ExTREME EVENT ANALySIS 33. Synthesis Report Volume I

ACCCRN India: Synthesis Report – Volume I 41 measurement by the bias correction factor. This enabled in comparing the results with respect to the observed information.

4.2 ExTREME EVENT ANALySIS

Based on the results from the above process Extreme event analysis EEA was carried out using the daily precipitation and temperature data. The best models which were selected from the bias correction and correlation analysis were considered for the EEA. The historical data used in this case is from GHCN daily. IMD gridded data was not used because GHCN provides the station data, which is more representative of the city under study rather than the grid, which is more representative of the region. Further, IMD data used for the bias correction and correlation analysis was gridded data of 0.5 degree x 0.5 degree, which is a representative sample of 50 sq. km. Such gridded data may not be able represent the daily precipitation and temperature levels, which are bound to change at a city level. Therefore, IMD data was used but to ill the gaps within the GHCN data days for which no GHCN data was available. This process ensured data continuity. The EEA were carried out for three indicators i.e. Rainfall, Minimum Temperature and Maximum. Historical daily weather data used for the EEA analysis were from the following periods: ƒ Rainfall: GHCN data 1901-2007 and model base line data 1961-2000 ƒ Minimum Temperature: GHCN data 1969-2007 and model base line data 1961-2000 ƒ Maximum Temperature: GHCN data 1969-2007 and model base line data 1961-2000 Following EEA was carried out for the historical, base line and model predicted future scenarios: 1. Percentile variations 5th, 10th, 90th and 95th percentiles within rainfall, minimum and maximum Temperature 2. Number of days where the rainfall is less than 2 mm, within all given months especially during rainy season ƒ The gridded historical rainfall and temperature data were procured from the Indian Meteorological Department. This data was used for gap illing within GHCN. There are several models, which attempt to model the future precipitation and temperature scenarios. From these models, two downscaled models were used in this analysis. 1. GCMs as downscaled by CSAG 2. PRECIS, RCM developed for India by Hadley research centre in collaboration with IITM. The results from the above models are simulations of the future climate with assumptions of certain emission scenarios. The results presented in this study are an indicative approximations of the future. Since the models are simple approximations of climate, there are inherent biases and uncertainty in their climate scenarios. The uncertainty includes the models inability to represent all the land-ocean-atmosphere interactions that inluences the current and future climate. Bias: Our conidence in a model’s scenarios of future climate is largely determined by how well that model can simulate historical, observed climate - past rainfall, past minimum or maximum temperatures both in time and in measure. The models usually tend to simplify the reality; the models tend to overestimate or underestimate past rain or temperatures. This variation from the observed measure is called the bias within the model. This deviationvariation, in time e.g. say average monsoon onset and withdrawal and in measure e.g. increase or decrease in temperature determines the conidence in the model. The model’s bias in replicating past rainfall and its ability to replicate the monsoon and summer was taken as a measure of uncertainty of the models ability in predicting the future climate scenarios. The models with low bias in both its ability to replicate the seasons and measures were selected for further analysis. In this analysis, multiplicative bias correction was carried out. The equation below describes the bias correction factor which was performed. Bias Correction Factor = Simulated Observed All future simulations for selected models were corrected for their bias by dividing the future simulated ACCCRN India: Synthesis Report – Volume I 42 3. Number of days within which the 24 hour precipitation has been more than 25 mm. 4. Number of days in a given month where the maximum temperature and minimum temperature exceeds 40°C and 27°C respectively.

4.3 UNCERTAINTIES