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• Monitoring temperature patterns at selected world heritage sites in Egypt using high resolution WorldClim data

  42-58

  Viranch N. Dave

  Views:

  488

  Long term temperature patterns helps in assessing changes in the climatic conditions of an area and climatic changes poses a major challenge to the world heritage sites whether it is natural or cultural. Therefore in this study using maximum and minimum temperature data for the period 1960-2021 downloaded from WorldClim 2.1 calculation of mean temperature is done in QGIS environment for the selected UNESCO world heritage sites of Arab Republic of Egypt. WorldClim 2.1 provides finer resolution gridded data downscaled from Climate Research Unit. Trend analysis using linear regression and Mann-Kendall method and Sen’s Slope estimate is used to understand the patterns of mean temperature at all the selected sites. The study reveals that mean temperature at all the selected sites is increasing but since 1990 the sites which are located geographically in lower Egypt are witnessing rapid increase in mean temperature compared to the sites located in upper Egypt which historically witnessed more temperature due to its geographical milieu. This study can help in stimulating the utility of geospatial data in understanding the changes in climatic parameters in relation to world heritage sites. Moreover it can serve as foundation upon which detailed longitudinal site specific investigation can be done.

• Analysis of Climate Variability and Agricultural Productivity in Mizoram, Northeast India

  53-64

  Benjamin L Saitluanga

  Gabriel Lalchhandama

  P Rinawma

  Views:

  283

  Mountainous regions are considered highly vulnerable to the affects of climate change. The extent of change and variability of climatic parameters is still unexamined in many remote mountainous areas.  This paper aims in understanding the change in pattern of rainfall and temperature for a period of 30 years in Mizoram. The analysis of time series changing trend in climatic variables is carried out by using Coefficient of Variation (CV), Mann-Kendall (M-K) and Sen’s Slope estimator. The analysis reveals that high variation is observed for both the variables in all the decadal, three decadal and seasonal change. The CV analysis shows that the highest seasonal rainfall variation occurs during winter and the highest seasonal temperature variation occurs during spring. Mann-Kendall test shows a significant change in rainfall with November showing the highest negative trend of rainfall. The temperature trend analysis in the study also reveals drastic change of temperature. An understanding of climatic change, trend and variability helps in predicting for better natural resources from the susceptibility of climate change.