Abstract

ABSTRACTThis article is the second of a series of two articles. In the first article, two models were developed with National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis and HadCM3 outputs, for statistically downscaling these outputs to monthly precipitation at a site in north‐western Victoria, Australia. In that study, it was seen that the downscaling model developed with NCEP/NCAR reanalysis outputs performs much better than the model developed with HadCM3 outputs. Furthermore, it was found that there is large bias in HadCM3 outputs which needs to be corrected. In this article, the downscaling model developed with NCEP/NCAR reanalysis outputs was used to downscale HadCM3 20th century climate experiment outputs to monthly precipitation over the period 1950–1999. In all four seasons, the precipitation downscaled with HadCM3 20th century outputs, displayed a large scatter and the majority of precipitation was overestimated. The precipitation downscaled with HadCM3 outputs was bias‐corrected against the observed precipitation pertaining to the period 1950–1999, using three techniques: (1) equidistant quantile mapping (EDQM), (2) monthly bias‐correction (MBC) and (3) nested bias‐correction (NBC). Although all these bias‐correction techniques were able to adequately correct the statistics of downscaled precipitation, the magnitude of the scatter of precipitation remained almost the same. Considering the performances and its ability to correct the cumulative distribution of precipitation, EDQM was selected for the bias‐correction of future precipitation projections. HadCM3 outputs for the A2 and B1 greenhouse gas scenarios were introduced to the downscaling model and the downscaled precipitation for the period 2000–2099 was bias‐corrected with the EDQM technique. Both A2 and B1 scenarios indicated a rise in the average of future precipitation in winter and a drop in it in summer and spring. These scenarios showed an increase in the maximum monthly precipitation in all seasons and an increase in percentage of months with zero precipitation in summer, autumn and spring.

Highlights

  • Over the 800 000-year period prior to the industrial revolution (1750–1850), the concentration of the atmospheric carbon dioxide [dominant greenhouse gas (GHG)] fluctuated approximately between 180 and 280 parts per million (Tripati et al, 2009)

  • It was realized that the model built with NCEP/NCAR outputs performed better than the model that was developed with Hadley Centre Coupled Model version 3 GCM (HadCM3) outputs

  • In this study the model built with NCEP/NCAR outputs was used for the future projections of monthly precipitation at the Halls Gap post office located in north western Victoria, Australia, with HadCM3 outputs corresponding to possible future climate as inputs

Read more

Summary

Introduction

Over the 800 000-year period prior to the industrial revolution (1750–1850), the concentration of the atmospheric carbon dioxide [dominant greenhouse gas (GHG)] fluctuated approximately between 180 and 280 parts per million (ppm) (Tripati et al, 2009). This article which is the second of the series of two articles, discusses the bias-correction and future precipitation projections of the statistical downscaling model developed in the first article, with NCEP/NCAR reanalysis outputs. This downscaling model was used in this study because of its better performances seen in the first article. Considering the performances of each of these three bias-corrections, only the EDQM technique was used for the bias-correction of monthly precipitation projections produced into future by the downscaling model with HadCM3 outputs pertaining to the future climate.

Study area and data
Generic methodology
Bias-correction
Equidistant quantile mapping
Step 1
Step 2
Step 3
Monthly bias-correction
Nested bias-correction
Potential of bias-correcting GCM outputs against reanalysis outputs
Application
Bias-correction of precipitation downscaled with HadCM3 outputs
Validation of performances of EDQM technique
Greenhouse gas emission scenarios
Bias-corrected future precipitation projections
Caveats and uncertainties involved in the study
Summary and conclusions
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call