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Precipitation has a strong and constant impact on different economic sectors, environment and social activities all over the world. An increasing interest for monitoring and estimating the precipitation characteristics can be claimed in the last decades. However, in some areas, the ground-based network is still sparse and the spatial data coverage insufficiently addresses the needs. In the last decades, different interpolation methods provide an efficient response for describing the spatial distribution of precipitation. In this study, we compare the performance of seven interpolation methods used for retrieving the mean annual precipitation over the mainland Portugal, as follows: local polynomial interpolation (LPI), global polynomial interpolation (GPI), radial basis function (RBF), inverse distance weighted (IDW), ordinary cokriging (OCK), universal cokriging (UCK) and empirical Bayesian kriging regression (EBKR). We generate the mean annual precipitation distribution using data from 128 rain gauge stations covering the period 1991 to 2000. The interpolation results were evaluated using cross-validation techniques and the performance of each method was evaluated using mean error (ME), mean absolute error (MAE), root mean square error (RMSE), Pearson’s correlation coefficient (R) and Taylor diagram. The results indicate that EBKR performs the best spatial distribution. In order to determine the accuracy of spatial distribution generated by the spatial interpolation methods, we calculate the prediction standard error (PSE). The PSE result of EBKR prediction over mainland Portugal increases from south to north.

Under the global climate change, research on the response characteristic of precipitation to climate change and its variation trend is of great significance. By employing the empirical orthogonal function (EOF), the TPFW-MK test and the PCD and PCP method, the multiple-time scale variability and spatial distribution of precipitation in different climate zones are studied by the monthly precipitation data from 122 meteorological stations in Northwestern China (NWC) during 1960–2015. The results indicated that the annual precipitation in 68% of the stations exhibited upward trends and the average annual precipitation increased at 2.6 mm per decade from 1960 to 2015. Opposite variation trends of annual precipitation were detected in different climate zones, significant positive trends in arid and semiarid zones, but negative trends in humid and semi-humid zones. Based on the Z-statistics by TPFW-MK test, winter precipitation exhibited a generally increasing trend, but the variation of summer precipitation showed remarkable regional differences. Mutation test indicated that middle 1980s was the major mutation point of precipitation series. According to the CDF plots, the proportion of precipitation between 0 and 300 mm decreased, while the proportion of precipitation more than 700 mm increased. The EOF analyses showed that the spatial distribution of precipitation had three typical modes, whole area consistent type, east–west opposite type and north–south opposite type. The greatest proportion of the whole area pattern revealed that the climate condition was controlled by some common factors despite the different variation trends. Trend analyses of PCD and PCP indicated that the inter-annual precipitation in about 77.3% of the stations had a high concentration degree, the unevenness of inter-annual precipitation distribution increased in humid and semi-humid zones and decreased in arid and semiarid zones, which was opposite to the variation trends of annual precipitation. Besides, the concentrate period of inter-annual precipitation had advanced over the last decades. The results will provide reliable references for addressing climate change, protecting ecological environment and preventing meteorological disasters.

Inhomogeneous spatiotemporal distribution of precipitation tends to causecauses floods and waterlogging,; an in-depth analysis of the inhomogeneous spatiotemporalthis distribution of precipitation can provide scientific methods for coping with droughts and floods and guiding agricultural production. On the basis ofBased on the monthly precipitation and temperature field data collected by 119 stations in Northwest China from 1961 to 2015, the interannual variability of the precipitation concentration index (PCI) and monthly precipitation accounting for the average proportion of annual precipitation (MPPAP) was detected using the Mann–Kendall test and Sen’s slope estimator; further, the degree of importance of the factors that affectaffecting the inhomogeneous distribution of precipitation were analyzed using Random Forestsrandom forests (RF). The resultsResults show that thePCI’s spatial distribution of PCI in Northwest China generally decreases and increases in the east and west, respectively; further, the results show that thePCI’s interannual variability of PCI significantly fluctuates substantially in southern Xinjiang and the west of the Qinghai Plateau but, and relatively slightly in other areas. As for theRegarding PCI’s multi-year average variability of PCI, the annual precipitation distribution tends to be homogeneous in most areas of northwestNorthwest China except in, excluding the middle of the Qinghai Plateau, where the inhomogeneity of annual precipitation distribution intensifies. In terms of the annual precipitation distribution, the monthly precipitation shows an increasing trend in Xinjiang; however, in other regions, it reduces in warm seasons and increases in cold seasons. By contrastContrastingly, MPPAP decreases in warm seasons and increases in cold seasons.ThePrecipitation inhomogeneity of precipitation has a significant negative feedbackresponse to climate warming, i.e., a high annual temperature corresponds to the homogeneity of the annual precipitation distribution in most parts of northwestNorthwest China. The westerly circulation and monsoon are the main factors that affectaffecting the inhomogeneity of precipitation in the northwestern region.

Landslide and debris flows are typically triggered by rainfall-related weather conditions, including short-duration storms and long-lasting rainfall. The critical precipitation of landslides and debris flow occurrence is different under various hydrometeorological conditions. In this study, the trigger sensitivities of different daily hydrological variables were assessed using 50 days-worth of recorded landslide and debris flows using the Soil and Water Assessment Tool model. The event days were divided into long-lasting rainfall trigger (LLR-trigger) event days and short-duration storm trigger (SDS-trigger) event days with six determinate criteria based on modeled wetness states. The landslide and debris flow prediction model was built using nine hydrometeorological variables, and the predictive performance was tested with simulated data from 2010 to 2012. The results suggest that, except for rainfall, historical hydrological variables and their development provide important information for triggering landslides and debris flows. The prediction model with an area under curve (AUC) value of 0.85 was able to capture most of the landslides and debris flows. The temporal distribution of the two triggering events predicted by the model was consistent with the annual precipitation distribution. In addition, the spatial variations of the specific trigger types could be attributed to the different land covers. Despite some uncertainty, this study provides an idea of improving the landslide and debris flow prediction model.

We investigate the global distribution of hourly precipitation and its connections with the El Niño–Southern Oscillation (ENSO) using both satellite precipitation estimates and the global sub-daily rainfall gauge dataset. Despite limited moisture availability over continental surfaces, we find that the highest mean and extreme hourly precipitation intensity (HPI) values are mainly located over continents rather than over oceans, a feature that is not evident in daily or coarser resolution data. After decomposing the total precipitation into the product of the number of wet hours (NWH) and HPI, we find that ENSO modulates total precipitation mainly through the NWH, while its effects on HPI are more limited. The contrasting responses to ENSO in NWH and HPI is particularly apparent at the rising branches of the Pacific and Atlantic Walker Circulations, and is also notable over land-based gauges in Australia, Malaysia, the USA, Japan and Europe across the whole distribution of hourly precipitation (i.e. extreme, moderate and light precipitation). These results provide new insights into the global precipitation distribution and its response to ENSO forcing.

The probability distribution of daily precipitation intensities, especially the probability of extremes, impacts a wide range of applications. In most regions this distribution decays slowly with size at first, approximately as a power law with an exponent between 0 and −1, and then more sharply, for values larger than a characteristic cutoff scale. This cutoff is important because it limits the probability of extreme daily precipitation occurrences in current climate. There is a long history of representing daily precipitation using a gamma distribution—here we present theory for how daily precipitation distributions get their shape. Processes shaping daily precipitation distributions can be separated into nonprecipitating and precipitating regime effects, the former partially controlling how many times in a day it rains, and the latter set by single-storm accumulations. Using previously developed theory for precipitation accumulation distributions—which follow a sharper power-law range (exponent < −1) with a physically derived cutoff for large sizes—analytical expressions for daily precipitation distribution power-law exponent and cutoff are calculated as a function of key physical parameters. Precipitating and nonprecipitating regime processes both contribute to reducing the power-law range exponent for the daily precipitation distribution relative to the fundamental exponent set by accumulations. The daily precipitation distribution cutoff is set by the precipitating regime and scales with moisture availability, with important consequences for future distribution shifts under global warming. Similar results extend to different averaging periods, providing insight into how the precipitation intensity distribution evolves as a function of both underlying physical climate conditions and averaging time.

We investigate the effect of using convection-permitting models (CPMs) spanning a pan-European domain on the representation of precipitation distribution at a climatic scale. In particular we compare two 2.2 km models with two 12 km models run by ETH Zürich (ETH-12 km and ETH-2.2 km) and the Met-Office (UKMO-12 km and UKMO-2.2 km). The two CPMs yield qualitatively similar differences to the precipitation climatology compared to the 12 km models, despite using different dynamical cores and different parameterization packages. A quantitative analysis confirms that the CPMs give the largest differences compared to 12 km models in the hourly precipitation distribution in regions and seasons where convection is a key process: in summer across the whole of Europe and in autumn over the Mediterranean Sea and coasts. Mean precipitation is increased over high orography, with an increased amplitude of the diurnal cycle. We highlight that both CPMs show an increased number of moderate to intense short-lasting events and a decreased number of longer-lasting low-intensity events everywhere, correcting (and often over-correcting) biases in the 12 km models. The overall hourly distribution and the intensity of the most intense events is improved in Switzerland and to a lesser extent in the UK but deteriorates in Germany. The timing of the peak in the diurnal cycle of precipitation is improved. At the daily time-scale, differences in the precipitation distribution are less clear but the greater Alpine region stands out with the largest differences. Also, Mediterranean autumnal intense events are better represented at the daily time-scale in both 2.2 km models, due to improved representation of mesoscale processes.

The study assesses the performance of 24 model runs from five COordinated Regional climate Downscaling Experiment (CORDEX) regional climate models (RCMs) in simulating East Africa’s spatio-temporal precipitation characteristics using a set of eight descriptors: consecutive dry days (CDD), consecutive wet days (CWD), simple precipitation intensity index (SDII), mean daily annual (pr_ANN), seasonal (pr_MAM and pr_OND) precipitation, and representatives of heavy precipitation (90p) and very intense precipitation (99p) events. Relatively better performing RCM runs are then used to assess projected precipitation changes (for the period 2071–2099 relative to 1977–2005) over the study domain under the representative concentration pathway (RCP) 8.5 scenario. The performance of RCMs is found to be descriptor and scope specific. Overall, RCA4 (r1i1p1) forced by CNRM-CERFACS-CNRM-CM5 and MPI-M-MPI-ESM-LR, REMO2009 (r1i1p1) forced by MPI-M-MPI-ESM-LR, and RCA4 (r2i1p1) forced by MPI-M-MPI-ESM-LR emerge as the top four RCM runs. We show that an ensemble mean of the top four model runs outperforms an ensemble mean of 24 model simulations and ensemble means for all runs in an RCM. Our analysis of projections shows a reduction (increase) in mean daily precipitation for MAM(OND), an increase(decrease) in CDD(CWD) events, and a general increase in SDII and the width of the right tail of the precipitation distribution (99p–90p). An increase in SDII and 99p–90p implies a possibility of occurrence of heavy and extreme precipitation incidences by the end of the twenty-first century. Our findings provide important information to support the region’s climate change adaptation and mitigation efforts.

The dynamic and thermal effects of the Tibetan Plateau (TP) on the precipitation in the Asian arid and monsoon regions were investigated using three numerical experiments—one using real topography, one with the whole TP removed, and one with sensible heat turned off over the TP. The results show that there are strong seasonal and regional differences in the dynamic and thermal effects of the TP on the precipitation in the Asian arid regions. The dynamic effect dominated the decrease in winter precipitation by blocking the westerly, while the thermal effect dominated the decrease in summer precipitation due to the TP-induced compensation downdraft in Central Asia and arid East Asia. The thermal effect dominated and accounted for 60% of the decrease in summer precipitation in West Asia. The results also show that both the dynamic and thermal effects of TP exhibit a more salient influence on the East Asian monsoon region than the South Asian monsoon region. The thermal effect dominated and accounted for 40% of the increase in summer precipitation due to intensification of the summer monsoon, while the dynamic effect dominated and accounted for 80% of the decrease in winter precipitation due to the northeast wind anomaly in the northern East Asian monsoon region. The anomalous wind can reach to the coast of South China and form frontal precipitation in the southern East Asian monsoon region in winter. The thermal effect dominated and accounted for 80% of the increase in precipitation in the pre-monsoon period due to intensification of the Asian summer monsoon.

A 1981–2010 average annual precipitation distribution has been prepared for Westland Tai Poutini National Park using a combination of new and historic precipitation observations. The distribution was prepared using a repeatable objective interpolation of observed precipitation and is able to be updated as new precipitation observations are made. With inclusion of undercatch assessments, the distribution indicates mean annual precipitation from 3500 mm at the windward western coast to over 10000 mm in the centre of the region. The area of the highest precipitation does not relate to any obvious topographic attribute such as elevation or the distance to an orographic boundary. No consistent cross-mountain precipitation profile was able to be determined from the observations with variations attributed to the different ridge and valley orientations that influence where precipitation falls to the ground. The new distribution gives a region-wide 1981–2010 mean annual precipitation of 6200 mm. The estimated precipitation at the Main Divide, along the eastern edge of the region, does not align with that previously assessed for the region immediately to the east (the Lake Pukaki catchment and Aoraki/Mt Cook National Park). This indicates there may be a discontinuity in the precipitation distribution across the Main Divide in this area.