Special Issue "Non-stationarity (Seasonality and Trends) in Time Series of Meteorological Extreme Events"

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Meteorology".

Deadline for manuscript submissions: closed (31 March 2023) | Viewed by 4937

Special Issue Editors

Director General Division, Croatian Meteorological andHydrological Service, 10000 Zagreb, Croatia
Interests: climate variations and trends in Croatia and Southeastern Europe; application of complex principal component analysis technique in explaining a connection between local meteorological field patterns; air temperature and precipitation, with patterns of large-scale circulation parameters like sea level air pressure; inhomogeneity of climate and hydrological time series; deterministic chaos; drought/wetness study using the Standardized Precipitation Index (SPI) and Palmer Drought Severity Index (PDSI); impact of climate variations and trends on water resources and agriculture
Special Issues, Collections and Topics in MDPI journals
Head of Data Processing and Management Department, Croatian Meteorological and Hydrological Service, Ravnice 48, 10000 Zagreb, Croatia
Interests: boundary-layer meteorology (application of Monin–Obukhov similarity theory for the wind speed estimation in the lower part of the atmospheric surface layer)
Special Issues, Collections and Topics in MDPI journals
Faculty of Civil Engineering, Architecture and Geodesy in Split, University of Split, Split, Croatia
Interests: engineering hydrology; karst hydrology; ecohydrology; climate changes; water resources research
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Meteorological (i.e., weather and climate) observations indicate that climate warming has grown worse in recent decades. It manifests in the increasingly frequent occurrence of extreme meteorological phenomena, including heat waves, intensive precipitation, and dry spells. Not only their frequency, but also their duration and intensity have increased in recent decades. A similar trend of changes is estimated for the next decades of the 21st century. At the same time, the aforementioned changes are accompanied by a decrease in the frequency of cold waves, including cold spells. As theoretical tools for analysis of meteorological extreme event time series usually require their specific characteristics (such as stationarity), strengthening of non-stationarity because of seasonality and trends becomes a big challenge, including estimation of their outlooks for future.

This issue will give preference to studies of any extreme meteorological phenomena, including air temperature and precipitation time series extremes, preferably using probability distributions adopted for a study of historical time series of extreme meteorological events under conditions of non-stationarity.

As extreme meteorological events produce great economic losses, the articles presented in this issue could be useful for a broad and diverse group of recipients.

Dr. Kreso Pandzic
Dr. Tanja Likso
Prof. Dr. Ognjen Bonacci
Guest Editors

Manuscript Submission Information

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Keywords

  • extreme weather and climate phenomena
  • non-stationarity of time series
  • probability distributions

Published Papers (3 papers)

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Research

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Article
Seasonal Aspects of Radiative and Advective Air Temperature Populations: A Canadian Perspective
Atmosphere 2022, 13(7), 1017; https://doi.org/10.3390/atmos13071017 - 24 Jun 2022
Cited by 2 | Viewed by 950
Abstract
Canadian high-frequency temperature time series exhibit physical heterogeneity in the coexistence of radiative and advective populations in the total air temperature sample. This work examines forty-five Canadian hourly air temperature records to study seasonal characteristics and variability of radiative and advective population counts [...] Read more.
Canadian high-frequency temperature time series exhibit physical heterogeneity in the coexistence of radiative and advective populations in the total air temperature sample. This work examines forty-five Canadian hourly air temperature records to study seasonal characteristics and variability of radiative and advective population counts and their corresponding temperature biases and trends. The Linear Pattern Discrimination algorithm, conceptualized in a previous study, was adjusted to seasonal analysis on the equinox-to-equinox time scale. Count analysis of radiative and advective days supports the existence of two distinct thermal regimes, Spring–Summer and Fall–Winter. Further, seasonal advective counts for the majority of examined stations typically decrease in numbers. The consistently warmer winter radiative temperature extrema points to the critical role of the advective population in control of the overall temperature magnitude. Canadian northwest warming trends are found to be the highest, indicating the amplifying effect of decreasing advective counts with rapidly increasing temperatures that weaken the advective population’s moderating ability to control the magnitude of the total temperature population. Full article
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Article
A Bayesian Hierarchical Spatial Copula Model: An Application to Extreme Temperatures in Extremadura (Spain)
Atmosphere 2021, 12(7), 897; https://doi.org/10.3390/atmos12070897 - 10 Jul 2021
Cited by 2 | Viewed by 1694
Abstract
A Bayesian hierarchical framework with a Gaussian copula and a generalized extreme value (GEV) marginal distribution is proposed for the description of spatial dependencies in data. This spatial copula model was applied to extreme summer temperatures over the Extremadura Region, in the southwest [...] Read more.
A Bayesian hierarchical framework with a Gaussian copula and a generalized extreme value (GEV) marginal distribution is proposed for the description of spatial dependencies in data. This spatial copula model was applied to extreme summer temperatures over the Extremadura Region, in the southwest of Spain, during the period 1980–2015, and compared with the spatial noncopula model. The Bayesian hierarchical model was implemented with a Monte Carlo Markov Chain (MCMC) method that allows the distribution of the model’s parameters to be estimated. The results show the GEV distribution’s shape parameter to take constant negative values, the location parameter to be altitude dependent, and the scale parameter values to be concentrated around the same value throughout the region. Further, the spatial copula model chosen presents lower deviance information criterion (DIC) values when spatial distributions are assumed for the GEV distribution’s location and scale parameters than when the scale parameter is taken to be constant over the region. Full article
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Review

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Review
A Review of Extreme Air Temperature Analysis in Croatia
Atmosphere 2022, 13(11), 1893; https://doi.org/10.3390/atmos13111893 - 12 Nov 2022
Cited by 1 | Viewed by 1118
Abstract
A historical review of extreme air temperature analysis in Croatia is presented. Two capital works on the subject were published in the 1970s by the Croatian Meteorological and Hydrological Service (DHMZ) and Faculty of Science University of Zagreb (PMF-Zagreb), respectively. The first is [...] Read more.
A historical review of extreme air temperature analysis in Croatia is presented. Two capital works on the subject were published in the 1970s by the Croatian Meteorological and Hydrological Service (DHMZ) and Faculty of Science University of Zagreb (PMF-Zagreb), respectively. The first is a monography on extreme value theory or extreme value analysis (EVA) with an application on more than a century-long time series of annual minima air temperature for Zagreb Grič weather station (Croatia) for the period 1862–1969. It is just a case study, with a lot of instructions regarding how to estimate the generalized extreme value (GEV) distribution parameters. The second is a master’s thesis with an application of the EVA on maxima air temperature time series for 41 weather stations from Croatia for the period 1950–1969. The shortness of the time series of the presented data caused instability in the estimation of GEV distribution parameters in transition areas from continental to maritime climate, but in general, the results are acceptable after a reduction of the 1950–1969 time series data on a ‘normal climate period’ 1910–1969. Both works were pioneering for that time in the South-Eastern Europe scale. A routine application of GEV distribution on the extreme air temperature (both minimum and maximum) for ten representative weather stations from Croatia is represented in Climate atlas of Croatia for the period 1961–1990, published by DHMZ in 2008. Theoretically estimated results fit well with empirical data. A review of long-term “warm” and “cold” indices of extreme air temperature for 41 weather stations from Croatia for the period 1951–2010 is represented in the Sixth National Communication Report of Croatia under the UNFCCC published by the Ministry for Environment and Nature Protection of Croatia (MZOIP) in 2014, showing a positive trend of “warm” and a negative trend of “cold” indices during the period 1951–2010 which tackled the non-stationarity of extreme air temperature time series. That topic of non-stationarity is more extensively considered using the results of a series of scientific papers published in the international journals which conducted a study of extreme air temperature of the wider Western Europe territory, including Croatia and other countries close to Croatia. Some authors of these papers stated that the GEV distribution parameters have to be considered as a function of time rather than fixed in time using covariates like North Atlantic Oscillation (NAO), coherent atmospheric blocking regions, linear trends in data caused by global warming and others covariates. The EVA results, connected with the global climate warming, could contribute to the national Natural Disaster Risk Reduction (NDRR) efforts. Full article
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