A Comprehensive Northern Hemisphere Particle Microphysics Data Set From the Precipitation Imaging Package
Microphysical observations of precipitating particles are critical data sources for numerical weather prediction models and remote sensing retrieval algorithms. However, obtaining coherent data sets of particle microphysics is challenging as they are often unindexed, distributed across disparate ins...
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| Vydáno v: | Earth and space science (Hoboken, N.J.) Ročník 11; číslo 5 |
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| Hlavní autoři: | , , , , , , , , , , , , , , , , , , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
Hoboken
John Wiley & Sons, Inc
01.05.2024
American Geophysical Union (AGU) |
| Témata: | |
| ISSN: | 2333-5084, 2333-5084 |
| On-line přístup: | Získat plný text |
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| Shrnutí: | Microphysical observations of precipitating particles are critical data sources for numerical weather prediction models and remote sensing retrieval algorithms. However, obtaining coherent data sets of particle microphysics is challenging as they are often unindexed, distributed across disparate institutions, and have not undergone a uniform quality control process. This work introduces a unified, comprehensive Northern Hemisphere particle microphysical data set from the National Aeronautics and Space Administration precipitation imaging package (PIP), accessible in a standardized data format and stored in a centralized, public repository. Data is collected from 10 measurement sites spanning 34° latitude (37°N–71°N) over 10 years (2014–2023), which comprise a set of 1,070,000 precipitating minutes. The provided data set includes measurements of a suite of microphysical attributes for both rain and snow, including distributions of particle size, vertical velocity, and effective density, along with higher‐order products including an approximation of volume‐weighted equivalent particle densities, liquid equivalent snowfall, and rainfall rate estimates. The data underwent a rigorous standardization and quality assurance process to filter out erroneous observations to produce a self‐describing, scalable, and achievable data set. Case study analyses demonstrate the capabilities of the data set in identifying physical processes like precipitation phase‐changes at high temporal resolution. Bulk precipitation characteristics from a multi‐site intercomparison also highlight distinct microphysical properties unique to each location. This curated PIP data set is a robust database of high‐quality particle microphysical observations for constraining future precipitation retrieval algorithms, and offers new insights toward better understanding regional and seasonal differences in bulk precipitation characteristics.
Plain Language Summary
This work introduces a new particle microphysics data set that is useful for improving weather prediction models and in enhancing precipitation estimation techniques. The data set, produced from National Aeronautics and Space Administration's precipitation imaging package, is comprehensive, well documented, and easy to access. It includes observations from 10 locations across the Northern Hemisphere over 10 years, providing information on both rain and snow. This information includes details like particle size, speed, and density, as well as estimates of rainfall and snowfall rates. The data has been standardized and checked for quality, making it reliable and easy to use. This product is a valuable resource for refining methods to measure precipitation, and offers new insights into regional and seasonal precipitation patterns.
Key Points
This data set contains high temporal resolution, disdrometer‐derived precipitation microphysics observations from 10 sites over 10 years
Rigorous quality control practices yield a scalable, self‐describing data set packaged into a common, standardized NetCDF format
The data's diverse geographic and environmental coverage offers new insights into regional and seasonal precipitation processes and patterns |
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| Bibliografie: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 National Aeronautics and Space Administration (NASA) Natural Sciences and Engineering Research Council of Canada AC05-76RL01830 None USDOE Office of Science (SC), Biological and Environmental Research (BER) |
| ISSN: | 2333-5084 2333-5084 |
| DOI: | 10.1029/2024EA003538 |