Measurement Dual-frequency Precipitation Radar Research Articles

The NASA‐JAXA Global Precipitation Measurement mission – part II: New frontiers in precipitation science

The <scp>NASA‐JAXA</scp> Global Precipitation Measurement mission – part <scp>II</scp>: New frontiers in precipitation science

Conversion of the Vertical Profile of Reflectivity From Ku-Band to C-Band Based on the Drop Size Distribution Measurements of the Global Precipitation Measurement Mission Dual-Frequency Precipitation Radar

The ground-based radar quantitative precipitation estimation (QPE) faces various challenges including the overestimation caused by the bright band (BB) in the stratiform region and the underestimation in mountainous areas when the terrain-enhanced precipitation occurs at the levels below ground-based radar measurements. The vertical precipitation structure provided by spaceborne radars, i.e., the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) and the Global Precipitation Measurement mission (GPM) Dual-frequency PR (DPR), is valuable for mitigating the above problems. Since the spaceborne radars and ground-based radars usually operate in different frequencies, e.g., the TRMM PR and the KuPR of GPM DPR work in Ku-band (13.8 and 13.6 GHz, respectively) and the ground-based radars in western China work in C-band (5.4 GHz), the reflectivity conversion from Ku-band to C-band is necessary before the vertical profile of reflectivity (VPR) measured by spaceborne radars can be utilized to improve the ground-based radar QPE in western China. This study presents a conversion method using GPM DPR measurements, i.e., the drop size distribution (DSD) for different precipitation types (the stratiform with/without BB and the convective cases) and particle phases (the solid, melting, and liquid). Using the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${T}$ </tex-math></inline-formula> -matrix method, the reflectivity difference between Ku-band and C-band is found and the Ku-band to C-band conversion relations are derived with the linear regression. These conversion relations have been validated by matching and comparing the converted C-band reflectivity with the C-band ground-based radar measurements. The results demonstrate the effectiveness and reliability of the conversion. This method can be extended for the reflectivity conversion in other frequencies and can facilitate the incorporation of reflectivity measurements from various instruments.

Monitoring of Inland Waters by Dual-Frequency Precipitation Radar: First Results

Permanent monitoring of inland waters in cold regions with long-time snow and ice covers is very important for the population safety. Modern spaceborne radars can significantly extend the capabilities of the terrestrial hydrological network, since they enable one to perform measurements over large areas. In 2014, the Japan Aerospace Exploration Agency (JAXA) launched the spaceborne dual-frequency precipitation radar (DPR). The main objective of the mission is the precipitation measurement. However, the radar cross section (RCS) measured at the maximal range contains information about the scattering surface. For the first time, DPR measurements over the Russian territory were processed. The sources of in situ data were hydrological stations. The Gorky reservoir and the Volga River were selected for sensing small-area inland waters. The data processing confirmed the possibility of detecting inland waters whose area is significantly smaller than the radar footprint. A ground-to-water ratio was introduced to estimate the open water area inside the footprint. Processing of the DPR data obtained for the Lake Baikal enabled us to calculate the dependence of the RCS on the incidence angle and propose a novel algorithm for separating open water and ice cover. The Moksha River was selected as a wetland with many small rivers. The data processing has shown that the spring change of inland waters and soil can be observed in the DPR image.

Global Precipitation Measuring Dual-Frequency Precipitation Radar Observations of Hailstorm Vertical Structure: Current Capabilities and Drawbacks

AbstractA statistical analysis of simultaneous observations of more than 800 hailstorms over the continental United States performed by the Global Precipitation Measurement (GPM) Dual-Frequency Precipitation Radar (DPR) and the ground-based Next Generation Weather Radar (NEXRAD) network has been carried out. Several distinctive features of DPR measurements of hail-bearing columns, potentially exploitable by hydrometeor classification algorithms, are identified. In particular, the height and the strength of the Ka-band reflectivity peak show a strong relationship with the hail shaft area within the instrument field of view (FOV). Signatures of multiple scattering (MS) at the Ka band are observed for a range of rimed particles, including but not exclusively for hail. MS amplifies uncertainty in the effective Ka reflectivity estimate and has a negative impact on the accuracy of dual-frequency rainfall retrievals at the ground. The hydrometeor composition of convective cells presents a large inhomogeneity within the DPR FOV. Strong nonuniform beamfilling (NUBF) introduces large ambiguities in the attenuation correction at Ku and Ka bands, which additionally hamper quantitative retrievals. The effective detection of profiles affected by MS is a very challenging task, since the inhomogeneity within the DPR FOV may result in measurements that look remarkably like MS signatures. The shape of the DPR reflectivity profiles is the result of the complex interplay between the scattering properties of the different hydrometeors, NUBF, and MS effects, which significantly reduces the ability of the DPR system to detect hail at the ground.

Detection of Intense Ice Precipitation with GPM/DPR

AbstractDetection 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.

A Comparison between the GPM Dual-Frequency Precipitation Radar and Ground-Based Radar Precipitation Rate Estimates in the Swiss Alps and Plateau

Abstract The Global Precipitation Measurement (GPM) mission Dual-Frequency Precipitation Radar (DPR) provides a unique set of three-dimensional radar precipitation estimates across much of the globe. Both terrain and climatic conditions can have a strong influence on the reliability of these estimates. Switzerland provides an ideal testbed to evaluate the performance of the DPR in complex terrain: it consists of a mixture of very complex terrain (the Alps) and the far flatter Swiss Plateau. It is also well instrumented, covered with a dense gauge network as well as a network of four dual-polarization C-band weather radars, with the same instrument network used in both the Plateau and the Alps. Here an evaluation of the GPM DPR rainfall rate products against the MeteoSwiss radar rainfall rate product for the first two years of the GPM DPR’s operation is presented. Errors in both detection and estimation are considered, broken down by terrain complexity, season, precipitation phase, precipitation type, and precipitation rate. Errors are considered both integrated across the entire domain and spatially, and consistent underestimation of precipitation by GPM is found. This rises to −51% in complex terrain in the winter, primarily due to the predominance of DPR measurements wholly in the solid phase, where problems are caused by lower reflectivities. The smaller vertical extent of precipitation in winter is also likely a cause. Both detection and estimation performance are found to be significantly better in summer than in winter, in liquid than in solid precipitation, and in flatter terrain than in complex terrain.

Improvements in Detection of Light Precipitation with the Global Precipitation Measurement Dual-Frequency Precipitation Radar (GPM DPR)

AbstractThis paper demonstrates the impact of the enhancement in detectability by the dual-frequency precipitation radar (DPR) on board the Global Precipitation Measurement (GPM) core observatory. By setting two minimum detectable reflectivities—12 and 18 dBZ—artificially to 6 months of GPM DPR measurements, the precipitation occurrence and volume increase by ~21.1% and ~1.9%, respectively, between 40°S and 40°N.GPM DPR is found to be able to detect light precipitation, which mainly consists of two distinct types. One type is shallow precipitation, which is most significant for convective precipitation over eastern parts of subtropical oceans, where deep convection is typically suppressed. The other type is probably associated with lower parts of anvil clouds associated with organized precipitation systems.While these echoes have lower reflectivities than the official value of the minimum detectable reflectivity, they are found to mostly consist of true precipitation signals, suggesting that the official value may be too conservative for some sort of meteorological analyses. These results are expected to further the understanding of both global energy and water budgets and the diabatic heating distribution.

A Consistent Treatment of Microwave Emissivity and Radar Backscatter for Retrieval of Precipitation over Water Surfaces.

The Global Precipitation Measurement satellite's Microwave Imager (GMI) and Dual-frequency Precipitation Radar (DPR) are designed to provide the most accurate instantaneous precipitation estimates currently available from space. The GPM Combined Algorithm (CORRA) plays a key role in this process by retrieving precipitation profiles that are consistent with GMI and DPR measurements; therefore it is desirable that the forward models in CORRA use the same geophysical input parameters. This study explores the feasibility of using internally consistent emissivity and surface backscatter cross section (σ 0) models for water surfaces in CORRA. An empirical model for DPR Ku and Ka σ 0 as a function of 10m wind speed and incidence angle is derived from GMI-only wind retrievals under clear conditions. This allows for the σ 0 measurements, which are also influenced by path-integrated attenuation (PIA) from precipitation, to be used as input to CORRA and for wind speed to be retrieved as output. Comparisons to buoy data give a wind rmse of 3.7 m/s for Ku+GMI and 3.2 m/s for Ku+Ka+GMI retrievals under precipitation (compared to 1.3 m/s for clear-sky GMI-only), and there is a reduction in bias from the GANAL background data (-10%) to the Ku+GMI (-3%) and Ku+Ka+GMI (-5%) retrievals. Ku+GMI retrievals of precipitation increase slightly in light (< 1 mm/hr) and decrease in moderate to heavy precipitation (> 1mm/hr). The Ku+Ka+GMI retrievals, being additionally constrained by the Ka reflectivity, increase only slightly in moderate and heavy precipitation at low wind speeds (< 5 m/s) relative to retrievals using the surface reference estimate of PIA as input.

An Initial Assessment of the Surface Reference Technique Applied to Data from the Dual-Frequency Precipitation Radar (DPR) on the GPM Satellite

AbstractIt has long been recognized that path-integrated attenuation (PIA) can be used to improve precipitation estimates from high-frequency weather radar data. One approach that provides an estimate of this quantity from airborne or spaceborne radar data is the surface reference technique (SRT), which uses measurements of the surface cross section in the presence and absence of precipitation. Measurements from the dual-frequency precipitation radar (DPR) on the Global Precipitation Measurement (GPM) satellite afford the first opportunity to test the method for spaceborne radar data at Ka band as well as for the Ku-band–Ka-band combination.The study begins by reviewing the basis of the single- and dual-frequency SRT. As the performance of the method is closely tied to the behavior of the normalized radar cross section (NRCS or σ0) of the surface, the statistics of σ0 derived from DPR measurements are given as a function of incidence angle and frequency for ocean and land backgrounds over a 1-month period. Several independent estimates of the PIA, formed by means of different surface reference datasets, can be used to test the consistency of the method since, in the absence of error, the estimates should be identical. Along with theoretical considerations, the comparisons provide an initial assessment of the performance of the single- and dual-frequency SRT for the DPR. The study finds that the dual-frequency SRT can provide improvement in the accuracy of path attenuation estimates relative to the single-frequency method, particularly at Ku band.

The Basic Performance of a Precipitation Retrieval Algorithm for the Global Precipitation Measurement Mission's Single/Dual-Frequency Radar Measurements

A precipitation retrieval algorithm is proposed for the dual-frequency precipitation radar (DPR) on the core satellite of the Global Precipitation Measurement mission. The proposed algorithm is called the HB-DFR algorithm, in reference to the combination of Histchfeld-Bordan's attenuation correction method (HB method) and the dual-frequency ratio (DFR) method. The HB-DFR algorithm is tested with a synthetic DPR dataset produced from the standard product of the PR on the Tropical Rainfall Measuring Mission. Precipitation rates estimated by the HB-DFR algorithm at the lowest (near-surface) range bin are evaluated by comparing them with the corresponding values calculated from the drop size distribution of the synthetic dataset. For “light precipitation” (below 1 mm h <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-1</sup> ), precipitation rates are slightly underestimated because of the multiple-solution problem in the DFR method. For “heavy precipitation” (above 10 mm h <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-1</sup> ), the precipitation rates are severely underestimated, and the biases become large when thick liquid phase precipitation occurs. For “medium precipitation” (between 1 and 10 mm h <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-1</sup> ), the estimates are satisfactory. As almost 50 % of precipitation falls as medium precipitation in the synthetic dataset, this result validates the usefulness of DPR measurements and the HB-DFR algorithm. Because the HB-DFR algorithm is a forward retrieval algorithm, it has multiple solutions and produces larger errors when applied to lower (farther) range bins. Unlike other dual-frequency algorithms, the HB-DFR algorithm can be easily switched to a single-frequency algorithm at a range bin where a measurement at one of the two frequencies is not available.

Applicability of the Iterative Backward Retrieval Method for the GPM Dual-Frequency Precipitation Radar

The Dual-frequency Precipitation Radar (DPR) on the core satellite of the Global Precipitation Measurement mission will measure the radar reflectivity factor in the Ku- and Ka-bands. A rain-rate retrieval algorithm that does not require a surface reference was developed (called the MA04 method). However, MA04 cannot give the true solution in some cases of heavy rainfall. MA04 is a simplified version of the iterative backward retrieval method (IBRM), and the IBRM is equivalent to the forward retrieval method with a constraint. The purpose of this study is to clarify the essential conditions under which the IBRM and MA04 can give the true solution (the conditions are referred to as “the applicability” as in the title). For the purpose, DPR measurements are simulated under simplified assumptions. The applicability of the IBRM and MA04 is closely related to the magnitude of internal attenuation. The upper limit of rain rate for which the IBRM can obtain a true solution is 10 to 20 mm · h <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-1</sup> if the internal attenuation occurs between the top and middle of the target range bin and the vertical resolution is 0.25 km. The upper limit of rain rate for which MA04 can obtain a true solution is dependent on the number of range bins, and it is 24 to 36 mm · h <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-1</sup> in the case of n = 12. MA04 can apply a wider range of rainfall than the IBRM because MA04 tends to select the solution with the smallest attenuation among possible solutions.