scholarly journals Significance of changes in medium-range forecast scores

2016 ◽  
Vol 68 (1) ◽  
pp. 30229 ◽  
Author(s):  
Alan J. Geer
1994 ◽  
Vol 9 (1) ◽  
pp. 3-20 ◽  
Author(s):  
Mary A. Bedrick ◽  
Anthony J. Cristaldi ◽  
Stephen J. Colucci ◽  
Daniel S. Wilks

2007 ◽  
Vol 135 (4) ◽  
pp. 1195-1207 ◽  
Author(s):  
Timothy F. Hogan ◽  
Randal L. Pauley

Abstract The influence of convective momentum transport (CMT) on tropical cyclone (TC) track forecasts is examined in the Navy Operational Global Atmospheric Prediction System (NOGAPS) with the Emanuel cumulus parameterization. Data assimilation and medium-range forecast experiments show that for 35 tropical cyclones during August and September 2004 the inclusion of CMT in the cumulus parameterization significantly improves the TC track forecasts. The tests show that the track forecasts are very sensitive to the magnitude of the Emanuel parameterization’s convective momentum transport parameter, which controls the CMT tendency returned by the parameterization. While the overall effect of this formulation of CMT in NOGAPS data assimilation/medium-range forecasts results in the surface pressure of tropical cyclones being less intense (and more consistent with the analysis), the parameterization is not equivalent to a simple diffusion of winds in the presence of convection. This is demonstrated by two data assimilation/medium-range forecast tests in which a vertical diffusion algorithm replaces the CMT. Two additional data assimilation/medium-range forecast experiments were conducted to test whether the skill increase primarily comes from the CMT in the immediate vicinity of the tropical cyclones. The results show that the inclusion of the CMT calculation in the vicinity of the TC makes the largest contribution to the increase in forecast skill, but the general contribution of CMT away from the TC also plays an important role.


1980 ◽  
Vol 108 (11) ◽  
pp. 1736-1773 ◽  
Author(s):  
A. Hollingsworth ◽  
K. Arpe ◽  
M. Tiedtke ◽  
M. Capaldo ◽  
H. Savijärvi

2005 ◽  
Vol 6 (2) ◽  
pp. 101-114 ◽  
Author(s):  
Kevin Werner ◽  
David Brandon ◽  
Martyn Clark ◽  
Subhrendu Gangopadhyay

Abstract This study introduces medium-range meteorological ensemble inputs of temperature and precipitation into the Ensemble Streamflow Prediction component of the National Weather Service River Forecast System (NWSRFS). The Climate Diagnostics Center (CDC) produced a reforecast archive of model forecast runs from a dynamically frozen version of the Medium-Range Forecast (MRF) model. This archive was used to derive statistical relationships between MRF variables and historical basin-average precipitation and temperatures. The latter are used to feed the Ensemble Streamflow Prediction (ESP) component of the NWSRFS. Two sets of ESP reforecasts were produced: A control run based on historically observed temperature and precipitation and an experimental run based on MRF-derived temperature and precipitation. This study found the MRF reforecasts to be generally superior to the control reforecasts, although there were situations when the downscaled MRF output actually degraded the forecast. Forecast improvements were most pronounced during the rising limb of the hydrograph—at this time accurate temperature forecasts improve predictions of the rate of snowmelt. Further improvements in streamflow forecasts at short forecast lead times may be possible by incorporating output from high-resolution regional atmospheric models into the NWSRFS.


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