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Shinta Seto
and
Toshio Iguchi

Abstract

A new attenuation correction method has been developed for the dual-frequency precipitation radar (DPR) on the core satellite of the Global Precipitation Measurement (GPM) mission. The new method is based on Hitschfeld and Bordan’s attenuation correction method (HB method), but the relationship between the specific attenuation k and the effective radar reflectivity factor Z e (kZ e relationship) is modified by using the dual-frequency ratio (DFR) of Z e and the surface reference technique (SRT). Therefore, the new method is called the HB-DFR-SRT method (H-D-S method). The previous attenuation correction method, called the HB-DFR method (H-D method), results in an underestimation of precipitation rates for heavy precipitation, but the H-D-S method mitigates the negative bias by means of the SRT. When only a single-frequency measurement is available, the H-D-S method is identical to the HB-SRT method (H-S method).

The attenuation correction methods were tested with a simple synthetic DPR dataset. As long as the SRT gives perfect estimates of path-integrated attenuation and the adjustment factor of the kZ e relationship (denoted by ε) is vertically constant, the H-S method is much better than the dual-frequency methods. Tests with SRT error and vertical variation in ε showed that the H-D method was better than the H-S method for weak precipitation, whereas the H-S method was better than the H-D method for heavy precipitation. The H-D-S method did not produce the best results for both weak and heavy precipitation, but the results are stable. Quantitative evaluation should be done with real DPR measurement datasets.

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Toshio Iguchi
and
Robert Meneghini

Abstract

This paper briefly reviews several single-frequency rain profiling methods for an airborne or spaceborne radar. The authors describe the different methods from a unified point of view starting from the basic differential equation. This facilitates the comparisons between the methods and also provides a better understanding of the physical and mathematical basis of the methods. The application of several methods to airborne radar data taken during the Convective and Precipitation/Electrification Experiment is shown. Finally, the authors consider a hybrid method that provides a smooth transition between the Hitschfeld-Bordan method, which performs well at low attenuations, and the surface reference method, for which the relative error decreases with increasing path attenuation.

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Toshiaki Kozu
and
Toshio Iguchi

Abstract

A method is studied to make a nonuniform beamfilling (NUBF) correction for the path-integrated attenuation (PIA) derived from spaceborne radar measurement. The key of this method is to estimate rain-rate variability within a radar field of view from the local statistics of a radar-measurable quantity (〈Q〉) such as PIA derived from the surface reference technique. Statistical analyses are made on spatial variabilities of the radar-measurable quantities using a shipborne radar dataset over the tropical Pacific obtained during the TOGA COARE field campaign. It is found that there are reasonably good correlations between the coarse-scale variability of 〈Q〉 and the finescale variability of rain rate, and the regression coefficient (slope) of these two quantities depends somewhat upon rain types. Based on the statistical analyses, the method is tested with a simulation using the same dataset. The test result indicates that this method is effective in reducing bias errors in the estimation of rain-rate statistics. Although it is also effective to make the NUBF correction on an individual instantaneous field-of-view basis, one must account for the variability of local rainfall statistical characteristics that may cause significant errors in the NUBF correction.

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Shinta Seto
and
Toshio Iguchi

Abstract

In this study, the authors used Tropical Rainfall Measuring Mission precipitation radar (TRMM PR) data to investigate changes in the actual (attenuation corrected) surface backscattering cross section (σ 0 e ) due to changes in surface conditions induced by rainfall, the effects of changes in σ 0 e on the path integrated attenuation (PIA) estimates by surface reference techniques (SRTs), and the effects on rain-rate estimates by the TRMM PR standard rain-rate retrieval algorithm.

Over land, σ 0 e is statistically higher under rainfall than under no rainfall conditions (soil moisture effect) unless the land surface is densely covered by vegetation. Over ocean, the dependence of σ 0 e on the incident angle differs under rainfall and no-rainfall conditions (wind speed effect). The alongtrack spatial reference (ATSR) method, one of the SRTs used in the standard algorithm, partially considers these effects, while the temporal reference (TR) method, another SRT, never involves these effects; its PIA estimates thus have negative biases over land. In the hybrid spatial reference (HSR) method used over ocean, different incident angles create different biases in PIA estimates. If the TR method is replaced by the ATSR method, the monthly rainfall amount in July 2001 all over the land within the TRMM coverage increases by 0.70%. The bias in the HSR method over ocean can be mitigated by fitting a σ 0θ curve separately to smaller incident angles and to larger incident angles. This improvement increases or decreases the monthly rainfall amounts in individual incident angle regions by up to 10%.

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Shinta Seto
,
Nobuhiro Takahashi
, and
Toshio Iguchi

Abstract

One of the goals of the Global Precipitation Measurement project, the successor to the Tropical Rainfall Measuring Mission (TRMM), is to produce a 3-hourly global rainfall map using several spaceborne microwave radiometers. It is important, although often difficult, to classify radiometer observations over land as either “rain” or “no rain” because background land surface conditions change significantly with time and location. In this study, a no-rain brightness temperature database was created to infer land surface conditions using simultaneous observations by TRMM Microwave Imager (TMI) and precipitation radar (PR) with a resolution of 1 month and 1° latitude × 1° longitude. This paper proposes new rain/no-rain classification (RNC) methods that use the database to determine the background brightness temperature. The proposed RNC methods and the RNC method developed for the Goddard profiling algorithm (GPROF; the standard rain-rate retrieval algorithm for TMI) are applied to all TMI observations for the entire year of 2000, and the results are evaluated against the RNC made by PR as the “truth.” The first method (M1) simply uses the average brightness temperature at 85-GHz vertical polarization [denoted as TB (85 V)] under no-rain conditions as the background brightness temperature at 85-GHz vertical polarization [denoted as TB e (85 V)]. The second method (M2) uses a regression equation between TB (85 V) and TB (22 V) under no-rain conditions from the database. Here, TB e (85 V) is calculated by substituting the observed TB (22 V) into the regression equation. The ratio of accurate rain detection by GPROF to all rain occurrences detected by PR was 59%. This ratio was 57% for M1 and 63% for M2. The ratio with the weight of the rain rate was 81% for M1 and 86% for M2; it was 80% for GPROF. These comparisons were made by setting a threshold using a constant coefficient k 0 to make the ratio of false rain detection to all no-rain occurrences detected by PR almost the same (approximately 0.85%) for all three methods. Further comparisons among the methods are made, and the reasons for the differences are investigated herein.

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Robert Meneghini
,
Liang Liao
, and
Toshio Iguchi

Abstract

The dual-frequency ratio of radar reflectivity factors (DFR) has been shown to be a useful quantity as it is independent of the number concentration of the particle size distribution and primarily a function of the mass-weighted particle diameter Dm . A drawback of DFR-related methods for rain estimation, however, is the nonunique relationship between Dm and DFR. At Ku- and Ka-band frequencies, two solutions for Dm exist when DFR is less than zero. This ambiguity generates multiple solutions for the range profiles of the particle size parameters. We investigate characteristics of these solutions for both the initial-value (forward) and final-value (backward) forms of the equations. To choose one among many possible range profiles of Dm , number concentration, and rain rate R, independently measured path attenuations are used. For the backward approach, the possibility exists of dispensing with externally measured path attenuations by achieving consistency between the input and output path attenuations. The methods are tested by means of a simulation based on disdrometer-measured raindrop size distributions and the results are compared with a simplified version of the operational RDm method.

Open access
Shinta Seto
,
Toshio Iguchi
, and
Robert Meneghini

Abstract

Spaceborne precipitation radars, including the Tropical Rainfall Measuring Mission’s Precipitation Radar (PR) and the Global Precipitation Measurement Mission’s Dual-Frequency Precipitation Radar (DPR), measure not only precipitation echoes but surface echoes as well, the latter of which are used to estimate the path-integrated attenuation (PIA) in the surface reference technique (SRT). In our previous study based on analyzing PR measurements, we found that attenuation-free surface backscattering cross sections (denoted by σ e 0 ) over land increased in the presence of precipitation. This behavior, called the soil moisture effect, causes an underestimate of the PIA by the SRT as the method does not explicitly consider this effect. In this study, measurements made by Ku-band Precipitation Radar (KuPR) and Ka-band Precipitation Radar (KaPR), which comprise the DPR, were analyzed to examine whether KuPR and KaPR exhibit similar dependencies on the soil moisture as does the PR. For both KuPR and KaPR, an increase in σ e 0 was observed for a large portion of the land area, except for forests and deserts. Results from the Hitschfeld–Bordan (HB) method suggest that σ e 0 increases with the surface precipitation rate for light precipitation events. Meanwhile, for heavy precipitation, owing to the degradation of the HB method, it is difficult to estimate σ e 0 quantitatively. Thus, a correction method for PIA that considers the soil moisture effect was developed and implemented into the DPR standard algorithm. With this correction, the surface precipitation rate estimates increased by approximately 18% for KuPR and 15% for the normal scan of KaPR over land.

Open access
Toshio Iguchi
,
Nozomi Kawamoto
, and
Riko Oki

Abstract

Detection of ice precipitation is one of the objectives in the Global Precipitation Measurement (GPM) mission. The dual-frequency precipitation radar (DPR) can provide precipitation echoes at two different frequencies, which may enable differentiating solid precipitation echoes from liquid precipitation echoes. A simple algorithm that flags the pixels that contain intense ice precipitation above the height of C is implemented in version 5 of the DPR products. In the inner swath of DPR measurements in which both Ku- and Ka-band radar echoes are available, the measured dual-frequency ratio ( ) together with the measured radar reflectivity factor is used to judge the existence of intense ice precipitation. Comparisons of the flagged pixels with surface measurements show that the algorithm correctly identifies relatively intense ice precipitation regions. The global distribution of the flagged pixels indicates an interesting difference between land and ocean, in particular in the distribution of ice precipitation that reaches the surface. The flag is also expected to be useful for improving precipitation retrieval algorithms by microwave radiometers.

Open access
Liang Liao
,
Robert Meneghini
, and
Toshio Iguchi

Abstract

Validating the results from the spaceborne Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) requires comparisons with well-calibrated ground-based radar measurements. At altitudes near the storm top, where effects of PR signal attenuation are small, the data are used to check the relative calibration accuracy of the radars. Near the surface, where attenuation effects at the PR frequency of 13.8 GHz can be significant, the data provide an assessment of the performance of the PR attenuation correction algorithm. The ground-based data are taken from the Doppler Weather Surveillance (WSR-88D) radar located at Melbourne, Florida. In 1998, 24 overpasses of the TRMM satellite over the Melbourne site occurred during times when significant precipitation was present in the overlap region of the PR and WSR-88D. Resampling the ground-based and spaceborne datasets to a common grid provides a means by which the radar reflectivity factors (dBZ) can be compared at different heights and for different rain types over ocean and land. The results from 1998 show that the dBZ fields derived from the PR data after attenuation correction agree to within about 1 dB of those obtained from the WSR-88D with relatively minor variations (0.3 dB) in this difference with height. Comparisons of rain rates also yield good agreement with the conditional mean rain rate from the PR and WSR-88D of 8.5 and 7.6 mm h−1, respectively. The agreement improves in the comparison of area-averaged rain rates where the PR and WSR-88D yield values of 1.25 and 1.21 mm h−1, respectively, with a correlation coefficient for the 24 overpasses of 0.95.

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Satoru Kobayashi
,
Hiroshi Kumagai
, and
Toshio Iguchi

Abstract

Digitized signals for a spaceborne weather radar are generated to inspect a Doppler signal processor, in which the digital signals are converted to analog through an arbitrary wave generator. A conventional Rice harmonic analysis is applied to include fluctuations of Fourier coefficients explicitly in a time series rather than in an ensemble. The accuracy of Doppler velocity is studied through this simulation for a mean estimator of contiguous pulse-pair operation in a space mission, characterized by a low signal-to-noise ratio (SNR) and a short coherence time. A linear perturbation formula is shown to deviate from the simulation as the SNR decreases and the pulse-pair interval increases. Furthermore, a theoretical limit in measurement accuracy is derived, beyond which the correlation signal is to be practically regarded as white noise, losing the physical meaning of measurement.

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