We investigate the impact of implementing an up-to-date and detailed land cover dataset in high-resolution regional climate simulations. We used the Weather Research Forecast (WRF) model version 3.6.1 on a high horizontal resolution of 5 km × 5 km, with 29 vertical levels, covering mainland Europe. We performed simulations within the year 2050, using future Representative Concentration Pathway 8.5 mid-century projections, for 2 winter (January, February) and the 2 summer months (June, July) to investigate the seasonal dependency of the impact of the land cover datasets on and their interaction with the different meteorological conditions prevailing in summer and winter. We compare simulations using the CORINE Land Cover dataset (100 × 100 m) and the standard United States Geological Survey (USGS) (~ 1 × 1 km) land use data for the same periods. Our analysis shows that simulated meteorological variables (temperature at 2 m, wind speed, sensible and latent heat fluxes and PBL heights) differ significantly between the WRF simulations, linked to the land cover parameterization. We quantify and discuss the modelling uncertainties arising from surface-type classifications and motivate the use of high resolution, and continuously updated land use inventories in climate modelling, especially for future projections. Our findings are particularly important for the summer season and over large urban centers, and we strongly recommend the use of high-quality resolution land use data in modelling experiments studying heat waves in synergy with the urban heat island phenomenon and land–surface interactions.
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Arnold D, Schicker I, Seibert P (2010) High-resolution atmospheric modelling in complex terrain for future climate simulations (HiRmod), Vienna Scientific Cluster report 2010. http://www.boku.ac.at/met/envmet/hirmod.html. Accessed 4 Aug 2018
Ball FK (1960) Control of inversion height by surface heating. Q J R Meteorol Soc 86:483–494
Bruyère CL, Monaghan AJ, Steinhoff DF, Yates D (2015) Bias-Corrected CMIP5 CESM data in WRF/MPAS intermediate file format. TN-515+STR, NCAR. https://doi.org/10.5065/d6445jj7
Büttner G, Feranec G, Jaffrain G (2002) Corine land cover update 2000, Technical guidelines. EEA Technical report No 89. https://land.copernicus.eu/user-corner/technical-library/techrep89.pdf. Accessed 4 Aug 2018
De Meij A, Vinuesa J-F (2014) Impact of SRTM and Corine land cover data on meteorological parameters using WRF. Atmos Res 143:351–370
De Meij A, Bossioli E, Vinuesa J-F, Penard C, Price I (2015) The effect of SRTM and Corine Land Cover and SRTM data on calculated gas and PM10 concentrations in WRF-Chem. Atmos Environ 101:173–199
Fraedrich K, Kleidon A, Lunkeit F (1999) A green planet versus a desert world: estimating the effect of vegetation extremes on the atmosphere. J Clim 12:3156–3163
Gaillard JC (2010) Vulnerability, capacity and resilience: perspectives for climate and development policy. J Int Dev 22:218–232. https://doi.org/10.1002/jid.1675
Giorgi F, Gutowski WJ (2015) Regional dynamical downscaling and the CORDEX initiative. Annu Rev Environ Resour 40(1):467–490
Grell GA, Devenyi D (2002) A generalized approach to parameterizing convection combining ensemble and data assimilation techniques. Geophys Res Lett. https://doi.org/10.1029/2002GL015311
Grell GA, Peckham SE, Schmitz R, McKeen SA, Frost G, Skamarock WC, Eder B (2005) Fully coupled ‘online’ chemistry in the WRF model. Atmos Environ 39:6957–6976
Hong S-Y, Noh Y, Dudhia J (2006) A new vertical diffusion package with an explicit treatment of entrainment processes. Mon Weather Rev 134:2318–2341
Iacono MJ, Delamere JS, Mlawer EJ, Shephard MW, Clough SA, Collins WD (2008) Radiative forcing by long-lived greenhouse gases: calculations with the AER radiative transfer models. J Geophys Res 113:D13103
IPCC (2014) Climate Change (2014) Synthesis Report. In: Core Writing Team, Pachauri RK, Meyer LA (eds) Contribution of Working Groups I, II and III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. IPCC, Geneva
Jacob D, Petersen J, Eggert B, Alias A, Christensen O, Bouwer L, Braun A, Colette A, Déqué M, Georgievski G, Georgopoulou E, Gobiet A, Menut L, Nikulin G, Haensler A, Hempelmann N, Jones C, Keuler K, Kovats S, Kröner N, Kotlarski S, Kriegsmann A, Martin E, van Meijgaard E, Moseley C, Pfeifer S, Preuschmann S, Radermacher C, Radtke K, Rechid D, Rounsevell M, Samuelsson P, Somot S, Soussana J-F, Teichmann C, Valentini R, Vautard R, Weber B, Yiou P (2014) EURO-CORDEX: new high-resolution climate change projections for European impact research. Reg Environ Change 14(2):563–578
Kim Y, Sartelet K, Raut J-C, Chazatte P (2013) Evaluation of the weather research and forecast/urban model over greater Paris. Bound Layer Meteorol 149:105–132. https://doi.org/10.1007/s10546-013-9838-6
Kotlarski S, Keuler K, Christensen OB, Colette A, Déqué M, Gobiet A, Goergen K, Jacob D, Lüthi D, van Meijgaard E, Nikulin G, Schär C, Teichmann C, Vautard R, Warrach-Sagi K, Wulfmeyer V (2014) Regional climate modeling on European scales: a joint standard evaluation of the EURO-CORDEX RCM ensemble. Geosci Model Dev 7:1297–1333. https://doi.org/10.5194/gmd-7-1297-2014
Mesinger F, Veljovic K (2013) Limited area NWP and regional climate modeling: a test of the relaxation vs Eta lateral boundary conditions. Meteorol Atmos Phys 119:1–16. https://doi.org/10.1007/s00703-012-0217-5
Mesinger F, Veljovic K (2017) Eta vs. sigma: review of past results, Gallus–Klemp test, and large-scale wind skill in ensemble experiments. Meteorol Atmos Phys 129:573–593. https://doi.org/10.1007/s00703-016-0496-3
Morrison H, Thompson G, Tatarskii V (2009) Impact of cloud microphysics on the development of trailing stratiform precipitation in a simulated squall line: comparison of one- and two-moment schemes. Mon Weather Rev 137:991–1007
Pineda N, Jorba O, Jorge J, Baldasano JM (2004) Using NOAA AVHRR and SPOT VGT data to estimate surface parameters: application to a mesoscale meteorological model. Int J Remote Sens 25(1):129–143
Seneviratne SI, Corti T, Davin EL, Hirschi M, Jaeger EB, Lehner I, Orlowsky B, Teuling AJ (2010) Investigating soil moisture–climate interactions in a changing climate: a review. Earth Sci Rev 99(3–4):125–161
Skamarock WC, Klemp JB, Dudhia J, Gill DO, Barker DM, Duda MG, Huang X-Y, Wang W, Powers JG (2008) A description of the advanced research WRF version 3. NCAR Technical Notes-475 + STR. https://doi.org/10.5065/D68S4MVH
United Nations, Department of Economic and Social Affairs, Population Division (2015) World urbanization prospects: the 2014 revision (ST/ESA/SER.A/366)
Van den Hurk BJJM (1995) Sparse canopy parameterizations for meteorological models, Ph.D. thesis. Wageningen Agricultural University, Wageningen
Veljovic K, Rajkovic B, Fennessy MJ, Altshuler EL, Mesinger F (2010) Regional climate modeling: should one attempt improving on the large scales? Lateral boundary condition scheme: Any impact? Meteorol Z 19:237–246. https://doi.org/10.1127/0941-2948/2010/0460
Warner TT (2011) Numerical weather and climate prediction. Cambridge University Press, Cambridge, p 526
Zittis G, Hadjinicolaou P, Lelieveld J (2014) Role of soil moisture in the amplification of climate warming in the eastern Mediterranean and the Middle East. Clim Res 59(1):27–37
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De Meij, A., Zittis, G. & Christoudias, T. On the uncertainties introduced by land cover data in high-resolution regional simulations. Meteorol Atmos Phys 131, 1213–1223 (2019). https://doi.org/10.1007/s00703-018-0632-3