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Zhang Y, Sieron SB, Lu Y, Chen X, Nystrom RG, Minamide M, Chan M, Hartman CM, Yao Z, Ruppert JH, Okazaki A, Greybush SJ, Clothiaux EE, Zhang F. Ensemble-Based Assimilation of Satellite All-Sky Microwave Radiances Improves Intensity and Rainfall Predictions for Hurricane Harvey (2017). Geophys Res Lett 2021; 48:e2021GL096410. [PMID: 35865360 PMCID: PMC9286819 DOI: 10.1029/2021gl096410] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Revised: 11/18/2021] [Accepted: 12/02/2021] [Indexed: 06/15/2023]
Abstract
Ensemble-based data assimilation of radar observations across inner-core regions of tropical cyclones (TCs) in tandem with satellite all-sky infrared (IR) radiances across the TC domain improves TC track and intensity forecasts. This study further investigates potential enhancements in TC track, intensity, and rainfall forecasts via assimilation of all-sky microwave (MW) radiances using Hurricane Harvey (2017) as an example. Assimilating Global Precipitation Measurement constellation all-sky MW radiances in addition to GOES-16 all-sky IR radiances reduces the forecast errors in the TC track, rapid intensification (RI), and peak intensity compared to assimilating all-sky IR radiances alone, including a 24-hr increase in forecast lead-time for RI. Assimilating all-sky MW radiances also improves Harvey's hydrometeor fields, which leads to improved forecasts of rainfall after Harvey's landfall. This study indicates that avenues exist for producing more accurate forecasts for TCs using available yet underutilized data, leading to better warnings of and preparedness for TC-associated hazards in the future.
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Affiliation(s)
- Yunji Zhang
- Department of Meteorology and Atmospheric ScienceCenter for Advanced Data Assimilation and Predictability TechniquesThe Pennsylvania State UniversityUniversity ParkPAUSA
| | | | | | - Xingchao Chen
- Department of Meteorology and Atmospheric ScienceCenter for Advanced Data Assimilation and Predictability TechniquesThe Pennsylvania State UniversityUniversity ParkPAUSA
| | | | - Masashi Minamide
- Department of Civil EngineeringThe University of TokyoTokyoJapan
| | - Man‐Yau Chan
- Department of Meteorology and Atmospheric ScienceCenter for Advanced Data Assimilation and Predictability TechniquesThe Pennsylvania State UniversityUniversity ParkPAUSA
| | - Christopher M. Hartman
- Department of Meteorology and Atmospheric ScienceCenter for Advanced Data Assimilation and Predictability TechniquesThe Pennsylvania State UniversityUniversity ParkPAUSA
| | - Zhu Yao
- Department of Meteorology and Atmospheric ScienceCenter for Advanced Data Assimilation and Predictability TechniquesThe Pennsylvania State UniversityUniversity ParkPAUSA
| | | | - Atsushi Okazaki
- Department of Global Environment and Disaster Prevention SciencesHirosaki UniversityHirosakiJapan
| | - Steven J. Greybush
- Department of Meteorology and Atmospheric ScienceCenter for Advanced Data Assimilation and Predictability TechniquesThe Pennsylvania State UniversityUniversity ParkPAUSA
| | - Eugene E. Clothiaux
- Department of Meteorology and Atmospheric ScienceCenter for Advanced Data Assimilation and Predictability TechniquesThe Pennsylvania State UniversityUniversity ParkPAUSA
| | - Fuqing Zhang
- Department of Meteorology and Atmospheric ScienceCenter for Advanced Data Assimilation and Predictability TechniquesThe Pennsylvania State UniversityUniversity ParkPAUSA
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Wing AA, Stauffer CL, Becker T, Reed KA, Ahn M, Arnold NP, Bony S, Branson M, Bryan GH, Chaboureau J, De Roode SR, Gayatri K, Hohenegger C, Hu I, Jansson F, Jones TR, Khairoutdinov M, Kim D, Martin ZK, Matsugishi S, Medeiros B, Miura H, Moon Y, Müller SK, Ohno T, Popp M, Prabhakaran T, Randall D, Rios‐Berrios R, Rochetin N, Roehrig R, Romps DM, Ruppert JH, Satoh M, Silvers LG, Singh MS, Stevens B, Tomassini L, van Heerwaarden CC, Wang S, Zhao M. Clouds and Convective Self-Aggregation in a Multimodel Ensemble of Radiative-Convective Equilibrium Simulations. J Adv Model Earth Syst 2020; 12:e2020MS002138. [PMID: 33042391 PMCID: PMC7539986 DOI: 10.1029/2020ms002138] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/10/2020] [Revised: 07/08/2020] [Accepted: 07/09/2020] [Indexed: 06/11/2023]
Abstract
The Radiative-Convective Equilibrium Model Intercomparison Project (RCEMIP) is an intercomparison of multiple types of numerical models configured in radiative-convective equilibrium (RCE). RCE is an idealization of the tropical atmosphere that has long been used to study basic questions in climate science. Here, we employ RCE to investigate the role that clouds and convective activity play in determining cloud feedbacks, climate sensitivity, the state of convective aggregation, and the equilibrium climate. RCEMIP is unique among intercomparisons in its inclusion of a wide range of model types, including atmospheric general circulation models (GCMs), single column models (SCMs), cloud-resolving models (CRMs), large eddy simulations (LES), and global cloud-resolving models (GCRMs). The first results are presented from the RCEMIP ensemble of more than 30 models. While there are large differences across the RCEMIP ensemble in the representation of mean profiles of temperature, humidity, and cloudiness, in a majority of models anvil clouds rise, warm, and decrease in area coverage in response to an increase in sea surface temperature (SST). Nearly all models exhibit self-aggregation in large domains and agree that self-aggregation acts to dry and warm the troposphere, reduce high cloudiness, and increase cooling to space. The degree of self-aggregation exhibits no clear tendency with warming. There is a wide range of climate sensitivities, but models with parameterized convection tend to have lower climate sensitivities than models with explicit convection. In models with parameterized convection, aggregated simulations have lower climate sensitivities than unaggregated simulations.
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Affiliation(s)
- Allison A. Wing
- Department of Earth, Ocean and Atmospheric ScienceFlorida State UniversityTallahasseeFLUSA
| | - Catherine L. Stauffer
- Department of Earth, Ocean and Atmospheric ScienceFlorida State UniversityTallahasseeFLUSA
| | | | - Kevin A. Reed
- School of Marine and Atmospheric SciencesStony Brook UniversityStony BrookNYUSA
| | - Min‐Seop Ahn
- Department of Atmospheric SciencesUniversity of WashingtonSeattleWAUSA
| | - Nathan P. Arnold
- Global Modeling and Assimilation OfficeNASA Goddard Space Flight CenterGreenbeltMDUSA
| | - Sandrine Bony
- Laboratoire de Météorologie Dynamique (LMD)/IPSL/Sorbonne Université/CNRSParisFrance
| | - Mark Branson
- Department of Atmospheric ScienceColorado State UniversityFort CollinsCOUSA
| | | | | | - Stephan R. De Roode
- Faculty of Civil Engineering and Geosciences, Department of Geoscience and Remote SensingDelft University of TechnologyDelftNetherlands
| | | | | | - I‐Kuan Hu
- Rosenstiel School of Marine and Atmospheric ScienceUniversity of MiamiMiamiFLUSA
| | - Fredrik Jansson
- Faculty of Civil Engineering and Geosciences, Department of Geoscience and Remote SensingDelft University of TechnologyDelftNetherlands
- Centrum Wiskunde and InformaticaAmsterdamNetherlands
| | - Todd R. Jones
- Department of MeteorologyUniversity of ReadingReadingUK
| | - Marat Khairoutdinov
- School of Marine and Atmospheric Sciences, and Institute for Advanced Computational Science, Stony Brook UniversityState University of New YorkStony BrookNYUSA
| | - Daehyun Kim
- Department of Atmospheric SciencesUniversity of WashingtonSeattleWAUSA
| | - Zane K. Martin
- Department of Applied Physics and Applied MathematicsColumbia UniversityNew YorkNYUSA
| | - Shuhei Matsugishi
- Atmosphere and Ocean Research InstituteThe University of TokyoKashiwaJapan
| | | | - Hiroaki Miura
- Department of Earth and Planetary Science, Graduate School of ScienceThe University of TokyoTokyoJapan
| | - Yumin Moon
- Department of Atmospheric SciencesUniversity of WashingtonSeattleWAUSA
| | | | - Tomoki Ohno
- Japan Agency for Marine‐Earth Science and TechnologyYokohamaJapan
| | - Max Popp
- Laboratoire de Météorologie Dynamique (LMD)/IPSL/Sorbonne Université/CNRS/École Polytechnique/École Normale SupérieureParisFrance
| | | | - David Randall
- Department of Atmospheric ScienceColorado State UniversityFort CollinsCOUSA
| | | | - Nicolas Rochetin
- Max Planck Institute for MeteorologyHamburgGermany
- Laboratoire de Météorologie Dynamique (LMD)/IPSL/Sorbonne Université/CNRS/École Polytechnique/École Normale SupérieureParisFrance
| | - Romain Roehrig
- CNRM, Université de Toulouse, Météo‐France, CNRSToulouseFrance
| | - David M. Romps
- Department of Earth and Planetary ScienceUniversity of CaliforniaBerkeleyCAUSA
- Climate and Ecosystem Sciences DivisionLawrence Berkeley National LaboratoryBerkeleyCAUSA
| | - James H. Ruppert
- Department of Meteorology and Atmospheric Science and Center for Advanced Data Assimilation and Predictability TechniquesPennsylvania State UniversityUniversity ParkPAUSA
| | - Masaki Satoh
- Atmosphere and Ocean Research InstituteThe University of TokyoKashiwaJapan
| | - Levi G. Silvers
- School of Marine and Atmospheric SciencesStony Brook UniversityStony BrookNYUSA
| | - Martin S. Singh
- School of Earth, Atmosphere, and EnvironmentMonash UniversityClaytonVictoriaAustralia
| | | | | | | | - Shuguang Wang
- Department of Applied Physics and Applied MathematicsColumbia UniversityNew YorkNYUSA
| | - Ming Zhao
- NOAA/Geophysical Fluid Dynamics LaboratoryPrincetonNJUSA
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Bony S, Stevens B, Ament F, Bigorre S, Chazette P, Crewell S, Delanoë J, Emanuel K, Farrell D, Flamant C, Gross S, Hirsch L, Karstensen J, Mayer B, Nuijens L, Ruppert JH, Sandu I, Siebesma P, Speich S, Szczap F, Totems J, Vogel R, Wendisch M, Wirth M. EUREC 4A: A Field Campaign to Elucidate the Couplings Between Clouds, Convection and Circulation. Surv Geophys 2017; 38:1529-1568. [PMID: 31997845 PMCID: PMC6956937 DOI: 10.1007/s10712-017-9428-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/14/2017] [Accepted: 09/14/2017] [Indexed: 05/30/2023]
Abstract
Trade-wind cumuli constitute the cloud type with the highest frequency of occurrence on Earth, and it has been shown that their sensitivity to changing environmental conditions will critically influence the magnitude and pace of future global warming. Research over the last decade has pointed out the importance of the interplay between clouds, convection and circulation in controling this sensitivity. Numerical models represent this interplay in diverse ways, which translates into different responses of trade-cumuli to climate perturbations. Climate models predict that the area covered by shallow cumuli at cloud base is very sensitive to changes in environmental conditions, while process models suggest the opposite. To understand and resolve this contradiction, we propose to organize a field campaign aimed at quantifying the physical properties of trade-cumuli (e.g., cloud fraction and water content) as a function of the large-scale environment. Beyond a better understanding of clouds-circulation coupling processes, the campaign will provide a reference data set that may be used as a benchmark for advancing the modelling and the satellite remote sensing of clouds and circulation. It will also be an opportunity for complementary investigations such as evaluating model convective parameterizations or studying the role of ocean mesoscale eddies in air-sea interactions and convective organization.
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Affiliation(s)
- Sandrine Bony
- LMD/IPSL, CNRS, Sorbonne Université, UPMC, 4 Place Jussieu, 75252 Paris, France
| | - Bjorn Stevens
- Max Planck Institute for Meteorology, Bundesstr. 53, 20146 Hamburg, Germany
| | - Felix Ament
- University of Hamburg, Bundesstrasse 55, 20146 Hamburg, Germany
| | - Sebastien Bigorre
- Woods Hole Oceanographic Institution, 266 Woods Hole Rd, Woods Hole, MA 02543 USA
| | - Patrick Chazette
- LSCE/IPSL, CNRS-CEA-UVSQ, CEA Saclay, 91191 Gif sur Yvette, France
| | - Susanne Crewell
- University of Cologne, Albertus-Magnus-Platz, 50923 Cologne, Germany
| | - Julien Delanoë
- LATMOS/IPSL, CNRS-UPMC-UVSQ, 11 Boulevard D’Alembert, 78280 Guyancourt, France
| | - Kerry Emanuel
- Massachusetts Institute of Technology, 77 Massachussetts Avenue, Cambridge, MA 02139 USA
| | - David Farrell
- Caribbean Institute for Meteorology and Hydrology, P.O. Box 130, Bridgetown, Barbados
| | - Cyrille Flamant
- LATMOS/IPSL, CNRS-UPMC-UVSQ, 11 Boulevard D’Alembert, 78280 Guyancourt, France
| | - Silke Gross
- German Aerospace Center, Múnchener Str. 20, 82234 Oberpfaffenhofen-Wessling, Germany
| | - Lutz Hirsch
- Max Planck Institute for Meteorology, Bundesstr. 53, 20146 Hamburg, Germany
| | - Johannes Karstensen
- GEOMAR Helmholtz Centre for Ocean Research, Duesternbrooker Weg 20, 24105 Kiel, Germany
| | - Bernhard Mayer
- Ludwig-Maximilians University of Munich, Theresienstrasse 37, 80333 Munich, Germany
| | - Louise Nuijens
- Delft University of Technology, P.O. Box 5048, 2600 GA Delft, The Netherlands
| | - James H. Ruppert
- Max Planck Institute for Meteorology, Bundesstr. 53, 20146 Hamburg, Germany
| | | | - Pier Siebesma
- Delft University of Technology and Royal Netherlands Meteorological Institute, De Bilt, Netherlands
| | - Sabrina Speich
- LMD/IPSL, Ecole Normale Supérieure, 24 rue Lhomond, 75231 Paris, France
| | - Frédéric Szczap
- Laboratoire de Météorologie Physique, UMR6016, CNRS, Aubière, France
| | - Julien Totems
- LSCE/IPSL, CNRS-CEA-UVSQ, CEA Saclay, 91191 Gif sur Yvette, France
| | - Raphaela Vogel
- Max Planck Institute for Meteorology, Bundesstr. 53, 20146 Hamburg, Germany
| | | | - Martin Wirth
- German Aerospace Center, Múnchener Str. 20, 82234 Oberpfaffenhofen-Wessling, Germany
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