scholarly journals STATISTICAL MODELS FOR FORECASTING AVERAGE MONTHLY TEMPERATURE AND MONTHLY PRECIPITATION AMOUNT IN PERM

2021 ◽  
pp. 84-95
Author(s):  
Valery N. Aptukov ◽  
◽  
Victor Yu. Mitin ◽  
Keyword(s):  
Precipitation Amount ◽  
Forecast Accuracy ◽  
Statistical Characteristics ◽  
Monthly Precipitation ◽  
Total Precipitation ◽  
Average Temperature ◽  
Temperature And Precipitation ◽  
Precipitation Anomalies ◽  
Fractality Index ◽  
Climate Series

The article proposes an approach to forecasting mean temperature and total precipitation for the upcoming month, based on the study of the regularities of the influence of statistical characteristics of temperature and precipitation of previous periods on them. Among the predictors, along with the basic statistical characteristics, we use the fractality index which is an indicator of the randomness/ determinism of the climate series. Within the framework of this approach, we have developed models of different levels to predict the temperature and total precipitation amount in the upcoming month. The main parameters of these models are described and the possibilities of their variation are indicated. Examples are given to illustrate the forecasting methodology using various types of models and include the results of quality control of the models, calculation of forecast accuracy and dependence of forecast accuracy of average temperature and precipitation on the month (climate season). When tested in 2020, models for forecasting temperature and precipitation for the upcoming month give good results: 9 correct forecasts of temperature anomalies out of 10 (90%) and 7 correct forecasts of precipitation anomalies out of 9 (77,7%).

scholarly journals ANALYSIS OF CHANGES IN AIR TEMPERATURE AND PRECIPITATION ACCORDING TO THE DATA OF WEATHER STATIONS STARITSA AND TVER OVER A LONG PERIOD

2020 ◽  
pp. 57-78
Author(s):  
Лариса Эдуардовна Лапина ◽  
Ирина Леонидовна Григорьева
Keyword(s):  
Air Temperature ◽  
Least Squares Method ◽  
Average Rate ◽  
Statistical Characteristics ◽  
Monthly Precipitation ◽  
Weather Station ◽  
Regional Variability ◽  
Temperature And Precipitation ◽  
Significant Difference ◽  
Weather Stations

Анализируется региональная изменчивость среднемноголетних характеристик температуры воздуха в приземном слое и осадков по данным метеостанций в Старице и Твери, расположенных в бассейне верхней Волги. Среднегодовые и среднемесячные значения характеристик проанализированы с использованием метода скользящего среднего. Рассмотрен 30-летний период осреднения. Проанализированы данные по метеостанции Старица с 1962 по 2017 гг., а по метеостанции Тверь - с 1944 по 2017 гг. Для Старицы использованы суточные данные, для Твери - только среднемесячные. Данные температуры приземного слоя воздуха для каждого года наблюдений аппроксимировались простой синусоидальной функцией. Показано, что среднемноголетние значения амплитуд годовых колебаний для обеих метеостанций имеют тенденцию к снижению, а среднегодовые значения температур - тенденцию к повышению. Методом наименьших квадратов найдены параметры уравнений прямых, описывающих изменчивость среднемноголетних величин амплитуд годовых колебаний и среднемноголетних годовых температур воздуха. Сравнивались периоды наблюдений с 1961 по 1990 гг. и с 1991 по 2017 гг. для Твери и Старицы. Приводятся статистические характеристики температуры воздуха и осадков для двух периодов, сопоставлены значения метеостанций в Старице и Твери. Показано, что существенная разница между значениями температуры воздуха для обеих метеостанций наблюдается только во втором периоде. Среднемноголетние годовые суммы атмосферных осадков в этих городах имеют тенденцию к повышению со средней скоростью 18 мм/год. Месячные суммы атмосферных осадков однозначной тенденции, одинаковой для всех месяцев, не имеют. Скорость роста среднемноголетних значений температуры воздуха в Твери оценивается в 0.04˚С/год, в Старице - 0.03˚С/год. Regional variability of the average annual characteristics of air temperature in the surface layer and precipitation is analyzed based on data from weather stations in Staritsa and Tver, located in the Upper Volga basin. The average annual and average monthly values of the characteristics are analyzed using the moving average method. The 30-year averaging period is considered. Data on the Staritsa weather station from 1962 to 2017 and on the Tver weather station from 1944 to 2017 were analyzed. For Staritsa daily data were used, while for Tver only the average monthly data was used. The surface air temperature data for each year of observations was approximated by a simple sinusoidal function. It is shown that the average annual values of the amplitudes of annual fluctuations for both weather stations tend to decrease, and the average annual values of temperatures tend to increase. The parameters of the linear equations describing the variability of the average annual values of the amplitudes of annual fluctuations and the average annual air temperatures are found using the least squares method. We compared the observation periods from 1961 to 1990 and from 1991 to 2017 for Tver and Staritsa. Statistical characteristics of air temperature and precipitation for both periods are given. Values for both weather stations are compared. It is shown that a significant difference between the air temperature values for both weather stations is observed only in the second period. The average annual precipitation in both cities tends to increase at an average rate of 18 mm /year. Monthly precipitation totals do not have the same trend for all months. The rate of growth of the average annual air temperature in Tver is estimated at 0.04˚C/year, in Staritsa - 0.03˚C/year.

The effect of N, P, S fertilizer, temperature and precipitation on the yield of bromegrass and alfalfa pasture established on a Luvisolic soil

1991 ◽  
Vol 71 (4) ◽  
pp. 1047-1055 ◽  
Author(s):  
W. F. Nuttall ◽  
D. H. McCartney ◽  
P. R. Horton ◽  
S. Bittman ◽  
J. Waddington
Keyword(s):  
Phosphate Fertilizer ◽  
Maximum Temperature ◽  
Total Precipitation ◽  
Significant Drop ◽  
Average Temperature ◽  
Temperature And Precipitation ◽  
Average Maximum ◽  
Wide Range ◽  
Herbage Yield ◽  
Average Maximum Temperature

This study was conducted over a 12-yr period to determine the effect of N, P, and S (elemental) fertilizers on yield of bromegrass (Bromus inermis Leyss.) and alfalfa (Medicago media Pers.) pasture established on a Gray Wooded, Luvisolic soil (Waitville loam) in northeastern Saskatchewan. Nitrogen fertilizer was applied at 0, 45, and 90 kg N ha−1 in combination with phosphate fertilizer applied at 0 and 20 kg P ha−1. Two additional treatments combined 90 N + 20 P (kg ha−1) with 23 S and 45 S (kg ha−1). In the first 3 yr of the study, only the application of N increased yields, from 2.54 to 3.45 t ha−1. The combination of time (years 1978–1980) and N fertilizer applied up to the rate of 90 kg N ha−1 resulted in a reduction in percentage alfalfa in the sward from 30.9 to 3.8% (Yr × N interaction). Over the 12-yr period, N increased average herbage yield from 1.99 to 2.95 t ha−1; P, from 2.23 to 3.05 t ha−1 and S from 3.48 to 4.19 t ha−1, respectively. The interaction effects of N × Yr, P × Yr and S × Yr all were significant indicating a wide range of response to the fertilizer elements among years. Herbage yield was positively related to total precipitation and negatively to mean maximum temperature for the months of May, June and July. The highest yield (7.49 t ha−1) was obtained with fertilizer (90N-20P-23S kg ha−1), 220 mm of rainfall (May, June and July) with an average maximum temperature of 19.7 °C. The lowest yield (0.84 t ha−1) was obtained with a control (no fertilizer), 160 mm of rainfall and average maximum temperature of 25.2 °C (fertilizer × temperature-precipitation interaction). Results of this study suggest that a rise in average temperature without a corresponding increase in precipitation, would produce a significant drop in bromegrass herbage yield. Key words: Pasture, nutrients, alfalfa, bromegrass, temperature, precipitation

scholarly journals Quantifying the joint distribution of drought indicators in Borneo fire-prone area

2021 ◽  
Vol 880 (1) ◽  
pp. 012002
Author(s):  
Mohamad Khoirun Najib ◽  
Sri Nurdiati ◽  
Ardhasena Sopaheluwakan
Keyword(s):  
Return Period ◽  
Joint Distribution ◽  
Risk Model ◽  
Peat Soil ◽  
Monthly Precipitation ◽  
Total Precipitation ◽  
Dry Spells ◽  
Dry Conditions ◽  
Precipitation Anomalies ◽  
Drought Indicators

Abstract Borneo island is prone to fire due to its large peat soil area. Fire activity in Borneo is associated with regional climate conditions, such as total precipitation, precipitation anomaly, and dry spells. Thus, knowing the relationship between drought indicators can provide preliminary knowledge in developing a fire risk model. Therefore, this study aims to quantify the copula-based joint distribution and to analyze the coincidence probability between drought indicators in Borneo fire-prone areas. From dependence analysis, we found that the average of 2 months of total precipitation (TP), monthly precipitation anomalies (PA), and the total of 3 months of dry spells (DS) provides a moderate correlation to hotspots in Borneo. The results show the probability of the dry-dry period is 26.63, 17.66, and 18.54 % for TP-DS, PA-DS, and TP-PA, respectively. All of these are higher than the probability of the wet-wet period, which is 25.01, 16.12, and 17.98 % for TP-DS, PA-DS, and TP-PA, respectively. Through the probability, the return period of TP-DS in the dry-dry situation 3.2 months/year, meaning the dry situation in total precipitation and dry spells that occur simultaneously could appear about 3 months in a year on average. Furthermore, the return period of PA-DS and TP-PA in the dry-dry situation is 2.12 and 2.22 months/year, respectively. Moreover, the probability of dry spells in dry conditions when given total precipitation in dry conditions is higher than given precipitation anomalies in dry conditions.

scholarly journals A Constrained Stochastic Weather Generator for Daily Mean Air Temperature and Precipitation

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 135
Author(s):  
Feifei Pan ◽  
Lisa Nagaoka ◽  
Steve Wolverton ◽  
Samuel F. Atkinson ◽  
Timothy A. Kohler ◽  
...  
Keyword(s):  
Air Temperature ◽  
Daily Precipitation ◽  
Precipitation Amount ◽  
Weather Conditions ◽  
Weather Generator ◽  
Total Precipitation ◽  
Sinusoidal Wave ◽  
Stochastic Weather Generator ◽  
Temperature And Precipitation ◽  
Unique Method

A constrained stochastic weather generator (CSWG) for producing daily mean air temperature and precipitation based on annual mean air temperature and precipitation from tree-ring records is developed and tested in this paper. The principle for stochastically generating daily mean air temperature assumes that temperatures in any year can be approximated by a sinusoidal wave function plus a perturbation from the baseline. The CSWG for stochastically producing daily precipitation is based on three additional assumptions: (1) In each month, the total precipitation can be estimated from annual precipitation if there exists a relationship between the annual and monthly precipitations. If that relationship exists, then (2) for each month, the number of dry days and the maximum daily precipitation can be estimated from the total precipitation in that month. Finally, (3) in each month, there exists a probability distribution of daily precipitation amount for each wet day. These assumptions allow the development of a weather generator that constrains statistically relevant daily temperature and precipitation predictions based on a specified annual value, and thus this study presents a unique method that can be used to explore historic (e.g., archeological questions) or future (e.g., climate change) daily weather conditions based upon specified annual values.

scholarly journals Performance comparison of filtering methods on modelling and forecasting the total precipitation amount: a case study for Muğla in Turkey

2021 ◽  
Author(s):  
Serdar Neslihanoglu ◽  
Ecem Ünal ◽  
Ceylan Yozgatlıgil
Keyword(s):  
State Space ◽  
State Space Model ◽  
Precipitation Amount ◽  
Exponential Smoothing ◽  
Monthly Precipitation ◽  
Total Precipitation ◽  
Space Model ◽  
Varying Coefficients ◽  
Monthly Total Precipitation ◽  
Modelling And Forecasting

Abstract Condensed water vapor in the atmosphere is observed as precipitation whenever moist air rises sufficiently enough to produce saturation, condensation, and the growth of precipitation particles. It is hard to measure the amount and concentration of total precipitation over time due to the changes in the amount of precipitation and the variability of climate. As a result of these, the modelling and forecasting of precipitation amount is challenging. For this reason, this study compares forecasting performances of different methods on monthly precipitation series with covariates including the temperature, relative humidity, and cloudiness of Muğla region, Turkey. To accomplish this, the performance of multiple linear regression, the state space model (SSM) via Kalman Filter, a hybrid model integrating the logistic regression and SSM models, the seasonal autoregressive integrated moving average (SARIMA), exponential smoothing with state space model (ETS), exponential smoothing state space model with Box-Cox transformation-ARMA errors-trend and seasonal components (TBATS), feed-forward neural network (NNETAR) and Prophet models are all compared. This comparison has yet to be undertaken in the literature. The empirical findings overwhelmingly support the SSM when modelling and forecasting the monthly total precipitation amount of the Muğla region, encouraging the time-varying coefficients extensions of the precipitation model.

The Life Cycle and Variability of Antarctic Weak Polar Vortex Events

2022 ◽  
pp. 1-63
Keyword(s):  
Life Cycle ◽  
Polar Vortex ◽  
Southern Annular Mode ◽  
Austral Spring ◽  
Stratospheric Polar Vortex ◽  
Temperature And Precipitation ◽  
Scale Temperature ◽  
Precipitation Anomalies ◽  
Polar Stratosphere ◽  
The Antarctic

Abstract Motivated by the strong Antarctic sudden stratospheric warming (SSW) in 2019, a survey on the similar Antarctic weak polar events (WPV) is presented, including their life cycle, dynamics, seasonality, and climatic impacts. The Antarctic WPVs have a frequency of about four events per decade, with the 2002 event being the only major SSW. They show a similar life cycle to the SSWs in the Northern Hemisphere but have a longer duration. They are primarily driven by enhanced upward-propagating wavenumber 1 in the presence of a preconditioned polar stratosphere, i.e., a weaker and more contracted Antarctic stratospheric polar vortex. Antarctic WPVs occur mainly in the austral spring. Their early occurrence is preceded by an easterly anomaly in the middle and upper equatorial stratosphere besides the preconditioned polar stratosphere. The Antarctic WPVs increase the ozone concentration in the polar region and are associated with an advanced seasonal transition of the stratospheric polar vortex by about one week. Their frequency doubles after 2000 and is closely related to the advanced Antarctic stratospheric final warming in recent decades. The WPV-resultant negative phase of the southern annular mode descends to the troposphere and persists for about three months, leading to persistent hemispheric scale temperature and precipitation anomalies.

scholarly journals Homogeneity Test and Correction of Daily Temperature and Precipitation Data (1978–2015) in North China

2018 ◽  
Vol 2018 ◽  
pp. 1-17 ◽  
Author(s):  
Lingling Shen ◽  
Li Lu ◽  
Tianjie Hu ◽  
Runsheng Lin ◽  
Ji Wang ◽  
...  
Keyword(s):  
Large Scale ◽  
North China ◽  
Maximum Temperature ◽  
Homogeneity Test ◽  
Climate Data ◽  
Average Temperature ◽  
Temperature And Precipitation ◽  
Daily Data ◽  
Before And After ◽  
Annual Average Temperature

Homogeneity of climate data is the basis for quantitative assessment of climate change. By using the MASH method, this work examined and corrected the homogeneity of the daily data including average, minimum, and maximum temperature and precipitation during 1978–2015 from 404/397 national meteorological stations in North China. Based on the meteorological station metadata, the results are analyzed and the differences before and after homogenization are compared. The results show that breakpoints are present pervasively in these temperature data. Most of them appeared after 2000. The stations with a host of breakpoints are mainly located in Beijing, Tianjin, and Hebei Province, where meteorological stations are densely distributed. The numbers of breakpoints in the daily precipitation series in North China during 1978–2015 also culminated in 2000. The reason for these breakpoints, called inhomogeneity, may be the large-scale replacement of meteorological instruments after 2000. After correction by the MASH method, the annual average temperature and minimum temperature decrease by 0.04°C and 0.06°C, respectively, while the maximum temperature increases by 0.01°C. The annual precipitation declines by 0.96 mm. The overall trends of temperature change before and after the correction are largely consistent, while the homogeneity of individual stations is significantly improved. Besides, due to the correction, the majority series of the precipitation are reduced and the correction amplitude is relatively large. During 1978–2015, the temperature in North China shows a rise trend, while the precipitation tends to decrease.

scholarly journals Historical Spatial and Temporal Climate Trends in Southern Ontario, Canada

2017 ◽  
Vol 56 (10) ◽  
pp. 2767-2787 ◽  
Author(s):  
Hussein Wazneh ◽  
M. Altaf Arain ◽  
Paulin Coulibaly
Keyword(s):  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Climate Indices ◽  
Total Precipitation ◽  
Southern Ontario ◽  
Temperature And Precipitation ◽  
Annual Total ◽  
Precipitation Indices ◽  
Temperature Indices

AbstractSpatial and temporal trends in historical temperature and precipitation extreme events were evaluated for southern Ontario, Canada. A number of climate indices were computed using observed and regional and global climate datasets for the area of study over the 1951–2013 period. A decrease in the frequency of cold temperature extremes and an increase in the frequency of warm temperature extremes was observed in the region. Overall, the numbers of extremely cold days decreased and hot nights increased. Nighttime warming was greater than daytime warming. The annual total precipitation and the frequency of extreme precipitation also increased. Spatially, for the precipitation indices, no significant trends were observed for annual total precipitation and extremely wet days in the southwest and the central part of Ontario. For temperature indices, cool days and warm night have significant trends in more than 90% of the study area. In general, the spatial variability of precipitation indices is much higher than that of temperature indices. In terms of comparisons between observed and simulated data, results showed large differences for both temperature and precipitation indices. For this region, the regional climate model was able to reproduce historical observed trends in climate indices very well as compared with global climate models. The statistical bias-correction method generally improved the ability of the global climate models to accurately simulate observed trends in climate indices.

scholarly journals Disaggregative Invariance of Daily Precipitation

1997 ◽  
Vol 36 (6) ◽  
pp. 721-734 ◽  
Author(s):  
Roman Krzysztofowicz ◽  
Thomas A. Pomroy
Keyword(s):  
Empirical Evidence ◽  
Diurnal Cycle ◽  
Daily Precipitation ◽  
Precipitation Amount ◽  
Total Precipitation ◽  
Stochastic Independence ◽  
Precipitation Forecasting ◽  
Precipitation Timing ◽  
Temporal Disaggregation ◽  
Precipitation Records

Abstract Disaggregative invariance refers to stochastic independence between the total precipitation amount and its temporal disaggregation. This property is investigated herein for areal average and point precipitation amounts accumulated over a 24-h period and disaggregated into four 6-h subperiods. Statistical analyses of precipitation records from 1948 to 1993 offer convincing empirical evidence against the disaggregative invariance and in favor of the conditional disaggregative invariance, which arises when the total amount and its temporal disaggregation are conditioned on the timing of precipitation within the diurnal cycle. The property of conditional disaggregative invariance allows the modeler or the forecaster to decompose the problem of quantitative precipitation forecasting into three tasks: (i) forecasting the precipitation timing; (ii) forecasting the total amount, conditional on timing; and (iii) forecasting the temporal disaggregation, conditional on timing. Tasks (ii) and (iii) can be performed independently of one another, and this offers a formidable advantage for applications.

scholarly journals Isotopes of oxygen-18 and deuterium in precipitation in Slovakia / Izotopy kyslíka-18 A deutéria v zrážkach na Slovensku

2012 ◽  
Vol 60 (4) ◽  
pp. 265-276 ◽  
Author(s):  
Ladislav Holko ◽  
Michal Dóša ◽  
Juraj Michalko ◽  
Martin Šanda
Keyword(s):  
Isotopic Composition ◽  
Air Temperature ◽  
Meteoric Water ◽  
Precipitation Amount ◽  
Data Series ◽  
Water Line ◽  
Temperature And Precipitation ◽  
Meteoric Water Line ◽  
The Mean ◽  
Available Information

The article synthesizes available information on isotopic composition of precipitation in Slovakia (the Western Carpathians). Monthly δ18O data from eleven stations and period 1988-1997 were used to investigate correlations among the stations, altitude, air temperature and precipitation amount effects. The mean annual altitude and air temperature gradients of δ18O in precipitation were 0.21‰/100 m and 0.36‰/1°C, respectively. Maps of spatial distribution of mean annual δ18O in precipitation based on both gradients were constructed. The two maps do not significantly differ for the majority of Slovakia. δ2H data were available for only three stations. Local meteoric water line derived for the station with the longest data series (δ2H = = 7.86δ18O + 6.99) was close to the Global Meteoric Water line. Its parameters in periods 1991-1993 and 1991-2008 did not change. The study indicates that a more detailed monitoring of isotopic composition of precipitation in mountains should be carried out in the future. The highest station exhibited very small seasonal variability of δ18O in precipitation compared to other Slovak stations. The second highest mountain station had significantly higher deuterium excess than the neighboring stations located in the valley. In some analyses the data from the nearest stations situated abroad (Vienna, Krakow) were used.

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