1 / 17

Marion Mittermaier and Clive Wilson

The use of an intensity-scale technique for assessing operational mesoscale precipitation forecasts. Marion Mittermaier and Clive Wilson. Outline. An intensity-scale technique (Casati et al. 2004) Model output and data description

cmixon
Download Presentation

Marion Mittermaier and Clive Wilson

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. The use of an intensity-scale technique for assessing operational mesoscale precipitation forecasts Marion Mittermaier and Clive Wilson

  2. Outline • An intensity-scale technique (Casati et al. 2004) • Model output and data description • Value added by higher resolution for a severe flooding event (Boscastle, August 2004) • A modified sign-test statistic for highlighting persistent/prevalent errors at the monthly time scale. • Radar vs gauge as “truth” • Concluding remarks

  3. 1. An intensity-scale technique ….. best illustrated with an example …. (from Casati, 2004)

  4. Radar Model forecast Radar > 1 mm Forecast > 1 mm Binary error image from Casati (2004)

  5. MSE skill score 1 0 -1 -2 -3 -4 spatial scale (km) Axes multiples of 2 threshold (mm/h) [from Casati (2004)]

  6. 2. Model output and data description • Mesoscale version of the Unified Model (MES) runs 4 times a day at ~12 km over the UK (for Unified Model description see Davies et al., QJRMS, 2005) • Newly implemented 4-km model now runs twice a day over the UK (see Bornemann et al, this conference) • Radar-rainfall accumulations available on a 5 km x 5 km national grid • ~2700 rain gauges have been used to produce a daily gridded rainfall product also on a 5 km x 5 km grid

  7. 3. Boscastle: the benefit of higher resolution? On 16.08.2004 over 180 mm were recorded by one gauge in a 5-hr period during a highly localised flooding event. How does one assess added benefit? • Output from the MES and 4 km model isn’t directly comparable • Basis of comparison should ideally be the same. Solution: Average the 4 km model output to the 12 km grid and compare against the same 12-km averaged radar rainfall product. …. consider 6-hr rainfall between 12-18Z from the 00Z run …

  8. 4 km 00Z 6 hr rainfall MES 00Z 6 hr rainfall 4 km 00Z avg 6 hr rainfall Max radar = 44 mm 46 mm 68 mm 7 mm 12-18Z 12-18Z 12-18Z 16Dx 16Dx Error scale (km) 2Dx 2Dx 1 mm 64 mm Rainfall threshold (mm)

  9. 4. A modified sign-test statistic • Distribution-free test as normality of errors can’t be assumed. • B = number of +ve skill scores for a given scale and intensity during a given time interval, e.g. 1 month. • Hypotheses: • H0 : SS >= 0 (implicit positive and skillful) • H1 : SS < 0 (less skill than a random forecast) • H0is rejected if b <= bn,awhere B ~ bi(n, 0.5) for small samples (n < 40), a = 0.025 • The value of (n – B) / n is shaded in intensity-phase space for each scale and intensity where H0 is rejected.

  10. Added benefit: comparison of prevalent errors at the monthly time scale May 2005 MES vs radar May 2005 4 km avg vs radar 32 mm X 48 km X X X X X X X X X X X X X X X X X X X X X • (sub-)“grid” scale errors are more prevalent at trace rainfall totals for the 4 km model • prevalent errors at twice and four times the MES grid length for thresholds > 16 mm are less for the 4 km model (captures large totals better)

  11. 5. Radar vs gauge as “truth” August 2004 MES vs radar August 2004 MES vs gauge X X X X X X X X X X X X X X X X X X X X X X • Slight shifts in the distribution of prevalent errors at the monthly time scale • Overall pattern very similar • Radar-rainfall fields preferred as they are truly spatial with a greater observation frequency

  12. 6. Concluding remarks • The 4 km model contains much more detail (even when averaged to 12 km) • Detail does not necessarily equal accuracy! Raw model output needs to be averaged • Scale-intensity analyses show that the need for averaging is (almost) independent of grid length (there is always grid noise, regardless) • The difference between error analyses produced using radar (true spatial) and gauge (point-interpolated) fields is minimal. Recommend that radar fields are used also because of the high observation frequency.

  13. Questions?

  14. MES 12Z 6 hr rainfall Radar 12Z 6 hr rainfall 4 km 12Z avg 6 hr rainfall 12-18Z 12-18Z 12-18Z 19 June 2005 Flash flooding caused by thunderstorms over North Yorkshire Error scale (km) Rainfall threshold (mm)

  15. Haar Wavelet filter deviation from mean value mean value + + mean value on all the domain Casati et al., 2004, Met Apps

  16. An intensity-scale technique using wavelets Haar mother wavelety 1 -1 0 1 2 4 n n+1 • Wavelets are locally defined real functions characterised by a location and a spatial scale. • Any real function can be expressed as a linear combination of wavelets, i.e. as a sum of components with different spatial scales. • Wavelet transforms deal with discontinuities better than Fourier transforms do

  17. wavelet decomposition of the binary error Scale 1 0 -1 from Casati (2004)

More Related