Impact of the selected boundary layer schemes and enhanced horizontal resolution on the Weather Research and Forecasting model performance on James Ross Island, Antarctic Peninsula

Michael Matějka; Kamil Láska

doi:10.5817/CPR2022-1-2

Impact of the selected boundary layer schemes and enhanced horizontal resolution on the Weather Research and Forecasting model performance on James Ross Island, Antarctic Peninsula

Vol.12,No.1(2022)

Michael Matějka Kamil Láska

https://doi.org/10.5817/CPR2022-1-2

PDF

Abstract

The output of the various Weather Research and Forecasting (WRF) model configurations was compared with ground-based observations in the northern part of James Ross Island, Antarctic Peninsula. In this region, a network of automatic weather stations deployed at ice-free sites (as well as small glaciers) is operated by the Czech Antarctic Research Programme. Data from these stations provide a unique opportunity to evaluate the WRF model in a complex terrain of James Ross Island. The model was forced by the ERA5 reanalysis data and the University of Bremen sea ice data. The model configurations include a novel Three-Dimensional Scale-Adaptive Turbulent Kinetic Energy (3D TKE) planetary boundary layer scheme and a more traditional Quasi-Normal Scale Elimination (QNSE) scheme. Impact of model horizontal resolution was evaluated by running simulations in both 700 m and 300 m. The validation period, 25 May 2019 to 12 June 2019, was selected to cover different stratification regimes of air temperature and a significant snowfall event. Air temperature was simulated well except for strong low-level inversions. These inversions occurred in 44% of all cases and contributed to a higher mean bias (2.0–2.9°C) at low-elevation sites than at high altitude sites (0.2–0.6°C). The selection of the 3D TKE scheme led to improvement at low-elevation sites; at high altitude sites, the differences between model configurations were rather small. The best performance in wind speed simulation was achieved with the combination of the 3D TKE scheme and 300 m model resolution. The most important improvement was decrease of bias at a coastal Mendel Station from 3.5 m·s‑1 with the QNSE scheme on the 700 m grid to 1.2 m·s‑1 with the 3D TKE scheme on the 300 m grid. The WRF model was also proven to simulate a large snowfall event with a good correspondence with the observed snow height.

Keywords:
polar meteorology; numerical simulation; WRF model; air temperature; snow cover; wind speed; Antarctic Peninsula

References

Aas, K. S., Berntsen, T. K., Boike, J., Etzelmüller, B., Kristjánsson, J. E., Maturilli, M., Schuler, T. V., Stordal, F. and Westermann, S. (2015): A comparison between simulated and observed surface energy balance at the Svalbard archipelago. Journal of Applied Meteorology and Climatology, 54: 1102-1119. doi: 10.1175/JAMC-D-14-0080.1

Aas, K.S., Dunse, T., Collier, E., Schuler, T.V., Berntsen, T.K., Kohler, J. and Luks, B. (2016): The climatic mass balance of Svalbard glaciers: A 1gree0-year simulation with a coupled atmosphere–glacier mass balance model. The Cryosphere, 10: 1089-1104. doi: 10.5194/tc-10-1089-2016

Bindschadler, R., Vornberger, P., Fleming, A., Fox, A., Mullins, J., Binnie, D., Paulsen, S., Granneman, B. and Gorodetzky, D. (2008): The landsat image mosaic of Antarctica. Remote Sensing of Environment, 112: 4214-4226. doi: 10.1016/j.rse.2008.07.006

Bromwich, D. H., Otieno, F. O., Hines, K. M., Manning, K. W. and Shilo, E. (2013): Comprehensive evaluation of polar weather research and forecasting model performance in the Antarctic. Polar weather research and forecasting model. Journal of Geophysical Research: Atmospheres, 118: 274-292. doi: 10.1029/2012JD018139

Cape, M.R., Vernet, M., Skvarca, P., Marinsek, S., Scambos, T. and Domack, E. (2015): Foehn winds link climate-driven warming to ice shelf evolution in Antarctica. Journal of Geophysical Research: Atmospheres, 120: 11,037-11,057. doi: 10.1002/2015JD023465

Davies, B. J., Carrivick, J. L., Glasser, N. F., Hambrey, M. J. and Smellie, J. L. (2012): Variable glacier response to atmospheric warming, northern Antarctic Peninsula, 1988–2009. The Cryosphere, 6: 1031-1048. doi: 10.5194/tc-6-1031-2012

Deb, P., Orr, A., Hosking, J. S., Phillips, T., Turner, J., Bannister, D., Pope, J. O. and Colwell, S. (2016): An assessment of the Polar Weather Research and Forecasting (WRF) model representation of near-surface meteorological variables over West Antarctica: Polar WRF Assessment Over West Antarctica. Journal of Geophysical Research: Atmospheres, 121: 1532-1548. doi: 10.1002/2015JD024037

Engel, Z., Láska, K., Nývlt, D. and Stachoň, Z. (2018): Surface mass balance of small glaciers on James Ross Island, north-eastern Antarctic Peninsula, during 2009–2015. Journal of Glaciology, 64: 349-361. doi: 10.1017/jog.2018.17

Gallée, H., Trouvilliez, A., Agosta, C., Genthon, C., Favier, V. and Naaim-Bouvet, F. (2013): Transport of snow by the wind: A comparison between observations in Adélie Land, Antarctica, and simulations made with the regional climate model MAR. Boundary-Layer Meteorology, 146: 133-147. doi: 10.1007/s10546-012-9764-z

Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz‐Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., Chiara, G., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R.J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., Rosnay, P., Rozum, I., Vamborg, F., Villaume, S. and Thépaut, J. (2020): The ERA5 global reanalysis. Quarterly Journal of the Royal Meteorological Society, 146: 1999-2049. doi: 10.1002/qj.3803

Howat, I. M., Porter, C., Smith, B. E., Noh, M.-J. and Morin, P. (2019): The reference elevation model of Antarctica. The Cryosphere, 13: 665-674. doi: 10.5194/tc-13-665-2019

Iacono, M. J., Delamere, J.S., Mlawer, E.J., Shephard, M.W., Clough, S.A. and Collins, W. D. (2008): Radiative forcing by long-lived greenhouse gases: Calculations with the AER radiative transfer models. Journal of Geophysical Research, 113: D13103. doi: 10.1029/ 2008JD009944

Johnson, H. K. (1999): Simple expressions for correcting wind speed data for elevation. Coastal Engineering, 36: 263-269. doi: 10.1016/S0378-3839(99)00016-2

Jonsell, U. Y., Navarro, F. J., Bañón, M., Lapazaran, J. J. and Otero, J. (2012): Sensitivity of a distributed temperature-radiation index melt model based on AWS observations and surface energy balance fluxes, Hurd Peninsula glaciers, Livingston Island, Antarctica. The Cryosphere, 6: 539-552. doi: 10.5194/tc-6-539-2012

Kern, S., Ozsoy-Çiçek, B. and Worby, A. (2016): Antarctic sea-ice thickness retrieval from ICESat: Inter-comparison of different approaches. Remote Sensing, 8: 538. doi: 10.3390/ rs8070538

Láska, K., Chládová, Z. and Hošek, J. (2017): High-resolution numerical simulation of summer wind field comparing WRF boundary-layer parametrizations over complex Arctic topography:

Case study from central Spitsbergen. Meteorologische Zeitschrift, 26: 391-408. doi: 10.1127/ metz/2017/0796

Lehning, M., Völksch, I., Gustafsson, D., Nguyen, T. A., Stähli, M. and Zappa, M. (2006): ALPINE3D: A detailed model of mountain surface processes and its application to snow hydrology. Hydrological Processes, 20: 2111-2128. doi: 10.1002/hyp.6204

Marsh, C. B., Pomeroy, J. W. and Wheater, H. S. (2020): The Canadian Hydrological Model (CHM) v1.0: A multi-scale, multi-extent, variable-complexity hydrological model – design and overview. Geoscientific Model Development, 13: 225-247. doi: 10.5194/gmd-13-225-2020

Matějka, M., Láska, K., Jeklová, K. and Hošek, J. (2021): High-resolution numerical modelling of near-surface atmospheric fields in the complex terrain of James Ross Island, Antarctic Peninsula. Atmosphere, 12: 360. doi: 10.3390/atmos12030360

Monaghan, A. J., Clark, M. P., Barlage, M. P., Newman, A. J., Xue, L., Arnold, J. R. and Rasmussen, R. M. (2018): High-resolution historical climate simulations over Alaska. Journal of Applied Meteorology and Climatology, 57: 709-731. doi: 10.1175/JAMC-D-17-0161.1

Niu, G.-Y., Yang, Z.-L., Mitchell, K. E., Chen, F., Ek, M. B., Barlage, M., Kumar, A., Manning, K., Niyogi, D., Rosero, E., Tewari, M. and Xia, Y. (2011): The community Noah land surface model with multiparameterization options (Noah-MP): 1. Model description and evaluation with local-scale measurements. Journal of Geophysical Research, 116: D12109. doi: 10.1029/2010JD015139

Oliva, M., Navarro, F., Hrbáček, F., Hernández, A., Nývlt, D., Pereira, P., Ruiz-Fernández, J. and Trigo, R. (2017): Recent regional climate cooling on the Antarctic Peninsula and associated impacts on the cryosphere. Science of The Total Environment, 580: 210-223. doi: 10.1016/j.scitotenv.2016.12.030

Shin, H. H., Dudhia, J. (2016): Evaluation of PBL parameterizations in WRF at subkilometer grid spacings: Turbulence statistics in the dry convective boundary layer. Monthly Weather Review, 144: 1161-1177. doi: 10.1175/MWR-D-15-0208.1

Spreen, G., Kaleschke, L. and Heygster, G. (2008): Sea ice remote sensing using AMSR-E 89-GHz channels. Journal of Geophysical Research, 113: C02S03. doi: 10.1029/2005JC003384

Steinhoff, D. F., Bromwich, D. H. and Monaghan, A. (2013): Dynamics of the foehn mechanism in the McMurdo Dry Valleys of Antarctica from polar WRF. Quarterly Journal of the Royal Meteorological Society, 139: 1615-1631. doi: 10.1002/qj.2038

Sukoriansky, S., Galperin, B. and Perov, V. (2005): Application of a new spectral theory of stably stratified turbulence to the atmospheric boundary layer over sea ice. Boundary-Layer Meteorology, 117: 231-257. doi: 10.1007/s10546-004-6848-4

Tastula, E.-M., Vihma, T. (2011): WRF model experiments on the Antarctic atmosphere in winter. Monthly Weather Review, 139: 1279-1291. doi: 10.1175/2010MWR3478.1

Tastula, E.-M., Vihma, T. and Andreas, E. L. (2012): Evaluation of polar WRF from modeling the atmospheric boundary layer over Antarctic sea ice in autumn and winter. Monthly Weather Review, 140: 3919-3935. doi: 10.1175/MWR-D-12-00016.1

Thompson, G., Field, P. R., Rasmussen, R. M. and Hall, W. D. (2008): Explicit forecasts of winter precipitation using an improved bulk microphysics scheme. Part II: Implementation of a new snow parameterization. Monthly Weather Review, 136: 5095-5115. doi: 10.1175/ 2008MWR2387.1

Turner, J., Lu, H., White, I., King, J. C., Phillips, T., Hosking, J. S., Bracegirdle, T. J., Marshall, G. J., Mulvaney, R. and Deb, P. (2016): Absence of 21^st century warming on Antarctic Peninsula consistent with natural variability. Nature, 535: 411-415. doi: 10.1038/ nature18645

Turton, J. V., Kirchgaessner, A., Ross, A. N. and King, J. C. (2017): Does high-resolution modelling improve the spatial analysis of föhn flow over the Larsen C Ice Shelf? Weather, 72: 192-196. doi: 10.1002/wea.3028

Turton, J.V., Mölg, T. and Van As, D. (2019): Atmospheric processes and climatological characteristics of the 79N Glacier (Northeast Greenland). Monthly Weather Review, 147: 1375-1394. doi: 10.1175/MWR-D-18-0366.1

Wang, W., Bruyere, C., Duda, M., Dudhia, J., Gill, D., Kavulich M., Werner, K., Chen, M., Lin, H-Ch., Michalakes, J., Rizvi, S., Zhang X., Berner, J., Munoz-Esparza, D., Reen, B., Ha, S. and Fossell, K. (2021): User’s guide for the advanced research WRF (ARW) modeling system version 4.3. Available at: https://www2.mmm.ucar.edu/wrf/users/docs/user_guide_v4/ v4.3/contents.html

Wille, J. D., Bromwich, D. H., Cassano, J. J., Nigro, M. A., Mateling, M. E. and Lazzara, M. A. (2017): Evaluation of the AMPS boundary layer simulations on the Ross ice shelf, Antarctica, with Unmanned Aircraft Observations. Journal of Applied Meteorology and Climatology, 56: 2239-2258. doi: 10.1175/JAMC-D-16-0339.1

Warner, T. T. (2011): Numerical weather and climate prediction. Cambridge University Press, Cambridge, New York, 526 p.

Zhang, X., Bao, J.-W., Chen, B. and Grell, E. D. (2018): A three-dimensional scale-adaptive turbulent kinetic energy scheme in the WRF-ARW model. Monthly Weather Review, 146: 2023-2045. doi: 10.1175/MWR-D-17-0356.1

Zhang, C., Zhang, J. (2018): Modeling study of foehn wind events in Antarctic Peninsula with WRF Forced by CCSM. Journal of Meteorological Research, 32: 909-922. doi: 10.1007/ s13351-018-8067-9

Metrics