scholarly journals Airborne Radar Observations of Severe Hailstorms: Implications for Future Spaceborne Radar

2013 ◽  
Vol 52 (8) ◽  
pp. 1851-1867 ◽  
Author(s):  
Gerald M. Heymsfield ◽  
Lin Tian ◽  
Lihua Li ◽  
Matthew McLinden ◽  
Jaime I. Cervantes
Keyword(s):  
High Altitude ◽  
Doppler Radar ◽  
Tropical Rainfall Measuring Mission ◽  
Airborne Radar ◽  
Dual Frequency ◽  
Precipitation Radar ◽  
Ka Band ◽  
Severe Thunderstorms ◽  
Radar Measurements ◽  
Spaceborne Radar

AbstractA new dual-frequency (Ku and Ka band) nadir-pointing Doppler radar on the high-altitude NASA ER-2 aircraft, called the High-Altitude Imaging Wind and Rain Airborne Profiler (HIWRAP), has collected data over severe thunderstorms in Oklahoma and Kansas during the Midlatitude Continental Convective Clouds Experiment (MC3E). The overarching motivation for this study is to understand the behavior of the dual-wavelength airborne radar measurements in a global variety of thunderstorms and how these may relate to future spaceborne-radar measurements. HIWRAP is operated at frequencies that are similar to those of the precipitation radar on the Tropical Rainfall Measuring Mission (Ku band) and the upcoming Global Precipitation Measurement mission satellite's dual-frequency (Ku and Ka bands) precipitation radar. The aircraft measurements of strong hailstorms have been combined with ground-based polarimetric measurements to obtain a better understanding of the response of the Ku- and Ka-band radar to the vertical distribution of the hydrometeors, including hail. Data from two flight lines on 24 May 2011 are presented. Doppler velocities were ~39 m s−1 at 10.7-km altitude from the first flight line early on 24 May, and the lower value of ~25 m s−1 on a second flight line later in the day. Vertical motions estimated using a fall speed estimate for large graupel and hail suggested that the first storm had an updraft that possibly exceeded 60 m s−1 for the more intense part of the storm. This large updraft speed along with reports of 5-cm hail at the surface, reflectivities reaching 70 dBZ at S band in the storm cores, and hail signals from polarimetric data provide a highly challenging situation for spaceborne-radar measurements in intense convective systems. The Ku- and Ka-band reflectivities rarely exceed ~47 and ~37 dBZ, respectively, in these storms.

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

2015 ◽  
Vol 32 (12) ◽  
pp. 2281-2296 ◽  
Author(s):  
Robert Meneghini ◽  
Hyokyung Kim ◽  
Liang Liao ◽  
Jeffrey A. Jones ◽  
John M. Kwiatkowski
Keyword(s):  
Cross Section ◽  
Radar Data ◽  
Single Frequency ◽  
Initial Assessment ◽  
Dual Frequency ◽  
Precipitation Radar ◽  
Frequency Method ◽  
Ka Band ◽  
Spaceborne Radar ◽  
Ku Band

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.

Spaceborne Doppler Radar Measurements of Rainfall: Correction of Errors Induced by Pointing Uncertainties

2005 ◽  
Vol 22 (11) ◽  
pp. 1676-1690 ◽  
Author(s):  
Simone Tanelli ◽  
Eastwood Im ◽  
Satoru Kobayashi ◽  
Roberto Mascelloni ◽  
Luca Facheris
Keyword(s):  
Doppler Radar ◽  
Sea Surface ◽  
Doppler Spectrum ◽  
Airborne Radar ◽  
Precipitation Radar ◽  
Analysis Technique ◽  
Correction Technique ◽  
Radar Echo ◽  
Radar Measurements ◽  
Nonuniform Beam

Abstract In this paper a sea surface radar echo spectral analysis technique to correct for the rainfall velocity error caused by radar-pointing uncertainty is presented. The correction procedure is quite straightforward when the radar is observing a homogeneous rainfall field. When nonuniform beam filling (NUBF) occurs and attenuating frequencies are used, however, additional steps are necessary in order to correctly estimate the antenna-pointing direction. This new technique relies on the application of the combined frequency–time (CFT) algorithm to correct for uneven attenuation effects on the observed sea surface Doppler spectrum. The performance of this correction technique was evaluated by a Monte Carlo simulation of the Doppler precipitation radar backscatter from high-resolution 3D rain fields (either generated by a cloud resolving numerical model or retrieved from airborne radar measurements). The results show that the antenna-pointing-induced error can, indeed, be reduced by the proposed technique in order to achieve 1 m s−1 accuracy on rainfall vertical velocity estimates.

scholarly journals Impact of Misrepresentation of Freezing-Level Height by the TRMM Algorithm on Shallow Rain Statistics over India and Adjoining Oceans

2013 ◽  
Vol 52 (9) ◽  
pp. 2001-2008 ◽  
Author(s):  
K. Saikranthi ◽  
T. Narayana Rao ◽  
B. Radhakrishna ◽  
S. Vijaya Bhaskara Rao
Keyword(s):  
Tropical Rainfall Measuring Mission ◽  
Precipitation Radar ◽  
Study Region ◽  
Freezing Level ◽  
Northwestern India ◽  
Trmm Precipitation ◽  
Radar Measurements ◽  
The Impact ◽  
The Himalaya ◽  
Level Height

AbstractThe estimation of freezing level-height (FLH) by the Tropical Rainfall Measuring Mission (TRMM) algorithm is evaluated, against several other data sources, over India and adjoining oceans. It is observed that the TRMM algorithm either underestimates or overestimates the FLH [relative to radiosonde- and ECMWF Interim Re-Analysis (ERA)-derived FLH] at latitudes > 20°N over India. The agreement between the FLHs obtained from ERA and radiosonde and the TRMM-derived brightband height suggests that usage of ERA-derived FLH may improve shallow rain statistics. The impact of misrepresentation of FLH by the TRMM algorithm on shallow rain statistics is assessed by using 13 yr of TRMM precipitation radar measurements. It is noted that the misidentification of FLH alone affects (mostly underestimates) the shallow rain occurrence and rain fraction by 3%–8% over the study region. The magnitude of underestimation is large over the southern slopes of the Himalaya, the northern plains, and in northwestern India. TRMM identifies most of the shallow rain (30%–50%) as cold rain in regions where the underestimation of FLH is high. This situation could introduce some error in the correction of reflectivity for attenuation and in the retrieval of latent heat profiles.

Ka-band high-altitude precipitation radar with ground measurements: data processing and initial validations

2020 ◽  
Author(s):  
Jakob Fusselman ◽  
Matthew Gilliam ◽  
Yan (Rockee) Zhang ◽  
Cameron Homeyer ◽  
William Blake
Keyword(s):  
Data Processing ◽  
High Altitude ◽  
Precipitation Radar ◽  
Ka Band

scholarly journals Rain Type Classification Algorithm Module for GPM Dual-Frequency Precipitation Radar

2016 ◽  
Vol 33 (9) ◽  
pp. 1887-1898 ◽  
Author(s):  
Jun Awaka ◽  
Minda Le ◽  
V. Chandrasekar ◽  
Naofumi Yoshida ◽  
Tomohiko Higashiuwatoko ◽  
...  
Keyword(s):  
Tropical Rainfall Measuring Mission ◽  
Classification Algorithm ◽  
Single Frequency ◽  
Dual Frequency ◽  
Precipitation Radar ◽  
Precipitation Measurement ◽  
Statistical Sense ◽  
Global Precipitation Measurement ◽  
Global Precipitation ◽  
Type Classification

AbstractThe 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.

scholarly journals Cloud Assumption of Precipitation Retrieval Algorithms for the Dual-Frequency Precipitation Radar

2020 ◽  
Vol 37 (11) ◽  
pp. 2015-2031
Author(s):  
Takuji Kubota ◽  
Shinta Seto ◽  
Masaki Satoh ◽  
Tomoe Nasuno ◽  
Toshio Iguchi ◽  
...  
Keyword(s):  
Liquid Water ◽  
Atmospheric Model ◽  
Liquid Water Content ◽  
Absolute Difference ◽  
Dual Frequency ◽  
Precipitation Radar ◽  
Cloud Liquid Water ◽  
Ka Band ◽  
Surface Precipitation ◽  
Precipitation Estimates

AbstractAn 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.

scholarly journals Latent heating profiles from GOES-16 and its comparison to heating from NEXRAD and GPM

2021 ◽  
Author(s):  
Yoonjin Lee ◽  
Christian D. Kummerow ◽  
Milija Zupanski
Keyword(s):  
Temporal Resolution ◽  
Weather Forecasting ◽  
Tropical Rainfall Measuring Mission ◽  
Latent Heating ◽  
Dual Frequency ◽  
Precipitation Radar ◽  
Model Simulations ◽  
Forecast Models ◽  
Climate Analysis ◽  
Heating Profiles

Abstract. Latent heating (LH) is an important quantity in both weather forecasting and climate analysis, being the essential factor driving convective systems. Yet, inferring LH rates from our current observing systems is challenging at best. For climate studies, LH has been retrieved from the Precipitation Radar (PR) on the Tropical Rainfall Measuring Mission (TRMM) using model simulations in the look-up table (LUT) that relates instantaneous radar profiles to corresponding heating profiles. These radars, first on TRMM and then Global Precipitation Measurement (GPM), provide a continuous record of LH. However, with observations approximately 3 days apart, its temporal resolution is too coarse to be used to initiate convection in forecast models. In operational forecast models such as High-Resolution Rapid Refresh (HRRR), convection is initiated from LH derived from ground based radar. Despite the high spatial and temporal resolution of ground-based radars, one disadvantage of using it is that its data are only available over well observed land areas. This study suggests a method to derive LH from the Geostationary Operational-Environmental Satellite-16 (GOES-16) in near-real time. Even though the visible and infrared channels on the Advanced Baseline Imager (ABI) provide mostly cloud top information, rapid changes in cloud top visible and infrared properties, when coupled to a LUT similar to those used by the TRMM and GPM radars, can equally be used to derive LH profiles for convective regions using model simulations coupled to a convective classification scheme and channel 14 (11.2 μm) brightness temperature. Convective regions detected by GOES-16 are assigned LH from the LUT, and they are compared with LH from NEXRAD and one of Dual-frequency Precipitation Radar (DPR) products, Goddard Convective-Stratiform Heating (CSH). LH obtained from GOES-16 show similar magnitude with NEXRAD and CSH, and vertical distribution of LH is also very similar with CSH. Overall, GOES LH appear to have the ability to mimic LH from radars, although the area identified as convective is roughly 25 % smaller than the current HRRR model, while the heating is correspondingly higher.

A Statistical Method for Reducing Sidelobe Clutter for the Ku-Band Precipitation Radar on board the GPM Core Observatory

2016 ◽  
Vol 33 (7) ◽  
pp. 1413-1428 ◽  
Author(s):  
Takuji Kubota ◽  
Toshio Iguchi ◽  
Masahiro Kojima ◽  
Liang Liao ◽  
Takeshi Masaki ◽  
...  
Keyword(s):  
Statistical Method ◽  
Tropical Rainfall Measuring Mission ◽  
Multiple Regression Model ◽  
Dual Frequency ◽  
Precipitation Radar ◽  
Explanatory Variables ◽  
Received Power ◽  
Free Region ◽  
Future Work ◽  
Ku Band

AbstractA statistical method to reduce the sidelobe clutter of the Ku-band precipitation radar (KuPR) of the Dual-Frequency Precipitation Radar (DPR) on board the Global Precipitation Measurement (GPM) Core Observatory is described and evaluated using DPR observations. The KuPR sidelobe clutter was much more severe than that of the Precipitation Radar on board the Tropical Rainfall Measuring Mission (TRMM), and it has caused the misidentification of precipitation. The statistical method to reduce sidelobe clutter was constructed by subtracting the estimated sidelobe power, based upon a multiple regression model with explanatory variables of the normalized radar cross section (NRCS) of surface, from the received power of the echo. The saturation of the NRCS at near-nadir angles, resulting from strong surface scattering, was considered in the calculation of the regression coefficients.The method was implemented in the KuPR algorithm and applied to KuPR-observed data. It was found that the received power from sidelobe clutter over the ocean was largely reduced by using the developed method, although some of the received power from the sidelobe clutter still remained. From the statistical results of the evaluations, it was shown that the number of KuPR precipitation events in the clutter region, after the method was applied, was comparable to that in the clutter-free region. This confirms the reasonable performance of the method in removing sidelobe clutter. For further improving the effectiveness of the method, it is necessary to improve the consideration of the NRCS saturation, which will be explored in future work.

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