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W.-K. Tao, T. Iguchi, and S. Lang

Abstract

The Goddard convective–stratiform heating (CSH) algorithm has been used to retrieve latent heating (LH) associated with clouds and cloud systems in support of the Tropical Rainfall Measuring Mission and Global Precipitation Measurement (GPM) mission. The CSH algorithm requires the use of a cloud-resolving model to simulate LH profiles to build lookup tables (LUTs). However, the current LUTs in the CSH algorithm are not suitable for retrieving LH profiles at high latitudes or winter conditions that are needed for GPM. The NASA Unified-Weather Research and Forecasting (NU-WRF) Model is used to simulate three eastern continental U.S. (CONUS) synoptic winter and three western coastal/offshore events. The relationship between LH structures (or profiles) and other precipitation properties (radar reflectivity, freezing-level height, echo-top height, maximum dBZ height, vertical dBZ gradient, and surface precipitation rate) is examined, and a new classification system is adopted with varying ranges for each of these precipitation properties to create LUTs representing high latitude/winter conditions. The performance of the new LUTs is examined using a self-consistency check for one CONUS and one West Coast offshore event by comparing LH profiles retrieved from the LUTs using model-simulated precipitation properties with those originally simulated by the model. The results of the self-consistency check validate the new classification and LUTs. The new LUTs provide the foundation for high-latitude retrievals that can then be merged with those from the tropical CSH algorithm to retrieve LH profiles over the entire GPM domain using precipitation properties retrieved from the GPM combined algorithm.

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Joanne Simpson, Jeffrey Halverson, Harold Pierce, Carlos Morales, and T. Iguchi
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R. Meneghini, J. A. Jones, T. Iguchi, K. Okamoto, and J. Kwiatkowski

Abstract

Data from the Tropical Rainfall Measuring Mission (TRMM) precipitation radar represent the first global rain-rate dataset acquired by a spaceborne weather radar. Because the radar operates at an attenuating wavelength, one of the principal issues concerns the accuracy of the attenuation correction algorithms. One way to test these algorithms is by means of a statistical method in which the probability distribution of rain rates at the high end is inferred by measurements at the low to intermediate range and by the assumption that the rain rates are lognormally distributed. Investigation of this method and the area–time integral methods using a global dataset provides an indication of how well methods of this kind can be expected to perform over different space–timescales and climatological regions using the sparsely sampled TRMM radar data. Identification of statistical relationships among the rain parameters and an understanding of the rain-rate distribution as a function of time and space may help to test the validity of the high-resolution rain-rate estimates.

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R. Meneghini, J. A. Jones, T. Iguchi, K. Okamoto, and J. Kwiatkowski

Abstract

Satellite weather radars that operate at attenuating wavelengths require an estimate of path attenuation to reconstruct the range profile of rainfall. One such method is the surface reference technique (SRT), by which attenuation is estimated as the difference between the surface cross section outside the rain and the apparent surface cross section measured in rain. This and the Hitschfeld–Bordan method are used operationally to estimate rain rate using data from the precipitation radar (PR) aboard the Tropical Rainfall Measuring Mission (TRMM) satellite. To overcome some of the problems associated with the latest operational version of the SRT, a hybrid surface reference is defined that uses information from the along-track and cross-track variations of the surface cross sections in rain-free areas. Over ocean, this approach eliminates most of the discontinuities in the path-attenuation field. Self-consistency of the estimates is tested by processing the orbits backward as well as forward. Calculations from 2 weeks of PR data show that 90% of the rain events over ocean for which the SRT is classified as reliable or marginally reliable are such that the absolute difference between the forward and backward estimates is less than 1 dB.

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Takamichi Iguchi, Toshihisa Matsui, Wei-Kuo Tao, Alexander P. Khain, Vaughan T. J. Phillips, Chris Kidd, Tristan L’Ecuyer, Scott A. Braun, and Arthur Hou

Abstract

Two mixed-phase precipitation events were observed on 21 September and 20 October 2010 over the southern part of Finland during the Light Precipitation Validation Experiment (LPVEx). These events have been simulated using the Weather Research and Forecasting Model coupled with spectral bin microphysics (WRF–SBM). The detailed ice-melting scheme with prognosis of the liquid water fraction during melting enables explicit simulation of microphysical properties in the melting layer. First, the simulations have been compared with C-band 3D radar measurements for the purpose of evaluating the overall profiles of cloud and precipitation. The simulation has some artificial convective patterns and errors in the forecast displacement of the precipitation system. The overall overestimation of reflectivity is consistent with a bias toward the range characterized by large-diameter droplets in the surface drop size distribution. Second, the structure of the melting bands has been evaluated against vertically pointing K-band radar measurements. A peak in reflectivity and a gradual change in Doppler velocity are observed and similarly simulated in the common temperature range from approximately 0° to 3°C. The effectiveness of the time-dependent melting scheme has been justified by intercomparison with a corresponding simulation using an instantaneous melting scheme. A weakness of the new melting scheme is that melting particles having high liquid water fractions on the order of 80%–90% cannot be simulated. This situation may cause underestimation of radar reflectivity in the melting layer because of the assumptions of melting-particle structure used to calculate the scattering properties.

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C. Kummerow, J. Simpson, O. Thiele, W. Barnes, A. T. C. Chang, E. Stocker, R. F. Adler, A. Hou, R. Kakar, F. Wentz, P. Ashcroft, T. Kozu, Y. Hong, K. Okamoto, T. Iguchi, H. Kuroiwa, E. Im, Z. Haddad, G. Huffman, B. Ferrier, W. S. Olson, E. Zipser, E. A. Smith, T. T. Wilheit, G. North, T. Krishnamurti, and K. Nakamura

Abstract

The Tropical Rainfall Measuring Mission (TRMM) satellite was launched on 27 November 1997, and data from all the instruments first became available approximately 30 days after the launch. Since then, much progress has been made in the calibration of the sensors, the improvement of the rainfall algorithms, and applications of these results to areas such as data assimilation and model initialization. The TRMM Microwave Imager (TMI) calibration has been corrected and verified to account for a small source of radiation leaking into the TMI receiver. The precipitation radar calibration has been adjusted upward slightly (by 0.6 dBZ) to match better the ground reference targets; the visible and infrared sensor calibration remains largely unchanged. Two versions of the TRMM rainfall algorithms are discussed. The at-launch (version 4) algorithms showed differences of 40% when averaged over the global Tropics over 30-day periods. The improvements to the rainfall algorithms that were undertaken after launch are presented, and intercomparisons of these products (version 5) show agreement improving to 24% for global tropical monthly averages. The ground-based radar rainfall product generation is discussed. Quality-control issues have delayed the routine production of these products until the summer of 2000, but comparisons of TRMM products with early versions of the ground validation products as well as with rain gauge network data suggest that uncertainties among the TRMM algorithms are of approximately the same magnitude as differences between TRMM products and ground-based rainfall estimates. The TRMM field experiment program is discussed to describe active areas of measurements and plans to use these data for further algorithm improvements. In addition to the many papers in this special issue, results coming from the analysis of TRMM products to study the diurnal cycle, the climatological description of the vertical profile of precipitation, storm types, and the distribution of shallow convection, as well as advances in data assimilation of moisture and model forecast improvements using TRMM data, are discussed in a companion TRMM special issue in the Journal of Climate (1 December 2000, Vol. 13, No. 23).

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W.-K. Tao, E. A. Smith, R. F. Adler, Z. S. Haddad, A. Y. Hou, T. Iguchi, R. Kakar, T. N. Krishnamurti, C. D. Kummerow, S. Lang, R. Meneghini, K. Nakamura, T. Nakazawa, K. Okamoto, W. S. Olson, S. Satoh, S. Shige, J. Simpson, Y. Takayabu, G. J. Tripoli, and S. Yang

Rainfall is a fundamental process within the Earth's hydrological cycle because it represents a principal forcing term in surface water budgets, while its energetics corollary, latent heating, is the principal source of atmospheric diabatic heating well into the middle latitudes. Latent heat production itself is a consequence of phase changes between the vapor, liquid, and frozen states of water. The properties of the vertical distribution of latent heat release modulate large-scale meridional and zonal circulations within the Tropics, as well as modify the energetic efficiencies of midlatitude weather systems.

This paper highlights the retrieval of latent heating from satellite measurements generated by the Tropical Rainfall Measuring Mission (TRMM) satellite observatory, which was launched in November 1997 as a joint American–Japanese space endeavor. Since then, TRMM measurements have been providing credible four-dimensional accounts of rainfall over the global Tropics and subtropics, information that can be used to estimate the space–time structure of latent heating across the Earth's low latitudes.

A set of algorithm methodologies for estimating latent heating based on precipitation-rate profile retrievals obtained from TRMM measurements has been under continuous development since the advent of the mission s research program. These algorithms are briefly described, followed by a discussion of the latent heating products that they generate. The paper then provides an overview of how TRMM-derived latent heating information is currently being used in conjunction with global weather and climate models, concluding with remarks intended to stimulate further research on latent heating retrieval from satellites.

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