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Products and Services for Disaster Mitigation and Economic Enhancement Edward O’Lenic, Chief Climate Operations Branch NOAA-NWS-Climate Prediction Center.

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Presentation on theme: "Products and Services for Disaster Mitigation and Economic Enhancement Edward O’Lenic, Chief Climate Operations Branch NOAA-NWS-Climate Prediction Center."— Presentation transcript:

1 Products and Services for Disaster Mitigation and Economic Enhancement Edward O’Lenic, Chief Climate Operations Branch NOAA-NWS-Climate Prediction Center Camp Springs, Maryland ed.olenic@noaa.gov 301-763-8000, ext 7528

2 Mission

3 Summary Climate forecasting, for any location, requires: –A global ocean-land-atmosphere approach which begins with monitoring. –Monitoring, coupled with long time series of ocean and atmospheric data permit us to diagnose climate system behavior and develop prediction schemes. –Science and user input drive product development. –Prediction techniques use physical/dynamical models and statistical prediction techniques to predict the future behavior of the climate system.

4 WEATHER vs. CLIMATE

5

6 Forecast Process Schematic Dynamical Model Forecasts Recent observations Historical observations Verifications / Statistical Tools Downscaling, Analogs, Composites Non-public web pages, automated databases Forecaster-created or automated products Dissemination to public

7 Forecast tools web page

8 Operations Concept for Ocean/Atmosphere Model NCEP currently uses dynamical coupled ocean-atmosphere models in combination with statistical models to produce seasonal outlooks with ½ to 5 ½ month leads and, to a lesser extent, monthly outlooks with ½ month lead. Enhanced model operations which include increased numbers of ensemble members, more frequent model runs and enhanced capability to include the influence of within-season variations in SST and OLR will be used to: - Produce more highly resolved distributions of predicted variables, - Produce forecasts which increasingly and more appropriately reflect the influence of intra-seasonal variability on middle latitude climate, - Produce improved week 2 and monthly outlooks and develop and implement new outlook products for the week 3-4 period. - Develop and implement new products to predict seasonal variations in frequency of extreme events, primarily during ENSO.

9 Detailed operations concept for ocean-atmosphere model Currently, coupled dynamical model forecasts are one of several tools used in preparing long-range outlooks. NCEP’s model is run to produce one set of ensemble forecasts per month during the first week of the month. This is done in a two-tiered system, in which first, an ensemble of 16 ocean forecasts are created using a coupled GCM. The average of these is used as the official SST forecast. This SST forecast is then used as the lower boundary for an AGCM to create a set of 20 atmosphere ensemble members. The forecasts are run out to 9 months. A 20-year run of the AGCM is created each month. The seasonal means from this run are used as the climatology to create anomaly maps from each of the ensemble members. The means of these anomaly maps are used as the forecast tools which are presented to the forecasters. The forecasters use the NCEP model tools, together with other model tools to subjectively create outlook maps of the probability of monthly and seasonal mean temperature and total precipitation category.

10 El Nino Global Impacts

11 La Nina Global Impacts

12 Monthly and Multi-Seasonal Outlooks Temperature

13 Monthly and Multi-Seasonal Outlooks Precipitation

14 Probability of Exceedance: June – August 2001 Cooling Degree Days in U. S. Climate Region 45 (western Kansas)

15 Extended Range Outlooks Outlooks for average temperature and precipitation for 6-10-, 8-14-days

16 Degree Day Assessment The CPC weekly Degree Day Assessment discusses the Heating Degree Day (HDD) or Cooling Degree Day (CDD) outlook for the coming week, and reviews temperature and degree day statistics for the past week and the heating season (November - March) or cooling season (May - September) to date. This Assessment can assist energy managers in anticipating and analyzing fuel demand, because degree days quantitatively reflect the public need for energy to heat and cool businesses and dwellings. The Last 2000/01 heating season discussion, issued March 19, 2001, indicated that the slow seasonal decline in HDD’s should generally continue March 19 – 25, with increases in 7-day totals (relative to last week) restricted to the Southeast, northern Gulf Coast, and middle Ohio Valley. Temperatures should average below normal from central and southern Texas eastward and northeastward through the south Atlantic, central Appalachian, and southern mid-Atlantic regions. In contrast, above-normal temperatures should prevail for most areas from the High Plains to the West Coast, except for most of Washington and Oregon. However, HDD totals should generally be within 60 of normal nationally, except in the northwestern Great Basin, where totals are expected to be 60 to 90 below normal.

17 Uses of Climate Outlooks

18 Linking Climate and Weather

19 8Provides weekly status of ongoing drought conditions 8Consolidates information from numerous federal and state agencies 8Combines several key drought indices (Palmer, soil moisture, precipitation on several time scales, etc.) with subjective input from local and regional experts 8Serves as a universal starting point for information access, from which users can delve into more detail 8Gives the outlook for drought conditions based upon most recent long-lead precipitation outlook. Drought Status and Prediction

20 PROBABILITY OF A HEAT WAVE MAXIMUM HEAT INDEX Heat Wave / Heat Index Outlooks

21 ENSO Diagnostics EL NIÑO/SOUTHERN OSCILLATION (ENSO) DIAGNOSTIC DISCUSSION issued by:CLIMATE PREDICTION CENTER/NCEP August 3, 2001 Sea surface temperature (SST) anomalies continued to increase in the central equatorial Pacific during July 2001. Since February 2001 SSTs and SST anomalies have steadily increased in the central equatorial Pacific Niño 4 region (Fig. 1) rising to their highest levels since the 1997-98 warm (El Niño) episode. By late July equatorial SST anomalies between 0.5°C and 1°C were observed between 165°E and 135°W (Fig. 2). Over the past two years there has been a gradual expansion of the area of positive equatorial subsurface temperature anomalies into the central Pacific and a gradual decrease in the strength and areal extent of the negative subsurface temperature anomalies in the eastern Pacific. This evolution is consistent with the decay of the subsurface thermal structure that characterizes the mature phase of cold episodes and the development of conditions usually found just prior to warm episodes. Accompanying this evolution has been a gradual transition from negative to positive SST anomalies between 160°E and 130°W. Positive SST anomalies are likely to continue in the equatorial Pacific during the remainder of 2001 and into the first half of 2002. This assessment is consistent with most coupled model and statistical model predictions that indicate warmer than normal oceanic conditions through early 2002. The impacts that this warming will have on global temperature and precipitation patterns depend to a large degree on its intensity. At the moment, there is considerable spread in the predicted SST anomalies, with most predictions indicating a weak or moderate warm episode (El Niño) by the end of 2001 and the beginning of 2002. Weekly updates for SST, 850-hPa wind, OLR and the equatorial subsurface temperature structure are available on the Climate Prediction Center homepage at: http://www.cpc.ncep.noaa.gov (Weekly Update). Forecasts fo the evolution of El Niño/La Niña are updated monthly in CPC's Climate Diagnostics Bulletin Forecast Forum.

22 A Real-Time Analysis of Daily Precipitation Over South Asia Domain –70 o E - 110 o E; 5 o N - 35 o N; Resolution –Daily (00Z - 00Z); 0.1 o latitude / longitude; Inputs –GTS gauge Observations of Daily Precipitation; –Estimates Derived From Satellite Observations; »GPI (IR); »SSM/I (Microwave); »AMSU (Microwave);

23 Algorithms –Reducing Random Error combining the 3 kinds of satellite estimates linearly through the Maximum Likelihood Estimation method, in which the weighting coefficients are inversely proportional to the individual error variance; – Removing Bias blending the output of the first step with the gauge data through the method of Reynolds (1988), in which the First-Step-Output and the gauge data are used to determine the ‘shape’ and the magnitude of the precipitation field, respectively; Outputs –Binary data files and GIF graphics files; –Available around 9AM EST at the CPC ftp site;

24 An Example of the Daily Analysis for August 25, 2001

25 Summary Climate forecasting, for any location, requires: –A global ocean-land-atmosphere approach which begins with monitoring. –Monitoring, coupled with long time series of ocean and atmospheric data permit us to diagnose climate system behavior and develop prediction schemes. –Prediction techniques use physical/dynamical models and statistical prediction techniques to predict the future behavior of the climate system. –Science and user input drive product development.


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