Can IMERG Data Capture the Scaling of Precipitation Extremes With Temperature at Different Time Scales?

• Published in: Geophysical research letters Vol. 49; no. 3
• Main Authors: Hosseini‐Moghari, Seyed‐Mohammad, Tang, Qiuhong
• Format: Journal Article
• Language: English
• Published: Washington John Wiley & Sons, Inc 16.02.2022
• Subjects: Climate change; Data capture; Datasets; dry and wet regions; Extreme weather; Global precipitation; Global warming; HadISD; High temperature; Hourly; Hydrologic data; Measurement; Performance evaluation; Precipitation; Precipitation data; Remote monitoring; Remote sensing; Scaling; scaling factor; Scaling factors; sub‐daily precipitation; Temperature; Temperature dependence; Temporal resolution; the CONUS; Time; United States > US
• ISSN: 0094-8276; 1944-8007
• DOI: 10.1029/2021GL096392

This study evaluates the validity of the Integrated Multisatellite Retrievals for Global Precipitation Measurement (IMERG) in scaling extreme precipitation with temperature (termed scaling factor, SF). To this end, we use Hadley‐Integrated Surface Database (HadISD) data set at 1‐hourly, 6‐hourly, and 24‐hourly scales between 2000 and 2020 over the contiguous United States (CONUS) as a reference data set. Our findings reveal that IMERG can capture changes in precipitation extremes with the temperature at 6‐hourly, and 24‐hourly scales, especially over dry regions. The difference between IMERG's SF and HadISD's SF at 6‐hourly scale is less than 0.3%/°C in dry areas. However, IMERG underestimates SF in wet regions, especially at 1‐hourly scale, up to ∼5%/°C. It is found that IMERG's performance is dependent on temperature, particularly at 1‐hourly scale. IMERG overestimates extreme precipitations when temperatures are below 5°–11°C while the opposite is true at higher temperatures, indicating the need for considering temperature in adjusting IMERG. Plain Language Summary Understanding the scaling rate of precipitation extremes with temperature can help to estimate precipitation extremes under global warming. However, we do not have in situ precipitation data in many parts of the world to monitor changes in precipitation extremes with temperature. The remotely sensed precipitation data sets that are available globally with high spatio‐temporal resolution might be excellent resources to use for this purpose. To discover that, in this study, we evaluated the performance of the Integrated Multisatellite Retrievals for Global Precipitation Measurement (IMERG) as one of the newest precipitation data sets for scaling extreme precipitation with temperature over the contiguous United States. We compared IMERG's results with Hadley‐Integrated Surface Database results at 1‐hourly, 6‐hourly, and 24‐hourly scales. Results indicate IMERG has a considerable performance at 6‐hourly and 24‐hourly time scales. Key Points Integrated Multi‐satellite Retrievals for Global Precipitation Measurement (IMERG) represents well the relationship between precipitation extremes and temperature at 6‐hourly and daily scales IMERG's scaling factors in dry areas are closer to the observations than in wet regions IMERG overestimates (underestimates) hourly precipitation extremes at low (high) temperatures