scholarly journals Railway suicides are less likely to occur on rainy days: Evidence from Japan

2021 ◽  
Author(s):  
Hajime Sueki
Keyword(s):  
Incidence Rate ◽  
Daily Rainfall ◽  
Rainfall Data ◽  
Japan Meteorological Agency ◽  
Daily Data ◽  
Railroad Company ◽  
The Relationship ◽  
Rainy Days ◽  
Rule Out

Background: Patrols at stations and along railway lines can reduce the number of railway suicides; however, it is not sufficiently clear when railway suicides are most likely to occur. Aim: We examined the relationship between daily rainfall and the occurrence of railway suicides. Methods: We received the locations and daily data on the occurrence of railway suicides from a major railroad company in Japan. We also collected rainfall data from the Japan Meteorological Agency database for a roughly central locations of the railroad company. The study covered a period of five years, from April 2016 to March 2021. Results: Suicides occurred on 23 rainy days (3.9%) and 92 non-rainy days (7.4%). The incidence of suicides on rainy days was significantly lower than that on non-rainy days. Limitations: We were not able to obtain daily data on the number of rail passengers; therefore, could not rule out the possibility that the suicide incidence rate is lower on rainy days because the number of railroad users is lower on such days. Conclusion: Information about the weather could be used to improve the efficiency of patrols to prevent railway suicides.

scholarly journals Relationships between Rainy Days, Mean Daily Intensity, and Seasonal Rainfall over the Koyna Catchment during 1961–2005

2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
S. Nandargi ◽  
S. S. Mulye
Keyword(s):  
Linear Relationship ◽  
Daily Rainfall ◽  
Rainfall Data ◽  
Seasonal Rainfall ◽  
Frequency Changes ◽  
Logarithmic Relationship ◽  
The Relationship ◽  
Rainfall Climatology ◽  
Rainy Days ◽  
Better Than

There are limitations in using monthly rainfall totals in studies of rainfall climatology as well as in hydrological and agricultural investigations. Variations in rainfall may be considered to result from frequency changes in the daily rainfall of the respective regime. In the present study, daily rainfall data of the stations inside the Koyna catchment has been analysed for the period of 1961–2005 to understand the relationship between the rain and rainy days, mean daily intensity (MDI) and seasonal rainfall over the catchment on monthly as well as seasonal scale. Considering the topographical location of the catchment, analysis of seasonal rainfall data of 8 stations suggests that a linear relationship fits better than the logarithmic relationship in the case of seasonal rainfall versus mean daily intensity. So far as seasonal rainfall versus number of rainy days is considered, the logarithmic relationship is found to be better.

Less rain and rainy days - lessons from 45 years of rainfall data (1971 to 2015) in the Kathmandu Valley, Nepal

2021 ◽  
Author(s):  
Rajaram Prajapati ◽  
Rocky Talchabhadel ◽  
Priya Silwal ◽  
Surabhi Upadhyay ◽  
Brandon Ertis ◽  
...  
Keyword(s):  
Temporal Variability ◽  
Temporal Trends ◽  
Daily Rainfall ◽  
Rainfall Data ◽  
Annual Rainfall ◽  
Kathmandu Valley ◽  
Light Rain ◽  
Mk Test ◽  
Spatio Temporal ◽  
Rainy Days

Abstract Understanding spatio-temporal variability in rainfall patterns is crucial for evaluating water balances needed for water resources planning and management. This paper investigates spatio-temporal variability in rainfall and assesses the frequency of daily rainfall observations from seven stations in the Kathmandu Valley, Nepal, from 1971–2015. Daily rainfall totals were classified into five classes, namely, A (light rain, daily rainfall < 10 mm in a day), B (between 10–50 mm), C (between 50–100 mm), D (between 100–150 mm) and E (> 150 mm). The relationship between daily rainfall and rainfall frequency of various rainfall rate classes were analysed. Kriging method was used for interpolation in interpreting seasonal and annual rainfall data and spatial maps were generated using QGIS. The Mann-Kendall (MK) test was performed to determine the temporal trends and Theil-Sen’s (TS) slope estimator was used in quantifying the magnitude of trends. Mountain stations showed a decreasing trend in rainfall for all seasons, ranging from − 8.4 mm/year at Sankhu to -21.8 mm/year at Thankot, whereas, a mixed pattern was found on the Valley floor. Mean annual rainfall in the Valley was 1610 mm. Both annual rainfall and the number of rainy days decreased in the Kathmandu Valley over the study period. The study indicated a significant reduction in rainfall after 2000. Since springs and shallow groundwater are the primary sources of water supply for residents in the Kathmandu Valley, it is apparent that decreasing rainfall will have (and is already having) an adverse impact on domestic, industrial, and agricultural water supplies, and the livelihoods of people.

scholarly journals Uncertainty of Intensity-Duration-Frequency Curves Due to Adoption or Otherwise of the Temperature Climate Variable in Rainfall Disaggregation

Water ◽  
2021 ◽  
Vol 13 (17) ◽  
pp. 2337
Author(s):  
Sherien Fadhel ◽  
Mustafa Al Aukidy ◽  
May Samir Saleh
Keyword(s):  
Daily Rainfall ◽  
Rainfall Data ◽  
The United Kingdom ◽  
Daily Rainfall Data ◽  
Daily Data ◽  
Idf Curves ◽  
The Difference ◽  
Intensity Duration Frequency ◽  
Historical Temperature ◽  
Temperature Climate

Most areas around the world lack fine rainfall records which are needed to derive Intensity-Duration-Frequency (IDF) curves, and those that are available are in the form of daily data. Thus, the disaggregation of rainfall data from coarse to fine temporal resolution may offer a solution to that problem. Most of the previous studies have adopted only historical rainfall data as the predictor to disaggregate daily rainfall data to hourly resolution, while only a few studies have adopted other historical climate variables besides rainfall for such a purpose. Therefore, this study adopts and assesses the performance of two methods of rainfall disaggregation one uses for historical temperature and rainfall variables while the other uses only historical rainfall data for disaggregation. The two methods are applied to disaggregate the current observed and projected modeled daily rainfall data to an hourly scale for a small urban area in the United Kingdom. Then, the IDF curves for the current and future climates are derived for each case of disaggregation and compared. After which, the uncertainties associated with the difference between the two cases are assessed. The constructed IDF curves (for the two cases of disaggregation) agree in the sense that they both show that there is a big difference between the current and future climates for all durations and frequencies. However, the uncertainty related to the difference between the results of the constructed IDF curves (for the two cases of disaggregation) for each climate is considerable, especially for short durations and long return periods. In addition, the projected and current rainfall values based on disaggregation case which adopts historical temperature and rainfall variables were higher than the corresponding projections and current values based on only rainfall data for the disaggregation.

scholarly journals Decadal Study of Changing Frequency and Intensity of Rainfall for Selected Locations of Tamil Nadu

2021 ◽  
Vol 16 (3) ◽  
pp. 898-907
Author(s):  
S. KOKILAVANI S. KOKILAVANI ◽  
SP. Ramanathan SP. Ramanathan ◽  
GA. Dheebakaran ◽  
N.K. Sathyamoorthy ◽  
B. Arthirani B. Arthirani ◽  
...  
Keyword(s):  
Tamil Nadu ◽  
Rainfall Intensity ◽  
Rainfall Variability ◽  
Daily Rainfall ◽  
Heavy Rain ◽  
Rainfall Data ◽  
Climatic Extremes ◽  
Increasing Trend ◽  
Research Centres ◽  
Rainy Days

Understanding the pattern of regional climatic extremes is essential for creating an important adaptation measure to safeguard farmers from monsoon tantrums. This paper focuses on the rainfall variability and intensity for spatially different locations of Tamil Nadu. The daily rainfall data over a period of 30 years (1990-2019) for the study locations were collected from the constituent research centres of TNAU. The results indicated that an increasing trend in SWM rainfall was observed in Coimbatore (209.3 to 300.6mm), Ooty (681.4 to 703.1mm), Aduthurai (227.8 to 320.6mm), Kovilpatti (132.8 to 141.3 mm) while the decreasing trend was observed in rest of the places. A decreasing trend was reported in general for all the places during NEM. The decreasing trend in the number of rainy days was registered in Kovilpatti, Virudhunagar and Killikulam that exhibits an alert in modifying the crop planning programme in those areas. The frequency of rainfall intensity revealed that except Ooty, the number of Heavy Rain (HR) to VHR(VHR) was found to be meagre to absent in most of the study locations.

scholarly journals Fitting of a Markov chain model for daily rainfall data at Calcutta

MAUSAM ◽  
2021 ◽  
Vol 22 (1) ◽  
pp. 67-74
Author(s):  
A. N. BASU
Keyword(s):  
Markov Chain ◽  
Geometric Distribution ◽  
Markov Chain Model ◽  
Probability Model ◽  
Daily Rainfall ◽  
Rainfall Data ◽  
Actual Data ◽  
Chain Model ◽  
Daily Rainfall Data ◽  
Rainy Days

A Markov chain probability model has been fitted to the daily rainfall data recorded at Calcutta. The 'wet spell' and 'weather cycles' are found to obey geometric distribution, The distribution of the number of rainy days per week has been calculated and compared with the actual data.

Evaluation of the climate generator model CLIGEN for rainfall data simulation in Bautzen catchment area, Germany

2013 ◽  
Vol 45 (4-5) ◽  
pp. 615-630 ◽  
Author(s):  
Mustafa Al-Mukhtar ◽  
Volkmar Dunger ◽  
Broder Merkel
Keyword(s):  
Catchment Area ◽  
Daily Rainfall ◽  
Rainfall Data ◽  
Data Simulation ◽  
Prediction Ability ◽  
Temporal Prediction ◽  
Generator Model ◽  
Daily Data ◽  
Input Parameters ◽  
Storm Duration

The objectives of this study were to: (i) evaluate the CLImate GENerator model (CLIGEN v.5.22564) to reproduce daily, monthly and yearly precipitation values across Bautzen catchment area, as well as storm patterns including maximum monthly 30 min intensity and average monthly storm duration at two stations, (ii) cross-validate CLIGEN's spatial and temporal prediction ability. Daily rainfall data were collected from three stations (Kubschütz, Sohland and Spittwitz) for the period 1991–2010, in addition to breakpoint rainfall data from Kubschütz for the period 2004–2010 and Sohland for the period 2005–2010. The daily data from the three stations were interpolated to the entire catchment area. These interpolated observed data were used to validate the results from CLIGEN twice, once when the model was run with input parameters calculated from the interpolated data, and once when the model was run with input parameters calculated from each station independently. The model was cross-validated with respect to time at each station independently. For that purpose, the period 1991–2010 was subdivided into two intervals for each station; the first one was used to calibrate the model and the second one to validate it and vice versa. Results showed that CLIGEN can be sufficiently used to simulate rainfall and storm pattern parameters.

scholarly journals Development of IDF-curves for tropical india by random cascade modeling

2013 ◽  
Vol 10 (4) ◽  
pp. 4709-4738 ◽  
Author(s):  
A. Rana ◽  
L. Bengtsson ◽  
J. Olsson ◽  
V. Jothiprakash
Keyword(s):  
Time Scales ◽  
Time Scale ◽  
Daily Rainfall ◽  
Rainfall Data ◽  
Efficient Design ◽  
Daily Data ◽  
Current Design ◽  
Idf Curves ◽  
Intensity Duration Frequency ◽  
Fine Time

Abstract. Efficient design of urban drainage systems is based on statistical analysis of past rainfall events at fine time scales. However, fine time scale rainfall data are usually lacking in many parts of the world. A possible way forward is to develop methods to derive fine time scale rain intensities from daily observations. This paper applied cascade-based disaggregation modeling for generation of fine time scale rainfall data for Mumbai, India from daily rainfall data. These data were disaggregated to 10-min values. The model was used to disaggregate daily data for the period 1951–2004 and develop intensity-duration-frequency (IDF) relationships. This disaggregation technique is commonly used assuming scale-invariance using constant parameters. For the Mumbai rains it was found better to use parameters dependent on time scale and rain volume. Very good agreement between modeled and observed disaggregation series was found for the time scales larger than 1/2 h for the 1/2-yr period when short term data were available. Although the parameters were allowed to change with time scale, the rain intensities of duration shorter than 1/2 h were overestimated. When IDF-curves had been established, they showed that the current design standard for Mumbai city, 25 mm h−1, has a return period of less than one year. Thus, annual recurring flooding problems in Mumbai appear evident.

scholarly journals Analysis of variability and projection of extreme rainfall in West Java

2021 ◽  
Vol 893 (1) ◽  
pp. 012012
Author(s):  
R C H Hutauruk ◽  
T Amin ◽  
A M Irawan
Keyword(s):  
Climate Change ◽  
Daily Rainfall ◽  
Extreme Rainfall ◽  
Rainfall Data ◽  
West Java ◽  
Maximum Rainfall ◽  
Rainfall Index ◽  
Extreme Rain ◽  
Rcp 8.5 ◽  
Rainy Days

Abstract This research discusses the effect of climate change on extreme rainfall in West Java using the RCP 4.5 and RCP 8.5 scenarios by comparing daily rainfall data with model ACCESS-1, CSIROMK3.6 model, MIROC-5 from NASA Earth Exchange Global Daily Downscaled Projection (NEX-GDDP) and the ensemble of three models each season with Extreme Dependency Score (EDS) method. This study projects an extreme rainfall index of 30 years (2011-2040). The three extreme rainfall indices issued by the Expert Detection Team and the Climate Change Index (ETCCDI) consisted of Rx1day, R50mm, and R95p used in this study. The results showed that the projection period (2011-2040) used RCP 8.5 which had a trend of increasing extreme rain index that was greater than RCP 4.5. For RCP 8.5 the maximum rainfall will increase in Indramayu, Majalengka, Purwakarta, Sukabumi and Ciamis areas. Increased rainy days occurred in Bogor, Bekasi, Karawang, Purwakarta, Bandung, Sumedang, Majalengka, Cirebon, Indramayu. Extreme rainfall will increase in Bekasi, Karawang and Bogor regions.

scholarly journals Taluka Wise Study of Rainfall Pattern in Nanded District of Marthwada Region (Maharashtra) Using Rainfall Data

2021 ◽  
Vol 10 (9) ◽  
pp. 333-350
Author(s):  
Ramesh Bethala B. V. Asewar ◽  
M. S. Peneke K. K. Dakhore ◽  
M. G. Jadhav A. M. Khobragade
Keyword(s):  
Crop Production ◽  
Rainfall Variability ◽  
Winter Season ◽  
Daily Rainfall ◽  
Rainfall Data ◽  
Annual Rainfall ◽  
Monsoon Period ◽  
Annual Basis ◽  
Rainy Days ◽  
Onset Of Monsoon

About 60 per cent of the total cultivable area of the country is rainfed. However, prolonged dry periods affect the final crop production. Monsoon is an important season for water supplies, from surface reservoir. Uneven distribution of rainfall, affect the agricultural production remarkably. The daily rainfall data was collected for each taluka of Nanded district for the period of 20 years (1998-2017) and it was to be summed up on meteorological weekly, monthly, seasonally, annual basis for each taluka of Nanded district basis for the study of rainfall characterization. The results indicated that weekly mean annual basis total rainfall was ranged between 720.0 mm in Deglur and 1009.9 mm in Mahur. The weekly highest rainfall on annual basis was recorded in Himayat Nagar (53.7 mm) in the 30th MW amongst all the taluka considering monsoon period (23 to 42 MW). The monthly mean rainfall indicated that the lowest and highest monthly mean rainfall amongst all the taluka was observed in Nanded, Kandhar, Loha, Hadgaon, Bhokar, Kinwat, Mahur, Dharmabad, Ardhapur, Naigaon talukas (0.0 mm) in the December month and in the Mahur taluka (283.1 mm) in July month. The seasonal distribution of Nanded district was obtained in winter season (6.1 mm), in summer (15.5 mm), in monsoon (578.3 mm), in post monsoon (216.6 mm). The annual rainfall data is statistical analyzed for Nanded district and within the year and taluka to taluka ranged C.V. (%) were between 25.0 to 46.9 %. The data of taluka-wise annual normal of weather parameter (i.e. rainfall and rainy days) calculated. Here, the results indicated that the onset of monsoon was observed in 23th MW and withdrawal in 43rd MW in Nanded district. It showed that average rainfall of Nanded district is 816.4 mm with 45.0 rainy days per year. The results clearly indicated the onset of monsoon in 23th MW and withdrawal of monsoon in 43rd MW for the Nanded district should be considered. The statistical analysis for rainfall variability was worked out and it was intra-annual as well as intra-taluka variation in Nanded district. It was ranged between 19.0 to 51.0 per cent with annual mean 45.0 rainy days per year.

scholarly journals Changes in ambient temperature increase hospital outpatient visits for allergic rhinitis in Xinxiang, China

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Jianhui Gao ◽  
Mengxue Lu ◽  
Yinzhen Sun ◽  
Jingyao Wang ◽  
Zhen An ◽  
...  
Keyword(s):  
Allergic Rhinitis ◽  
Ambient Temperature ◽  
Positive Association ◽  
Ambient Air ◽  
Ambient Air Pollution ◽  
Hospital Outpatient ◽  
Distributed Lag ◽  
Outpatient Visits ◽  
Daily Data ◽  
The Relationship

Abstract Background The effect of ambient temperature on allergic rhinitis (AR) remains unclear. Accordingly, this study aimed to explore the relationship between ambient temperature and the risk of AR outpatients in Xinxiang, China. Method Daily data of outpatients for AR, meteorological conditions, and ambient air pollution in Xinxiang, China were collected from 2015 to 2018. The lag-exposure-response relationship between daily mean temperature and the number of hospital outpatient visits for AR was analyzed by distributed lag non-linear model (DLNM). Humidity, long-time trends, day of the week, public holidays, and air pollutants including sulfur dioxide (SO2), and nitrogen dioxide (NO2) were controlled as covariates simultaneously. Results A total of 14,965 AR outpatient records were collected. The relationship between ambient temperature and AR outpatients was generally M-shaped. There was a higher risk of AR outpatient when the temperature was 1.6–9.3 °C, at a lag of 0–7 days. Additionally, the positive association became significant when the temperature rose to 23.5–28.5 °C, at lag 0–3 days. The effects were strongest at the 25th (7 °C) percentile, at lag of 0–7 days (RR: 1.32, 95% confidence intervals (CI): 1.05–1.67), and at the 75th (25 °C) percentile at a lag of 0–3 days (RR: 1.15, 95% CI: 1.02–1.29), respectively. Furthermore, men were more sensitive to temperature changes than women, and the younger groups appeared to be more influenced. Conclusions Both mild cold and mild hot temperatures may significantly increase the risk of AR outpatients in Xinxiang, China. These findings could have important public health implications for the occurrence and prevention of AR.

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