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Some Behaviors of CPC Monthly Precipitation Forecasts In Nebraska James McCormick University of Nebraska-Lincoln School of Natural Resources August 16,

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Presentation on theme: "Some Behaviors of CPC Monthly Precipitation Forecasts In Nebraska James McCormick University of Nebraska-Lincoln School of Natural Resources August 16,"— Presentation transcript:

1 Some Behaviors of CPC Monthly Precipitation Forecasts In Nebraska James McCormick University of Nebraska-Lincoln School of Natural Resources August 16, 2007

2 Outline Purpose Definitions Methodology Accuracy Physical Explanations Conclusions Future Work Acknowledgements References

3 Purpose To examine tendencies and accuracy of monthly precipitation products in Nebraska Discover physical reasoning for ‘missed’ forecasts

4 Definitions Time Period: October 1995 – November 2006 Monthly Precipitation Outlook Above, Below, Near Normal, Equal Chances

5 Methodology 9 Stations In Nebraska Chosen Ainsworth, Broken Bow, Chadron, Hastings, Lincoln, McCook, Norfolk, North Platte, Omaha Values Collected By Reading Maps – ‘The Average User’ Rainfall Data Taken From High Plains Regional Climate Center

6 Methodology (cont.) Use 30-Year Data To Create Verification Thresholds Find the Median Value For Each 30 Year Period Divide Each 30 Year Period Into Thirds

7 Methodology (cont.) Assign forecasts values of ‘1’ for above normal, ‘0’ for near normal or equal chances, and ‘-1’ for below normal For this binomial analysis, assign all precipitation values (with 2 exceptions) values of ‘1’ for above 30-year median, and values of ‘-1’ for below 30-year median Subtract observation value from forecast value; take absolute value Values of 0 are considered accurate forecasts; values of 2 considered poor forecasts

8 Verification Issues… How does the generic user see the product? How does the meteorological user see the product? What to do with the ‘Near Normal’ forecast product, which has never been used in monthly precipitation forecasts for Nebraska? How to deal with ‘Equal Chance’ Forecasts

9 Point Verification Advantages Use of rain gauge data Precipitation measurement as opposed Disadvantages Individual points do not necessarily represent atmospheric behavior over larger spaces

10 Binomal Verification Ainsworth: 32 Forecasts – (20A/12B) Broken Bow: 31 Forecasts – (21A/10B) Chadron: 29 Forecasts – (21A/8B) Hastings: 29 Forecasts – (19A/10B) Lincoln: 32 Forecasts – (21A/11B) McCook: 28 Forecasts – (20A/8B) Norfolk: 32 Forecasts – (21A/11B) North Platte: 28 Forecasts – (19A/9B) Omaha: 33 Forecasts – (21A/12B) Scottsbluff:

11 Binomial Verification Results (for above/below forecasts) Ainsworth: 18/32 Accurate (56.25%) Broken Bow: 8/30 Accurate (26.67%) Chadron: 20/29 Accurate (68.97%) Hastings: 15/29 Accurate (51.72%) Lincoln: 15/32 Accurate (46.88%) McCook: 13/28 Accurate (53.57%) Norfolk: 14/32 Accurate (43.75%) North Platte: 19/28 Accurate (67.86%) Omaha: 14/33 Accurate (42.42%) Overall: 136/273 Accurate (49.618%)

12 Binomial Results (pre-June 2001 vs post-June 2001) # Of Errors Ainsworth: (9/5) Broken Bow: (13/10) Chadron: (7/2) Hastings: (8/6) Lincoln: (9/8) McCook: (10/5) Norfolk: (11/7) North Platte: (6/3) Omaha: (8/11) Scottsbluff: # Of Forecasts Ainsworth: (18/15) Broken Bow: (17/13) Chadron: (19/10) Hastings: (18/11) Lincoln: (18/14) McCook: (18/10) Norfolk: (17/11) North Platte: (16/12) Omaha: (18/15) Scottsbluff:

13 Regional Verification National Weather Service Precipitation Analysis Examined in Cases of Missed Precipitation Forecasts

14 Higher Confidences… Current standards of confidence implemented in early st Level: 33-40% confidence of above/below normal conditions 2 nd Level: 40-49% confidence of above/below normal conditions 3 rd Level: 50-59% confidence of above/below normal conditions And so on…

15 Higher Confidences (Cont.) Since the confidence levels were implemented, none of the selected Nebraska stations have been placed in a confidence level of 50% or greater, for above or below normal forecasts

16 Higher Confidence Results Ainsworth: (0/2) Broken Bow: (0/2) Chadron: (0/1) Hastings: (0/2) Lincoln: (0/1) McCook: (1/1) Norfolk: (0/2) North Platte: (0/2) Omaha: (1/2) OVERALL: (2/15) – % Accuracy!!

17 May 2006 Forecast Normal Values (in) Ainsworth Lower Third: Median: 3.19 Upper Third: 3.64

18 May 2006 Results

19 What Happened? 28 Days Produced.74 inches of rain… while 2 days produced 4.42 inches of rain

20 December 2006 Forecast

21 Results

22 Precipitation Totals (Inches) Pre-December 15 th Ainsworth: 0.00 Broken Bow: 0.00 Chadron: 0.00 Hastings: 0.00 Lincoln: 0.00 McCook: 0.00 Norfolk: 0.07 North Platte: 0.00 Omaha: 0.11 Total (in) Ainsworth: 1.81 Broken Bow: 2.16 Chadron:.37 Hastings: 2.48 Lincoln: 3.05 McCook: 4.08 Norfolk: 2.62 North Platte: 2.56 Omaha: 2.25

23 December 2006 (continued) Total (in) Ainsworth: 1.81 Broken Bow: 2.16 Chadron:.37 Hastings: 2.48 Lincoln: 3.05 McCook: 4.08 Norfolk: 2.62 North Platte: 2.56 Omaha: Year High (in) Ainsworth: 1.36 Broken Bow: 1.24 Chadron: 1.89 Hastings: 2.81 Lincoln: 3.41 McCook: 2.1 Norfolk: 2.25 North Platte: 1.22 Omaha: 5.42

24 Physically… What happened? - Two synoptic weather systems affected the central plains within the last 10 days of the month

25 Conclusions No significant increase in forecast aggressiveness – equal chance forecasts remain much more common in Nebraska than forecasts of either above or below normal Overall trends suggest that even fewer above/below normal forecasts are being issued currently compared to the late 1990s Current monthly precipitation forecast confidence levels are fairly conservative in relation to other CPC products, especially those of equal or shorter forecast duration Forecasts of above normal precipitation are more common during the last 10 years This result may suggest that forecasting ‘below’ normal precipitation is inherently more difficult than forecasting ‘above’ normal precipitation The forecasts of higher confidence do not show a significant tendency to be accurate

26 Conclusions Precipitation forecasts for monthly and seasonal values, at one single point, are frequently at the whim of the mesoscale behavior of thunderstorms… especially in spring and summer months This behavior is unpredictable at short ranges… much less days in advance While winter weather patterns may seemingly be more predictable (synoptically driven), there is less ‘margin for error’ The difference between the top 1/3 and bottom 1/3 of the 30 year normals is less than.25 inches of precipitation in many cases This behavior is unpredictable at short ranges… much less days in advance

27 Conclusions (Cont.) Short term weather patterns, even for the majority of the month, do not, in all cases, indicate the precipitation tendency (as evidenced by December 2006)

28 Concurrent/Future Work Forecast Analysis for Monthly Temperature and Seasonal Forecasts Forecast Analysis for 5 Other Regions of the Nation Continued, in-depth physical exploration for missed and accurate forecasts Forecast Analysis of Short Term Forecasts

29 Acknowledgements Dr. Steve Hu, School of Natural Resources, University of Nebraska-Lincoln Donald Van Dyke and Clark Evans, Department of Meteorology, Florida State University Nich Smith, Computer Support

30 Sources Climate Prediction Center, High Plains Regional Climate Center, National Weather Service Precipitation Analysis, cip_analysis_new.php Storm Prediction Center Image Archive


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