Effectiveness of Gaussian Distribution Mapping for Bias Correction of RCM Simulated Temperature for Junagadh Region

Abstract

The Gaussian distribution mapping approach was adopted to correct the biases in the simulation of temperature data by RCA4 RCM. It included the bias correction of temperature for the baseline period and future scenarios . The bias correction also included calibration (1965-1995) and validation (1996-2005) by comparing it with actual observation. The bias correction improved the mean and coefficient of variation (Cv) for the calibration period with goodness of fit near to 1.0 and with reasonable goodness of fit during the validation period for RCA4 (IPCHEC) RCMs. The statistical properties like skewness coefficient (Cs) and kurtosis coefficient (Ck) were not altered because of using normal distribution for bias correction of temperature for calibration, validation and future scenario. The mean and coefficient of variation (Cv) of simulated daily temperature by RCA4 (IPCHEC) for the future scenario were required to get corrected. The Gaussian distribution mapping approach was found very effective tool for the bias correction of the RCA4 RCM simulated temperature for the Junagadh region of the Gujarat state of India.

Study on Physicochemical Properties of Clay Loam Soil of Junagadh Region

“…To calculate how much water is available to plants, it is vital to know how much water the soil can hold under different pressures (Patel and Rank, 2016;2020). For every crop, the ability of the soil to retain water in the crop root zone is crucial (Rank et al, 2016;2022a;2022b). Knowing the parameters of the soil is necessary to reproduce water flow through unsaturated soils (Vora et al, 2016;Vekariya et al, 2021a).…”