scholarly journals Multidimensional extremes: joint study of precipitation and temperature time series

2021 ◽  
Author(s):  
Beatrix Izsák ◽  
Tamás Szentimrey ◽  
Mónika Lakatos ◽  
Rita Pongrácz
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Extreme Values ◽  
Standardized Precipitation Index ◽  
Single Element ◽  
Average Temperature ◽  
Temperature And Precipitation ◽  
The Standardized Precipitation Index ◽  
Climatic Time Series ◽  
Precipitation And Temperature

<p>To study climate change, it is essential to analyze extremes as well. The study of extremes can be done on the one hand by examining the time series of extreme climatic events and on the other hand by examining the extremes of climatic time series. In the latter case, if we analyze a single element, the extreme is the maximum or minimum of the given time series. In the present study, we determine the extreme values of climatic time series by examining several meteorological elements together and thus determining the extremes. In general, the main difficulties are connected with the different probability distribution of the variables and the handling of the stochastic connection between them. The first issue can be solved by the standardization procedures, i.e. to transform the variables into standard normal ones. For example, the Standardized Precipitation Index (SPI) uses precipitation sums assuming gamma distribution, or the standardization of temperature series assumes normal distribution. In case of more variables, the problem of stochastic connection can be solved on the basis of the vector norm of the variables defined by their covariance matrix. According to this methodology we have developed a new index in order to examine the precipitation and temperature variables jointly. We present the new index with the mathematical background, furthermore some examples for spatio-temporal examination of these indices using our software MASH (Multiple Analysis of Series for Homogenization; Szentimrey) and MISH (Meteorological Interpolation based on Surface Homogenized Data Basis; Szentimrey, Bihari). For our study, we used the daily average temperature and precipitation time series in Hungary for the period 1870-2020. First of all, our analyses indicate that even though some years may not be considered extreme if only either precipitation or average temperature is taken in to account, but examining the two elements together these years were extreme years indeed. Based on these, therefore, the study of the extremes of multidimensional climate time series complements and thus makes the study of climate change more efficient compared to examining only one-dimensional time series.</p>

Creation of a representative climatological database for Hungary from 1870 to 2020

2021 ◽  
Author(s):  
Beatrix Izsák ◽  
Mónika Lakatos ◽  
Rita Pongrácz ◽  
Tamás Szentimrey ◽  
Olivér Szentes
Keyword(s):  
Time Series ◽  
Data Series ◽  
Data Sets ◽  
Average Temperature ◽  
Temperature And Precipitation ◽  
Innovation Fund ◽  
Daily Data ◽  
Observation Network ◽  
Meteorological Elements ◽  
Climate Studies

<p>Climate studies, in particular those related to climate change, require long, high-quality, controlled data sets that are representative both spatially and temporally. Changing the conditions in which the measurements were taken, for example relocating the station, or a change in the frequency and time of measurements, or in the instruments used may result in an fractured time series. To avoid these problems, data errors and inhomogeneities are eliminated for Hungary and data gaps are filled in by using the MASH (Multiple Analysis of Series for Homogenization, Szentimrey) homogenization procedure. Homogenization of the data series raises the problem that how to homogenize long and short data series together within the same process, since the meteorological observation network was upgraded significantly in the last decades. It is possible to solve these problems with the method MASH due to its adequate mathematical principles for such purposes. The solution includes the synchronization of the common parts’ inhomogeneities within three (or more) different MASH processing of the three (or more) datasets with different lengths. Then, the homogenized station data series are interpolated to the whole area of Hungary, to a 0.1 degree regular grid. For this purpose, the MISH (Meteorological Interpolation based on Surface Homogenized Data Basis; Szentimrey and Bihari) program system is used. The MISH procedure was developed specifically for the interpolation of various meteorological elements. Hungarian time series of daily average temperature and precipitation sum for the period 1870-2020 were used in this study, thus providing the longest homogenized, gridded daily data sets in the region with up-to-date information already included.</p><p><em>Supported by the ÚNKP-20-3 New National Excellence Program of the Ministry for Innovation andTechnology from the source of the National Research, Development and Innovation Fund.</em></p>

scholarly journals Climatic Trends in Different Bioclimatic Zones in the Chitwan Annapurna Landscape, Nepal

Climate ◽  
2020 ◽  
Vol 8 (11) ◽  
pp. 136
Author(s):  
Dol Raj Luitel ◽  
Pramod K. Jha ◽  
Mohan Siwakoti ◽  
Madan Lall Shrestha ◽  
Rangaswamy Munniappan
Keyword(s):  
Climate Change ◽  
Time Series Data ◽  
Lapse Rate ◽  
Series Data ◽  
Average Temperature ◽  
Temperature And Precipitation ◽  
Average Annual Temperature ◽  
Bioclimatic Zone ◽  
The Impact ◽  
Precipitation Trends

The Chitwan Annapurna Landscape (CHAL) is the central part of the Himalayas and covers all bioclimatic zones with major endemism of flora, unique agro-biodiversity, environmental, cultural and socio-economic importance. Not much is known about temperature and precipitation trends along the different bioclimatic zones nor how changes in these parameters might impact the whole natural process, including biodiversity and ecosystems, in the CHAL. Analysis of daily temperature and precipitation time series data (1970–2019) was carried out in seven bioclimatic zones extending from lowland Terai to the higher Himalayas. The non-parametric Mann-Kendall test was applied to determine the trends, which were quantified by Sen’s slope. Annual and decade interval average temperature, precipitation trends, and lapse rate were analyzed in each bioclimatic zone. In the seven bioclimatic zones, precipitation showed a mixed pattern of decreasing and increasing trends (four bioclimatic zones showed a decreasing and three bioclimatic zones an increasing trend). Precipitation did not show any particular trend at decade intervals but the pattern of rainfall decreases after 2000AD. The average annual temperature at different bioclimatic zones clearly indicates that temperature at higher elevations is increasing significantly more than at lower elevations. In lower tropical bioclimatic zone (LTBZ), upper tropical bioclimatic zone (UTBZ), lower subtropical bioclimatic zone (LSBZ), upper subtropical bioclimatic zone (USBZ), and temperate bioclimatic zone (TBZ), the average temperature increased by 0.022, 0.030, 0.036, 0.042 and 0.051 °C/year, respectively. The decade level temperature scenario revealed that the hottest decade was from 1999–2009 and average decade level increases of temperature at different bioclimatic zones ranges from 0.2 to 0.27 °C /decade. The average temperature and precipitation was found clearly different from one bioclimatic zone to other. This is the first time that bioclimatic zone level precipitation and temperature trends have been analyzed for the CHAL. The rate of additional temperature rise at higher altitudes compared to lower elevations meets the requirements to mitigate climate change in different bioclimatic zones in a different ways. This information would be fundamental to safeguarding vulnerable communities, ecosystem and relevant climate-sensitive sectors from the impact of climate change through formulation of sector-wise climate change adaptation strategies and improving the livelihood of rural communities.

scholarly journals Method Consideration of Variation Diagnosis and Design Value Calculation of Flood Sequence in Yiluo River Basin, China

Water ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 2722
Author(s):  
Xinxin Li ◽  
Xixia Ma ◽  
Xiaodong Li ◽  
Wenjiang Zhang
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Human Activities ◽  
Extreme Values ◽  
Frequency Estimation ◽  
Synthesis Method ◽  
Estimation Method ◽  
Stationary Time Series ◽  
Distribution Model ◽  
Design Flood

The conventional approaches of the design flood calculation are based on the assumption that the hydrological time series is subject to the same distribution in the past, present, and future, i.e., the series should be consistent. However, the traditional methods may result in overdesign in the water conservancy project since the series has non-stationary variations due to climate change and human activities. Therefore, it is necessary to develop a new approach for frequency estimation of non-stationary time series of extreme values. This study used four kinds of mutation test methods (the linear trend correlation coefficient, Mann–Kendall test, sliding t-test, and Pettitt test) to identify the trend and mutation of the annual maximum flow series (1950–2006) of three hydrological stations in the Yiluo River Basin. Then we evaluated the performance of two types of design flood methods (the time series decomposition-synthesis method, the mixed distribution model) under the impacts of climate change and human activities on hydro-meteorological conditions. The results showed that (a) the design flood value obtained by the time series decomposition-synthesis method based on the series of the backward restore is larger than that obtained by the decomposition synthesis method based on the series of the forward restore; (b) when the return period is 100 years or less, the design flood value obtained by the mixed distribution model using the capacity ratio parameter estimation method is less than that obtained by the hybrid distribution model with simulated annealing parameter estimation method; and (c) both methods can overcome sequence inconsistency in design frequencies. This study provides insight into the frequency estimation of non-stationary time series of extreme values under the impacts of climate change and human activities on hydro-meteorological conditions.

Relationship between heating/cooling period and changing temperature conditions in the urban areas of Hungary

2020 ◽  
Author(s):  
Csenge Dian ◽  
Attila Talamon ◽  
Rita Pongrácz ◽  
Judit Bartholy
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Energy Consumption ◽  
Extreme Values ◽  
Building Design ◽  
Temperature Time Series ◽  
Maximum Temperature ◽  
Design Parameters ◽  
Daily Average ◽  
Temperature Time

<p>Climate change, extreme weather conditions, and local scale urban heat island (UHI) effect altogether have substantial impacts on people’s health and comfort. The urban population spends most of its time in buildings, therefore, it is important to examine the relationship between weather/climate conditions and indoor environment. The role of buildings is complex in this context. On the one hand UHI effect is mostly created by buildings and artificial surfaces. On the other hand they account for about 40% of energy consumption on European average. Since environmental protection requires increased energy efficiency, the ultimate goal from this perspective is to achieve nearly zero-energy buildings. When estimating energy consumption, daily average temperatures are taken into account. The design parameters (e.g. for heating systems) are determined using temperature-based criteria. However, due to climate change, these critical values are likely to change as well. Therefore, it is important to examine the temperature time series affecting the energy consumption of buildings. For the analysis focusing on the Carpathian region within central/eastern Europe, we used the daily average, minimum and maximum temperature time series of five Hungarian cities (i.e. Budapest, Debrecen, Szeged, Pécs and Szombathely). The main aim of this study is to investigate the effect of changing daily average temperatures and the rising extreme values on building design parameters, especially heating and cooling periods (including the length and average temperatures of such periods).</p>

scholarly journals Drought cycle tracking in Hungary using Standardized Precipitation Index (SPI)

2019 ◽  
pp. 97-101 ◽  
Author(s):  
Safwan A. Mohammed ◽  
Endre Harsányi
Keyword(s):  
Climate Change ◽  
Eastern Europe ◽  
Natural Hazard ◽  
Standardized Precipitation Index ◽  
Precipitation Index ◽  
Rainfall Data ◽  
Trend Test ◽  
Economic Sectors ◽  
Similar Vein ◽  
The Standardized Precipitation Index

 Drought is one of the natural hazard risks which badly affects both agricultural and socio-economic sectors. Hungary, which is located in Eastern Europe has been suffering from different drought cycles; therefore, the aim of this study is to analyse the rainfall data obtained from ten metrological stations (Békéscsaba, Budapest, Debrecen, Győr, Kékestető, Miskolc, Pápa, Pécs, Szeged, Siófok, Szolnok) between 1985 and 2016, by using the Standardized Precipitation Index (SPI). The results showed that 2011 was recorded as the worst drought cycle of the studied period, where the SPI ranged between -0.22 (extreme drought) in Siófok, and 0.15 (no drought) in Miskolc. In a similar vein, the study highlighted the year 2010 to be the best hydrological year, when the SPI reached 0.73 (mildly wet) on average. Interestingly, the Mann-Kendall trend test for the drought cycle showed no positive trends in the study area. Finally, more investigation should be conducted into the climate change spatial drought cycle in Europe.

scholarly journals Analysing 21st century meteorological and hydrological drought events in Slovakia

2018 ◽  
Vol 66 (4) ◽  
pp. 393-403 ◽  
Author(s):  
Miriam Fendeková ◽  
Tobias Gauster ◽  
Lívia Labudová ◽  
Dana Vrablíková ◽  
Zuzana Danáčová ◽  
...  
Keyword(s):  
Water Balance ◽  
Extreme Values ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
River Basins ◽  
Hydrological Drought ◽  
Water Balance Components ◽  
Extreme Values Distribution ◽  
The Standardized Precipitation Index ◽  
The Relationship

Abstract Several quite severe droughts occurred in Europe in the 21st century; three of them (2003, 2012 and 2015) hit also Slovakia. The Standardized Precipitation Index (SPI) and Standardized Precipitation and Evapotranspiration Index (SPEI) were used for assessment of meteorological drought occurrence. The research was established on discharge time series representing twelve river basins in Slovakia within the period 1981–2015. Sequent Peak Algorithm method based on fixed threshold, three parametric Weibull and generalized extreme values distribution GEV, factor and multiple regression analyses were employed to evaluate occurrence and parameters of hydrological drought in 2003, 2011–2012 and 2015, and the relationship among the water balance components. Results showed that drought parameters in evaluated river basins of Slovakia differed in respective years, most of the basins suffered more by 2003 and 2012 drought than by the 2015 one. Water balance components analysis for the entire period 1931–2016 showed that because of continuously increasing air temperature and balance evapotranspiration there is a decrease of runoff in the Slovak territory.

scholarly journals Methods for the Design of Climate Change Scenario in Slovakia for the 21St Century

2009 ◽  
Vol 1 (1) ◽  
pp. 77-90 ◽  
Author(s):  
Marian Melo ◽  
Milan Lapin ◽  
Ingrid Damborska
Keyword(s):  
Climate Change ◽  
Time Series ◽  
21St Century ◽  
Climate Change Scenario ◽  
Change Scenario ◽  
Climate Change Scenarios ◽  
Precipitation Time Series ◽  
Impact Studies ◽  
Temperature And Precipitation ◽  
Mean Temperature

Abstract In this paper methods of climate-change scenario projection in Slovakia for the 21st century are outlined. Temperature and precipitation time series of the Hurbanovo Observatory in 1871-2007 (Slovak Hydrometeorological Institute) and data from four global GCMs (GISS 1998, CGCM1, CGCM2, HadCM3) are utilized for the design of climate change scenarios. Selected results of different climate change scenarios (based on different methods) for the region of Slovakia (up to 2100) are presented. The increase in annual mean temperature is about 3°C, though the results are ambiguous in the case of precipitation. These scenarios are required by users in impact studies, mainly from the hydrology, agriculture and forestry sectors.

scholarly journals An overview of drought events in the Carpathian Region in 1961–2010

2013 ◽  
Vol 10 (1) ◽  
pp. 21-32 ◽  
Author(s):  
J. Spinoni ◽  
T. Antofie ◽  
P. Barbosa ◽  
Z. Bihari ◽  
M. Lakatos ◽  
...  
Keyword(s):  
Climate Change ◽  
Heat Waves ◽  
Standardized Precipitation Index ◽  
Aridity Index ◽  
Research Centre ◽  
Drought Risk ◽  
Joint Research ◽  
Temperature And Precipitation ◽  
Carpathian Region ◽  
Drought Indicators

Abstract. The Carpathians and their rich biosphere are considered to be highly vulnerable to climate change. Drought is one of the major climate-related damaging natural phenomena and in Europe it has been occurring with increasing frequency, intensity, and duration in the last decades. Due to climate change, land cover changes, and intensive land use, the Carpathian Region is one of the areas at highest drought risk in Europe. In order to analyze the drought events over the last 50 yr in the area, we used a 1961–2010 daily gridded temperature and precipitation dataset. From this, monthly 0.1° × 0.1° grids of four drought indicators (Standardized Precipitation-Evapotranspiration Index (SPEI), Standardized Precipitation Index (SPI), Reconnaissance Drought Indicator (RDI), and Palfai Aridity/Drought Index (PADI)) have been calculated. SPI, SPEI, and RDI have been computed at different time scales (3, 6, and 12 months), whilst PADI has been computed on an annual basis. The dataset used in this paper has been constructed in the framework of the CARPATCLIM project, run by a consortium of institutions from 9 countries (Austria, Croatia, Czech Republic, Hungary, Poland, Romania, Serbia, Slovakia, and Ukraine) with scientific support by the Joint Research Centre (JRC) of the European Commission. Temperature and precipitation station data have been collected, quality-checked, completed, homogenized, and interpolated on the 0.1° × 0.1° grid, and drought indicators have been consequently calculated on the grid itself. Monthly and annual series of the cited indicators are presented, together with high-resolution maps and statistical analysis of their correlation. A list of drought events between 1961 and 2010, based on the agreement of the indicators, is presented. We also discuss three case studies: drought in 1990, 2000, and 2003. The drought indicators have been compared both on spatial and temporal scales: it resulted that SPI, SPEI, and RDI are highly comparable, especially over a 12-month accumulation period. SPEI, which includes PET (Potential Evapo-Transpiration) as RDI does, proved to perform best if drought is caused by heat waves, whilst SPI performed best if drought is mainly driven by a rainfall deficit, because SPEI and RDI can be extreme in dry periods. According to PADI, the Carpathian Region has a sufficient natural water supply on average, with some spots that fall into the ''mild dry'' class, and this is also confirmed by the FAO-UNEP aridity index and the Köppen-Geiger climate classification.

Spatiotemporal evolution of drought events and its contribution on vegetation growth in the river source region

2020 ◽  
Author(s):  
Shuang Zhu
Keyword(s):  
Climate Change ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Standardized Precipitation Index ◽  
Precipitation Index ◽  
Spatiotemporal Evolution ◽  
Area Index ◽  
Vegetation Growth ◽  
Evolution Characteristics ◽  
The Standardized Precipitation Index

<p><span lang="EN-US"><span>Climate change has been proved to exacerbate drought events and further cause huge economic and ecological losses worldwide. Therefore, it is of great significance to study the long-term evolution characteristics of drought events and quantify the impact of drought events on typical ecological indexes. Based on the measured historical precipitation data, the standardized precipitation index of different time scales was extracted to measure water deficit. The leaf area index with wide range and high precision was generated based on the Modis remote sensing image and denoising processing to represent vegetation growth. Trend analysis and change point analysis were carried out to study the spatiotemporal evolution characteristics of the concerned drought indexes. Then, with hypothesis test, appropriate copula multivariate analysis method was innovatively introduced to construct joint distribution of the standardized precipitation index and leaf area index. The contribution of drought on vegetation growth was expected to be quantified by deriving the conditional copula and preset marginal distributions. The upper Yangtze River where biomass is extremely sensitive to climate change was taken as a study area. The results show that drought events in this region have significant spatial heterogeneity. The leaf area index is highly influenced by the meteorological drought index. From no drought to severe drought, the vegetation index is distributed more and more toward the low value. Copula is very potential to find the inner relationship of the standardized precipitation index and leaf area index. The study is useful to deepen the understanding of the internal mechanism of drought events and discuss reasonable disaster prevention and mitigation countermeasures.</span></span></p> <p> </p>

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