Here we present the first multi-model ensemble of regional climate simulations at kilometer-scale horizontal grid spacing over a decade long period. A total of 23 simulations run with a horizontal grid spacing of $$\sim $$ ∼ 3 km, driven by ERA-Interim reanalysis, and performed by 22 European research groups are analysed. Six different regional climate models (RCMs) are represented in the ensemble. The simulations are compared against available high-resolution precipitation observations and coarse resolution ($$\sim $$ ∼ 12 km) RCMs with parameterized convection. The model simulations and observations are compared with respect to mean precipitation, precipitation intensity and frequency, and heavy precipitation on daily and hourly timescales in different seasons. The results show that kilometer-scale models produce a more realistic representation of precipitation than the coarse resolution RCMs. The most significant improvements are found for heavy precipitation and precipitation frequency on both daily and hourly time scales in the summer season. In general, kilometer-scale models tend to produce more intense precipitation and reduced wet-hour frequency compared to coarse resolution models. On average, the multi-model mean shows a reduction of bias from $$\sim \,$$ ∼ −40% at 12 km to $$\sim \,$$ ∼ −3% at 3 km for heavy hourly precipitation in summer. Furthermore, the uncertainty ranges i.e. the variability between the models for wet hour frequency is reduced by half with the use of kilometer-scale models. Although differences between the model simulations at the kilometer-scale and observations still exist, it is evident that these simulations are superior to the coarse-resolution RCM simulations in the representing precipitation in the present-day climate, and thus offer a promising way forward for investigations of climate and climate change at local to regional scales.
This paper presents the first multi-model ensemble of 10-year, "convection-permitting" kilometer-scale regional climate model (RCM) scenario simulations downscaled from selected CMIP5 GCM projections for historical and end of century time slices. The technique is to first downscale the CMIP5 GCM projections to an intermediate 12-15 km resolution grid using RCMs, and then use these fields to downscale further to the kilometer scale. The aim of the paper is to provide an overview of the representation of the precipitation characteristics and their projected changes over the greater Alpine domain within a Coordinated Regional Climate Downscaling Experiment Flagship Pilot Study and the European Climate Prediction system project, tasked with investigating convective processes at the kilometer scale. An ensemble of 12 simulations performed by different research groups around Europe is analyzed. The simulations are evaluated through comparison with high resolution observations while the complementary ensemble of 12 km resolution driving models is used as a benchmark to evaluate the added value of the convection-permitting ensemble. The results show that the kilometer-scale ensemble is able to improve the representation of fine scale details of mean daily, wet-day/hour frequency, wet-day/hour intensity and heavy precipitation on a seasonal scale, reducing uncertainty over some regions. It also improves the representation of the summer diurnal cycle, showing more realistic onset and peak of convection. The kilometer-scale ensemble refines and enhances the projected patterns of change from the coarser resolution simulations and even modifies the sign of the precipitation intensity change and heavy precipitation over some regions. The convection permitting simulations also show larger changes for all indices over the diurnal cycle, also suggesting a change in the duration of convection over some regions. A larger positive change of frequency of heavy to severe precipitation is found. The results are encouraging towards the use of convection-permitting model ensembles to produce robust assessments of the local impacts of future climate change.
Abstract. The Land Use and Climate Across Scales Flagship Pilot Study (LUCAS FPS) is a coordinated community effort to improve the integration of Land Use Change (LUC) in Regional Climate Models (RCMs) and to quantify the biogeophysical effects of LUC on local to regional climate in Europe. In the first phase of LUCAS, nine RCMs are used to explore the biogeophysical impacts of re-/afforestation over Europe. Namely, two idealized experiments representing respectively a non-forested and a maximally forested Europe are compared in order to quantify spatial and temporal variations in the regional climate sensitivity to forestation. We find some robust features in the simulated response to forestation. In particular, all models indicate a year-round decrease in surface albedo, which is most pronounced in winter and spring at high latitudes. This results in a winter warming effect, which is relatively robust across models. However, there are also a number of strongly diverging responses. For instance, there is no agreement on the sign of temperature changes in summer with some RCMs predicting a widespread cooling from forestation, a widespread warming, or a mixed response. A large part of the inter-model spread is attributed to the representation of land processes. In particular, differences in the partitioning of sensible and latent heat are identified as a key source of uncertainty. In contrast, for precipitation, the representation of atmospheric processes dictates more directly the simulated response. In conclusion, the multi-model approach we use here has the potential to deliver more robust and reliable information to stakeholders involved in land use planning, as compared to results based on single models. However, given the contradictory responses identified, our results also show that there are still fundamental uncertainties that need to be tackled to better anticipate the possible intended or unintended consequences of LUC on regional climates.
Western Iberia has recently shown increasing frequency of drought conditions coupled with heatwave events, leading to exacerbated limiting climatic conditions for plant growth. It is not clear to what extent wood growth and density of agroforestry species have suffered from such changes or recent extreme climate events. To address this question, tree-ring width and density chronologies were built for a Pinus pinaster stand in southern Portugal and correlated with climate variables, including the minimum, mean and maximum temperatures and the number of cold days. Monthly and maximum daily precipitations were also analyzed as well as dry spells. The drought effect was assessed using the standardized precipitation-evapotranspiration (SPEI) multi-scalar drought index, between 1 to 24-months. The climate-growth/density relationships were evaluated for the period 1958-2011. We show that both wood radial growth and density highly benefit from the strong decay of cold days and the increase of minimum temperature. Yet the benefits are hindered by long-term water deficit, which results in different levels of impact on wood radial growth and density. Despite of the intensification of long-term water deficit, tree-ring width appears to benefit from the minimum temperature increase, whereas the effects of long-term droughts significantly prevail on tree-ring density. Our results further highlight the dependency of the species on deep water sources after the juvenile stage. The impact of climate changes on long-term droughts and their repercussion on the shallow groundwater table and P. pinaster’s vulnerability are also discussed. This work provides relevant information for forest management in the semi-arid area of the Alentejo region of Portugal. It should ease the elaboration of mitigation strategies to assure P. pinaster’s production capacity and quality in response to more arid conditions in the near future in the region.
Despite the efforts of the modelling community to improve the representation of the sea surface temperature (SST) over the South Eastern Tropical Atlantic, warm biases still persist. In this work we use four different configurations of the fullycoupled AWI Climate Model (AWI-CM) which allow us to gain physics-based insight into the role of the oceanic and atmospheric resolutions of the model in the regional distribution of the SST. Our results show that a sole refinement of the oceanic resolution reduces warm biases further than a single increase of the atmospheric component. An increased oceanic resolution is required (i) to simulate properly the Agulhas Current and its associated rings; (ii) to reinforce the northwardflowing Benguela Current and (iii) to intensify coastal upwelling. The best results are obtained when both resolutions are refined. However, even in that case, warm biases persist, reflecting that some processes and feedbacks are still not optimally resolved. Our results indicate that overheating is not due to insufficient upwelling, but rather due to upwelling of waters which are warmer than observations as a result of an erroneous representation of the vertical distribution of temperature. Errors in the representation of the vertical temperature profile are the consequence of a warm bias in the simulated climate state.Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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