Evaluation of Precipitation from Weather Prediction Models, Satellites and Radars Charles Lin Department of Atmospheric and Oceanic Sciences McGill University, Montreal, Quebec, Canada

Collaborators Slavko Vasić Isztar Zawadzki Barry Turner

Objective To characterize and inter-compare precipitation retrieved from models, radars and satellites using spectral analysis and frequency distribution

Methodology Spectral domain –Scale decomposition using Fourier modes and wavelets Frequency domain –Frequency distribution

Domain of analysis –Central and eastern US: 2,160 km × 2,160 km Weather prediction models –Canadian GEM/HIMAP (10 km resolution) –US ETA, NCEP (12 km) Radar data –US composite (5 km resolution) Satellite –GOES (5 km resolution)

1-hour accumulated precipitation 21 days in 2003, days with satellite data 2003 September 12, 13, 18, 27 October 14, 17, 25, 26, May 21, 22, 30, 31 June 11, 24 July 3, 4, 5, 6 August 19, 20

Scale decomposition analysis

Accumulated precipitation for 11h-12h - October 26, ,160 km

Scale decomposition: Fourier and wavelet

Spectral amplitudes at different wavenumbers (k H = 2 n )

Lag correlation analysis, 1-h accumulation (R = radar; G = GEM)

Frequency Distribution Analysis 21 days of 24 hourly accumulated precipitation → over 500 hourly samples Domain of 2,160 km × 2,160 km at 12 km resolution → Total of 180 × 180 = 32,400 pixels Bin hourly precipitation of each pixel, with bin width δ Count frequency of precipitation for each bin → histogram

Frequency distribution: Near power law dependence Radar: ±1 standard deviation

Quartile analysis (3 days) Total frequency

Compare skill of model forecasts and radar nowcasts

Categorical skill scores for 24-h GEM/HIMAP and ETA model forecasts POD: Probability of detection FAR: False alarm rate CSI: Critical success index

Skill of Precipitation Forecasts from NWP Models and Radar Nowcasts Golding (1998), Austin et al. (1987), Wilson et al. (1998) Theoretical limit of predictability Nowcasting methods Numerical weather prediction models

Experimental Design Five 9-hour radar nowcasts: 0300, 0600, 0900, 1200 & 1500 UTC 24-hour GEM-HIMAP & ETA forecasts Time [h]

21-day averaged skill scores (1-hour accumulated precipitation, ) - Threshold: 0.1 mm/h - Lin, Vasic, Kilambi, Turner and Zawadzki (2005)

Summary Scale decomposition and frequency analysis of model and radar precipitation Enhanced falloff of power of model precipitation at high wavenumbers compared to radar Significant loss in power of models at scales ≈ 10 Δx Approximate power law dependence for frequency distribution Skill of 24-h model forecast is relatively constant, and is better than radar nowcasts after a lead time of about 6-8 hours

Thank you!