Thursday, 26 January 2017: 3:30 PM
602 (Washington State Convention Center )
The leading modes of subseasonal atmospheric circulation variability play an important role in determining subseasonal surface meteorological variations during warm season; they have been crucial in the development of a number of recent short-term warm-season drought extremes over North America. These leading modes are often present in the form of stationary Rossby waves guided by mean jet streams. Many current models, including the NASA GEOS-5 GCM, are, however, deficient by simulating weak and disoriented NH jet streams during warm season, especially over the north Pacific. This talk presents evidence that such model bias can adversely affect the model representation of stationary Rossby waves and their effects over North America, thereby strongly limiting the model prediction skill of subseasonal drought development over North America. Here, by applying 6-hourly climatological analysis increments from MERRA-2 to model basic state variables within the free-running GEOS-5 AGCM, we have successfully (though artificially) removed much of the GEOS-5 AGCM mean jet bias during warm season. We then performed two comprehensive hindcast experiments for warm seasons, using the standard and the mean jet bias corrected GEOS-5 AGCM, respectively. The comparison between the two AGCM hindcast experiments shows that the corrected mean jet streams improve considerably subseasonal hindcast skill for North American droughts that developed as a result of stationary Rossby waves. This supports that correct simulation of mean jet streams (location, shape, magnitude) in a GCM is necessary for a skillful prediction of stationary Rossby waves and their effect on subseasonal drought development over North America. In the above context, we will also discuss our assessment of predictability of stationary Rossby waves and the impact of model mean jet bias on the assessment.
![](images/flag.png)
![](images/blue_ribbon.png)