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  • Author or Editor: T. C. Chang x
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C. Prabhakara, H. D. Chang, and A. T. C. Chang

Abstract

Nimbus 7 Scanning Multichannel Microwave Radiometer (SMMR) brightness temperature measurements in the 21 and 18 GHz channels are used to sense the precipitable water in the atmosphere over oceans. The difference in the brightness temperature (T 21T 18), both in the horizontal and vertical polarization, is found to be essentially a function of the precipitable water in the atmosphere. An equation, based on the physical considerations of the radiative transfer in the microwave region, is developed to relate the precipitable water to (T 21T 18). It is shown from theoretical calculations that the signal (T 21T 18) does not suffer severely from the noise introduced by variations in sea surface temperature, surface winds and liquid water content in non-raining clouds. The rms deviation between the estimated precipitable water from SMMR data and that given by the closely coincident ship radiosondes is about 0.25 g cm−2.

Global maps of precipitable water over oceans derived from SMMR data reveal several salient features associated with ocean currents and the large-scale general circulation in the atmosphere.

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C. Prabhakara, I. Wang, A. T. C. Chang, and P. Gloersen

Abstract

The Nimbus 7 Scanning Multichannel Microwave Radiometer (SMMR) brightness temperature measurements over the global oceans have been examined with the help of statistical and empirical techniques. Such analyses show that zonal averages of brightness temperature measured by SMMR, over the oceans, on a large scale are primarily influenced by the water vapor in the atmosphere. Liquid water in the clouds and rain, which has a much smaller spatial and temporal scale, contributes substantially to the variability of the SMMR measurements within the latitudinal zones. The surface wind not only increase the surface emissivity but through its interactions with the atmosphere produces correlations, in the SMMR brightness temperature data, that have significant meteorological implications. It is found that a simple meteorological model can explain the general characteristics of these data. With the help of this model, methods are developed for investigation of surface temperature, liquid water content in the atmosphere, and surface wind speed over the global oceans. Monthly mean estimates of the sea surface temperature and surface winds are compared with ship measurements. Estimates of liquid water content in the atmosphere are consistent with earlier satellite measurements.

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W. Viezee, H. Shigeishi, and A. T. C. Chang

Abstract

We describe a research study in which we explored the application to rainfall prediction of cloud liquid water data obtained from the SCAMS experiment of Nimbus 6. The study area is the Pacific Northwest coast of the United States, where rainfall is produced by extratropical storms that approach from across the Pacific Ocean.

SCAMS data related to cloud liquid water over the ocean, and coastal rainfall data, are analyzed for 20 different storm systems in the northeastern Pacific Ocean; these produced significant rainfall from Washington to central California during the period October 1975-March 1976. Results show that the distribution of storm-cloud water analyzed from the SCAMS data over the ocean foreshadows the distribution of coastal rainfall accumulated from the storm at a later time.

We conclude that passive microwave sensor measurements of cloud water over the ocean, when used in conjunction with numerical and other objective guidance, can be used to enhance the accuracy of predictions of coastal rainfall distribution.

Limitations in the SCAMS measurements and in the data analysis and interpretation are noted.

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Edward Rodgers, Honnappa Siddalingaiah, A. T. C. Chang, and Thomas Wilheit

Abstract

At 37 GHz, the frequency at which the Nimbus 6 Electrically Scanning Microwave Radiometer (ESMR 6) measures upwelling radiance, it has been shown theoretically that the atmospheric scattering and the relative independence on electromagnetic polarization of the radiances emerging from hydrometeors make it possible to monitor remotely active rainfall over land. In order to verify experimentally these theoretical findings and to develop an algorithm to monitor rainfall over land, the digitized ESMR 6 measurements were examined statistically.

Horizontally and vertically polarized brightness temperature pairs (TH,TV) from ESMR 6 were sampled for areas of rainfall over land as determined from the rain recording stations and the WSR 57 radar, and areas of wet and dry ground (whose thermodynamic temperatures were greater than 5°C) over the southeastern United States. These three categories of brightness temperatures were found to be significantly different in the sense that the chances that the mean vectors of any two populations coincided were less than 1 in 100. Since these categories were significantly different, classification algorithms were then developed. Three decision rules were examined: the Fisher linear classifier, the Bayesian quadratic classifier, and a non-parametric linear classifier. The Bayesian algorithm was found to perform best, particularly at a higher confidence level. An independent test case analysis showed that a rainfall area delineated by the Bayesian classifier coincided well with the synoptic-scale rainfall area mapped by ground recording rain data and radar echoes.

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Long S. Chiu, Alfred T. C. Chang, and John Janowiak

Abstract

Three years of monthly rain rates over 5° × 5° latitude–longitude boxes have been calculated for oceanic regions 50°N–50°S from measurements taken by the Special Sensor Microwave/Imager on board the Defense Meteorological Satellite Program satellites using the technique developed by Wilheit et al. The annual and seasonal zonal-mean rain rates are larger than Jaeger's climatological estimates but are smaller than those estimated from the GOES precipitation index (GPI) for the same period. Regional comparison with the GPI showed that these rain rates are smaller in the north Indian Ocean and in the southern extratropics where the GPI is known to overestimate. The differences are also dominated by a jump at 170°W in the GPI rain rates across the mid Pacific Ocean. This jump is attributed to the fusion of different satellite measurements in producing the GPI.

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A. T. C. Chang, A. Barnes, M. Glass, R. Kakar, and T. T. Wilheit

Abstract

The retrieval of rainfall intensity over the oceans from passive microwave observations is based on a radiative transfer model. Direct rainfall observations of oceanic rainfall are virtually nonexistent making validation of the retrievals extremely difficult. Observations of the model assumptions provide an alternative approach for improving and developing confidence in the rainfall retrievals. In the winter of 1983, the NASA CV-990 aircraft was equipped with a payload suitable for examining several of the model assumptions. The payload included microwave and infrared radiometers, mirror hygrometers, temperature probes, and PMS probes. On two occasions the aircraft ascended on a spiral track through stratiform precipitation providing an opportunity to study the atmospheric parameters. The assumptions concerning liquid hydrometeors, water vapor, lapse rate, and non-precipitating clouds were studied. Model assumptions seem to be supported by these observations.

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T. T. Wilheit, A. T. C. Chang, M. S. V. Rao, E. B. Rodgers, and J. S. Theon

Abstract

A theoretical model for calculating microwave radiative transfer in raining atmospheres is developed. These calculations are compared with microwave brightness temperatures at a wavelength of 1.55 cm measured by the Electrically Scanning Microwave Radiometer (ESMR) on the Nimbus 5 satellite and rain rates derived from WSR-57 meteorological radar measurements. A specially designed ground-based verification experiment was also performed, wherein upward viewing microwave brightness temperature measurements at wavelengths of 1.55 and 0.81 cm were compared with directly measured rain rates. It is shown that over ocean areas, brightness temperature measurements from ESMR may be interpreted in terms of rain rate with about an accuracy of a factor of 2 over the range 1–25 mm h−1 rain rate.

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T. T. Wilheit, A. T. C. Chang, J. L. King, E. B. Rodgers, R. A. Nieman, B. M. Krupp, A. S. Milman, J. S. Stratigos, and H. Siddalingaiah

Abstract

Observations of rain cells in the remains of a decaying tropical storm were made by Airborne Microwave Radiometers at 19.35 and 92 GHz and three frequencies near 183 GHz. Extremely low brightness temperatures, as low as 140 K, were noted in the 92 and 183 GHz observations. These can be accounted for by the ice often associated with raindrop formation. Further, the 183 GHz observations can be interpreted in terms of the height of the ice. The brightness temperatures observed suggest the presence of precipitationsized ice as high as 9 km or more.

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Elizabeth C. Weatherhead, Greg E. Bodeker, Alessandro Fassò, Kai-Lan Chang, Jeffrey K. Lazo, C. T. M. Clack, Dale F. Hurst, Birgit Hassler, Jason M. English, and Soner Yorgun

Abstract

Observing systems consisting of a finite number of in situ monitoring stations can provide high-quality measurements with the ability to quality assure both the instruments and the data but offer limited information over larger geographic areas. This paper quantifies the spatial coverage represented by a finite set of monitoring stations by using global data—data that are possibly of lower resolution and quality. For illustration purposes, merged satellite temperature data from Microwave Sounding Units are used to estimate the representativeness of the Global Climate Observing System Reference Upper-Air Network (GRUAN). While many metrics exist for evaluating the representativeness of a site, the ability to have highly accurate monthly averaged data is essential for both trend detection and climatology evaluation. The calculated correlations of the monthly averaged upper-troposphere satellite-derived temperatures over the GRUAN stations with all other pixels around the globe show that the current 9 certified GRUAN stations have moderate correlations (r ≥ 0.7) for approximately 10% of the earth, but an expanded network incorporating another 15 stations would result in moderate correlations for just over 60% of the earth. This analysis indicates that the value of additional stations can be quantified by using historical, satellite, or model data and can be used to reveal critical gaps in current monitoring capabilities. Evaluating the value of potential additional stations and prioritizing their initiation can optimize networks. The expansion of networks can be evaluated in a manner that allows for optimal benefit on the basis of optimization theory and economic analyses.

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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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