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Tao WK, Wu D, Lang S, Chern JD, Peters-Lidard C, Fridlind A, Matsui T. High-resolution NU-WRF simulations of a deep convective-precipitation system during MC3E: Further improvements and comparisons between Goddard microphysics schemes and observations. JOURNAL OF GEOPHYSICAL RESEARCH. ATMOSPHERES : JGR 2016; 121:1278-1305. [PMID: 32802697 PMCID: PMC7427821 DOI: 10.1002/2015jd023986] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
The Goddard microphysics was recently improved by adding a fourth ice class (frozen drops/hail). This new 4ICE scheme was developed and tested in the Goddard Cumulus Ensemble (GCE) model for an intense continental squall line and a moderate, less organized continental case. Simulated peak radar reflectivity profiles were improved in intensity and shape for both cases, as were the overall reflectivity probability distributions versus observations. In this study, the new Goddard 4ICE scheme is implemented into the regional-scale NASA Unified-Weather Research and Forecasting (NU-WRF) model, modified and evaluated for the same intense squall line, which occurred during the Midlatitude Continental Convective Clouds Experiment (MC3E). NU-WRF simulated radar reflectivities, total rainfall, propagation, and convective system structures using the 4ICE scheme modified herein agree as well as or significantly better with observations than the original 4ICE and two previous 3ICE (graupel or hail) versions of the Goddard microphysics. With the modified 4ICE, the bin microphysics-based rain evaporation correction improves propagation and in conjunction with eliminating the unrealistic dry collection of ice/snow by hail can replicate the erect, narrow, and intense convective cores. Revisions to the ice supersaturation, ice number concentration formula, and snow size mapping, including a new snow breakup effect, allow the modified 4ICE to produce a stronger, better organized system, more snow, and mimic the strong aggregation signature in the radar distributions. NU-WRF original 4ICE simulated radar reflectivity distributions are consistent with and generally superior to those using the GCE due to the less restrictive domain and lateral boundaries.
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Affiliation(s)
- Wei-Kuo Tao
- Mesoscale Atmospheric Processes Laboratory, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
| | - Di Wu
- Mesoscale Atmospheric Processes Laboratory, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
- Science Systems and Applications, Inc., Lanham, Maryland, USA
| | - Stephen Lang
- Mesoscale Atmospheric Processes Laboratory, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
- Science Systems and Applications, Inc., Lanham, Maryland, USA
| | - Jiun-Dar Chern
- Mesoscale Atmospheric Processes Laboratory, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
- Goddard Earth Sciences Technology and Research Program, Morgan State University, Baltimore, Maryland, USA
| | - Christa Peters-Lidard
- Hydrological Sciences Laboratory, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
| | - Ann Fridlind
- NASA Goddard Institute for Space Studies, New York, New York, USA
| | - Toshihisa Matsui
- Mesoscale Atmospheric Processes Laboratory, NASA Goddard Space Flight Center, Greenbelt, Maryland, USA
- Earth System Science Interdisciplinary Center, University of Maryland, College Park, Maryland, USA
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van Lier-Walqui M, Fridlind AM, Ackerman AS, Collis S, Helmus J, MacGorman DR, North K, Kollias P, Posselt DJ. On polarimetric radar signatures of deep convection for model evaluation: columns of specific differential phase observed during MC3E. MONTHLY WEATHER REVIEW 2016; 144:737-758. [PMID: 29503466 PMCID: PMC5831334 DOI: 10.1175/mwr-d-15-0100.1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
The representation of deep convection in general circulation models is in part informed by cloud-resolving models (CRMs) that function at higher spatial and temporal resolution; however, recent studies have shown that CRMs often fail at capturing the details of deep convection updrafts. With the goal of providing constraint on CRM simulation of deep convection updrafts, ground-based remote-sensing observations are analyzed and statistically correlated for four deep convection events observed during the Midlatitude Continental Convective Clouds Experiment (MC3E). Since positive values of specific differential phase (KDP) observed above the melting level are associated with deep convection updraft cells, so-called "KDP columns" are analyzed using two scanning polarimetric radars in Oklahoma: the National Weather Service Vance WSR-88D (KVNX) and the Department of Energy C-band Scanning Atmospheric Radiation Measurement (ARM) Precipitation Radar (C-SAPR). KVNX and C-SAPR KDP volumes and columns are then statistically correlated with vertical winds retrieved via multi-Doppler wind analysis, lightning flash activity derived from the Oklahoma Lightning Mapping Array, and KVNX differential reflectivity (ZDR). Results indicate strong correlations of KDP volume above the melting level with updraft mass flux, lightning flash activity, and intense rainfall. Analysis of KDP columns reveals signatures of changing updraft properties from one storm event to another as well as during event evolution. Comparison of ZDR to KDP shows commonalities in information content of each, as well as potential problems with ZDR associated with observational artifacts.
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Affiliation(s)
- Marcus van Lier-Walqui
- Corresponding author address: Marcus van Lier-Walqui, CCSR, Columbia University, 2880 Broadway, New York, NY 10027.
| | | | | | - Scott Collis
- Environmental Sciences Division, Argonne National Laboratory, Argonne, Illinois
| | - Jonathan Helmus
- Environmental Sciences Division, Argonne National Laboratory, Argonne, Illinois
| | - Donald R. MacGorman
- NOAA/National Severe Storms Laboratory, and Cooperative Institute for Mesoscale Meteorological Studies, Norman, Oklahoma
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Prein AF, Langhans W, Fosser G, Ferrone A, Ban N, Goergen K, Keller M, Tölle M, Gutjahr O, Feser F, Brisson E, Kollet S, Schmidli J, van Lipzig NPM, Leung R. A review on regional convection-permitting climate modeling: Demonstrations, prospects, and challenges. REVIEWS OF GEOPHYSICS (WASHINGTON, D.C. : 1985) 2015; 53:323-361. [PMID: 27478878 PMCID: PMC4949718 DOI: 10.1002/2014rg000475] [Citation(s) in RCA: 58] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/15/2014] [Revised: 04/06/2015] [Accepted: 04/07/2015] [Indexed: 05/09/2023]
Abstract
Regional climate modeling using convection-permitting models (CPMs; horizontal grid spacing <4 km) emerges as a promising framework to provide more reliable climate information on regional to local scales compared to traditionally used large-scale models (LSMs; horizontal grid spacing >10 km). CPMs no longer rely on convection parameterization schemes, which had been identified as a major source of errors and uncertainties in LSMs. Moreover, CPMs allow for a more accurate representation of surface and orography fields. The drawback of CPMs is the high demand on computational resources. For this reason, first CPM climate simulations only appeared a decade ago. In this study, we aim to provide a common basis for CPM climate simulations by giving a holistic review of the topic. The most important components in CPMs such as physical parameterizations and dynamical formulations are discussed critically. An overview of weaknesses and an outlook on required future developments is provided. Most importantly, this review presents the consolidated outcome of studies that addressed the added value of CPM climate simulations compared to LSMs. Improvements are evident mostly for climate statistics related to deep convection, mountainous regions, or extreme events. The climate change signals of CPM simulations suggest an increase in flash floods, changes in hail storm characteristics, and reductions in the snowpack over mountains. In conclusion, CPMs are a very promising tool for future climate research. However, coordinated modeling programs are crucially needed to advance parameterizations of unresolved physics and to assess the full potential of CPMs.
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Affiliation(s)
- Andreas F Prein
- National Center for Atmospheric Research Boulder Colorado USA; Wegener Center for Global and Climate Change (WEGC) University of Graz Graz Austria
| | - Wolfgang Langhans
- Earth Sciences Division Lawrence Berkeley National Laboratory Berkeley California USA
| | | | - Andrew Ferrone
- Luxembourg Institute of Science and Technology, Environmental Research and Innovation Department Environmental Resource Center Belvaux Luxembourg
| | - Nikolina Ban
- Institute for Atmospheric and Climate Science ETH Zurich Zurich Switzerland
| | - Klaus Goergen
- Meteorological Institute University of Bonn Bonn Germany; Jülich Supercomputing Centre Research Centre Jülich Jülich Germany; Centre for High-Performance Scientific Computing in Terrestrial Systems ABC/J Geoverbund Jülich Germany
| | - Michael Keller
- Institute for Atmospheric and Climate Science ETH Zurich Zurich Switzerland; Center for Climate Systems Modeling ETH Zurich Zurich Switzerland
| | - Merja Tölle
- Institute of Geography Justus-Liebig Universität Gießen Giessen Germany
| | - Oliver Gutjahr
- Regional and Environmental Sciences, Department of Environmental Meteorology University of Trier Trier Germany
| | - Frauke Feser
- Institute for Coastal Research Helmholtz-Zentrum Geesthacht Centre for Materials and Coastal Research Geesthacht Germany
| | - Erwan Brisson
- Institut für Atmosphäre und Umwelt Goethe-Universitt Frankfurt am Main Frankfurt Germany
| | - Stefan Kollet
- Centre for High-Performance Scientific Computing in Terrestrial Systems ABC/J Geoverbund Jülich Germany; Agrosphere (IBG-3) Research Centre Jülich Jülich Germany
| | - Juerg Schmidli
- Institute for Atmospheric and Climate Science ETH Zurich Zurich Switzerland; Center for Climate Systems Modeling ETH Zurich Zurich Switzerland
| | | | - Ruby Leung
- Pacific Northwest National Laboratory Richland Washington USA
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