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  • Author or Editor: Michael I. Biggerstaff x
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Eun-Kyoung Seo and Michael I. Biggerstaff

Abstract

The impact of model microphysics on the retrieval of cloud properties based on passive microwave observations was examined using a three-dimensional, nonhydrostatic, adaptive-grid cloud model to simulate a mesoscale convective system over ocean. Two microphysical schemes, based on similar bulk two-class liquid and three-class ice parameterizations, were used to simulate storms with differing amounts of supercooled cloud water typical of both the tropical oceanic environment, in which there is little supercooled cloud water, and midlatitude continental environments in which supercooled cloud water is more plentiful. For convective surface-level rain rates, the uncertainty varied between 20% and 60% depending on which combination of passive and active microwave observations was used in the retrieval. The uncertainty in surface rain rate did not depend on the microphysical scheme or the parameter settings except for retrievals over stratiform regions based on 85-GHz brightness temperatures TB alone or 85-GHz TB and radar reflectivity combined. In contrast, systematic differences in the treatment of the production of cloud water, cloud ice, and snow between the parameterization schemes coupled with the low correlation between those properties and the passive microwave TB examined here led to significant differences in the uncertainty in retrievals of those cloud properties and latent heating. The variability in uncertainty of hydrometeor structure and latent heating associated with the different microphysical parameterizations exceeded the inherent variability in TB–cloud property relations. This was true at the finescales of the cloud model as well as at scales consistent with satellite footprints in which the inherent variability in TB–cloud property relations are reduced by area averaging.

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Eun-Kyoung Seo and Michael I. Biggerstaff

Abstract

Empirical orthogonal function (EOF) analysis of radiance vectors associated with emission and scattering indices for the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) has been performed to examine the regional variability in relations between brightness temperature and rain rate over portions of the tropical oceans known to exhibit regional differences due to different thermodynamic environments and different large-scale forcing. The TMI indices and rain rates used in this study are the products of the Goddard profiling algorithm (GPROF), version 6. The EOF framework reduces the nine-dimensional space of the brightness temperatures and their polarizations to just two dimensions associated with the EOF coefficients. Vertical profiles of reflectivity from the TRMM precipitation radar (PR) are used to show that the statistically obtained EOFs represent bulk physical characteristics of raining clouds. Hence, EOF analysis provides an efficient framework for diagnosing regional differences in cloud structures that affect brightness temperature–rain-rate relations. The EOF framework revealed fundamental differences in the behavior of TMI surface rain-rate retrievals versus retrievals that are based on the PR aboard the TRMM satellite. In EOF space, TMI rain rates were bimodally distributed, with one mode indicating higher rain rates with greater high-density ice and rainwater content in the cloud and the other mode being consistent with moderately heavy warm rain from shallow convection. In contrast, the PR rain-rate distribution showed high rain rates being assigned over a much greater diversity of cloud structures. The manifold of EOF space constructively shows that, of the regions examined here, the tropical northwestern Pacific Ocean region produces the greatest occurrence of particularly strong cumulonimbus clouds.

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Michael I. Biggerstaff and Steven A. Listemaa

Abstract

An improved algorithm for the partitioning of radar reflectivity into convective and stratiform rain classifications has been developed and tested using data from the Houston, Texas, Weather Surveillance Radar-1988 Doppler. The algorithm starts with output from the current operational version of the Tropical Rainfall Measuring Mission (TRMM) convective/stratiform classification scheme for the ground-based validation sites and corrects the output based on physical characteristics of convective and stratiform rain diagnosed from the three-dimensional structure of the radar reflectivity field. The modified algorithm improved the performance of echo classification by correcting two main sources of error. Heavy stratiform rain, originally classified as convective, and the periphery of convective cores, originally classified as stratiform, were both reclassified by the modified algorithm. When applied to a large dataset of convective storms comprising squall lines, unorganized convection, and embedded convection, it was found that roughly 25% of the total echo area and 14% of the total rain volume were reclassified. The magnitudes of the differences between the original and modified algorithms varied with the morphology of the storm system, suggesting that the quality of current echo classification information supplied by the TRMM program could vary by location depending on the structure of the dominant precipitation systems within a given region. The analysis presented here helps to establish the level of uncertainty in the existing echo classification products available from TRMM.

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Michael I. Biggerstaff, Eun-Kyoung Seo, Svetla M. Hristova-Veleva, and Kwang-Yul Kim

Abstract

The impact of model microphysics on the relationships among hydrometeor profiles, latent heating, and derived satellite microwave brightness temperatures TB have been examined using a nonhydrostatic, adaptive-grid cloud model to simulate a mesoscale convective system over water. Two microphysical schemes (each employing three-ice bulk parameterizations) were tested for two different assumptions in the number of ice crystals assumed to be activated at 0°C to produce simulations with differing amounts of supercooled cloud water. The model output was examined using empirical orthogonal function (EOF) analysis, which provided a quantitative framework in which to compare the simulations. Differences in the structure of the vertical anomaly patterns were related to physical processes and attributed to different approaches in cloud microphysical parameterizations in the two schemes. Correlations between the first EOF coefficients of cloud properties and TB at frequencies associated with the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) showed additional differences between the two parameterization schemes that affected the relationship between hydrometeors and TB. Classified in terms of TB, the microphysical schemes produced significantly different mean vertical profiles of cloud water, cloud ice, snow, vertical velocity, and latent heating. The impact of supercooled cloud water on the 85-GHz TB led to a 15% variation in mean convective rain mass at the surface. The variability in mean profiles produced by the four simulations indicates that the retrievals of cloud properties, especially latent heating, based on TMI frequencies are dependent on the particular microphysical parameterizations used to construct the retrieval database.

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