Deepening our understanding of shallow precipitation measurements from space

2020 ◽  
Author(s):  
Linda Bogerd ◽  
Hidde Leijnse ◽  
Aart Overeem ◽  
Remko Uijlenhoet
Keyword(s):  
Research Area ◽  
Level Ii ◽  
Precipitation Measurement ◽  
Ground Validation ◽  
Precipitation Type ◽  
Project Structure ◽  
Global Precipitation Measurement ◽  
Global Precipitation ◽  
The Impact

<p><span><span>Satellite-based remote sensing provides a unique opportunity for the estimation of global precipitation patterns. </span><span>In order to use this approach, it is crucial that the uncertainty in the satellite estimations is precisely understood. T</span><span>he retrieval</span><span> of high-latitude precipitation </span><span>(especially shallow precipitation) </span><span>remains challenging for satellite precipitation monitoring. </span><span>This </span><span>project</span><span> will quantify the quality of the precipitation estimations obtained from</span> <span>the Global Precipitation Measurement (GPM) mission, where the focus will be on the level II and III products.</span> <span>Initially, t</span><span>h</span><span>e </span><span>Netherlands </span><span>is chosen as research area, since it has an excellent infrastructure with both in-situ and remotely sensed ground-based precipitation measurements, </span><span>its flat topography,</span> <span>and the </span><span>frequent</span> <span>occurrence</span><span> of shallow precipitation events. The project will study the influence of precipitation type and the impact of the seasons on the accuracy </span><span>of the GPM products. </span><span>Hereafter, the project will focus on the physical causes behind the discrepancies between the GPM products and the ground validation</span><span>, </span><span>w</span><span>hich can be used to improve the </span><span>retrieval</span><span> algorithms. The </span><span>presentation</span><span> will outline the project structure and will demonstrate </span><span>the</span> <span>initial</span><span> results. </span></span></p>

Microphysical features indicated by GPM DPR product “flagHeavyIcePrecip” – Case studies on lightning activity

2020 ◽  
Author(s):  
Kenji Suzuki ◽  
Rimpei Kamamoto ◽  
Tetsuya Kawano ◽  
Katsuhiro Nakagawa ◽  
Yuki Kaneko
Keyword(s):  
Heavy Rain ◽  
Lightning Activity ◽  
Dual Frequency ◽  
Convective Clouds ◽  
Precipitation Measurement ◽  
X Band ◽  
Precipitation Type ◽  
Global Precipitation Measurement ◽  
Global Precipitation

<p>Two products from the Global Precipitation Measurement (GPM) Dual-frequency Precipitation Radar (DPR) algorithms, a flag of intense solid precipitation above the –10°C height (“flagHeavyIcePrecip”), and a classification of precipitation type (“typePrecip”) were validated quantitatively from the viewpoint of microphysics using ground-based in-situ hydrometeor measurements and X-band multi-parameter (X-MP) radar observations of snow clouds that occurred on 4 February 2018. The distribution of the “flagHeavyIcePrecip” footprints was in good agreement with that of the graupel-dominant pixels classified by the X-MP radar hydrometeor classification. In addition, the vertical profiles of X-MP radar reflectivity exhibited significant differences between footprints flagged and unflagged by “flagHeavyPrecip”. We confirmed the effectiveness of “flagHeavyIcePrecip”, which is built into “typePrecip” algorithm, for detecting intense ice precipitation and concluded that "flagHeavyIcePrecip" is appropriate to useful for determining convective clouds.</p><p>It is well known that the lightning activity is closely related to the convection. We examined the lightning activity using GPM DPR product flagHeavyIcePrecip that indicates the existence of graupel in the upper cloud. On 20 June 2016, we experienced heavy rain with active lightning during Baiu monsoon rainy season, while the GPM DPR passed over Kyushu region in Japan. The distribution of “flagHeavyIcePrecip” obtained from the GPM DPR well corresponded to the CG/IC lightning concentration. On 4 September 2019, isolated thunder clouds observed by the GPM DPR was also similar to the “flagHeavyIcePrecip” distribution. However, partially there was IC lightning without “flagHeavyIcePrecip”, which was positive lightning. It was suggested to have been produced in the upper clouds in which positive ice crystals were dominant.</p>

scholarly journals Data-Enabled Field Experiment Planning, Management, and Research Using Cyberinfrastructure

2015 ◽  
Vol 16 (3) ◽  
pp. 1155-1170 ◽  
Author(s):  
Ibrahim Demir ◽  
Helen Conover ◽  
Witold F. Krajewski ◽  
Bong-Chul Seo ◽  
Radosław Goska ◽  
...  
Keyword(s):  
Experiment Planning ◽  
Field Campaign ◽  
Resource Center ◽  
Weather Radars ◽  
Related Space ◽  
Precipitation Measurement ◽  
Ground Validation ◽  
Global Precipitation Measurement ◽  
Global Precipitation ◽  
Informatics Tools

Abstract In the spring of 2013, NASA conducted a field campaign known as Iowa Flood Studies (IFloodS) as part of the Ground Validation (GV) program for the Global Precipitation Measurement (GPM) mission. The purpose of IFloodS was to enhance the understanding of flood-related, space-based observations of precipitation processes in events that transpire worldwide. NASA used a number of scientific instruments such as ground-based weather radars, rain and soil moisture gauges, stream gauges, and disdrometers to monitor rainfall events in Iowa. This article presents the cyberinfrastructure tools and systems that supported the planning, reporting, and management of the field campaign and that allow these data and models to be accessed, evaluated, and shared for research. The authors describe the collaborative informatics tools, which are suitable for the network design, that were used to select the locations in which to place the instruments. How the authors used information technology tools for instrument monitoring, data acquisition, and visualizations after deploying the instruments and how they used a different set of tools to support data analysis and modeling after the campaign are also explained. All data collected during the campaign are available through the Global Hydrology Resource Center (GHRC), a NASA Distributed Active Archive Center (DAAC).

scholarly journals Global Precipitation Measurement (GPM) Ground Validation (GV) Prototype in the Korean Peninsula

2014 ◽  
Vol 31 (9) ◽  
pp. 1902-1921 ◽  
Author(s):  
Ji-Hye Kim ◽  
Mi-Lim Ou ◽  
Jun-Dong Park ◽  
Kenneth R. Morris ◽  
Mathew R. Schwaller ◽  
...  
Keyword(s):  
Korean Peninsula ◽  
Rain Rate ◽  
Tropical Rainfall Measuring Mission ◽  
Rain Gauge ◽  
International Partnerships ◽  
Precipitation Measurement ◽  
Ground Validation ◽  
Microwave Imager ◽  
Global Precipitation Measurement ◽  
Global Precipitation

Abstract Since 2009, the Korea Meteorological Administration (KMA) has participated in ground validation (GV) projects through international partnerships within the framework of the Global Precipitation Measurement (GPM) Mission. The goal of this work is to assess the reliability of ground-based measurements in the Korean Peninsula as a means for validating precipitation products retrieved from satellite microwave sensors, with an emphasis on East Asian precipitation. KMA has a well-developed operational weather service infrastructure composed of meteorological radars, a dense rain gauge network, and automated weather stations. Measurements from these systems, including data from four ground-based radars (GRs), were combined with satellite data from the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) and used as a proxy for GPM GV over the Korean Peninsula. A time series of mean reflectivity differences (GR − PR) for stratiform-only and above-brightband-only data showed that the time-averaged difference fell between −2.0 and +1.0 dBZ for the four GRs used in this study. Site-specific adjustments for these relative mean biases were applied to GR reflectivities, and detailed statistical comparisons of reflectivity and rain rate between PR and bias-adjusted GR were carried out. In rain-rate comparisons, surface rain from the TRMM Microwave Imager (TMI) and the rain gauges were added and the results varied according to rain type. Bias correction has had a positive effect on GR rain rate comparing with PR and gauge rain rates. This study confirmed advance preparation for GPM GV system was optimized on the Korean Peninsula using the official framework.

scholarly journals Evaluation of Radar Rainfall Products: Lessons Learned from the NASA TRMM Validation Program in Florida

2006 ◽  
Vol 23 (11) ◽  
pp. 1492-1505 ◽  
Author(s):  
Eyal Amitai ◽  
David A. Marks ◽  
David B. Wolff ◽  
David S. Silberstein ◽  
Brad L. Fisher ◽  
...  
Keyword(s):  
Tropical Rainfall Measuring Mission ◽  
Product Evaluation ◽  
Radar Data ◽  
Lessons Learned ◽  
Limiting Factors ◽  
Radar Rainfall ◽  
Precipitation Measurement ◽  
Ground Validation ◽  
Global Precipitation Measurement ◽  
Global Precipitation

Abstract Evaluation of the Tropical Rainfall Measuring Mission (TRMM) satellite observations is conducted through a comprehensive ground validation (GV) program. Since the launch of TRMM in late 1997, standardized instantaneous and monthly rainfall products are routinely generated using quality-controlled ground-based radar data adjusted to the gauge accumulations from four primary sites. As part of the NASA TRMM GV program, effort is being made to evaluate these GV products. This paper describes the product evaluation effort for the Melbourne, Florida, site. This effort allows us to evaluate the radar rainfall estimates, to improve the algorithms in order to develop better GV products for comparison with the satellite products, and to recognize the major limiting factors in evaluating the estimates that reflect current limitations in radar rainfall estimation. Lessons learned and suggested improvements from this 8-yr mission are summarized in the context of improving planning for future precipitation missions, for example, the Global Precipitation Measurement (GPM).

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

2016 ◽  
Vol 33 (4) ◽  
pp. 653-667 ◽  
Author(s):  
Atsushi Hamada ◽  
Yukari N. Takayabu
Keyword(s):  
Deep Convection ◽  
Convective Precipitation ◽  
Dual Frequency ◽  
Precipitation Radar ◽  
Precipitation Measurement ◽  
Subtropical Oceans ◽  
Global Precipitation Measurement ◽  
Global Precipitation ◽  
The Impact ◽  
Light Precipitation

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.

scholarly journals A Ground Validation Network for the Global Precipitation Measurement Mission

2011 ◽  
Vol 28 (3) ◽  
pp. 301-319 ◽  
Author(s):  
Mathew R. Schwaller ◽  
K. Robert Morris
Keyword(s):  
Attenuation Correction ◽  
Radar Data ◽  
Radar Reflectivity ◽  
Retrieval Algorithm ◽  
Precipitation Data ◽  
Precipitation Measurement ◽  
Trmm Pr ◽  
Ground Validation ◽  
Global Precipitation Measurement ◽  
Global Precipitation

Abstract A prototype Validation Network (VN) is currently operating as part of the Ground Validation System for NASA’s Global Precipitation Measurement (GPM) mission. The VN supports precipitation retrieval algorithm development in the GPM prelaunch era. Postlaunch, the VN will be used to validate GPM spacecraft instrument measurements and retrieved precipitation data products. The period of record for the VN prototype starts on 8 August 2006 and runs to the present day. The VN database includes spacecraft data from the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) and coincident ground radar (GR) data from operational meteorological networks in the United States, Australia, Korea, and the Kwajalein Atoll in the Marshall Islands. Satellite and ground radar data products are collected whenever the PR satellite track crosses within 200 km of a VN ground radar, and these data are stored permanently in the VN database. VN products are generated from coincident PR and GR observations when a significant rain event occurs. The VN algorithm matches PR and GR radar data (including retrieved precipitation data in the case of the PR) by calculating averages of PR reflectivity (both raw and attenuation corrected) and rain rate, and GR reflectivity at the geometric intersection of the PR rays with the individual GR elevation sweeps. The algorithm thus averages the minimum PR and GR sample volumes needed to “matchup” the spatially coincident PR and GR data types. The result of this technique is a set of vertical profiles for a given rainfall event, with coincident PR and GR samples matched at specified heights throughout the profile. VN data can be used to validate satellite measurements and to track ground radar calibration over time. A comparison of matched TRMM PR and GR radar reflectivity factor data found a remarkably small difference between the PR and GR radar reflectivity factor averaged over this period of record in stratiform and convective rain cases when samples were taken from high in the atmosphere. A significant difference in PR and GR reflectivity was found in convective cases, particularly in convective samples from the lower part of the atmosphere. In this case, the mean difference between PR and corrected GR reflectivity was −1.88 dBZ. The PR–GR bias was found to increase with the amount of PR attenuation correction applied, with the PR–GR bias reaching −3.07 dBZ in cases where the attenuation correction applied is >6 dBZ. Additional analysis indicated that the version 6 TRMM PR retrieval algorithm underestimates rainfall in case of convective rain in the lower part of the atmosphere by 30%–40%.

scholarly journals Toward Improving Ice Water Content and Snow-Rate Retrievals from Radars. Part II: Results from Three Wavelength Radar–Collocated In Situ Measurements and CloudSat–GPM–TRMM Radar Data

2018 ◽  
Vol 57 (2) ◽  
pp. 365-389 ◽  
Author(s):  
Andrew Heymsfield ◽  
Aaron Bansemer ◽  
Norman B. Wood ◽  
Guosheng Liu ◽  
Simone Tanelli ◽  
...  
Keyword(s):  
Mass Flux ◽  
Tropical Rainfall Measuring Mission ◽  
Radar Data ◽  
Validation Data ◽  
Precipitation Measurement ◽  
Ice Water Content ◽  
Global Precipitation Measurement ◽  
Ice Water ◽  
Global Precipitation

AbstractTwo methods for deriving relationships between the equivalent radar reflectivity factor Ze and the snowfall rate S at three radar wavelengths are described. The first method uses collocations of in situ aircraft (microphysical observations) and overflying aircraft (radar observations) from two field programs to develop Ze–S relationships. In the second method, measurements of Ze at the top of the melting layer (ML), from radars on the Tropical Rainfall Measuring Mission (TRMM), Global Precipitation Measurement (GPM), and CloudSat satellites, are related to the retrieved rainfall rate R at the base of the ML, assuming that the mass flux through the ML is constant. Retrievals of R are likely to be more reliable than S because far fewer assumptions are involved in the retrieval and because supporting ground-based validation data are available. The Ze–S relationships developed here for the collocations and the mass-flux technique are compared with those derived from level 2 retrievals from the standard satellite products and with a number of relationships developed and reported by others. It is shown that there are substantial differences among them. The relationships developed here promise improvements in snowfall-rate retrievals from satellite-based radar measurements.

scholarly journals The Olympic Mountains Experiment (OLYMPEX)

2017 ◽  
Vol 98 (10) ◽  
pp. 2167-2188 ◽  
Author(s):  
Robert A. Houze ◽  
Lynn A. McMurdie ◽  
Walter A. Petersen ◽  
Mathew R. Schwaller ◽  
William Baccus ◽  
...  
Keyword(s):  
Winter Season ◽  
Snow Accumulation ◽  
Satellite Mission ◽  
Olympic Mountains ◽  
Precipitation Measurement ◽  
Ground Validation ◽  
Research Aircraft ◽  
Frontal Systems ◽  
Global Precipitation Measurement ◽  
Global Precipitation

Abstract The Olympic Mountains Experiment (OLYMPEX) took place during the 2015/16 fall–winter season in the vicinity of the mountainous Olympic Peninsula of Washington State. The goals of OLYMPEX were to provide physical and hydrologic ground validation for the U.S.–Japan Global Precipitation Measurement (GPM) satellite mission and, more specifically, to study how precipitation in Pacific frontal systems is modified by passage over coastal mountains. Four transportable scanning dual-polarization Doppler radars of various wavelengths were installed. Surface stations were placed at various altitudes to measure precipitation rates, particle size distributions, and fall velocities. Autonomous recording cameras monitored and recorded snow accumulation. Four research aircraft supplied by NASA investigated precipitation processes and snow cover, and supplemental rawinsondes and dropsondes were deployed during precipitation events. Numerous Pacific frontal systems were sampled, including several reaching “atmospheric river” status, warm- and cold-frontal systems, and postfrontal convection.

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