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    Global Distribution of Snow Precipitation Features and Their Properties from 3 Years of GPM Observations

    Source: Journal of Climate:;2018:;volume 031:;issue 010::page 3731
    Author:
    Adhikari, Abishek
    ,
    Liu, Chuntao
    ,
    Kulie, Mark S.
    DOI: 10.1175/JCLI-D-17-0012.1
    Publisher: American Meteorological Society
    Abstract: AbstractUsing a 3-yr Global Precipitation Mission (GPM) Ku-band Precipitation Radar (KuPR) dataset, snow features (SFs) are defined by grouping the contiguous area of nonzero solid precipitation. The near-surface wet bulb temperatures calculated from ERA-Interim reanalysis data are used to verify that SFs are colder than 1°C to omit snowfall that melts before reaching the surface. The properties of SFs are summarized to understand the global distribution and characteristics of snow systems. The seasonal and diurnal variations of SFs and their properties are analyzed over Northern and Southern Hemispheric land and ocean separately.To quantify the amount of snow missed by the GPM KuPR and the amount of snow underestimated by the CloudSat Cloud Profiling (CPR), 3-yr KuPR pixel-level data are compared with 4-yr CloudSat CPR observations. The overall underestimation of snowfall during heavy snow events by CPR is less than 3% compared to the combined CPR and KuPR estimates. KuPR underestimates about 52% of weak snow. Only a small percentage of SFs have sizes greater than 10 000 km2 (0.35%), maximum near-surface reflectivity above 30 dBZ (5.1%), or echo top above 5 km (1.6%); however, they contribute 40%, 49.5%, or 30.4% of the global volumetric snow detected by KuPR. Snow in the Northern Hemisphere has stronger diurnal and seasonal variation compared to the Southern Hemisphere. Most of the SFs over the ocean are found with relatively smaller, less intense, and shallower echo tops than over land.
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      Global Distribution of Snow Precipitation Features and Their Properties from 3 Years of GPM Observations

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    contributor authorAdhikari, Abishek
    contributor authorLiu, Chuntao
    contributor authorKulie, Mark S.
    date accessioned2019-09-19T10:08:21Z
    date available2019-09-19T10:08:21Z
    date copyright2/26/2018 12:00:00 AM
    date issued2018
    identifier otherjcli-d-17-0012.1.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4261965
    description abstractAbstractUsing a 3-yr Global Precipitation Mission (GPM) Ku-band Precipitation Radar (KuPR) dataset, snow features (SFs) are defined by grouping the contiguous area of nonzero solid precipitation. The near-surface wet bulb temperatures calculated from ERA-Interim reanalysis data are used to verify that SFs are colder than 1°C to omit snowfall that melts before reaching the surface. The properties of SFs are summarized to understand the global distribution and characteristics of snow systems. The seasonal and diurnal variations of SFs and their properties are analyzed over Northern and Southern Hemispheric land and ocean separately.To quantify the amount of snow missed by the GPM KuPR and the amount of snow underestimated by the CloudSat Cloud Profiling (CPR), 3-yr KuPR pixel-level data are compared with 4-yr CloudSat CPR observations. The overall underestimation of snowfall during heavy snow events by CPR is less than 3% compared to the combined CPR and KuPR estimates. KuPR underestimates about 52% of weak snow. Only a small percentage of SFs have sizes greater than 10 000 km2 (0.35%), maximum near-surface reflectivity above 30 dBZ (5.1%), or echo top above 5 km (1.6%); however, they contribute 40%, 49.5%, or 30.4% of the global volumetric snow detected by KuPR. Snow in the Northern Hemisphere has stronger diurnal and seasonal variation compared to the Southern Hemisphere. Most of the SFs over the ocean are found with relatively smaller, less intense, and shallower echo tops than over land.
    publisherAmerican Meteorological Society
    titleGlobal Distribution of Snow Precipitation Features and Their Properties from 3 Years of GPM Observations
    typeJournal Paper
    journal volume31
    journal issue10
    journal titleJournal of Climate
    identifier doi10.1175/JCLI-D-17-0012.1
    journal fristpage3731
    journal lastpage3754
    treeJournal of Climate:;2018:;volume 031:;issue 010
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian