Телефон: 522-81-45

Geoinformatika 2017; 3(63) : 56-66  (in Ukrainian)

TOTAL CLOUD COVER IN UKRAINE TILL THE MID-21st CENTURY, BASED ON THE DATA OF AN ENSEMBLE OF REGIONAL CLIMATE MODELS

S.V. Krakovska1, L.V. Palamarchuk2, А.K. Bilozerova3, Т.M. Shpytal1

1Ukrainian Hydrometeorological Institute, 37, Prospekt Nauki, Kyiv, 03028, Ukraine, е-mail: svitlanakrakovska@gmail.com, shpital@bigmir.net
2Taras Shevchenko National University of Kyiv, 64/13, Volodymyrska Str., Kyiv, 01601, Ukraine, е-mail: palamarchuk.l@ukr.net
3Ukrainian Hydrometeorological Center, 6-В, Zolotovoritska Str., Kyiv-30, 01601, Ukraine, е-mail: alla.bilozerova@gmail.com

Purpose. The paper analyzes the features of spatiotemporal distributions of total cloud cover (TCC) in Ukraine for the past and future climatic periods. TCC and the number of clear and overcast days were analyzed based on the data from the Klimatychnyi Kadastr Ukrainy (Inventory of Climate in Ukraine) for the Standard WMO climatic period 1961-1990. The observation data at 9 meteorological stations evenly covering the territory of Ukraine in the period of 1961-2000 serve as a benchmark for verification and bias correction of regional climate models (RCMs) from the FP-6 ENSEMBLES initiated with boundary conditions from ERA-40 for 1961-2000 and IPCC SRES A1B for 1951-2050 (ensembles-eu.metoffice.com).
Design/methodology/approach. Verification of 12 RCMs by statistical analysis has shown the following: while the data of any individual RCM can have significant absolute errors affecting the reliability of projected characteristics, systematic errors of ensembles of RCMs are in general less significant and can be corrected based on the observational data in the past periods. The paper presents an original methodology of RCM verification and bias correction, which permits to identify and form for TCC an optimum ensemble of 9 RCMs initiated with different Atmosphere-Oceans Global Circulation Models that ensure maximum completeness and range of TCC under possible future climatic scenarios.
Findings. Spatiotemporal distributions of TCC in Ukraine for the periods of 2011-2030 and 2031-2050 calculated with the verified and bias-corrected ensemble of 9RCMs showed an overall decrease of annual TCC by 1-2% in both periods, with maximum values in spring and summer seasons up to 3%, while for winter seasons slight increase of TCC by 1% is projected. The obtained maps of expected annual and seasonal TCC changes show spatial inhomogeneity and allow us to analyze regional features in both future periods.
Practical value/implications. The obtained spatiotemporal distributions of TCC can serve as a basis for further re­search and evaluation of recent and future changes in other climate indicators associated with TCC and for many scientific fields and economic sectors related to and dependant on climate characteristics till the middle of the 21st century: agrometeorology, hydrology, biology, ecology, agriculture, energy, construction, transport, tourism, health care, recreation and others.

Keywords: total cloud cover, regional climate model, ensemble of models, verification of model data.

The full text of papers will be available after 01/04/2019

References:

  1. Research of climate change regional peculiarities in Ukraine for the 21st century based on numerical modeling. Zvitpro NDR (zaklyuchnyi). Shyfrroboty 1/11. Kyiv: Ukrainskyi hydrometeorolohichnyi instytut. 2013, 173 p. [in Ukrainian].
  2. Zabolotska T.M., Pidhurska V.M., Shpytal T.M. The features of cloud cover changes over Ukrainian territory during 1961-2008. Nauk. praci UNDHMI.Kyiv, 2011, iss. 260, pp. 54-66 [in Ukrainian].
  3. Zabolotska T.M., Shpyh V.M. Quantitative changes of cloud cover as indicator of global warming period. Nauk. praci UNDHMI. Kyiv, 2015, iss. 267, pp. 23-27 [in Ukrainian].
  4. Klimatychnyi kadastr Ukrainy (elektronna versiia). Derzhavna hidrometeorolohichna sluzhba, UNDHMI, Tsentralna Heofizychna Observatoriia. Kyiv, 2006 [in Ukrainian].
  5. Krakovska S.V., Gnatiuk N.V. Changes of Surface River Runoff in Ukraine till 2050 Based on the Projection of Regional Climate Model Remo. Geoinformatika. 2013, no. 3, pp. 76-81 [in Ukrainian].
  6. Krakovska S.V., Gnatiuk N.V., Shpytal T.M., Palamarchuk L.V. Projections of surface air temperature changes based on data of regional climate models ensemble in the regions of Ukraine in the 21st century. Nauk. praci UNDHMI. Kyiv, 2016, iss. 268, pp. 33-44 [in Ukrainian].
  7. Krakovska S.V., Palamarchuk L.V., Shpytal T.M. Electronic databases and results of numerical simulations in defining specialized climate indices. Hydrology, hydrochemistry and hydroecology: the scientific collection. Kyiv, 2016, vol. 3 (42), pp. 95-105 [in Ukrainian].
  8. Pirnach H.M. Chyselne modeliuvannia khmar ta opadiv u systemakh atmosfernykh frontiv. Kyiv: Nika-Tsentr, 2008, 295 p. [in Ukrainian].
  9. Shestoye natsionalnoye soobshcheniye Ukrainy po voprosam izmeneniya klimata podgotovlenoe na vypolneniye statey 4 i 12 Ramochnoy konventsii OON ob izmenenii klimata i stati 7 Kiotskogo protokola. Kyiv: 2012, 342 p.URL:http://unfccc.int/files/national_reports/annex_i_natcom/submitted_natcom/application/pdf/6nc_v7_final_[1].pdf (Accessed 30.05.2017) [in Russian].
  10. Gnatiuk N., Krakovska S., Palamarchuk L., Bilozerova A. Climate change projections for Ukraine in the 21st century based on the best RCM ensembles.Geophysical Research Abstracts. 2013. URL: http://meetingorganizer.copernicus.org/EGU2013/EGU2013-889-1.pdf(Accessed 30 May 2017).
  11. Nakićenović N., Swart R. Special Report on Emissions Scenarios. A Special Report of Working Group III of the Intergovernmental Panel on Climate Change. Cambridge: Cambridge University Press, 2000, 599 р.
  12. The science research and results of the ENSEMBLES project.URL: http://ensembles-eu.metoffice.com(Accessed 30 May 2017).
  13. Warren S.G., Eastman R.M., Hahn C.J. A survey of Changes in Cloud Cover and Cloud Types over Land from Surface Observations, 1971-96. rnal of Climate. 2007, no. 20, pp. 717-738.
  14. World Meteorological Day – 23 March 2017. https://public.wmo.int/en/WorldMetDay2017(Accessed 30 May 2017).