High-resolution climate change simulations over the Lesser Antilles are performed using the ALADIN-Climate regional climate model nested within the global model ARPEGE (Météo-France). Three sets of ...simulations are conducted at 10 km grid spacing for reference (1971-2000) and future climate (2071-2100) under two CMIP5 scenarios (RCP4.5 and RCP8.5). With the dynamical downscaling, islands of Lesser Antilles are considered as land by the model, whereas, for the driving model, there is only sea over the domain. Temperature and precipitation change are analysed on land and on sea separately. For temperature, the warming is greater on land than on sea, especially for the minimum daily temperature (3.2°C vs. 2.3°C for the RCP85 scenario). For precipitation, projections are less reliable because the seasonality is not well reproduced by the model. Nevertheless, simulations exhibit the fact that projections on land differ from one island to the other and disagree with those on sea notably during the wet season. This underlines the importance of the dynamical downscaling to study the climate on small islands. Statistical downscaling has been performed on the Guadeloupe Island to study changes in extreme precipitation indices. The projections provided by the regional climate model suggest an increase in extreme rainfall events: longer dry periods, a bigger annual total precipitation, more frequent very heavy daily precipitation and a stronger 1 d maximum precipitation, whereas for the driving Global Climate Model, these trends are less intense.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
This study focuses on the spatial distribution of mean annual and monthly precipitation in a small island (1128 km
2
) named Martinique, located in the Lesser Antilles. Only 35 meteorological ...stations are available on the territory, which has a complex topography. With a digital elevation model (DEM), 17 covariates that are likely to explain precipitation were built. Several interpolation methods, such as regression-kriging (𝖬𝖫𝖱𝖪, 𝖯𝖢𝖱𝖪, and 𝖯𝖫𝖲𝖪) and external drift kriging (𝖤𝖣𝖪) were tested using a cross-validation procedure. For the regression methods, predictors were chosen by established techniques whereas a new approach is proposed to select external drifts in a kriging which is based on a stepwise model selection by the Akaike Information Criterion (AIC). The prediction accuracy was assessed at validation sites with three different skill scores. Results show that using methods with no predictors such as inverse distance weighting (𝖨𝖣𝖶) or universal kriging (𝖴𝖪) is inappropriate in such a territory. 𝖤𝖣𝖪 appears to outperform regression methods for any criteria, and selecting predictors by our approach improves the prediction of mean annual precipitation compared to kriging with only elevation as drift. Finally, the predicting performance was also studied by varying the size of the training set leading to less conclusive results for 𝖤𝖣𝖪 and its performance. Nevertheless, the proposed method seems to be a good way to improve the mapping of climatic variables in a small island.
SHYREG method is a regionalized method for rainfall and flood frequency analysis (FFA). It is based on processes simulation. It couples an hourly rainfall generator with a rainfall-runoff model, ...simplified enough to be regionalized. The method has been calibrated using all hydro meteorological data available at the national level. In France, that represents about 2800 raingauges of the French Weather Service network and about 1800 stations of the hydrometric National Bank network. Then, the method has been regionalized to provide a rainfall and flow quantiles database. An evaluation of the method was carried out during different thesis works and more recently during the ANR project Extraflo, with the aim of comparing different FFA approaches. The accuracy of the method in estimating rainfall and flow quantiles has been proved, as well as its stability due to a parameterization based on average values. The link with rainfall seems preferable to extrapolation based solely on the flow. Thus, another interest of the method is to take into account extreme flood behaviour with help of rainfall frequency estimation. In addition, the approach is implicitly multi-durational, and only one regionalization meets all the needs in terms hydrological hazards characterisation. For engineering needs and to avoid repeating the method implementation, this method has been applied throughout a 50 meters resolution mesh to provide a complete flood quantiles database over the French territory providing regional information on hydrological hazards. However, it is subject to restrictions related to the nature of the method: the SHYREG flows are “natural”, and do not take into account specific cases like the basins highly influenced by presence of hydraulic works, flood expansion areas, high snowmelt or karsts. Information about these restrictions and uncertainty estimation is provided with this database, which can be consulted via web access.
The latest version of the atmospheric general circulation model ARPEGE‐Climat was used to perform 5‐member ensemble simulations for both present and RCP8.5 scenario climates (mid‐21st century). The ...rotated/stretched configuration enables a local horizontal resolution of less than 15 km over the tropical North Atlantic basin. Moreover, a tracking algorithm was used to extract tropical cyclones (TCs) simulated by the model. Through an Eulerian approach, this paper focuses on the relationships between TCs and rainfall over three French islands in the West Indies. Although the model underestimates the occurrence of TCs over this latitude band, especially in September, precipitation rates during TC days are realistic. Indeed, the model shows a good capacity to reproduce different relationships between island rainfall and TC characteristics such as proximity and intensity. In addition to rainfall distribution, the TC contribution to annual cumulative rainfall is also well captured by the model. We used three different series characterizing precipitation at the island scale to underline that the model overestimates the area that is impacted by TC rainfall. According to the simulations, the number of minor TCs tends to decrease in the future (about −15%) over the study domain (50–70°W × 10–25°N) despite a +1.6°C over ocean warming. In contrast, no trend was detected in the number of major hurricanes. Except for annual precipitation that decreases significantly in the future (about −15%), no significant change was detected in the relationships between TC properties and island rainfall.
Tropical cyclones (TCs) are common in the eastern Caribbean where they cause heavy precipitation. A high‐resolution climate model is used to determine whether local residents of three small islands will likely be more subject to TC rainfall hazard in the future. We pay particular attention to verify if the observed strong associations between island rainfall and TC characteristics (proximity and intensity) are well reproduced by the model, and if a change in these relationships may be expected in the future.
•Uncertainties of flood frequency estimation methods were analysed on 1112 stations.•Purely statistical methods and a continuous simulation method were compared.•Theoretical sampling distribution of ...parameters and bootstrap method were used.•Propagation of rainfall quantiles uncertainties to runoff uncertainties was studied.•For extreme flood quantiles the uncertainties are mostly due to the rainfall generator.
Flood frequency analyses (FFAs) are needed for flood risk management. Many methods exist ranging from classical purely statistical approaches to more complex approaches based on process simulation. The results of these methods are associated with uncertainties that are sometimes difficult to estimate due to the complexity of the approaches or the number of parameters, especially for process simulation. This is the case of the simulation-based FFA approach called SHYREG presented in this paper, in which a rainfall generator is coupled with a simple rainfall-runoff model in an attempt to estimate the uncertainties due to the estimation of the seven parameters needed to estimate flood frequencies. The six parameters of the rainfall generator are mean values, so their theoretical distribution is known and can be used to estimate the generator uncertainties. In contrast, the theoretical distribution of the single hydrological model parameter is unknown; consequently, a bootstrap method is applied to estimate the calibration uncertainties. The propagation of uncertainty from the rainfall generator to the hydrological model is also taken into account. This method is applied to 1112 basins throughout France. Uncertainties coming from the SHYREG method and from purely statistical approaches are compared, and the results are discussed according to the length of the recorded observations, basin size and basin location. Uncertainties of the SHYREG method decrease as the basin size increases or as the length of the recorded flow increases. Moreover, the results show that the confidence intervals of the SHYREG method are relatively small despite the complexity of the method and the number of parameters (seven). This is due to the stability of the parameters and takes into account the dependence of uncertainties due to the rainfall model and the hydrological calibration. Indeed, the uncertainties on the flow quantiles are on the same order of magnitude as those associated with the use of a statistical law with two parameters (here generalised extreme value Type I distribution) and clearly lower than those associated with the use of a three-parameter law (here generalised extreme value Type II distribution). For extreme flood quantiles, the uncertainties are mostly due to the rainfall generator because of the progressive saturation of the hydrological model.
Extreme events are rarely observed, so their analysis is generally based on observations of more frequent values. The relevance of the flood frequency analysis (FFA) method depends on its capability ...to estimate the frequency of extreme values with reasonable accuracy using extrapolation. An FFA method based on stochastic simulation of flood event is assessed based on its reliability and stability. For such an assessment, different training/testing decompositions are performed for a set of data from more than 1000 gauging stations. We showed that the method enables relevant 'predictive' estimates, e.g. by assigning correct return periods to the record values that are systematically absent in calibration datasets. The model is also highly stable vis-a-vis the sampling. This characteristic is linked to the use of regional statistical rainfall data and a simple rainfall-runoff model that requires the calibration of only one parameter.
Editor D. Koutsoyiannis Associate editor Q. Zhang
A snow model forced by temperature and precipitation is used to simulate the spatial distribution of snow water equivalent (SWE) over a 600 000 km² portion of the province ofQuebec, Canada. We ...propose to improve model simulations by assimilating SWE data from sporadic manual snow surveys with a particle filter. A temporally and spatially correlated perturbation of the meteorological forcing is used to generate the set of particles. The magnitude of the perturbations is fixed objectively. First, the particle filter and direct insertion were both applied on 88 sites for which measured SWE consisted of more or less five values per year over a period of 17 years. The temporal correlation of perturbations enables us to improve the accuracy and the ensemble dispersion of the particle filter, while the spatial correlation leads to a spatial coherence in the particle weights. The spatial estimates of SWE obtained with the particle filter are compared with those obtained through optimal interpolation of the snow survey data, which is the current operational practice in Quebec. Cross-validation results as well as validation against an independent dataset show that the proposed particle filter enables us to improve the spatial distribution of the snow water equivalent compared with optimal interpolation.
Celotno besedilo
Dostopno za:
BFBNIB, DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
The hourly rainfall stochastic model SHYPRE is based on the simulation of descriptive variables. It generates long series of hourly rainfall and enables an at-site empirical estimation of ...distribution quantiles over France. The present study focuses on the improvement of the rainfall generator by modelling storm characteristics dependence by the copula approach. An evaluation framework is proposed to evaluate the goodness-of-fit of a given method over a territory with a particular care for the extreme part of the distribution. It is used to illustrate the impact of the copula choice on the estimation of rainfall quantiles. Contrary to Clayton copula, both the Gumbel’s and Frank’s permit to improve significantly the performance of the model in the sub-daily rainfall generation. According to our criteria, the final version of SHYPRE proposes a better estimation of rainfall quantiles than the classical extreme value distributions.
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