The Canadian Global Environmental Multiscale model on the Yin-Yang grid system

2011 ◽  
Vol 137 (660) ◽  
pp. 1913-1926 ◽  
Author(s):  
Abdessamad Qaddouri ◽  
Vivian Lee
Keyword(s):  
Multiscale Model ◽  
Grid System ◽  
Global Environmental ◽  
Yin Yang ◽  
Global Environmental Multiscale

scholarly journals Evaluation of GPS Precipitable Water over Canada and the IGS Network

2005 ◽  
Vol 44 (1) ◽  
pp. 153-166 ◽  
Author(s):  
Godelieve Deblonde ◽  
Stephen Macpherson ◽  
Yves Mireault ◽  
Pierre Héroux
Keyword(s):  
Precipitable Water ◽  
Multiscale Model ◽  
Geodetic Survey ◽  
Tropospheric Delay ◽  
Observation Network ◽  
Global Environmental ◽  
The Mean ◽  
The Tropics ◽  
Estimated Error ◽  
Global Environmental Multiscale

Abstract Precipitable water (PW) derived from the GPS zenith tropospheric delay (ZTD) is evaluated (as a first step toward variational data assimilation) through comparison with that of collocated radiosondes (RS_PW), operational analyses, and 6-h forecasts (from the Canadian Global Environmental Multiscale model) of the Canadian Meteorological Centre. Two sources of ZTD data are considered: 1) final ZTD (over Canada), computed by the Geodetic Survey Division (GSD) of Natural Resources Canada, and 2) final ZTD (distributed globally), obtained from the International GPS Service (IGS). The mean GSD GPS–derived PW (GPS_PW) is 14.9 mm (reflecting the relatively cold Canadian climate), whereas that of the IGS dataset is 20.8 mm. Intercomparison statistics [correlation, standard deviation (SD), and bias] between GPS_PW and RS_PW are, respectively, 0.97, 2.04 mm, and 1.35 mm for the GSD data and 0.98, 2.6 mm, and 0.67 mm for the IGS data. Comparisons of GPS_PW with 6-h forecast PW (TRIAL_PW) show slightly lower correlations and a higher SD. The increase in SD is greater for the IGS data, which is not surprising, because in regions such as the Tropics and subtropics, moisture forecasts are of a lower quality and the RS observation network is sparse. From a three-way intercomparison (IGS GPS_PW, RS_PW, and TRIAL_PW) of the SD statistics, it is found that GPS_PW has the lowest estimated PW error (≈1 mm) for PW in the 5–30-mm range. For PW greater than 30 mm, the RS_PW estimated error is ≈2 mm, and that of GPS_PW is ≈2.5 mm. The TRIAL_PW estimated error increases with PW, reaching 5.5 mm in the 40–55-mm PW range. These intercomparison results indicate that GPS_PW should be a useful source of humidity information for NWP applications.

scholarly journals GEM-AQ, an on-line global multiscale chemical weather system: model description and evaluation of gas phase chemistry processes

2007 ◽  
Vol 7 (5) ◽  
pp. 14895-14937 ◽  
Author(s):  
J. W. Kaminski ◽  
L. Neary ◽  
J. Struzewska ◽  
J. C. McConnell ◽  
A. Lupu ◽  
...  
Keyword(s):  
Multiscale Model ◽  
Global Scale ◽  
Tropospheric Chemistry ◽  
Model Description ◽  
Weather System ◽  
Gas Phase Chemistry ◽  
Global Environmental ◽  
On Line ◽  
Phase Chemistry ◽  
Global Environmental Multiscale

Abstract. Tropospheric chemistry and air quality processes were implemented on-line in the Global Environmental Multiscale model. The integrated model, GEM-AQ, has been developed as a platform to investigate chemical weather at scales from global to urban. The model was exercised for five years (2001–2005) to evaluate its ability to simulate seasonal variations and regional distributions of trace gases such as ozone, nitrogen dioxide and carbon monoxide on the global scale. The model results presented are compared with observations from satellites, aircraft measurement campaigns and balloon sondes.

scholarly journals Verification of High-Resolution Medium-Range Precipitation Forecasts from Global Environmental Multiscale Model over China during 2009–2013

Atmosphere ◽  
2018 ◽  
Vol 9 (3) ◽  
pp. 104 ◽  
Author(s):  
Huating Xu ◽  
Zhiyong Wu ◽  
Lifeng Luo ◽  
Hai He
Keyword(s):  
High Resolution ◽  
Multiscale Model ◽  
Global Environmental ◽  
Medium Range ◽  
Global Environmental Multiscale

scholarly journals Validation of the Global Environmental Multiscale Model (GEM) for Iran

2021 ◽  
Author(s):  
Mohammad Mohammadlou ◽  
Abdolreza Bahremand ◽  
Daniel Princz ◽  
Nicholas Kinar ◽  
Saman Razavi
Keyword(s):  
Climate Change ◽  
Data Assimilation ◽  
Arid Zone ◽  
Model Performance ◽  
Multiscale Model ◽  
Global Scale ◽  
Temperature And Precipitation ◽  
Global Environmental ◽  
Global Environmental Multiscale ◽  
Semi Arid

Abstract The Global Environmental Multiscale Model (GEM) is an integrated forecasting and data assimilation system developed by Environment and Climate Change Canada. The model is currently in operational use for data assimilation and forecasting at global 25 km to 15 km scales; regional 10 km scales over North America; and 2.5 km scales over Canada. To demonstrate the performance of the GEM model for forecasting applications, global forecast outputs of GEM at the 25 km scale were compared to temperature and precipitation datasets collected over an area of 1,648,000 km2 especially representative of the country of Iran on a daily temporal scale. Using the De Martonne method for climate classification and data from 177 meteorological stations, the country of Iran was classified into three zones: an arid zone with 87 stations; a semi-arid zone with 63 stations; and a humid zone with 27 stations. GEM model outputs were compared to observations in each of these demarcated zones. The results show good agreement between modelled and measured daily temperatures with Kling-Gupta efficiencies of 0.76, 0.71 and 0.78 in arid, semi-arid and humid regions respectively, and a moderate agreement between modelled and measured annual precipitation with 50.06%, 35.6% and 15.38% differences in arid, semi-arid and humid regions, respectively. The results also indicate that there is a significant systematic error between the elevation of the stations and the average elevation of corresponding GEM grid cells (13%). The results provide an evaluation of the model performance for Iran to be utilized for climate change applications in a regional context and can serve as a basis for the development of future high-resolution GEM model versions on a global scale.

scholarly journals Spatial Forecasts of Maximum Hail Size Using Prognostic Model Soundings and HAILCAST

2006 ◽  
Vol 21 (2) ◽  
pp. 206-219 ◽  
Author(s):  
Julian C. Brimelow ◽  
Gerhard W. Reuter ◽  
Ron Goodson ◽  
Terrence W. Krauss
Keyword(s):  
Prognostic Model ◽  
Multiscale Model ◽  
Maximum Diameter ◽  
Small Spatial Scale ◽  
Canadian Prairies ◽  
Global Environmental ◽  
Southern Alberta ◽  
Forecast Technique ◽  
Nwp Model ◽  
Global Environmental Multiscale

Abstract Forecasting the occurrence of hail and the maximum hail size is a challenging problem. This paper investigates the feasibility of producing maps of the forecast maximum hail size over the Canadian prairies using 12-h prognostic soundings from an operational NWP model as input for a numerical hail growth model. Specifically, the Global Environmental Multiscale model run by the Canadian Meteorological Center is used to provide the initial data for the HAILCAST model on a 0.5° × 0.5° grid. Maps depicting maximum hail size for the Canadian prairies are generated for 0000 UTC for each day from 1 June to 31 August 2000. The forecast hail-size maps are compared with radar-derived vertically integrated liquid data over southern Alberta and surface hail reports. Verification statistics suggest that the forecast technique is skillful at identifying the occurrence of a hail day versus no-hail day up to 12 h in advance. The technique is also skillful at predicting the main threat areas. The maximum diameter of the hailstones is generally forecast quite accurately when compared with surface observations. However, the technique displays limited skill when forecasting the distribution of hail on a small spatial scale.

OSIRIS observations of a tongue of NOx in the lower stratosphere at the Antarctic vortex edge: comparison with a high-resolution simulation from the Global Environmental Multiscale (GEM) model

2007 ◽  
Vol 85 (11) ◽  
pp. 1195-1207 ◽  
Author(s):  
C E Sioris ◽  
S Chabrillat ◽  
C A McLinden ◽  
C S Haley ◽  
Y J Rochon ◽  
...  
Keyword(s):  
Lower Stratosphere ◽  
Three Dimensional ◽  
Multiscale Model ◽  
Dimensional Structure ◽  
Small Scale ◽  
Breaking Wave ◽  
Austral Spring ◽  
Global Environmental ◽  
The Antarctic ◽  
Global Environmental Multiscale

Selected NOx profiles of the Antarctic lower stratosphere inferred from OSIRIS NO2 observations are presented from the austral spring of 2003. These observations show a tongue of NOx at 100 hPa, with a concentration typical of the middle stratosphere. Simulations with the Global Environmental Multiscale model show that this small-scale tongue of NOx-rich air descended into the lower stratosphere. The tongue was formed as a result of a Rossby wave breaking days earlier, transporting NOx from the pole, where larger concentrations had recently appeared, to the edge of the vortex. The three-dimensional structure of the breaking wave is illustrated in detail. PACS Nos.: 92.60.hf, 92.60.Xg, 93.30.Ca

scholarly journals Application of the Semi-Lagrangian Inherently Conserving and Efficient (SLICE) Transport Method to Divergent Flows on a C Grid

2008 ◽  
Vol 136 (12) ◽  
pp. 4850-4866 ◽  
Author(s):  
Ahmed Mahidjiba ◽  
Abdessamad Qaddouri ◽  
Jean Côté
Keyword(s):  
Total Mass ◽  
Small Scale ◽  
Local Conservation ◽  
Cartesian Coordinates ◽  
Passive Advection ◽  
Global Environmental ◽  
Global Environmental Multiscale ◽  
Transport Method

Abstract Local conservation with the Semi-Lagrangian Inherently Conserving and Efficient (SLICE) transport method with a new trajectory algorithm is studied. Validation results of 1D and 2D passive advection with this new algorithm, which converges twice as fast as the old one, on the Arakawa C grid of a model in Cartesian coordinates are obtained. The effects of numerically computed divergence and trajectories on the results were also investigated. Random small-scale errors due to the divergence, especially with realistic winds, can be observed. The total mass is conserved, however, and is not affected since the results show clearly that SLICE ensures a perfect local conservation. This work represents the first step toward implementation of SLICE in the operational Canadian Global Environmental Multiscale (GEM) model.

scholarly journals Assessment of a NEMO-based hydrodynamic modelling system for the Great Lakes

2012 ◽  
Vol 47 (3-4) ◽  
pp. 198-214 ◽  
Author(s):  
Frederic Dupont ◽  
Padala Chittibabu ◽  
Vincent Fortin ◽  
Yerubandi R. Rao ◽  
Youyu Lu
Keyword(s):  
Great Lakes ◽  
Thermal Structure ◽  
Three Dimensional ◽  
Multiscale Model ◽  
Ocean Model ◽  
Global Ocean ◽  
Central Basin ◽  
Surface Mixed Layer ◽  
Global Environmental ◽  
Modelling System

Environment Canada recently developed a coupled lake–atmosphere–hydrological modelling system for the Laurentian Great Lakes. This modelling system consists of the Canadian Regional Deterministic Prediction System (RDPS), which is based on the Global Environmental Multiscale model (GEM), the MESH (Modélisation Environnementale Surface et Hydrologie) surface and river routing model, and a hydrodynamic model based on the three-dimensional global ocean model Nucleus for European Modelling of the Ocean (NEMO). This paper describes the performance of the NEMO model in the Great Lakes. The model was run from 2004 to 2009 with atmospheric forcing from GEM and river forcing from the MESH modelling system for the Great Lakes region and compared with available observations in selected lakes. The NEMO model is able to produce observed variations of lake levels, ice concentrations, lake surface temperatures, surface currents and vertical thermal structure reasonably well in most of the Great Lakes. However, the model produced a diffused thermocline in the central basin of Lake Erie. The model predicted evaporation is relatively strong in the upper lakes. Preliminary results of the modelling system indicate that the model needs further improvements in atmospheric–lake exchange bulk formulae and surface mixed layer physics.

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