Abstract

Satellite remote sensing is an indispensable means of measuring and monitoring precipitation on a global scale. The Tropical Rainfall Measuring Mission (TRMM) is continuing to make significant progress in helping the global features of precipitation to be understood, particularly with the help of a pair of spaceborne microwave sensors, the TRMM Microwave Imager (TMI) and precipitation radar (PR). The TRMM version-5 standard products, however, are known to have a systematic inconsistency in mean monthly rainfall. To clarify the origin of this inconsistency, the authors investigate the zonal mean precipitation and the regional trends in the hydrometeor profiles in terms of the precipitation water content (PWC) and the precipitation water path (PWP) derived from the TMI profiling algorithm (2A12) and the PR profile (2A25). An excess of PR over TMI in near-surface PWC is identified in the midlatitudes (especially in winter), whereas PWP exhibits a striking excess of TMI over PR around the tropical rainfall maximum. It is shown that these inconsistencies arise from TMI underestimating the near-surface PWC in midlatitude winter and PR underestimating PWP in the Tropics. This conclusion is supported by the contoured-frequency-by-altitude diagrams as a function of PWC. Correlations between rain rate and PWC/PWP indicate that the TMI profiling algorithm tends to provide a larger rain rate than the PR profile under a given PWC or PWP, which exaggerates the excess by TMI and cancels the excess by PR through the conversion from precipitation water to rain rate. As a consequence, the disagreement in the rainfall products between TMI and PR is a combined result of the intrinsic bias originating from the different physical principles between TMI and PR measurements and the purely algorithmic bias inherent in the conversion from precipitation water to rain rate.

Abstract

A generalized method is presented to derive a “two scale” raindrop size distribution (DSD) model over a spatial or temporal domain in which a statistical rain parameter relation exists. The two-scale model is generally defined as a model in which one DSD parameter is allowed to vary rapidly and the other is constant over a certain space or time domain. The existence of a rain parameter relation such as the radar reflectivity–rainfall rate (Z–R) relation over a spatial or temporal domain is an example of such a two-scale DSD model. A procedure is described that employs a statistical rain parameter relation with an assumption of the gamma DSD model. An example using Z–R relations obtained at Kototabang, West Sumatra, is presented. The result shows that the resulting two-scale DSD model expressed by conventional DSD parameters depends on the assumed value of parameter μ while rain parameter relations such as k–Z_e relations from those models using different μ values are very close to each other, indicating the stability of the model against the variation of μ and the validity of this method. The result is applied to the DSD model for the Tropical Rainfall Measuring Mission (TRMM) precipitation radar 2A25 (versions 5 and 6) algorithm. The derivation procedure of the 2A25 DSD model is described. Through the application of this model, it has become possible to make a logically well-organized rain profiling algorithm and reasonable rain attenuation correction and rainfall estimates, as described in an earlier paper by Iguchi et al.

Abstract

Use of dual-wavelength radar, with properly chosen wavelengths, will significantly lessen the ambiguities in the retrieval of microphysical properties of hydrometeors. In this paper, a dual-wavelength algorithm is described to estimate the characteristic parameters of the snow size distributions. An analysis of the computational results, made at X and Ka bands (T-39 airborne radar) and at S and X bands (CP-2 ground-based radar), indicates that valid estimates of the median volume diameter of snow particles, D ₀, should be possible if one of the two wavelengths of the radar operates in the non-Rayleigh scattering region. However, the accuracy may be affected to some extent if the shape factors of the gamma distribution used for describing the particle distribution are chosen far from the true values or if cloud water attenuation is significant. To examine the validity and accuracy of the dual-wavelength radar algorithms, the algorithms are applied to the data taken from the Convective and Precipitation-Electrification Experiment (CaPE) in 1991, in which the dual-wavelength airborne radar was coordinated with in situ aircraft particle observations and ground-based radar measurements. Having carefully coregistered the data obtained from the different platforms, the airborne radar-derived size distributions are then compared with the in situ measurements and ground-based radar. Good agreement is found for these comparisons despite the uncertainties resulting from mismatches of the sample volumes among the different sensors as well as spatial and temporal offsets.

The authors discuss the origin of a unique footprint on the sea induced by storm winds and rainfall as seen by synthetic aperture radar (SAR) from space. Two hypotheses are presented to explain the origin of an apparent wind shadow downwind of a storm cell. The first suggests that the cool air pool from the storm acts as an obstacle to divert the low-level easterly ambient winds and leaves a “wind shadow” on its downwind side. This theory is discarded because of the excessive storm lifetime needed to cause the long downstream “shadow.” The second hypothesis invokes the cool outflows from two preexisting storm cells such that their boundaries intersect obliquely leaving a triangular wedge of weaker winds and radar cross section (i.e., the shadow). A new precipitation cell is initiated at the point of intersection of the boundaries at the apex of the shadow, giving the illusion that this cell is the cause of the shadow. While the authors lack corroborative observations, this theory is consistent with prior evidence of the triggering of convective clouds and precipitation by intersecting cool air boundaries. The regular observation of such persistent cool air storm outflow boundaries both in satellite observations, and more recently in SAR imagery, suggests that such discontinuities are ubiquitous and serve to trigger new convection in the absence of large-scale forcing.

Abstract

This paper describes the Tropical Rainfall Measuring Mission (TRMM) standard algorithm that estimates the vertical profiles of attenuation-corrected radar reflectivity factor and rainfall rate. In particular, this paper focuses on the critical steps in the algorithm. These steps are attenuation correction, selection of the default drop size distribution model including vertical variations, and correction for the nonuniform beam-filling effect. The attenuation correction is based on a hybrid of the Hitschfeld–Bordan method and a surface reference method. A new algorithm to obtain an optimum weighting function is described. The nonuniform beam-filling problem is analyzed as a two-dimensional problem. The default drop size distribution model is selected according to the criterion that the attenuation estimates derived from the model and the independent estimates from the surface reference with the nonuniform beam-filling correction are consistent for rain over ocean. It is found that the drop size distribution models that are consistent for convective rain over ocean are not consistent over land, indicating a change in the size distributions associated with convective rain over land and ocean, respectively.

Abstract

During the rainy season over the East China Sea, convective rainfalls often show melting layer (ML) characteristics in polarimetric radar variables. In this research, the appearance ratio of the ML (the ratio of rainfall area accompanied by polarimetric ML signatures) and the variation in height of the level of the ML signature maximum (MLSM level; defined by the level of the ρ _hv minimum in the ML) in a convective rainfall region in a rainfall system over the East China Sea observed on 2 June 2006 were studied using C-band polarimetric radar (COBRA). For this analysis, a method of rainfall type classification that evaluates the presence of an ML in addition to providing conventional convective–stratiform classification using range–height indicator (RHI) observation data was developed. This rainfall type classification includes two steps: conventional convective–stratiform separation using the horizontal distribution of Z_h at 2-km altitude, and ML detection using the vertical profile of ρ _hv at each horizontal grid point. Using a combination of these two classifications, the following four rainfall types were identified: 1) convective rainfall with an ML, 2) convective rainfall with no ML, 3) stratiform rainfall with an ML, and 4) stratiform rainfall with no ML. An ML was detected in 53.9% of the convective region in the rainfall system. Using the same definition, an ML was detected in 83.1% of the stratiform region. The ML in the convective region showed a marked decrease in ρ _hv coincident with an increase in Z _DR around the ambient 0°C level, as did that in the stratiform region. Melting aggregated snow was the likely cause of the ML signature in the convective region. The average height of the MLSM level in the convective region was 4.64 km, which is 0.46 km higher than that in the stratiform region (4.18 km) and 0.27 km higher than the ambient 0°C level (4.37 km).

Abstract

Seto et al. developed rain/no-rain classification (RNC) methods over land for the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI). In this study, the methods are modified for application to other microwave radiometers. The previous methods match TMI observations with TRMM precipitation radar (PR) observations, classify the TMI pixels into rain pixels and no-rain pixels, and then statistically summarize the observed brightness temperature at the no-rain pixels into a land surface brightness temperature database. In the modified methods, the probability distribution of brightness temperature under no-rain conditions is derived from unclassified TMI pixels without the use of PR. A test with the TMI shows that the modified (PR independent) methods are better than the RNC method developed for the Goddard profiling algorithm (GPROF; the standard algorithm for the TMI) while they are slightly poorer than corresponding previous (PR dependent) methods. M2d, one of the PR-independent methods, is applied to observations from the Advanced Microwave Scanning Radiometer for Earth Observing Satellite (AMSR-E), is evaluated for a matchup case with PR, and is evaluated for 1 yr with a rain gauge dataset in Japan. M2d is incorporated into a retrieval algorithm developed by the Global Satellite Mapping of Precipitation project to be applied for the AMSR-E. In latitudes above 30°N, the rain-rate retrieval is compared with a rain gauge dataset by the Global Precipitation Climatology Center. Without a snow mask, a large amount of false rainfall due to snow contamination occurs. Therefore, a simple snow mask using the 23.8-GHz channel is applied and the threshold of the mask is optimized. Between 30° and 60°N, the optimized snow mask forces the miss of an estimated 10% of the total rainfall.

Abstract

In developing the upcoming Global Precipitation Measurement (GPM) mission, a dual-frequency Ku–Ka-band radar system will be used to measure rainfall in such a fashion that the reflectivity ratio intrinsic to the measurement will be sensitive to underlying variations in the drop size distribution (DSD) of rain. This will enable improved techniques for retrieving rain rates, which are dependent upon several key properties of the DSD. This study examines this problem by considering a three-parameter set defined by liquid water content (W), DSD effective radius (r _e ), and DSD effective variance (υ _e ). Using radiative transfer simulations, this parameter set is shown to be related to a radar reflectivity factor and specific attenuation in such a fashion that details of the DSDs are immaterial under constant W, and thus effectively represent important variations in DSD that affect rain rate but with a minimal number of parameters. The analysis also examines the effectiveness of including some measure of mean Doppler fall velocity of raindrops ( υ ), given that the fundamental properties of a given precipitation situation are uniquely defined by a combination of a drop mass spectrum and drop vertical velocity spectrum. The results of this study have bearing on how future dual-frequency precipitation retrieval algorithms could be formulated to optimize the sensitivity to underlying DSD variability, a problem that has greatly upheld past progress in radar rain retrieval.

Abstract

The variation in drop size distribution (DSD) and the attenuation at higher frequencies are the two major impairments for quantitative rain-rate estimation. The sensitivity of rain-rate estimators (such as reflectivity factor Z, differential reflectivity Z _DR, and the specific differential propagation phase shift KDP), to the variations in DSD, raindrop shape parameter, and also to the variation in temperature, is examined at 13.8 GHz using the T-matrix procedure. It has been found that KDP is not only less sensitive to the variations in these physical quantities but is also linearly related to rain rate. The degree of deviation in KDP due to raindrop shape variation is almost comparable to that due to the DSD variations. The computed phase shift upon backscattering, δ, is a very large quantity at 13.8 GHz (e.g., δ = 24° for a raindrop with 6.5 mm diameter). It has been noticed that δ is almost comparable to KDP and even higher than KDP, especially at lower rain rates. Nevertheless, through proper utilization of the theoretically observed limits of δ, a scheme is presented that includes a suitable smoothing filter combined with averaging over space and time techniques for estimating the KDP from the profile of the differential propagation phase shift ϕ _DP. The KDP thus derived is found to be a better rain-rate estimator than reflectivity alone. The observed good agreement between the KDP estimated rain rates and those measured by the disdrometer indicates that KDP can be a better estimator at least for the uniform as well as intense rainfall (>40 mm h⁻¹) at Ku-band frequencies.

Abstract

The Global Precipitation Measurement (GPM) Dual-Frequency Precipitation Radar (DPR) algorithms consist of modules. This paper describes version 4 (V4) of GPM DPR level 2 (L2) classification (CSF) modules, which consist of two single-frequency (SF) modules—that is, Ku-only and Ka-only modules—and a dual-frequency (DF) module. Each CSF module detects bright band (BB) and classifies rain into three major types, that is, stratiform, convective, and other. The Ku-only and Ka-only CSF modules use algorithms that are similar to the Tropical Rainfall Measuring Mission (TRMM) rain type classification algorithm 2A23. The DF CSF module uses a new method called the measured dual-frequency ratio (DFRm) method for the rain type classification and the detection of BB. It is shown that the Ku-only CSF module and the DF CSF module produce almost indistinguishable rain type counts in a statistical sense. It is also shown that the DFRm method in the DF CSF module improves the detection of BB.