnitudes are sensitive to the choice of length of the precipitation accumulation period. [ABSTRACT FROM AUTHOR]

Extreme rainfall over Southwestern United States/Northwestern Mexico (SWUNWM) has been mostly investigated during wet seasons, while no or little attention has been paid to extreme rainfall during dry seasons despite its vital importance for sustaining vegetation and ecosystems. Here we examine the top 1% rainfall over SWUNWM in June, the driest month on average, and assess how it is affected by the ocean with a 50 km-resolution global climate model. Comparing millennia-long simulations with and without the ocean, we find that the ocean does not change the pattern and magnitude of atmospheric circulation associated with June extreme rainfall, but significantly enhances rainfall intensity. This intensification is attributed to a larger variability of atmospheric moisture content enhanced mainly by the sea surface temperature (SST) in the tropical Pacific. The similarities in the atmospheric circulation associated with, and the temporal characteristics of, June extreme rainfall between the two simulations point to a dominant control of extreme rainfall dynamics by atmospheric intrinsic processes and atmosphere-land coupling. These modeling results imply that the predictability of occurrence of June extreme rainfall over SWUNWM is limited by atmospheric intrinsic dynamics and atmosphere-land coupling, while reliable predictions of its intensity likely require a faithful simulation of SST variability, especially in the tropical Pacific. [ABSTRACT FROM AUTHOR]

This study investigates the impact of the Madden–Julian oscillation (MJO) on U.S. tornadogenesis using atmospheric reanalysis and model experiments. Our analysis shows that the impact of MJO on U.S. tornadogenesis is most significant in May–July and during MJO phases 3–4 and 5–6 (P3456). These MJO phases are characterized by anomalous ascending motion over the Maritime Continent (MC) and anomalous subsidence over the northeast Pacific (EP), generating anomalous diabatic heating and cooling, respectively. These in turn generate large-scale atmospheric conditions conducive to tornadogenesis in the United States, enhancing the North American low-level jet (NALLJ) and thus increasing the influx of warm and moist air from the Gulf of Mexico to the United States and increasing the low-level wind shear and convective available potential energy along its path. Conversely, during MJO phases 1–2 and 7–8, the opposite patterns of atmospheric anomalies appear over the United States producing unfavorable environments for U.S. tornadogenesis. We further investigate the underlying mechanism for MJO-induced atmospheric circulations conducive to U.S. tornadogenesis using a linear baroclinic model (LBM). The LBM is forced by diabatic heating over the MC and cooling over the EP, which characterizes the P3456 MJO phase. The model experiment reproduces an anomalous ridge over the southern United States and associated anomalous low-level anticyclone that enhances the NALLJ and increases tornadic environmental parameters. Additional sensitivity experiments prescribing the diabatic heating over the MC and diabatic cooling over the EP independently demonstrate that diabatic cooling over the EP is the main driver for producing regional atmospheric conditions favorable for U.S. tornadogenesis. [ABSTRACT FROM AUTHOR]

A composite analysis reveals how the Madden–Julian oscillation (MJO) impacts North American rainfall through perturbations in both the upper-tropospheric flow and regional low-level moisture availability. Upper-level divergence associated with the MJO tropical convection drives a quasi-stationary Rossby wave response to the midlatitudes. This forces a midlatitude upper-level dipolar geopotential height anomaly that is accompanied by a westward retraction of the jet stream and reduced rainfall over the central-eastern North Pacific. A reverse effect is found as the MJO propagates eastward across the Maritime Continent. These large differences in the extratropical upper-level flow, combined with anomalies in the regional supply of water vapor, have a profound impact on southeastern U.S. rainfall. The low-frequency variability, including that associated with ENSO, can modify the seasonal background flow (e.g., El Niño and La Niña basic states) affecting the distribution, strength, and propagation of the intraseasonal oscillation and the extratropical teleconnection patterns. The combined effects of the ENSO and the MJO signals result in both spatial and temporal patterns of interference and modulation of North American rainfall. The results from this study show that during a particular phase of an active MJO, the extratropical response can considerably enhance or mask the interannual ENSO signal in the United States, potentially resulting in anomalies of the opposite sign than that expected during a specific ENSO phase. Analyses of specific MJO events during an El Niño or La Niña episode reveal significant contributions to extreme events via constructive and destructive interference of the MJO and ENSO signals. [ABSTRACT FROM AUTHOR]

The frequency and intensity of heat waves in the United States is projected to increase in the 21st century. We investigate dry and humid heat waves in a pair of high‐resolution model simulations that constrain large‐scale atmospheric circulation, to isolate the thermodynamic impacts on characteristics of present and future heat waves over the United States. The two kinds of heat waves show differences in mean intensity, amplitude, duration, and frequency over the Southeast, Northeast, and Midwest, while their characteristics are largely similar in the drier central and western United States. In a warmer climate, relative humidity is projected to decrease during dry heat waves, whereas it remains unchanged during humid heat waves. However, the overall increase in daily maximum temperature intensifies the heat stress during future humid and dry heat waves across all regions. With large‐scale circulation constrained, these simulations emphasize the importance of thermodynamic drivers in determining future heat wave characteristics. Key Points: Historic U.S. heat waves are investigated in high‐resolution WRF simulations nudged toward reanalysis with and without anthropogenic warmingDry heat waves become drier, and humid heat waves stay humid in a warmer climate, showing temperature‐driven increase in future heat stressResults suggest thermodynamic drivers dominate future changes in characteristics of both dry and humid heat waves [ABSTRACT FROM AUTHOR]

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

Regional-scale air pollution models are routinely being used worldwide for research, forecasting air quality, and regulatory purposes. It is well recognized that there are both reducible (systematic) and irreducible (unsystematic) errors in the meteorology–atmospheric-chemistry modeling systems. The inherent (random) uncertainty stems from our inability to properly characterize stochastic variations in atmospheric dynamics and chemistry and from the incommensurability associated with comparisons of the volume-averaged model estimates with point measurements. Because stochastic variations are not being explicitly simulated in the current generation of regional-scale meteorology–air quality models, one should expect to find differences between the model estimates and corresponding observations. This paper presents an observation-based methodology to determine the expected errors from current-generation regional air quality models even when the model design, physics, chemistry, and numerical analysis, as well as its input data, were "perfect". To this end, the short-term synoptic-scale fluctuations embedded in the daily maximum 8 h ozone time series are separated from the longer-term forcing using a simple recursive moving average filter. The inherent uncertainty attributable to the stochastic nature of the atmosphere is determined based on 30+ years of historical ozone time series data measured at various monitoring sites in the contiguous United States (CONUS). The results reveal that the expected root mean square error (RMSE) at the median and 95th percentile is about 2 and 5 ppb , respectively, even for perfect air quality models driven with perfect input data. Quantitative estimation of the limit to the model's accuracy will help in objectively assessing the current state of the science in regional air pollution models, measuring progress in their evolution, and providing meaningful and firm targets for improvements in their accuracy relative to ambient measurements. [ABSTRACT FROM AUTHOR]

This study examines space-time patterns of summer daily rainfall variability across the Northeast United States, with a focus on historical trends and the potential for long-lead predictability. Ahidden Markov model based on daily data is used to define six weather states that represent distinct patterns of rainfall across the region, and composites are used to examine atmospheric circulation during each state. The states represent the occurrence of region-wide dry and wet conditions associated with a large-scale ridge and trough over the Northeast, respectively, as well as inland and coastal storm tracks. There is a positive trend in the frequency of the weather state associated with heavy, regionwide rainfall, which is mirrored by a decreasing trend in the frequency of stationary ridges and regionwide dry conditions. The frequency of state occurrences is also examined for historical Northeast droughts. Two primary drought types emerge that are characterized by region-wide dry conditions linked to a persistent ridge and an eastward-shifted storm track associated with light precipitation along the coastline. Finally, composites of May sea surface temperature anomalies (SSTAs) prior to summers with high and low frequencies of each weather state are used to assess long-lead predictability. These composites are compared against similar composites based on regional anomalies in low streamflow conditions [June-August 7-day low flows (SDLFs)]. Results indicate that springtime SSTs, particularly those in the Caribbean Sea and tropical North Atlantic Ocean, provide some predictability for summers with above-average precipitation and SDLFs, but SSTs provide little information on the occurrence of drought conditions across the Northeast. [ABSTRACT FROM AUTHOR]

Climate data obtained from global climate models (GCMs) form the basis of most studies of regional climate change and its impacts. Using the northeastern U.S. as a test case, we develop a framework to systematically sub-select reliable models for use in climate change studies in the region. Model performance over the historical period is evaluated first for a wide variety of standard and process metrics including large-scale atmospheric circulation features that drive regional climate variability. The inclusion of process-based metrics allows identification of credible models in capturing key processes relevant for the climate of the northeastern U.S. Model performance is then used in conjunction with the assessment of redundancy in model projections, especially in summer precipitation, to eliminate models that have better performing counterparts. Finally, we retain some mixed-performing models to maintain the range of climate model uncertainty, required by the fact that model biases are not strongly related to their respective projections. This framework leads to the retention of 16 of 36 CMIP5 GCMs that (a) have a satisfactory historical performance for a variety of metrics and (b) provide diverse climate projections consistent with uncertainties in the multi-model ensemble (MME). Overall, the models show significant variations in their performance across metrics and seasons with none emerging as the best model in all metrics. The retained set reduces the number of models by more than one half, easing the computational burden of using the entire CMIP5 MME, while still maintaining a wide range of projections for risk assessment. The retention of some mixed-performing models to maintain ensemble uncertainty suggests a potential to narrow the ranges in temperature and precipitation. But any further refinement should be based on a more detailed analysis of models in capturing regional climate variability and extremes to avoid providing overconfident projections. [ABSTRACT FROM AUTHOR]

High-impact extratropical cyclones (ETCs) cause considerable damage along the northeast coast of the United States through strong winds and inundation, but these relatively rare events are difficult to analyze owing to limited historical records. Using a 1505-yr simulation from the GFDL FLOR coupled model, statistical analyses of extreme events are performed including exceedance probability computations to compare estimates from shorter segments to estimates that could be obtained from a record of considerable length. The most extreme events possess characteristics including exceptionally low central pressure, hurricane-force winds, and a large surge potential, which would greatly impact nearby regions. Return level estimates of metrics of ETC intensity using shorter, historical-length segments of the FLOR simulation are underestimated compared to levels determined using the full simulation. This indicates that if the underlying distributions of observed ETC metrics are similar to those of the 1505-yr FLOR distributions, the actual frequency of extreme ETC events could also be underestimated. Comparisons between FLOR and reanalysis products suggest that not all features of simulated high-impact ETCs are representative of observations. Spatial track densities are similar, but FLOR exhibits a negative bias in central pressure and a positive bias in wind speed, particularly for more intense events. Although the existence of these model biases precludes the quantitative use of model-derived return statistics as a substitute for those derived from shorter observational records, this work suggests that statistics from future models of higher fidelity could be used to better constrain the probability of extreme ETC events and their impacts. [ABSTRACT FROM AUTHOR]

In this paper, we build upon previous literature in directly addressing the temporal relationship between the stratospheric and tropospheric polar vortex (PV), sea level pressure (SLP), and resultant cold air outbreaks (CAO). An atmospheric and teleconnection analysis was conducted on 49 predefined CAOs across the eastern United States from 1948 to 2016. Clusters of SLP, 100 and 10‐mb geopotential height anomalies were mapped utilizing self‐organizing maps (SOMs) to understand the surface, tropospheric PV, and stratospheric PV patterns preceding CAOs. The Arctic Oscillation (AO), North Atlantic Oscillation (NAO), and Pacific–North American (PNA) teleconnections were used as variables to explain the magnitude and location of mid‐latitude Arctic air displacement. Persistently negative SLP anomalies across the Arctic and North Atlantic were evident 1–2 weeks prior to the CAOs throughout the winter. The tropospheric and stratospheric PV were found to be persistently weak/weakening prior to mid‐winter CAOs and predominantly strong and off‐centred prior to early and late season CAOs. Negative phases of the AO and NAO were favoured prior to CAOs, while the PNA was found to be less applicable. This method of CAO and synoptic pattern characterization benefits from a continuous pattern representation and provides insight as to how specific teleconnections and atmospheric patterns lead to CAOs in the eastern United States. This study has shown that persistently negative SLP anomalies across the Arctic and North Atlantic were evident 1–2 weeks prior to cold air outbreaks (CAOs) in the eastern United States throughout the winter. The tropospheric and stratospheric polar vortex (PV) were found to be persistently weak/weakening prior to mid‐winter CAOs and predominantly strong and off‐centred prior to early and late season CAOs. [ABSTRACT FROM AUTHOR]

In June 2020, a record level of Saharan dust was transported across the Atlantic Ocean impacting air quality in the Caribbean Basin and the United States (US). Satellite images showed the transport, while a series of ground-based monitoring stations captured the surface impacts as the Saharan dust was transported to the Caribbean basin and then moved into the Southern (Houston, Texas; WL), Eastern (Bone, North Carolina; APP) and Midwestern (Bondville, Illinois; BND) US. The present study characterizes the Saharan dust event (SDE) using a comprehensive set of satellite observations and in-situ measurements of particulate matter (PM), and aerosol optical properties (AOPs; σ scat : scattering coefficient, σ abs : absorption coefficient, SAE: scattering Ångström exponent and AAE: absorption Ångström exponent). The Saharan dust intrusion was identified at each site by a marked increase in σ scat , and AAE and a simultaneous decrease in SAE. A maximum hourly average PM 2.5 concentration and σ scat (525 nm) of 97.5 μg m−3 and 190 Mm−1 was observed at WL during the SDE. The maximum hourly average σ scat (550 nm) for PM 10 size cut of 215 and 66.9 Mm−1 was observed at APP and BND, respectively, during the SDE. The AAE at each site reached above 1.3 with an average value of 1.39 ± 0.35, 3.34 ± 0.56 and 1.65 ± 0.27 at WL, APP, and BND, respectively, during the SDE, whereas the average SAE dropped below 0.5 at WL and APP and below 0.9 at BND. The results demonstrated that the identification of SDE using AOPs depends largely on the location of the measurement, which determines the background characteristics of a site. The results suggest that other intensive AOPs like asymmetry parameter (g) and single scattering albedo Ångström exponent (SSAAE) can also be exploited to characterize SDE. Aerosol radiative forcing (ARF) estimates indicate that the SDE resulted in the heating of the atmosphere (+5.37 to +11.8 W m−2) at the rate of 0.11–0.24 K day−1 at the US sites. This atmospheric heating from transported Saharan dust can alter the regional atmospheric dynamics and is relevant to understand potential changes in regional climate. [Display omitted] • Impact of June 2020 Saharan dust event (SDE) on aerosol optical properties in the US. • The June 2020 SDE caused heating of the atmosphere at a rate of up to 0.24 K day−1. • Radiative impacts of SDE are critical for accurate prediction of climate change in the US. [ABSTRACT FROM AUTHOR]

Real-time ensemble forecasts from the Pennsylvania State University (PSU) WRF EnKF system (APSU) for Hurricane Joaquin (2015) are examined in this study. The ensemble forecasts, from early in Joaquin's life cycle, displayed large track spread, with nearly half of the ensemble members tracking Joaquin toward the U.S. East Coast and the other half tracking Joaquin out to sea. The ensemble forecasts also displayed large intensity spread, with many of the members developing into major hurricanes and other ensemble members not intensifying at all. Initial condition differences from the regions greater than (less than) 300 km were isolated by effectively removing initial condition differences in desired regions through relaxing each ensemble member to GFS (APSU) initial conditions. The regions of initial condition errors contributing to the track spread were examined, and the dominant source of track errors arose from the region greater than 300 km from the tropical cyclone center. Further examination of the track divergence revealed that the region between 600 and 900 km from the initial position of Joaquin was found to be the largest source of initial condition errors that contributed to this divergence. Small differences in the low-level steering flow, originating from perturbations between 600 and 900 km from the initial position, appear to have resulted in the bifurcation of the forecast tracks of Joaquin. The initial condition errors north of the initial position of Joaquin were also shown to contribute most significantly to the track divergence. The region inside of 300 km, specifically, the initial intensity of Joaquin, was the dominant source of initial condition errors contributing to the intensity spread. [ABSTRACT FROM AUTHOR]

Rapid onset droughts, termed “flash droughts”, present a series of unique challenges for drought monitoring, forecasting, and mitigation. Due to the rapid onset and lack of early warning systems, stakeholders can be caught off-guard by flash droughts and suffer disproportionate impacts. Despite these impacts, little is known about the physical drivers of flash droughts. The purpose of this study is to determine antecedent meteorological conditions prior to the onset of flash drought in the Eastern United States. Emphasizing the agricultural impacts, flash droughts were defined as periods when the pentad-average 0–40 cm volumetric water content declines from at least the 40th percentile to below the 20th percentile in 4 pentads or less. Meteorological variables from 125 stations in the Eastern U.S. from March − October 1979 − 2010 were analyzed for their relationships with flash drought onset. Consistent with previous findings, flash drought was associated with decreased precipitation and humidity, increased solar radiation, and elevated temperatures. However logistic regression results suggest variables that accounted for surface moisture balance and/or atmospheric evaporative demand were more closely linked with the likelihood of flash drought than temperature and/or precipitation. Associated surface conditions are likely driven by ridging in the mid to upper level troposphere, which is shown to be more persistent leading up the flash droughts in the northern half of the study region. Our results elucidate the meteorological conditions immediately prior to the onset of one type or “flavor” of flash drought, defined by characteristic rapid intensification. Arguably, one could define flash drought with soil moisture thresholds varying from those used in this study and/or different time scales of soil moisture depletion. Therefore, we additionally argue that absences of both a standard flash drought definition and consistent precedent for identifying flash drought complicates monitoring and predicting these events. [ABSTRACT FROM AUTHOR]

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

Long-term relationships between mean-state climatic conditions and flood frequencies in the midcontinental United States (US) are not well established because instrumental records of fluvial processes are limited to the current warm period (CWP; the last ca. 150 years) and continuous paleo-flood records are exceedingly rare. Here, we investigate climate-flood relationships in the midcontinental US by reconstructing flood frequencies at Half Moon Pond, a 1600-year-old oxbow lake on the lower White River, Indiana (watershed = ca, 29,000 km2). We used sediment accumulation rates and clastic fluxes constrained by high-resolution radiocarbon (14C) dating. Frequent flooding, as indicated by high sedimentation rates and clastic fluxes to Half Moon Pond, occurred leading up to and during the Medieval Climate Anomaly (MCA; 950–1250 CE) when paleoclimate records suggest the predominance of ocean-atmosphere mean states resembling the negative phases of the Pacific Decadal Oscillation (-PDO-like) and Pacific North American Mode (-PNA-like). Reductions in sedimentation rates and clastic fluxes, indicating reduced flooding, subsequently occurred during the transition out of the MCA and into the Little Ice Age (LIA; 1250–1830 CE) as ocean-atmosphere conditions shifted to + PDO-like and +PNA-like mean states. Sedimentation rates and clastic fluxes increased again after ca. 1800 CE, indicating increased flooding during the CWP as ocean-atmosphere conditions returned to -PDO-like and -PNA-like mean states. The White River trends were notably antiphased with sedimentation-rate-based flood frequencies for the lower Ohio River (500,000 km2 watershed) prior to 1830 CE. This antiphased relationship is consistent with flooding in moderate to small watersheds in the Midwest being sensitive to the occurrence of rainstorm events, which were more frequent leading up to and during the MCA, and flooding in large watersheds being more sensitive to large spring melts associated with extensive snowpacks, which characterized the LIA. That both the White and Ohio rivers experienced their most frequent flooding during the CWP suggests deforestation and changing land use practices increased flooding on Midwestern watersheds across scales despite a current climatic mean state that in the past only resulted in increased flooding on moderate to small watersheds. Continued increased in midcontinental rainfall are therefore likely to enhance the occurrence of floods in Midwestern watersheds across different geographic scales. • Sediment accumulation rates and clastic flux records reveal Common Era flood frequencies for the White River, IN. • Pacific North American mode-like (PNA-like) conditions were a primary driver of White River flooding. • Positive (negative) PNA-like atmospheric circulation decreased (increased) White River flooding. • White River flooding was anti-phased with the Ohio River. • Watershed-scale responses to precipitation seasonality account for anti-phased White and Ohio river flood relationships. [ABSTRACT FROM AUTHOR]

Warm season dry spells over the central and eastern United States are classified into three canonical types via a hierarchical cluster analysis for the period 1950-2005. Four CMIP5 models exhibit diverging skill in representing the observed behavior, ranging from southern Great Plains dry spells that are reasonably simulated by all four models to southeastern U.S. dry spells that are only accurately captured by one model. A model's skill in representing a particular dry spell cluster is positively correlated with the model's ability to simulate the large-scale meteorological patterns (LMPs) accompanying the dry spell. The interannual variability and overall observed decreasing trend in dry spell days are represented with varying degrees of accuracy by the four models. The results 1) highlight existing shortcomings in the climate model representation of regional dry spells and 2) illustrate the importance of properly simulating the observed spectrum of LMPs in minimizing these shortcomings. [ABSTRACT FROM AUTHOR]

This study documents and investigates biases in simulating summer surface air temperature (SAT) variability over the continental United States in the Atmospheric Model Intercomparison Project (AMIP) experiment from phase 5 of the Coupled Model Intercomparison Project (CMIP5). Empirical orthogonal function (EOF) and multivariate regression analyses are used to assess the relative importance of circulation and the land surface feedback at setting summer SAT over a 30-yr period (1979-2008). Regions of high SAT variability are closely associated with midtropospheric highs, subsidence, and radiative heating accompanying clear-sky conditions. The land surface exerts a spatially variable influence on SAT through the sensible heat flux and is a second-order effect in the high-variability centers of action (COAs) in observational estimates. The majority of the AMIP models feature high SAT variability over the central United States, displaced south and/or west of observed COAs. SAT COAs in models tend to be concomitant and strongly coupled with regions of high sensible heat flux variability, suggesting that excessive land-atmosphere interaction in these models modulates U.S. summer SAT. In the central United States, models with climatological warm biases also feature less evapotranspiration than ERA-Interim but reasonably reproduce observed SAT variability in the region. Models that overestimate SAT variability tend to reproduce ERA-Interim SAT and evapotranspiration climatology. In light of potential model biases, this analysis calls for careful evaluation of the land-atmosphere interaction hot spot region identified in the central United States. Additionally, tropical sea surface temperatures play a role in forcing the leading EOF mode for summer SAT in models. This relationship is not apparent in observations. [ABSTRACT FROM AUTHOR]

This study investigates the refined simulation skill that results when the regional Climate extension of the Weather Research and Forecasting (CWRF) model is nested in the ECMWF Hamburg version 4.5 (ECHAM) atmospheric general circulation model over the United States during 1980-2009, where observed sea surface temperatures are used in both models. Over the contiguous US, for each of the four seasons from winter to fall, CWRF reduces the root mean square error of the ECHAM seasonal mean surface air temperature simulation by 0.19, 0.82, 2.02 and 1.85 °C, and increases the equitable threat score of seasonal mean precipitation by 0.18, 0.11, 0.09 and 0.12. CWRF also simulates much more realistically daily precipitation frequency and heavy precipitation events, typically over the Central Great Plains, Cascade Mountains and Gulf Coast States. These CWRF skill enhancements are attributed to the increased spatial resolution and physics refinements in representing orographic, terrestrial hydrology, convection, and cloud-aerosol-radiation effects and their interactions. Empirical orthogonal function analysis of seasonal mean precipitation and surface air temperature interannual variability shows that, in general, CWRF substantially improves the spatial distribution of both quantities, while temporal evolution (i.e. interannual variability) of the first 3 primary patterns is highly correlated with that of the driving ECHAM (except for summer precipitation), and they both have low temporal correlations against observations. During winter, when large-scale forcing dominates, both models also have similar responses to strong ENSO signals where they successfully capture observed precipitation composite anomalies but substantially fail to reproduce surface air temperature anomalies. When driven by the ECMWF Reanalysis Interim, CWRF produces a very realistic interannual evolution of large-scale precipitation and surface air temperature patterns where the temporal correlations with observations are significant. These results indicate that CWRF can greatly improve mesoscale regional climate structures but it cannot change interannual variations of the large-scale patterns, which are determined by the driving lateral boundary conditions. [ABSTRACT FROM AUTHOR]

The objective of this work is to study in detail a strong North Pacific, large amplitude, and long-lived blocking event that occurred during January 23–February 16, 2014. Indeed, it was the 11th strongest Northern Hemisphere event lasting longer than 20 days since 1968. This event formed out of the strong ridge that was associated with the devastating drought in the Western United States during the winter season of 2013-2014. This blocking event had many outstanding dynamical characteristics, the chief of which was that it survived an abrupt change in the planetary-scale flow when the Pacific North American pattern index changed from positive to negative in early February. The block then reintensified and persisted into mid-February. Several diagnostic techniques are employed to investigate the change in the planetary-scale flow during early February 2014 that have been applied to blocking before but aren’t as well known in the blocking literature. [ABSTRACT FROM AUTHOR]

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

The frequency and severity of extreme events are tightly associated with the variance of precipitation. As climate warms, the acceleration in hydrological cycle is likely to enhance the variance of precipitation across the globe. However, due to the lack of an effective analysis method, the mechanisms responsible for the changes of precipitation variance are poorly understood, especially on regional scales. Our study fills this gap by formulating a variance partition algorithm, which explicitly quantifies the contributions of atmospheric thermodynamics (specific humidity) and dynamics (wind) to the changes in regional-scale precipitation variance. Taking Southeastern (SE) United States (US) summer precipitation as an example, the algorithm is applied to the simulations of current and future climate by phase 5 of Coupled Model Intercomparison Project (CMIP5) models. The analysis suggests that compared to observations, most CMIP5 models (~60 %) tend to underestimate the summer precipitation variance over the SE US during the 1950-1999, primarily due to the errors in the modeled dynamic processes (i.e. large-scale circulation). Among the 18 CMIP5 models analyzed in this study, six of them reasonably simulate SE US summer precipitation variance in the twentieth century and the underlying physical processes; these models are thus applied for mechanistic study of future changes in SE US summer precipitation variance. In the future, the six models collectively project an intensification of SE US summer precipitation variance, resulting from the combined effects of atmospheric thermodynamics and dynamics. Between them, the latter plays a more important role. Specifically, thermodynamics results in more frequent and intensified wet summers, but does not contribute to the projected increase in the frequency and intensity of dry summers. In contrast, atmospheric dynamics explains the projected enhancement in both wet and dry summers, indicating its importance in understanding future climate change over the SE US. The results suggest that the intensified SE US summer precipitation variance is not a purely thermodynamic response to greenhouse gases forcing, and cannot be explained without the contribution of atmospheric dynamics. Our analysis provides important insights to understand the mechanisms of SE US summer precipitation variance change. The algorithm formulated in this study can be easily applied to other regions and seasons to systematically explore the mechanisms responsible for the changes in precipitation extremes in a warming climate. [ABSTRACT FROM AUTHOR]

An ensemble of future climate projections performed with the regional climate model RegCM4 is used to assess changes in inter-annual variability of precipitation over Southern Mexico and Central America (SMECAM). Two different Global Climate Models (GCMs) from the coupled model intercomparison project phase 5 are used to provide boundary conditions for two different RegCM4 configurations. This results in four regional climate projections extending from 1970 to 2100 for the greenhouse gas representative concentration pathway RCP8.5. The precipitation variability over the SMECAM region and its dependence on the gradient between Atlantic and Pacific sea surface temperature (SST) anomalies are verified by reproducing SST anomaly patterns during wettest and driest years similar to those seen in observational datasets. RegCM4 does a comparably better job than the driving GCMs. This strong relationship between precipitation and SST anomalies does not appear to change substantially under future climate conditions. For the rainy season, June to September, we find a future change in inter-annual variability of precipitation towards a much greater occurrence of very dry seasons over the SMECAM region, with this change being more pronounced in the regional than in the global model projections. A greater warming of the Tropical Northeastern Pacific (TNP) compared to the Tropical North Atlantic (TNA), which causes stronger wind fluxes from the TNA to the TNP through the Caribbean Low Level Jet, is identified as the main process responsible for these drier conditions. [ABSTRACT FROM AUTHOR]

ABSTRACT A majority of area burned in the Eastern United States (EUS) results from a limited number of exceptionally large wildfires. Relationships between climatic conditions and the occurrence of very large-fires (VLF) in the EUS were examined using composite and climate-niche analyses that consider atmospheric factors across inter-annual, sub-seasonal and synoptic temporal scales. While most large-fires in the EUS coincided with below normal fuel moisture and elevated fire weather, VLF preferentially occurred during a long-term drought accompanied by more acute sub-seasonal drought realized through fuel moisture stress and elevated fire-weather conditions. These results were corroborated across the EUS, with varying influences of drought, fire danger and fire weather discriminating VLF from other large fires across different geographical regions. We also show that the probability of VLF conditioned by fire occurrence increases when long-term drought, depleted fuel moisture and elevated fire weather align. This framework illustrates the compounding role of different timescales in VLF occurrence and serves as a basis for improving VLF predictions with seasonal climate forecasts and climate change scenarios. [ABSTRACT FROM AUTHOR]

Idealized atmospheric general circulation model (AGCM) experiments by the U.S. Climate Variability and Predictability Program (CLIVAR) Drought Working Group were used in order to study the influence of natural modes of sea surface temperature (SST) variability in the Pacific on drought in the contiguous United States. The current study expands on previous results by examining the atmospheric response of three AGCMs to three different patterns of the idealized Pacific SST anomalies that operate on different time scales: low-frequency (decadal), high-frequency (interannual), and a pan-Pacific pattern that retains characteristics of interannual and decadal variability. While forcing patterns are generally similar in appearance, results indicate that differences in the relative amplitude of the equatorial and extratropical components of the SST forcing are sufficient to give rise to differing teleconnections, leading to regional differences in the amplitude and significance of the precipitation response. Results indicate that the differences in simulated drought response between AGCMs to different cool-phase (La Niña-like) SST patterns are determined by model sensitivity to changes in the relative amplitude of the equatorial and extratropical components of the SSTA forcing, the strength of the land-atmosphere coupling, and by the amplitude of internal atmospheric variability. Results indicate that the northwestern United States and Great Plains regions are particularly sensitive to the extratropical component of the SST forcing. Evidence is also found that when the cool-phase patterns of SST combine, as they have in recent years, constructive interference leads to an enhanced drought response over the Great Plains. [ABSTRACT FROM AUTHOR]

In 2011, exceptionally low atmospheric moisture content combined with moderately high temperatures to produce a record-high vapor pressure deficit (VPD) in the southwestern United States (SW). These conditions combined with record-low cold-season precipitation to cause widespread drought and extreme wildfires. Although interannual VPD variability is generally dominated by temperature, high VPD in 2011 was also driven by a lack of atmospheric moisture. The May-July 2011 dewpoint in the SW was 4.5 standard deviations below the long-term mean. Lack of atmospheric moisture was promoted by already very dry soils and amplified by a strong ocean-to-continent sea level pressure gradient and upper-level convergence that drove dry northerly winds and subsidence upwind of and over the SW. Subsidence drove divergence of rapid and dry surface winds over the SW, suppressing southerly moisture imports and removing moisture from already dry soils. Model projections developed for the fifth phase of the Coupled Model Intercomparison Project (CMIP5) suggest that by the 2050s warming trends will cause mean warm-season VPD to be comparable to the record-high VPD observed in 2011. CMIP5 projections also suggest increased interannual variability of VPD, independent of trends in background mean levels, as a result of increased variability of dewpoint, temperature, vapor pressure, and saturation vapor pressure. Increased variability in VPD translates to increased probability of 2011-type VPD anomalies, which would be superimposed on ever-greater background VPD levels. Although temperature will continue to be the primary driver of interannual VPD variability, 2011 served as an important reminder that atmospheric moisture content can also drive impactful VPD anomalies. [ABSTRACT FROM AUTHOR]

Change in water availability is of great concern in the coastal southwest United States ( CSW US). Reconstructing the history of water pre–1800 AD requires the use of proxy data. Lakes provide long-lived, high-resolution terrestrial archives of past hydrologic change, and their sediments contain a variety of proxies. This study presents geochemical and sedimentological data from Zaca Lake, CA (Santa Barbara County) used to reconstruct a 3000 year history of winter season moisture source ( δD wax ) and catchment run-off (125–2000 μm sand) at decadal resolution. Here we show that winter season moisture source and run-off are highly variable over the past 3000 years; superimposed are regime shifts between wetter or drier conditions that persist on average over multiple centuries. Moisture source and run-off do not consistently covary indicating multiple atmospheric circulation modes where wetter/drier conditions prevail. Grain-size analysis reveals two intervals of multi-century drought with less run-off that pre-date the “epic droughts” as identified by Cook et al. (2004). A well-defined wet period with more run-off is identified during the Little Ice Age. Notably, the grain size data show strong coherence with western North American percent drought area indices for the past 1000 years. As a result, our data extend the history of drought and pluvials back to 3000 calendar years BP in the CSW US. Comparison to tropical Pacific proxies confirms the long-term relationship between El Niño and enhanced run-off in the CSW US. Our results demonstrate the long-term importance of the tropical Pacific to the CSW US winter season hydroclimate. [ABSTRACT FROM AUTHOR]

A simple analytical model including both diurnal thermal forcing over sloping terrain (the 'Holton' mechanism) and diurnally varying boundary layer friction (the 'Blackadar' mechanism) is developed to account for the observed amplitude and phase of the low-level jet (LLJ) over the Great Plains and to understand better the role of each mechanism. The present model indicates that, for the pure Holton mechanism (time-independent friction coefficient), the maximum southerly wind speed occurs (depending on the assumed friction coefficient) between sunset and midnight local standard time, which is earlier than the observed after-midnight maximum. For the pure Blackadar mechanism (time-independent thermal forcing), the present model shows that generally occurs later (closer to sunrise) than observed and has a strong latitudinal dependence. For both mechanisms combined, the present model indicates that occurs near to the observed time, which lies between the time obtained in the pure Holton mechanism and the time obtained in the pure Blackadar mechanism; furthermore, is larger (and closer to that observed) than in each one considered individually. The amplitude and phase of the LLJ as a function of latitude can be obtained by the combined model by allowing for the observed latitude-dependent mean and diurnally varying thermal forcing. [ABSTRACT FROM AUTHOR]

During the summer, strong surface heating combines with the terrain and land-water contrasts of the northwest United States to create a complex array of diurnal circulations. Though observational and modeling studies have described some of these circulations, advances in high-resolution numerical modeling allow for a more comprehensive and three-dimensional examination. To simulate typical summer conditions over the Pacific Northwest, 3-hourly Global Forecast System (GFS) model output for July and August 2009-11 was used to initialize and provide boundary conditions for a high-resolution Weather Research and Forecasting (WRF) Model run. To ensure the realism of the simulation, it was compared to observations from a collection of days representing typical summer conditions. Generally, it was found that the simulated diurnal wind, relative humidity, and temperature were close to the observations. It is shown that regional diurnal circulations over the Pacific Northwest occur on a number of interacting scales, ranging from upslope/downslope winds on local terrain features to larger-scale circulations such as between the Pacific Ocean and the western Oregon and Washington interiors. Such multiscale diurnal circulations occur concurrently, with the interactions producing complex structures, several of which are described in this paper. Wind speeds in the Strait of Juan de Fuca and downstream of the major Cascade Mountain gaps reach maxima between 2100 and 2400 local daylight time (LDT), while most other areas have peak winds earlier in the day. Localized nocturnal low-level wind maxima are described, including one over the northern Willamette Valley and another over the high plateau of eastern Oregon. [ABSTRACT FROM AUTHOR]