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University of Reading 2008www.reading.ac.ukTTISS September 2009 Impact of targeted dropsondes on European forecasts Emma Irvine Sue Gray and John Methven (Reading University) Ian Renfrew (UEA), Richard Swinbank (Met Office) Slide 2 GFDex (Renfrew et al 2008, BAMS): Duration: 19/02-12/03 2007 Base: Keflavik, Iceland Aircraft: BAE-146 (FAAM) Targeted Observations: 4 flights 7 -11 dropsondes per flight Dropsondes sent to GTS and assimilated into operational 1200 UTC forecasts Targeting During GFDex Slide 3 3 Analysing the impact of targeted observations Run hindcasts for field campaign period (Feb-Mar 07) Model: Met Office Unified Model, 24km grid 4D-VAR data assimilation scheme, 48km grid North-Atlantic European domain Two sets of hindcasts: Control routine obs. only Targeted routine obs. + targeted obs. (dropsondes) Focus on one case here: 01 March 2007. For more details see Irvine et al. 2009 QJRMS (in press) Slide 4 4 TESV sensitive area prediction and flight track 9 targeted sondes (red crosses) released along flight track 8 non-targeted sondes (blue triangles) also released Targeted hindcast assimilated only targeted sonde data (all sonde data was assimilated into operational 12Z forecasts) Slide 5 5 Impact to total energy at targeting time (T+0) -30 -15 -5 5 15 30 m 2 s -2 degradationimprovement Slide 6 6 Impact to total energy at T+12 -30 -15 -5 5 15 30 m 2 s -2 degradationimprovement Slide 7 7 Impact to total energy at T+24 -30 -15 -5 5 15 30 m 2 s -2 degradation improvement Slide 8 8 Forecast impact due to targeted sondes is mixed The maximum forecast improvement from assimilating targeted observations is 7% after 18 hours, and maximum degradation is 5% after 36 hours Slide 9 9 Method of increasing the impact of targeted observations 1.Reduce the dropsonde observation errors 2.Increase the density of the sonde observations Operational sonde observation errors in wind (solid line) Slide 10 10 Forecast impact resulting from targeted sonde data Errors: ops All sondes (solid line), targeted sondes only (dashed line) The maximum forecast improvement from is now 17% after 18 hours, and maximum degradation is 7% after 36 hours Slide 11 Impact of dropsonde data on Greenland coast ORIGINAL DATASETMODIFIED DATASET (Replaced sondes on Greenland coast with sondes in Denmark Strait) Slide 12 Forecast Improvement without assimilating sondes on Greenland coast Dashed line = ORIGINAL DATASET Dotted line = MODIFIED DATASET (no sondes near Greenland) Slide 13 Why do the dropsondes on the Greenland coast degrade the forecast? Is this due to the spreading of information up the steep orography? 13 Slide 14 14 Conclusions Targeted sondes released into a TESV sensitive region caused a maximum forecast improvement of 7% after 18- hours Reducing the dropsonde observation errors increased the maximum improvement by ~3% Two observations near the coast of Greenland degraded the forecast by spreading information up the steeply sloping orography; using sondes released further into the Denmark Strait increased the impact to 17% Slide 15 Potential solution: Reject sonde data below 850hPa? 5% increase in peak forecast improvement when the sondes near Greenland have data below 850hPa rejected (green line) Slide 16 16 Dropsonde Observation Error Profiles: temperature Calculated values for GFDex sonde data Operational values (solid line) Slide 17 17 Forecast Impact from GFDex targeted data Perturbation total energy metric: At 850, 500, 250 hPa Slide 18 18 A comparison of dropsonde and model data Model adjustment to sonde data Difference between sonde and model data