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We analyze the calibration stability of the 17-yr precipitation radar (PR) data on board the Tropical Rainfall Measuring Mission (TRMM) satellite to develop a precipitation climate record from the spaceborne precipitation radar data of the TRMM and following satellite missions. Since the PR measures the normalized radar cross section (NRCS) over the ocean surface, the temporal change in the NRCS whose variability is insensitive to the sea surface wind is regarded as the temporal change of the PR calibration. The temporal change of the PR calibration in TRMM, version 7, is found to be 0.19 dB decade−1 from 1998 to 2013. The calibration change is simply adjusted to evaluate the NRCS time series and the near-surface precipitation trend analysis within the latitudinal band between 35°S and 35°N. The NRCS time series at nadir and off-nadir are uncorrelated before the calibration adjustment, but they are correlated after the adjustment. The 0.19 dB decade−1 change of the PR calibration causes an overestimation of 0.08 mm day−1 decade−1 or 2.9% decade−1 for the linear trend of the near-surface precipitation. Even after the adjustment, agreement of the results among the satellite products depends on the analysis period. The temporal stability of the data quality is also important to evaluate the plausible trend analysis. The reprocessing of the PR data in TRMM, version 8 (or later), takes into account the temporal adjustment of the calibration change based upon the results of this study, which can provide more credible data for a long-term precipitation analysis. Significance Statement: The stability of long-term data is very important for climate research so that an account of temporal calibration changes in the sensor must be made. In this study, we investigate the calibration stability of the TRMM PR data and evaluate its impact on the precipitation trend analysis. The temporal change of the PR calibration is estimated to be 0.19 dB decade−1. Compensating for this change improves the consistency of precipitation trend analysis between the PR and other precipitation datasets. The reprocessed PR data provide more probable data for long-term precipitation analysis. [ABSTRACT FROM AUTHOR]

A new algorithm is proposed, which estimates two parameters of the particle size distribution (PSD) at each range bin from the global precipitation measurement’s (GPM’s) dual-frequency precipitation radar (DPR) data. The equation that expresses the relationship of the PSD parameters between adjacent range bins is derived. By including the attenuation effect within the bin in the discretized equation, the new algorithm alleviates the double-solution problem when attenuation within the bin is sufficiently large. The stability of the solutions to the equation depends on the value of the mean diameter $D_{m}$ and its gradient with respect to the range in the case of liquid precipitation. There is a critical diameter above which the backward processing of the equation provides a stable or moderately diverging solution, unlike the forward processing that often gives unstable solutions. To provide a set of initial conditions without using the surface reference technique (SRT) in the backward processing, an initialization method using the Hitschfeld–Bordan (HB) attenuation correction method is proposed and tested. The proposed algorithm may provide a tool for investigating the assumptions used in various algorithms. [ABSTRACT FROM AUTHOR]

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 R–Dm method. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Assessments on the performance of dual-frequency (13.6/35.5 GHz) Precipitation Radar (DPR) rain retrieval techniques are performed by means other than relying on the surface reference technique. A DPR inversion technique (DPR-IT) with an independent estimate of the differential attenuation, i.e., the difference of attenuation differences between two frequencies over a certain range, is introduced as an alternative to surface reference or iterative methods for resolving the path-integrated attenuation (PIA) information. Retrieval performance of the proposed method is tested to some vertical rain profiles synthesized with arbitrarily defined and disdrometer-measured raindrop-size distribution data. Retrievals of two other DPR-IT-type methods, namely the DPR-IT with sets of preselected surface PIAs at two frequencies from wide ranges and the DPR-IT iterative algorithm, are also considered for the analysis. The comparison of the simulated results obtained from these three methods is presented and discussed. Index Terms--Differential attenuation, dual-frequency rain retrieval, Global Precipitation Measurement (GPM).

Range profile data from the surface echo of the Precipitation Radar (PR) onboard the Tropical Rainfall Measuring Mission (TRMM) satellite enable the assessment of the nonuniformity of rainfall. The surface echo profile can be converted to a horizontal pattern of surface echo strength within the PR's footprint at off-nadir angles. Then, using the no-rain surface echo profile over ocean as a reference, the horizontal pattern of the path-integrated attenuation (PIA) can be estimated under moderate to heavy rainfall. Based on the horizontal pattern of the PIA, the nonuniform beam-filling parameter is estimated. However, this technique is applicable only to off-nadir angles and over ocean. Comparisons using ground-based radar data obtained simultaneously with TRMM data verify the effectiveness of this technique. Index Terms--Nonuniform beam filling (NUBF), surface echo, Tropical Rainfall Measuring Mission (TRMM).

The Tropical Rainfall Measuring Mission (TRMM) satellite changed its altitude from 350 to 402.5 km in August 2001. As a result, the level-1 algorithm for the new orbit of the Precipitation Radar (PR) onboard the TRMM has to correct the 'beam mismatch' resulting from the altitude change. Since the PR uses fixed transmission-reception timing, an altitude change of 50 km corresponds to a delay of return signals of 1 pulse repetition interval (PRI). This is not a serious problem if the angle bin of the next pulse is the same as the angle bin of the current pulse. Otherwise, return signals arrive at the PR when the antenna direction shifts to the next angle bin. This is caned a 'beam mismatch.' It affects one pulse sample out of 32 averaged pulse samples. In other words, one 'beam mismatch' pulse sample and 31 normal pulse samples are averaged at the onboard processor of the PR. A new algorithm was added to the PR's level-1 algorithm, 1B21, to eliminate this mismatch sample at the 402.5-km altitude. In this paper, the effect of beam mismatch is estimated for both rain echo and surface echo in terms of the received power and the incident angle dependency. The basic function of the beam mismatch correction algorithm is to estimate the received power of the mismatched pulse. Theoretically, the effective round-trip antenna pattern of a mismatched pulse has a peak right in the middle of the transmission and reception directions with a gain reduction of 6 dB. The new 1B21 algorithm uses the average of the received power of successive angle bins with a 6-dB gain reduction as the power from the mismatched pulse. The effectiveness of the correction algorithm was evaluated using high angular resolution data obtained during external calibration observations and the statistics of the normalized radar cross section of the earth's surface ([[sigma].sup.0]), which is thought to be unchanged. The estimated error was less than 0.2 dB for the rain echo, and a large error of up to 0.5 dB was found at the boundary of the surface based on the error estimation using high angular resolution data. The difference in [[sigma].sup.0] and its angle dependency is explained using a simple surface model. The model results indicate the correction error reaches up to 0.8 dB at the skirts of the surface echo. Index Terms--Algorithm, orbit boost, Tropical Rainfall Measuring Mission (TRMM).

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.sub.e]), and DSD effective variance ([v.sub.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 ([bar.v]), 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.

Pulse patterns are designed by adopting variable pulse repetition frequency (VPRF) for space missions involving beam scans in the cross-track direction, especially intended for the Global Precipitation Measurement Project (GPM). To cope with large variance in range from a satellite, which is caused by the beam swing and the earth oblateness, a systematic algorithm is proposed, increasing sampling rates. Index Terms--Global Precipitation Measurement Project (GPM), rain radar, spaceborne radar, variable pulse repetition frequency.

The Global Precipitation Measurement (GPM) Dual-frequency Precipitation Radar (DPR) has operated in full scan (FS) mode in both the Ku-band and Ka-band since May 2018. This FS mode can enable about 245 km full swath dual-frequency processing for the first time, whereas previous algorithms enabled dual-frequency processing in the narrower inner swath, having a width of approximately 125 km. This paper describes the classification (CSF) module in newly developed DPR level 2 V06X experimental algorithms corresponding to the FS mode. The CSF module classifies precipitation as three major types, stratiform, convective, and other, and provides bright-band (BB) information. One-month statistics show that a significant jump occurs in the Ka-band precipitation type counts at the edges of the inner swath due to the different sensitivity of Ka-band radar in Ka-band Matched Scan (Ka-MS) mode compared with that in Ka-band High Sensitivity (Ka-HS) mode. However, precipitation type counts indicate that dual-frequency processing works well not only in the inner swath but also in the outer swath. Statistics on BB counts show a significant improvement in BB detection, especially in the outer swath, when dual-frequency processing is performed. In addition, the V06X Ku-band algorithm solves two problems related to the CSF module: (a) appearance of a very large near-surface precipitation rate of stratiform precipitation reclassified by the slope method and (b) a rare case of misjudging BB peak as an upper part of surface echo. The data structures of GPM DPR algorithms were drastically changed in V06X. The new data structures introduced in V06X will be used in V07A and later. In this regard, the V06X CSF module outlined in this paper is a prototype of future versions of each CSF algorithm. [ABSTRACT FROM AUTHOR]

For the past two decades, precipitation radars (PR) onboard low‐orbiting satellites such as Tropical Rainfall Measuring Mission (TRMM) have provided invaluable insight into global precipitation variability and led to advancements in numerical weather prediction through data assimilation. Building upon this success, planning has begun on the next generation of satellite‐based PR instruments, with the consideration for a future geostationary‐based PR (GPR), bringing the advantage of higher observation frequency over previous and current PR satellites. Following the successful demonstration by a recent study to test the feasibility of a GPR to obtain three‐dimensional precipitation data, this study takes the first step to investigate the potential usefulness of GPR observations for numerical weather prediction by performing a perfect model observing system simulation experiment (OSSE) for a West Pacific tropical cyclone (TC). Data assimilation experiments are performed assimilating reflectivity observations obtained for a range of beam sampling spans, following a previous finding that oversampling improves observation quality. Results showed observations obtained with finer sampling spans of 5 km and 10 km were able to better capture key tropical cyclone features in analyses, including the eye, heavy rainfall associated with the eyewall, and outer convective rainbands. Results also showed that through increased moistening and upward velocity within the inner storm environment, assimilation of observations drove an intensification of the secondary circulation and deepening of the storm, leading to an improvement in TC intensity error. Intensity forecasts were found improved for assimilation of observations obtained with increasingly finer beam sampling span, suggesting an important benefit of oversampling. Plain Language Summary: In a recent study, the feasibility of a future precipitation radar based onboard a geostationary satellite (GPR) that could obtain three‐dimensional precipitation measurements was successfully tested. In this study, we take the first step to investigate whether reflectivity observations can be used to improve analyses and forecasts of global weather systems. We perform data assimilation experiments that use simulated GPR observations for a West Pacific tropical cyclone, with observations obtained with varying radar beam sampling spans to generate observation oversampling, following a previous finding that this improves observation quality. Results found that key convective features of the tropical cyclone (TC), including the eye, eyewall structure, and outer rainbands, were all better captured in simulations assimilating observations obtained with finer beam sampling spans, with 5 km sampling providing best results. Observations were also found to have a positive impact on TC intensity in both model analyses and forecasts, with forecast errors for minimum sea level pressure improved at all lead times up to 18 h. TC intensity forecasts were also improved with increasingly finer beam span, suggesting an important potential benefit of oversampling for TC prediction. Key Points: Reflectivity observations from a geostationary precipitation radar improved representation of convective features for a tropical cycloneOversampling with finer beam sampling span improved tropical cyclone intensity errors in analyses and forecastsOversampling improved precipitation and maximum surface wind intensity in forecasts [ABSTRACT FROM AUTHOR]

An assumption related to clouds is one of uncertain factors in precipitation retrievals by the Dual-Frequency Precipitation Radar (DPR) on board the Global Precipitation Measurement (GPM) Core Observatory. While an attenuation due to cloud ice is negligibly small for Ku and Ka bands, attenuation by cloud liquid water is larger in the Ka band and estimating precipitation intensity with high accuracy from Ka-band observations can require developing a method to estimate the attenuation due to cloud liquid water content (CLWC). This paper describes a CLWC database used in the DPR level-2 algorithm for the GPM V06A product. In the algorithm, the CLWC value is assumed using the database with inputs of precipitation-related variables, temperature, and geolocation information. A calculation of the database was made using the 3.5-km-mesh global atmospheric simulation derived from the Nonhydrostatic Icosahedral Atmospheric Model (NICAM) global cloud-system-resolving model. Impacts of current CLWC assumptions for surface precipitation estimates were evaluated by comparisons of precipitation retrieval results between default values and 0 mg m−3 of the CLWC. The impacts were quantified by the normalized mean absolute difference (NMAD) and the NMAD values showed 2.3% for the Ku, 9.9% for the Ka, and 6.5% for the dual-frequency algorithms in global averages, while they were larger in the tropics than in high latitudes. Effects of the precipitation estimates from the CLWC assumption were examined further in terms of retrieval processes affected by the CLWC assumption. This study emphasizes the CLWC assumption provided more effects on the precipitation estimates through estimating path-integrated attenuation due to rain. [ABSTRACT FROM AUTHOR]

Calibration consistency between Ku-band radars flown on the Tropical Rainfall Measuring Mission’s (TRMM’s) precipitation radar (PR) and the global precipitation measurement (GPM) mission’s dual-frequency PR (DPR) can be attained by the use of the normalized radar cross section (NRCS) or $\sigma ^{0}$ over the oceans. With the use of the sea surface echo (SSE) data obtained from the spaceborne PRs, this article aims to estimate the radar parameters of pulsewidth and beamwidth and to evaluate the bias in the NRCS estimates caused by the discrete range sampling. Since the SSE shape is closely related to the received pulsewidth and the two-way cross-track beamwidth, those parameters are individually estimated from the SSE shapes. The SSE shapes are also used to evaluate the impact of the discrete range sampling on the NRCS statistics. The pulsewidth and beamwidth estimated from the SSEs compare well with the level-1 values and accurately reflect changes in the configuration of the radars. The NRCS statistics in GPM version 06 show that the calibration consistency between GPM KuPR and TRMM PR is evaluated within the range of −0.39 to +0.03 dB (−0.48 to +0.11 dB) with (without) the peak correction. [ABSTRACT FROM AUTHOR]

The orbit of the tropical rainfall measuring mission (TRMM) satellite was boosted from 350 to 402.5 km in August 2001 to extend its lifetime by conserving fuel. Since the timing between transmission and reception by the precipitation radar (PR) onboard the TRMM satellite was a fixed constant for measurement from an original altitude of 350 km, the PR encountered a mismatch between the transmitting and receiving beams after the TRMM orbit boost. Although the PR algorithm in TRMM Version 7 employs a correction for the beam mismatch, its error remains as an underestimation of the precipitation estimates near surface in the second half of the swath. This paper aims to mitigate the beam-mismatch correction error in Version 7. The beam-mismatch correction needs to estimate the radar echo that would be measured in the virtual intermediate beam between the beam in question and the previous adjacent beam. The beam-mismatch correction developed in this paper assumes that the surface and precipitation echoes change linearly in the horizontal direction in parallel to the surface between the two beams. The new correction is tested with observational data, indicating that the method improves the accuracy of the correction at off-nadir angles. Statistics of the surface normalized radar cross sections and the bright band peak intensities at off-nadir angles are improved using the method. The asymmetric bias of the precipitation estimates with respect to the scan angle in Version 7 is mitigated by 95.9% over ocean and 72.5% over land with the new correction. [ABSTRACT FROM AUTHOR]

Spaceborne precipitation radars, such as the Tropical Rainfall Measuring Mission (TRMM) and the Global Precipitation Measurement (GPM) Core Observatory, have been important platforms to provide a direct measurement of three-dimensional precipitation structure globally. Building upon the success of TRMM and GPM Core Observatory, the Japan Aerospace Exploration Agency (JAXA) is currently surveying the feasibility of a potential satellite mission equipped with a precipitation radar on a geostationary orbit. The quasi-continuous observation realized by the geostationary satellite radar would offer a new insight into meteorology and would advance numerical weather prediction (NWP) through their effective use by data assimilation. Although the radar would be beneficial, the radar on the geostationary orbit measures precipitation obliquely at off-nadir points. In addition, the observing resolution will be several times larger than those on board TRMM and GPM Core Observatory due to the limited antenna size that we could deliver. The tilted sampling volume and the coarse resolution would result in more contamination from surface clutter. To investigate the impact of these limitations and to explore the potential usefulness of the geostationary satellite radar, this study simulates the observation data for a typhoon case using an NWP model and a radar simulator. The results demonstrate that it would be possible to obtain three-dimensional precipitation data. However, the quality of the observation depends on the beam width, the beam sampling span, and the position of precipitation systems. With a wide beam width and a coarse beam span, the radar cannot observe weak precipitation at low altitudes due to surface clutter. The limitation can be mitigated by oversampling (i.e., a wide beam width and a fine sampling span). With a narrow beam width and a fine beam sampling span, the surface clutter interference is confined to the surface level. When the precipitation system is located far from the nadir, the precipitation signal is obtained only for strong precipitation. [ABSTRACT FROM AUTHOR]

Heavy ice precipitation (HIP) flags in the products of dual‐frequency precipitation radar (DPR) on board the Global Precipitation Measurement (GPM) core satellite indicate the existence of large ice particles. In this study, we analyzed the distribution of a HIP band detected along the warm front of an oceanic extratropical cyclone. The HIP band was more than 125 km long and probably exceeded the 245‐km range of the Ku‐band precipitation radar. We found two zones with distinct microphysical processes in the HIP band. Ice particles near the echo top height showed little change in their median size with height, where frontogenetical updraft was maximum. This suggests that particles are generated and grown in this zone by the updrafts. In the zone below, the particle sizes increased as the height decreased, implying particles aggregate as they fall. Plain Language Summary: Bands of heavy snowfall are often reported in the presence of extratropical cyclones over land. However, observations of bands of heavy snowfall over the ocean are limited. In this study, we detected a band of heavy snowfall occurring over the ocean using satellite‐borne precipitation radar for the first time. This signal had a narrow width of 10–20 km and a length that was likely greater than the 245‐km swath of the Ku‐band radar. We examined the change in precipitation echoes with height for the snowfall to understand how ice particles grow and subsequently result in heavy snowfall. The analysis suggested that in the upper layer of the heavy snowfall band, ice particles are produced and grown by an upward flow, and that in the middle layer, they collide with other ice crystals, resulting in larger crystals, which subsequently fall. Further statistical analysis of similar signals could reveal the structure and driving mechanisms for heavy snowfall over the land and ocean in future studies. Key Points: We detected a heavy ice precipitation (HIP) band along the warm front of an oceanic cyclone observed by GPM/DPRIce particles are grown by updraft near the echo top height of the HIP band and then aggregate in the zone below [ABSTRACT FROM AUTHOR]

A phased-array weather radar (PAWR) with fast scanning and wide elevation coverage capabilities has been developed. The PAWR transmits elevationally broad beams by feeding power to a limited number of its antenna elements, and receives signals reflected by precipitation media using all 128 antenna elements, each of which is connected to an analog-to-digital converter (ADC). After ADC sampling, digital processing of beamforming is applied to the received signals to accomplish receptions simultaneously over multiple angles. The PAWR can, thereby, make observations at 100-m range increments out to 60 km at 1° azimuth angle intervals over a range of 360° and at about 1° elevation-angle intervals from 0°–90° within the short time of 30 s. Reflectivity factors measured by the PAWR were compared with those from a collocated C-band radar, and were found to have a bias of 0.53 dB and a standard deviation of 3.68 dB, which indicates sufficient accuracy for observing precipitation. Furthermore, in a sample observation of convective rain, the PAWR detected a precipitation core 9 min before it reached the ground by its 30-s fast scanning and wide elevation coverage. It, thereby, became evident that the fast scanning and wide elevation coverage capabilities of the PAWR give earlier detection and a higher detection probability, which will enable earlier and more accurate warnings of severe weather phenomena and a better potential of mitigating the damage. [ABSTRACT FROM AUTHOR]

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 2108C is implemented in version 5 of the DPR products. In the inner swath of DPR measurements in which both Kuand Ka-band radar echoes are available, the measured dual-frequency ratio (DFRm) 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. [ABSTRACT FROM AUTHOR]