1. © 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)

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

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)

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)

5. 5 Impact to total energy at targeting time (T+0) -30 -15 -5 5 15 30 m 2 s -2 degradationimprovement

6. 6 Impact to total energy at T+12 -30 -15 -5 5 15 30 m 2 s -2 degradationimprovement

7. 7 Impact to total energy at T+24 -30 -15 -5 5 15 30 m 2 s -2 degradation improvement

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

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)

10. 10 Forecast impact resulting from targeted sonde data Errors: ops ½ ¼ 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

11. Impact of dropsonde data on Greenland coast ORIGINAL DATASETMODIFIED DATASET (Replaced sondes on Greenland coast with sondes in Denmark Strait)

12. Forecast Improvement without assimilating sondes on Greenland coast Dashed line = ORIGINAL DATASET Dotted line = MODIFIED DATASET (no sondes near Greenland)

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

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%

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)

16. 16 Dropsonde Observation Error Profiles: temperature Calculated values for GFDex sonde data Operational values (solid line)

17. 17 Forecast Impact from GFDex targeted data Perturbation total energy metric: At 850, 500, 250 hPa

18. 18 A comparison of dropsonde and model data Model adjustment to sonde data Difference between sonde and model data