Spaceborne Precipitation Radar Research Articles

Development of a Precipitation Climate Record from Spaceborne Precipitation Radar Data. Part II: Temporal Adjustment of the Calibration Change Using the Ocean Normalized Radar Cross Section

Abstract 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.

Reconstruction of 3D DPR Observations Using GMI Radiances

AbstractThree‐dimensional global precipitation observation is crucial for understanding climate and weather dynamics. While spaceborne precipitation radars provide precise but limited observations, passive microwave imagers are available much more frequently. In this study, we propose a deep learning approach to reconstruct active radar observations using passive microwave radiances. We introduce the Hybrid Deep Neural Network (HDNN) model, which utilizes reflectivity profiles from the Dual‐frequency Precipitation Radar (DPR) onboard the Global Precipitation Measurement (GPM) Core Observatory Satellite as the “target” and combines radiances from the GPM Microwave Imager (GMI) with supplementary reanalysis data to serve as the “features.” Results underscore the HDNN's exemplary performance, with a root mean square error below 4 dBZ across all altitude levels, and a consistent accuracy across different precipitation types. Its efficacy is further illustrated when applied to typhoon cases of Haishen and Khanun, emerging as a superior tool for capturing 3D structures of expansive precipitation systems.

Vertical structure of tropical cyclone precipitation over the North Indian Ocean: a spaceborne precipitation radar perspective

ABSTRACT Spaceborne precipitation radars provide an unprecedented opportunity to study three-dimensional structure of precipitation, particularly over the open ocean where in-situ observations are rather meagre. In this study, instantaneous surface precipitation characteristics and their vertical structures during the tropical cyclones (TCs) over the North Indian Ocean (NIO) between 2014 and 2022 have been analysed using the dual-frequency precipitation radar onboard the Global Precipitation Measurement Core Observatory. Although stratiform precipitation accounts for more than 70% of total TC surface precipitation area, convective precipitation contributes about half of the total TC surface precipitation amount over the NIO. About 90% of stratiform TC precipitation area yields surface precipitation of less than 10 mm/hour. The vertical structures of stratiform and convective TC precipitation vary with surface precipitation intensity and have nearly similar characteristics over both basins of the NIO. This preliminary quantitative TC precipitation analysis would be useful for better understanding of precipitation processes during TCs over the NIO, and for further advancement in numerical models through improved parameterization schemes for TC precipitation forecasting.

Validation of Spaceborne Precipitation Radar Data by Rain Gauges and Disdrometers over the Complex Topography of the Northeastern Indian Subcontinent

Validation of Spaceborne Precipitation Radar Data by Rain Gauges and Disdrometers over the Complex Topography of the Northeastern Indian Subcontinent

Towards development of a storm index using satellite observation for near real‐time monitoring of thunderstorm over India

This study focuses on the development of a storm index by integrating Outgoing Longwave Radiation (OLR) from current operational Indian Satellites INSAT3D/3DR and reflectivity from space borne Precipitation Radar (PR) onboard Tropical Rainfall Measuring Mission (TRMM) for near real-time monitoring of thunderstorms. Using a reflectivity threshold for the detection of thunderstorms, an OLR threshold was identified from the relationship between OLR and reflectivity. A storm index has been defined as the OLR threshold divided by actual OLR values. The derived index can be very helpful for operational forecasts of intense and widespread thunderstorms over India and its neighborhood.

Convective Couplings with Equatorial Rossby Waves and Equatorial Kelvin Waves. Part II: Coupled Precipitation Characteristics

Abstract Detailed precipitation characteristics coupled with equatorial Rossby and Kelvin waves are investigated. We prepare a rainfall event dataset using the Tropical Rainfall Measurement Mission (TRMM) Precipitation Radar (PR) level 2 data. Utilizing three indices, area size, maximum echo-top height, and stratiform precipitation ratio, rainfall events are classified into mesoscale convective system (MCS), deep, congestus, and shallow convective events, and “other” type. We perform composite analyses based on the wave phase defined in Part I. Precipitation amount in Rossby waves is in phase with column water vapor (CWV) anomalies and is mainly contributed by MCSs, which are simultaneously activated with deep convection. The large CWV can support deep development and organization of convection. Shallow and congestus convective events indicate their peaks just before the active phase on 10°N or in the later part of the convectively suppressed phase on the equator. A five-step evolution is shown in Kelvin waves. In the first stage, shallow convective events are triggered by high SST, followed by a dominance of congestus convective events. Then, in the developing stage, deep convective events become dominant. In the mature stage, heavy precipitation is contributed by MCSs, and mostly stratiform rain is maximized at later stages. Kelvin waves indicate relatively weak connection to CWV fluctuation. Although contrasted evolutions are indicated, large contributions by MCSs to precipitation amount are common among the two coupled waves. This is considered to result in the commonality of the equivalent depths with their top-heavy heating. Significance Statement A coupling mechanism between equatorial waves and convective activity is a key issue in the tropical meteorology. While many previous idealized studies suggested some instability mechanisms, detailed precipitation characteristics is not enough investigated. We prepare rainfall-event dataset observed from a spaceborne Precipitation Radar on board the TRMM satellite to quantify detailed precipitation characteristics statistically and compare equatorial Rossby waves and equatorial Kelvin waves. We found that organized convective systems and deep convection are simultaneously activated in the Rossby waves and a clear transition of convective activity is shown in the Kelvin waves. These characteristics highly correspond to waves’ synoptic-scale structures. Our observational results of detailed evolutions of rainfall events will improve understanding of coupling processes.

Simple Derivation of the Nonuniform Beam Filling (NUBF) Bias Formula in Spaceborne Doppler Radar Measurements

The nonuniform beam filling (NUBF) bias in Doppler velocity measurements from a spaceborne precipitation radar is investigated. A simple derivation of the already-known formula that relates the bias to the along-track gradient of measured radar reflectivity in dBZ is shown. From the formula, the uncertainty of bias correction due to discretization is discussed. The error is shown to be proportional to the square of the spacing for discretization, and is related to the third moment of the distribution of the radar reflectivity convolved with the antenna pattern. The effectiveness of averaging is also shown from a simulation.

How Many Types of Severe Hailstorm Environments Are There Globally?

AbstractUnderstanding how severe hailstorms will respond to climate change remains challenging partially due to an incomplete understanding of how different environments produce hail. Leveraging a record of 14,297 global potential severe hailstorms detected by spaceborne precipitation radar, here for the first time, we explore global differences in the five distinct environmental types producing these storms. Two are found over tropical plains and hills with high convective instability, high‐moderate moisture, and low vertical wind shear (VWS). The third type are supercell environments characterized by strong VWS, with moderate instability and moisture, commonly occurring over mid‐latitude plains. Higher latitude plains and elevated terrain reflect the final two, with moderate VWS and low melting height, instability, and moisture. The variety of hailstorm environment types illustrates distinctions in the associated convective mode and embryo type, highlighting that multiple environment types pose challenges for modeling present frequency and anticipating the response of hail to climate change.

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

Estimates of Spaceborne Precipitation Radar Pulsewidth and Beamwidth Using Sea Surface Echo Data

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 σ <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</sup> 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.

A Feasibility Study on Wide Swath Observation by Spaceborne Precipitation Radar

A feasibility study on wide swath observation assuming future spaceborne precipitation radar was demonstrated using data obtained from a wide swath observation experiment conducted in September 2017 by using the dual-frequency precipitation radar onboard the global precipitation measurement core observatory. In this experiment, scan angles of the Ku-band precipitation radar (KuPR) and Ka-band precipitation radar (KaPR) were experimentally changed to observe from nadir to about +34°. While the result showed that the precipitation echo could be obtained at wider scan angles, the occurrence of sidelobe and grating lobe clutters not seen in a normal scan were simultaneously observed. The mainlobe clutter height of KuPR increased linearly along the incident angle, and 0.5 mm/h precipitation may be masked up to 4 km over land at the angle of +34°. Besides, the grating lobe clutter clearly occurred in KuPR when the ground surface of the grating lobe direction was land or sea ice. The maximum scan angle without the grating lobe contamination was +23.43°, approximately corresponding to 355 km swath width with the orbit altitude of 407 km. For KaPR, the grating lobe contamination was not significant and the mainlobe clutter height peaked at the scan angle of around 26°, and then tended to decrease at larger scan angles. Therefore, precipitation at the lower altitude may have a chance to be detected even at larger scan angles, while weaker surface echoes at larger scan angles may need new techniques to estimate precipitation for the KaPR.

Comparison of GPM DPR and Airborne Radar Observations in OLYMPEX

Previous work has shown that the relatively large resolution volume of spaceborne precipitation radars can affect precipitation measurements in several ways. During the Olympic Mountains Experiment (OLYMPEX), Ku- and Ka-band airborne radar measurements of precipitation were obtained during two Global Precipitation Measurement (GPM) overpasses, one case over land and one case over ocean. The authors compare the GPM-measured radar quantities with the same quantities inferred from the higher spatial resolution airborne radar data. Differences include smaller maximum reflectivity and path attenuation and more significant surface clutter in mountainous areas for GPM.

Vegetation Mapping by Using GPM/DPR over the Mongolian Land

Mongolian steppe is one of the largest and important ecosystems. The degradation of grassland and the expansion of desert are occurring due to drought and desertification processes. We attempted monitoring of the broad-scale vegetation in Mongolia by a space-borne precipitation radar, which may complement typical approaches of vegetation monitoring (such as NDVI). We utilized the Global Precipitation Mission’s (GPM) dual-frequency precipitation radar (DPR). We characterized backscatter (σ0) of GPM/DPR’s two microwave bands (Ku and Ka) with respect to the dominant vegetation zones (forest, grassland, desert). Both Ku and Ka radars’ σ0 values were investigated for incidence angle dependency and the seasonal variation. As a result, the use of multi-angle, multi-band observations of GPM/DPR could help to characterize the vegetation zones. Especially, the σ0 at incidence angles between 1° and 8° represented useful characteristics of vegetation. Based on it, by using unsupervised clustering, we produced annual maps describing vegetation zones from 2014 to 2018. The result indicated that Mongolia experienced extensive changes in grassland and desert areas during the study years.

Simulating precipitation radar observations from a geostationary satellite

Abstract. 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.

Spatial variability of airborne radar reflectivity and velocity measurements of tropical rain with application to spaceborne radar

One of the challenges in accurate estimation of rainfall from spaceborne radars is achievement of adequate spatial resolution with reasonable-sized antennas. Previous studies have shown that variability of precipitation within the radar beam can result in errors in rainfall and Doppler estimation from spaceborne radars. In designing these radars, it is therefore necessary to achieve a spatial resolution that reduces such errors to acceptable levels. In this work the author considers data acquired by airborne radar in the tropics or sub-tropics, over ocean. The author confirms many of the findings of previous studies, specifically large Ku-band reflectivity fluctuations and relatively short Ku-band reflectivity correlation lengths in convective areas. This study also examines similar statistics for Ku-band path integrated attenuation and for vertical motion, the latter of which is not widely discussed in the literature. Results from these observations are then applied to spatial resolution considerations for future spaceborne precipitation radars.

Evaluation and Hydrological Validation of GPM Precipitation Products over the Nanliu River Basin, Beibu Gulf

Adequate and high-quality precipitation estimates, from spaceborne precipitation radars, are necessary for a variety of applications in hydrology. In this study, we investigated the performance of two Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement (GPM) mission (IMERG) products, against gauge observations over a small river basin, the Beibu Gulf—the Nanliu River basin, and evaluated their capability of streamflow simulation, based on a conceptual watershed model from April 2014 to December 2016. The results showed that both IMERG_Cal and IMERG_Uncal could roughly capture the spatial patterns of precipitation with slight over/underestimation (Relative Bias (RB) values of 6.5% and −5.5%, respectively) at a basin scale. At grid-cell scales, two IMERG products got an RB of −23.3% to 18.9%, Correlation Coefficient (CC) of 0.521 to 0.744, and Root Mean Square Error (RMSE) of 11.3 to 17.5 mm. There were some considerable errors in heavy precipitation events, and the IMERG significantly overestimated the amounts of these extreme events. The two IMERG products showed a higher accuracy and lower error rate, when detecting the light precipitation. IMERG-driven simulation had a better quality when the model was calibrated with satellite data rather than with rain gauge data. This analysis implied that IMERG products have potential in hydrological applications, in this region, and need further improvement in algorithms.

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.

Evolution of Precipitation Structure During the November DYNAMO MJO Event: Cloud‐Resolving Model Intercomparison and Cross Validation Using Radar Observations

AbstractEvolution of precipitation structures are simulated and compared with radar observations for the November Madden‐Julian Oscillation (MJO) event during the DYNAmics of the MJO (DYNAMO) field campaign. Three ground‐based, ship‐borne, and spaceborne precipitation radars and three cloud‐resolving models (CRMs) driven by observed large‐scale forcing are used to study precipitation structures at different locations over the central equatorial Indian Ocean. Convective strength is represented by 0‐dBZ echo‐top heights, and convective organization by contiguous 17‐dBZ areas. The multi‐radar and multi‐model framework allows for more stringent model validations. The emphasis is on testing models' ability to simulate subtle differences observed at different radar sites when the MJO event passed through. The results show that CRMs forced by site‐specific large‐scale forcing can reproduce not only common features in cloud populations but also subtle variations observed by different radars. The comparisons also revealed common deficiencies in CRM simulations where they underestimate radar echo‐top heights for the strongest convection within large, organized precipitation features. Cross validations with multiple radars and models also enable quantitative comparisons in CRM sensitivity studies using different large‐scale forcing, microphysical schemes and parameters, resolutions, and domain sizes. In terms of radar echo‐top height temporal variations, many model sensitivity tests have better correlations than radar/model comparisons, indicating robustness in model performance on this aspect. It is further shown that well‐validated model simulations could be used to constrain uncertainties in observed echo‐top heights when the low‐resolution surveillance scanning strategy is used.

Documentation of multifactorial relationships between precipitation and topography of the Tibetan Plateau using spaceborne precipitation radars

Precipitation is one of the most important hydrometeorological components of the Tibetan Plateau (TP). The relationships between precipitation and topography in the TP were investigated using 17 years of Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) data and 2 years of Global Precipitation Measurement (GPM) dual-frequency precipitation radar (DPR) data. First, the retrieval and total errors of the two radars were quantified in the TP using ground-based precipitation datasets. The TRMM PR and GPM DPR both significantly underestimate the precipitation, with total errors up to 40% and 53%, respectively. Then, precipitation of the two radars was corrected prior to effective application. The correction was separately performed for each river basin in the TP by adding total errors. Finally, precipitation–topography relationships were documented using corrected radar data. The main findings on precipitation–topography relationships are: (1) precipitation generally decreases with increasing elevation from 2 to 6 km in the TP. However, the trend is inverse in the Qaidam Basin which is characterized by extremely low precipitation in the interior basin and high precipitation along the windward slopes of surrounding mountains; (2) quantitative relationships between precipitation and elevation can be depicted for most exorheic basins in the TP using exponential fitting. The coefficients of determination for the fitting are higher than 0.9 in six basins; (3) the relationships based on GPM DPR data are less robust due to its fewer samples, whereas the GPM DPR probably resolves the problem of overestimating precipitation in some grid pixels with high elevation, compared to the TRMM PR; (4) three typical mountains (i.e., Himalaya, Hengduan, and Tianshan mountains) exhibit significantly negative correlation between precipitation and elevation. Particularly, there are two bands of precipitation maxima along the southern slopes of the central Himalayas (78°E–88°E), corresponding to the two-step topography, which affects the vegetation distribution. This study provides insights into the precipitation–topography relationships in the TP and its surrounding regions based on data from spaceborne precipitation radars.

Similarities and Improvements of GPM Dual-Frequency Precipitation Radar (DPR) upon TRMM Precipitation Radar (PR) in Global Precipitation Rate Estimation, Type Classification and Vertical Profiling

Spaceborne precipitation radars are powerful tools used to acquire adequate and high-quality precipitation estimates with high spatial resolution for a variety of applications in hydrological research. The Global Precipitation Measurement (GPM) mission, which deployed the first spaceborne Ka- and Ku-dual frequency radar (DPR), was launched in February 2014 as the upgraded successor of the Tropical Rainfall Measuring Mission (TRMM). This study matches the swath data of TRMM PR and GPM DPR Level 2 products during their overlapping periods at the global scale to investigate their similarities and DPR’s improvements concerning precipitation amount estimation and type classification of GPM DPR over TRMM PR. Results show that PR and DPR agree very well with each other in the global distribution of precipitation, while DPR improves the detectability of precipitation events significantly, particularly for light precipitation. The occurrences of total precipitation and the light precipitation (rain rates &lt; 1 mm/h) detected by GPM DPR are ~1.7 and ~2.53 times more than that of PR. With regard to type classification, the dual-frequency (Ka/Ku) and single frequency (Ku) methods performed similarly. In both inner (the central 25 beams) and outer swaths (1–12 beams and 38–49 beams) of DPR, the results are consistent. GPM DPR improves precipitation type classification remarkably, reducing the misclassification of clouds and noise signals as precipitation type “other” from 10.14% of TRMM PR to 0.5%. Generally, GPM DPR exhibits the same type division for around 82.89% (71.02%) of stratiform (convective) precipitation events recognized by TRMM PR. With regard to the freezing level height and bright band (BB) height, both radars correspond with each other very well, contributing to the consistency in stratiform precipitation classification. Both heights show clear latitudinal dependence. Results in this study shall contribute to future development of spaceborne radar precipitation retrievals and benefit hydrological and meteorological research.