A range of in situ, satellite and reanalysis products on a common daily 1°×1°latitude/longitude grid were extracted from the Frequent Rainfall Observations on Grids database to help facilitate intercomparison and analysis of precipitation extremes on a global scale. 22 products met the criteria for this analysis, namely that daily data were available over global land areas from 50°S to 50°N since at least 2001. From these daily gridded data, 10 annual indices that represent aspects of extreme precipitation frequency, duration and intensity were calculated. Results were analysed for individual products and also for four cluster types: (i) in situ, (ii) corrected satellite, (iii) uncorrected satellite and (iv) reanalyses. Climatologies based on a common 13-year period (2001-2013) showed substantial differences between some products. Timeseries (which ranged from 13 years to 67 years) also highlighted some substantial differences between products. A coefficient of variation showed that the in situ products were most similar to each other while reanalysis products had the largest variations. Reanalyses however agreed better with in situ observations over extra-tropical land areas compared to the satellite clusters, although reanalysis products tended to fall into 'wet' and 'dry' camps overall. Some indices were more robust than others across products with daily precipitation intensity showing the least variation between products and days above 20 mm showing the largest variation. In general, the results of this study show that global space-based precipitation products show the potential for climate scale analyses of extremes. While we recommend caution for all products dependent on their intended application, this particularly applies to reanalyses which show the most divergence across results. OPEN ACCESS RECEIVED

Using the standardized precipitation evapotranspiration index, this study examines the combined effects of El Niño-Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO) on global droughts in terms of magnitude, timing, and duration. The ENSO-affected drought hotspots are identified based on drought magnitude and probability of occurrence: five hotspots for El Niño (Amazon, India, central China, Indonesia, and eastern Australia) and four hotspots for La Niña (southeastern United States, southern South America, East Africa, and Southwest Asia). When ENSO and PDO are in phase, most of the hotspots exhibit an intensification and expansion of drought, more clearly at longer time scales (6-12 months), supporting previous studies. Interestingly, the in-phase PDO advances El Niño-induced drought onset by early summer of the previous year, whereas it delays the withdrawal of La Niña-induced drought until the end of the event year. This asymmetric response is found to be in part associated with the earlier start and later end of El Niño itself during warm PDO, which does not hold for the La Niña/cold PDO composites. Further analyses of the responses of precipitation (P) and potential evapotranspiration (PET) to different ENSO-PDO combinations suggest the important role of P reduction in determining drought magnitude and timing over most of the hotspots, with some contribution of enhanced PET to drier conditions over a few La Niña hotspots. It is also found that the PDO modulation of El Niño-induced drought occurs primarily through the eastern Pacific El Niño with a limited influence on the central Pacific El Niño.

The ability of regional climate models (RCMs) to accurately simulate the current climate is increasingly important for impact assessments over Southeast Asia (SEA), identified as one of the world's most vulnerable regions to climate change. In this study, we evaluate the performance of a set of regional highresolution simulations from the Coordinated Regional Climate Downscaling Experiment-SEA (CORDEX-SEA) in simulating rainfall over the region. Simulations of the 1982-2005 seasonal mean climatology of daily precipitation and precipitation distribution over land are compared to observations from different sources (i.e., in situ-based and satellite-based). We also evaluate to what extent the precipitation distribution in RCMs is closer to observations than their associated forcing global climate models (GCMs). Observational estimates of precipitation over SEA have large uncertainties, making the model evaluations complicated. Despite these difficulties, our results highlight that RCMs can reproduce some complexities in the spatial distribution of seasonal rainfall but generally have a larger wet bias than GCMs. This is particularly true for the extremes in which RCMs show a large overestimation of rainfall intensity. There are some precipitation quantiles and grid points in which RCMs show limited reductions in biases compared to observations, but there is no consistency across all simulations and RCMs are generally further away from observations than their forcing GCMs. We find that greater intensity in RCMs over CORDEX-SEA compared to their associated forcing GCMs is firstly associated with the increased supply of moisture from both local and large-scale sources. Second, a widespread increase in convective precipitation is found across the region in RCMs. Our findings suggest that a model's ability to simulate precipitation over the region relies more on the RCM setup itself (e.g., parameterization scheme), rather than its forcing GCM. This should be considered when assessing the reliability of RCM precipitation simulations for future projections.