Climate Projections over the Great Lakes Region: Using Two-way Coupling of a Regional Climate Model with a 3-D Lake Model

Warming trends of the Laurentian Great Lakes and surrounding areas have been observed in recent decades, and concerns continue to rise about the pace and pattern of future climate change over the world’s largest freshwater system. To date, many regional climate models used for the Great Lakes projection either neglected the lake-atmosphere interactions or only coupled with 1-D column lake models to represent the lake hydrodynamics. The study presents the Great Lakes climate change projection that has employed the two-way coupling of a regional climate model with a 3-D lake model (GLARM) to resolve 3-D hydrodynamics important for large lakes. Using the three carefully selected CMIP5 AOGCMS, we show that the GLARM ensemble average substantially reduces the surface air temperature and precipitation biases of the driving AOGCM ensemble average in present-day climate simulations. The improvements are not only displayed from the atmospheric perspective but also evidenced in accurate simulations of lake surface temperature, and ice coverage and duration. After that, we present the GLARM projected climate change for the mid-21st century (2030–2049) and the late century (2080–2099) for the RCP4.5 and RCP8.5. Under RCP 8.5, the Great Lakes basin is projected to warm by 1.3–2.2 °C by the mid-21st century and 4.0–4.9 °C by the end of the century relative to the early-century (2000–2019). Moderate mitigation (RCP 4.5) reduces the mid-century warming to 0.8–1.9 °C and late-century warming to 1.8–2.7 °C. Annual precipitation in GLARM is projected to increase for the entire basin, varying from −0.4 % to 10.5 % during the mid-century and 1.2 % to 28.5 % during the late-century under different scenarios and simulations. The most significant increases are projected in spring and early summer when current precipitation is highest and little increase in winter when it is lowest. Lake surface temperatures (LSTs) are also projected to increase across the five lakes in all of the simulations, but with strong seasonal and spatial heterogeneities. The most significant LST increase will occur in Lake Superior. The strongest warming was projected in spring, followed by strong summer warming, suggesting earlier and more intense stratification in the future. In contrast, a relatively smaller increase in LSTs during fall and winter are projected with heat transfer to the deepwater due to strong mixing and energy required for ice melting. Correspondingly, the highest monthly mean ice cover is projected to be 3–6 % and 8–20 % across the lakes by the end of the century in RCP 8.5 and RCP 4.5, respectively. In the coastal regions, ice duration will decrease by up to 30–50 days.

A Bayesian Hierarchical Spatio-Temporal Model for Extreme Temperatures in Extremadura (Spain) Simulated by a Regional Climate Model

A statistical study was made of the temporal trend in extreme temperatures in the region of Extremadura (Spain) during the period 1981-2015 using a Regional Climate Model. For this purpose, a dataset of extreme temperature was obtained from the Weather Research and Forecating (WRF) Regional Climate Model. This dataset was then subjected to a statistical study using a Bayesian hierarchical spatio-temporal model with a Generalized Extreme Value (GEV) parametrization of the extreme data. The Bayesian model was implemented in a Markov chain Monte Carlo framework that allows the posterior distribution of the parameters that intervene in the model to be estimated. The role of the altitude dependence of the temperature was considered in the proposed model. The results for the spatial-trend parameter lend confidence to the model since they are consistent with the dry adiabatic gradient. Furthermore, the statistical model showed a slight negative trend for the location parameter. This unexpected result may be due to the internal and modeling uncertainties in the WRF model. The shape parameter was negative, meaning that there is an upper bound for extreme temperatures in the model.

Balanced estimate and uncertainty assessment of European climate change using the large EURO-CORDEX regional climate model ensemble

Large multiscenario multimodel ensembles (MMEs) of regional climate model (RCM) experiments driven by global climate models (GCMs) are made available worldwide and aim at providing robust estimates of climate changes and associated uncertainties. Due to many missing combinations of emission scenarios and climate models leading to sparse scenario–GCM–RCM matrices, these large ensembles, however, are very unbalanced, which makes uncertainty analyses impossible with standard approaches. In this paper, the uncertainty assessment is carried out by applying an advanced statistical approach, called QUALYPSO, to a very large ensemble of 87 EURO-CORDEX climate projections, the largest MME based on regional climate models ever produced in Europe. This analysis provides a detailed description of this MME, including (i) balanced estimates of mean changes for near-surface temperature and precipitation in Europe, (ii) the total uncertainty of projections and its partition as a function of time, and (iii) the list of the most important contributors to the model uncertainty. For changes in total precipitation and mean temperature in winter (DJF) and summer (JJA), the uncertainty due to RCMs can be as large as the uncertainty due to GCMs at the end of the century (2071–2099). Both uncertainty sources are mainly due to a small number of individual models clearly identified. Due to the highly unbalanced character of the MME, mean estimated changes can drastically differ from standard average estimates based on the raw ensemble of opportunity. For the RCP4.5 emission scenario in central–eastern Europe for instance, the difference between balanced and direct estimates is up to 0.8 ∘C for summer temperature changes and up to 20 % for summer precipitation changes at the end of the century.

A new perspective on permafrost boundaries in France during the Last Glacial Maximum

During the Last Glacial Maximum (LGM), a very cold and dry period around 26.5–19 kyr BP, permafrost was widespread across Europe. In this work, we explore the possible benefit of using regional climate model data to improve the permafrost representation in France, decipher how the atmospheric circulation affects the permafrost boundaries in the models, and test the role of ground thermal contraction cracking in wedge development during the LGM. With these aims, criteria for possible thermal contraction cracking of the ground are applied to climate model data for the first time. Our results show that the permafrost extent and ground cracking regions deviate from proxy evidence when the simulated large-scale circulation in both global and regional climate models favours prevailing westerly winds. A colder and, with regard to proxy data, more realistic version of the LGM climate is achieved given more frequent easterly winds conditions. Given the appropriate forcing, an added value of the regional climate model simulation can be achieved in representing permafrost and ground thermal contraction cracking. Furthermore, the model data provide evidence that thermal contraction cracking occurred in Europe during the LGM in a wide latitudinal band south of the probable permafrost border, in agreement with field data analysis. This enables the reconsideration of the role of sand-wedge casts to identify past permafrost regions.

The effect of topography on east African rainfall based on regional climate model

The effect of topography on June to August (JJA) rainfall over east Africa is investigated using the International Centre for Theoretical Physics (ICTP) Regional Climate Model (RegCM4.0). Grell convection scheme with Fritsch-Chappell closure assumption is used. The control simulation is done with actual topography and sensitivity experiments are carried out with topography reduced to 75%, 25% and to zero. The model output was evaluated against Climate Research Unit (CRU) dataset, gridded at 0.5 degree resolution and ERA-interim datasets, gridded at 0.75 degree resolution. Results show that the mean JJA rainfall significantly reduces over the region when topography elevation is reduced. Based on the model, when the topography over the selected region (KTU) is reduced to 25%, the mean JJA rainfall over east Africa is reduced by roughly half. The maximum rainfall reduction is however observed around the region over which topography is reduced. The reduction in topography resulted into an anomalous moisture divergence over the region at low level (850 hPa). Divergence at low level results in vertical shrinking which suppresses convection due to subsidence. The strength of moisture transport and the zonal wind speed at 850hpa increased with decrease in topography, which may be responsible for the observed shift in moisture convergence zone from western Kenya to northern Uganda. The findings from this study would provide insight into the effect of topography on the east African climate and call for more detailed investigative research, particularly in the region. The results may motivate researchers and modeling centers to further improve on the performance of the model over the region.

Towards an improved representation of carbonaceous aerosols over the Indian monsoon region in a regional climate model RegCM4.6

Mitigation of carbonaceous aerosol emissions is expected to provide climate and health co-benefits. The accurate representation of carbonaceous aerosols in climate models is critical for reducing uncertainties in their climate feedbacks. In this regard, emission fluxes and aerosol life-cycle processes are the two primary sources of uncertainties. Here we demonstrate that incorporating a dynamic ageing scheme and emission estimates that are updated for the local sources improve the representation of carbonaceous aerosols over the Indian monsoon region in a regional climate model, RegCM, compared to its default configuration. The mean BC and OC surface concentrations in 2010 are estimated to be 4.25 and 10.35 μg m−3, respectively, over the Indo-Gangetic Plain (IGP), in the augmented model. The BC column burden over the polluted IGP is found to be 2.47 mg m−2, 69.95 % higher than in the default model configuration and much closer to available observations. The anthropogenic AOD increases by more than 19 % over the IGP due to the model enhancement, also leading to a better agreement with observed AOD. The top-of-the-atmosphere, surface, and atmospheric anthropogenic aerosol shortwave radiative forcing are estimated at −0.3, −9.3, and 9.0 W m−2, respectively, over the IGP and −0.89, −5.33, and 4.44 W m−2, respectively, over Peninsular India. Our results suggest that both the accurate estimates of emission fluxes and a better representation of aerosol processes are required to improve the aerosol life cycle representation in the climate model.