Evaluation of satellite-based precipitation estimation over Iran

Pari-Sima Katiraie-Boroujerdy,Nasrin Nasrollahi,Kuo-Lin Hsu,Soroosh Sorooshian

doi:10.1016/j.jaridenv.2013.05.013

Abstract

Precipitation in semi-arid countries such as Iran is one of the most important elements for all aspects of human life. In areas with sparse ground-based precipitation observation networks, the reliable high spatial and temporal resolution of satellite-based precipitation estimation might be the best source for meteorological and hydrological studies. In the present study, four different satellite rainfall estimates (CMORPH, PERSIANN, adjusted PERSIANN, and TRMM-3B42 V6) are evaluated using a relatively dense Islamic Republic of Iran's Meteorological Organization (IRIMO) rain-gauge network as reference. These evaluations were done at daily and monthly time scales with a spatial resolution of 0.25° × 0.25° latitude/longitude. The topography of Iran is complicated and includes different, very diverse climates. For example, there is an extremely wet (low-elevation) Caspian Sea coastal region in the north, an arid desert in the center, and high mountainous areas in the west and north. Different rainfall regimes vary between these extremes. In order to conduct an objective intercomparison of the various satellite products, the study was designed to minimize the level of uncertainties in the evaluation process. To reduce gauge uncertainties, only the 32 pixels, which include at least five rain gauges, are considered. Evaluation results vary by different areas. The satellite products had a Probability of Detection (POD) greater than 40% in the southern part of the country and the regions of the Zagros Mountains. However, all satellite products exhibited poor performance over the Caspian Sea coastal region, where they underestimated precipitation in this relatively wet and moderate climate region. Seasonal analysis shows that spring precipitations are detected more accurately than winter precipitation, especially for the mountainous areas all over the country. Comparisons of different satellite products show that adj-PERSIANN and TRMM-3B42 V6 have better performance, and CMORPH has poor estimation, especially over the Zagros Mountains. The comparison between PERSIANN and adj-PERSIANN shows that the bias adjustment improved the POD, which is a daily scale statistic.

Highlights

IntroductionIn arid and semi-arid regions of the world, estimation of precipitation is of particular interest to the decision makers (i.e., water managers, agriculturalists, industrialists, climatologists, etc.), but is important for human life and activities
In arid and semi-arid regions of the world, estimation of precipitation is of particular interest to the decision makers, but is important for human life and activities
It should be noted that the Tropical Rainfall Measuring Mission (TRMM) 3B42 V6 and adj-PERSIANN data were adjusted with Global Precipitation Climatology Project (GPCP) data

Summary

Introduction

In arid and semi-arid regions of the world, estimation of precipitation is of particular interest to the decision makers (i.e., water managers, agriculturalists, industrialists, climatologists, etc.), but is important for human life and activities. Rainfall data are usually available from gauges that show pointscale measurements. These instruments have the advantage of being direct in-situ measurements, but their poor areal coverage. A number of satellite-based precipitation estimation products with high spatial (quarter latitude/longitude degree) and temporal (hourly) resolution and near-global coverage have been developed. Satellite-based precipitation data are especially useful in semi-arid regions, where ground measurements are very sparse and/or nonexistent. Some of the satellite products use ground-based measurements such as gauge data to reduce the bias. These products are similar in that most of them combine data from passive microwave and thermal infrared

Objectives

Results

Conclusion