scholarly journals Trends, Variability, and Seasonality of Maximum Annual Daily Precipitation in the Upper Vistula Basin, Poland

Atmosphere ◽  
2018 ◽  
Vol 9 (8) ◽  
pp. 313 ◽  
Author(s):  
Dariusz Młyński ◽  
Marta Cebulska ◽  
Andrzej Wałęga
Keyword(s):  
Daily Precipitation ◽  
Weather Conditions ◽  
Kendall Test ◽  
Total Precipitation ◽  
Predictability Index ◽  
Precipitation Seasonality ◽  
Significance Levels ◽  
Seasonality Index ◽  
Summer Half ◽  
Weather Stations

The aim of this study was to detect trends in maximum annual daily precipitation in the Upper Vistula Basin. We analyzed data from 51 weather stations between 1971 and 2014. Then we used the Mann–Kendall test to detect monotonical trends of the precipitation for three significance levels: 1, 5, and 10%. Our analysis of weather conditions helped us describe the mechanism behind the formation of maximum annual daily precipitation. To analyze precipitation seasonality, we also used Colwell indices. Our study identified a significant trend of the highest daily precipitation for the assumed significance levels (0.01, 0.05, 0.1) for 22% of the investigated weather stations at different elevations. The significant trends found were positive and an increase in precipitation is expected. From 1971 to 2014, the maximum daily total precipitation most often occurred in the summer half-year, i.e., from May until September. These months included a total of 88% of days with the highest daily precipitation. The predictability index for the highest total precipitation within the area was high and exceeded 5%. It was markedly affected by the coefficient of constancy (C) and to a lesser degree by the seasonality index (M). Our analysis demonstrated a convergence of the Colwell indices and frequency of cyclonic situation and, therefore, confirmed their usability in the analysis of precipitation seasonality.

scholarly journals Trends in daily precipitation in highlands region of Santa Catarina, southern Brazil

2018 ◽  
Vol 13 (1) ◽  
pp. 1
Author(s):  
Eder Alexandre Schatz Sá ◽  
Carolina Natel de Moura ◽  
Victor Luís Padilha ◽  
Claudia Guimarães Camargo Campos
Keyword(s):  
Daily Precipitation ◽  
Kendall Test ◽  
Rainfall Anomaly ◽  
La Niña ◽  
Southern Brazil ◽  
Santa Catarina ◽  
La Nina ◽  
Daily Precipitation Data ◽  
Precipitation Anomalies ◽  
Weather Stations

This study evaluates the occurrence of trends in time series of precipitation in the highlands region of Santa Catarina, Southern Brazil. Daily precipitation data of three weather stations at Lages, São Joaquim and Campos Novos were used to evaluate rainfall trends. The trends were analyzed through the Seasonal Mann Kendall test, to include occurrence of maximum annual 1-day precipitation (RX1), maximum annual consecutive 2-day precipitation (RX2) and maximum annual consecutive 3-day precipitation (RX3) and evaluation of Rainfall Anomaly Index (RAI). Trends were identified in two of three weather stations investigated. Positive precipitation trends were found in the spring and winter for Lages, and in the spring and summer for São Joaquim. Also, there is a trend of increase in the RX1, RX2 and RX3 frequencies and an increase in positive anomalies in the last decade for these stations. There are no statistically significant trends in the precipitation of Campos Novos, which may be associated with the short series of available data for the analysis. The occurrence of El Niño phenomenon with moderate to strong intensity was usually associated with the occurrence of positive precipitation anomalies and the La Niña phenomenon was related to the occurrence of negative anomalies. However, the influence of La Niña in the periods of negative anomaly has been reduced since the beginning of the 21st century.

scholarly journals Analysis of spatial patterns of trends in the frequency and intensity of Indian precipitation

MAUSAM ◽  
2021 ◽  
Vol 57 (3) ◽  
pp. 431-436
Author(s):  
SHOURASENI SEN ROY ◽  
ROBERT C. BALLING, JR.
Keyword(s):  
Daily Precipitation ◽  
Mean Annual Precipitation ◽  
Total Precipitation ◽  
Time Period ◽  
Spatial Dimensions ◽  
The Mean ◽  
Weather Stations ◽  
Precipitation Records ◽  
Western Half ◽  
Over Time

bl ‘’kks/k Ik= esa lewps Hkkjr ds 129 ekSle dsanzksa ds fy, 1910 ls 2000 rd dh le;kof/k ds nSfud o"kkZ ds fjdkM+ksaZ dks ,df=r fd;k x;k gS A blds ckn fofHkUu ekSle foKkfud mi[kaM+ksa ds fy, ek/; okf"kZd o"kkZ ds ekuksa ds vuqlkj bu dsanzksa dks ukS fHkUu&fHkUu {ks=ksa esa ck¡Vk x;k gS A izR;sd {ks= ds fy, gj ik¡p izfr’kr ds varjky ij dqy o"kkZ vkSj o"kkZ dh ckjackjrk dk foLr`r fo’ys"k.k fd;k gS A bu ifj.kkeksa ls lkekU;r% Hkkjr ds yxHkx lHkh Hkkxksa esa o"kkZ dh deh dk irk pyk gS tcfd dsoy mRrj if’peh Hkkxksa esa o"kkZ esa o`f) ns[kh xbZ gS A o"kkZ ds izfr lSadM+k oxZ varjkyksa ds vuqlkj fd, x, gekjs fo’ys"k.k ls ;g irk pyrk gS fd fo’ks"k :Ik ls ns’k ds vk/ks Hkkx if’peh {ks= esa vfro`f"V dh ?kVuk,¡ ckj&ckj gksrh gSa A Hkkjrh; o"kkZ ds LFkkfud vk;keksa ij izdk’k Mkyus okys gkmxVu bR;kfn (2001) ds vkbZ- ih- lh- lh- ds oSKkfud ewY;kadu vkSj vU; v/;;uksa ds lkFk gekjs ifj.kke O;kid :Ik ls esy [kkrs gSa A We assembled daily precipitation records for 129 weather stations spread all over India for the time period 1910 to 2000. Next we classified these stations into nine different regions according to the mean annual precipitation values for the different India meteorological sub-divisions. We conducted detailed analysis of total precipitation and the frequency of precipitation for each five-percentile interval for every region.  In general, our results show a decrease in precipitation throughout much of India with only the northwest showing an increase. Our analyses by precipitation percentile class intervals show that the most extreme events have become more frequent, particularly in the western half of the country. Our results are broadly consistent with the IPCC Scientific Assessment by Houghton et al. (2001) and other studies focusing on the spatial dimensions of Indian precipitation over time.  

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 Cars as next generation mobile weather stations: an initial investigation

2021 ◽  
Author(s):  
Giuliano Andrea Pagani ◽  
Marcel Molendijk ◽  
Jan Willem Noteboom
Keyword(s):  
Air Temperature ◽  
Weather Conditions ◽  
Ground Temperature ◽  
Warning Systems ◽  
Traction Control ◽  
The Future ◽  
Weather Stations ◽  
Temporal And Spatial ◽  
Positive Correlation Coefficient ◽  
Digital Equipment

<p>Modern automobiles are becoming more and more “computers on the wheels” having lots of digital equipment on board. Such equipment is both for the comfort and entertainment of the passengers and for their safety. Sensors play a key role in measuring several parameters of the car performance (e.g., traction control, anti-lock breaking system) and also environmental  parameters are observed directly (e.g., air temperature) or can be somehow inferred (e.g., precipitation via windscreen wipers activity/speed).</p><p>KNMI has been provided air temperature recorded every 10 minutes by thousands of vehicles driving in the Netherlands for the period January-October 2020. We have performed an initial exploratory temporal and spatial analysis to understand the most promising periods of the day and areas where sufficient data is available to perform a more thorough data analysis in the future. Furthermore, we have performed a correlation analysis between the outside temperature measured by cars and air and ground temperature observed by official weather station sensors placed at one location on the Dutch highways. The correlation results for three randomly selected days (with different weather conditions) show a good positive correlation coefficient ranging from 0.93 to 0.76 for car and station air temperature and from 0.91 to 0.67 for car temperature and station ground temperature.</p><p>This initial exploration paves the way to the use of (OEM) car data as (mobile) weather stations. We foresee in the future to use a combination of sensed variables from cars such as air temperature, traction control, windscreen wipers activity for example to improve observations of road slipperiness and related warning systems that are not restricted to Dutch highways only.</p>

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 Combining Weather Stations for Electric Load Forecasting

Energies ◽  
2019 ◽  
Vol 12 (8) ◽  
pp. 1510 ◽  
Author(s):  
Masoud Sobhani ◽  
Allison Campbell ◽  
Saurabh Sangamwar ◽  
Changlin Li ◽  
Tao Hong
Keyword(s):  
Load Forecasting ◽  
Weather Conditions ◽  
Vital Role ◽  
Alternative Methods ◽  
Electric Load ◽  
Weather Variables ◽  
Energy Forecasting ◽  
Key Factor ◽  
Weather Stations ◽  
Vast Area

Weather is a key factor affecting electricity demand. Many load forecasting models rely on weather variables. Weather stations provide point measurements of weather conditions in a service area. Since the load is spread geographically, a single weather station may not sufficiently explain the variations of the load over a vast area. Therefore, a proper combination of multiple weather stations plays a vital role in load forecasting. This paper answers the question: given a number of weather stations, how should they be combined for load forecasting? Simple averaging has been a commonly used and effective method in the literature. In this paper, we compared the performance of seven alternative methods with simple averaging as the benchmark using the data of the Global Energy Forecasting Competition 2012. The results demonstrate that some of the methods outperform the benchmark in combining weather stations. In addition, averaging the forecasts from these methods outperforms most individual methods.

scholarly journals Probability Models and Statistical Tests for Extreme Precipitation Based on Generalized Negative Binomial Distributions

Mathematics ◽  
2020 ◽  
Vol 8 (4) ◽  
pp. 604 ◽  
Author(s):  
Victor Korolev ◽  
Andrey Gorshenin
Keyword(s):  
Negative Binomial ◽  
Daily Precipitation ◽  
Global Climate ◽  
Statistical Tests ◽  
Real Data ◽  
Total Precipitation ◽  
Climate Trends ◽  
Probability Models ◽  
Precipitation Volume ◽  
Precipitation Total

Mathematical models are proposed for statistical regularities of maximum daily precipitation within a wet period and total precipitation volume per wet period. The proposed models are based on the generalized negative binomial (GNB) distribution of the duration of a wet period. The GNB distribution is a mixed Poisson distribution, the mixing distribution being generalized gamma (GG). The GNB distribution demonstrates excellent fit with real data of durations of wet periods measured in days. By means of limit theorems for statistics constructed from samples with random sizes having the GNB distribution, asymptotic approximations are proposed for the distributions of maximum daily precipitation volume within a wet period and total precipitation volume for a wet period. It is shown that the exponent power parameter in the mixing GG distribution matches slow global climate trends. The bounds for the accuracy of the proposed approximations are presented. Several tests for daily precipitation, total precipitation volume and precipitation intensities to be abnormally extremal are proposed and compared to the traditional PoT-method. The results of the application of this test to real data are presented.

scholarly journals Impacts of Atmospheric Rivers in Extreme Precipitation on the European Macaronesian Islands

Atmosphere ◽  
2018 ◽  
Vol 9 (8) ◽  
pp. 325 ◽  
Author(s):  
Alexandre M. Ramos ◽  
Ricardo M. Trigo ◽  
Ricardo Tomé ◽  
Margarida L. R. Liberato
Keyword(s):  
Canary Islands ◽  
Extreme Precipitation ◽  
Daily Precipitation ◽  
Comprehensive Assessment ◽  
Atmospheric Rivers ◽  
Extreme Precipitation Events ◽  
Macaronesian Islands ◽  
Weather Stations ◽  
The Relationship ◽  
Precipitation Events

The European Macaronesia Archipelagos (Azores, Madeira and Canary Islands) are struck frequently by extreme precipitation events. Here we present a comprehensive assessment on the relationship between atmospheric rivers and extreme precipitation events in these three Atlantic Archipelagos. The relationship between the daily precipitation from the various weather stations located in the different Macaronesia islands and the occurrence of atmospheric rivers (obtained from four different reanalyses datasets) are analysed. It is shown that the atmospheric rivers’ influence over extreme precipitation (above the 90th percentile) is higher in the Azores islands when compared to Madeira or Canary Islands. In Azores, for the most extreme precipitation days, the presence of atmospheric rivers is particularly significant (up to 50%), while for Madeira, the importance of the atmospheric rivers is reduced (between 30% and 40%). For the Canary Islands, the occurrence of atmospheric rivers on extreme precipitation is even lower.

scholarly journals Verification of WRF modelled fire weather in the 2009–10 New Zealand fire season

2014 ◽  
Vol 23 (1) ◽  
pp. 34 ◽  
Author(s):  
C. C. Simpson ◽  
H. G. Pearce ◽  
A. P. Sturman ◽  
P. Zawar-Reza
Keyword(s):  
New Zealand ◽  
Weather Conditions ◽  
Model Error ◽  
Dew Point ◽  
Fire Season ◽  
Fire Weather ◽  
Fire Weather Index ◽  
Wind Speeds ◽  
Air Temperatures ◽  
Weather Stations

The Weather Research and Forecasting (WRF) mesoscale model was used to simulate the fire weather conditions for the 2009–10 wildland fire season in New Zealand. The suitability of WRF to simulate the high-end fire weather conditions for this period was assessed through direct comparison with observational data taken from 23 surface and two upper-air stations located across New Zealand. The weather variables and fire weather indices considered in the verification were the 1200 hours NZST air temperature, relative humidity, wind speed and direction, 24-h rainfall, New Zealand Fire Weather Index (FWI) and Continuous Haines Index (CHI). On observed high-end fire weather days, the model under-predicted the air temperatures and relative humidities, and over-predicted the wind speeds and 24-h rainfall at most weather stations. The results demonstrated that although WRF is suitable for modelling the air temperatures, there are issues with modelling the wind speeds and rainfall quantities. The model error in the wind speeds and 24-h rainfall contributed significantly towards the model under-prediction of the FWI on observed high-end fire weather days. In addition, the model was not suitable for predicting the number of high-end fire weather days at most weather stations, which represents a serious operational limitation of the WRF model for fire management applications. Finally, the modelled CHI values were only in moderate agreement with the observed values, principally due to the model error in the dew point depression at 850hPa.

scholarly journals Statistical analysis of daily precipitation in the Bydgoszcz region

2018 ◽  
Vol 23 ◽  
pp. 00004
Author(s):  
Waldemar Bojar ◽  
Leszek Knopik ◽  
Renata Kuśmierek-Tomaszewska ◽  
Jacek Żarski ◽  
Wojciech Żarski
Keyword(s):  
Statistical Analysis ◽  
Gamma Distribution ◽  
Daily Precipitation ◽  
Precipitation Amount ◽  
City Centre ◽  
Total Precipitation ◽  
Precipitation Frequency ◽  
Potential Variation ◽  
The City ◽  
Daily Total

The aim of the research has been to provide a statistical analysis of precipitation in the Bydgoszcz region based on the results of the measurements taken at the Experiment Station of the UTP University of Science and Technology in Bydgoszcz, located at Mochle, about 20 km away from the city centre. The paper analyses the daily total precipitation throughout 43 years (1971—2013). The analysis demonstrated a high dependence of the indicators studied on the month, confirming the annual pattern typical for the transitional climate of the temperate zone. In general, it shows an advantage of the amount and variation, and less considerably — the daily precipitation frequency in summer months, as compared with the winter months. The distribution of the probability of the daily precipitation amount for each month turned out to be compliant with gamma distribution, which allows for a potential variation in the future.

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