The Use of Weather Research and Forecasting Model to Predict Rainfall in Tropical Peatland: 1. Model Parameterization

Abstract

Rainfall dynamics play a vital role in tropical peatland by providing sufficient water to keep peat moist throughout the year. Therefore, information of rainfall data either historical or forecasting data has risen in recent decades especially for an alert system of fire. Here the Weather and Research Forecasting (WRF) model may act as a tool to provide forecasting weather data. This study aims to do parameterization on WRF parameters for peatland in Sumatra, and to perform bias correction on the WRF’s rainfall output with observed data. We performed stepwise calibration to choose the best five physical schemes of WRF for use in the study area. The output WRF’s rainfall was bias corrected by spatially observed rainfall data for 2019 at day resolution. Our results showed the following schemes namely (i) Eta scheme for cloud microphysical parameters; (ii) GD scheme for cumulus cloud parameters, (iii) MYJ scheme for planetary boundary layer parameters; (iv) RRTM for longwave radiation; and (v) New Goddard schemes for shortwave radiation are best combination for being used to predict rainfall in maritime continent. The spatially interpolated observed rainfall with the Inverse Distance Weighting (IDW) was outperformed for calibration process of WRF’s rainfall as shown by statistical indicators used in this study. Further, the findings have contributed to advance knowledge of rainfall forecasting in maritime continent, particularly in providing data to support the development of fire danger rating system for Indonesian peatland.

The Impact of Rewetting Peatland on Fire Hazard in Riau, Indonesia

“…The Weather Research and Forecasting model (WRF) is the longest-lasting and most advanced numerical weather prediction system. Since its development in 2001, the WRF model has been widely used for a broad range of applications across different topics [23,[26][27][28][29].…”

“…Soil moisture was a proxy for water table (Equation ( 4)). In this research, we followed the approach proposed by Sanusi et al [23] that used characteristics of peat water retention to determine the top and lower boundary of moisture (water suction at saturation and wilting point, respectively). Then, we rescaled the distribution of soil moisture at each grid as an input for Equation ( 4).…”

“…WRF has widely been applied in fire research by providing weather input data of drought-fire models, such as in Australia [20], Poland [21], and the United States [22]. In Indonesia, the applicability of the WRF of fire assessment has been initiated recently in Sumatra peatlands [23,24].…”

Assessment of hybrid machine learning algorithms using TRMM rainfall data for daily inflow forecasting in Três Marias Reservoir, eastern Brazil

“…Ref. [ 21 ] utilized the Weather Research and Forecasting (WRF) model for rainfall prediction in tropical peatlands. They performed parameterization of the WRF for the maritime continent and identified the optimal combination of physical schemes for accurate rainfall prediction, contributing to the creation of a fire risk assessment system for Indonesian peatlands.…”