ASSIMILATION OF RADAR RAINFALL DATA. Anthony Illingworth, Univ of Reading, 27 th meeting of Interagency Committee Met Office, Exeter 7 April 2004.

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ASSIMILATION OF RADAR RAINFALL DATA. Anthony Illingworth, Univ of Reading, 27 th meeting of Interagency Committee Met Office, Exeter 7 April 2004

RADAR IS NOT FULLY EXPLOITED IN FORECASTS. At present use ‘latent heat nudging’ – change the moisture in the column so latent heat release in the model is closer to what it should be for the observed rainfall. But how do you do this if the forecast model analysis has some rain but radar observations show it is in the wrong place. Need to ‘increment ’ analysis to agree better with the observations. Must also change dynamics so the model keeps the rain in the ‘new’ position as the model steps forward in time.

HYPOTHESIS: TO INCREASE THE RAIN IN THE MODEL INCREASE THE MOISTURE CONVERGENCE. 1. Stage one: check that an increment in moisture convergence produces an increment in rainfall. 2. Before using radar data check the model. Compare the analysis at To with the forecast for To – if the analysis has an increment of rain – is this related to an increment in moisture flux convergence? Does it also have an increment in moisture flux convergence? 3. Can we force an increment in moisture flux convergence via the Richardson equation.

CONCLUSIONS from one year’s analysis of the model: 1. SO FAR: Comparing analysis at To with forecast at To from an earlier time: Increment in precipation is proportional to the increment in moisture convergence Increment in precipation is proportional to increment in Richardson. 2 NEXT STAGE. Use the radar observations – if they do not agree with model analysis – then to increment rainfall in model: Do this by changing the dynamics by incrementing the Richardson equation term.