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TRMM Latent Heating Retrieval: Applications and Comparisons with Field Campaigns and Large-Scale Analyses

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  • 1 Mesoscale Atmospheric Processes Laboratory, NASA Goddard Space Flight Center, Greenbelt, Maryland
  • 2 Atmosphere and Ocean Research Institute, The University of Tokyo, Kashiwa, Chiba, Japan
  • 3 Science Systems and Applications Inc., Lanham, Maryland
  • 4 Division of Earth and Planetary Sciences, Kyoto University, Kyoto, Japan
  • 5 UMBC Joint Center for Earth Systems Technology, University of Maryland at Baltimore, Baltimore, Maryland
  • 6 Jet Propulsion Laboratory, California Institute of Technology, Pasadena, California
  • 7 Joint Institute for Regional Earth System Science and Engineering, University of California, California
  • 8 Rosenstiel School of Marine and Atmospheric Science, University of Miami, Miami, Florida
  • 9 Earth System Science Interdisciplinary Center, Joint Global Change Research Institute, University of Maryland, College Park, College Park, Maryland
  • 10 Department of Meteorology, Florida State University, Tallahassee, Florida
  • 11 Goddard Earth Sciences Technology and Research, Morgan State University, Baltimore, Maryland
  • 12 Department of Atmospheric Science, Colorado State University, Fort Collins, Colorado
  • 13 Department of Atmospheric Science, University of Washington, Seattle, Washington
  • 14 NASA Headquarters, Science Mission Directorate, Washington, D.C.
  • 15 Hydrospheric Atmospheric Research Center, Nagoya University, Nagoya, Japan
  • 16 Earth Observation Research Center, Japan Aerospace Exploration Agency, Tsukuba, Japan
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Abstract

Yanai and coauthors utilized the meteorological data collected from a sounding network to present a pioneering work in 1973 on thermodynamic budgets, which are referred to as the apparent heat source (Q1) and apparent moisture sink (Q2). Latent heating (LH) is one of the most dominant terms in Q1. Yanai’s paper motivated the development of satellite-based LH algorithms and provided a theoretical background for imposing large-scale advective forcing into cloud-resolving models (CRMs). These CRM-simulated LH and Q1 data have been used to generate the look-up tables in Tropical Rainfall Measuring Mission (TRMM) LH algorithms. A set of algorithms developed for retrieving LH profiles from TRMM-based rainfall profiles is described and evaluated, including details concerning their intrinsic space–time resolutions. Included in the paper are results from a variety of validation analyses that define the uncertainty of the LH profile estimates. Also, examples of how TRMM-retrieved LH profiles have been used to understand the life cycle of the MJO and improve the predictions of global weather and climate models as well as comparisons with large-scale analyses are provided. Areas for further improvement of the TRMM products are discussed.

Corresponding author address: Dr. Wei-Kuo Tao, NASA/Goddard Space Flight Center, Mesoscale Atmospheric Processes Laboratory (Code 612), Greenbelt, MD 20771. E-mail: wei-kuo.tao-1@nasa.gov

Abstract

Yanai and coauthors utilized the meteorological data collected from a sounding network to present a pioneering work in 1973 on thermodynamic budgets, which are referred to as the apparent heat source (Q1) and apparent moisture sink (Q2). Latent heating (LH) is one of the most dominant terms in Q1. Yanai’s paper motivated the development of satellite-based LH algorithms and provided a theoretical background for imposing large-scale advective forcing into cloud-resolving models (CRMs). These CRM-simulated LH and Q1 data have been used to generate the look-up tables in Tropical Rainfall Measuring Mission (TRMM) LH algorithms. A set of algorithms developed for retrieving LH profiles from TRMM-based rainfall profiles is described and evaluated, including details concerning their intrinsic space–time resolutions. Included in the paper are results from a variety of validation analyses that define the uncertainty of the LH profile estimates. Also, examples of how TRMM-retrieved LH profiles have been used to understand the life cycle of the MJO and improve the predictions of global weather and climate models as well as comparisons with large-scale analyses are provided. Areas for further improvement of the TRMM products are discussed.

Corresponding author address: Dr. Wei-Kuo Tao, NASA/Goddard Space Flight Center, Mesoscale Atmospheric Processes Laboratory (Code 612), Greenbelt, MD 20771. E-mail: wei-kuo.tao-1@nasa.gov
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