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...
Saved in:
| Published in: | Earth and space science (Hoboken, N.J.) Vol. 11; no. 5 |
|---|---|
| Main Authors: | , , , , , , , , , , , , , , , , , , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Hoboken
John Wiley & Sons, Inc
01.05.2024
American Geophysical Union (AGU) |
| Subjects: | |
| ISSN: | 2333-5084, 2333-5084 |
| Online Access: | Get full text |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Abstract | 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 |
|---|---|
| AbstractList | 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. 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. 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. 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 Abstract 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. 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 |
| Author | Chibisov, Alexey King, Fraser Kulie, Mark S. Wong, Telyana Wood, Norman Moisseev, Dimitri Rodriguez, Peter Stuefer, Martin Cooper, Steven J. Lerber, Annakaisa Mateling, Marian Wingo, Matthew T. Wolff, David B. Pettersen, Claire Bliven, Larry F. Leskinen, Matti Schirtzinger, Carl Cerrai, Diego L’Ecuyer, Tristan Nesbitt, Stephen W. Petersen, Walter A. McMurdie, Lynn |
| Author_xml | – sequence: 1 givenname: Fraser orcidid: 0000-0003-1698-8482 surname: King fullname: King, Fraser email: kingfr@umich.edu organization: University of Michigan – sequence: 2 givenname: Claire orcidid: 0000-0002-8685-6242 surname: Pettersen fullname: Pettersen, Claire email: pettersc@umich.edu organization: University of Michigan – sequence: 3 givenname: Larry F. surname: Bliven fullname: Bliven, Larry F. organization: Wallops Flight Facility – sequence: 4 givenname: Diego orcidid: 0000-0001-5918-4885 surname: Cerrai fullname: Cerrai, Diego organization: University of Connecticut – sequence: 5 givenname: Alexey surname: Chibisov fullname: Chibisov, Alexey organization: Wallops Flight Facility – sequence: 6 givenname: Steven J. surname: Cooper fullname: Cooper, Steven J. organization: University of Utah – sequence: 7 givenname: Tristan orcidid: 0000-0002-7584-4836 surname: L’Ecuyer fullname: L’Ecuyer, Tristan organization: University of Wisconsin–Madison – sequence: 8 givenname: Mark S. orcidid: 0000-0003-1400-1007 surname: Kulie fullname: Kulie, Mark S. organization: NOAA/NESDIS/Center for Satellite Applications and Research – sequence: 9 givenname: Matti surname: Leskinen fullname: Leskinen, Matti organization: University of Helsinki – sequence: 10 givenname: Marian orcidid: 0000-0002-5255-3040 surname: Mateling fullname: Mateling, Marian organization: University of Wisconsin–Madison – sequence: 11 givenname: Lynn orcidid: 0000-0002-5342-0960 surname: McMurdie fullname: McMurdie, Lynn organization: University of Washington – sequence: 12 givenname: Dimitri orcidid: 0000-0002-4575-0409 surname: Moisseev fullname: Moisseev, Dimitri organization: Finnish Meteorological Institute – sequence: 13 givenname: Stephen W. surname: Nesbitt fullname: Nesbitt, Stephen W. organization: University of Illinois Urbana–Champaign – sequence: 14 givenname: Walter A. surname: Petersen fullname: Petersen, Walter A. organization: NASA Marshall Space Flight Center – sequence: 15 givenname: Peter surname: Rodriguez fullname: Rodriguez, Peter organization: Environment and Climate Change Canada – sequence: 16 givenname: Carl surname: Schirtzinger fullname: Schirtzinger, Carl organization: Wallops Flight Facility – sequence: 17 givenname: Martin surname: Stuefer fullname: Stuefer, Martin organization: University of Alaska Fairbanks – sequence: 18 givenname: Annakaisa orcidid: 0000-0003-2890-1217 surname: Lerber fullname: Lerber, Annakaisa organization: Finnish Meteorological Institute – sequence: 19 givenname: Matthew T. surname: Wingo fullname: Wingo, Matthew T. organization: University of Alabama – sequence: 20 givenname: David B. surname: Wolff fullname: Wolff, David B. organization: Wallops Flight Facility – sequence: 21 givenname: Telyana surname: Wong fullname: Wong, Telyana organization: University of Alaska Fairbanks – sequence: 22 givenname: Norman orcidid: 0000-0001-8228-3910 surname: Wood fullname: Wood, Norman organization: University of Wisconsin–Madison |
| BackLink | https://www.osti.gov/servlets/purl/2352252$$D View this record in Osti.gov |
| BookMark | eNqFkU1vEzEQhi1UJErpjR9gwZVQf6zX62MUUhqpX1LgbDneceKQtRfbBeXf45IIVRzak0ej5309885bdBJiAITeU_KZEqYuGGHNfEoIF7x7hU4Z53wiSNecPKnfoPOct4QQykRb-VPkp3gWhzHBBkL2vwDfxlQ2kAK-gsHnsZaA700q3u4A33ib4rjZZ28z_mKKwUso-DLFAVcRvk9g_eiLKT4GvBjM2od1VdsfZg3v0GtndhnOj-8Z-n45_za7mlzffV3MptcT28hWTKhyXe9cJ-lKmAZsa7rOgVGK9qCcIUw6SWuHEEepdECBMN4zaxsqm550_AwtDr59NFs9Jj-YtNfReP23EdNaH9fRtBXAadszIVWzWoGSfce4VMIy1nL76PXh4BVz8TpbX8BubAwBbNGMC8YEq9DHAzSm-PMBctHb-JBC3VFz0hLZCCV5pT4dqJpgzgncv9Eo0Y8H1E8PWHH2H26PuZZk_O4F0W-_g_2zH-j5cslqYoL_ARkdrAM |
| CitedBy_id | crossref_primary_10_1126_sciadv_adu0162 |
| Cites_doi | 10.5194/acp‐21‐11955‐2021 10.1175/1520‐0450(2001)040〈1965:TSOTTR〉2.0.CO;2 10.1002/qj.49712555707 10.5194/essd‐14‐4995‐2022 10.1007/s10584‐017‐1899‐y 10.3390/atmos11060619 10.5194/amt‐15‐1439‐2022 10.5194/amt‐9‐4825‐2016 10.5194/hess‐24‐4887‐2020 10.1175/2008JTECHA1148.1 10.5194/bgd‐9‐527‐2012 10.5194/amt‐14‐869‐2021 10.1175/2010JAMC2535.1 10.5194/amt‐6‐3635‐2013 10.1017/CBO9780511581168 10.48550/arXiv.1704.03924 10.1175/JAMC‐D‐19‐0099.1 10.1007/s00703‐011‐0142‐z 10.1175/BAMS‐D‐20‐0246.1 10.5194/amt‐15‐4443‐2022 10.1175/AMSMONOGRAPHS‐D‐15‐0023.1 10.1175/BAMS‐D‐20‐0228.1 10.1175/1520‐0442‐12.1.46 10.1080/07055900.2018.1433627 10.1175/BAMS‐D‐13‐00164.1 10.3390/atmos11080785 10.1175/1520‐0450(1977)016〈1322:PAAIRM〉2.0.CO;2 10.1029/2008JD009982 10.1029/2010JD015420 10.1007/s00034‐009‐9130‐7 10.1175/BAMS‐D‐18‐0291.1 10.1109/IGARSS.2019.8899120 10.1175/JAMC‐D‐21‐0131.1 10.1175/BAMS‐D‐13‐00262.1 10.5194/hess‐19‐951‐2015 10.1038/s41598‐018‐34450‐3 10.1007/s10584‐013‐0822‐4 10.1175/MWR‐D‐20‐0164.1 10.1029/2021JD034754 10.1007/978-94-007-5603-8_9 10.1175/JAMC‐D‐20‐0248.1 10.1029/2022JD037132 10.1002/qj.3803 10.1175/JAS‐D‐17‐0242.1 10.1016/j.jhydrol.2015.05.042 10.7302/37yx‐9q53 10.1175/BAMS‐D‐14‐00199.1 10.3390/rs13112183 10.1175/1520‐0450(2002)041〈0272:AEBPRA〉2.0.CO;2 10.1126/sciadv.aax6869 10.1175/JAMC‐D‐16‐0379.1 10.1007/s10668‐022‐02330‐6 10.1038/s41612‐020‐00137‐8 10.1175/BAMS‐D‐12‐00227.1 10.1007/978-3-030-52171-4_12 10.1002/2013JD021303 10.1175/MWR2810.1 10.5194/amt‐15‐6035‐2022 10.1175/MWR‐D‐17‐0267.1 10.1016/j.earscirev.2020.103171 10.5194/amt‐15‐6545‐2022 10.1175/BAMS‐D‐19‐0128.1 10.1175/BAMS‐D‐21‐0007.1 10.1175/BAMS‐84‐12‐1807 10.1038/nclimate3240 10.1029/2019MS001689 10.1175/2008JHM1067.1 10.1175/BAMS‐D‐19‐0027.1 10.3390/atmos8120253 10.1175/BAMS‐D‐16‐0182.1 10.3390/atmos12030363 10.1175/JAMC‐D‐18‐0281.1 10.1175/2009JAMC2156.1 10.5194/amt‐10‐2557‐2017 |
| ContentType | Journal Article |
| Copyright | 2024. The Authors. Earth and Space Science published by Wiley Periodicals LLC on behalf of American Geophysical Union. 2024. This work is published under http://creativecommons.org/licenses/by/4.0/ (the "License"). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. |
| Copyright_xml | – notice: 2024. The Authors. Earth and Space Science published by Wiley Periodicals LLC on behalf of American Geophysical Union. – notice: 2024. This work is published under http://creativecommons.org/licenses/by/4.0/ (the "License"). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. |
| CorporateAuthor | ARM Data Center, Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States) |
| CorporateAuthor_xml | – name: ARM Data Center, Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States) |
| DBID | 24P AAYXX CITATION ABUWG AEUYN AFKRA AZQEC BENPR BHPHI BKSAR CCPQU DWQXO HCIFZ PCBAR PHGZM PHGZT PIMPY PKEHL PQEST PQQKQ PQUKI OIOZB OTOTI DOA |
| DOI | 10.1029/2024EA003538 |
| DatabaseName | Wiley Online Library Open Access CrossRef ProQuest Central (Alumni) ProQuest One Sustainability ProQuest Central UK/Ireland ProQuest Central Essentials ProQuest Central Natural Science Collection Earth, Atmospheric & Aquatic Science Collection ProQuest One ProQuest Central Korea SciTech Premium Collection Earth, Atmospheric & Aquatic Science Database ProQuest Central Premium ProQuest One Academic (New) Publicly Available Content Database ProQuest One Academic Middle East (New) ProQuest One Academic Eastern Edition (DO NOT USE) ProQuest One Academic (retired) ProQuest One Academic UKI Edition OSTI.GOV - Hybrid OSTI.GOV DOAJ Directory of Open Access Journals |
| DatabaseTitle | CrossRef Publicly Available Content Database ProQuest One Academic Middle East (New) ProQuest Central Essentials ProQuest One Academic Eastern Edition Earth, Atmospheric & Aquatic Science Database ProQuest Central (Alumni Edition) SciTech Premium Collection ProQuest One Community College Earth, Atmospheric & Aquatic Science Collection ProQuest Central ProQuest One Sustainability ProQuest One Academic UKI Edition Natural Science Collection ProQuest Central Korea ProQuest Central (New) ProQuest One Academic ProQuest One Academic (New) |
| DatabaseTitleList | Publicly Available Content Database CrossRef |
| Database_xml | – sequence: 1 dbid: 24P name: Wiley Online Library Open Access url: https://authorservices.wiley.com/open-science/open-access/browse-journals.html sourceTypes: Publisher – sequence: 2 dbid: DOA name: DOAJ Directory of Open Access Journals url: https://www.doaj.org/ sourceTypes: Open Website – sequence: 3 dbid: PIMPY name: Publicly Available Content Database url: http://search.proquest.com/publiccontent sourceTypes: Aggregation Database |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Geology |
| EISSN | 2333-5084 |
| EndPage | n/a |
| ExternalDocumentID | oai_doaj_org_article_165e316d25794bbe97d823795c2263c8 2352252 10_1029_2024EA003538 ESS21745 |
| Genre | dataArticle |
| GeographicLocations | Northern Hemisphere United States--US Finland Michigan |
| GeographicLocations_xml | – name: Michigan – name: Finland – name: United States--US – name: Northern Hemisphere |
| GrantInformation_xml | – fundername: National Aeronautics and Space Administration funderid: 80NSSC22K0789; 80NSSC19K0712; 80NSSC18K0701 – fundername: Natural Sciences and Engineering Research Council of Canada funderid: 577912 |
| GroupedDBID | 0R~ 1OC 24P 5VS AAFWJ AAHHS AAZKR ABDBF ACCFJ ACCMX ACUHS ACXQS ADBBV ADKYN ADZMN ADZOD AEEZP AEQDE AEUYN AFKRA AFPKN AIWBW AJBDE ALMA_UNASSIGNED_HOLDINGS ALUQN AVUZU BCNDV BENPR BHPHI BKSAR CCPQU EBS EJD GODZA GROUPED_DOAJ HCIFZ IAO IGS ITC KQ8 M~E O9- OK1 PCBAR PIMPY WIN AAMMB AAYXX AEFGJ AFFHD AGXDD AIDQK AIDYY CITATION IEP PHGZM PHGZT ABUWG AZQEC DWQXO PKEHL PQEST PQQKQ PQUKI PUEGO OIOZB OTOTI |
| ID | FETCH-LOGICAL-c4765-19f8dff871b5a4ec6a88fea991de9fa027f718fe00f117fe1e023d2cc4174d083 |
| IEDL.DBID | 24P |
| ISICitedReferencesCount | 4 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=001222927700001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| ISSN | 2333-5084 |
| IngestDate | Mon Nov 10 04:34:29 EST 2025 Mon Jun 16 02:55:07 EDT 2025 Thu Sep 11 12:11:21 EDT 2025 Tue Nov 18 21:50:49 EST 2025 Sat Nov 29 07:33:41 EST 2025 Wed Jan 22 17:20:30 EST 2025 |
| IsDoiOpenAccess | true |
| IsOpenAccess | true |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 5 |
| Language | English |
| License | Attribution |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c4765-19f8dff871b5a4ec6a88fea991de9fa027f718fe00f117fe1e023d2cc4174d083 |
| Notes | 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) |
| ORCID | 0000-0001-8228-3910 0000-0003-1698-8482 0000-0002-5255-3040 0000-0003-1400-1007 0000-0002-4575-0409 0000-0001-5918-4885 0000-0002-7584-4836 0000-0002-8685-6242 0000-0003-2890-1217 0000-0002-5342-0960 0000000314001007 0000000253420960 0000000316988482 0000000159184885 0000000252553040 0000000328901217 0000000286856242 0000000245750409 0000000182283910 0000000275844836 |
| OpenAccessLink | https://onlinelibrary.wiley.com/doi/abs/10.1029%2F2024EA003538 |
| PQID | 3060745973 |
| PQPubID | 4368366 |
| PageCount | 21 |
| ParticipantIDs | doaj_primary_oai_doaj_org_article_165e316d25794bbe97d823795c2263c8 osti_scitechconnect_2352252 proquest_journals_3060745973 crossref_primary_10_1029_2024EA003538 crossref_citationtrail_10_1029_2024EA003538 wiley_primary_10_1029_2024EA003538_ESS21745 |
| PublicationCentury | 2000 |
| PublicationDate | May 2024 |
| PublicationDateYYYYMMDD | 2024-05-01 |
| PublicationDate_xml | – month: 05 year: 2024 text: May 2024 |
| PublicationDecade | 2020 |
| PublicationPlace | Hoboken |
| PublicationPlace_xml | – name: Hoboken – name: United States |
| PublicationTitle | Earth and space science (Hoboken, N.J.) |
| PublicationYear | 2024 |
| Publisher | John Wiley & Sons, Inc American Geophysical Union (AGU) |
| Publisher_xml | – name: John Wiley & Sons, Inc – name: American Geophysical Union (AGU) |
| References | 2011; 116 2017; 7 2011; 113 2017; 8 2017; 1 2021; 21 2021; 126 2019; 58 2020; 204 2020; 59 2020; 12 1999; 125 2020; 11 2013; 120 2013; 6 2009; 48 2020; 6 2004; 132 2018; 8 2020; 3 2023; 25 2009; 10 2002; 41 1999; 12 2008; 113 2014; 95 2003; 84 2018; 75 2014; 119 2015; 19 2021; 102 2018; 146 2015; 96 2021; 149 2002; 7 2002; 1 2023; 128 2009 2016; 97 2006 2015; 527 2020; 101 2004 2020; 146 2009; 26 2016; 57 2009; 28 2021; 14 2021; 13 2021; 12 2000; 39 2023 2022 2021 2022; 61 1977; 16 2020 2017; 10 2017; 98 2017; 56 2011; 50 2019 2022; 14 2018 2022; 15 2020; 24 2016 2017; 141 2013 2018; 56 2021; 60 2016; 9 2012; 9 2022; 103 e_1_2_10_23_1 e_1_2_10_46_1 e_1_2_10_69_1 e_1_2_10_21_1 e_1_2_10_44_1 NPS (e_1_2_10_57_1) 2018 Peters G. (e_1_2_10_59_1) 2002; 7 e_1_2_10_42_1 e_1_2_10_40_1 e_1_2_10_70_1 e_1_2_10_2_1 e_1_2_10_72_1 e_1_2_10_4_1 e_1_2_10_18_1 e_1_2_10_74_1 e_1_2_10_53_1 e_1_2_10_6_1 e_1_2_10_16_1 e_1_2_10_39_1 e_1_2_10_76_1 e_1_2_10_55_1 e_1_2_10_8_1 e_1_2_10_14_1 e_1_2_10_37_1 e_1_2_10_78_1 e_1_2_10_58_1 e_1_2_10_13_1 e_1_2_10_11_1 e_1_2_10_32_1 e_1_2_10_30_1 Junkins J. L. C. (e_1_2_10_34_1) 2004 e_1_2_10_51_1 Arias P. (e_1_2_10_3_1) 2021 McMurdie L. (e_1_2_10_48_1) 2020 e_1_2_10_80_1 e_1_2_10_82_1 e_1_2_10_61_1 e_1_2_10_84_1 e_1_2_10_29_1 e_1_2_10_63_1 e_1_2_10_27_1 e_1_2_10_65_1 e_1_2_10_25_1 e_1_2_10_67_1 e_1_2_10_24_1 e_1_2_10_45_1 e_1_2_10_22_1 e_1_2_10_43_1 e_1_2_10_41_1 e_1_2_10_71_1 e_1_2_10_73_1 e_1_2_10_52_1 e_1_2_10_19_1 e_1_2_10_75_1 e_1_2_10_54_1 Pörtner H. (e_1_2_10_64_1) 2019 e_1_2_10_5_1 e_1_2_10_17_1 e_1_2_10_38_1 e_1_2_10_77_1 e_1_2_10_56_1 e_1_2_10_79_1 e_1_2_10_7_1 e_1_2_10_15_1 e_1_2_10_36_1 e_1_2_10_12_1 e_1_2_10_35_1 e_1_2_10_9_1 e_1_2_10_10_1 e_1_2_10_33_1 e_1_2_10_31_1 e_1_2_10_50_1 Drebs A. (e_1_2_10_20_1) 2002; 1 e_1_2_10_60_1 e_1_2_10_81_1 e_1_2_10_62_1 e_1_2_10_83_1 e_1_2_10_85_1 e_1_2_10_28_1 e_1_2_10_49_1 e_1_2_10_66_1 e_1_2_10_26_1 e_1_2_10_47_1 e_1_2_10_68_1 |
| References_xml | – year: 2009 – volume: 3 start-page: 1 issue: 1 year: 2020 end-page: 5 article-title: Constraint on precipitation response to climate change by combination of atmospheric energy and water budgets publication-title: npj Climate and Atmospheric Science – volume: 95 start-page: 701 issue: 5 year: 2014 end-page: 722 article-title: The global precipitation measurement mission publication-title: Bulletin of the American Meteorological Society – volume: 60 start-page: 1127 issue: 8 year: 2021 end-page: 1148 article-title: High‐latitude precipitation: Snowfall regimes at two distinct sites in Scandinavia publication-title: Journal of Applied Meteorology and Climatology – volume: 56 start-page: 1561 issue: 6 year: 2017 end-page: 1582 article-title: Microphysical properties of snow and their link to Ze–S relations during BAECC 2014 publication-title: Journal of Applied Meteorology and Climatology – volume: 97 start-page: 1909 issue: 10 year: 2016 end-page: 1928 article-title: BAECC: A field campaign to elucidate the impact of biogenic aerosols on clouds and climate publication-title: Bulletin of the American Meteorological Society – volume: 56 start-page: 71 issue: 2 year: 2018 end-page: 95 article-title: An overview of surface‐based precipitation observations at environment and climate change Canada publication-title: Atmosphere‐Ocean – volume: 8 issue: 1 year: 2018 article-title: The impact of Arctic warming on increased rainfall publication-title: Scientific Reports – volume: 120 start-page: 357 issue: 1 year: 2013 end-page: 374 article-title: Climate change impacts on global agriculture publication-title: Climatic Change – volume: 11 issue: 6 year: 2020 article-title: Evaluation of the microphysical assumptions within GPM‐DPR using ground‐based observations of rain and snow publication-title: Atmosphere – volume: 125 start-page: 1607 issue: 557 year: 1999 end-page: 1636 article-title: A microphysically based precipitation scheme for the UK meteorological office unified model publication-title: Quarterly Journal of the Royal Meteorological Society – volume: 14 start-page: 869 issue: 2 year: 2021 end-page: 888 article-title: What millimeter‐wavelength radar reflectivity reveals about snowfall: An information‐centric analysis publication-title: Atmospheric Measurement Techniques – volume: 50 start-page: 433 issue: 2 year: 2011 end-page: 448 article-title: A modular optimal estimation method for combined radar–radiometer precipitation profiling publication-title: Journal of Applied Meteorology and Climatology – volume: 132 start-page: 2610 issue: 11 year: 2004 end-page: 2627 article-title: Precipitation uncertainty due to variations in precipitation particle parameters within a simple microphysics scheme publication-title: Monthly Weather Review – year: 2018 – volume: 103 start-page: E1243 issue: 5 year: 2022 end-page: E1269 article-title: Chasing snowstorms: The investigation of microphysics and precipitation for Atlantic coast‐threatening snowstorms (IMPACTS) campaign publication-title: Bulletin of the American Meteorological Society – volume: 59 start-page: 103 issue: 1 year: 2020 end-page: 124 article-title: A composite analysis of snowfall modes from four winter seasons in Marquette, Michigan publication-title: Journal of Applied Meteorology and Climatology – volume: 102 start-page: E1317 issue: 7 year: 2021 end-page: E1339 article-title: Snowfall in the northern great lakes: Lessons learned from a multisensor observatory publication-title: Bulletin of the American Meteorological Society – volume: 12 issue: 8 year: 2020 article-title: Confronting the challenge of modeling cloud and precipitation microphysics publication-title: Journal of Advances in Modeling Earth Systems – volume: 146 start-page: 1023 issue: 4 year: 2018 end-page: 1044 article-title: Synoptic control over orographic precipitation distributions during the olympics mountains experiment (OLYMPEX) publication-title: Monthly Weather Review – volume: 12 issue: 3 year: 2021 article-title: Seasonal estimates and uncertainties of snow accumulation from CloudSat precipitation retrievals publication-title: Atmosphere – volume: 101 start-page: E109 issue: 2 year: 2020 end-page: E128 article-title: The Canadian Arctic weather science project: Introduction to the Iqaluit site publication-title: Bulletin of the American Meteorological Society – volume: 11 issue: 8 year: 2020 article-title: The precipitation imaging package: Assessment of microphysical and bulk characteristics of snow publication-title: Atmosphere – volume: 96 start-page: 1719 issue: 10 year: 2015 end-page: 1741 article-title: Global precipitation measurement cold season precipitation experiment (GCPEX): For measurement’s Sake, let it snow publication-title: Bulletin of the American Meteorological Society – volume: 527 start-page: 943 year: 2015 end-page: 957 article-title: Propagation of satellite precipitation uncertainties through a distributed hydrologic model: A case study in the Tocantins–Araguaia basin in Brazil publication-title: Journal of Hydrology – volume: 21 start-page: 11955 issue: 15 year: 2021 end-page: 11978 article-title: Impact of wind pattern and complex topography on snow microphysics during International Collaborative Experiment for PyeongChang 2018 Olympic and Paralympic winter games (ICE‐POP 2018) publication-title: Atmospheric Chemistry and Physics – volume: 7 start-page: 353 year: 2002 end-page: 362 article-title: Rain observations with a vertically looking micro rain radar (MRR) publication-title: Boreal Environment Research – year: 2022 – volume: 25 start-page: 7325 issue: 7 year: 2023 end-page: 7343 article-title: Long‐term effects of temperature and precipitation on economic growth of selected MENA region countries publication-title: Environment, Development and Sustainability – volume: 19 start-page: 951 issue: 2 year: 2015 end-page: 967 article-title: Derivation of a new continuous adjustment function for correcting wind‐induced loss of solid precipitation: Results of a Norwegian field study publication-title: Hydrology and Earth System Sciences – volume: 6 issue: 7 year: 2020 article-title: Strong future increases in Arctic precipitation variability linked to poleward moisture transport publication-title: Science Advances – year: 2004 – volume: 126 issue: 13 year: 2021 article-title: The influence of atmospheric rivers on cold‐season precipitation in the upper great lakes region publication-title: Journal of Geophysical Research: Atmospheres – volume: 141 start-page: 287 issue: 2 year: 2017 end-page: 299 article-title: Effects of climate change on snowpack and fire potential in the western USA publication-title: Climatic Change – volume: 98 start-page: 2167 issue: 10 year: 2017 end-page: 2188 article-title: The olympic mountains experiment (OLYMPEX) publication-title: Bulletin of the American Meteorological Society – volume: 24 start-page: 4887 issue: 10 year: 2020 end-page: 4902 article-title: Application of machine learning techniques for regional bias correction of snow water equivalent estimates in Ontario, Canada publication-title: Hydrology and Earth System Sciences – year: 2019 – volume: 128 issue: 2 year: 2023 article-title: Multi‐year analysis of rain‐snow levels at Marquette, Michigan publication-title: Journal of Geophysical Research: Atmospheres – volume: 15 start-page: 4443 issue: 15 year: 2022 end-page: 4461 article-title: Validation of the aeolus level‐2B wind product over northern Canada and the Arctic publication-title: Atmospheric Measurement Techniques – volume: 75 start-page: 1453 issue: 5 year: 2018 end-page: 1476 article-title: Primary modes of global drop size distributions publication-title: Journal of the Atmospheric Sciences – volume: 149 start-page: 503 issue: 2 year: 2021 end-page: 520 article-title: Microphysical enhancement processes within stratiform precipitation on the barrier and sub‐barrier scale of the olympic mountains publication-title: Monthly Weather Review – volume: 15 start-page: 6035 issue: 20 year: 2022 end-page: 6050 article-title: DeepPrecip: A deep neural network for precipitation retrievals publication-title: Atmospheric Measurement Techniques – volume: 10 start-page: 2557 issue: 7 year: 2017 end-page: 2571 article-title: A variational technique to estimate snowfall rate from coincident radar, snowflake, and fall‐speed observations publication-title: Atmospheric Measurement Techniques – volume: 28 start-page: 819 issue: 6 year: 2009 end-page: 843 article-title: Fast normalized cross‐correlation publication-title: Circuits, Systems, and Signal Processing – volume: 8 issue: 12 year: 2017 article-title: On the precipitation and precipitation change in Alaska publication-title: Atmosphere – volume: 204 year: 2020 article-title: Meteorological aspects of heavy precipitation in relation to floods—An overview publication-title: Earth‐Science Reviews – volume: 58 start-page: 1337 issue: 6 year: 2019 end-page: 1352 article-title: Estimation of snowfall properties at a mountainous site in Norway using combined radar and in situ microphysical observations publication-title: Journal of Applied Meteorology and Climatology – volume: 7 start-page: 263 issue: 4 year: 2017 end-page: 267 article-title: Towards a rain‐dominated Arctic publication-title: Nature Climate Change – volume: 113 issue: D8 year: 2008 article-title: CloudSat mission: Performance and early science after the first year of operation publication-title: Journal of Geophysical Research – start-page: 4561 year: 2019 end-page: 4564 – volume: 16 start-page: 1322 issue: 12 year: 1977 end-page: 1331 article-title: Path‐ and area‐integrated rainfall measurement by microwave attenuation in the 1–3 cm band publication-title: Journal of Applied Meteorology and Climatology – volume: 1 start-page: 1 year: 2002 end-page: 99 article-title: Climatological statistics of Finland 1971–2000 publication-title: Climatic Statistics of Finland – volume: 26 start-page: 167 issue: 2 year: 2009 end-page: 179 article-title: Presenting the snowflake video imager (SVI) publication-title: Journal of Atmospheric and Oceanic Technology – volume: 9 start-page: 2033 year: 2012 end-page: 2044 article-title: Snowpack concentrations and estimated fluxes of volatile organic compounds in a boreal forest publication-title: Biogeosciences – year: 2016 – volume: 6 start-page: 3635 issue: 12 year: 2013 end-page: 3648 article-title: Characterization of video disdrometer uncertainties and impacts on estimates of snowfall rate and radar reflectivity publication-title: Atmospheric Measurement Techniques – volume: 12 start-page: 46 issue: 1 year: 1999 end-page: 63 article-title: Review of science issues, deployment strategy, and status for the ARM North Slope of Alaska–adjacent Arctic Ocean climate research site publication-title: Journal of Climate – volume: 84 start-page: 1807 issue: 12 year: 2003 end-page: 1826 article-title: Improvement of microphysical parameterization through observational verification experiment publication-title: Bulletin of the American Meteorological Society – volume: 9 start-page: 4825 issue: 9 year: 2016 end-page: 4841 article-title: Ensemble mean density and its connection to other microphysical properties of falling snow as observed in Southern Finland publication-title: Atmospheric Measurement Techniques – volume: 57 start-page: 8.1 issue: 1 year: 2016 end-page: 8.13 article-title: The ARM North Slope of Alaska (NSA) sites publication-title: Meteorological Monographs – volume: 119 start-page: 8941 issue: 14 year: 2014 end-page: 8961 article-title: Estimating snow microphysical properties using collocated multisensor observations publication-title: Journal of Geophysical Research: Atmospheres – volume: 96 start-page: 1311 issue: 8 year: 2015 end-page: 1332 article-title: The EarthCARE satellite: The next step forward in global measurements of clouds, aerosols, precipitation, and radiation publication-title: Bulletin of the American Meteorological Society – start-page: 471 year: 2013 end-page: 487 – volume: 48 start-page: 2242 issue: 11 year: 2009 end-page: 2256 article-title: A combined multisensor optimal estimation retrieval algorithm for oceanic warm rain clouds publication-title: Journal of Applied Meteorology and Climatology – volume: 61 start-page: 1077 issue: 8 year: 2022 end-page: 1085 article-title: A gamma parameterization for precipitating particle size distributions containing snowflake aggregates drawn from five field Experiments publication-title: Journal of Applied Meteorology and Climatology – volume: 13 issue: 11 year: 2021 article-title: The precipitation imaging package: Phase partitioning capabilities publication-title: Remote Sensing – volume: 15 start-page: 6545 issue: 22 year: 2022 end-page: 6561 article-title: A comparative evaluation of snowflake particle shape estimation techniques used by the precipitation imaging package (PIP), multi‐angle snowflake camera (MASC), and two‐dimensional video disdrometer (2DVD) publication-title: Atmospheric Measurement Techniques – year: 2006 – year: 2020 – year: 2023 – volume: 103 start-page: E370 issue: 2 year: 2022 end-page: E388 article-title: How well are we measuring snow post‐SPICE? publication-title: Bulletin of the American Meteorological Society – volume: 14 start-page: 4995 issue: 11 year: 2022 end-page: 5017 article-title: Enhanced automated meteorological observations at the Canadian Arctic Weather Science (CAWS) supersites publication-title: Earth System Science Data – volume: 116 issue: D18 year: 2011 article-title: Comparisons and analyses of aircraft and satellite observations for wintertime mixed‐phase clouds publication-title: Journal of Geophysical Research – volume: 103 start-page: E1762 issue: 8 year: 2022 end-page: E1780 article-title: Exploring snowfall variability through the high‐latitude measurement of snowfall (HiLaMS) field campaign publication-title: Bulletin of the American Meteorological Society – volume: 10 start-page: 1011 issue: 4 year: 2009 end-page: 1025 article-title: Effects of precipitation uncertainty on discharge calculations for main river basins publication-title: Journal of Hydrometeorology – volume: 146 start-page: 1999 issue: 730 year: 2020 end-page: 2049 article-title: The ERA5 global reanalysis publication-title: Quarterly Journal of the Royal Meteorological Society – start-page: 33 year: 2021 end-page: 144 – volume: 101 start-page: E1512 issue: 9 year: 2020 end-page: E1523 article-title: Optimal estimation retrievals and their uncertainties: What every atmospheric scientist should know publication-title: Bulletin of the American Meteorological Society – volume: 1 start-page: 161 issue: 1 year: 2017 end-page: 187 article-title: A tutorial on kernel density estimation and recent advances publication-title: arXiv – volume: 39 start-page: 1965 issue: 12 year: 2000 end-page: 1982 article-title: The status of the tropical rainfall measuring mission (TRMM) after two years in orbit publication-title: Journal of Applied Meteorology and Climatology – volume: 41 start-page: 272 issue: 3 year: 2002 end-page: 285 article-title: An estimation‐based precipitation retrieval algorithm for attenuating radars publication-title: Journal of Applied Meteorology and Climatology – start-page: 359 year: 2021 end-page: 400 – volume: 113 start-page: 75 issue: 1 year: 2011 end-page: 87 article-title: Observation of snowfall with a low‐power FM‐CW K‐band radar (micro rain radar) publication-title: Meteorology and Atmospheric Physics – volume: 15 start-page: 1439 issue: 5 year: 2022 end-page: 1464 article-title: Snow microphysical retrieval from the NASA D3R radar during ICE‐POP 2018 publication-title: Atmospheric Measurement Techniques – ident: e_1_2_10_35_1 doi: 10.5194/acp‐21‐11955‐2021 – ident: e_1_2_10_42_1 doi: 10.1175/1520‐0450(2001)040〈1965:TSOTTR〉2.0.CO;2 – ident: e_1_2_10_79_1 doi: 10.1002/qj.49712555707 – ident: e_1_2_10_46_1 doi: 10.5194/essd‐14‐4995‐2022 – ident: e_1_2_10_25_1 doi: 10.1007/s10584‐017‐1899‐y – ident: e_1_2_10_13_1 doi: 10.3390/atmos11060619 – ident: e_1_2_10_54_1 doi: 10.5194/amt‐15‐1439‐2022 – ident: e_1_2_10_76_1 doi: 10.5194/amt‐9‐4825‐2016 – ident: e_1_2_10_60_1 – ident: e_1_2_10_37_1 doi: 10.5194/hess‐24‐4887‐2020 – ident: e_1_2_10_55_1 doi: 10.1175/2008JTECHA1148.1 – ident: e_1_2_10_2_1 doi: 10.5194/bgd‐9‐527‐2012 – ident: e_1_2_10_81_1 doi: 10.5194/amt‐14‐869‐2021 – ident: e_1_2_10_53_1 doi: 10.1175/2010JAMC2535.1 – ident: e_1_2_10_82_1 doi: 10.5194/amt‐6‐3635‐2013 – volume-title: Weather—Olympic National Park year: 2018 ident: e_1_2_10_57_1 – ident: e_1_2_10_75_1 doi: 10.1017/CBO9780511581168 – ident: e_1_2_10_14_1 doi: 10.48550/arXiv.1704.03924 – ident: e_1_2_10_63_1 doi: 10.1175/JAMC‐D‐19‐0099.1 – ident: e_1_2_10_39_1 doi: 10.1007/s00703‐011‐0142‐z – ident: e_1_2_10_49_1 doi: 10.1175/BAMS‐D‐20‐0246.1 – ident: e_1_2_10_23_1 – start-page: 755 volume-title: IPCC, 2019: IPCC special report on the ocean and cryosphere in a changing climate year: 2019 ident: e_1_2_10_64_1 – ident: e_1_2_10_15_1 doi: 10.5194/amt‐15‐4443‐2022 – volume-title: IMPACTS field campaign data collection year: 2020 ident: e_1_2_10_48_1 – ident: e_1_2_10_77_1 doi: 10.1175/AMSMONOGRAPHS‐D‐15‐0023.1 – start-page: 33 volume-title: Climate change 2021: The physical science basis. Contribution of working group I to the sixth assessment report of the intergovernmental panel on climate change year: 2021 ident: e_1_2_10_3_1 – ident: e_1_2_10_40_1 doi: 10.1175/BAMS‐D‐20‐0228.1 – ident: e_1_2_10_72_1 doi: 10.1175/1520‐0442‐12.1.46 – ident: e_1_2_10_50_1 doi: 10.1080/07055900.2018.1433627 – ident: e_1_2_10_30_1 doi: 10.1175/BAMS‐D‐13‐00164.1 – ident: e_1_2_10_62_1 doi: 10.3390/atmos11080785 – ident: e_1_2_10_4_1 doi: 10.1175/1520‐0450(1977)016〈1322:PAAIRM〉2.0.CO;2 – ident: e_1_2_10_73_1 doi: 10.1029/2008JD009982 – ident: e_1_2_10_56_1 doi: 10.1029/2010JD015420 – volume: 7 start-page: 353 year: 2002 ident: e_1_2_10_59_1 article-title: Rain observations with a vertically looking micro rain radar (MRR) publication-title: Boreal Environment Research – ident: e_1_2_10_67_1 – ident: e_1_2_10_84_1 doi: 10.1007/s00034‐009‐9130‐7 – ident: e_1_2_10_33_1 doi: 10.1175/BAMS‐D‐18‐0291.1 – ident: e_1_2_10_12_1 doi: 10.1109/IGARSS.2019.8899120 – ident: e_1_2_10_22_1 doi: 10.1175/JAMC‐D‐21‐0131.1 – ident: e_1_2_10_71_1 doi: 10.1175/BAMS‐D‐13‐00262.1 – ident: e_1_2_10_80_1 doi: 10.5194/hess‐19‐951‐2015 – ident: e_1_2_10_6_1 doi: 10.1038/s41598‐018‐34450‐3 – ident: e_1_2_10_10_1 doi: 10.1007/s10584‐013‐0822‐4 – ident: e_1_2_10_85_1 doi: 10.1175/MWR‐D‐20‐0164.1 – ident: e_1_2_10_47_1 doi: 10.1029/2021JD034754 – ident: e_1_2_10_27_1 doi: 10.1007/978-94-007-5603-8_9 – ident: e_1_2_10_69_1 doi: 10.1175/JAMC‐D‐20‐0248.1 – ident: e_1_2_10_70_1 doi: 10.1029/2022JD037132 – ident: e_1_2_10_29_1 doi: 10.1002/qj.3803 – ident: e_1_2_10_19_1 doi: 10.1175/JAS‐D‐17‐0242.1 – ident: e_1_2_10_24_1 doi: 10.1016/j.jhydrol.2015.05.042 – ident: e_1_2_10_38_1 doi: 10.7302/37yx‐9q53 – ident: e_1_2_10_58_1 doi: 10.1175/BAMS‐D‐14‐00199.1 – ident: e_1_2_10_61_1 doi: 10.3390/rs13112183 – ident: e_1_2_10_43_1 doi: 10.1175/1520‐0450(2002)041〈0272:AEBPRA〉2.0.CO;2 – ident: e_1_2_10_8_1 doi: 10.1126/sciadv.aax6869 – ident: e_1_2_10_44_1 doi: 10.1175/JAMC‐D‐16‐0379.1 – ident: e_1_2_10_51_1 doi: 10.1007/s10668‐022‐02330‐6 – ident: e_1_2_10_18_1 doi: 10.1038/s41612‐020‐00137‐8 – ident: e_1_2_10_32_1 doi: 10.1175/BAMS‐D‐12‐00227.1 – ident: e_1_2_10_11_1 doi: 10.1007/978-3-030-52171-4_12 – ident: e_1_2_10_83_1 doi: 10.1002/2013JD021303 – ident: e_1_2_10_26_1 doi: 10.1175/MWR2810.1 – volume-title: Optimal estimation of dynamic systems year: 2004 ident: e_1_2_10_34_1 – ident: e_1_2_10_36_1 doi: 10.5194/amt‐15‐6035‐2022 – ident: e_1_2_10_65_1 doi: 10.1175/MWR‐D‐17‐0267.1 – ident: e_1_2_10_9_1 doi: 10.1016/j.earscirev.2020.103171 – volume: 1 start-page: 1 year: 2002 ident: e_1_2_10_20_1 article-title: Climatological statistics of Finland 1971–2000 publication-title: Climatic Statistics of Finland – ident: e_1_2_10_28_1 doi: 10.5194/amt‐15‐6545‐2022 – ident: e_1_2_10_41_1 doi: 10.1175/BAMS‐D‐19‐0128.1 – ident: e_1_2_10_16_1 doi: 10.1175/BAMS‐D‐21‐0007.1 – ident: e_1_2_10_74_1 doi: 10.1175/BAMS‐84‐12‐1807 – ident: e_1_2_10_7_1 doi: 10.1038/nclimate3240 – ident: e_1_2_10_52_1 doi: 10.1029/2019MS001689 – ident: e_1_2_10_5_1 doi: 10.1175/2008JHM1067.1 – ident: e_1_2_10_45_1 doi: 10.1175/BAMS‐D‐19‐0027.1 – ident: e_1_2_10_78_1 doi: 10.3390/atmos8120253 – ident: e_1_2_10_31_1 doi: 10.1175/BAMS‐D‐16‐0182.1 – ident: e_1_2_10_21_1 doi: 10.3390/atmos12030363 – ident: e_1_2_10_68_1 doi: 10.1175/JAMC‐D‐18‐0281.1 – ident: e_1_2_10_66_1 doi: 10.1175/2009JAMC2156.1 – ident: e_1_2_10_17_1 doi: 10.5194/amt‐10‐2557‐2017 |
| SSID | ssj0001256024 |
| Score | 2.2818882 |
| Snippet | Microphysical observations of precipitating particles are critical data sources for numerical weather prediction models and remote sensing retrieval... Abstract Microphysical observations of precipitating particles are critical data sources for numerical weather prediction models and remote sensing retrieval... |
| SourceID | doaj osti proquest crossref wiley |
| SourceType | Open Website Open Access Repository Aggregation Database Enrichment Source Index Database Publisher |
| SubjectTerms | Algorithms Datasets disdrometer Forests Lakes Measurement techniques microphysics Particle size particle size distribution Precipitation precipitation imaging package Prediction models Quality assurance Quality control Rainfall rate Remote sensing Snow Weather forecasting |
| SummonAdditionalLinks | – databaseName: DOAJ Directory of Open Access Journals dbid: DOA link: http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV1LT9wwELYqRCUuqLQgtjzkAz1VEeusncTH5bGA1K5WKq32Zjn2WCDYh7IBiX_fGSeg9ABceooU2dHY48l8Y4-_YexIpdqDFCJBSKQTaUufFCAhUbkNPnid6Zht8edHPh4X06medEp9UU5YQw_cTNyxyBQMROZxaWlZlqBzT_wqWjkEDgMXr_n2c90JpprdFfTkqWwz3fuppiBfng_p4IyuonR8UKTqx8cCTeofmNkFq9HbjD6xzRYm8mEj3hb7APPP7ONFLMP79IXdDjkZcgU3Tf45j8cvUM35JdVvI6oA4JN2cPwnJd01WxgrfmZry39BzUfVYsaxE58QwcWy5ermV7NYtwh7uzv812yz36Pz69PLpC2akDiZZyoROhQ-BIyDSmUluMwWRQCLMNCDDhaj0IDuKEC_H4TIAwhAr-1T5yTGJh4B2Q5bmy_msMu4tEVeDCxkRbCyDKBLJUqPGkyDlFaEHvv-PI3GtVJSYYt7E0-2U226k95j315aLxsmjVfanZBGXtoQ_3V8gavCtBNn3lsVPbZH-jQII4gL11HSkKtNSnBTpT22_6xm05rsymDshHAK46sBjiuq_k0xDdoHhXPq6_-Qd49t0MebTMp9tlZXD3DA1t1jfbuqDuPa_gsf2_jS priority: 102 providerName: Directory of Open Access Journals – databaseName: ProQuest Central dbid: BENPR link: http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1Lb9QwELZKCxIXKC-xtFQ-wAlFrLN2Ep-qLey2lWC14qXeLMceQwXdLNmA1H_PjOMty4FeeooU2ZGTGc9845l8w9gLlWsPUogMIZHOpK19VoGETJU2-OB1oWO1xZd35WxWnZ3peTpwW6WyyrVNjIbaN47OyF8jtEVvh_B3dLj8mVHXKMquphYat9gOMZWhnu8cTWbzDxunLOjRc5kq3oe5pmBfTsaUQKNfUjZ8UaTsx0uDW-sfuLkJWqPXmd6_6Xp32b2EN_m4V5AHbAsWD9md49jP9_IROx9zsggtfOsL2XnM40C74CfUCI44B4DPk3rx91S915-FrPhb21n-ETo-bZsLjpP4nJgylon0m59exAZIONt9R6P1mH2eTj69OclS94XMybJQmdCh8iFgQFUrK8EVtqoCWMSTHnSwGM4G9GsBhsMgRBlAALp_nzsnMcjxiOyesO1Fs4CnjEtbldXIQlEFK-sAulai9qgKeZDSijBgr9ZyMC6tkjpk_DAxRZ5rsym1AXt5NXrZU3L8Z9wRifRqDBFpxxtN-9WkD2dEoWAkCo-WS8u6Bl16ou_RyiEuHTl8yB4phEE8QqS6jqqPXGdywq0qH7D9tfBN2vsr81fy-F5Rd65dpsGNRnGhenb9w_bYXZrWF1vus-2u_QXP2W33uztftQdJ8f8AU7AJig priority: 102 providerName: ProQuest |
| Title | A Comprehensive Northern Hemisphere Particle Microphysics Data Set From the Precipitation Imaging Package |
| URI | https://onlinelibrary.wiley.com/doi/abs/10.1029%2F2024EA003538 https://www.proquest.com/docview/3060745973 https://www.osti.gov/servlets/purl/2352252 https://doaj.org/article/165e316d25794bbe97d823795c2263c8 |
| Volume | 11 |
| WOSCitedRecordID | wos001222927700001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| journalDatabaseRights | – providerCode: PRVAON databaseName: DOAJ Directory of Open Access Journals customDbUrl: eissn: 2333-5084 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0001256024 issn: 2333-5084 databaseCode: DOA dateStart: 20140101 isFulltext: true titleUrlDefault: https://www.doaj.org/ providerName: Directory of Open Access Journals – providerCode: PRVPQU databaseName: Earth, Atmospheric & Aquatic Science Database customDbUrl: eissn: 2333-5084 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0001256024 issn: 2333-5084 databaseCode: PCBAR dateStart: 20141201 isFulltext: true titleUrlDefault: https://search.proquest.com/eaasdb providerName: ProQuest – providerCode: PRVPQU databaseName: ProQuest Central customDbUrl: eissn: 2333-5084 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0001256024 issn: 2333-5084 databaseCode: BENPR dateStart: 20141201 isFulltext: true titleUrlDefault: https://www.proquest.com/central providerName: ProQuest – providerCode: PRVPQU databaseName: Publicly Available Content Database customDbUrl: eissn: 2333-5084 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0001256024 issn: 2333-5084 databaseCode: PIMPY dateStart: 20141201 isFulltext: true titleUrlDefault: http://search.proquest.com/publiccontent providerName: ProQuest – providerCode: PRVWIB databaseName: Wiley Online Library Free Content customDbUrl: eissn: 2333-5084 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0001256024 issn: 2333-5084 databaseCode: WIN dateStart: 20140101 isFulltext: true titleUrlDefault: https://onlinelibrary.wiley.com providerName: Wiley-Blackwell – providerCode: PRVWIB databaseName: Wiley Online Library Open Access customDbUrl: eissn: 2333-5084 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0001256024 issn: 2333-5084 databaseCode: 24P dateStart: 20140101 isFulltext: true titleUrlDefault: https://authorservices.wiley.com/open-science/open-access/browse-journals.html providerName: Wiley-Blackwell |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1Lb9QwELagBYkL74qlZeUDnFBEHTsPH7ewS1eiq4hnOVmOPYYKultlAxL_nhnHXW0PICFOUSLHcuyZ8TfjyTeMPS1y7UEJkSEk0pmyrc9qUJAVlQ0-eF3qmG3x8U21WNSnp7pJATf6F2bgh9gE3Egzor0mBbftOpENEEcmeu1qOqGTMFlfZ7tCyIqkOlfNVowF9_NY1zaXUmaIRVTKfccuXmx3cGVXiuT9eFmhkl0BntvwNe4_szv_O_K77HZCnnwyiMo9dg2W99nN17Gy768H7GzCyTZ08HVIaefxRAe6JT-mknDEPgC8SYLGTyiPb4iKrPkr21v-Dno-61bnHF_iDXFmXCT6bz4_j6WQ8G33Dc3XQ_ZhNn3_8jhLdRgyp6qyyIQOtQ8BXau2sApcaes6gEVk6UEHi45twB0uwOFhEKIKIACBgM-dU-jueMR4e2xnuVrCI8aVrataWijrYFUbQLeFaD0KRR6UsiKM2PPLdTAujZJqZXw38bA812Z78kbs2ab1xUDO8Yd2R7SkmzZEqR0frLovJk2cEWUBUpQebZhWbQu68kTkowuHCFU67GSfBMIgMiF6XUd5SK43OSHYIh-xg0s5MckKrA26Y4jQ0GWT-F1RIv46TIMqRx5i8fifWu-zW_R8yMI8YDt99wOesBvuZ3-27sZRI8Zs92i6aN6OY8gB75r5SfMZ7z7NF78Bri4Mvg |
| linkProvider | Wiley-Blackwell |
| linkToHtml | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V1LbxMxELZKCoILb0RoAR_oCa3IOt6HDwgF2pCoSRSJgsrJ9dpjWpVmw2YB9U_xG5nZRwkHeuuB00ore-TH55nP9niGsReRUA5kGAZIiVQgTeaCFCQEUWK8807FqvK2-DRJZrP08FDNN9iv9i0MuVW2OrFS1C63dEb-CqktWjukv_03y28BZY2i29U2hUYNi304_4lbttXr8S7O744Qw72Dd6OgySoQWJnEURAqnzrvcaOQRUaCjU2aejDIkxwob3Cb5lFfe-j1fBgmHkJAs-aEtRLJu0PGgnKvsU1JYO-wzfl4Ov-8dqqDDELIxsO-JxQdLsi9AV3Y0ROYNdtXpQjAT45L-S96u06SKys3vPO_jc9ddrvh03xQL4B7bAMW99mN91W-4vMH7GTASeMVcFw76vPqngqKBR9RojuKqQB83iwfPiXvxPqsZ8V3TWn4Byj5sMjPOFbic4oEsmyCmvPxWZXgCWvbU1TKD9nHK-nnI9ZZ5At4zLg0aZL2DcSpNzLzoLIozBxCXXgpTei77GU779o2raQMIF915QIglF5HSZftXJRe1iFH_lHuLUHoogwFCq9-5MUX3QycDuMI-mHsEKxKZhmoxFF4IhVZ5N19i0K2CIAa-RYFDbbkXWVLLYiXR6LLtluw6Ua3rfQfpGG_Kqxe2kyNioT2vdGTy4U9ZzdHB9OJnoxn-1vsFomoHUu3WacsvsNTdt3-KE9WxbNm0XF2dNU4_g3as2eC |
| linkToPdf | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V1Lb9QwELbKFhAX3oilBXygJxR143UePiC0sF26aruKxEPl5Dr2mFalmyUbQP1r_Dpm8ijLgd564BQpsi3H-Wb82f48w9iLSCgHMgwDpEQqkCZ3QQoSgigx3nmnYlWrLT7tJ7NZeniosjX2q7sLQ7LKzifWjtoVlvbIt5Ha4myH9He47VtZRDaevF58CyiDFJ20duk0GojswflPXL4tX03H-K-3hJjsfHi7G7QZBgIrkzgKQuVT5z0uGvLISLCxSVMPBjmTA-UNLtk8-m4Pg4EPw8RDCDjFOWGtRCLvkL1gu9fYOlJyKXpsPZseZJ9XdniQTQjZqu0HQtFGg9wZ0eEdXYdZmQfrdAH4KNCs_6K6q4S5nvEmd_7nsbrLbrc8m48aw7jH1mB-n914V-cxPn_ATkacPGEJx42An9fnV1DO-S4lwKNYC8Cz1qz4AakWmz2gJR-byvD3UPFJWZxxrMQzihCyaIOd8-lZnfgJa9tTdNYP2ccr-c5HrDcv5vCYcWnSJB0aiFNvZO5B5VGYOzQB4aU0oe-zlx0GtG17SZlBvupaGiCUXkVMn21dlF40oUj-Ue4NwemiDAUQr18U5RfdDpwO4wiGYezQYyuZ56ASR2GLVGSRjw8tNrJBYNTIwyiYsCXVla20IL4eiT7b7ICnW5-31H9Qh99V4_bSbmp0MLQejp5c3thzdhPBq_ens70NdotaaPSmm6xXld_hKbtuf1Qny_JZa3-cHV01jH8DRxFwQg |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=A+Comprehensive+Northern+Hemisphere+Particle+Microphysics+Data+Set+From+the+Precipitation+Imaging+Package&rft.jtitle=Earth+and+space+science+%28Hoboken%2C+N.J.%29&rft.au=King%2C+Fraser&rft.au=Pettersen%2C+Claire&rft.au=Bliven%2C+Larry+F.&rft.au=Cerrai%2C+Diego&rft.date=2024-05-01&rft.issn=2333-5084&rft.eissn=2333-5084&rft.volume=11&rft.issue=5&rft_id=info:doi/10.1029%2F2024EA003538&rft.externalDBID=n%2Fa&rft.externalDocID=10_1029_2024EA003538 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=2333-5084&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=2333-5084&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=2333-5084&client=summon |