Cold waves commonly occur in higher latitudes under prevailing high pressure systems especially during winter season which cause serious economical loss and cold related death. Accurate prediction of such severe weather events is important for decision making by administrators and for mitigation planning. An Advanced high resolution Weather Research and Forecasting mesoscale model is used to simulate a severe cold wave event occurred during January 2006 over Europe. The model is integrated for 31 days starting from 00UTC of 1 January 2006 with 30 km horizontal resolution. Comparison of the model derived area averaged daily mean temperatures at 2m height from different zones over the central Europe with observations indicates that the model is able to simulate the occurrence of the cold wave with the observed time lag of 1 to 3days but with lesser intensity. The temperature, winds, surface pressure and the geopential heights at 500?hPa reveal that the cold wave development associates with the southward progression of a high pressure system and cold air advection. The results have good agreement with the analysis fields indicates that the model has the ability to reproduce the time evolution of the cold wave event. 1. Introduction Advance information of extreme weather phenomena such as cold waves is very important to avert their adverse impact on the life and economy of a given region. Prediction of the cold weather events in advance of 15 to 30 days is a challenging issue for the researchers and is useful for the administrators to minimize the damage and for adopting necessary mitigation measures. Cold waves belong to the weather phenomenon which occurs when marked cooling of the air persists for a period of at least few days [1, 2]. Cold waves generally occur with an advection of cold air mass over a large area associated with radiative cooling when a blocking anticyclone develops and persists for at least few days. Several studies have reported observed strong warming in the end of the nineteen century, with an evident increase in minimum and maximum temperatures in Central and Eastern Europe [3, 4] and in the whole Baltic region [5] indicating that mortality risk increases every winter in Central and Eastern Europe [6]. Though the rise in mean daily and mean minimum temperatures does not necessarily affect the frequency of extreme cold weather [7]; however it exerts a strong impact on the environment and society. Numerical simulation of cold waves requires incorporation of the various atmospheric processes in the model such as the interaction of the
References
[1]
A. M. G. Klein Tank and G. P. K?nnen, “Trends in indices of daily temperature and precipitation extremes in Europe, 1946–99,” Journal of Climate, vol. 16, no. 22, pp. 3665–3680, 2003.
[2]
A. Moberg and P. D. Jones, “Trends in indices for extremes in daily temperature and precipitation in central and western Europe, 1901–99,” International Journal of Climatology, vol. 25, no. 9, pp. 1149–1171, 2005.
[3]
R. Heino, R. Brázdil, and R. Brázdil, “Progress in the study of climatic extremes in Northern and Central Europe,” Climatic Change, vol. 42, no. 1, pp. 151–181, 1999.
[4]
J. Wibig and B. Glowicki, “Trends of minimum and maximum temperature in Poland,” Climate Research, vol. 20, no. 2, pp. 123–133, 2002.
[5]
The BACC Author Team, Assessment of Climate Change for the Baltic Sea Basin, Springer, Berlin, Germany, 2008.
[6]
M. M. Huynen, P. Martens, D. Schram, M. P. Weijenberg, and A. E. Kunst, “The impact of heat waves and cold spells on mortality rates in the Dutch population,” Environmental Health Perspectives, vol. 109, no. 5, pp. 463–470, 2001.
[7]
J. E. Walsh, A. S. Phillips, D. H. Portis, and W. L. Chapman, “Extreme cold outbreaks in the United States and Europe, 1948–99,” Journal of Climate, vol. 14, no. 12, pp. 2642–2658, 2001.
[8]
J. S. Kain and J. M. Fritsch, “Convective parameterization for mesoscale models: the Kain-Fritsch scheme,” in The Representation of Cumulus Convection in Numerical Models, K. A. Emanuel and D. J. Raymond, Eds., Amer. Meteor. Soc., 1993.
[9]
J. S. Kain and J. Kain, “The Kain-Fritsch convective parameterization: an update,” Journal of Applied Meteorology, vol. 43, no. 1, pp. 170–181, 2004.
[10]
R. E. Dickinson, R. M. Errico, F. Giorgi, and G. T. Bates, “A regional climate model for the western United States,” Climatic Change, vol. 15, no. 3, pp. 383–422, 1989.
[11]
F. Giorgi and G. T. Bates, “The climatological skill of a regional model over complex terrain,” Monthly Weather Review, vol. 117, no. 11, pp. 2325–2347, 1989.
[12]
F. Giorgi, C. Shields Brodeur, and G.T. Bates, “Regional climate change scenarios over the United States produced with a nested regional climate model,” Journal of Climate, vol. 7, no. 3, pp. 375–399, 1994.
[13]
H. Hirakuchi and F. Giorgi, “Multiyear present-day and 2×CO2 simulations on monsoon climate over eastern Asia and Japan with a regional climate model nested in a general circulation model,” Journal of Geophysical Research, vol. 100, no. D10, pp. 21,105–21,125, 1995.
[14]
R. G. Jones, J. M. Murphy, and M. Noguer, “Simulation of climate change over Europe using a nested regional-climate model. I: assessment of control climate, including sensitivity to location of lateral boundaries,” Quarterly Journal of the Royal Meteorological Society, vol. 121, no. 526, pp. 1413–1449, 1995.
[15]
R. G. Jones, J. M. Murphy, M. Noguer, and A. B. Keen, “Simulation of climate change over Europe using a nested regional-climate model. II: comparison of driving and regional model responses to a doubling of carbon dioxide,” Quarterly Journal of the Royal Meteorological Society, vol. 123, no. 538, pp. 265–292, 1997.
[16]
J. H. Christensen, B. Machenhauer, R. G. Jones, C. Sch?r, P. M. Ruti, M. Castro, and G. Visconti, “Validation of present-day regional climate simulations over Europe. LAM simulations with observed boundary conditions,” Climate Dynamics, vol. 13, no. 7-8, pp. 489–506, 1997.
[17]
F. Georgi and L. O. Mearns, “Regional climate modeling revisited: an introduction to the special issue,” vol. IC/98/191, 1–44, 1998, http://www.ictp.trieste.it/~pub_off.
[18]
W. Wang, D. Barker, C. Bruyère, J. Dudhia, D. Gill, and J. Michalakes, “WRF Version 2 modeling system user’s guide,” 2004, http://www.mmm.ucar.edu/wrf/users/docs/user_guide/.
[19]
J. Michalakes, J. Dudhia, D. Gill, et al., “The weather research and forecast model: software architecture and performance,” in Proceeding of the 11th ECMWF Workshop on the Use of High Performance Computing in Meteorology, G. Mozdzynski, Ed., Reading, UK, October 2004.
[20]
W. C. Skamarock, J. B. Klemp, J. Dudhia, et al., “A description of the Advanced Research WRF Version 3,” Technical Note TN-475+STR, NCAR, 2008.
[21]
E. Kalnay, M. Kanamitsu, and M. Kanamitsu, “The NCEP/NCAR 40-year reanalysis project,” Bulletin of the American Meteorological Society, vol. 77, no. 3, pp. 437–471, 1996.
[22]
A. M. G. Klein Tank, J. B. Wijngaard, and J. B. Wijngaard, “Daily dataset of 20th-century surface air temperature and precipitation series for the European Climate Assessment,” International Journal of Climatology, vol. 22, no. 12, pp. 1441–1453, 2002.