Beam-filling Correction Research Articles

Effects of TRMM Boost on Oceanic Rainfall Estimates Based on Microwave Emission Brightness Temperature Histograms (METH)

Abstract A physical–statistical algorithm for estimating space–time average oceanic rainfall has been applied to microwave measurements taken by the Special Sensor Microwave Imager (SSM/I) on board the Defense Meteorological Satellite Program (DMSP) satellites and the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) on board the TRMM satellite. The algorithm is based on Microwave Emission Brightness Temperature Histograms (METH) and produces monthly rainfall over 5° × 5° latitude–longitude boxes as a TRMM standard product (3A11). The TRMM satellite was boosted from an altitude of 350–402 km in August 2001 to extend its mission life. The orbit boost affected the orbital parameters, rain-rate–brightness temperature relations, and then rain-rate parameters. Using oceanic rain rates derived from SSM/I, the difference between 3A11 and SSM/I for the preboost and postboost periods was analyzed. The difference shows a significant jump from the preboost to the postboost data if no adjustments were made for the postboost TRMM data. The jumps in rain-rate parameters are attributed to the changes in earth’s incidence angle of TMI, affecting the brightness temperature in the TMI channels, the retrieved altitude of the freezing level, and the beam-filling correction factor. The changes in the brightness temperature (and freezing level) estimates and the beam-filling correction factor accounted for differences of approximately 4.9% and 1.5%, respectively. After the orbital and radiometric parameters are corrected for the boost, there is no detectable jump between the pre- and postboost 3A11 rain rates. The intersatellite calibration results demonstrate the robustness of the technique in producing a long record of climate-scale oceanic rainfall.

Intercalibrated Passive Microwave Rain Products from the Unified Microwave Ocean Retrieval Algorithm (UMORA)

AbstractThe Unified Microwave Ocean Retrieval Algorithm (UMORA) simultaneously retrieves sea surface temperature, surface wind speed, columnar water vapor, columnar cloud water, and surface rain rate from a variety of passive microwave radiometers including the Special Sensor Microwave Imager (SSM/I), the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI), and the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E). The rain component of UMORA explicitly parameterizes the three physical processes governing passive microwave rain retrievals: the beamfilling effect, cloud and rainwater partitioning, and effective rain layer thickness. Rain retrievals from the previous version of UMORA disagreed among different sensors and were too high in the tropics. These issues have been fixed with more realistic rain column heights and proper modeling of saturation and footprint-resolution effects in the beamfilling correction. The purpose of this paper is to describe the rain algorithm and its recent improvements and to compare UMORA retrievals with Goddard Profiling Algorithm (GPROF) and Global Precipitation Climatology Project (GPCP) rain rates. On average, TMI retrievals from UMORA agree well with GPROF; however, large differences become apparent when the instantaneous retrievals are compared on a pixel-to-pixel basis. The differences are due to fundamental algorithm differences. For example, UMORA generally retrieves higher total liquid water, but GPROF retrieves a higher surface rain rate for a given amount of total liquid water because of differences in microphysical assumptions. Comparison of UMORA SSM/I retrievals with GPCP shows similar spatial patterns, but GPCP has higher global averages because of greater amounts of precipitation in the extratropics. UMORA and GPCP have similar linear trends over the period 1988–2005 with similar spatial patterns.

The Effects of Rainfall Inhomogeneity on Climate Variability of Rainfall Estimated from Passive Microwave Sensors

Abstract Passive microwave rainfall estimates that exploit the emission signal of raindrops in the atmosphere are sensitive to the inhomogeneity of rainfall within the satellite field of view (FOV). In particular, the concave nature of the brightness temperature (Tb) versus rainfall relations at frequencies capable of detecting the blackbody emission of raindrops cause retrieval algorithms to systematically underestimate precipitation unless the rainfall is homogeneous within a radiometer FOV, or the inhomogeneity is accounted for explicitly. This problem has a long history in the passive microwave community and has been termed the beam-filling error. While not a true error, correcting for it requires a priori knowledge about the actual distribution of the rainfall within the satellite FOV, or at least a statistical representation of this inhomogeneity. This study first examines the magnitude of this beam-filling correction when slant-path radiative transfer calculations are used to account for the obliqu...

Nonsystematic Errors of Monthly Oceanic Rainfall Derived from SSM/I

About 10 yr (July 1987-December 1997 with December 1987 missing) of oceanic monthly rainfall based on data taken by the Special Sensor Microwave/Imager (SSM/I) on board the Defense Meteorological Satellite Program satellites have been computed. The technique, based on the work of Wilheit et al., includes improved parameterization of the beam-filling correction, a refined land mask and sea ice filter. Monthly means are calculated for both 5° and 2.5° latitude-longitude boxes. Monthly means over the latitude band of 50°N-50°S and error statistics are presented. The time-averaged rain rate is 3.09 mm day ' (std dev of 0.15 mm day -1 ) with an error of 38.0% (std dev of 3.0%) for the 5° monthly means over the 10-yr period. These statistics compare favorably with 3.00 mm day -1 (std dev of 0.19 mm day -1 ) and 46.7% (std dev of 3.4%) computed from the 2.5° monthly means for the period January 1992-December 1994. Examination of the different rain rate categories shows no distinct discontinuity, except for months with a large number of missing SSM/I data. An independent estimate of the error using observations from two satellites shows an error of 31% (std dev of 2.7%), consistent with the 38% estimated using (A.M. and P.M.) data from one satellite alone. Error estimates (31%) based on the 5° means by averaging four neighboring 2.5° boxes are larger than those (23%) estimated by assuming the means for these neighboring boxes are independent, thus suggesting spatial dependence of the 2.5° means. Multiple regression analyses show that the error varies inversely as the square root of the number of samples but exhibits a somewhat weaker dependence on the mean rain rate. Regression analyses show a power law dependence of -0.255 to -0.265 on the rain rate for the 5° monthly means using data from a single satellite and a dependence of - -0.366 for the 5° monthly means and -0.337 for the 2.5° monthly means based on two satellite measurements. The latter estimate is consistent with that obtained by Bell et al. using a different rainfall retrieval technique.

SSM/I Rain Retrievals within a Unified All-Weather Ocean Algorithm

A new method for the physical retrieval of rain rates from satellite microwave radiometers is presented. The method is part of a unified ocean parameter retrieval algorithm that is based on the fundamental principles of radiative transfer. The algorithm simultaneously finds near-surface wind speed W, columnar water vapor V, columnar cloud liquid water L, rain rate R, and effective radiating temperature TU for the upwelling radiation. Comparisons with radiosondes demonstrate that the algorithm is able to retrieve water vapor when rain is present. For rain rates from 1 to 15 mm h−1, the rms difference between the retrieved water vapor and the radiosonde value is 5 mm. A novel feature of the rain retrieval method is a beamfilling correction that is based upon the ratio of the retrieved liquid water absorption coefficients at 37 and 19 GHz. This spectral ratio decreases by about 40% when heavy and light rain coexist within the SSM/I footprint as compared to the case of uniform rain. This correction increases the rain rate when the spectral ratio is small. However, even with this beamfilling correction, tropical rainfall is still unrealistically low when the freezing level in the Tropics (∼5 km) is used to specify the rain layer thickness. Realism is restored by reducing the assumed tropical rain-layer thickness to 3 km. This adjustment is probably compensating for two processes: 1) the existence of warm rain for which the rain layer does not extend to the freezing level and 2) very heavy rain for which the 19-GHz channels saturate. Global rain rates are produced for the 1991–94 period from two SSM/Is. The authors find that approximately 6% of the SSM/I observations detect measurable rain rates (R > 0.2 mm h−1). The global rain maps show features that are, in general, similar to those reported in previously published rain climatologies. However, some differences that seem to be related to nonprecipitating cloud water are apparent.

Effects of field of view inhomogeneities on the rain estimation from microwave radiometry

We present a method to estimate the beamfilling correction factor for rain rates calculated from SSM/I data at 19 GHz, horizontal polarization. An application to a tropical situation is presented, where brightness temperatures vary typically from 175 K to 235K. We show the quantitative dependence of this correction with the fraction of the field of view covered by rain. This leads to a correction factor in the range 1.5-3.

Rainfall Estimation from ESMR-5 Measurements and Application to El Niño

An algorithm to estimate monthly 5° × 5° area-averaged rain rate over the oceans from January 1973 to December 1976 using single-channel microwave data from the Nimbus-5 satellite has been developed. This study extends the work of Shin et al. by including the full width of scan angles (from −50° to 50°) in order to reduce sampling error. The scan-angle dependence of the estimated rain rate due to variable antenna sidelobe effects, surface emissivity, and propagation pathlength is eliminated using a statistical method. A globally uniform beam-filling correction factor of 2.2 is applied in this study. Comparison with island station rainfall measurements over the Pacific shows a remarkably high correlation between two data in the equatorial dry zone and South Pacific convergence zone (SPCZ) but a low correlation in the extratropics and equatorial western Pacific. It is also proved that the retrieved rain rates are statistically significant. The rainfall deviations from non-El Niño years April 1973 to December 1975 reveal the temporal and spatial variations produced by the 1972–73 and 1976–77 El Niño episodes. We observe an increase of rainfall over the eastern and central equatorial Pacific Ocean and a decrease over the equatorial western Pacific Ocean and eastern Australia during these events. Consistent with previous work, the rainfall anomaly of the 1972–73 El Niño was much stronger than that of the 1976–77 El Niño.

Retrieval of Monthly Rainfall Indices from Microwave Radiometric Measurements Using Probability Distribution Functions

Abstract An algorithm for the estimation of monthly rain totals for 5° cells over the oceans from histograms of SSM/I brightness temperatures has been developed. Them are three novel features to this algorithm. First, it uses knowledge of the form of the rainfall intensity probability density function to augment the measurements. Second, a linear combination of the 19.35 and 22.235 GHz channels has been employed to reduce the impact of variability of water vapor. Third, an objective technique has been developed to estimate the rain layer thickness from the 19.35- and 22.235-GHz brightness temperature histograms. Comparison with climatologies and the GATE radar observations suggest that the estimates are reasonable in spite of not having a beam-filling correction. By-products of the retrievals indicate that the SSM/I instrument noise level and calibration stability am quite good.