Long term monthly and inter-seasonal weather variability analysis for the lower Shivalik foothills of Punjab

This paper aims to study the long-term trends in different weather parameters, i.e., temperature, rainfall, rainy days, sunshine hours, evaporation, relative humidity and temperature over Lower Shivalik foothills of Punjab. The daily weather data of about 35 years from agrometeorological observatory of Regional Research Station Ballowal Saunkhri representing Lower Shivalik foothills had been used for trend analysis for kharif (May - October), rabi (November - April), winter (January - February), pre-monsoon (March - May), monsoon (June - September) and post monsoon (October - December) season. The linear regression method has been used to estimate the magnitude of change per year and its coefficient of determination, whose statistical significance was checked by the F test. The annual maximum temperature, morning and evening relative humidity has increased whereas rainfall, evaporation sunshine hours and wind speed has decreased significantly at this region. No significant change in annual minimum temperature and diurnal range has been observed. Monthly maximum temperature revealed significant increase except January, June and December, whereas, monthly minimum temperature increased significantly for February, March and October and decreased for June. Among different seasons, maximum temperature increased significantly for all seasons except winter season, whereas, minimum temperature increased significantly for kharif and post monsoon season only. The evaporation, sunshine hours and wind speed have also decreased and relative humidity decreased significantly at this region. Significant reduction in kharif, monsoon and post monsoon rainfall has been observed at Lower Shivalik foothills. As the region lacks assured irrigation facilities so decreasing rainfall and change in the other weather parameters will have profound effects on the agriculture in this region so there is need to develop climate resilient agricultural technologies.

Short term prediction of atmospheric temperature using neural networks

In this paper, a neural network based forecasting model for the maximum and the minimum temperature for the ground level is proposed. A backpropagation method of gradient-decent learning in multi-layer perceptron (MLP) type of neural network with only one hidden layer is considered. This network consists of 25 input nodes and two output nodes. The network is trained with a varying number of nodes in the hidden layer using a set of training sample and each of them is tested with a set of test sample. It accepts previous two consecutive days information (such as pressures, temperatures, relative humidities, etc.) as inputs for the estimation of the maximum and the minimum temperature as output. The network with 20 or less neurons in the hidden layer is found to be "optimum" and it produces an error within ±2° C for 80% of test cases.

Assessment of weather effect on flower morphogenesis and fruit set in mango varieties in central India

A two-year field experiment was initiated in 2017-18 and 2018-19 years simultaneously to assess temperature on flower morphogenesis stages, flower sex ratio (hermaphrodite/staminate male flower) and fruit set in monoembryonic Langra and Amrapali varieties. Different dates of flower phenological stages viz., bud, panicle, bloom and flower initiation, pea, marble, egg, and maturity of fruits were recorded. The Langra variety exhibited bud initiation after mid December whereas Amrapali variety by the end of December. The range of mean maximum / minimum temperature as 26-31/10-12 °C promoted hermaphrodite flowers per panicle by 74 per cent in Langra variety, whereas range of 27-29/11-13 °C favored by 35 per cent in Amrapali variety. A positive and significant correlation between total number of flower / panicle and flower sex ratio in both the varieties suggested that higher temperature during initial flower phenologies improved number of hermaphrodite flowers. A mean minimum temperature for producing more number of hermaphrodite flower exhibited a range of 11-14 °C under central Indian conditions. Fruit set was maximum during pea stage and decline afterwards in marble and fruit maturity stages due to sudden rise in temperature at marble stage that caused in drop down of humidity thereby resulted in fruit drop in both the varieties.

Forecasting of minimum temperature over Gangtok

A study has been conducted to assess day-to-day changes, departure and persistence of minimum temperature and the frequency of cold wave and severe cold wave over Gangtok for five winter months i.e., November-March for the years 1969 to 1992. Regression models have also been formulated to forecast minimum temperature with the knowledge of dew point, cloud amount, maximum temperature and minimum temperature recorded on previous day. In case of changes, ‘little change’ and ‘no change’ constitute about four-fifth of total changes. The cases of nearly normal were found maximum when departure of minimum temperature from normal was considered. Frequency of cold wave and severe cold wave has been recorded more in January and February respectively. It has been observed that there is a gradual fall in the percentage frequency with the increase in the magnitude of variation. Regression model gives good results from November to February.

Effects of weather and moon phases on emergency medical use after fall injury: A population-based nationwide study

Background Previous studies reported that changes in weather and phases of moon are associated with medical emergencies and injuries. However, such studies were limited to hospital or community level without explaining the combined effects of weather and moon phases. We investigated whether changes in weather and moon phases affected emergency department (ED) visits due to fall injuries (FIs) based on nationwide emergency patient registry data. Methods Nationwide daily data of ED visits after FI were collected from 11 provinces (7 metropolitan cities and 4 rural provinces) in Korea between January 2014 and December 2018. The daily number of FIs was standardized into FI per million population (FPP) in each province. A multivariate regression analysis was conducted to elucidate the relationship between weather factors and moon phases with respect to daily FPP in each province. The correlation between weather factors and FI severity was also analyzed. Results The study analyzed 666,912 patients (418,135 in metropolitan and 248,777 in rural areas) who visited EDs on weekdays. No regional difference was found in age or gender distribution between the two areas. Precipitation, minimum temperature and wind speed showed a significant association with FI in metropolitan areas. In addition, sunshine duration was also substantial risk factors for FI in rural areas. The incidence of FIs was increased on full moon days than on other days in rural areas. Injury severity was associated with weather factors such as minimum temperature, wind speed, and cloud cover. Conclusion Weather changes such as precipitation, minimum temperature, and wind speed are associated with FI in metropolitan and rural areas. In addition, sunshine duration and full moon are significantly associated with FI incidence only in rural areas. Weather factors are associated with FI severity.

A Critical Analysis of Effect of Projected Temperature and Rainfall for Differential Sowing of Maize Cultivars Under RCP4.5 and RCP6.0 Scenarios for Punjab

A simulation study was conducted for two cultivars of maize (PMH1 and PMH2) in four agroclimatic zones of Punjab state of India where climate change depicts a consistent rise in temperature and increased variability in amount and distribution of rainfall. The yield assessment was performed for four agroclimatic zones of Punjab comprising of seven locations because variability in temperature rise and rainfall existed from location to location. Corrected ensemble model weather data (temperature and rainfall) for RCP4.5 and RCP6.0 was used as an input in the calibrated and validated CERES-Maize model and yield was simulated for a period of 70 years. The simulated yield for near as well as far-future was statistically assessed to understand the yield trend in Punjab under current dates of sowing and the results indicated a strong negative correlation between the yield and the weather parameters under the two scenarios at the considered four agroclimatic zones of Punjab. An increase in maximum and minimum temperature was observed ranging 0-4°C and 3-8°C, respectively at all the agroclimatic zones except Faridkot (zone V) where the increase in minimum temperature was observed by 0-3°C during the crop growth season while the rainfall variability ranged from 200-800mm under both the scenarios. At agroclimatic zone II and zone III similar results were obtained with higher yields at later dates of sowing and the rainfall at agroclimatic zone III was higher under RCP6.0 (300-600mm) while the yields for agroclimatic zone IV and V (Abohar) with rainfall variation of 270-450mm and 200-400mm, respectively showed no yield increment. Maize at Faridkot performed well with higher yields at early sowing dates. Among the two cultivars PMH1 showed more high yield years than PMH2 for most of the years. The yield under differential sowing dates showed the first fortnight of June and end June to be the best sowing dates for most of the locations as the yield for these dates were higher for most of the years. Thus, the study can be further applied to decide the future sowing window of maize for the agricultural state like Punjab.

Analysis of Past and Projected Trends of Rainfall and Temperature Parameters in Eastern and Western Hararghe Zones, Ethiopia

Smallholder farmers in East and West Hararghe zones, Ethiopia frequently face problems of climate extremes. Knowledge of past and projected climate change and variability at local and regional scales can help develop adaptation measures. A study was therefore conducted to investigate the spatio-temporal dynamics of rainfall and temperature in the past (1988–2017) and projected periods of 2030 and 2050 under two Representative Concentration Pathways (RCP4.5 and RCP8.5) at selected stations in East and West Hararghe zones, Ethiopia. To detect the trends and magnitude of change Mann–Kendall test and Sen’s slope estimator were employed, respectively. The result of the study indicated that for the last three decades annual and seasonal and monthly rainfall showed high variability but the changes are not statistically significant. On the other hand, the minimum temperature of the ‘Belg’ season showed a significant (p < 0.05) increment. The mean annual minimum temperature is projected to increase by 0.34 °C and 2.52 °C for 2030, and 0.41 °C and 4.15 °C for 2050 under RCP4.5 and RCP8.5, respectively. Additionally, the mean maximum temperature is projected to change by −0.02 °C and 1.14 °C for 2030, and 0.54 °C and 1.87 °C for 2050 under RCP4.5 and RCP 8.5, respectively. Annual rainfall amount is also projected to increase by 2.5% and 29% for 2030, and 12% and 32% for 2050 under RCP4.5 and RCP 8.5, respectively. Hence, it is concluded that there was an increasing trend in the Belg season minimum temperature. A significant increasing trend in rainfall and temperature are projected compared to the baseline period for most of the districts studied. This implies a need to design climate-smart crop and livestock production strategies, as well as an early warning system to counter the drastic effects of climate change and variability on agricultural production and farmers’ livelihood in the region.

Analysis of Climate Parameters as Indicators of Climate Changes in Central and Eastern Iraq: Khanaqin Climate Conditions as A Case Study

The climate parameters of rainfall, and average of maximum and minimum temperature were investigated for the period of 2000-2019 in three stations in central and eastern Iraq (Baghdad, Diyala, and Kut provinces). Evidence of climate change was noticed from the results, reflected by decreased mean values of annual rainfall with increased mean of maximum and minimum temperature. In addition, the water balance and the climatic conditions were determined for Khanaqin station for the years 1981-2019. The analysis of Khanaqin climate parameters demonstrated total annual mean values of rainfall of 260.86mm and evaporation of 3119.59mm. The mean monthly relative humidity was 46.65%, sunshine was 8.39h/day, temperature was 23.36Co and wind speed was 1.86m/sec. Water surplus was recorded in Khanaqin area, with values of (24.00mm) (34.18mm) (40.31mm) (28.83mm) and (19.92mm) in November, December, January, February and March respectively. The climate classification of Khanaqin area indicated semi dry and dry climates. Moreover, the region has water deficit that reached up to 43.56 % of the total rainfall values.