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http://dx.doi.org/10.5532/KJAFM.2020.22.3.152

Construction of NCAM-LAMP Precipitation and Soil Moisture Database to Support Landslide Prediction  

So, Yun-Yeong (National Center for AgroMeteorology)
Lee, Su-Jung (National Center for AgroMeteorology)
Choi, Sung-Won (National Center for AgroMeteorology)
Lee, Seung-Jae (National Center for AgroMeteorology)
Publication Information
Korean Journal of Agricultural and Forest Meteorology / v.22, no.3, 2020 , pp. 152-163 More about this Journal
Abstract
The present study introduces a procedure to prepare and manage a high-resolution rainfall and soil moisture (SM) database in the LAMP prediction system, especially for landslide researchers. The procedure also includes converting the data into spatial resolution suitable for their interest regions following proper map projection methods. The LAMP model precipitation and SM data are quantitatively and qualitatively evaluated to identify the model prediction characteristics using the ERA5 reanalysis precipitation and observed 10m depth SM data. A detailed process of converting LAMP Weather Research and Forecasting (WRF) output data for 10m horizontal resolution is described in a step-wise manner, providing technical convenience for users to easily convert NetCDF data from the WRF model into TIF data in ArcGIS. The converted data can be viewed and downloaded via the LAMP website (http://df.ncam.kr/lamp/index.do) of the National Center for AgroMeteorology. The constructed database will contribute to monitoring and prediction of landslide risk prior to landslide response steps and should be data quality controlled by more observation data.
Keywords
Rainfall; Soil moisture; NetCDF; ArcGIS; Map projection; LAMP;
Citations & Related Records
Times Cited By KSCI : 15  (Citation Analysis)
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