Abstract
The Tropical Rainfall Measuring Mission (TRMM) and Global Precipitation Mission (GPM) are the most important and widely used data sources in several applications—e.g., forecasting drought and flood, and managing water resources—especially in the areas with sparse or no other robust sources. This study explored the accuracy and precision of satellite data products over a span of 18 years (2000–2017) using synoptic ground station data for three regions in Iran with different climates, namely (a) humid and high rainfall, (b) semi-arid, and (c) arid. The results show that the monthly precipitation products of GPM and TRMM overestimate the rainfall. On average, they overestimated the precipitation amount by 11% in humid, by 50% in semi-arid, and by 43% in arid climate conditions compared to the ground-based data. This study also evaluated the satellite data accuracy in drought and wet conditions based on the standardized precipitation index (SPI) and different seasons. The results showed that the accuracy of satellite data varies significantly under drought, wet, and normal conditions and different timescales, being lowest under drought conditions, especially in arid regions. The highest accuracy was obtained on the 12-month timescale and the lowest on the 3-month timescale. Although the accuracy of the data is dependent on the season, the seasonal effects depend on climatic conditions.
Highlights
Water is a major part of a country’s economic and social development, and precipitation is the principal source of freshwater on the Earth
The provision of accurate precipitation data leads to improvements in various agricultural applications, water resource management, and natural disaster forecasting
Despite the advantages of satellite precipitation products, remote sensing measurements are inaccurate in some parts of the world, leading to incorrect results and unreliable interpretations
Summary
Water is a major part of a country’s economic and social development, and precipitation is the principal source of freshwater on the Earth. Efficient management in this field needs accurate and precise information on precipitation and its spatio-temporal variations [1]. Precipitation data are used in many areas, such as flood modeling [4], landslides [5], heavy rain forecast [6], water resource management [7], drought monitoring [8], hydrological modeling [9], meteorological applications [10,11], and improving crop yield and soil moisture estimation [12]. Reliable measurements of areal precipitation are still the major challenge of hydrology research and water management in all their sub-fields [13,14,15]. Rainfall timing and spatial distribution make reliable measurements even more complicated in many semi-arid, arid, and mountainous regions, while precipitation gauges are often sparsely distributed [15,16,17]
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