Home Mathematics Numerical study of properties of air heat content indicators based on stochastic models of the joint meteorological series
Article
Licensed
Unlicensed Requires Authentication

Numerical study of properties of air heat content indicators based on stochastic models of the joint meteorological series

  • Nina A. Kargapolova EMAIL logo , Elena I. Khlebnikova and Vasily A. Ogorodnikov
Published/Copyright: April 12, 2019

Abstract

The paper presents results of numerical studies of stochastic properties of time series of the enthalpy of humid air and the heat index characterizing the heat content and thermal effects of humid air on human beings. The study was based on real meteorological observations and stochastic model of joint time series for surface air temperature and relative humidity taking into account daily course of real meteorological processes.

MSC 2010: 65C05; 65C20; 86A10
  1. Funding: The work was performed under the State Assignment of ICM&MG SB RAS (project 0315–2016–0002) and was partly financially supported by the Russian Foundation for Basic Research (project No. 18–01–00149-a) and by the President of the Russian Federation Grant (project No. MK–659.2017.1).

References

[1] P. Ailliot, D. Allard, V. Monbet, and P. Naveau, Stochastic weather generators: an overview of weather type models. J. Socit. Franaise. Stat. 156 (2015), No. 1, 101–113.Search in Google Scholar

[2] G. B. Anderson, M. L. Bell, and R. D. Peng, Methods to calculate the heat index as an exposure metric in environmental health research. Env. Health Perspect. 121 (2013), No. 10, 1111–1119.10.1289/ehp.1206273Search in Google Scholar PubMed PubMed Central

[3] J. Bessac, P. Ailliot, and V. Monbet, Gaussian linear state-space model for wind fields in the North–East Atlantic. Environmetrics26 (2015), No. 1, 29–38.10.1002/env.2299Search in Google Scholar

[4] I. Burton, K. L. Ebi, and G. McGregor, Biometeorology for adaptation to climate variability and change. In: Biometeorology for Adaptation to Climate Variability and Change. Biometeorology, 1. (Eds. K. L. Ebi, I. Burton, and G. R. McGregor). Springer, Dordrecht, 2009.10.1007/978-1-4020-8921-3Search in Google Scholar

[5] Center for Disease Control and Prevention. URL: https://www.cdc.gov/pictureofamerica/pdfs/Picture_of_America_Heat-Related_Illness.pdfSearch in Google Scholar

[6] K. V. Derenok and V. A. Ogorodnikov, Numerical simulation of significant long-term decreases in air temperature. Russ. J. Numer. Anal. Math. Modelling (2008) 23, No. 3, 223–277.10.1515/RJNAMM.2008.014Search in Google Scholar

[7] M. S. Desai and A. G. Dhorde, Trends in thermal discomfort indices over western coastal cities of India. Theor. Appl. Climatol. (2018) 131, No. 3–4, 1305–1321.10.1007/s00704-017-2042-8Search in Google Scholar

[8] A. I. Evstafieva, E. I. Khlebnikova, and V. A. Ogorodnikov, Numerical stochastic models for complexes of time series of weather elements. Russ. J. Numer. Anal. Math. Modelling20 (2005), No. 6, 535–548.10.1515/156939805774879606Search in Google Scholar

[9] C. R. de Freitas and E. A. Grigorieva, A comprehensive catalogue and classification of human thermal climate indices. Int. J. Biometeorology59 (2015), No. 1, 109–120.10.1007/s00484-014-0819-3Search in Google Scholar PubMed

[10] Guide to Meteorological Instruments and Methods of Observation: CIMO guide. WMO, Switzerland, 2014.Search in Google Scholar

[11] N. Kargapolova, Monte Carlo simulation of non-stationary air temperature time-series. In: Proc. 8th Int. Conf. Simulation and Modelling Methodologies, Technologies and Applications. 2018, pp. 323–329.10.5220/0006833403230329Search in Google Scholar

[12] N. Kargapolova, Stochastic model of the joint time-series of air temperature and atmospheric pressure. In: Proc. 32nd European Modelling and Simulation Conference. 2018, pp. 199–204.Search in Google Scholar

[13] N. Kargapolova, E. Khlebnikova, and V. Ogorodnikov, Monte Carlo simulation of the joint non-Gaussian periodically correlated time-series of air temperature and relative humidity. Stat. Papers (2018), 10.1007/s00362-018-1031-z.Search in Google Scholar

[14] Yu. Khomutskii, Usage of observed temperature data for designing of air conditioning and ventilation systems. World of Climate101 (2017), 156–161 (in Russian).Search in Google Scholar

[15] N. V. Kobisheva, V. V. Stadnik, M. V. Klueva, G. B. Pigoltsina, E. M. Akentieva, L. P. Galuk, E. N. Razova, and U. A. Semenov, Guidance on Specialized Climatological Service of the Economy. Asterion, St. Petersburg, 2008 (in Russian).Search in Google Scholar

[16] A. S. Marchenko and L. A. Minakova, Probabilistic model of air temperature time-series. Meteorology and Hydrology (1980), No. 9, 39–47 (in Russian).Search in Google Scholar

[17] M. A. Mikheev and I. M. Mikheeva, Basics of Heat Transfer. Energia, Moscow, 1977 (in Russian).Search in Google Scholar

[18] National Weather Service, URL: https://www.weather.gov/psr/HeatSafetySearch in Google Scholar

[19] V. E. Nitsis, Usage of climatic information for designing of ventilation and air conditioning systems. Proc. Voeikov Main Geophysical Observatory475 (1983), 3–7 (in Russian).Search in Google Scholar

[20] V. A. Ogorodnikov and S. M. Prigarin, Numerical Modelling of Random Processes and Fields: Algorithms and Applications. VSP, Utrecht, 1996.10.1515/9783110941999Search in Google Scholar

[21] A. G. Perry, M. J. Korenberg, G. G. Hall, and K. M. Moore, Modeling and syndromic surveillance for estimating weather-induced heat-related illness. J. Environ. Public Health (2011), 10.1155/2011/750236.Search in Google Scholar

[22] Z. A. Piranashvili, Some problems of statistical probabilistic modelling of random processes. In: Probl. Operat. Res., Tbilisi, 1966, pp. 53–91 (in Russian).Search in Google Scholar

[23] Z. Rakib, Characterization of climate change in southwestern Bangladesh: trend analysis of temperature, humidity, heat index, and rainfall. Clim. Res. (2018) 76, No. 3, 241–252.10.3354/cr01535Search in Google Scholar

[24] L. P. Rothfusz, The Heat Index ‘Equation’ (or, More Than You Ever Wanted to Know About Heat Index). SR 90–23. NOAA, Fort Worth, TX, 1990.Search in Google Scholar

[25] C. Schoen, A new empirical model of the temperature–humidity index. J. Appl. Meteorol. 44 (2005), 1413–1420.10.1175/JAM2285.1Search in Google Scholar

[26] Yu. V. Semenov, Air Conditioning Systems with Surface-Type Air Coolers. Technosphera, Moscow, 2014 (in Russian).Search in Google Scholar

[27] M. A. Semenov, Simulation of extreme weather events by a stochastic weather generator. Clim. Res. 35 (2008), 203–212.10.3354/cr00731Search in Google Scholar

[28] N. Shartova, D. Shaposhnikov, P. Konstantinov, and B. Revich, Cardiovascular mortality during heat waves in temperate climate: an association with bioclimatic indices. Int. J. Environ. Health Research28 (2018), No. 5, 522–534.10.1080/09603123.2018.1495322Search in Google Scholar

[29] R. G. Steadman, The assessment of sultriness, part I: A temperature-humidity index based on human physiology and clothing science. J. Appl. Meteor. 18 (1979), 861–873.10.1175/1520-0450(1979)018<0861:TAOSPI>2.0.CO;2Search in Google Scholar

[30] R. G. Steadman, A universal scale of apparent temperature. J. Climate. Appl. Meteorol. 23 (1984), 1674–1687.10.1175/1520-0450(1984)023<1674:AUSOAT>2.0.CO;2Search in Google Scholar

[31] A. Verdin, B. Rajagopalan, W. Kleiber, G. Podesta, and F. Bert, A conditional stochastic weather generator for seasonal to multi-decadal simulations. J. Hydrology (2015), doi:10.1016/j.jhydrol.2015.12.036.Search in Google Scholar

[32] S. Zare, N. Hasheminejad, H. E. Shirvan, R. Hemmatjo, K. Sarebanzadeh, and S. Ahmadi, Comparing universal thermal climate index (UTCI) with selected thermal indices/environmental parameters during 12 months of the year. Weather and Clim. Extremes19 (2018), 49–57.10.1016/j.wace.2018.01.004Search in Google Scholar

Received: 2018-11-23
Accepted: 2019-01-09
Published Online: 2019-04-12
Published in Print: 2019-04-24

© 2019 Walter de Gruyter GmbH, Berlin/Boston

Downloaded on 15.1.2026 from https://www.degruyterbrill.com/document/doi/10.1515/rnam-2019-0008/pdf
Scroll to top button