Creation of NCEP/NOAA Data Correction Factors with Data Observations to Fill in Blank Data

Abstract

The gaps between meteorological observation data have triggered scientists to find methods that can be applied to replace the unavailable data. In this study,  the authors tried to find alternative methods to fill in blank data between observation stations with NCEP / NOAA satellite data. To fill in the blank data, a satellite data correction factor was determined from the observation data. Gridded satellite data was approached by interpolating distance weighting (IDW) technique. Correction factors calculated from   the   reduction   in   observation   data   and satellite IDW (NCEP / NOAA) were collected in a

classy frequency distribution table of the observation data. This process would lead to finding the mode,  and the correction factor in the region is the median of the model. This research was conducted in the West Kalimantan region using   6   BMKG   meteorological   observations station including Mempawah, Ketapang, Paloh, Nangapinoh, Sintang, and Putusibau. The results showed that the higher the elevation of an area, the greater correction value (the highest elevation in Putussibau 40-50 meters above sea level, the greatest correction  value  1.5°C)  achieved. This correction value was possible to be applied to fill in the blank data, by adding them to the satellite data of the same element.