Analysis of angular momentum loss in weather prediction models

Wednesday, 20 April 2016: 3:15 PM
Miramar 1 & 2 (The Condado Hilton Plaza)
Ernesto W. Findlay, SUNY, Albany, NY
Manuscript (947.0 kB)

Analysis of angular momentum loss in weather prediction models Ernesto Findlay Department of Environmental and Atmospheric Science, University at Albany, Albany, New York The angular momentum (AM) with respect to the earth's axis of rotation is one of the fundamental parameters used to characterize the general circulation of the atmosphere and the climate (Peioxoto and Oort 1992). Atmospheric angular momentum (AAM) provides a convenient framework to track subseasonal weather and climate phenomena. Loss of AAM in the medium-range forecasts in the National Centers for Environmental Prediction (NCEP) reanalysis model was found by Huang and Sardeshmukh (1999). They speculated that most of the loss was due to the parameterization of gravity wave drag (GWD) in the model. However, impacts of corrected drag were often opposite expectations in regions of the drag, suggesting other sources of error. The hypothesis of this project is that global loss in AAM in models is tied to local loss in AM as a function of forecast time, and that this loss is mainly due to gravity wave drag combined with locally different terms in the budget that also yield large errors. AM Analysis will be performed on reanalysis data at each grid point to assess the geographical distribution of AM. Since reanalysis budgets do not conserve AM, results will be compared with the residual (i.e., the difference between the model AAM time tendency and the sum of the budget terms). This study is likely to reveal the dynamical pathways through which local and global atmospheric angular momentum evolve with time. It will also determine how skillful models are in predicting subseasonal events as expressed in angular momentum. Some preliminary results have shown, for example, that during April-June 2015, atmospheric angular momentum anomalies were consistently negative, which usually corresponds to a negative El Nino Southern Oscillation (ENSO) state, but results suggest that most of the negative signal originated from the stratosphere (as determined by the Quasi-biennial oscillation).
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