Temporal Patterns of the Two-Dimensional Spatial Trends in Summer Temperature and Monsoon Precipitation of Bangladesh

Abstract

Two climate indices, TXx and PRCPTOT, representing the summer maximum temperature and annual total monsoon precipitation, respectively, in Bangladesh were computed. The temperature and precipitation measurements from 34 meteorological stations during the temporal extent of 1948–2007 were applied for indices’ computation under thorough quality control. The spatial trends of the indices were analyzed by applying two-dimensional least square approach along latitudes and longitudes of the observation points. The temporal patterns of the spatial trends were identified by temporally interpolating them applying thin plate smoothing spline method. The analyses of TXx identified regional scale spatial trends in the east-west and south-north directions, which were increasing between 1948 and 1980s. After the 1980s the spatial trends started decreasing, and after 2000 the spatial trend along the south-north changed its direction to the north-south and continued until present. The analyses of the PRCPTOT identified spatial trends in the west-east and north-south directions, which were decreasing between 1948 and 1980s and thereafter increasing until present. About half of the spatial trends were significant in F-statistics at or more than 90% confidence level. Thus, the obtained results indicated a significant climatic shift within the regional scale of the country during the study period.

Representativeness impacts on accuracy and precision of climate spatial interpolation in data-scarce regions

“…The influence of the number of data on the accuracy and precision of spatial interpolation has been discussed as of utmost importance (Sluiter, ; Li and Heap, ) and several studies have highlighted the consequences of scarce data (e.g. Goovaerts, ; Bhowmik and Cabral, ; Bhowmik, , ; Bhowmik and Costa, ). By contrast, the present study shows that the representativeness of the data, i.e.…”

“…Given the significantly low representativeness of the data, accurate and precise PRCPTOT surfaces for Bangladesh are not producible for the 1948–2007 period. Nevertheless, a few studies have computed precipitation surfaces despite the data scarcity and low representativeness in Bangladesh (Shahid, , ; Bhowmik, , ), and in other data‐scarce regions (Suhaila and Jemain, ). This study showed that these surfaces are not satisfactorily accurate and precise, thus they do not provide enough detail and should be used cautiously in comprehensive research.…”

“…This study showed that these surfaces are not satisfactorily accurate and precise, thus they do not provide enough detail and should be used cautiously in comprehensive research. In contrast, the regional temperature surfaces, as computed by Bhowmik (2012Bhowmik ( , 2013 and Bhowmik and Cabral (2013) are satisfactorily accurate and precise and can be used in further research. 376 Bhowmik and Costa…”

“…Two annual climate indices, the annual total precipitation in wet days (PRCPTOT) and the yearly maximum value of the daily maximum temperatures (TXx), were computed. These indices are recommended by the joint CCl/CLIVAR/JCOMM Expert Team on Climate Change Detection and Indices (ETCCDI) (Peterson et al , ; Frich et al , ) and allow analysis of climatic changes in Bangladesh (Bhowmik, , ). A thorough quality control has been performed on the raw data before computation of the indices.…”

“…Thus, PRCPTOT and TXx values were obtained for 8–32 and 10–34 data locations, respectively, for the 1948–2007 period. Detailed formulation of the indices and quality control procedures can be found in Zhang and Yang (), Bhowmik (, ) and Bhowmik and Cabral ().…”