Statistical evaluation of temporary changes in annual precipitation in the plain territory of Ukraine

2020 ◽  
Vol 101-102 (3-4) ◽  
pp. 7-18
Author(s):  
Liudmyla Palamarchuk ◽  
Iryna Shedemenko
Keyword(s):  
Time Series ◽  
Linear Trend ◽  
Statistical Characteristics ◽  
Annual Precipitation ◽  
Mean Annual Precipitation ◽  
Positive Trend ◽  
The South ◽  
Positive Skewness ◽  
Weather Stations ◽  
Skewness And Kurtosis

The field of precipitation of the plain territory of Ukraine is investigated according to the data of evenly spaced 18 weather stations. The annual precipitation is analyzed for periods of different duration (from the beginning of observations at the station until 2015) and for the period 1961-2015. The main statistical characteristics are calculated, the patterns of their changes in the study area are shown. Gradient of decrease in multi-year annual precipitation for 1961-2015 (650 to 400 mm) directed from the northwest to the south and southeast of the country. The value of positive skewness and kurtosis, the coefficient of variation (0.16-0.26), on the contrary, increases in this direction. The standard deviation (91-137 mm) is maximum in the southwest and in the center of the plain part of Ukraine. It was determined that the distribution of annual precipitation can be considered normal, mainly with positive skewness and kurtosis. Multi-year fluctuations in annual precipitation are approximated by linear trend equations and a polynomial of the 6th degree. Regions with a negative and positive linear trend of annual precipitation in 1961-2015 were identified. A downward trend in precipitation was noted at stations located in a “strip” from the southwest (Chernivtsi) to the northeast (Sumy) through the center of Ukraine. In the south-west of this region (Vinnytsia), the decrease in precipitation is the greatest: the negative linear trend is statistically significant, the slope of the trend is -2.35, the coefficient of determination is 0.14; mean annual precipitation for 1991-2015 compared to 1961-1990 less by 10.5%, 53.4 mm. In the rest of the plain territory of the country, there was a tendency towards an increase in precipitation, but the positive trend for all stations is statistically insignificant. The absence of statistically significant linear trends (except for Vinnytsia) can be explained by the relative stability of the multi-year precipitation regime during this period. The use of a more complex approximation and a long time series of observations increased the trend approximation confidence, but the influence of these factors is not unambiguous for all weather stations. On the graphs of polynomial trends, the cycle manifestation in the time series of annual precipitation depends on the length of the observation series and decreases from west to east of Ukraine. The duration of the cycles is 25-30 and 35-40 years when determined according to the data of 1961-2015, and from 70 to 90 and 120 years according to the series of observations more than 100 years. In 2016-2025, as shown by estimates by the equations of polynomials of the 6th degree, a decrease in annual precipitation will prevail on the plain territory of Ukraine compared to 1961-2015. The largest decrease (by 10-13%) is likely in the central regions (Poltava, Dnipro). an increase (by 5%) - in the southwest (Vinnitsa, Chernivtsi).

scholarly journals A precipitation-based regionalization for Western Iran and regional drought variability

2008 ◽  
Vol 12 (6) ◽  
pp. 1309-1321 ◽  
Author(s):  
T. Raziei ◽  
I. Bordi ◽  
L. S. Pereira
Keyword(s):  
Linear Trend ◽  
Climatic Variability ◽  
Annual Precipitation ◽  
Time Variability ◽  
Positive Trend ◽  
The South ◽  
Western Iran ◽  
The North ◽  
Precipitation Regimes

Abstract. The spatial distribution of the seasonal and annual precipitation was analyzed in western Iran using data from 140 stations covering the period 1965–2000. Applying the Precipitation Concentration Index (PCI), the intra-annual precipitation variability was also studied. Furthermore, nine precipitation-derived parameters were used to regionalize climate in western Iran using principal component analysis and clustering techniques. Results suggest that five spatially homogenous sub-regions can be identified characterized by different precipitation regimes. The spatial pattern of seasonal precipitation seems to be highly controlled by the wide latitudinal extent of the region and by the pronounced orographic relieves, and the time of occurrence of the maximum precipitation varies from spring in the north to winter in the south. The time variability of dry and wet periods in the identified sub-regions was analyzed using the Precipitation Index (PI) and the existence of any long-term trend was tested. Results show that the northern and southern regions of western Iran are characterized by different climatic variability. Furthermore, a negative long-term linear trend in the north and a weak positive trend in the south of the study area have been detected though they are not statistically significant.

scholarly journals A precipitation-based regionalization for Western Iran and regional drought variability

2008 ◽  
Vol 5 (4) ◽  
pp. 2133-2167 ◽  
Author(s):  
T. Raziei ◽  
I. Bordi ◽  
L. S. Pereira
Keyword(s):  
Linear Trend ◽  
Climatic Variability ◽  
Annual Precipitation ◽  
Time Variability ◽  
Positive Trend ◽  
The South ◽  
Western Iran ◽  
The North ◽  
Precipitation Regimes

Abstract. The spatial distribution of the seasonal and annual precipitation was analyzed in western Iran using data from 140 stations covering the period 1965–2000. Applying the Precipitation Concentration Index (PCI), the intra-annual precipitation variability was also studied. Furthermore, nine precipitation-derived parameters were used to regionalize climate in western Iran using principal component analysis and clustering techniques. Results suggest that five spatially homogenous sub-regions can be identified characterized by different precipitation regimes. The spatial pattern of seasonal precipitation seems to be highly controlled by the wide latitudinal extent of the region and by the pronounced orographic relieves, and the time of occurrence of the maximum precipitation varies from spring in the north to winter in the south. The time variability of dry and wet periods in the identified sub-regions was analyzed using the Precipitation Index (PI) and the existence of any long-term trend was tested. Results show that the northern and southern regions of western Iran are characterized by different climatic variability. Furthermore, a negative long-term linear trend in the north and a weak positive trend in the south of the study area have been detected though they are not statistically significant.

Near-real time mapping of Keetch-Byram drought index in the south-eastern United States

2002 ◽  
Vol 11 (4) ◽  
pp. 281 ◽  
Author(s):  
Michael J. Janis ◽  
Michael B. Johnson ◽  
Gloria Forthun
Keyword(s):  
United States ◽  
Drought Index ◽  
Maximum Temperature ◽  
Daily Maximum Temperature ◽  
Mean Annual Precipitation ◽  
Eastern United States ◽  
The South ◽  
South Eastern ◽  
Input Parameters ◽  
Weather Stations

High spatial resolution maps of daily Keetch-Byram Drought Index (KBDI) are constructed for the south-eastern United States. KBDI is a cumulative algorithm for estimating fire potential from meteorological information, including daily maximum temperature, daily total precipitation, and mean annual precipitation. With few input parameters, the KBDI is attractive for providing estimates of fire potential at a large number of locations. The Southeast Regional Climate Center (SERCC) applies the original algorithms over daily time steps to maximize the response time in the event of rapidly increasing fire potential. Algorithms are applied to a network of 261 weather stations across the south-eastern United States to provide regional contour maps of KBDI as well as maps of week-to-week KBDI difference. Though uniformity and spatial density of weather stations and the consistency of input parameters are potential hurdles, it is shown that careful compilation of meteorological databases makes KBDI a tractable and valuable monitoring tool for automated fire-potential monitoring.

scholarly journals Spatiotemporal analysis of some extreme rainfall indices over Iraq (1981–2017)

2021 ◽  
Vol 30 (2) ◽  
pp. 221-235
Author(s):  
Alaa Al-Lami ◽  
Hasanain Al-Shamarti ◽  
Yaseen Al-Timimi
Keyword(s):  
Time Series ◽  
Extreme Rainfall ◽  
Spatiotemporal Analysis ◽  
Rate Of Change ◽  
Mean Annual Precipitation ◽  
Spatiotemporal Pattern ◽  
Northwestern Part ◽  
Positive Trend ◽  
Human Environment ◽  
The Impact

Extreme rainfall is one of the environmental hazards with disastrous effects on the human environment. Water resources management is very vulnerable to any changes in rainfall intensities. A spatiotemporal analysis is essential for study the impact of climate change and variability on extreme rainfall. In this study, daily rainfall data for 36 meteorological stations in Iraq during 1981–2017 were used to investigate the spatiotemporal pattern of 10 extreme rainfall indices using RClimDex package. These indices were classified into two categories: rainfall total (PRCPTOT, SDII, R95p, R99p, RX1day, and RX5day) and rainfall days (CDD, CWD, R10, and R20). Depending on the mean annual precipitation data, the study area was divided into three climatic zones to examine the time series features of those 10 indices. Results showed a tendency to increase in precipitation toward the northwestern part of Iraq, and more than 70% of stations achieved a positive trend for most indices. The most frequent negative trend appeared in eight stations distributed in the western and southern parts of Iraq, namely (Heet, Haditha, Anah, Rutba, Qaim, Nukheb, Najaf, and Fao). A significant positive trend appeared obviously in PRCPTOT and R95p with a rate of 0.1–4.6 and 0.5–2.7 mm per year, respectively. Additionally, the least trend increasing appeared in all precipitation days indices specifically in R10 and R20. Time series analyses revealed a positive trend in all regions under study, except SDII in the southern region. The most significant rate of change was noticed in regions one and two (northern and middle parts of Iraq), particularly for PRCPTOT and R95p 3.26 and 2.45 mm per day, respectively. Only the northern and eastern regions of Iraq experienced a high probability of significant extreme rainfall.

scholarly journals Spatio-Temporal Trends of Monthly and Annual Precipitation in Aguascalientes, Mexico

Atmosphere ◽  
2020 ◽  
Vol 11 (5) ◽  
pp. 437
Author(s):  
Osías Ruiz-Alvarez ◽  
Vijay P. Singh ◽  
Juan Enciso-Medina ◽  
Ronald Ernesto Ontiveros-Capurata ◽  
Arturo Corrales-Suastegui
Keyword(s):  
Time Series ◽  
Annual Precipitation ◽  
Irrigated Agriculture ◽  
Monthly Precipitation ◽  
Precipitation Trend ◽  
Precipitation Time Series ◽  
June July August ◽  
Precipitation Decrease ◽  
Weather Stations ◽  
June July

The objective of this research was to analyze the temporal patterns of monthly and annual precipitation at 36 weather stations of Aguascalientes, Mexico. The precipitation trend was determined by the Mann–Kendall method and the rate of change with the Theil–Sen estimator. In total, 468 time series were analyzed, 432 out of them were monthly, and 36 were annual. Out of the total monthly precipitation time series, 42 series showed a statistically significant trend (p ≤ 0.05), from which 8/34 showed a statistically significant negative/positive trend. The statistically significant negative trends of monthly precipitation occurred in January, April, October, and December. These trends denoted more significant irrigation water use, higher water extractions from the aquifers in autumn–winter, more significant drought occurrence, low forest productivity, higher wildfire risk, and greater frost risk. The statistically significant positive trends occurred in May, June, July, August, and September; to a certain extent, these would contribute to the hydrology, agriculture, and ecosystem but also could provoke problems due to water excess. In some months, the annual precipitation variability and El Niño-Southern Oscillation (ENSO) were statistically correlated, so it could be established that in Aguascalientes, this phenomenon is one of the causes of the yearly precipitation variation. Out of the total annual precipitation time series, only nine series were statistically significant positive; eight out of them originated by the augments of monthly precipitation. Thirteen weather stations showed statistically significant trends in the total precipitation of the growing season (May, June, July, August, and September); these stations are located in regions of irrigated agriculture. The precipitation decrease in dry months can be mitigated using shorter cycle varieties with lower water consumption, irrigation methods with high efficiency, and repairing irrigation infrastructure. The precipitation increase in humid months can be used to store water and use it during the dry season, and its adverse effects can be palliated with the use of varieties resistant to root diseases and lodging. The results of this work will be beneficial in the management of agriculture, hydrology, and water resources of Aguascalientes and in neighboring arid regions affected by climate change.

Multi-Time Scale Analysis on Characteristics of Precipitation in Hebei Province

2015 ◽  
Vol 1092-1093 ◽  
pp. 1165-1170 ◽  
Author(s):  
Meng Wang ◽  
Bao Hong Lu ◽  
Han Wen Zhang ◽  
Cong Fei Zhu
Keyword(s):  
Abrupt Change ◽  
Linear Trend ◽  
Kendall Test ◽  
Hebei Province ◽  
Change Points ◽  
Annual Precipitation ◽  
Precipitation Trend ◽  
Multi Scale ◽  
Weather Stations ◽  
Autumn And Winter

Based on the precipitation data observed monthly of 19 weather stations in Hebei province from 1960 to 2011, three methods, linear trend estimation, Mann-Kendall test as well as Morlet wavelet transformation, were adopted to analyze the characteristics of precipitation trend, abrupt change points and cyclical variations under the circumstance of multi-time scales in the past 52 years. Annual precipitation had a decreasing trend, and precipitation in spring increased dramatically, meanwhile precipitation of summer decreased significantly; however, precipitations in autumn and winter were fluctuated in an acceptable range. There were various abrupt change points both in annual precipitation series and in spring as well as in summer, yet any abrupt change points were found in autumn and winter. Multi-scale periodicities were found by wavelet analysis in annual and seasonal precipitations.

Models For Forecasting The Number Of Russian Grandparents

2021 ◽  
Author(s):  
Anna Bagirova ◽  
Oksana Shubat
Keyword(s):  
Time Series ◽  
Linear Trend ◽  
Statistical Characteristics ◽  
Trend Model ◽  
Human Fertility ◽  
First Child ◽  
Absolute Growth ◽  
Statistical Survey ◽  
Age Of Entry ◽  
Logistic Functions

Russian demographic statistics does not provide information about the number of grandparents. The aim of our study is to present models for forecasting their number. We used data from the Human Fertility Database to estimate the average age of a mother at the birth of her first child. Based on the simulated age of Russian women’s entry into grandparenthood, the time series of the number of Russian grandmothers was created. To obtain prospective estimates of the number of Russian grandmothers, we tested various models used in demography to forecast population size – mathematical (based on exponential and logistic functions) and statistical (based on statistical characteristics of time series). To estimate the number of grandmothers who are significantly involved in caring for grandchildren, we used data from the Federal statistical survey. Our results are as follows: 1) there is an increase in the age of entry into grandparenthood; 2) we estimated the size of potential grandmothers in different years and we found two models which are more appropriate for forecasting: linear trend model and average absolute growth model; 3) using these models, we predicted an increase in the number of both potential and active grandmothers in the next 5 years.

scholarly journals Antarctic ozone loss in 1979–2010: first sign of ozone recovery

2013 ◽  
Vol 13 (3) ◽  
pp. 1625-1635 ◽  
Author(s):  
J. Kuttippurath ◽  
F. Lefèvre ◽  
J.-P. Pommereau ◽  
H. K. Roscoe ◽  
F. Goutail ◽  
...  
Keyword(s):  
Time Series ◽  
Linear Trend ◽  
Piecewise Linear ◽  
Montreal Protocol ◽  
Successful Implementation ◽  
Positive Trend ◽  
Ozone Monitoring Instrument ◽  
Ozone Loss ◽  
Ozone Trends ◽  
Antarctic Ozone

Abstract. A long-term ozone loss time series is necessary to understand the evolution of ozone in Antarctica. Therefore, we construct the time series using ground-based, satellite and bias-corrected multi-sensor reanalysis (MSR) data sets for the period 1989–2010. The trends in ozone over 1979–2010 are also estimated to further elucidate its evolution in the wake of decreasing halogen levels in the stratosphere. Our analysis with ground-based observations shows that the average ozone loss in the Antarctic is about −33 to −50% (−90 to −155 DU (Dobson Unit)) in 1989–1992, and then stayed at around −48% (−160 DU). The ozone loss in the warmer winters (e.g. 2002 and 2004) is lower (−37 to −46%), and in the very cold winters (e.g. 2003 and 2006) it is higher (−52 to −55%). These loss estimates are in good agreement with those estimated from satellite observations, where the differences are less than ±3%. The ozone trends based on the equivalent effective Antarctic stratospheric chlorine (EEASC) and piecewise linear trend (PWLT) functions for the vortex averaged ground-based, Total Ozone Mapping Spectrometer/Ozone Monitoring Instrument (TOMS/OMI), and MSR data averaged over September–November exhibit about −4.6 DU yr−1 over 1979–1999, corroborating the role of halogens in the ozone decrease during the period. The ozone trends computed for the 2000–2010 period are about +1 DU yr−1 for EEASC and +2.6 DU yr−1 for the PWLT functions. The larger positive PWLT trends for the 2000–2010 period indicate the influence of dynamics and other basis functions on the increase of ozone. The trends in both periods are significant at 95% confidence intervals for all analyses. Therefore, our study suggests that Antarctic ozone shows a significant positive trend toward its recovery, and hence, leaves a clear signature of the successful implementation of the Montreal Protocol.

scholarly journals SPLINE MODELS OF CONTEMPORARY, 2030, 2060 AND 2090 CLIMATES FOR MICHOACÁN STATE, MÉXICO. IMPACTS ON THE VEGETATION

2012 ◽  
Vol 35 (4) ◽  
pp. 333
Author(s):  
Cuauhtémoc Sáenz-Romero ◽  
Gerald E. Rehfeldt ◽  
Nicholas L. Crookston ◽  
Pierre Duval ◽  
Jean Beaulieu
Keyword(s):  
General Circulation ◽  
Climate Models ◽  
Climate Model ◽  
Aridity Index ◽  
General Circulation Models ◽  
Annual Precipitation ◽  
Mean Annual Precipitation ◽  
Mean Annual Temperature ◽  
Emission Scenarios ◽  
Weather Stations

Climate data from 149 weather stations of Michoacán State, at Western México, were extracted from a spline climate model developed for México’s contemporary climate (1961-1990), and for climate projected for the decades centered in years 2030, 2060 and 2090. The model was constructed using outputs from three general circulation models (GCMs: Canadian, Hadley and Geophysical Fluid Dynamics) from two emission scenarios (A “pessimistic” and B “optimistic”). Mean annual temperature (MAT), mean annual precipitation (MAP), annual degree days > 5 °C (DD5), and annual aridity index (DD50.5/MAP) were mapped for Michoacán at an 1 km2 scale, and means were estimated averaging all weather stations. The state average in GCMs and emission scenarios point out that mean annual temperature would increase 1.4 °C by year 2030, 2.2 °C by year 2060 and 3.6 °C by year 2090; whereas annual precipitation would decrease 5.6 % by year 2030, 5.9 % by year 2060 and 7.8 % by year 2090. Climate models can be used for inferring plant-climate relationships and for developing programs to counteract global warming effects. Climate variables were estimated also at Pinus hartwegii and Pinus pseudostrobus growth locations, at Pico de Tancítaro in Central Western Michoacán and Nuevo San Juan Parangaricutiro (near Tancítaro), respectively. According to the annual aridity index values estimated for such locations, it is necessary to conduct assisted migration to match current genotypes to projected climates. This translates into an altitudinal shift of 400 to 450 m higher to match 2030 climates predicted by Canadian Model scenario A2, and 600 to 800 m to match 2060 climates.

scholarly journals Decadal variations in atmospheric water vapor time series estimated using ground-based GNSS

2016 ◽  
Author(s):  
Fadwa Alshawaf ◽  
Galina Dick ◽  
Stefan Heise ◽  
Tzvetan Simeonov ◽  
Sibylle Vey ◽  
...  
Keyword(s):  
Time Series ◽  
Water Vapor ◽  
Linear Trend ◽  
Precipitable Water ◽  
The Other ◽  
Global Navigation Satellite Systems ◽  
Positive Trend ◽  
Satellite Systems ◽  
Decadal Variations ◽  
Global Navigation Satellite

Abstract. Ground-based GNSS (Global Navigation Satellite Systems) have efficiently been used since the 1990s as a meteorological observing system. Recently scientists used GNSS time series of precipitable water vapor (PWV) for climate research. In this work, we use time series from GNSS, European Center for Medium-Range Weather Forecasts Reanalysis (ERA-Interim) data, and meteorological measurements to evaluate climate evolution in Central Europe. The assessment of climate change requires monitoring of different atmospheric variables such as temperature, PWV, precipitation, and snow cover. PWV time series were obtained by three methods: 1) estimated from ground-based GNSS observations using the method of precise point positioning, 2) inferred from ERA-Interim data, and 3) determined based on daily surface measurements of temperature and relative humidity. The other variables are available from surface meteorological stations or received from ERA-Interim. The PWV trend component estimated from GNSS data strongly correlates with that estimated from the other data sets. The linear trend is estimated by straight line fitting over 30 years of seasonally-adjusted PWV time series obtained using meteorological measurements. The results show a positive trend in the PWV time series at more than 60 GNSS sites with an increase of 0.3–0.6 mm/decade. In this paper, we compare the results of three stations. The temporal increment of the PWV correlates with the temporal increase in the temperature levels.

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