TY - JOUR

T1 - Stochastic simulation of the spatio-temporal field of the average daily heat index in southern Russia

AU - Kargapolova, Nina

N1 - Funding Information: Acknowledgements. The study of the real daily average heat index was carried out under state contract with ICMMG SB RAS (0315-2019-0002). The model development was partly financially supported by the Russian Foundation for Basic Research (grant No. 18-01-00149-a), as well as the Government of the Novosibirsk region according to research project No. 19-41-543001-r_mol_a. Publisher Copyright: © 2020 Inter-Research. All rights reserved. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.

PY - 2020

Y1 - 2020

N2 - Numerical models of the heat index time series and spatio-temporal fields can be used for a variety of purposes, from the study of the dynamics of heat waves to projections of the influence of future climate on humans. To conduct these studies one must have efficient numerical models that successfully reproduce key features of the real weather processes. In this study, 2 numerical stochastic models of the spatio-temporal non-Gaussian field of the average daily heat index (ADHI) are considered. The field is simulated on an irregular grid determined by the location of weather stations. The first model is based on the method of the inverse distribution function. The second model is constructed using the normalization method. Real data collected at weather stations located in southern Russia are used to both determine the input parameters and to verify the proposed models. It is shown that the first model reproduces the properties of the real field of the ADHI more precisely compared to the second one, but the numerical implementation of the first model is significantly more time consuming. In the future, it is intended to transform the models presented to a numerical model of the conditional spatio-temporal field of the ADHI defined on a dense spatio-temporal grid and to use the model constructed for the stochastic forecasting of the heat index.

AB - Numerical models of the heat index time series and spatio-temporal fields can be used for a variety of purposes, from the study of the dynamics of heat waves to projections of the influence of future climate on humans. To conduct these studies one must have efficient numerical models that successfully reproduce key features of the real weather processes. In this study, 2 numerical stochastic models of the spatio-temporal non-Gaussian field of the average daily heat index (ADHI) are considered. The field is simulated on an irregular grid determined by the location of weather stations. The first model is based on the method of the inverse distribution function. The second model is constructed using the normalization method. Real data collected at weather stations located in southern Russia are used to both determine the input parameters and to verify the proposed models. It is shown that the first model reproduces the properties of the real field of the ADHI more precisely compared to the second one, but the numerical implementation of the first model is significantly more time consuming. In the future, it is intended to transform the models presented to a numerical model of the conditional spatio-temporal field of the ADHI defined on a dense spatio-temporal grid and to use the model constructed for the stochastic forecasting of the heat index.

KW - Heat index

KW - Non-Gaussian random process

KW - Southern Russia

KW - Spatio-temporal random field

KW - Stochastic simulation

UR - http://www.scopus.com/inward/record.url?scp=85101341613&partnerID=8YFLogxK

U2 - 10.3354/CR01623

DO - 10.3354/CR01623

M3 - Article

AN - SCOPUS:85101341613

VL - 82

SP - 149

EP - 160

JO - Climate Research

JF - Climate Research

SN - 0936-577X

ER -