Journal cover Journal topic
Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

IF value: 3.668
IF3.668
IF 5-year value: 3.707
IF 5-year
3.707
CiteScore value: 6.3
CiteScore
6.3
SNIP value: 1.383
SNIP1.383
IPP value: 3.75
IPP3.75
SJR value: 1.525
SJR1.525
Scimago H <br class='widget-line-break'>index value: 77
Scimago H
index
77
h5-index value: 49
h5-index49
Preprints
https://doi.org/10.5194/amt-2020-111
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-2020-111
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  20 Apr 2020

20 Apr 2020

Review status
A revised version of this preprint was accepted for the journal AMT and is expected to appear here in due course.

Calibration of global MODIS cloud amount using CALIOP cloud profiles

Andrzej Z. Kotarba Andrzej Z. Kotarba
  • Space Research Centre, Polish Academy of Sciences, 00-716 Warsaw, Poland

Abstract. The Moderate Resolution Imaging Spectroradiometer (MODIS) cloud detection procedure classifies instantaneous fields of view (IFOV) as either confident cloudy, probably cloudy, probably clear, or confident clear. The cloud amount calculation requires quantitative cloud fractions to be assigned to these classes. The operational procedure used by NASA assumes that confident clear and probably clear IFOV are cloud-free (cloud fraction 0 %), while the remaining categories are completely filled with clouds (cloud fraction 100 %). This study demonstrates that this best guess approach is unreliable, especially on a regional/ local scale. We use data from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument flown on the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) mission, collocated with MODIS/ Aqua IFOV. Based on 33,793,648 paired observations acquired in January and July 2015, we conclude that actual cloud fractions to be associated with MODIS cloud mask categories are 21.5 %, 27.7 %, 66.6 %, and 94.7 %. Spatial variability is significant, even within a single MODIS algorithm path, and the operational approach introduces uncertainties of up to 30 % of cloud amount, notably in the polar regions at night, and in selected locations over the northern hemisphere. Applications of MODIS data at ~10 degrees resolution (or finer) should first assess the extent of the error. Uncertainties were related to the efficiency of the cloud masking algorithm. Until the algorithm can be significantly modified, our method is a robust way to calibrate (correct) MODIS estimates. It can be also used for MODIS/ Terra data, and other missions where the footprint is collocated with CALIPSO.

Andrzej Z. Kotarba

Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement

Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement

Andrzej Z. Kotarba

Andrzej Z. Kotarba

Viewed

Total article views: 327 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
240 74 13 327 9 12
  • HTML: 240
  • PDF: 74
  • XML: 13
  • Total: 327
  • BibTeX: 9
  • EndNote: 12
Views and downloads (calculated since 20 Apr 2020)
Cumulative views and downloads (calculated since 20 Apr 2020)

Viewed (geographical distribution)

Total article views: 286 (including HTML, PDF, and XML) Thereof 286 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Saved

No saved metrics found.

Discussed

No discussed metrics found.
Latest update: 21 Sep 2020
Publications Copernicus
Download
Short summary
Paper evaluates the operational approach for producing global (Level3 product) cloud amount based on MODIS cloud masks (Level2). Using CALIPSO we calculate the actual cloud fractions for each cloud mask category, which are 21.5 %, 27.7 %, 66.6 %, and 94.7 % instead of assumed 0 %, 0 %, 100 % and 100 %. Consequently we find the operational procedure unreliable, especially on a regional/ local scale. A methods is suggested how to correct/calibrate MODIS global data using CALIPSO detections.
Paper evaluates the operational approach for producing global (Level3 product) cloud amount...
Citation