Impacts of active satellite sensors' low-level cloud detection limitations on cloud radiative forcing in the Arctic
Advanced Search
Select up to three search categories and corresponding keywords using the fields to the right. Refer to the Help section for more detailed instructions.

Search our Collections & Repository

For very narrow results

When looking for a specific result

Best used for discovery & interchangable words

Recommended to be used in conjunction with other fields

Dates

to

Document Data
Library
People
Clear All
Clear All

For additional assistance using the Custom Query please check out our Help Page

i

Impacts of active satellite sensors' low-level cloud detection limitations on cloud radiative forcing in the Arctic

  • 2022

  • By Liu, Yinghui
  • Source: Atmospheric Chemistry and Physics, 22(12), 8151-8173
Filetype[PDF-7.46 MB]


Select the Download button to view the document
This document is over 5mb in size and cannot be previewed
Details Supporting Files You May Also Like

Details:

  • Journal Title:
    Atmospheric Chemistry and Physics
  • Personal Author:
    Liu, Yinghui
  • NOAA Program & Office:
    NOAA General Documents
  • Description:
    Previous studies revealed that satellites sensors with the best detection capability identify 25 %–40 % and 0 %–25 % fewer clouds below 0.5 and between 0.5–1.0 km, respectively, over the Arctic. Quantifying the impacts of cloud detection limitations on the radiation flux are critical especially over the Arctic Ocean considering the dramatic changes in Arctic sea ice. In this study, the proxies of the space-based radar, CloudSat, and lidar, CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations), cloud masks are derived based on simulated radar reflectivity with QuickBeam and cloud optical thickness using retrieved cloud properties from surface-based radar and lidar during the Surface Heat Budget of the Arctic Ocean (SHEBA) experiment. Limitations in low-level cloud detection by the space-based active sensors, and the impact of these limitations on the radiation fluxes at the surface and the top of the atmosphere (TOA), are estimated with radiative transfer model Streamer. The results show that the combined CloudSat and CALIPSO product generally detects all clouds above 1 km, while detecting 25 % (9 %) fewer in absolute values below 600 m (600 m to 1 km) than surface observations. These detection limitations lead to uncertainties in the monthly mean cloud radiative forcing (CRF), with maximum absolute monthly mean values of 2.5 and 3.4 Wm−2 at the surface and TOA, respectively. Cloud information from only CALIPSO or CloudSat lead to larger cloud detection differences compared to the surface observations and larger CRF uncertainties with absolute monthly means larger than 10.0 Wm−2 at the surface and TOA. The uncertainties for individual cases are larger – up to 30 Wm−2. These uncertainties need to be considered when radiation flux products from CloudSat and CALIPSO are used in climate and weather studies.
  • Keywords:
  • Source:
    Atmospheric Chemistry and Physics, 22(12), 8151-8173
  • DOI:
  • ISSN:
    1680-7324
  • Format:
    PDF
  • Publisher:
    Copernicus GmbH
  • Document Type:
    Journal Article
  • License:
  • Rights Information:
    CC BY
  • Compliance:
    Library
  • Main Document Checksum:
  • Download URL:
  • File Type:

You May Also Like

Checkout today's featured content at repository.library.noaa.gov

Version 3.27.1