The importance of using a high-resolution model to study the climate change on small islands: the Lesser Antilles case

Abstract

A B S T R A C T High-resolution climate change simulations over the Lesser Antilles are performed using the ALADIN-Climate regional climate model nested within the global model ARPEGE (Me´te´o-France). Three sets of simulations are conducted at 10 km grid spacing for reference (1971Á2000) and future climate (2071Á2100) 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 (3.28C vs. 2.38C 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.

Projected changes in wind speed and its energy potential in China using a high‐resolution regional climate model

“…Credible estimates of climate variables are the basis and premise of the assessment of the climate change impacts, while the high resolution of simulation is one of the decisive factors, especially for wind, precipitation and extreme climate variables, which are mainly subjected to regional terrains, vegetation, convection and so on. In terms of the importance of high resolution, Cantet et al found that high‐resolution simulation in temperature showed remarkable advantages over small islands. Lee and Hong thought that the finer resolution model was more efficient in producing the major characteristics the precipitation distribution and temperature distribution.…”

Projected Changes in Soil Temperature and Surface Energy Budget Components over the Alps and Northern Italy

“…As we aim to evaluate the climate change effects on the energy budget components, we also used the RCM output, instead of the station observations, to drive the LSM. Currently, horizontal resolutions of some RCMs are around 10 km (e.g., references [67][68][69][70][71]). This is sufficiently high to infer the general characteristics of the energy and hydrologic cycles for large and medium scale basins, though still quite coarse to allow the energy budget components in a small scale basin to be detailed (e.g., references [69,70]).…”

Projections of tropical cyclone rainfall over land with an Eulerian approach: Case study of three islands in the West Indies

“…Six‐hourly precipitation time series provided by ARPEGE were aggregated to obtain daily rainfall, for which we applied the well‐known quantile–quantile correction. Such correction method enables to reduce biases through the entire range of the distribution (Gudmundsson et al ., 2012) and is particularly well adapted for extreme rainfall (Cantet et al ., 2014). Each station is associated with the nearest (land) model point (see Figure 2).…”