The assessment of local and regional impacts of climate change often requires downscaling of general circulation model (GCM) projections from coarser GCM-scale to finer localor catchmentscale spatial resolution. This paper provides an assessment of two downscaling approaches for simulation of daily rainfall over Sydney, Australia. The two downscaling alternatives compared include a multivariate...

introduction the main perspective in seasonal prediction of precipitation is presentation of a qualitative prediction for upcoming seasons. the information gained from such predictions can be used for decision making in various disciplines such as agriculture, water management and hydropower production. besides, it can help us reduce the adverse effects of climatic changes like drought and floo...

.............................................................................................................................................. iv 1.0 Introduction.......................................................................................................................... 1 2.0 Experiments..................................................................................................

An improved statistical-dynamical downscaling method for the regionalization of large-scale climate analyses or simulations is introduced. The method is based on the disaggregation of a multi-year time-series of large-scale meteorological data into multi-day episodes of quasistationary circulation. The episodes are subsequently grouped into a de®ned number of classes. A regional model is used t...

In this paper, a multifractal downscaling technique is applied to adequately transformed and lag corrected normalized difference vegetation index (NDVI) in order to obtain daily estimates of rainfall in an area of the Peruvian Andean high plateau. This downscaling procedure is temporal in nature since the original NDVI information is provided at an irregular temporal sampling period between 8 a...

The advent of powerful computers has enabled atmospheric scientists to run weather forecast and climate models at ever increasing resolutions. Of particular interest are limited area models with high temporal and spatial resolution that can be run affordably on workstations. These models, initialized and forced at the boundaries with data from large-scale models with coarse resolution, resolve ...

We compare regional climate change scenarios (temperature and precipitation) over eastern Nebraska produced by a semiempirical statistical downscaling (SDS) technique and regional climate model (RegCM2) experiments, both using large scale information from the same coarse resolution general circulation model (GCM) control and 2 x COe simulations. The SDS method is based on the circulation patter...

We explore the sources of forecast uncertainty in a mixed dynamical-stochastic ensemble prediction chain for small-scale precipitation, suitable for hydrological applications. To this end, we apply the stochastic downscaling method RainFARM to each member of ensemble limitedarea forecasts provided by the COSMO-LEPS system. Aim of the work is to quantitatively compare the relative weights of the...

Dynamical downscaling has been extensively used to study regional climate forced by large-scale global climate models. During the downscaling process, however, the simulation of regional climate models (RCMs) tends to drift away from the driving fields. Developing a solution that addresses this issue, by retaining the large scale features (from the large-scale fields) and the small-scale featur...

numerous studies yet have been carried out on downscaling of the large-scale climate data usingboth dynamical and statistical methods to investigate the hydrological and meteorological impacts of climatechange on different parts of the world. this study was also conducted to investigate the capability of feedforwardneural network with error back-propagation algorithm to downscale the provincial...