Abstract

Abstract. General Circulation Models (GCMs) successfully simulate future climate variability and climate change on a global scale; however, poor spatial resolution constrains their application for impact studies at a regional or a local level. The dynamically downscaled precipitation and temperature data were used for the future climate scenarios prediction for the period 2000–2050s, under the Special Report on Emissions Scenarios (SRES) A2 and A1B scenarios. In addition, rating equation was developed from measured discharge and gauge (stage) height data. The generated precipitation and temperature data from downscale and rating equation was used to run the HBV-Light 3.0 conceptual rainfall–runoff model for the calibration and validation of the model, gauge height was taken in the reference period (1988–2009). In the HBV-Light 3.0, a GAP optimization approach was used to calibrate the observed streamflow. From the precipitation scenarios with SRES A2 and A1B emissions at Kyanging, an increase of precipitation during summer and spring and a decrease during winter and autumn seasons was shown. The model projected annual precipitation for the 2050s of both the A2 and A1B scenarios are 716.4 mm and 703.6 mm, respectively. Such precipitation projections indicate the future increase of precipitation in all seasons except the summer. By the end of the 2050s simulation projects an increase maximum (minimum) discharge of 37.8 m3/s (13.9 m3/s) for A1B scenario and 36.2 m3/s (14.3 m3/s) for A2 scenario. A maximum projected discharge will increase for all seasons except for spring, whereas the minimum will decrease in summer.

Highlights

  • Climate and water studies play an important role in the protection of the environment

  • Performance of SDSM downscaling based on National Centres for Environmental Prediction (NCEP) and General Circulation Models (GCMs) predictors at Langtang, Kyanging are evaluated using statistical properties of daily climate data

  • It was found that the application of SDSM for statistical downscaling is suitable for developing daily climate scenarios

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Summary

INTRODUCTION

Climate and water studies play an important role in the protection of the environment. This study attempts to assess the downscaling of GCMs simulated gridded data to high resolution regional gridded or point data models: dynamical climate model, weather typing, transform function and scenario generation (http://www.cics.uvic.ca/scenarios/index.cgi?Scenarios). The Coupled Global Climate Model (CGCM3) of National Centres for Environmental Prediction (NCEP) predictors have been considered as the independent variables for multiple regression analysis for climate observation as a dependent variable. Optimization of the model was completed by applying the ordinary least squares method. In the above analyses, observed and NCEP data sets have a year length of 365 days (366 in leap years). The historical meteorological daily observed climate data are used as a predictor and input in the statistical downscaling method. The extreme daily simulated mean discharge at Syaprubasi hydrological station is 60.5 m3/s

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