J4.3A Identifying a Soil Moisture-Rainfall Feedback in the 2016 New York Summer Drought

Tuesday, 8 January 2019: 3:30 PM
North 127ABC (Phoenix Convention Center - West and North Buildings)
Marc J Alessi, Cornell Univ., Ithaca, NY; and A. T. DeGaetano and T. Ault

The Advanced Weather Research and Forecasting (WRF) model is utilized to identify the existence of a soil moisture-rainfall feedback during the 2016 New York summer drought. First, combinations of physics parameterizations are tested to identify ideal combinations for predicting precipitation amounts in the Northeastern U.S. during the summer. A weighted ensemble is developed based on how well certain combinations hindcast precipitation during previous summers. This ensemble is then used to simulate total precipitation during the summer of 2016 with three different soil moisture initializations: a control run with unaltered soil moisture, a run with increased, near capacity, soil moisture, and a run with decreased soil moisture.

Overall, a positive soil moisture-rainfall feedback is identified. Total rainfall increased across most of the Northeast U.S. when comparing the dry soil moisture scenario to the wet soil moisture scenario. When comparing the control soil moisture scenario to the wet soil moisture scenario, neither a positive nor negative feedback is identified, since the wet and control scenarios had similar soil moisture values on the regional scale. However, a distinct positive soil moisture-rainfall feedback occurs over the Upstate New York drought region when comparing rainfall from the control to dry soil moisture scenarios. Had there been drier soil moisture values heading into the summer months, even less rain could have occurred in this area.

- Indicates paper has been withdrawn from meeting
- Indicates an Award Winner