Kong Rong, Wang Jianjie, Liang Feng, et al. Applying scale decomposition method to verification of quantitative precipitation nowcasts. J Appl Meteor Sci, 2010, 21(5): 535-544.
Citation: Kong Rong, Wang Jianjie, Liang Feng, et al. Applying scale decomposition method to verification of quantitative precipitation nowcasts. J Appl Meteor Sci, 2010, 21(5): 535-544.

Applying Scale Decomposition Method to Verification of Quantitative Precipitation Nowcasts

  • Received Date: 2009-07-13
  • Rev Recd Date: 2010-07-17
  • Publish Date: 2010-10-31
  • Verification of quantitative precipitation forecast has always been a challenge due to the high discontinuity of rainfall in spatial and temporal scales. Conventional methods (TS and MSE score, etc.) cannot meet the need for verification of high resolution (1—2 km) forecasts. In recent years, several new spatial verification approaches which can give more information about the complex spatial structure of forecast field have been developed, such as the intensity-scale verification method, the feather based (or object-oriented) verification method, neighborhood (or fuzzy) verification method and field deformation approaches etc. The attempt to use the intensity scale technique is introduced by Casati et al. to assess radar based 1 hour quantitative precipitation forecasts for 4 different nowcasting systems (BJANC, GRAPES SWIFT, STEPS, and CARDS) which attended the World Weather Research Program for the Beijing 2008 Olympic Games (WWRP B08FDP). The intensity-scale verification approach accounts for the spatial structure of the forecast field and allows the skill score to be diagnosed as a function of the spatial scale of the forecast error and intensity of the precipitation events. Different precipitation types (convective, stratiform and mixed type) during B08FDP demo period are selected to get representative results, it shows that these nowcasting systems exhibit forecasting skills only when the precipitation system is above 32 km spatial scale and last longer than 1 hour despite the using of most advanced systems in the world with the high resolution of 1 to 2 km. For spatial scale lower than that, the forecasting ability is very limited, which indicates that product performance characterized at different spatial scale should be considered in the applying of nowcasting products. When analyzing the forecasting errors with different spatial and temporal scales, it's found that more than 60% and more than 85% of the forecasting error come from spatial scales smaller than 8 km and time scales smaller than 1 hour respectively. Improvements in smaller scales precipitation forecasts are important. Most nowcasting systems explore the linear extrapolation technique to make 0 to 2 hours nowcasts, yet the valid extrapolation time is very limited, especially for smaller scale (less than 1 hour) convective systems, which is mainly caused by the nonlinear development of the convections. Therefore, more information about the circulation which has close relation to the movement and development of the storm should be considered. So far, the most popular way is to blend the radar based extrapolation with the dense observations and numerical model based potential forecast.
  • Fig. 1  Schematic diagram of one dimensional Harr wavelet transform

    Fig. 2  Schematic figure of verification region (512 km×512 km cover Beijing area)

    Fig. 3  1-hour precipitation energy (Wml2) ratio of different spatial scale (a) and temporal scale (b) to the whole scales (from analysis fields) for 6 cases during B08FDP demo period

    Fig. 4  Skill score distribution of 1-hour precipitation forecast (average of 4 systems) with precipitation spatial scale and intensity for 4 cases (taking the process average for every case) in 2008 (a) 09:00 14 July—09:00 15 July, (b) 19:00 8 August—12:00 9 August, (c) 11:00—22:00 14 August, (d) 12:00 21 August—07:00 22 August

    Fig. 5  Error contribution of 1-hour precipitation forecast (average of 4 systems) on each scale to that of the sum of whole scales for 4 casesin 2008 (taking the process average for every case) (a) 09:00 14 July—09:00 15 July, (b) 19:00 8 August—12:00 9 August, (c) 11:00—22:00 14 August, (d) 12:00 21 August—07:00 22 August

    Fig. 6  Skill score distribution of 1-hour precipitation forecast with precipitation temporal scale and intensity for 4 casesin 2008 (a) 09:00 14 July—09:00 15 July, (b) 19:00 8 August—12:00 9 August, (c) 11:00—22:00 14 August, (d) 12:00 21 August—07:00 22 August

    Fig. 7  Error contribution of 1-hour precipitation forecast (average of 4 systems) on each temporal scale to that of the sum of whole scale for 4 cases in 2008 (a) 09:00 14July— 09:00 15 July, (b) 19:00 8 August—12:00 9 August, (c) 11:00—22:00 14 August, (d) 12:00 21 August—07:00 22 August

    Table  1  Probability distribution of event A

    Table  2  Posterior probability distribution of event B

    Table  3  List of main rainfall processes in 2008

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    • Received : 2009-07-13
    • Accepted : 2010-07-17
    • Published : 2010-10-31

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