Evidence map›Paper›PMID 31213729›Full record

ArticleQuarterly journal of the Royal Meteorological Society. Royal Meteorological Society (Great Britain)2018

The Global Precipitation Measurement (GPM) mission's scientific achievements and societal contributions: reviewing four years of advanced rain and snow observations.

Gail Skofronick-Jackson, Dalia Kirschbaum, Walter Petersen, George Huffman, Chris Kidd, Erich Stocker, Ramesh Kakar

Abstract read
In one paragraph

Article in Quarterly journal of the Royal Meteorological Society. Royal Meteorological Society (Great Britain), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Article
  7. Spaceborne Cloud and Precipitation Radars: Status, Challenges, and Ways Forward.Reviews of geophysics (Washington, D.C. : 1985) · 2020
    Review
  8. Article
  9. Physical Evaluation of GPM DPR Single- and Dual-Wavelength Algorithms.Journal of atmospheric and oceanic technology · 2019
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Gail Skofronick-JacksonCode 612.0, NASA Goddard Space Flight Center, Greenbelt, MD.
Dalia KirschbaumCode 612.0, NASA Goddard Space Flight Center, Greenbelt, MD.
Walter PetersenST11, NASA Marshall Space Flight Center, Earth Sciences Office, National Space and Technology Center, Huntsville, AL.
George HuffmanCode 612.0, NASA Goddard Space Flight Center, Greenbelt, MD.
Chris KiddEarth System Science Interdisciplinary Center, University of Maryland, College Park, MD.
Erich StockerCode 612.0, NASA Goddard Space Flight Center, Greenbelt, MD.
Ramesh KakarNASA Headquarters, Washington, D.C.

Funding

Goddard Space Flight Center NASAIntramural NASA N-999999
6 · The paper itself

Abstract

Precipitation represents a life-critical energy and hydrologic exchange between the Earth's atmosphere and its surface. As such, knowledge of where, when, and how much rain and snow falls is essential for scientific research and societal applications. Building on the 17-year success of the Tropical Rainfall Measurement Mission (TRMM), the Global Precipitation Measurement (GPM) Core Observatory (GPM-CO) is the first U.S. National Aeronautical and Space Administration (NASA) satellite mission specifically designed with sensors to observe the structure and intensities of both rain and falling snow. The GPM-CO has proved to be a worthy successor to TRMM, extending and improving high-quality active and passive microwave observations across all times of day. The GPM-CO launched in early 2014, is a joint mission between NASA and the Japanese Aerospace Exploration Agency (JAXA), with sensors that include the NASA-provided GPM Microwave Imager and the JAXA-provided Dual-frequency Precipitation Radar. These sensors were devised with high accuracy standards enabling them to be used as a reference for inter-calibrating a constellation of partner satellite data. These intercalibrated partner satellite retrievals are used with infrared data to produce merged precipitation estimates at temporal scales of 30 minutes and spatial scales of 0.1° × 0.1°. Precipitation estimates from the GPM-CO and partner constellation satellites, provided in near real time and later reprocessed with all ancillary data, are an indispensable source of precipitation data for operational and scientific users. Advances have been made using GPM data, primarily in improving sensor calibration, retrieval algorithms, and ground validation measurements, and used to further our understanding of the characteristics of liquid and frozen precipitation and the science of water and hydrological cycles for climate/weather forecasting. These advances have extended to societal benefits related to water resources, operational numerical weather prediction, hurricane monitoring, prediction, and disaster response, extremes, and disease.

Indexed as

applicationsprecipitationrainremote sensingsatellitesnow

Identifiers

PMID31213729
PMCPMC6581458

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.