Evaluating Regional Atmospheric Water Vapour Estimates Derived from GPS and Short-Range Forecasts of the Canadian Global Environmental Multiscale Model in Southern Alberta

2008 ◽  
Vol 46 (4) ◽  
pp. 455-471 ◽  
Author(s):  
C. D. Smith ◽  
N. Nicholson ◽  
S. Skone ◽  
G. S. Strong
Keyword(s):  
Water Vapour ◽  
Short Range ◽  
Multiscale Model ◽  
Atmospheric Water ◽  
Atmospheric Water Vapour ◽  
Global Environmental ◽  
Southern Alberta ◽  
Global Environmental Multiscale ◽  
Range Forecasts

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.

Atmospheric water vapour processing

Waterlines ◽  
1993 ◽  
Vol 12 (2) ◽  
pp. 20-22 ◽  
Author(s):  
Roland Wahlgren
Keyword(s):  
Water Vapour ◽  
Atmospheric Water ◽  
Atmospheric Water Vapour

scholarly journals Radiative effects of changing atmospheric water vapour

Tellus B ◽  
1984 ◽  
Vol 36 (3) ◽  
pp. 149-162 ◽  
Author(s):  
G. Mark Doherty ◽  
Reginald E. Newell
Keyword(s):  
Water Vapour ◽  
Atmospheric Water ◽  
Radiative Effects ◽  
Atmospheric Water Vapour

scholarly journals MAX-DOAS observations of the total atmospheric water vapour column and comparison with independent observations

2013 ◽  
Vol 6 (1) ◽  
pp. 131-149 ◽  
Author(s):  
T. Wagner ◽  
M. O. Andreae ◽  
S. Beirle ◽  
S. Dörner ◽  
K. Mies ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Water Vapour ◽  
Satellite Observations ◽  
Shielding Effect ◽  
Optical Absorption Spectroscopy ◽  
Atmospheric Water ◽  
Near Surface ◽  
Atmospheric Water Vapour ◽  
Independent Observations ◽  
Good Agreement

Abstract. We developed an algorithm for the retrieval of the atmospheric water vapour column from Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) observations in the yellow and red spectral range. The retrieval is based on the so-called geometric approximation and does not depend on explicit a priori information for individual observations, extensive radiative transfer simulations, or the construction of large look-up tables. Disturbances of the radiative transfer due to aerosols and clouds are simply corrected using the simultaneously measured absorptions of the oxygen dimer, O4. We applied our algorithm to MAX-DOAS observations made at the Max Planck Institute for Chemistry in Mainz, Germany, from March to August 2011, and compared the results to independent observations. Good agreement with Aerosol Robotic Network (AERONET) and European Centre for Medium-Range Weather Forecasting (ECMWF) H2O vertical column densities (VCDs) is found, while the agreement with satellite observations is less good, most probably caused by the shielding effect of clouds for the satellite observations. Good agreement is also found with near-surface in situ observations, and it was possible to derive average daily H2O scale heights (between 1.5 km and 3 km). MAX-DOAS measurements use cheap and simple instrumentation and can be run automatically. One important advantage of our algorithm is that the H2O VCD can be retrieved even under cloudy conditions (except clouds with very high optical thickness).

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