Passive microwave algorithm development and evaluation

The scientific objectives of this grant are: (1) thoroughly evaluate, both theoretically and empirically, all available Special Sensor Microwave Imager (SSM/I) retrieval algorithms for column water vapor, column liquid water, and surface wind speed; (2) where both appropriate and feasible, develop, validate, and document satellite passive microwave retrieval algorithms that offer significantly improved performance compared with currently available algorithms; and (3) refine and validate a novel physical inversion scheme for retrieving rain rate over the ocean. This report summarizes work accomplished or in progress during the first year of a three year grant. The emphasis during the first year has been on the validation and refinement of the rain rate algorithm published by Petty and on the analysis of independent data sets that can be used to help evaluate the performance of rain rate algorithms over remote areas of the ocean. Two articles in the area of global oceanic precipitation are attached

Frequencies and Characteristics of Global Oceanic Precipitation from Shipboard Present-Weather Reports

Ship reports of present weather obtained from the Comprehensive Ocean-Atmosphere Data Set are analyzed for the period 1958-91 in order to elucidate regional and seasonal variations in the climatological frequency, phase, intensity, and character of oceanic precipitation. Specific findings of note include the following: 1) The frequency of thunderstorm reports, relative to all precipitation reports, is a strong function of location, with thunderstorm activity being favored within 1000-3000 km of major tropical and subtropical land masses, while being quite rare at other locations, even within the intertropical convergence zone. 2) The latitudinal frequency of precipitation over the southern oceans increases steadily toward the Antarctic continent and shows relatively little seasonal variation. The frequency of convective activity, however, shows considerable seasonal variability, with sharp winter maxima occurring near 38 deg. latitude in both hemispheres. 3) Drizzle is the preferred form of precipitation in a number of regions, most of which coincide with known regions of persistent marine stratus and stratocumulus in the subtropical highs. Less well documented is the high relative frequency of drizzle in the vicinity of the equatorial sea surface temperature front in the eastern Pacific. 4) Regional differences in the temporal scale of precipitation events (e.g., transient showers versus steady precipitation) are clearly depicted by way of the ratio of the frequency of precipitation at the observation time to the frequency of all precipitation reports, including precipitation during the previous hour. The results of this study suggest that many current satellite rainfall estimation techniques may substantially underestimate the fractional coverage or frequency of precipitation poleward of 50 deg. latitude and in the subtropical dry zones. They also draw attention to the need to carefully account for regional differences in the physical and spatial properties of rainfall when developing calibration relationships for satellite algorithms

Atmospheric water parameters in mid-latitude cyclones observed by microwave radiometry and compared to model calculations

Existing and experimental algorithms for various parameters of atmospheric water content such as integrated water vapor, cloud water, precipitation, are used to examine the distribution of these quantities in mid latitude cyclones. The data was obtained from signals given by the special sensor microwave/imager (SSM/I) and compared with data from the nimbus scanning multichannel microwave radiometer (SMMR) for North Atlantic cyclones. The potential of microwave remote sensing for enhancing knowledge of the horizontal structure of these storms and to aid the development and testing of the cloud and precipitation aspects of limited area numerical models of cyclonic storms is investigated

Bayesian Retrieval of Complete Posterior PDFs of Oceanic Rain Rate From Microwave Observations

This paper presents a new Bayesian algorithm for retrieving surface rain rate from Tropical Rainfall Measurements Mission (TRMM) Microwave Imager (TMI) over the ocean, along with validations against estimates from the TRMM Precipitation Radar (PR). The Bayesian approach offers a rigorous basis for optimally combining multichannel observations with prior knowledge. While other rain rate algorithms have been published that are based at least partly on Bayesian reasoning, this is believed to be the first self-contained algorithm that fully exploits Bayes Theorem to yield not just a single rain rate, but rather a continuous posterior probability distribution of rain rate. To advance our understanding of theoretical benefits of the Bayesian approach, we have conducted sensitivity analyses based on two synthetic datasets for which the true conditional and prior distribution are known. Results demonstrate that even when the prior and conditional likelihoods are specified perfectly, biased retrievals may occur at high rain rates. This bias is not the result of a defect of the Bayesian formalism but rather represents the expected outcome when the physical constraint imposed by the radiometric observations is weak, due to saturation effects. It is also suggested that the choice of the estimators and the prior information are both crucial to the retrieval. In addition, the performance of our Bayesian algorithm is found to be comparable to that of other benchmark algorithms in real-world applications, while having the additional advantage of providing a complete continuous posterior probability distribution of surface rain rate

SSM/I Rainfall Volume Correlated with Deepening Rate in Extratropical Cyclones

With the emergence of reasonably robust, physically based rain rate algorithms designed for the Special Sensor Microwave/Imager (SSM/I), a unique opportunity exists to directly observe a physical component which can contribute to or be a signature of cyclone deepening (latent heat release). The emphasis of the research in this paper is to seek systematic differences in rain rate observed by the SSM/I, using the algorithm of Petty in cases of explosive and nonexplosive cyclone deepening

Rainfall rates and the vertical distribution of diabatic heating components over tropical oceans

During the fall of 1993, nearly all of the emphasis on this project was devoted to the completion of Ph.D. research. In January 1994, a poster summarizing research was presented at the 8th Conference on Atmospheric Radiation held in Nashville, TN. In February 1994, we submitted two papers for publication. Finally, we learned that we have had a paper accepted for poster presentation at the European Conference on the Global Energy and Water Cycle to be held in London, England in July 1994. Titles for all these papers are provided

A New Inversion-Based Algorithm for Retrieval of Over-Water Rain Rate from SSM/I Multichannel Imagery

This paper discusses certain aspects of a new inversion based algorithm for the retrieval of rain rate over the open ocean from the special sensor microwave/imager (SSM/I) multichannel imagery. This algorithm takes a more detailed physical approach to the retrieval problem than previously discussed algorithms that perform explicit forward radiative transfer calculations based on detailed model hydrometer profiles and attempt to match the observations to the predicted brightness temperature

Microwave Properties of Ice-Phase Hydrometeors for Radar and Radiometers: Sensitivity to Model Assumptions

A simplied framework is presented for assessing the qualitative sensitivities of computed microwave properties, satellite brightness temperatures, and radar reflectivities to assumptions concerning the physical properties of ice-phase hydrometeors. Properties considered included the shape parameter of a gamma size distribution andthe melted-equivalent mass median diameter D0, the particle density, dielectric mixing formula, and the choice of complex index of refraction for ice. We examine these properties at selected radiometer frequencies of 18.7, 36.5, 89.0, and 150.0 GHz; and radar frequencies at 2.8, 13.4, 35.6, and 94.0 GHz consistent with existing and planned remote sensing instruments. Passive and active microwave observables of ice particles arefound to be extremely sensitive to the melted-equivalent mass median diameter D0 ofthe size distribution. Similar large sensitivities are found for variations in the ice vol-ume fraction whenever the geometric mass median diameter exceeds approximately 1/8th of the wavelength. At 94 GHz the two-way path integrated attenuation is potentially large for dense compact particles. The distribution parameter mu has a relatively weak effect on any observable: less than 1-2 K in brightness temperature and up to 2.7 dB difference in the effective radar reflectivity. Reversal of the roles of ice and air in the MaxwellGarnett dielectric mixing formula leads to a signicant change in both microwave brightness temperature (10 K) and radar reflectivity (2 dB). The choice of Warren (1984) or Warren and Brandt (2008) for the complex index of refraction of ice can produce a 3%-4% change in the brightness temperature depression

Multisensor Observation and Simulation of Snowfall During the 2003 Wakasa Bay Field Experiment

This research seeks to assess and improve the accuracy of microphysical assumptions used in satellite passive microwave radiative transfer models and retrieval algorithms by exploiting complementary observations from satellite radiometers, such as TRMM/AMSR-E/GPM, and coincident aircraft instruments, such as the next generation precipitation radar (PR-2). We focus in particular on aircraft data obtained during the Wakasa Bay field experiment, Japan 2003, pertaining to surface snowfall events. The observations of vertical profiles of reflectivity and Doppler-derived fall speeds are used in conjunction with the radiometric measurements to identify 1-D profiles of precipitation particle types, sizes, and concentrations that are consistent with the observations

Bayesian retrieval of complete posterior PDFs of oceanic rain rate from microwave observations

A new Bayesian algorithm for retrieving surface rain rate from Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) over the ocean is presented, along with validations against estimates from the TRMM Precipitation Radar (PR). The Bayesian approach offers a rigorous basis for optimally combining multichannel observations with prior knowledge. While other rain-rate algorithms have been published that are based at least partly on Bayesian reasoning, this is believed to be the first self-contained algorithm that fully exploits Bayes’s theorem to yield not just a single rain rate, but rather a continuous posterior probability distribution of rain rate. To advance the understanding of theoretical benefits of the Bayesian approach, sensitivity analyses have been conducted based on two synthetic datasets for which the “true” conditional and prior distribution are known. Results demonstrate that even when the prior and conditional likelihoods are specified perfectly, biased retrievals may occur at high rain rates. This bias is not the result of a defect of the Bayesian formalism, but rather represents the expected outcome when the physical constraint imposed by the radiometric observations is weak owing to saturation effects. It is also suggested that both the choice of the estimators and the prior information are crucial to the retrieval. In addition, the performance of the Bayesian algorithm herein is found to be comparable to that of other benchmark algorithms in real-world applications, while having the additional advantage of providing a complete continuous posterior probability distribution of surface rain rate