Climate Change Impact Assessment for Aji Basin Using Statistical Downscaling and Bias Correction of Climate Model Outputs
| Autor: | N. S Vithlani, H. D. Rank |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
010504 meteorology & atmospheric sciences
Meteorology 0208 environmental biotechnology 02 engineering and technology Structural basin 01 natural sciences 020801 environmental engineering Climate change impact assessment Climatology Environmental science Climate model Bias correction 0105 earth and related environmental sciences General Environmental Science Downscaling |
| Zdroj: | Current World Environment. 11:670-678 |
| ISSN: | 2320-8031 0973-4929 |
| DOI: | 10.12944/cwe.11.2.40 |
| Popis: | For the future projections Global climate models (GCMs) enable development of climate projections and relate greenhouse gas forcing to future potential climate states. When focusing it on smaller scales it exhibit some limitations to overcome this problem, regional climate models (RCMs) and other downscaling methods have been developed. To ensure statistics of the downscaled output matched the corresponding statistics of the observed data, bias correction was used. Quantify future changes of climate extremes were analyzed, based on these downscaled data from two RCMs grid points. Subset of indices and models, results of bias corrected model output and raw for the present day climate were compared with observation, which demonstrated that bias correction is important for RCM outputs. Bias correction directed agreements of extreme climate indices for future climate it does not correct for lag inverse autocorrelation and fraction of wet and dry days. But, it was observed that adjusting both the biases in the mean and variability, relatively simple non-linear correction, leads to better reproduction of observed extreme daily and multi-daily precipitation amounts. Due to climate change temperature and precipitation will increased day by day. |
| Databáze: | OpenAIRE |
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