GPM Annual and Daily Precipitation Data for Real-Time Short-Term Nowcasting: A Pilot Study for a Way Forward in Data Assimilation

Kaiyang Wang,Prateek Singh,Yunqing Xu,Xiaonan Tang,Lingrong Kong,Zixin Yang,Jianli Hao,Fangyu Guo

doi:10.3390/w13101422

Abstract

This study explores the quality of data produced by Global Precipitation Measurement (GPM) and the potential of GPM for real-time short-term nowcasting using MATLAB and the Short-Term Ensemble Prediction System (STEPS). Precipitation data obtained by rain gauges during the period 2015 to 2017 were used in this comparative analysis. The results show that the quality of GPM precipitation has different degrees efficacies at the national scale, which were revealed at the performance analysis stage of the study. After data quality checking, five representative precipitation events were selected for nowcasting evaluation. The GPM estimated precipitation compared to a 30 min forecast using STEPS precipitation nowcast results, showing that the GPM precipitation data performed well in nowcasting between 0 to 120 min. However, the accuracy and quality of nowcasting precipitation significantly reduced with increased lead time. A major finding from the study is that the quality of precipitation data can be improved through blending processes such as kriging with external drift and the double-kernel smoothing method, which enhances the quality of nowcast over longer lead times.

Highlights

Precipitation is regarded as an essential component of global energy and water cycles, and it plays a significant role in the interactions between atmosphere, biosphere and hydrosphere [1]
Accurate estimation and prediction of precipitation is important for a wide range of applications, such as agricultural crop forecasting, monitoring freshwater resources and numerical weather prediction
To evaluate the Global Precipitation Measurement (GPM) Integrated Multi-satellite Retrievals for GPM (IMERG), several steps were carried out, which are presented in Figure 1 below

Summary

Introduction

Precipitation is regarded as an essential component of global energy and water cycles, and it plays a significant role in the interactions between atmosphere, biosphere and hydrosphere [1]. The measurement of precipitation provides essential information to weather forecasters and climate scientists and to a wide range of decision-makers, including agriculturalists, hydrologists, industrialists and emergency managers [2]. Accurate estimation and prediction of precipitation is important for a wide range of applications, such as agricultural crop forecasting, monitoring freshwater resources and numerical weather prediction. In the last three decades, satellite measurement of precipitation has grown to be an uninterrupted, reliable and cost-effective source over large data-void areas [3]. In 1997, NASA sent the first dedicated meteorological precipitation satellite—the Tropical Rainfall Measurement Mission (TRMM) Multi-satellite Precipitation. Analysis (TMPA)—with the National Space Development Agency (NASDA) to measure energy and precipitation exchange across tropical and subtropical areas of the world for 17 years (1997–2014) [4,5].

Objectives

Methods

Conclusion