The Pan-Canadian High Resolution (2.5 km) Deterministic Prediction SystemSource: Weather and Forecasting:;2016:;volume( 031 ):;issue: 006::page 1791Author:Milbrandt, Jason A.
,
Bélair, Stéphane
,
Faucher, Manon
,
Vallée, Marcel
,
Carrera, Marco L.
,
Glazer, Anna
DOI: 10.1175/WAF-D-16-0035.1Publisher: American Meteorological Society
Abstract: ince November 2014, the Meteorological Services of Canada (MSC) has been running a real-time numerical weather prediction system that provides deterministic forecasts on a regional domain with a 2.5-km horizontal grid spacing covering a large portion of Canada using the Global Environmental Multiscale (GEM) forecast model. This system, referred to as the High Resolution Deterministic Prediction System (HRDPS), is currently downscaled from MSC?s operational 10-km GEM-based regional system but uses initial surface fields from a high-resolution (2.5 km) land data assimilation system coupled to the HRDPS and initial hydrometeor fields from the forecast of a 2.5-km cycle, which reduces the spinup time for clouds and precipitation. Forecast runs of 48 h are provided four times daily. The HRDPS was tested and compared to the operational 10-km system. Model runs from the two systems were evaluated against surface observations for common weather elements (temperature, humidity, winds, and precipitation), fractional cloud cover, and also against upper-air soundings, all using standard metrics. Although the predictions of some fields were degraded in some specific regions, the HRDPS generally outperformed the operational system for a majority of the scores. The evaluation illustrates the added value of the 2.5-km model and the potential for improved numerical guidance for the prediction of high-impact weather.
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contributor author | Milbrandt, Jason A. | |
contributor author | Bélair, Stéphane | |
contributor author | Faucher, Manon | |
contributor author | Vallée, Marcel | |
contributor author | Carrera, Marco L. | |
contributor author | Glazer, Anna | |
date accessioned | 2017-06-09T17:37:21Z | |
date available | 2017-06-09T17:37:21Z | |
date copyright | 2016/12/01 | |
date issued | 2016 | |
identifier issn | 0882-8156 | |
identifier other | ams-88230.pdf | |
identifier uri | http://onlinelibrary.yabesh.ir/handle/yetl/4231987 | |
description abstract | ince November 2014, the Meteorological Services of Canada (MSC) has been running a real-time numerical weather prediction system that provides deterministic forecasts on a regional domain with a 2.5-km horizontal grid spacing covering a large portion of Canada using the Global Environmental Multiscale (GEM) forecast model. This system, referred to as the High Resolution Deterministic Prediction System (HRDPS), is currently downscaled from MSC?s operational 10-km GEM-based regional system but uses initial surface fields from a high-resolution (2.5 km) land data assimilation system coupled to the HRDPS and initial hydrometeor fields from the forecast of a 2.5-km cycle, which reduces the spinup time for clouds and precipitation. Forecast runs of 48 h are provided four times daily. The HRDPS was tested and compared to the operational 10-km system. Model runs from the two systems were evaluated against surface observations for common weather elements (temperature, humidity, winds, and precipitation), fractional cloud cover, and also against upper-air soundings, all using standard metrics. Although the predictions of some fields were degraded in some specific regions, the HRDPS generally outperformed the operational system for a majority of the scores. The evaluation illustrates the added value of the 2.5-km model and the potential for improved numerical guidance for the prediction of high-impact weather. | |
publisher | American Meteorological Society | |
title | The Pan-Canadian High Resolution (2.5 km) Deterministic Prediction System | |
type | Journal Paper | |
journal volume | 31 | |
journal issue | 6 | |
journal title | Weather and Forecasting | |
identifier doi | 10.1175/WAF-D-16-0035.1 | |
journal fristpage | 1791 | |
journal lastpage | 1816 | |
tree | Weather and Forecasting:;2016:;volume( 031 ):;issue: 006 | |
contenttype | Fulltext |