scholarly journals Prediction vs. Performance of IDF Curves from Precipitation Data of Regional Climate Models for a Brazilian Coastal County

2018 ◽  
Author(s):  
Daniela Martins ◽  
Nadiane Smaha Kruk ◽  
Paulo Ivo Braga de Queiroz ◽  
Wilson Cabral de Souza Júnior ◽  
Gabriele Vanessa Tschöke
Keyword(s):  
Climate Changes ◽  
Climate Models ◽  
Global Climate ◽  
Regional Climate ◽  
Control Period ◽  
Regional Climate Models ◽  
Global Climate Models ◽  
Precipitation Data ◽  
Drainage Systems ◽  
Idf Curves

Drainage systems are usually dimensioned for design storms based on intensity-duration-frequency (IDF) curves of extreme precipitation. For each location, different IDF curves are established based on local hydrological conditions. Recent research shows that these curves also vary with time, and should be updated with recent data. The purpose of this study is to evaluate IDF curves obtained from precipitation simulations from the Eta RCM, comparing them with IDF curves obtained from data of a rainfall station. Climate models can be a useful tool for assessing the impacts of climate changes on drainage systems, referring precipitation forecasts. In this study, the Eta RCM was forced by two global climate models: HadGEM2-ES and MIROC5. The bias of the precipitation data, generated by RCM models, was corrected using a Gamma distribution. The Juqueriquerê River Basin, in the cities of Caraguatatuba and São Sebastião, São Paulo State, Brazil, was chosen as a case study. The results show a good correlation between the IDF curves of simulated and observed rainfall for the control period (1960-2005), indicating the strong possibility of using the Eta RCM precipitation forecasts for 2007 - 2099 to establish future IDFs thereby, taking into account climate changes in urban drainage design.

scholarly journals Regional climate models downscaling in the Alpine area with Multimodel SuperEnsemble

2012 ◽  
Vol 9 (8) ◽  
pp. 9425-9454 ◽  
Author(s):  
D. Cane ◽  
S. Barbarino ◽  
L. A. Renier ◽  
C. Ronchi
Keyword(s):  
Climate Models ◽  
Global Climate ◽  
Regional Climate ◽  
Control Period ◽  
Regional Climate Models ◽  
Global Climate Models ◽  
Temperature Fields ◽  
Optimal Interpolation ◽  
Climate Change Scenarios ◽  
Alpine Area

Abstract. The climatic scenarios show a strong signal of warming in the Alpine area already for the mid XXI century. The climate simulations, however, even when obtained with Regional Climate Models (RCMs), are affected by strong errors where compared with observations, due to their difficulties in representing the complex orography of the Alps and limitations in their physical parametrization. Therefore the aim of this work is reducing these model biases using a specific post processing statistic technique to obtain a more suitable projection of climate change scenarios in the Alpine area. For our purposes we use a selection of RCMs runs from the ENSEMBLES project, carefully chosen in order to maximise the variety of leading Global Climate Models and of the RCMs themselves, calculated on the SRES scenario A1B. The reference observation for the Greater Alpine Area are extracted from the European dataset E-OBS produced by the project ENSEMBLES with an available resolution of 25 km. For the study area of Piedmont daily temperature and precipitation observations (1957–present) were carefully gridded on a 14-km grid over Piedmont Region with an Optimal Interpolation technique. Hence, we applied the Multimodel SuperEnsemble technique to temperature fields, reducing the high biases of RCMs temperature field compared to observations in the control period. We propose also the first application to RCMS of a brand new probabilistic Multimodel SuperEnsemble Dressing technique to estimate precipitation fields, already applied successfully to weather forecast models, with careful description of precipitation Probability Density Functions conditioned to the model outputs. This technique reduces the strong precipitation overestimation by RCMs over the alpine chain and reproduces well the monthly behaviour of precipitation in the control period.

scholarly journals Assessment of Changes in Annual Maximum Precipitations in the Iberian Peninsula under Climate Change

Water ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 2375 ◽  
Author(s):  
Carlos Garijo ◽  
Luis Mediero
Keyword(s):  
Climate Change ◽  
Iberian Peninsula ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Regional Climate ◽  
Control Period ◽  
Regional Climate Models ◽  
Global Climate Models ◽  
The Future

Climate model projections can be used to assess the future expected behavior of extreme precipitation due to climate change. In Europe, the EURO-CORDEX project provides precipitation projections in the future under various representative concentration pathways (RCP), through regionalized outputs of Global Climate Models (GCM) by a set of Regional Climate Models (RCM). In this work, 12 combinations of GCM and RCM under two scenarios (RCP 4.5 and RCP 8.5) supplied by the EURO-CORDEX project are analyzed in the Iberian Peninsula and the Balearic Islands. Precipitation quantiles for a set of exceedance probabilities are estimated by using the Generalized Extreme Value (GEV) distribution function fitted by the L-moment method. Precipitation quantiles expected in the future period are compared with the precipitation quantiles in the control period, for each climate model. An approach based on Monte Carlo simulations is developed to assess the uncertainty from the climate model projections. Expected changes in the future are compared with the sampling uncertainty in the control period to identify statistically significant changes. The higher the significance threshold, the fewer cells with changes are identified. Consequently, a set of maps are obtained for various thresholds to assist the decision making process in subsequent climate change studies.

A Bayesian Hierarchical Model for Heterogeneous RCM–GCM Multimodel Ensembles*

2015 ◽  
Vol 28 (15) ◽  
pp. 6249-6266 ◽  
Author(s):  
Christian Kerkhoff ◽  
Hans R. Künsch ◽  
Christoph Schär
Keyword(s):  
Hierarchical Model ◽  
Climate Models ◽  
Global Climate ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Bayesian Hierarchical Model ◽  
Global Climate Models ◽  
Seasonal Temperature ◽  
Bayesian Hierarchical ◽  
Multimodel Ensembles

Abstract A Bayesian hierarchical model for heterogeneous multimodel ensembles of global and regional climate models is presented. By applying the methodology herein to regional and seasonal temperature averages from the ENSEMBLES project, probabilistic projections of future climate are derived. Intermodel correlations that are particularly strong between regional climate models and their driving global climate models are explicitly accounted for. Instead of working with time slices, a data archive is investigated in a transient setting. This enables a coherent treatment of internal variability on multidecadal time scales. Results are presented for four European regions to highlight the feasibility of the approach. In particular, the methodology is able to objectively identify patterns of variability changes, in ways that previously required subjective expert knowledge. Furthermore, this study underlines that assumptions about bias changes have an effect on the projected warming. It is also shown that validating the out-of-sample predictive performance is possible on short-term prediction horizons and that the hierarchical model herein is competitive. Additionally, the findings indicate that instead of running a large suite of regional climate models all forced by the same driver, priority should be given to a rich diversity of global climate models that force a number of regional climate models in the experimental design of future multimodel ensembles.

scholarly journals Regional climate models downscaling in the Alpine area with multimodel superensemble

2013 ◽  
Vol 17 (5) ◽  
pp. 2017-2028 ◽  
Author(s):  
D. Cane ◽  
S. Barbarino ◽  
L. A. Renier ◽  
C. Ronchi
Keyword(s):  
Climate Models ◽  
Regional Climate ◽  
Control Period ◽  
Regional Climate Models ◽  
Global Climate Models ◽  
Temperature Fields ◽  
Optimal Interpolation ◽  
Climate Change Scenarios ◽  
Alpine Area ◽  
Ensembles Project

Abstract. The climatic scenarios show a strong signal of warming in the Alpine area already for the mid-XXI century. The climate simulations, however, even when obtained with regional climate models (RCMs), are affected by strong errors when compared with observations, due both to their difficulties in representing the complex orography of the Alps and to limitations in their physical parametrization. Therefore, the aim of this work is to reduce these model biases by using a specific post processing statistic technique, in order to obtain a more suitable projection of climate change scenarios in the Alpine area. For our purposes we used a selection of regional climate models (RCMs) runs which were developed in the framework of the ENSEMBLES project. They were carefully chosen with the aim to maximise the variety of leading global climate models and of the RCMs themselves, calculated on the SRES scenario A1B. The reference observations for the greater Alpine area were extracted from the European dataset E-OBS (produced by the ENSEMBLES project), which have an available resolution of 25 km. For the study area of Piedmont daily temperature and precipitation observations (covering the period from 1957 to the present) were carefully gridded on a 14 km grid over Piedmont region through the use of an optimal interpolation technique. Hence, we applied the multimodel superensemble technique to temperature fields, reducing the high biases of RCMs temperature field compared to observations in the control period. We also proposed the application of a brand new probabilistic multimodel superensemble dressing technique, already applied to weather forecast models successfully, to RCMS: the aim was to estimate precipitation fields, with careful description of precipitation probability density functions conditioned to the model outputs. This technique allowed for reducing the strong precipitation overestimation, arising from the use of RCMs, over the Alpine chain and to reproduce well the monthly behaviour of precipitation in the control period.

scholarly journals Quantification of the Expected Changes in Annual Maximum Daily Precipitation Quantiles under Climate Change in the Iberian Peninsula

Proceedings ◽  
2018 ◽  
Vol 7 (1) ◽  
pp. 23 ◽  
Author(s):  
Carlos Garijo ◽  
Luis Mediero
Keyword(s):  
Climate Change ◽  
Iberian Peninsula ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Regional Climate ◽  
Control Period ◽  
Regional Climate Models ◽  
The Future

Climate model projections can be used to assess the expected behaviour of extreme precipitations in the future due to climate change. The European part of the Coordinated Regional Climate Downscalling Experiment (EURO-CORDEX) provides precipitation projections for the future under various representative concentration pathways (RCPs) through regionalised Global Climate Model (GCM) outputs by a set of Regional Climate Models (RCMs). In this work, 12 combinations of GCM and RCM under two scenarios (RCP 4.5 and RCP 8.5) supplied by the EURO-CORDEX are analysed for the Iberian Peninsula. Precipitation quantiles for a set of probabilities of non-exceedance are estimated by using the Generalized Extreme Value (GEV) distribution and L-moments. Precipitation quantiles expected in the future are compared with the precipitation quantiles in the control period for each climate model. An approach based on Monte Carlo simulations is developed in order to assess the uncertainty from the climate model projections. Expected changes in the future are compared with the sampling uncertainty in the control period. Thus, statistically significant changes are identified. The higher the significance threshold, the fewer cells with significant changes are identified. Consequently, a set of maps are obtained in order to assist the decision-making process in subsequent climate change studies.

scholarly journals Stochastic Rainfall Downscaling of Climate Models

2014 ◽  
Vol 15 (2) ◽  
pp. 830-843 ◽  
Author(s):  
D. D’Onofrio ◽  
E. Palazzi ◽  
J. von Hardenberg ◽  
A. Provenzale ◽  
S. Calmanti
Keyword(s):  
Climate Models ◽  
Global Climate ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Amplitude Distribution ◽  
Global Climate Models ◽  
Added Value ◽  
Small Scale ◽  
Physically Based ◽  
Stochastic Downscaling

Abstract Precipitation extremes and small-scale variability are essential drivers in many climate change impact studies. However, the spatial resolution currently achieved by global climate models (GCMs) and regional climate models (RCMs) is still insufficient to correctly identify the fine structure of precipitation intensity fields. In the absence of a proper physically based representation, this scale gap can be at least temporarily bridged by adopting a stochastic rainfall downscaling technique. In this work, a precipitation downscaling chain is introduced where the global 40-yr ECMWF Re-Analysis (ERA-40) (at about 120-km resolution) is dynamically downscaled using the Protheus RCM at 30-km resolution. The RCM precipitation is then further downscaled using a stochastic downscaling technique, the Rainfall Filtered Autoregressive Model (RainFARM), which has been extended for application to long climate simulations. The application of the stochastic downscaling technique directly to the larger-scale reanalysis field at about 120-km resolution is also discussed. To assess the ability of this approach in reproducing the main statistical properties of precipitation, the downscaled model results are compared with the precipitation data provided by a dense network of 122 rain gauges in northwestern Italy, in the time period from 1958 to 2001. The high-resolution precipitation fields obtained by stochastically downscaling the RCM outputs reproduce well the seasonality and amplitude distribution of the observed precipitation during most of the year, including extreme events and variance. In addition, the RainFARM outputs compare more favorably to observations when the procedure is applied to the RCM output rather than to the global reanalyses, highlighting the added value of reaching high enough resolution with a dynamical model.

scholarly journals Spatio-temporal trends of hydrological components: the case of the Tafna basin (northwestern Algeria)

2021 ◽  
Author(s):  
Amina Mami ◽  
Djilali Yebdri ◽  
Sabine Sauvage ◽  
Mélanie Raimonet ◽  
José Miguel
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Assessment Tool ◽  
Global Climate ◽  
Swat Model ◽  
Regional Climate ◽  
Temporal Trends ◽  
Regional Climate Models ◽  
Global Climate Models ◽  
The Future

Abstract Climate change is expected to increase in the future in the Mediterranean region, including Algeria. The Tafna basin, vulnerable to drought, is one of the most important catchments ensuring water self-sufficiency in northwestern Algeria. The objective of this study is to estimate the evolution of hydrological components of the Tafna basin, throughout 2020–2099, comparing to the period 1981–2000. The SWAT model (Soil and Water Assessment Tool), calibrated and validated on the Tafna basin with good Nash at the outlet 0.82, is applied to analyze the spatial and temporal evolution of hydrological components, over the basin throughout 2020–2099. The application is produced using a precipitation and temperature minimum/maximum of an ensemble of climate model outputs obtained from a combination of eight global climate models and two regional climate models of Coordinated Regional Climate Downscaling Experiment project. The results of this study show that the decrease of precipitation in January, on average −25%, ranged between −5% and −44% in the future. This diminution affects all of the water components and fluxes of a watershed, namely, in descending order of impact: the river discharge causing a decrease −36%, the soil water available −31%, the evapotranspiration −30%, and the lateral flow −29%.

scholarly journals Effect of Model Resolution on Intense and Extreme Precipitationinthe Mediterranean Region

Atmosphere ◽  
2020 ◽  
Vol 11 (7) ◽  
pp. 699
Author(s):  
Dario Conte ◽  
Silvio Gualdi ◽  
Piero Lionello
Keyword(s):  
Climate Change ◽  
Mediterranean Region ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Model ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Global Climate Models ◽  
Total Precipitation ◽  
Model Resolution

This study explores the role of model resolution on the simulation of precipitation and on the estimate of its future change in the Mediterranean region. It compares the results of two regional climate models (RCMs, with two different horizontal grid resolutions, 0.44 and 0.11 degs, covering the whole Mediterranean region) and of the global climate model (GCM, 0.75 degs) that has provided the boundary conditions for them. The regional climate models include an interactive oceanic component with a resolution of 1/16 degs. The period 1960–2100 and the representative concentration pathways RCP4.5 and RCP8.5 are considered. The results show that, in the present climate, increasing resolution increases total precipitation and its extremes over steep orography, while it has the opposite effect over flat areas and the sea. Considering climate change, in all simulations, total precipitation will decrease over most of the considered domain except at the northern boundary, where it will increase. Extreme precipitation will increase over most of the northern Mediterranean region and decrease over the sea and some southern areas. Further, the overall probability of precipitation (frequency of wet days) significantly decreases over most of the region, but wet days will be characterized with precipitation intensity higher than the present. Our analysis shows that: (1) these projected changes are robust with respect to the considered range of model resolution; (2) increasing the resolution (within the considered resolution range) decreases the magnitude of these climate change effects. However, it is likely that resolution plays a less important role than other factors, such as the different physics of regional and global climate models. It remains to be investigated whether further increasing the resolution (and reaching the scale explicitly permitting convection) would change this conclusion.

Hydrological simulations in the Rhine basin

2005 ◽  
Vol 51 (5) ◽  
pp. 1-4
Author(s):  
B. van den Hurk ◽  
J. Beersma ◽  
G. Lenderink
Keyword(s):  
Land Surface ◽  
Climate Models ◽  
Global Climate ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Global Climate Models ◽  
Rhine River ◽  
Rhine Basin ◽  
The Impact ◽  
Selection Of

Simulations with regional climate models (RCMs), carried out for the Rhine basin, have been analyzed in the context of implications of the possible future discharge of the Rhine river. In a first analysis, the runoff generated by the RCMs is compared to observations, in order to detect the way the RCMs treat anomalies in precipitation in their land surface component. A second analysis is devoted to the frequency distribution of area averaged precipitation, and the impact of selection of various driving global climate models.

Sign in / Sign up

Export Citation Format

Share Document