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Wesley Berg and Susan K. Avery

Abstract

Estimates of monthly rainfall have been computed over the tropical Pacific using passive microwave satellite observations from the Special Sensor Microwave/Imager (SSM/I) for the period from July 1987 through December 1991. The monthly estimates were calibrated using measurements from a network of Pacific atoll rain gauges and compared to other satellite-based rainfall estimation techniques. Based on these monthly estimates, an analysis of the variability of large-scale features over intraseasonal to interannual timescales has been performed. While the major precipitation features as well as the seasonal variability of the rainfall distributions show good agreement with expected values, the presence of a moderately intense El Niño during 1986–87 and an intense La Niña during 1988–89 highlights this time period.

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Wesley Berg, Tristan L'Ecuyer, and Christian Kummerow

Abstract

Intercomparisons of satellite rainfall products have historically focused on the issue of global mean biases. Regional and temporal variations in these biases, however, are equally important for many climate applications. This has led to a critical examination of rainfall estimates from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and precipitation radar (PR). Because of the time-dependent nature of these biases, it is not possible to apply corrections based on regionally defined characteristics. Instead, this paper seeks to relate PR–TMI differences to physical variables that can lead to a better understanding of the mechanisms responsible for the observed differences. To simplify the analysis, issues related to differences in rainfall detection and intensity are investigated separately. For clouds identified as raining by both sensors, differences in rainfall intensity are found to be highly correlated with column water vapor. Adjusting either TMI or PR rain rates based on this simple relationship, which is relatively invariant over both seasonal and interannual time scales, results in a 65%–75% reduction in the rms difference between seasonally averaged climate rainfall estimates. Differences in rainfall detection are most prominent along the midlatitude storm tracks, where widespread, isolated convection trailing frontal systems is often detected only by the higher-resolution PR. Conversely, over the East China Sea clouds below the ∼18-dBZ PR rainfall detection threshold are frequently identified as raining by the TMI. Calculations based on in situ aerosol data collected south of Japan support a hypothesis that high concentrations of sulfate aerosols may contribute to abnormally high liquid water contents within nonprecipitating clouds in this region.

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Wesley Berg, Tristan L’Ecuyer, and John M. Haynes
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Wesley Berg, Tristan L’Ecuyer, and John M. Haynes

Abstract

A combination of rainfall estimates from the 13.8-GHz Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) and the 94-GHz CloudSat Cloud Profiling Radar (CPR) is used to assess the distribution of rainfall intensity over tropical and subtropical oceans. These two spaceborne radars provide highly complementary information: the PR provides the best information on the total rain volume because of its ability to estimate the intensity of all but the lightest rain rates while the CPR’s higher sensitivity provides superior rainfall detection as well as estimates of drizzle and light rain. Over the TRMM region between 35°S and 35°N, rainfall frequency from the CPR is around 9%, approximately 2.5 times that detected by the PR, and the CPR estimates indicate a contribution by light rain that is undetected by the PR of around 10% of the total. Stratifying the results by total precipitable water (TPW) as a proxy for rainfall regime indicates dramatic differences over stratus-dominated subsidence regions, with nearly 20% of the total rain occurring as light rain. Over moist tropical regions, the CPR substantially underestimates rain from intense convective storms because of large attenuation and multiple-scattering effects while the PR misses very little of the total rain volume because of a lower relative contribution from light rain. Over low-TPW regions, however, inconsistencies between estimates from the PR and the CPR point to uncertainties in the algorithm assumptions that remain to be understood and addressed.

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Wesley Berg, John J. Bates, and Darren L. Jackson

Abstract

Satellite microwave and infrared instruments sensitive to upper-tropospheric water vapor (UTWV) are compared using both simulated and observed cloud-cleared brightness temperatures (Tb’s). To filter out cloudy scenes, a cloud detection algorithm is developed for the Special Sensor Microwave/Temperature-2 (SSM/T2 or T2) data using the 92- and 150-GHz window channels. An analysis of the effect of clouds on the T2 183-GHz channels shows sensitivity primarily to high clouds containing ice, resulting in significantly better sampling of UTWV Tb’s over the convective zones and regions of persistent cloudiness. This is in contrast to the infrared sensors, which are extremely sensitive to any cloud contamination in the satellite field of view. A comparison of simulated UTWV Tb’s from T2, the High-resolution Infrared Sounder (HIRS), and the Visible Infrared Spin Scan Radiometer (VISSR) indicates a higher overall sensitivity to changes in UTWV in the T2 channel. HIRS and VISSR, however, are more sensitive to moisture at higher levels. Cloud-cleared Tb’s from T2 and HIRS were found to be highly correlated in the tropical dry zones and in regions of strong seasonal variability but less correlated at higher latitudes. The advantages of the microwave T2 sensor for monitoring UTWV are demonstrated by its greater sensitivity to changes in upper-tropospheric moisture and superior coverage over cloudy regions.

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Hilawe Semunegus, Wesley Berg, John J. Bates, Kenneth R. Knapp, and Christian Kummerow

Abstract

The National Oceanic and Atmospheric Administration National Climatic Data Center has served as the archive of the Defense Meteorological Satellite Program Special Sensor Microwave Imager (SSM/I) data from the F-8, F-10, F-11, F-13, F-14, and F-15 platforms covering the period from July 1987 to the present. Passive microwave satellite measurements from SSM/I have been used to generate climate products in support of national and international programs. The SSM/I temperature data record (TDR) and sensor data record (SDR) datasets have been reprocessed and stored as network Common Data Form (netCDF) 3-hourly files. In addition to reformatting the data, a normalized anomaly (z score) for each footprint temperature value was calculated by subtracting each radiance value with the corresponding monthly 1° grid climatological mean and dividing it by the associated climatological standard deviation. Threshold checks were also used to detect radiance, temporal, and geolocation values that were outside the expected ranges. The application of z scores and threshold parameters in the form of embedded quality flags has improved the fidelity of the SSM/I TDR/SDR period of record for climatological applications. This effort has helped to preserve and increase the data maturity level of the longest satellite passive microwave period of record while completing a key first step before developing a homogenized and intercalibrated SSM/I climate data record in the near future.

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