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  • Author or Editor: G. Skofronick-Jackson x
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S. A. Ackerman, S. Platnick, P. K. Bhartia, B. Duncan, T. L’Ecuyer, A. Heidinger, G. Skofronick-Jackson, N. Loeb, T. Schmit, and N. Smith

Abstract

Satellite meteorology is a relatively new branch of the atmospheric sciences. The field emerged in the late 1950s during the Cold War and built on the advances in rocketry after World War II. In less than 70 years, satellite observations have transformed the way scientists observe and study Earth. This paper discusses some of the key advances in our understanding of the energy and water cycles, weather forecasting, and atmospheric composition enabled by satellite observations. While progress truly has been an international achievement, in accord with a monograph observing the centennial of the American Meteorological Society, as well as limited space, the emphasis of this chapter is on the U.S. satellite effort.

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J. J. Shi, W-K. Tao, T. Matsui, R. Cifelli, A. Hou, S. Lang, A. Tokay, N-Y. Wang, C. Peters-Lidard, G. Skofronick-Jackson, S. Rutledge, and W. Petersen

Abstract

One of the grand challenges of the Global Precipitation Measurement (GPM) mission is to improve cold-season precipitation measurements in mid- and high latitudes through the use of high-frequency passive microwave radiometry. For this purpose, the Weather Research and Forecasting model (WRF) with the Goddard microphysics scheme is coupled with a Satellite Data Simulation Unit (WRF–SDSU) to facilitate snowfall retrieval algorithms over land by providing a virtual cloud library and corresponding microwave brightness temperature measurements consistent with the GPM Microwave Imager (GMI). When this study was initiated, there were no prior published results using WRF at cloud-resolving resolution (1 km or finer) for high-latitude snow events. This study tested the Goddard cloud microphysics scheme in WRF for two different snowstorm events (a lake-effect event and a synoptic event between 20 and 22 January 2007) that took place over the Canadian CloudSat/Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) Validation Project (C3VP) site in Ontario, Canada. The 24-h-accumulated snowfall predicted by WRF with the Goddard microphysics was comparable to that observed by the ground-based radar for both events. The model correctly predicted the onset and termination of both snow events at the Centre for Atmospheric Research Experiments site. The WRF simulations captured the basic cloud patterns as seen by the ground-based radar and satellite [i.e., CloudSat and Advanced Microwave Sounding Unit B (AMSU-B)] observations, including the snowband featured in the lake event. The results reveal that WRF was able to capture the cloud macrostructure reasonably well. Sensitivity tests utilizing both the “2ICE” (ice and snow) and “3ICE” (ice, snow, and graupel) options in the Goddard microphysical scheme were also conducted. The domain- and time-averaged cloud species profiles from the WRF simulations with both microphysical options show identical results (due to weak vertical velocities and therefore the absence of large precipitating liquid or high-density ice particles like graupel). Both microphysics options produced an appreciable amount of liquid water, and the model cloud liquid water profiles compared well to the in situ C3VP aircraft measurements when only grid points in the vicinity of the flight paths were considered. However, statistical comparisons between observed and simulated radar echoes show that the model tended to have a high bias of several reflectivity decibels (dBZ), which shows that additional research is needed to improve the current cloud microphysics scheme for the extremely cold environment in high latitudes, despite the fact that the simulated ice/liquid water contents may have been reasonable for both events. Future aircraft observations are also needed to verify the existence of graupel in high-latitude continental snow events.

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W.-K. Tao, Y. N. Takayabu, S. Lang, S. Shige, W. Olson, A. Hou, G. Skofronick-Jackson, X. Jiang, C. Zhang, W. Lau, T. Krishnamurti, D. Waliser, M. Grecu, P. E. Ciesielski, R. H. Johnson, R. Houze, R. Kakar, K. Nakamura, S. Braun, S. Hagos, R. Oki, and A. Bhardwaj

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 (Q 1) and apparent moisture sink (Q 2). Latent heating (LH) is one of the most dominant terms in Q 1. 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 Q 1 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.

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