YaBeSH Engineering and Technology Library

    • Journals
    • PaperQuest
    • YSE Standards
    • YaBeSH
    • Login
    View Item 
    •   YE&T Library
    • AMS
    • Journal of Atmospheric and Oceanic Technology
    • View Item
    •   YE&T Library
    • AMS
    • Journal of Atmospheric and Oceanic Technology
    • View Item
    • All Fields
    • Source Title
    • Year
    • Publisher
    • Title
    • Subject
    • Author
    • DOI
    • ISBN
    Advanced Search
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Archive

    Estimation of Random Error Statistics in High-Resolution Radiosondes, ERA-Interim, and COSMIC Radio Occultation Soundings in the Northeast Pacific Ocean during the MAGIC Campaign

    Source: Journal of Atmospheric and Oceanic Technology:;2022:;volume( 039 ):;issue: 009::page 1387
    Author:
    Xuelei Feng
    ,
    Richard Anthes
    ,
    Jeremiah Sjoberg
    DOI: 10.1175/JTECH-D-21-0171.1
    Publisher: American Meteorological Society
    Abstract: Random errors (uncertainties) in COSMIC radio occultation (RO) soundings, ERA-Interim (ERAi) reanalyses, and high-resolution radiosondes (RS) are estimated in the northeast Pacific Ocean during the MAGIC campaign in 2012 and 2013 using the three-cornered hat method. Estimated refractivity and bending angle errors peak at ∼2 km, and have a secondary peak at ∼15 km. They are related to vertical and horizontal gradients of temperature and water vapor and associated atmospheric variability at these two levels. MAGIC RS refractivity and bending angles obtained from forward models have the largest uncertainties, followed by COSMIC RO soundings. ERAi has the smallest uncertainties. The large RS uncertainties can be primarily attributed to representativeness errors (differences). Differences in space and time of the RO and model datasets from the RS observations, error correlations among datasets, and the small sample size are other possible reasons contributing to these differences of estimated error statistics. RO temperature and humidity are retrieved from refractivity using a one-dimensional variational (1D-Var) method from the COSMIC Data Analysis and Archive Center (CDAAC). The estimated errors for COSMIC temperature are comparable to those of the MAGIC RS except near 1 km, where they are much higher. The estimated errors for COSMIC specific humidity are similar to the MAGIC specific humidity errors below ∼5 km and much smaller above this level. Estimates of COSMIC random errors based on ERAi, JRA-55, and MERRA-2 reanalyses in the same region, as well as comparison with estimates from other studies, support the reliability of our estimates.
    • Download: (968.4Kb)
    • Show Full MetaData Hide Full MetaData
    • Item Order
    • Go To Publisher
    • Statistics

      Estimation of Random Error Statistics in High-Resolution Radiosondes, ERA-Interim, and COSMIC Radio Occultation Soundings in the Northeast Pacific Ocean during the MAGIC Campaign

    URI
    https://yetl.yabesh.ir/yetl1/handle/yetl/4290413
    Collections
    • Journal of Atmospheric and Oceanic Technology

    Show full item record

    contributor authorXuelei Feng
    contributor authorRichard Anthes
    contributor authorJeremiah Sjoberg
    date accessioned2023-04-12T18:53:03Z
    date available2023-04-12T18:53:03Z
    date copyright2022/09/01
    date issued2022
    identifier otherJTECH-D-21-0171.1.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4290413
    description abstractRandom errors (uncertainties) in COSMIC radio occultation (RO) soundings, ERA-Interim (ERAi) reanalyses, and high-resolution radiosondes (RS) are estimated in the northeast Pacific Ocean during the MAGIC campaign in 2012 and 2013 using the three-cornered hat method. Estimated refractivity and bending angle errors peak at ∼2 km, and have a secondary peak at ∼15 km. They are related to vertical and horizontal gradients of temperature and water vapor and associated atmospheric variability at these two levels. MAGIC RS refractivity and bending angles obtained from forward models have the largest uncertainties, followed by COSMIC RO soundings. ERAi has the smallest uncertainties. The large RS uncertainties can be primarily attributed to representativeness errors (differences). Differences in space and time of the RO and model datasets from the RS observations, error correlations among datasets, and the small sample size are other possible reasons contributing to these differences of estimated error statistics. RO temperature and humidity are retrieved from refractivity using a one-dimensional variational (1D-Var) method from the COSMIC Data Analysis and Archive Center (CDAAC). The estimated errors for COSMIC temperature are comparable to those of the MAGIC RS except near 1 km, where they are much higher. The estimated errors for COSMIC specific humidity are similar to the MAGIC specific humidity errors below ∼5 km and much smaller above this level. Estimates of COSMIC random errors based on ERAi, JRA-55, and MERRA-2 reanalyses in the same region, as well as comparison with estimates from other studies, support the reliability of our estimates.
    publisherAmerican Meteorological Society
    titleEstimation of Random Error Statistics in High-Resolution Radiosondes, ERA-Interim, and COSMIC Radio Occultation Soundings in the Northeast Pacific Ocean during the MAGIC Campaign
    typeJournal Paper
    journal volume39
    journal issue9
    journal titleJournal of Atmospheric and Oceanic Technology
    identifier doi10.1175/JTECH-D-21-0171.1
    journal fristpage1387
    journal lastpage1394
    page1387–1394
    treeJournal of Atmospheric and Oceanic Technology:;2022:;volume( 039 ):;issue: 009
    contenttypeFulltext
    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian
     
    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian