Evaluation of diurnal variation of GPM IMERG‐derived summer precipitation over the contiguous US using MRMS data

Abstract

Precipitation Measurement (GPM), which provides merged microwave and infrared satellite precipitation estimates, over the contiguous US. The study focuses on diurnal variations in precipitation during a two-year summer period (June-August, 2014-2015). The normalized amplitude and phase of the diurnal cycle of IMERG are evaluated against those of ground reference from the Multi-Radar/Multi-Sensor system in terms of precipitation amount, frequency and intensity on a 1 • /1 h scale. IMERG well captures large-scale regional features of the diurnal cycle of precipitation and overall agrees well with the reference for both diurnal and semidiurnal variations. The comparison results indicate that the IMERG precipitation estimates can be a reliable alternative to ground-based measurements even at the subdaily scale; however, region-specific data discrepancies are still observed. For instance, we reveal that IMERG substantially overestimates normalized amplitude of diurnal precipitation in the central US, while IMERG tends to underestimate diurnal variations over the mountain regions in the western and eastern US. In terms of phase, we find a significant difference in the timing of peak precipitation between convective and stratiform regions of mesoscale convective systems (MCSs) over the Great Plains. This time shift is more apparent during the mature and dissipation stages of MCSs, which lead to relatively early peaks in the diurnal cycle of precipitation from IMERG. This phase bias implies a higher sensitivity of IMERG towards the convective regions of MCSs, supposedly because of the brightness temperature depression coming from ice particles aloft sampled by spaceborne passive microwave sensors. Such discrepancy between the actual and satellite-estimated precipitation timing can be challenging, e.g. when the satellite data are used to study subdaily precipitation processes or to validate numerical simulations. Consequently, our assessment of the IMERG performances highlights the need for improvements in the IMERG system.

Evaluation of precipitation datasets against local observations in southwestern Iran

“…It might be associated with infrared sensors F I G U R E 2 Comparison of mean monthly precipitation (mm per month) for different datasets (symbols) across all grids of Karun basin (2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015). Red lines denote datasets which did not employ gauge data, while blue lines indicate datasets which use some gauge records, and turquoise lines refer to datasets which extensively used gauge observations T A B L E 2 Statistical measures of the evaluated monthly datasets over Karun basin (2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015) Group Dataset having difficulties to detect warm cloud process especially over mountains (Dinku et al, 2018;O and Kirstetter, 2018). The underestimation in SM2RAIN-CCI could be related to the fact that once the surface soil is saturated after intense or long-lasting precipitation events, no additional increase is possible such that no additional precipitation can be deduced from the soil moisture data (Brocca et al, 2013).…”

The Role of Sea Surface Temperature Forcing in the Life-Cycle of Mediterranean Cyclones

“…More details can be found in the following articles and references within [42][43][44][45][46]. It should be mentioned that several studies [47][48][49] have indicated an overestimation of IMERG products in the estimated precipitation under heavy rainfall events.…”

GPM-Derived Climatology of Attenuation Due to Clouds and Precipitation at Ka-Band

“…High spatial and temporal resolution satellite precipitation products, such as IMERG, offer an unprecedented opportunity to investigate the diurnal cycle. Reference [42] showed that the 30-min temporal resolution IMERG well captures the diurnal and semidiurnal precipitation patterns identified by Fig. 6.…”

“…In a parallel study [43], we have analyzed the diurnal cycle across the globe using four years of IMERG data (June 2014-May 2018); for each 5 • lat/lon grid box, precipitation occurrence, amount (mean precipitation, including zero values), and intensity (the conditional mean for precipitation >0 mm/h) have been computed at half-hour resolution. These histograms have been fit by diurnal and semidiurnal harmonic functions with a least-squared-error method [42], weighted by their random errors [43]. The importance of the diurnal and semidiurnal cycles has been then evaluated by looking at the amplitudes of the corresponding harmonics, whereas the position of the maximum in the diurnal harmonic provides the timing of the peak.…”