Recent numerical modeling and theoretical work deduce that potential vorticity (PV) can turn negative in the Northern Hemisphere as a result of localized convective heating embedded in vertical wind shear. It has been further postulated that negative potential vorticity (NPV) may be relevant for the large-scale circulation, as it has been observed to grow in scale into elongated mesoscale bands when in close proximity to the jet stream, accelerating jet stream winds and degrading numerical weather prediction skill. However, these findings are largely confined to case studies. Here, we use a climatological and composite perspective to evaluate the occurrence of elongated bands of NPV over the northwest Atlantic and its implications for jet stream dynamics. This research focuses on synoptic-scale bands (>1650 km) of NPV that are in close proximity (< 100 km) to the jet stream (termed NPV-jet interactions) using ERA5 data from January 2000 to December 2021. Climatological characteristics show that NPV-jet interactions occur most frequently over the coastal western Atlantic during boreal winter along 40 degrees N. This latitude band has also seen an 11 % increase (relative change) in NPV-jet interactions over the 22-year time period. Separating NPV-jet interactions into three distinct large-scale flow patterns using k-means clustering conceptually illustrates the evolution of NPV features from their initial formation along the westward flank of the ridge to the eastern flank of the ridge. The large-scale environment of NPV-jet interactions is characterized by a trough-ridge couplet adjacent to positive integrated vapor transport (IVT) anomalies, conducive to warm conveyor belts and mesoscale convective systems. Even when NPV is positioned in a more adiabatic environment (far away from regions of strong IVT anomalies), robust positive-PV gradient and wind speed anomalies exist along the jet stream. Inspecting three detailed case studies that serve as archetypes of the three clusters, we showed that the presence of NPV near the jet stream adiabatically enhances wave activity flux due to NPV mutually strengthening momentum transport and the ageostrophic flux of the geopotential. The results show that the close proximity of synoptic-scale NPV to the jet stream is conducive to the occurrence of wind speed maxima and could be dynamically relevant in enhancing downstream development despite NPV's theorized origin from submesoscales.

Atmospheric rivers (ARs) are long, narrow synoptic scale weather features important for Earth’s hydrological cycle typically transporting water vapor poleward, delivering precipitation important for local climates. Understanding ARs in a warming climate is problematic because the AR response to climate change is tied to how the feature is defined. The Atmospheric River Tracking Method Intercomparison Project (ARTMIP) provides insights into this problem by comparing 16 atmospheric river detection tools (ARDTs) to a common data set consisting of high resolution climate change simulations from a global atmospheric general circulation model. ARDTs mostly show increases in frequency and intensity, but the scale of the response is largely dependent on algorithmic criteria. Across ARDTs, bulk characteristics suggest intensity and spatial footprint are inversely correlated, and most focus regions experience increases in precipitation volume coming from extreme ARs. The spread of the AR precipitation response under climate change is large and dependent on ARDT selection.

Both atmospheric warming and poleward moisture transport increase the likelihood of sea ice surface melt. In the Southern Hemisphere, short-lived extratropical cyclones (ETCs) are responsible for a bulk of total heat and moisture transport toward high latitudes. Although these storms form ubiquitously in the midlatitudes, moisture availability and temperature characteristics vary by source region. In this study, we assess atmospheric, oceanic, and sea ice concentration (SIC) anomalies associated with austral winter ETCs over different Antarctic regions using ERA5 reanalysis data. Between 1990 and 2019, we find a total of 514 ETCs, with greater storm frequency in the eastern hemisphere groups. Compared to the climatology, sea ice melts (grows) behind the warm (cold) front of each system and is negatively correlated with atmospheric poleward moisture transport, temperature, meridional winds, and sea surface temperature for all ETCs. We find that Bellingshausen storms move moisture and warm air furthest poleward over their lifespan. However, East Weddell and East Antarctic ETCs are responsible for greater absolute poleward moisture transport than Bellingshausen and Ross systems. More intense ETCs correspond to greater SIC through Day 1, suggesting that SIC impacts ETC strength, regardless of ETC region. From cyclogenesis to cyclolysis, sea ice extent declines underneath composite ETCs, trends are generally not significant. Overall, while sea ice response produced by ETC-induced atmospheric and oceanic changes varies regionally, the long-term impacts of ETCs on regional sea ice are negligible over the study period. Antarctic air has become warmer and moister recently. Most of this warming and moistening is caused by short-lived, large-scale storms (i.e., extratropical cyclones (ETCs)). However, the ETC formation location impacts its ability to move warm, moist air toward Antarctica. Here, we investigate how 514 detected wintertime ETCs from different regions impact Antarctic atmosphere, ocean, and sea ice conditions using ERA5 reanalysis between 1990 and 2019. For all storm locations, the storm's east side moves warmer, moister air toward the Antarctic coast, while the west side moves colder, drier air toward the equator. We also find that Bellingshausen Sea ETCs produce greater atmospheric warming and moistening closer to the Antarctic shoreline (relative to average conditions). However, East Weddell and East Antarctic ETCs move more total moisture toward Antarctica. Even though ETCs warm and moisten the local air, stronger ETCs correspond to enhanced sea ice when they form. Despite this relationship, we find that the sea ice edge moves closer to the Antarctic shoreline between ETC formation and dissipation. Overall, ETC impacts on sea ice through air and oceanic changes vary around the Antarctic coastline. However, it does not seem like historical ETCs had long-term impacts on Antarctic sea ice. Bellingshausen extratropical cyclones (ETCs) induce greater atmospheric moisture transport and warming at high latitudes than other cyclone groupsSea ice concentration (SIC) change is best related to 2-m temperature anomalies for all cyclone locationsETC intensity corresponds to greater SIC between cyclogenesis and day 1

We present a machine learning model that post-processes high-resolution, deterministic forecasts to produce short to medium-range probabilistic forecasts for seven core weather variables.We developed and operationally implemented a multi-task neural network with a custom loss function, the Continuous Ranked Probability Score (CRPS), using input data from the High Resolution Rapid Refresh (HRRR) model.This combined high-resolution Numerical Weather Prediction (NWP) modeling with machine learning to generate more accurate deterministic and probabilistic forecasts.The results show deterministic forecast improvements in Root Mean Squared Error (RMSE) from 3% to 25% and probabilistic improvements in CRPS from 31% to 45% over the HRRR model.The multi-task neural network is cheap to train and fast to run operationally on hourly forecasts.SIGNIFICANCE STATEMENT: Weather forecasting is a challenging problem.Operational forecasts use numerical weather prediction (NWP) models that solve physical equations.These weather forecasts are statistically post-processed to correct errors.Traditionally, uncertainties in the forecasts are captured by creating an ensemble of deterministic predictions with variations in the initial conditions and the NWP model.In this study, we developed a post-processing system to correct weather forecasting errors relative to observations and to produce probabilistic ensembles.Our system uses machine learning to generate more accurate deterministic and probabilistic weather forecasts.The post-processing system is cheap, fast, and deployed operationally.

Synoptic-scale filaments of negative potential vorticity (PV) in the northern hemisphere tropopause can form adjacent to the jet stream in the presence of convection and moderate shear (i.e., severe thunderstorm environments). Case-studies have shown that synoptic-scale negative PV can influence in-situ jet stream dynamics. Negative PV arises due to strong vorticity in convective updrafts, driven by the horizontal gradient of diabatic heating (O < 10 km). Its origin from scales not resolvable by contemporary global weather models can thus also impinge on jet stream forecast skill.Nevertheless, little is still known about the characteristics of synoptic-scale negative PV. How frequently is it observed? And what are its ‘typical’ impacts on the jet stream?Focusing on North America where severe thunderstorms are frequent, we design an algorithm that tracks the temporal evolution of closed contours of upper-level, negative PV air using ERA5 data. We composites instances in which it is in close-proximity to (‘interacts with’) the jet stream and assess its dynamical response. The role of negative PV on jet evolution and its downstream response over the Atlantic is facilitated through a combination of lagged composite analysis and K-means clustering.Our composite results in combination with preliminary high-resolution model simulations highlight that elongated bands of negative PV frequently interact with the jet stream, intensify jet wind maxima and may serve as an amplification source for Rossby waves.

Data and analysis pipelines from the paper "Meteorological Drivers of Resource Adequacy Failures in Current and High Renewable Western U.S. Power Systems"

Power system resource adequacy (RA), or its ability to continually balance energy supply and demand, underpins human and economic health. How meteorology affects RA and RA failures, particularly with increasing penetrations of renewables, is poorly understood. We characterize large-scale circulation patterns that drive RA failures in the Western U.S. at increasing wind and solar penetrations by integrating power system and synoptic meteorology methods. At up to 60% renewable penetration and across analyzed weather years, three high pressure patterns drive nearly all RA failures. The highest pressure anomaly is the dominant driver, accounting for 20-100% of risk hours and 43-100% of cumulative risk at 60% renewable penetration. The three high pressure patterns exhibit positive surface temperature anomalies, mixed surface solar radiation anomalies, and negative wind speed anomalies across our region, which collectively increase demand and decrease supply. Our characterized meteorological drivers align with meteorology during the California 2020 rolling blackouts, indicating continued vulnerability of power systems to these impactful weather patterns as renewables grow.

North American Mesoscale Convective Systems (MCSs) have been linked to instances of poorly forecasted Rossby wave packets (RWPs). A computationally inexpensive investigation is proposed to demonstrate a dynamical mechanism by which MCSs modify a RWP associated with a high‐impact weather event. Global ensemble forecast data, reanalysis and high‐resolution observations are used to assess the remote role of negative potential vorticity (PV) arising from divergent outflow on RWP propagation coinciding with the 11–21 June 2017 European heatwave. In this case, synoptic‐scale bands of negative PV which advect toward the jet stream arise from regions of active MCSs. The forecast data results show that the numerical misrepresentation of the anticyclonic circulation associated with negative PV can impinge on the forecast of a RWP. In each of the four forecasting models assessed, ensemble members that advected lower values of PV toward the equatorward branch of a North American ridge favored enhanced poleward amplification of the ridge and a more eastward progression of the RWP. The more eastward displacement of the RWP also coincided with an enhanced wave activity flux downstream. Although, we do not find a significant impact on the forecasted heatwave. The results urge further investigation into the role of negative PV in remotely influencing high‐impact weather.

Atmospheric rivers, or long but narrow regions of enhanced water vapor transport, are an important component of the hydrologic cycle as they are responsible for much of the poleward transport of water vapor and result in precipitation, sometimes extreme in intensity. Despite their importance, much uncertainty remains in the detection of atmospheric rivers in large datasets such as reanalyses and century scale climate simulations. To understand this uncertainty, the Atmospheric River Tracking Method Intercomparison Project (ARTMIP) developed tiered experiments, including the Tier 2 Reanalysis Intercomparison that is presented here. Eleven detection algorithms submitted hourly tags‐‐binary fields indicating the presence or absence of atmospheric rivers‐‐of detected atmospheric rivers in the Modern Era Retrospective Analysis for Research and Applications, version 2 (MERRA‐2) and European Centre for Medium‐Range Weather Forecasts' Reanalysis Version 5 (ERA5) as well as six‐hourly tags in the Japanese 55‐year Reanalysis (JRA‐55). Due to a higher climatological mean for integrated water vapor transport in MERRA‐2, atmospheric rivers were detected more frequently relative to the other two reanalyses, particularly in algorithms that use a fixed threshold for water vapor transport. The finer horizontal resolution of ERA5 resulted in narrower atmospheric rivers and an ability to detect atmospheric rivers along resolved coastlines. The fraction of hemispheric area covered by ARs varies throughout the year in all three reanalyses, with different atmospheric river detection tools having different seasonal cycles.

The Atmospheric River (AR) Tracking Method Intercomparison Project (ARTMIP) is a community effort to systematically assess how the uncertainties from AR detectors (ARDTs) impact our scientific understanding of ARs. This study describes the ARTMIP Tier 2 experimental design and initial results using the Coupled Model Intercomparison Project (CMIP) Phases 5 and 6 multi‐model ensembles. We show that AR statistics from a given ARDT in CMIP5/6 historical simulations compare remarkably well with the MERRA‐2 reanalysis. In CMIP5/6 future simulations, most ARDTs project a global increase in AR frequency, counts, and sizes, especially along the western coastlines of the Pacific and Atlantic oceans. We find that the choice of ARDT is the dominant contributor to the uncertainty in projected AR frequency when compared with model choice. These results imply that new projects investigating future changes in ARs should explicitly consider ARDT uncertainty as a core part of the experimental design.

Paleoclimate proxies indicate that changes in insolation since the mid-Holocene have driven widespread hydrologic changes across the midlatitudes. It is unclear how atmospheric rivers (ARs), which are fundamental to global moisture transport today, may have contributed to these Holocene hydroclimate changes. Here, we use a set of climate model simulations with the Community Earth System Model (CESM), and introduce an AR algorithm optimized to identify ARs within different climate states, to show that changes to the location and intensity of landfalling ARs explain the majority of the precipitation difference between the mid-Holocene and the preindustrial period in several midlatitude regions. During the mid-Holocene, enhanced seasonality increased summer season AR vapor content and displaced ARs poleward of their preindustrial period trajectories, especially in the Northern Hemisphere. Consequently, in high midlatitude coastal areas of western North America and East Asia, ARs account for greater than 10% more of total precipitation during the mid-Holocene, and nearly 100% of the simulated change in precipitation between the two climates. The simulated AR changes are consistent with moisture-sensitive proxy records and with present-day relationships between ARs and regional circulation, enhancing confidence that ARs served as the underlying synoptic mechanism responsible for mid-Holocene hydroclimate anomalies in several coastal mid-latitude areas. The results indicate that ARs are sensitive to background climate state, and suggest that changes in ARs may have contributed to hydroclimate changes throughout Earth's past. (C) 2020 The Author(s). Published by Elsevier B.V.

Atmospheric rivers (ARs) are characterized by intense moisture transport, which, on landfall, produce precipitation which can be both beneficial and destructive. ARs in California, for example, are known to have ended drought conditions but also to have caused substantial socio-economic damage from landslides and flooding linked to extreme precipitation. Understanding how AR characteristics will respond to a warming climate is, therefore, vital to the resilience of communities affected by them, such as the western USA, Europe, East Asia and South Africa. In this Review, we use a theoretical framework to synthesize understanding of the dynamic and thermodynamic responses of ARs to anthropogenic warming and connect them to observed and projected changes and impacts revealed by observations and complex models. Evidence suggests that increased atmospheric moisture (governed by Clausius–Clapeyron scaling) will enhance the intensity of AR-related precipitation — and related hydrological extremes — but with changes that are ultimately linked to topographic barriers. However, due to their dependency on both weather and climate-scale processes, which themselves are often poorly constrained, projections are uncertain. To build confidence and improve resilience, future work must focus efforts on characterizing the multiscale development of ARs and in obtaining observations from understudied regions, including the West Pacific, South Pacific and South Atlantic.

The 3rd ARTMIP Workshop What: Over 30 participants from multiple universities and research insititutions met to discuss new results from the Atmospheric River Tracking Method Intercomparison Project. Where: Lawrence Berkeley National Lab, Berkeley, CA, USA When: 16-18 October 2019

© 2020 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).Corresponding author: Anna M. Wilson, amw061@ucsd.edu