✦ LIBER ✦

Statistical downscaling of monthly forecasts

✍ Scribed by Willem A. Landman; Warren J. Tennant

Publisher: John Wiley and Sons
Year: 2000
Tongue: English
Weight: 289 KB
Volume: 20
Category: Article
ISSN: 0899-8418
DOI: 10.1002/1097-0088(20001115)20:13<1521::aid-joc558>3.0.co;2-n

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

A statistical downscaling method for mon

A statistical downscaling method for monthly total precipitation over Turkey

✍ Hasan Tatli; H. Nüzhet Dalfes; Ş Sibel Menteş 📂 Article 📅 2004 🏛 John Wiley and Sons 🌐 English ⚖ 952 KB

## Abstract Researchers are aware of certain types of problems that arise when modelling interconnections between general circulation and regional processes, such as prediction of regional, local‐scale climate variables from large‐scale processes, e.g. by means of general circulation model (GCM) ou

Correction and downscaling of NWP wind s

Correction and downscaling of NWP wind speed forecasts

✍ Tom Howard; Peter Clark 📂 Article 📅 2007 🏛 John Wiley and Sons 🌐 English ⚖ 190 KB

## Abstract NWP models typically parametrize the effects of unresolved orography, often through use of an effective (orographic) roughness. Whilst this parametrization realistically models the orographic drag on the synoptic‐scale flow, it creates two problems for the assimilation of wind observati

A comparison of statistical downscaling

A comparison of statistical downscaling methods suited for wildfire applications

✍ John T. Abatzoglou; Timothy J. Brown 📂 Article 📅 2011 🏛 John Wiley and Sons 🌐 English ⚖ 779 KB

## Abstract Place‐based data is required in wildfire analyses, particularly in regions of diverse terrain that foster not only strong gradients in meteorological variables, but also complex fire behaviour. However, a majority of downscaling methods are inappropriate for wildfire application due to

Statistical downscaling of daily precipi

Statistical downscaling of daily precipitation from observed and modelled atmospheric fields

✍ Stephen P. Charles; Bryson C. Bates; Ian N. Smith; James P. Hughes 📂 Article 📅 2004 🏛 John Wiley and Sons 🌐 English ⚖ 275 KB

## Abstract Statistical downscaling techniques have been developed to address the spatial scale disparity between the horizontal computational grids of general circulation models (GCMs), typically 300–500 km, and point‐scale meteorological observations. This has been driven, predominantly, by the n

Monthly data and short-term forecasting:

Monthly data and short-term forecasting: an assessment of monthly data in a VAR model

✍ Eduardo Salazar; Martin Weale 📂 Article 📅 1999 🏛 John Wiley and Sons 🌐 English ⚖ 170 KB 👁 1 views

Use of monthly data for economic forecasting purposes is typically constrained by the absence of monthly estimates of GDP. Such data can be interpolated but are then prone to measurement error. However, the variance matrix of the measurement errors is typically known. We present a technique for esti

A logistic regression approach for month

A logistic regression approach for monthly rainfall forecasts in meteorological subdivisions of India based on DEMETER retrospective forecasts

✍ K. Prasad; S. K. Dash; U. C. Mohanty 📂 Article 📅 2009 🏛 John Wiley and Sons 🌐 English ⚖ 203 KB

## Abstract A multi‐predictor logistic regression model has been developed for probabilistic forecasts of domain average rainfall on monthly timescale for three study regions namely, India as a whole, and two homogeneous meteorological subdivisions of India, i.e. Orissa on the east coast and Gujara