Spatial Interpolation of Daily Precipitation in a High Mountainous Watershed Based on Gauge Observations and a Regional Climate Model Simulation

Abstract Precipitation is a primary climate forcing factor in catchment hydrology, and its spatial distribution is essential for understanding the spatial variability of ecohydrological processes in a catchment. In mountainous areas, meteorological stations are generally too sparse to represent the spatial distribution of precipitation. This study develops a spatial interpolation method that combines meteorological observations and regional climate model (RCM) outputs. The method considers the precipitation–elevation relationship in the mountain region and the topographic effects, especially the mountain blocking effect. Furthermore, using this method, this study produced a 3-km-resolution precipitation dataset from 1960 to 2014 in the middle and upper reaches of the Heihe River basin located on the northern slope of the Qilian Mountains in the northeastern Tibetan Plateau. Cross validation based on the station observations showed that this method is reasonable. The rationality of the interpolated precipitation data was also evaluated by the catchment water balances using the observed river discharge and the actual evapotranspiration based on remote sensing. The interpolated precipitation data were compared with the China Gauge-Based Daily Precipitation Analysis product and the RCM output and was shown to be optimal. The results showed that the proposed method effectively used the information from the meteorological observations and the RCM simulations and provided the spatial distributions of daily precipitations with reasonable accuracy and high resolution, which is important for a distributed hydrological simulation at the catchment scale.

Download Full-text

Evaluation of extreme precipitation over the Nordic region using a convection-permitting regional climate model

10.5194/egusphere-egu2020-10506 ◽

2020 ◽

Author(s):

Erika Toivonen ◽

Danijel Belušić ◽

Emma Dybro Thomassen ◽

Peter Berg ◽

Ole Bøssing Christensen ◽

...

Keyword(s):

High Resolution ◽

Regional Climate Model ◽

Extreme Precipitation ◽

Climate Model ◽

Daily Precipitation ◽

Regional Climate ◽

Precipitation Extremes ◽

Nordic Region ◽

Mesh Resolution ◽

Grid Mesh

Extreme precipitation events have a major impact upon our society. Although many studies have indicated that it is likely that the frequency of such events will increase in a warmer climate, little has been done to assess changes in extreme precipitation at a sub-daily scale. Recently, there is more and more evidence that high-resolution convection-permitting models (CPMs) (grid-mesh typically < 4 km) can represent especially short-duration precipitation extremes more accurately when compared with coarser-resolution regional climate models (RCMs).This study investigates sub-daily and daily precipitation characteristics based on hourly output data from the HARMONIE-Climate model at 3-km and 12-km grid-mesh resolution over the Nordic region between 1998 and 2018. The RCM modelling chain uses the ERA-Interim reanalysis to drive a 12-km grid-mesh simulation which is further downscaled to 3-km grid-mesh resolution using a non-hydrostatic model set-up.The statistical properties of the modeled extreme precipitation are compared to several sub-daily and daily observational products, including gridded and in-situ gauge data, from April to September. We investigate the skill of the model to represent different aspects of the frequency and intensity of extreme precipitation as well as intensity&#8211;duration&#8211;frequency (IDF) curves that are commonly used to investigate short duration extremes from an urban planning perspective. The high grid resolution combined with the 20-year-long simulation period allows for a robust assessment at a climatological time scale and enables us to examine the added value of high-resolution CPM in reproducing precipitation extremes over the Nordic region. Based on the tentative results, the high-resolution CPM can realistically capture the characteristics of precipitation extremes, for instance, in terms of improved diurnal cycle and maximum intensities of sub-daily precipitation.

Download Full-text

Assessing Goodness of Fit to a Gamma Distribution and Estimating Future Projection on Daily Precipitation Frequency Using Regional Climate Model Simulations over Japan with and without the Influence of Tropical Cyclones

Journal of Hydrometeorology ◽

10.1175/jhm-d-20-0068.1 ◽

2020 ◽

Vol 21 (12) ◽

pp. 2997-3010

Author(s):

Akihiko Murata ◽

Shun-ichi I. Watanabe ◽

Hidetaka Sasaki ◽

Hiroaki Kawase ◽

Masaya Nosaka

Keyword(s):

Tropical Cyclones ◽

Gamma Distribution ◽

Goodness Of Fit ◽

Climate Model ◽

Daily Precipitation ◽

Regional Climate ◽

Precipitation Data ◽

Precipitation Frequency ◽

Climate Model Simulations ◽

Two Parameters

AbstractGoodness of fit in daily precipitation frequency to a gamma distribution was examined, focusing on adverse effects originating from the shortage of sampled tropical cyclones, using precipitation data with and without the influence of tropical cyclones. The data used in this study were obtained through rain gauge observations and regional climate model simulations under the RCP8.5 scenario and the present climate. An empirical cumulative distribution function (CDF), calculated from a sample of precipitation data for each location, was compared with a theoretical CDF derived from two parameters of a gamma distribution. Using these two CDFs, the root-mean-square error (RMSE) was calculated as an indicator of the goodness of fit. The RMSE exhibited a decreasing tendency when the influence of tropical cyclones was removed. This means that the empirical CDF derived from sampled precipitation more closely resembled the theoretical CDF when compared with the relationship between empirical and theoretical CDFs, including precipitation data associated with tropical cyclones. Future changes in the two parameters of the gamma distribution, without the influence of tropical cyclones, depend on regions in Japan, indicating a regional dependence on changes in the shape and scale of the CDF. The magnitude of increases in no-rain days was also dependent on regions of Japan, although the number of no-rain days increased overall. This simplified approach is useful for analyzing climate change from a broad perspective.

Download Full-text

Customization of RegCM3 Regional Climate Model for Eastern Africa and a Tropical Indian Ocean Domain

Journal of Climate ◽

10.1175/2009jcli2388.1 ◽

2009 ◽

Vol 22 (13) ◽

pp. 3595-3616 ◽

Cited By ~ 53

Author(s):

Neil Davis ◽

Jared Bowden ◽

Fredrick Semazzi ◽

Lian Xie ◽

Bariş Önol

Keyword(s):

Spatial Distribution ◽

Indian Ocean ◽

Regional Climate Model ◽

Climate Model ◽

Regional Climate ◽

Eastern Africa ◽

Massachusetts Institute Of Technology ◽

Convective Rainfall ◽

Total Rainfall ◽

Sensitivity Tests

Abstract Rainfall is a driving factor of climate in the tropics and needs to be properly represented within a climate model. This study customizes the precipitation processes over the tropical regions of eastern Africa and the Indian Ocean using the International Centre for Theoretical Physics (ICTP) Regional Climate Model (RegCM3). The convective schemes of Grell with closures Arakawa–Schubert (Grell–AS)/Fritch–Chappel (Grell–FC) and Massachusetts Institute of Technology–Emanuel (MIT–EMAN) were compared to determine the most realistic spatial distribution of rainfall and partitioning of convective/stratiform rainfall when compared to observations from the Tropical Rainfall Measuring Mission (TRMM). Both Grell–AS and Grell–FC underpredicted convective rainfall rates over land, while over the ocean Grell–FC (Grell–AS) over- (under-) estimates convective rainfall. MIT–EMAN provides the most realistic pardoning and spatial distribution of convective rainfall despite the tendency for overestimating total rainfall. MIT–EMAN was used to further customize the subgrid explicit moisture scheme (SUBEX). Sensitivity tests were performed on the gridbox relative humidity threshold for cloudiness (RHmin) and the autoconversion scale factor (Cacs). An RHmin value of 60% (RHmin-60) reduced the amount of total rainfall over five heterogeneous rainfall regions in eastern Africa, with most of the reduction coming from the convective rainfall. Then, Cacs sensitivity tests improved upon the total rainfall amounts and convective stratiform partitioning compared to RHmin-60. Based upon all sensitivity simulations performed, the combination of the MIT–EMAN convective scheme, RHmin-60, and halving the model default value (0.4) of Cacs provided the most realistic simulation in terms of spatial distribution, convective partition, rainfall totals, and temperature bias when compared to observations.

Download Full-text

Bias Correction, Quantile Mapping, and Downscaling: Revisiting the Inflation Issue

Journal of Climate ◽

10.1175/jcli-d-12-00821.1 ◽

2013 ◽

Vol 26 (6) ◽

pp. 2137-2143 ◽

Cited By ~ 271

Author(s):

Douglas Maraun

Keyword(s):

Regional Climate Model ◽

Bias Correction ◽

Climate Model ◽

Daily Precipitation ◽

Temporal Structure ◽

Regional Climate ◽

Quantile Mapping ◽

Model Simulations ◽

Scale Mismatch ◽

Climate Model Simulations

Abstract Quantile mapping is routinely applied to correct biases of regional climate model simulations compared to observational data. If the observations are of similar resolution as the regional climate model, quantile mapping is a feasible approach. However, if the observations are of much higher resolution, quantile mapping also attempts to bridge this scale mismatch. Here, it is shown for daily precipitation that such quantile mapping–based downscaling is not feasible but introduces similar problems as inflation of perfect prognosis (“prog”) downscaling: the spatial and temporal structure of the corrected time series is misrepresented, the drizzle effect for area means is overcorrected, area-mean extremes are overestimated, and trends are affected. To overcome these problems, stochastic bias correction is required.

Download Full-text

Comparison of Daily Precipitation Bias Correction Methods Based on Four Regional Climate Model Outputs in Ouémé Basin, Benin

Hydrology ◽

10.11648/j.hyd.20160406.11 ◽

2016 ◽

Vol 4 (6) ◽

pp. 58 ◽

Cited By ~ 10

Author(s):

Yèkambèssoun N’Tcha M’Po

Keyword(s):

Regional Climate Model ◽

Bias Correction ◽

Climate Model ◽

Daily Precipitation ◽

Regional Climate ◽

Precipitation Bias

Download Full-text

Exploring metrics of extreme daily precipitation in a large ensemble of regional climate model simulations

Climate Research ◽

10.3354/cr00946 ◽

2010 ◽

Vol 44 (2-3) ◽

pp. 151-166 ◽

Cited By ~ 62

Author(s):

G Lenderink

Keyword(s):

Regional Climate Model ◽

Climate Model ◽

Daily Precipitation ◽

Regional Climate ◽

Large Ensemble ◽

Model Simulations ◽

Climate Model Simulations

Download Full-text

Evaluation of the Hydrological Cycle over the Mississippi River Basin as Simulated by the Canadian Regional Climate Model (CRCM)

Journal of Hydrometeorology ◽

10.1175/jhm627.1 ◽

2007 ◽

Vol 8 (5) ◽

pp. 969-988 ◽

Cited By ~ 132

Author(s):

Biljana Music ◽

Daniel Caya

Keyword(s):

Spatial Distribution ◽

Regional Climate Model ◽

River Basin ◽

Mississippi River ◽

Water Budget ◽

Climate Model ◽

Hydrological Cycle ◽

Water Cycle ◽

Regional Climate ◽

Physical Parameterizations

Abstract The water cycle over a given region is governed by many complex multiscale interactions and feedbacks, and their representation in climate models can vary in complexity. To understand which of the key processes require better representation, evaluation and validation of all components of the simulated water cycle are required. Adequate assessing of the simulated hydrological cycle over a given region is not trivial because observations for various water cycle components are seldom available at the regional scale. In this paper, a comprehensive validation method of the water budget components over a river basin is presented. In addition, the sensitivity of the hydrological cycle in the Canadian Regional Climate Model (CRCM) to a more realistic representation of the land surface processes, as well as radiation, cloud cover, and atmospheric boundary layer mixing is investigated. The changes to the physical parameterizations are assessed by evaluating the CRCM hydrological cycle over the Mississippi River basin. The first part of the evaluation looks at the basin annual means. The second part consists of the analysis and validation of the annual cycle of all water budget components. Finally, the third part is directed toward the spatial distribution of the annual mean precipitation, evapotranspiration, and runoff. Results indicate a strong response of the CRCM evapotranspiration and precipitation biases to the physical parameterization changes. Noticeable improvement was obtained in the simulated annual cycles of precipitation, evapotranspiration, moisture flux convergence, and terrestrial water storage tendency when more sophisticated physical parameterizations were used. Some improvements are also observed for the simulated spatial distribution of precipitation and evapotranspiration. The simulated runoff is less sensitive to changes in the CRCM physical parameterizations.

Download Full-text