Frequency Of Hourly Precipitation Research Articles

A downscaling and bias correction method for climate model ensemble simulations of local-scale hourly precipitation

Ensemble simulations of climate models are used to assess the impact of climate change on precipitation, and require downscaling at the local scale. Statistical downscaling methods have been used to estimate daily and monthly precipitation from observed and simulated data. Downscaling of short-term precipitation data is necessary for more accurate prediction of extreme precipitation events and related disasters at the regional level. In this study, we developed and investigated the performance of a downscaling method for climate model simulations of hourly precipitation. Our method was designed to recognize time-varying precipitation systems that can be represented at the same resolution as the numerical model. Downscaling improved the estimation of the spatial distribution of hourly precipitation frequency, monthly average, and 99th percentile values. The climate change in precipitation amount and frequency were shown in almost all areas by using the 50 ensemble averages of estimated precipitation, although the natural variability was too large to compare with observations. The changes in precipitation were consistent with simulations. Therefore, our downscaling method improved the evaluation of the climatic characteristics of extreme precipitation events and more comprehensively represented the influence of local factors, such as topography, which have been difficult to evaluate using previous methods.

A bias correction method for precipitation through recognizing mesoscale precipitation systems corresponding to weather conditions

Accurate estimations of local precipitation are necessary for assessing water resources and water-related disaster risks. Numerical models are typically used to estimate precipitation, but biases can result from insufficient resolution and incomplete physical processes. To correct these biases, various bias correction methods have been developed. Recently, bias correction methods using machine learning have been developed for improved performance. However, estimating local hourly precipitation characteristics remains difficult due to the nonlinearity of precipitation. Here, we focused on precipitation systems that could be reproduced by numerical models, and estimated the spatial distribution of local precipitation by recognizing the relationship between simulated and observed precipitation with a resolution of 0.06 degrees using a machine learning method. We subsequently applied a quantile mapping method to modify the precipitation amounts. Validation showed that our method could significantly reduce bias in numerical simulations, especially the spatial distribution of hourly precipitation frequency. However, the bias in the temporal distribution of hourly precipitation did not improve. Spatial autocorrelation analysis showed that this method can predict precipitation systems with spatial scales of 2500 to 40000 km2, which are associated with large-scale disturbances (e.g., cold fronts, warm fronts, and low-pressure systems). The high accuracy of these estimates indicates that the spatial distribution of hourly precipitation frequency is strongly dependent on precipitation systems with these spatial scales. Accordingly, our method shows that the relationship between the spatial distribution of precipitation systems and local precipitation is strong, and by recognizing this relationship, the spatial distribution of local hourly precipitation can be accurately estimated.

Variability of hourly precipitation during the warm season over eastern China using gauge observations and ERA5

Hourly precipitation is important in climate research because it is closely related to convective synoptic systems and short-term weather forecasts. In this study, characteristics like climatology, inter-annual variability and diurnal cycle are quantified from 1979 to 2015 over eastern China using hourly gauge observations and ERA5 precipitation dataset. The results show that the reanalysis can reproduce the spatial pattern of precipitation climatology, but it generally overestimates the frequency and underestimates the intensity, resulting in a better estimate of the precipitation amount. The mean relative biases of ERA5 compared to gauge observations are 137.04%, −49.09% and 16.30% for precipitation frequency, intensity and amount, respectively. ERA5 has positive correlation coefficients with gauge observations in inter-annual variations of hourly precipitation quantities, but with lack of long-term trend estimation. At national scale, the trend of the annual mean hourly precipitation amount calculated by ERA5 is −0.009 mm/h/decade, which is much smaller than the 0.002 mm/h/decade based on gauge observations. The trends of the annual mean hourly precipitation frequency and intensity calculated by ERA5 (−0.901%/decade and − 0.008 mm/h/decade) are also smaller than those based on the gauge observations (−0.044%/decade and 0.023 mm/h/decade). ERA5 can also reproduce the diurnal cycle of the gauge observations, but largely overestimates the precipitation amount during daytime. The reanalyses agree with gauge observations best over the south China region, whereas the worst performance occurs over northern southwest China. The results can provide a useful reference for the hydrological and meteorological research about the hourly precipitation.

Examining the Robustness of a Spatial Bootstrap Regional Approach for Radar-Based Hourly Precipitation Frequency Analysis

Radar-based Quantitative Precipitation Estimates (QPE) provide rainfall products with high temporal and spatial resolutions as opposed to sparse observations from rain gauges. Radar-based QPE’s have been widely used in many hydrological and meteorological applications; however, using these high-resolution products in the development of Precipitation Frequency Estimates (PFE) is impeded by their typically short-record availability. The current study evaluates the robustness of a spatial bootstrap regional approach, in comparison to a pixel-based (i.e., at site) approach, to derive PFEs using hourly radar-based multi-sensor precipitation estimation (MPE) product over the state of Louisiana in the US. The spatial bootstrap sampling technique augments the local pixel sample by incorporating rainfall data from surrounding pixels with decreasing importance when distance increases. We modeled extreme hourly rainfall data based on annual maximum series (AMS) using the generalized extreme value statistical distribution. The results showed a reduction in the uncertainty bounds of the PFEs when using the regional spatial bootstrap approach compared to the pixel-based estimation, with an average reduction of 10% and 2% in the 2- and 5-year return periods, respectively. Using gauge-based PFE’s as a reference, the spatial bootstrap regional approach outperforms the pixel-based approach in terms of robustness to outliers identified in the radar-based AMS of some pixels. However, the systematic bias inherent to radar-based QPE especially for extreme rainfall cases, appear to cause considerable underestimation in PFEs in both the pixel-based and the regional approaches.

Global distribution of the intensity and frequency of hourly precipitation and their responses to ENSO

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.

HOURLY PRECIPITATION PATTERNS IN A BRAZILIAN TROPICAL CITY

The research on precipitation is related to analysis of its spatiotemporal variability using daily, monthly and annual data. However, there is a scarcity in the availability of information on how this variable is distributed over the hours of the day. Thus, the objective of this study was to analyze the intensity and hourly patterns of precipitation in Cuiabá in the State of Mato Grosso. Precipitation data were collected at the Cuiabá weather station of the National Institute of Meteorology from 2003 to 2018. The relative frequency of hourly precipitation was analyzed by the Spiegel method. The relative frequency of precipitation in wet season was high in the afternoon from 16:00 h (6.2%) to 17:00 h (5.9%) and low in the morning from 10:00 (3.0%) to 11:00 (2.8%). The relative frequency of precipitation during the dry season was high at 05:00 h (5.0%) and 17:00 h (5.4%) and low from 12:00 h (2.6%) and 13:00 h (2.2%). In general, the intensity of precipitation in the region was predominantly weak, followed by moderate, strong and very strong. The precipitation events in Cuiabá generally occur in the late afternoon, resulting from convective activity in the region.

Effects of Horizontal Resolution on Hourly Precipitation in AGCM Simulations

AbstractTo analyze the effects of horizontal resolution on hourly precipitation, four Atmospheric Model Intercomparison Project simulations are carried out using the Chinese Academy of Sciences Earth System Model (CAS-ESM) and the Community Earth System Model (CESM) during 1998–2016. They include CAS-ESM at resolutions of 1.4° latitude × 1.4° longitude (CAS-ESM L) and 0.5° × 0.5° (CAS-ESM H), and CESM at resolutions of 1.9° latitude × 2.5° longitude (CESM L) and 0.47° × 0.63° (CESM H), respectively. We focus on the simulated hourly precipitation frequency and assess the frequency with respect to high-resolution satellite observations and reanalysis. The high-resolution experiments show some improvements of measurable precipitation (>0.02 mm h−1) frequency. Noticeable improvement of heavy rainfall (>2 mm h−1) frequency is demonstrated at the high resolutions. The zonal mean, seasonal mean, and area-weighted average frequency support the above results. The high-resolution experiments outperform the low-resolution experiments in reproducing hourly precipitation intensity and amount. The added value is apparent in heavy precipitation intensity from CAS-ESM H and CESM H. Over the monsoon regions and tropical convergence zones, the patterns of probability density functions for precipitation from high-resolution experiments are closer to the observations and reanalysis than those from the low-resolution simulations. The improvement of measurable precipitation frequency is mainly caused by the reductions of the convective rainfall occurrence at high resolutions. The increasing large-scale precipitation and reasonable integrated water vapor flux contribute to the improvements in measurable rainfall intensity and heavy precipitation characteristics. The results of this study support the concept that high-resolution global simulations could produce improved hourly precipitation capabilities, especially for heavy rainfall.

Evaluation of precipitation over an oceanic region of Japan in convection-permitting regional climate model simulations

We investigated the performance of a convection-permitting regional climate model with respect to precipitation in the present climate around the southwestern oceanic region of Japan. The effects of explicit representation of convective processes without cumulus parameterization can be properly estimated by using a model domain without complex topography or convoluted coastlines. The amounts of annual and monthly precipitation and the frequencies of daily and hourly precipitation were well reproduced by the convection-permitting model with a 2-km grid spacing, and its performance was better than that of a model with a coarser mesh. In particular, the frequencies of hourly precipitation in the convection-permitting simulation matched the observed frequencies for precipitation intensities below 20 mm h−1. Above intensities of 20 mm h−1, however, the convection-permitting model tended to overestimate the frequency of hourly precipitation. To explore the mechanism of this overestimation of heavy hourly precipitation, the sensitivity of the frequency distribution of precipitation to the horizontal resolution was tested by changing the horizontal grid spacing of the model from 2 to 4 km and then 1.5 km. The results showed that the overestimation was increased when the horizontal resolution was coarser, owing to spurious grid-scale precipitation, which causes heavy precipitation to be highly concentrated in a single grid. This spurious grid-scale precipitation may be caused by insufficient representation of convective downdrafts in convection-permitting simulations by models with coarser resolutions.

Comparing CAM5 and Superparameterized CAM5 Simulations of Summer Precipitation Characteristics over Continental East Asia: Mean State, Frequency–Intensity Relationship, Diurnal Cycle, and Influencing Factors

Abstract Numerical experiments are conducted to investigate the differences between summer precipitation over continental East Asia simulated by the Community Atmosphere Model, version 5 (CAM5), and superparameterized CAM5 (SPCAM5, a multiscale modeling framework). The results show that SPCAM5 effectively alleviates several original biases. Overestimates of precipitation on the eastern periphery of the Tibetan Plateau are reduced from CAM5 to SPCAM5 as a result of decreases in both the average hourly precipitation frequency and mean hourly intensity. Underestimates along the coastal regions in southern China are improved following a corresponding increase in mean hourly intensity and a decrease in average hourly precipitation frequency. The frequency–intesnsity relationship is also more realistic in SPCAM5. For western China, overestimated frequency values (in CAM5) of both weak-to-moderate (0–20 mm day−1) and heavy (20–50 mm day−1) intensity ranges are reduced in SPCAM5. For southern China, overestimates of frequency values (in CAM5) in the weak-to-moderate range are also reduced, whereas underestimates in the intense ranges are enhanced. In terms of diurnal variability, SPCAM5 generally exhibits a delay in the afternoon peak time and greater diurnal amplitude. The possible physical reasons for the variations in the precipitation between the models are further investigated. It is found that the change in deep convection intensity is a primary factor governing the shift in the precipitation simulations. SPCAM5 better simulates an intermediate transition stage from shallow to deep convection, which helps the deep convection to grow more fully to a greater magnitude, thus delaying the peak time and increasing the precipitation maxima.

An analysis on the relationship between land subsidence and floods at the Kujukuri Plain in Chiba Prefecture, Japan

Abstract. Surface environments at the Kujukuri Plain in Chiba Prefecture, Japan, in 1970, 2004, and 2013, were analyzed and compared to discuss the possible impact of land subsidence on the occurrence of floods. The study area has been suffered from land subsidence due to ground deformation from paleo-earthquakes, tectonic activities, and human-induced subsidence by groundwater exploitation. Meteorological data, geomorphological data including DEM obtained from the airborne laser scanning (1-m spatial resolution), leveling data, and the result of our assessment map (Chen et al., 2015) were used in this study. Clear relationship between floods and land subsidence was not recognized, while geomorphological setting, urbanization, and change of precipitation pattern were found to contribute to the floods. The flood prone-area is distributed on the characteristic geomorphological setting such as floodplain and back swamp. It was revealed that the urban area has been expanded on these geomorphological setting in recent years. The frequency of hourly precipitation was also shown to be increased in the past ca. 40 years, and this could induce rapid freshet and overflow of small- and medium-sized rivers and sewerage lines. The distribution of depression areas was increased from 2004 to 2013. This change could be associated with the ground deformation after the Tohoku earthquake (Mw = 9.0) in 2011.

A gridded dataset of hourly precipitation in Germany: Its construction, climatology and application

A so-called disaggregation technique is used to combine daily rain gauge measurements and hourly radar composites in order to produce a dataset of hourly precipitation in Germany on a grid with a horizontal resolution of 7 km for the years 2001-2004. This state-of-the-art observation-based dataset of precipitation has a high temporal and spatial resolution and will be extended continuously during the upcoming years. Limitations of its quality, which are due to intrinsic problems with observing the highly variable field of precipitation, are discussed and quantified where possible. The dataset offers novel possibilities to investigate the climatology of precipitation and to verify precipitation forecasts from numerical weather prediction models. The frequency of hourly precipitation in Germany above the detection limit of 0.1 mm/h amounts to 10-30 % in winter, with clear maxima in the mountainous regions, and to 6-20 % in summer, when the spatial variability is considerably reduced. The 95th percentile of the frequency distribution is significantly larger in summer than in winter, with local maxima in the mountainous regions in winter, and in the Alpine Foreland and upper Elbe catchment in summer. It is shown that the operational model COSMO-7 with a horizontal resolution of 7 km captures the geographical distribution of the frequency and of the 95th percentile of hourly precipitation in Germany very well. In contrast, the model is not able to realistically simulate the diurnal cycle of precipitation in any region of Germany during summer.

Recent trends in diurnal variation of precipitation at Valentia on the west coast of Ireland

An investigation of 54 years of hourly precipitation at Valentia, on the south-west coast of Ireland, shows a change point in the annual amounts in the years around 1975 (identified by the Pettitt—Mann—Whitney statistic). This results in a 10% increase in the mean annual precipitation from a pre-1975 value of 1375 mm to a post-1975 value of 1507 mm. Most of that increase is absorbed in the months of March and October. The frequency of hourly precipitation in March in the post-1975 period is 57% greater than that of March in the pre-1975 period. However, the magnitude of the hourly intensity of precipitation in March for both periods was similar. Significant changes in wet hour frequency also occurred in October with no corresponding change in hourly intensity. These results compliment findings by others, that regions in Northern European latitudes have experienced an increase in precipitation since the mid-1970s.