CONUS and sub-regional monthly cloudiness supporting for the trend analysis: "CONUS Cloud Pattern Change 1980-2020" Vo T.T., Hu L., Xue L., Chen S. (2024)

The dataset supporting for the publication: "CONUS Cloud Pattern Change 1980-2020" Vo T.T., Hu L., Xue L., Chen S. (2024), Journal of Climate. 

The data format is in tabular form (.csv, comma delimited). Each row is the monthly aggregated for each sub-region  More specifically, the description of each column with associated with its unit formatted in the table are listed as follows:

datetime: time of the observation (formatted as month/day/year)

original_time_series: original cloud coverage before processing using the trend analysis mentioned in the paper (unit: percentage, %)

enso_neutral: cloud coverage removing the ENSO effect using linear regression method followed by Gu and Adler 2011 (unit: percentage, %)

cloud_coverage: cloud coverage removing the ENSO effect and seasonality and remainder (refer to the cloud coverage used in the manuscript) using Seasonal Decomposition of Time Series by Loess (STL) method (unit: percentage, %)

region_name_list: name of the sub-region

cloud_type: certain cloud type (all clouds refers to total clouds)

References: 

Gu, G., & Adler, R. F. (2011). Precipitation and temperature variations on the interannual time scale: Assessing the impact of ENSO and volcanic eruptions. Journal of Climate, 24(9), 2258–2270. https://doi.org/10.1175/2010JCLI3727.1

Cleveland, R. B., Cleveland, W. S., & Terpenning, I. (1990). STL: A Seasonal-Trend Decomposition Procedure Based on Loess. Journal of Official Statistics, 6(1), 3. http://ezproxy.montevallo.edu:2048/login?url=https://www.proquest.com/scholarly-journals/stl-seasonal-trend-decomposition-procedure-based/docview/1266805989/se-2?accountid=12538