Natural Hazards and Earth System Science
www.nat-hazards-earth-syst-sci.net
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8
3
2008
10.5194/nhess-8-445-2008
http://www.nat-hazards-earth-syst-sci.net/8/445/2008/
http://www.nat-hazards-earth-syst-sci.net/8/445/2008/nhess-8-445-2008.html
http://www.nat-hazards-earth-syst-sci.net/8/445/2008/nhess-8-445-2008.pdf
445
460
2008-05-08
Introducing uncertainty of radar-rainfall estimates to the verification of mesoscale model precipitation forecasts
M. P. Mittermaier
marion.mittermaier@metoffice.gov.uk
Mesoscale Model Development and Diagnostics Group, Met Office, UK
A simple measure of the uncertainty associated with using radar-derived
rainfall estimates as "truth" has been introduced to the Numerical
Weather Prediction (NWP) verification process to assess the effect
on forecast skill and errors. Deterministic precipitation forecasts
from the mesoscale version of the UK Met Office Unified Model for a
two-day high-impact event and for a month were verified at the daily and
six-hourly time scale using a spatially-based intensity-scale method
and various traditional skill scores such as the Equitable Threat
Score (ETS) and log-odds ratio. Radar-rainfall accumulations from the
UK Nimrod radar-composite were used.
<br><br>
The results show that the inclusion of uncertainty has some effect,
shifting the forecast errors and skill. The study also allowed for the
comparison of results from the intensity-scale method and traditional
skill scores. It showed that the two methods complement each other, one
detailing the scale and rainfall accumulation thresholds where the errors occur,
the other showing how skillful the forecast is. It was also found that for the
six-hourly forecasts the error distributions remain similar with forecast
lead time but skill decreases. This highlights the difference between
forecast error and forecast skill, and that they are not necessarily the same.
Bowler, N.: Explicitly accounting for observation error in categorical verification of forecasts, Mon. Weather Rev., 134, 1600–1606, 2006.
Bowler, N., Pierce, C., and Seed, A.: STEPS:A probabilistic precipitation forecasting scheme which merges extrapolation nowcast with downscaled nwp, Q. J. Roy. Meteorol. Soc., 132, 2127–2155, 2006.
Briggs, W M. and Levine, R A.: Wavelets and field forecast verification, Mon. Weather Rev., 125, 1329–1341, 1997.
Casati, B. and Wilson, L.: A new spatial-scale decomposition of the Brier score: Application to the verification of lightning probability forecasts, Mon. Weather Rev., 135, 3052–3069, 2007.
Casati, B., Ross, G., and Stephenson, D.: A new intensity-scale approach for the verification of spatial precipitation forecasts, Meteorol. Appl., 11, 141–154, 2004.
Davies, T., Cullen, M., Malcolm, A., Mawson, M., Staniforth, A., White, A., and Wood, N.: A new dynamical core for the Met Office's global and regional modelling of the atmosphere, Q. J. Roy. Meteorol. Soc., 131, 1759–1782, 2005.
Germann, U., Berenguer, M., Sempere-Torres, D., and Salvade, G.: Ensemble radar precipitation estimation – a new topic on the radar horizon, Proceedings 4th European Conference on Radar in Meteorology and Hydrology, pages 559–562, 2006.
Göber, M., Wilson, C., Milton, S., and Stephenson, D.: Fairplay in the verification of operational quantitative precipitation forecasts, J. Hydrol., 288(1–2), 225–236, 2004.
Golding, B W.: NIMROD: a system for generating automated very short range forecast, Meteorol Appl, 5, 1–16, 1998.
Golding, B W.: Quantitative Precipitation Forecasting in the UK, J. Hydrol., 239, 286–305, 2000.
Harrison, D L., Driscoll, S J., and Kitchen, M.: Improving precipitation estimates from weather radar using quality control and correction techniques, Meteorol. Appl., 6, 135–144, 2000.
Jolliffe, I T. and Stephenson, D B. (Eds.): Forecast Verification: A Practitioner's Guide in Atmospheric Science, John Wiley and Sons, 2003.
Joss, J. and Waldvogel, A.: Precipitation measurements in hydrology, in: Radar in Meteorology: Battan Memorial and 40th Anniversary Radar Meteorology Conference, edited by: D Atlas, pages 577–606, AMS, 1990.
Macpherson, B.: Operational experience with assimilation of rainfall data in the Met Office mesoscale model, Meteor. Atmos. Phys., 76, 3–8, 2001.
Mittermaier, M.: Using an intensity-scale technique to assess the added benefit of high-resolution model precipitation forecasts, Atmos. Sci. Lett., 7(2), 35–42, 2006.
Mittermaier, M.: The potential impact of using persistence as a reference forecast on perceived forecast skill, Wea. Forecasting, in press, 2008.
Mittermaier, M., Hogan, R., and Illingworth, A.: Using mesoscale model winds for correcting wind-drift errors in radar estimates of surface rainfall, Q. J. Roy. Meteorol. Soc., 130, 2105–2125, 2004.
Roberts, N. and Lean, H.: Scale-selective verification of rainfall accumulations from high-resolution forecasts of convective events, Mon. Weather Rev., 136(1), 78–97, 2008.
Saetra, O., Hersbach, H., Bidlot, J.-R., and Richardson, D.: Effects of observation errors on the statistics for ensemble spread and reliability, Mon. Weather Rev., 132, 1487–1501, 2004.
Seed, A.: A dynamic and spatial scaling approach to advection forecasting, J. Appl. Meteor., 42(3), 381–388, 2003.
Turner, B., Zawadzki, I., and Germann, U.: Predictability of precipitation from continental radar images. Part III: Operational nowcasting implementation (MAPLE), J. Appl. Meteor., 43(2), 231–248, 2004.
Vasi\'c, S., Lin, C., Zawadzki, I., Bousquet, O., and Chaumont, D.: Evaluation of precipitation from Numerical Weather Prediction models and satellites using values retrieved from radars, Mon. Weather Rev., 135, 3750–3766, 2007.
Wilks, D.: Statistical Methods in Atmospheric Sciences, Academic Press, 2nd edition, 2006.
Zepeda-Arce, J. and Foufoula-Georgiou, E.: Space-time rainfall organization and its role in validating quantitative precipitation forecasts, J. Geophys. Res., 105, 10 129–10 146, 2000.