DISTRIBUSI SPASIAL SPEKTRAL TAHUNAN DAN SEMI-TAHUNAN PRECIPITABLE WATER VAPOR (PWV) DARI DATA INACORS DI INDONESIA

The use of the Global Navigation Satellite System (GNSS) data is not only for positioning, but also used for other studies. One of the Studies of GNSS Data Utilization Beyond Determination of Position is for studies related to Meteorology. One of the variables in the atmosphere that greatly disrupts...

Full description

Saved in:
Bibliographic Details
Main Author: Reza, Mohammad
Format: Final Project
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/65175
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Institut Teknologi Bandung
Language: Indonesia
Description
Summary:The use of the Global Navigation Satellite System (GNSS) data is not only for positioning, but also used for other studies. One of the Studies of GNSS Data Utilization Beyond Determination of Position is for studies related to Meteorology. One of the variables in the atmosphere that greatly disrupts GNSS signal propagation is the water vapor content in the atmosphere. In determining the position of using GNSS, the effects of water vapor must be eliminated to the maximum because it is considered a disruption (noise), but, in a meteorological study it is considered information (signal) which can provide an overview related to physical processes that occur in the atmosphere, by utilizing Water vapor data which is a variable that disrupts GNSS signal propagation, we can learn the meteorological phenomena in Indonesia, in this study it will focus on the annual and semi-annual water vapor cycle. Therefore, in this study, GNSS observation data will be used from INA-Cors. By utilizing GNSS observation data from INA-CORS Station can be lowered into PWV data. PWV data from each observation station in Indonesia will be processed by using Lomb Scargle Periodogram (LSP). Spectral analysis of the periodogram will be carried out so that the period of the period can study meteorological phenomena in Indonesia. In addition, by utilizing periodograms, the author can create a spatial distribution map of an annual spectral and semi-year in Indonesia by utilizing the annual and semi-annual signal strength variables of each period that has been created. Annual and semi-annual water vapor distribution maps in Indonesia can provide information regarding the annual and semi-annual cycle area boundaries that can be useful for future GNSS studies