Initial Assessment of the Weather Research and Forecasting Model for Forecasting Bioclimatic Conditions During Breeze Circulation – Case Study of the Słowiński National Park
PDF

Keywords

breeze circulation
sea breeze index
WRF
the Słowiński National Park
bioclimatic conditions

How to Cite

Czernecki, B., & Półrolniczak, M. (2013). Initial Assessment of the Weather Research and Forecasting Model for Forecasting Bioclimatic Conditions During Breeze Circulation – Case Study of the Słowiński National Park. Quaestiones Geographicae, 32(3), 5–14. https://doi.org/10.2478/quageo-2013-0021

Abstract

Land-sea interaction at the Polish Baltic Coast impacts the specific local climate conditions. Thermally driven circulation, observed mainly in the summer season, causes the advection of the cool sea air over land and influences the local atmospheric environment, including bioclimatic conditions. The aim of this paper is to present the evaluation of the WRF model for forecasting sensitive bioclimatic conditions on a selected day with sea breeze in the vicinity of the Łeba Sandbar (the Słowiński National Park). The results obtained from a numerical weather prediction model were post-processed to calculate the daily variability of two biothermal indices: the Effective Temperature (ET) and the Dry Cooling Power (H). To evaluate the thermal comfort of a person wearing typical clothes, the Michajlow’s, Petrovič and Kacvińsky’s scales were adopted. A detailed analysis performed for 31st July 2010 shows in most cases a satisfactory level of agreement between the simulated data and the in-situ measurements for nested domains with horizontal grid resolution less than 2 km. However, the simulation results tend to underestimate the thermal comfort, especially in the middle part of the Łeba Sandbar due to terrain data misrepresentations, which results in the overestimation of wind speed.

https://doi.org/10.2478/quageo-2013-0021
PDF

References

Bednorz E., Kolendowicz L., 2010. Daily course of the soil temperature in summer in chosen ecosystems of Słowiński National Park, northern Poland. Quaestiones Geographicae 29(1): 5-12.

Błażejczyk K., 1980. Bioklimat Łeby (Bioclimate of Łeba). Problemy Uzdrowiskowe 7(153): 69-97.

Borzyszkowski J., Mordawski J., Treder J., 1999. Historia, geografia,język i piśmiennictwo Kaszubów - jazek i pismieniznaKaszebów. Wydawnictwo Marek Różak, Gdańsk.

Chen F., Dudhia J., 2001. Coupling an Advanced Land Surface- Hydrology Model with the Penn State-NCAR MM5 Modeling System. Part I: Model Implementation and Sensitivity. Monthly Weather Review 129: 569-585.

Chen F., Sun W.Y., 2002. A one-dimensional time dependent cloud model. Journal of Meteorological Society of Japan 80: 99-118.

Czernecki B., 2012. Wyznaczanie szorstkości aerodynamicznej modeli meteorologicznych w skali lokalnej. In: K. Fortuniak et al. (ed.), Przestrzeń w badaniach geograficznych. Wydawnictwo Uniwersytetu Łódzkiego: 112-119.

Czernecki B., 2013 [accepted]. Creating wind field time-series over the Southern Baltic area using a dynamical downscaling approach. Meteorologische Zeitschrift.

Duś E., 1993. Zagrożenia dla zdrowia w świadomości mieszkańców Górnośląskiego Okręgu Przemysłowego. In: M. Kowalski (ed.), Materiały Konferencji z Geografii Medycznej“Zdrowie a środowisko”, UMCS, Lublin: 157-166.

JRC-EEA, 2005. CORINE land cover updating for the year 2000: image 2000 and CLC2000. In: V. Lima (ed.), Productsand Methods. Report EUR 21757 EN. JRC-Ispra.

Kain J.S., 2004. The Kain-Fritsch Convective Parameterization: An Update. Journal of Applied Meteorology 43: 170-181.

Kolendowicz L., Bednorz E., 2010. Topoclimatic differentiation of the area of the Słowiński National Park, Northern Poland. Quaestiones Geographicae. 29(1): 49-56.

Kondracki J., 2002. Geografia regionalna Polski. PWN, Warszawa.

Kozłowska-Szczęsna T., Błażejczyk K., Krawczyk B., 1997. Bioklimatologia człowieka. Metody i ich zastosowanie w badaniach bioklimatu Polski. Monografie IGiPZ PAN. 1.

Lin Y.-L., Farley R.D., Orville H.D., 1983. Bulk parameterization of the snow field in a cloud model. Journal of AppliedMeteorology 22: 1065-1092.

Matzarakis A., 2006. Weather and climate related information for tourism. Tour Hosp. Plan Dev 3: 99-115.

Michalczewski J., 1967. Synoptyczne studium bryz morskich polskiegowybrzeża Bałtyku. PSHM, Warszawa.

Mlawer E.J., Taubman S.J., Brown P.D., Iacono M.J., Clough S.A., 1997. Radiative transfer for inhomogeneous atmosphere: RRTM, a validated correlated-k model for the long-wave. Journal of Geophysical Research 102(D14): 16663-16682.

Papanastasiou D., Melas D., Bartzanas T., Kittas C., 2010. Temperature, comfort and pollution levels during heat waves and the role of sea breeze. International Journal ofBiometeorology 54: 307-317.

Pena A., Hahmann A., Hasager C., Bingol F., Karagali I., Badger J., Badger M., Clausen N., 2011. South Baltic WindAtlas: South Baltic Offshore Wind Energy Regions Project. Technical report, Danmarks Tekniske Universitet, Risø Nationallaboratoriet for Bæredygtig Energi.

Półrolniczak M., 2011. Sensible temperature at the Łeba Sandbar (Słowiński National Park) on selected days of the 2010 summer season. Quaestiones Geographicae 30(3): 83-99.

Reynolds R.W., Smith T.M., Liu C., Chelton D.B., Casey K.S., Schlax M.G., 2007. Daily High-Resolution-Blended Analyses for Sea Surface Temperature. Journal of Climate 20: 5473-5496.

Simpson J., 1994. Sea breeze and local winds. Cambridge University Press. 248 p.

Skamarock W.C., Klemp J.B., Dudhia J., Gill D.O., Barker D.M., Wang W., Powers J.G., 2005. A description of the AdvancedResearch WRF Version 2. NCAR Tech Notes-468.

Świątek M., 2004. Wieloletnia i sezonowa zmienność wektora wiatru geostroficznego nad południowym Bałtykiem. In: M. Ciaciura (ed.), Stan środowiska przyrodniczego podstawowymwarunkiem zdrowotności społeczeństwa, Wyd. Uniw. Szczec. 239-250.

Tijm A.B.C., Holtslag A.A.M., van Delden A.J., 1999. Observations and modeling of the sea breeze with the return current. Monthly Weather Review 127: 625-640.