Abstract
This study assessed the uncertainty in the spatial pattern of rainfall trends in six widely used monthly gridded rainfall datasets for 1979–2010. Bangladesh is considered as the case study area where changes in rainfall are the highest concern due to global warming-induced climate change. The evaluation was based on the ability of the gridded data to estimate the spatial patterns of the magnitude and significance of annual and seasonal rainfall trends estimated using Mann–Kendall (MK) and modified MK (mMK) tests at 34 gauges. A set of statistical indices including Kling–Gupta efficiency, modified index of agreement (md), skill score (SS), and Jaccard similarity index (JSI) were used. The results showed a large variation in the spatial patterns of rainfall trends obtained using different gridded datasets. Global Precipitation Climatology Centre (GPCC) data was found to be the most suitable rainfall data for the assessment of annual and seasonal rainfall trends in Bangladesh which showed a JSI, md, and SS of 22%, 0.61, and 0.73, respectively, when compared with the observed annual trend. Assessment of long-term trend in rainfall (1901–2017) using mMK test revealed no change in annual rainfall and changes in seasonal rainfall only at a few grid points in Bangladesh over the last century.
Highlights
Trend analysis provides important information required for planning adaptation and mitigation to climate changes [1]
The autocorrelation function (AFC) was used was used in to this study to find correlation a significant for various lags, while the presence of in this study find a significant forcorrelation various time lags, while time the presence of decadal and multidecadal and multi-decadal variability in the time series of climate indices were assessed through decadal variability in the time series of climate indices were assessed through wavelet decomposition of wavelet decomposition timeplot series data [50]
The results revealed a large variation in the spatial pattern of the trends in annual and results
Summary
Trend analysis provides important information required for planning adaptation and mitigation to climate changes [1]. A large volume of literature is available on trend analysis of various climatic variables using different methods [2,3]. One of the major impediments to the analysis of climatic trends is the availability of long-term quality climate data. Reliable analysis of climatic trends requires high-quality data for at least 30 years [4], which is often difficult to obtain for many regions of the world. Gridded climate data are suggested for such study in regions where long-term high-quality climate data are not available. With the pace of development, the reliability of gridded climate data in replicating actual properties of regional climate has been improved, and such data has been widely used for climatic trend analysis across the world
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