Incorporating Stochastic Weather Generators into Studies on Climate Impacts: Methods and Uncertainties
By adopting various stochastic weather generators, different research groups in their recent studies have realized the importance of the effects of climatic variability on crop growth and development. The conventional assessments derived climate change scenarios from General Circulation Models (GCMs) experiments, however, are incapable of helping to understand this importance. The particular interest here is to review the general methodological scheme to incorporate stochastic weather generator into climate impact studies and the specific approaches in our studies, and put forward uncertainties that still exist.
A variety of approaches have been taken to develop the parameterization program and stochastic experiment, and adjust the parameters of a typical stochastic weather generator called WGEN. Usually, the changes in monthly means and variances of weather variables between controlled and changed climate are used to perturb the parameters to generate the intended daily climate scenarios. We establish a parameterization program and methods for stochastic experiment of WGEN in the light of outputs of short-term climate prediction models, and evaluate its simulations on both temporal and spatial scales. Also, we manipulated parameters in relation to the changes in precipitation to produce the intended types and qualitative magnitudes of climatic variability. These adjustments yield various changes in climatic variability for sensitivity analyses. The impacts of changes in climatic variability on maize growth, final yield, and agro-climatic resources in Northeast China are assessed and presented as the case studies through the above methods.
However, this corporation is still equivocal due to deficiencies of the generator and unsophisticated manipulation of parameters. To detect and simulate the changes in climatic variability is one of the indispensable ways to reduce the uncertainties in this aspect.
Key wordsStochastic weather generator Climate impacts Climatic variability
Unable to display preview. Download preview PDF.
- Houghton, J. T., L. G. Meira Filho, and B. A. Callander et al. (eds.), 1996: Contribution of WGI to the second assessment report of the intergovernmental panel on climate change: Climate change 1995 (The science of climate change), Report of the IPCC, WMO and UNEP, University Press, Cambridge, 572 pp.Google Scholar
- Richardson, C. W., and D. A. Wright, 1984: WGEN: A model for generating daily weather variables, U.S. Dept. of Agriculture, Agricultural Res. Service, ARS-8, 83 pp.Google Scholar
- Smith, J. B., and D. Tirpak et al., (eds.), 1989: The potential effects of global climate change on the united states, U.S. I EPA, EPA-230-05-89-050, 413 pp.Google Scholar
- Wu Jindong, and Wang Futang, 2000a: Study on the creation of daily climatic variation scenarios with a stochatic weather generator and various interpolations. Quart. J. Appl. Meteor., 11, 129–136 (in Chinese).Google Scholar
- Wu Jindong, Wang Shili, and Zhang Jianmin, 2000b: A numerical simulation of the impacts of climate change on water and thermal resources in Northeast China. Resources Science, 22(6), 36–42 (in Chinese).Google Scholar
- Wu Jindong, and Wang Futang, 2000c: Study on the parameters programme of a stochastic weather generator and evaluation of its simulation. Acta Meteorologica Sinica, 58, 49–59 (in Chinese).Google Scholar