CLASSIFYING, CONVERGING, SIMULATING OF NSDSAS AND TRMM WEATHER DATA AGGREGATION USING HIERARCHICAL SEARCH ALGORITHM

Mark Anthony  Mercado,; Freedom John  C. Ferrera,; Gene Christopher  P. Romuga,; Jairus Noah  L. Polintan,; Rimmon Gerard  A. Silvala,

CLASSIFYING, CONVERGING, SIMULATING OF NSDSAS AND TRMM WEATHER DATA AGGREGATION USING HIERARCHICAL SEARCH ALGORITHM

Gene Christopher P. Romuga | Jairus Noah L. Polintan | Mark Anthony Mercado | Rimmon Gerard A. Silvala | Freedom John C. Ferrera

Discipline: Computer Science

Abstract:

In predicting yield, there are different weather data needed. Weather variables consist of solar radiation, maximum temperature, minimum temperature, dew point, wind speed, and precipitation. As it is the case with other crop simulation models applications, the aim of the system was generally to prepare the input data to run the model. To run the model, merging and classifying of weather data are required to produce an input for yield prediction. Raw data have two sources, NSDSAS and TRMM. Naval Systems Data Support Activity (NSDSAS) weather data are available global weather data produced by NASA Langley Research Center Power Project funded through NASA Earth Science Directorate Applied Science Program. Tropical Rainfall Measuring Mission (TRMM) is a public available rainfall weather data produced by NASA and obtained from space-borne rain radar and microwave radiometric data covering precipitation over the tropics in a band between 35 degrees north and south latitudes.