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Alexander A. Jacques, John D. Horel, Erik T. Crosman, and Frank L. Vernon

Abstract

Large-magnitude pressure signatures associated with a wide range of atmospheric phenomena (e.g., mesoscale gravity waves, convective complexes, tropical disturbances, and synoptic storm systems) are examined using a unique set of surface pressure sensors deployed as part of the National Science Foundation EarthScope USArray Transportable Array. As part of the USArray project, approximately 400 seismic stations were deployed in a pseudogrid fashion across a portion of the United States for 1–2 yr, then retrieved and redeployed farther east. Surface pressure observations at a sampling frequency of 1 Hz were examined during the period 1 January 2010–28 February 2014 when the seismic array was transitioning from the central to eastern continental United States. Surface pressure time series at over 900 locations were bandpass filtered to examine pressure perturbations on three temporal scales: meso- (10 min–4 h), subsynoptic (4–30 h), and synoptic (30 h–5 days) scales.

Case studies of strong pressure perturbations are analyzed using web tools developed to visualize and track tens of thousands of such events with respect to archived radar imagery and surface wind observations. Seasonal assessments of the bandpass-filtered variance and frequency of large-magnitude events are conducted to identify prominent areas of activity. Large-magnitude mesoscale pressure perturbations occurred most frequently during spring in the southern Great Plains and shifted northward during summer. Synoptic-scale pressure perturbations are strongest during winter in the northern states with maxima located near the East Coast associated with frequent synoptic development along the coastal storm track.

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Alexander A. Jacques, John D. Horel, Erik T. Crosman, and Frank L. Vernon

Abstract

Mesoscale convective phenomena induce pressure perturbations that can alter the strength and magnitude of surface winds, precipitation, and other sensible weather, which, in some cases, can inflict injuries and damage to property. This work extends prior research to identify and characterize mesoscale pressure features using a unique resource of 1-Hz pressure observations available from the USArray Transportable Array (TA) seismic field campaign.

A two-dimensional variational technique is used to obtain 5-km surface pressure analysis grids every 5 min from 1 March to 31 August 2011 from the TA observations and gridded surface pressure from the Real-Time Mesoscale Analysis over a swath of the central United States. Bandpass-filtering and feature-tracking algorithms are employed to isolate, identify, and assess prominent mesoscale pressure perturbations and their properties. Two case studies, the first involving mesoscale convective systems and the second using a solitary gravity wave, are analyzed using additional surface observation and gridded data resources. Summary statistics for tracked features during the period reviewed indicate a majority of perturbations last less than 3 h, produce maximum perturbation magnitudes between 2 and 5 hPa, and move at speeds ranging from 15 to 35 m s−1. The results of this study combined with improvements nationwide in real-time access to pressure observations at subhourly reporting intervals highlight the potential for improved detection and nowcasting of high-impact mesoscale weather features.

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Taylor A. McCorkle, John D. Horel, Alexander A. Jacques, and Trevor Alcott

Abstract

The High-Resolution Rapid Refresh–Alaska (HRRR-AK) modeling system provides 3-km horizontal resolution and 0–36-h forecast guidance for weather conditions over Alaska. This study evaluated the experimental version of the HRRR-AK system available from December 2016 to June 2017, prior to its operational deployment by the National Centers for Environmental Prediction in July 2018. Surface pressure observations from 158 National Weather Service (NWS) stations assimilated during the model’s production cycle and pressure observations from 101 USArray Transportable Array (TA) stations that were not assimilated were used to evaluate 265 complete 0–36-h forecasts of the altimeter setting (surface pressure reduced to sea level). The TA network is the largest recent expansion of Alaskan weather observations and provides an independent evaluation of the model’s performance during this period. Throughout the study period, systematic differences in altimeter setting between the HRRR-AK 0-h forecasts were larger relative to the unassimilated TA observations than relative to the assimilated NWS observations. Upon removal of these initial biases from each of the subsequent 1–36-h altimeter setting forecasts, the model’s 36-h forecast root-mean-square errors at the NWS and TA locations were comparable. The model’s treatment of rapid warming and downslope winds that developed in the lee of the Alaska Range during 12–15 February is examined. The HRRR-AK 0-h forecasts were used to diagnose the synoptic and mesoscale conditions during this period. The model forecasts underestimated the abrupt increases in the temperature and intensity of the downslope winds with smaller errors as the downslope wind events evolved.

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Mark Govett, Jim Rosinski, Jacques Middlecoff, Tom Henderson, Jin Lee, Alexander MacDonald, Ning Wang, Paul Madden, Julie Schramm, and Antonio Duarte

Abstract

The design and performance of the Non-Hydrostatic Icosahedral Model (NIM) global weather prediction model is described. NIM is a dynamical core designed to run on central processing unit (CPU), graphics processing unit (GPU), and Many Integrated Core (MIC) processors. It demonstrates efficient parallel performance and scalability to tens of thousands of compute nodes and has been an effective way to make comparisons between traditional CPU and emerging fine-grain processors. The design of the NIM also serves as a useful guide in the fine-grain parallelization of the finite volume cubed (FV3) model recently chosen by the National Weather Service (NWS) to become its next operational global weather prediction model.

This paper describes the code structure and parallelization of NIM using standards-compliant open multiprocessing (OpenMP) and open accelerator (OpenACC) directives. NIM uses the directives to support a single, performance-portable code that runs on CPU, GPU, and MIC systems. Performance results are compared for five generations of computer chips including the recently released Intel Knights Landing and NVIDIA Pascal chips. Single and multinode performance and scalability is also shown, along with a cost–benefit comparison based on vendor list prices.

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Rainer Bleck, Jian-Wen Bao, Stanley G. Benjamin, John M. Brown, Michael Fiorino, Thomas B. Henderson, Jin-Luen Lee, Alexander E. MacDonald, Paul Madden, Jacques Middlecoff, James Rosinski, Tanya G. Smirnova, Shan Sun, and Ning Wang

Abstract

A hydrostatic global weather prediction model based on an icosahedral horizontal grid and a hybrid terrain-following/isentropic vertical coordinate is described. The model is an extension to three spatial dimensions of a previously developed, icosahedral, shallow-water model featuring user-selectable horizontal resolution and employing indirect addressing techniques. The vertical grid is adaptive to maximize the portion of the atmosphere mapped into the isentropic coordinate subdomain. The model, best described as a stacked shallow-water model, is being tested extensively on real-time medium-range forecasts to ready it for possible inclusion in operational multimodel ensembles for medium-range to seasonal prediction.

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John C. Lin, Logan Mitchell, Erik Crosman, Daniel L. Mendoza, Martin Buchert, Ryan Bares, Ben Fasoli, David R. Bowling, Diane Pataki, Douglas Catharine, Courtenay Strong, Kevin R. Gurney, Risa Patarasuk, Munkhbayar Baasandorj, Alexander Jacques, Sebastian Hoch, John Horel, and Jim Ehleringer

Abstract

Urban areas are responsible for a substantial proportion of anthropogenic carbon emissions around the world. As global populations increasingly reside in cities, the role of urban emissions in determining the future trajectory of carbon emissions is magnified. Consequently, a number of research efforts have been started in the United States and beyond, focusing on observing atmospheric carbon dioxide (CO2) and relating its variations to carbon emissions in cities. Because carbon emissions are intimately tied to socioeconomic activity through the combustion of fossil fuels, and many cities are actively adopting emission reduction plans, such urban carbon research efforts give rise to opportunities for stakeholder engagement and guidance on other environmental issues, such as air quality.

This paper describes a research effort centered in the Salt Lake City, Utah, metropolitan region, which is the locus for one of the longest-running urban CO2 networks in the world. The Salt Lake City area provides a rich environment for studying anthropogenic emissions and for understanding the relationship between emissions and socioeconomic activity when the CO2 observations are enhanced with a) air quality observations, b) novel mobile observations from platforms on light-rail public transit trains and a news helicopter, c) dense meteorological observations, and d) modeling efforts that include atmospheric simulations and high-resolution emission inventories.

Carbon dioxide and other atmospheric observations are presented, along with associated modeling work. Examples in which the work benefited from and contributed to the interests of multiple stakeholders (e.g., policymakers, air quality managers, municipal government, urban planners, industry, and the general public) are discussed.

Open access