[1] The climatological diurnal cycle of precipitation in the tropics is analyzed using data from rain gauges on ocean buoys and satellite measurements by the Tropical Rainfall Measuring Mission (TRMM) satellite. The ocean buoy data are from the NOAA/Pacific Marine Environmental Laboratory Tropical Atmosphere-Ocean/Triangle Trans-Ocean buoy Network in the tropical Pacific Ocean. TRMM data are from the precipitation radar (PR) and the TRMM microwave imager (TMI). Climatological hourly mean precipitation rates are analyzed in terms of the diurnal and semidiurnal harmonics. Both data sets confirm an early morning peak in precipitation over ocean regions. The amplitude of the diurnal harmonic over the oceans is typically less than 25% of the mean precipitation rate. Over tropical land masses the rainfall peaks in the afternoon and evening hours. The relative amplitude of the diurnal harmonic over land is larger than over the ocean, often exceeding 50% of the mean rain rate. Previously noted differences between the TMI and PR rainfall retrievals persist in the diurnal cycle. On average the TMI measures more rainfall than the PR and has a larger diurnal variation. Phase differences between the two instruments do not show a consistent bias.

Background: For the past few years, scientific controversy has surrounded the large number of errors in forensic and literature mitochondrial DNA (mtDNA) data. However, recent research has shown that using mtDNA phylogeny and referring to known mtDNA haplotypes can be useful for checking the quality of sequence data.

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In this study, the effect of zero measurements on the spatial correlation function of rainfall is analyzed for the quantification of a rainfall field. The use of a bivariate mixed distribution function made it possible to analyze and compare the spatial correlation functions for these three different data sets: only the positive measurements at both gauge locations, positive measurements at either one or both gauge locations, and all measurements including zero at both locations. As an example, the spatial correlation functions are derived for the Geum River Basin, Korea and evaluated for the wet and dry seasons, respectively. Results show that the effect of zero measurements on spatial correlation structures is significant during the wet season, when the interstation correlations were estimated significantly lower than those during the dry season. It was also found that only the case considering positive measurements are valid for the quantification of rainfall field. Even during the wet season, the inter-station correlation coefficients derived by considering the zero measurements show their high variability along with many abnormally looking high estimates, which made the quantification of the spatial correlation function become very ambiguous.