Some climatological characteristics of the changing pattern of temperature in Bangladesh – A diagnostic approach

Based on climatological data of maximum and minimum temperatures of seventeen stations for a period of 60 years (1949 - 2008), obtained from Bangladesh Meteorological Department (BMD), the changing pattern of temperature in Bangladesh has been investigated. Some characteristics of annual variation and spatial distribution of mean monthly minimum, mean monthly maximum and mean monthly temperature, annual variation and spatial distribution of mean monthly amplitude of temperature have been explained. The characteristics of changing pattern of temperature such as standard deviation, coefficient of variation, ratio between mean monthly maximum and mean monthly minimum temperatures have been studied. The run of the temperature in different stations for the years 1949-2008, the periodicity of mean annual temperature and mean decade deviations have been discussed. The integral curve of mean annual temperature for Dhaka has been prepared and explained. Regression analysis for mean monthly temperature of January, April, July and October for the stations Sylhet, Chittagong, Khulna and Rangpur with Dhaka have been analyzed. Some linear correlation equations have been deduced. In the investigation, attempts (as far as possible) have been made to explain the synoptic cause of the changing pattern of temperature in Bangladesh.

Impact of climate variability on human health: A pilot study in tertiary care hospital of Eastern Uttar Pradesh, India

This study is an attempt to find out the effect of climate variables on respiratory, cardiovascular, vector-borne and diarrheal diseases from 2004-2013 carried out at Sir Sunder Lal hospital, Varanasi, Uttar Pradesh with focus on eastern Uttar Pradesh. The study shows that cases of Chronic Obstructive Pulmonary Disorder (COPD) and Cardiovascular Disorders (CVD) didn’t show any significant relation with any of the climate variables. With increase of 1 C mean maximum monthly temperature the estimated decrease in number of Tuberculosis (TB) patients was 4 (95% CI = 4.95-3.05) while a 1C increase in minimum monthly temperature showed increase of TB patients by 4 (95% CI = 4.95-3.05). One percent increase of monthly averaged relative humidity is estimated to increase the one pneumonia patients (95% CI = 1.95-0.05) at any given month. One-degree increase in given monthly temperature will increase the load of one diarrhea patients (95% CI = 1.95-0.05) monthly. Dengue and Malaria patients showed increasing monthly malaria cases by 5 (95% CI = 5.95-4.05) with 1C rise in minimum monthly temperature and by 1 patient (95% CI = 1.95-0.05) with increase in 1% relative humidity. Encephalitis showed an increase of one patient load (95% CI = 1.95-0.05) with monthly increase of 1C in maximum temperature. The study shows advance knowledge of health information, on timescales of seasons to decades ahead, would aid effective planning of health response measures and infrastructure at local and regional scale.

Thornthwaite Models for Estimating Potential evapotranspiration in Medan City

Evapotranspiration plays a big role in the hydrology process. Potential Evapotranspiration (PET) always keeps soil moisture available, although an amount of water evaporates through evaporation and transpiration. The Thornthwaite equation uses air temperature and latitude from meteorological observations for estimating PET. Medan City is one of the biggest cities in Indonesia that have a problem with land-use change that affected water balance. This study is to estimate the PET and to learn the water balance in Medan City. The monthly temperature data for the period 2011-2020 is collected from three meteorological stations for estimating PET using the Thornthwaite equation. The highest monthly temperature is in Belawan Maritime Meteorological Station yet the lowest rainfall. The trends of PET depend on the month. The highest PET in Jan.-Apr. and Sep.-Dec. are in Belawan Maritime Meteorological Station, while the highest PET in May-Aug. is in Indonesia Agency for Meteorology Climatology and Geophysics Region I Medan. The P-PET has shown negative and positive values. The lowest P-PET is found in Belawan Maritime Meteorological Station in March and the highest P-PET is found in Indonesia Agency for Meteorology Climatology and Geophysics Region I Medan in October.

Global Warming in Cameron Highlands: Forecasting its Temperature Level via ARIMA vs ARAR

The average global temperature has increased at a rapid rate over the past 50 years leading to global warming. The impact of climate change can be felt across the continents. In this research, analysis was conducted to model and forecast the monthly temperature of Cameron Highlands in 2020 and 2021, against its historical monthly average temperature from January 1990 until December 2019. Two (2) methods namely (i) Seasonal Autoregressive Integrated Moving Average (SARIMA) model and (ii) Autoregressive Autoregressive (ARAR) algorithm were compared to determine the best model to forecast the monthly temperature of Cameron Highlands. SARIMA (1,1,2)(1,1,1)12 was found to be the best at forecasting the monthly temperature in Cameron Highlands as RMSE and MAPE values were lower than ARAR. In year 2021, the temperature in Cameron Highlands is estimated to increase by 1.6 °C. The result of the forecast showed that its monthly temperature was expected to increase in the next two (2) years. Hence, this calls for serious action to be taken by higher authorities.

Associations between environmental covariates and temporal changes in malaria incidence in high transmission settings of Uganda: a distributed lag nonlinear analysis

Background Environmental factors such as temperature, rainfall, and vegetation cover play a critical role in malaria transmission. However, quantifying the relationships between environmental factors and measures of disease burden relevant for public health can be complex as effects are often non-linear and subject to temporal lags between when changes in environmental factors lead to changes in malaria incidence. The study investigated the effect of environmental covariates on malaria incidence in high transmission settings of Uganda. Methods This study leveraged data from seven malaria reference centres (MRCs) located in high transmission settings of Uganda over a 24-month period. Estimates of monthly malaria incidence (MI) were derived from MRCs’ catchment areas. Environmental data including monthly temperature, rainfall, and normalized difference vegetation index (NDVI) were obtained from remote sensing sources. A distributed lag nonlinear model was used to investigate the effect of environmental covariates on malaria incidence. Results Overall, the median (range) monthly temperature was 30 °C (26–47), rainfall 133.0 mm (3.0–247), NDVI 0.66 (0.24–0.80) and MI was 790 per 1000 person-years (73–3973). Temperature of 35 °C was significantly associated with malaria incidence compared to the median observed temperature (30 °C) at month lag 2 (IRR: 2.00, 95% CI: 1.42–2.83) and the increased cumulative IRR of malaria at month lags 1–4, with the highest cumulative IRR of 8.16 (95% CI: 3.41–20.26) at lag-month 4. Rainfall of 200 mm significantly increased IRR of malaria compared to the median observed rainfall (133 mm) at lag-month 0 (IRR: 1.24, 95% CI: 1.01–1.52) and the increased cumulative IRR of malaria at month lags 1–4, with the highest cumulative IRR of 1.99(95% CI: 1.22–2.27) at lag-month 4. Average NVDI of 0.72 significantly increased the cumulative IRR of malaria compared to the median observed NDVI (0.66) at month lags 2–4, with the highest cumulative IRR of 1.57(95% CI: 1.09–2.25) at lag-month 4. Conclusions In high-malaria transmission settings, high values of environmental covariates were associated with increased cumulative IRR of malaria, with IRR peaks at variable lag times. The complex associations identified are valuable for designing strategies for early warning, prevention, and control of seasonal malaria surges and epidemics.

TREND OF TEMPERATURE AND RELATIVE HUMIDITY IN EAST SIANG DISTRICT OF ARUNACHAL PRADESH, INDIA

A study was conducted in the East Siang District of Arunachal Pradesh for the time period from 2000 to 2018 in order to study the temperature and relative humidity parameters of climate change in the study area. The study was based on secondary data collected from the regional meteorological centre wherein official data was collected for the years 2000 to 2018 for temperature and 2006 to 2018 for relative humidity. It was observed that maximum temperature in the study area exhibited an increasing trend during the study period. A monthly temperature study also showed that maximum temperature for the study area exhibited a significant increase during the months of February, July and August. The average annual Relative Humidity for East Siang during 2006-2018 was found to be 76.72 and 77.04 at 0830 hrs and 1730 hrs IST respectively. The monthly study of the Relative Humidity showed significant increase for the evening hours of 1730 hours IST during the months of April, and a significant decreasing trend for the months of September and October

Effect of Environmental Factors on Apricot (Prunus armeniaca L.) Yield in the City of Jerusalem Occupied, Palestine

Apricot is a deciduous perennial tree, which classified within to the Rosacea family, sensitive to climatic factors, and its production has an economic role for many countries of the world, including Palestine. Mean annual temperatures and precipitation were analyzed, using data from a meteorological station of Jerusalem, Palestine, which has recorded between the year (1993-2012), and with the same number of years of apricot production, knowing that production data were taken from the Palestinian Statistics Center for the mentioned period. On the other hand, we used Professor Salvador Ravers Martins' methodology to classify the Earth in the process of analyzing environmental factors, there are two aspects of the factors: The first is climatic, which is the amount of rain or precipitation, mean monthly temperature and soil water reserve, and the second factor is the bioclimatic, which is annual ombrothermic index, simple continentality index, compensated thermicity index, and water deficit. In conclusion, Jerusalem was adversely affected by mean monthly temperature, precipitation, compensated thermicity index, deficit water, annual ombrothermic index during (1997-2002 and 2007-2012), but positively influenced by soil water reserve on apricot production, during (1993-1997 and 2002-2007), with a great rate of the variance in axis F1 (98.8%), axis F2 (0.82%) and symmetrical plot axes F1and F2 (99.8%), when the correspondence analysis was applied. However, humid areas characterized by mild summers are the suitable region for apricot production and productivity, with a temperature ranging between 22-24°C, at which high quality production can be obtained, the amount of rain is between 600 - 800 mm annually. Final, environmental regions in the thermomediterranean and the Mesomediterranean, with simple continentality index is 17 - 22, annual ombrothermic index is 2.5, while the compensated thermicity index is about 250/420, to obtain the highest ideal production of apricots in Jerusalem, Palestine.