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NH Extra-tropical Cyclone Activity in the 20 th Century Reanalysis Data - preliminary results X. L. Wang 1 , V. R. Swail 1 , Y. Feng 1 G.P. Compo 2,3 , J.S. Whitaker 3 , P.D. Sardeshmukh 2,3 , R. J. Allan 4.
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NH Extra-tropical Cyclone Activity in the 20th Century Reanalysis Data- preliminary resultsX. L. Wang1, V. R. Swail1, Y. Feng1G.P. Compo2,3, J.S. Whitaker3, P.D. Sardeshmukh2,3, R. J. Allan4 1. Climate Research Division, S&T Branch, Environment Canada, Toronto, Canada2. University of Colorado, CIRES, Climate Diagnostic Center, Boulder, CO, USA 3. NOAA Earth System Research Laboratory, Physical Sciences Division, Boulder, CO, USA4. Hadley Center, Met Office, Exeter, UK 2nd ACRE Workshop, Queensland, Australia, 1-3 April 2009
Outline • Introduction - Datasets & algorithm • 1949-1958 (overlapping period) climate of cyclone activity of 20th Century Reanalysis (C20r, ensemble mean) versus that of NCEP-NCAR Reanalysis 1 (NCEP1) • Series of regional average cyclone counts and intensity for 1908-2008 (C20r, NCEP1, NCEP2) • Summary and next step
Equal Area SSM/I Earth C20r: 2.0x2.0 lat-long grid NCEP: 2.5x2.5 lat-long grid 250x250 km EASE-grid as required by the cyclone detection/tracking algorithm used Datasets: Global 6-hourly MSLP fields • Ensemble means of C20r v1 for 1908-1958 • NCEP/NCAR Reanalysis 1 (NCEP1) for 1948-2008 • NCEP-DOE Reanalysis 2 (NCEP2) for 1979-2007
1. Cyclone detection: identify the point or adjacent points of the min. MSLP over a 7x7 array of points. at least 1 hPa lower than surrounding gridpoint values Cyclone center @ the point of the largest local Laplacian of pressure Cyclone detection/tracking algorithm: (Courtesy of Mark Serreze; Serreze et al. 1997) 2. Cyclone tracking: based on a “nearest neighbor” analysis of the positions of cyclones between two consecutive “observing” times. Results not analyzed at this preliminary stage MSLP is an extrapolated field Exclude areas of elev. > 1000 m (“black out”)
Terminology Cyclone: A single low pressure center at a specific time & site Cyclone-track: A cyclone and its trajectory during its lifetime (should consist of several cyclones, one at each “observing” time) Strong-cyclones: Intensity ≥ 15 units Weak-cyclones: Intensity < 15 units All cyclones Not analyzed at this preliminary stage Cyclone intensity = Local Laplacian of pressure (Unit: 10-5 hPa/km2) For each season: Cyclone Activity Index = Total_Count * Mean_Intensity
Differences in 1949-1958 mean (NCEP1 minus C20r) Black areas: elev. > 1000 m Seasonal count of all cyclones Seasonal mean intensity of all cyclones No extensive areas of significant differences JFM: Yellow-Red: C20r < NCEP1 Cyan-Blue: C20r > NCEP1 C20r - weaker Hatching: at least 5% significance ensemble mean AMJ:
Black areas: elev. > 1000 m Differences in 1949-1958 mean (NCEP1 minus C20r) Seasonal count of all cyclones Seasonal mean intensity of all cyclones No extensive areas of significant differences JAS: Yellow-Red: C20r < NCEP1 Cyan-Blue: C20r > NCEP1 Hatching: at least 5% significance OND:
Time series of regional average cyclone counts/intensity for each season during 1908-2008
JFM counts JFM mean intensity 30N 35N 50N AMJ counts AMJ mean intensity 55N 75N 40N 50N JAS counts JAS mean intensity Intensity might be biased low due to the use of ensemble mean! OND counts OND mean intensity Larger diff. between NCEP1-2 C20r matches NCEP2 better All cyclones (strong + weak) Northern Europe No trend in frequency of winter cyclone Discontinuity? Pretty good match & homogeneous
JFM counts JFM mean intensity 30N 35N 50N AMJ counts 55N 75N AMJ mean intensity 40N 50N JAS counts JAS mean intensity OND counts OND mean intensity Strong cyclones Increasing frequency of strong cyclones? Mean intensity series seem more homogeneous than count series Northern Europe Fewer cyclones in ensemble mean data can reach the strong category Homogeneity of count series is expected to be improved
JFM counts JFM mean intensity AMJ counts AMJ mean intensity 50N 40N 75N 55N JAS counts JAS mean intensity 50N 30N 35N OND mean intensity OND counts All cyclones High lat. North Atlantic Pretty good match & homogeneous Needs to check the first 2 decades (much fewer data available?)
JFM counts Increasing frequency of strong cyclones? JFM mean intensity AMJ counts 50N 40N 75N AMJ mean intensity 55N JAS counts 50N 30N 35N JAS mean intensity OND counts Increasing frequency of strong cyclones? OND mean intensity Strong cyclones High lat. North Atlantic More homogeneous intensity series than count series in the warm seasons Pretty good match & homogeneous Homogeneity of count series is expected to be improved by analyzing individual members
JFM counts JFM mean intensity AMJ counts AMJ mean intensity 50N 40N 75N 55N JAS counts JAS mean intensity 50N 30N 35N OND counts OND mean intensity All cyclones Mid-lat. North Atlantic Pretty good match & homogeneous Homogeneity of intensity series could be improved by analyzing individual members
JFM counts JFM mean intensity AMJ counts 50N 40N 75N AMJ mean intensity 55N JAS counts 50N 30N 35N JAS mean intensity OND counts OND mean intensity Strong cyclones Mid-lat. North Atlantic good match & homogeneous
JFM mean intensity JFM counts AMJ mean intensity AMJ counts 40N 35N 55N JAS mean intensity JAS counts 50N 75N 50N 30N OND mean intensity OND counts All cyclones Homogeneous but biased low Homogeneous but biased low Central North America Homogeneous but biased low Homogeneous but biased low Homogeneous but biased low Homogeneous but biased low ensemble mean low biases in count & intensity Homogeneous but biased low Homogeneous but biased low
JFM counts JFM mean intensity AMJ counts AMJ mean intensity 40N 55N 35N 50N 75N JAS counts JAS mean intensity 50N 30N OND counts OND mean intensity All cyclones Canadian Arctic region (data sparse) Temporal homogeneity is questionable, especially in the early decades Not expected to disappear in… Needs verification with long-term stn data
JFM counts JFM mean intensity AMJ counts AMJ mean intensity 35N 30N 50N 55N JAS counts JAS mean intensity 75N 40N 50N OND counts OND mean intensity All cyclones Mid-lat. North Pacific Good match & homogeneous except …
JFM counts JFM mean intensity AMJ counts AMJ mean intensity 35N 30N 50N 55N 75N JAS counts JAS mean intensity 40N 50N OND counts OND mean intensity All cyclones High-lat. North Pacific Need to check temporal homogeneity, especially in the first few decades much fewer data available back then?
JFM counts JFM mean intensity AMJ counts AMJ mean intensity 35N 30N 50N 55N JAS counts JAS mean intensity 75N 40N 50N OND counts OND mean intensity All cyclones Northeast Asia Notable differences between NCEP1 & either NCEP2 or C20r Temporal homogeneity: questionable (data sparse in early decades?)
Summary and next step 1. Ensemble mean of C20r (v1): - Pretty comparable (to NCEP1) & homogeneous representation of cyclone activity over the N. Atlantic and N. Europe in all seasons, and over the mid-lat. N. Pacific (except for the first decade, 1908-1918) - Reasonably comparable &homogeneous representation of cyclone activity over central North America, especially in cold seasons (OND-JFM) - Seems to have temporal discontinuities over Canadian Arctic, high-lat N. Pacific, and NE Asia (data sparse areas; data availability info can be used to look into this problem) 2. Next step: - To apply the cyclone detection/tracking algorithm to the individual run of the C20r v2 ensemble for 1891-2003 - compare the results with NCEP1, NCEP2, ERA40, and with storm index from station data - assess long-term trends and variability of cyclone activity since 1891.
Average over NE Atlantic region: V1 ensmean Surface (10 m) wind speed extremes (WsP99) taken from C20r & ERA40 vs. geo-wind extremes (WgP99) derived from in-situ pressure obs
Average over NH land area Average over NH ocean area JFM mean intensity JFM counts JFM mean intensity JFM counts AMJ mean intensity AMJ counts AMJ counts AMJ mean intensity JAS mean intensity JAS counts JAS counts JAS mean intensity OND counts OND mean intensity OND counts OND mean intensity All cyclones