A Look at Climate Prediction Centers Products and Services

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A Look at Climate Prediction Centers Products
and Services

• Ed OLenic
• NOAA-NWS-Climate Prediction Center
• Camp Springs, Maryland
• ed.olenic_at_noaa.gov
• 301-763-8000, ext 7528
• Eastern Region Climate Services Workshop
• Raliegh, North Carolina
• September 17, 2003
•  

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Objectives

• CPC products and terms
• CPCs web site
• MJO tropical convection - hope
• Outlooks
• Verification

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Climate Versus Weather
Top Graph Observed daily average Temperature
(T), May 2000-April 2001 (jagged curve, an
example of weather), and 30-year average
(1971-2000) of daily average T (also called the
normal, (smooth curve) the standard definition
of climate) at Albany, New York. Note the
large day-to-day variability indicated by the
red (above-normal) and blue (below normal) daily
T events. Bottom Graph Result of subtracting
the normal from the daily average T in the top
graph and then performing a 31- day running
average. Note the expanded scale on the lower
graph. The extended periods of above and below
normal 31-day average T are, examples of
short-term climate variability. Green line is
the average of the departures over May 2000-April
2001.
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CPC Data-to-Product Process Schematic
REAL-TIME OBS
DYNAMICAL MODEL ENSEMBLES
HISTORICAL OBSERV-ATIONS
CLIMO
STATISTICAL MODELS
MONITORING - PREDICTION TOOLS, WEB PAGES
FORECASTS, EXPERT ASSESSMENTS, MONITORING
PRODUCTS
AWIPS, PRINTED PUBLICATIONS, WEB PAGES/AUTOMATED
PRODUCTS AND DATABASES
USER FEEDBACK VIA CSD
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Some Definitions

• Climate Average of weather over days, weeks,
  months, years
• Climate Prediction Concerned with averages and
  variability, rather than weather.
• Climatology Average over a long time relative
  to features being studied (BORING)
• 3-class system Divide the climatology into
  highest, lowest and middle thirds.
• Lead time Time between the issuance of a
  forecast and when it becomes valid.
• 6-10 day forecast 5-day mean forecast at lead 5
  days.
• 8-14 day forecast 7-day mean forecast at lead 7
  days.
• 0.5 month outlook ½ month lead forecast of
  seasonal mean T, P
• Probability P(A) ( possible events (H)) /
  (total possible outcomes (HT))
• Probability anomaly probability of an event
  climatological probability of an event.
• Total probability probability anomaly
  climatological probability
• Probability distribution Graph where the area
  under the curveprob. of an event.
• Extreme event An event in the upper-, or
  lower-most part of a probability dist.
• Southern Oscillation A back and forth pressure
  variation with opposite sign between the eastern
  (Tahiti) and western (Darwin) portions of the
  tropical Pacific.
• ENSO El Nino/Southern Oscillation, made up of El
  Nino (warm) and La Nina (cold)
• ENSO-Neutral Usually refers to years which are
  neither El Nino nor La Nina
• Trend most recent 10(15) year means of observed
  T(P) minus the 30-yr climatology
• Maritime Continent Indonesia and surrounding
  region, a focus of tropical convection
• MJO Madden-Julian Oscillation, a wave 1
  tropical disturbance with dry and wet phases

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Total SST7-day mean centered on 03 September,
2003SSTa
Warm Pool
nino 3.4
Cold Tongue
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CPC Home Page
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Climate HighlightsUS Hazards Assessment
The U.S. Hazards Assessment page is a
comprehensive source of up-to- date information
on the status of the Global climate. The left
column is intended to let you self-brief, and is
used by Hazards briefers to prepare and brief
the product.
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US Seas Drought Outlook
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Climate Highlights ENSO Diagnostic
Discussionhttp//www.cpc.ncep.noaa.gov/products/a
nalysis_monitoring/enso_advisory/index.html
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Outlook Products link
Outlooks Products http//www.cpc.ncep.noaa.gov
/products/predictions
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6-10 day T
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6-10 day P
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Monthly Outlook
S/N is larger for Seasonal than Monthly.
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0.5 mo lead seasonal T, P outlook
Outlooks combine long-term trends, soil-moisture
effects, model forecasts with typical ENSO cycle
impacts, when appropriate.
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SST forecast
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Diurnal Cycle of Convection Can Lead to Large
Time and Space Scale Phenomena
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Why the MJO is important

• Intimately related to active/break cycles of the
  Australian and Asian Monsoons
• Offers potential to provide extended
  predictability up to 15-20 days in tropics
• Affects weather (predictably?) over the western
  US and elsewhere
• Associated westerly wind events generate Tropical
  Pacific ocean Kelvin waves which may
  significantly modify the evolution and amplitude
  of El Nino (e.g. 1997, 1991)
• Large inter-annual variability in the activity of
  the MJO has implications for the predictability
  of the coupled ocean-atmosphere system

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MJO Activity and Inter-annual SST
1 season lag correlation 0.65

• West Pacific SST in Fall versus MJO Activity in
  Winter
• Foundation for link with ENSO?
• 95 level assuming zero correlation and 22 dof is
  0.43

MJO ACTIVITY
West Pacific SST
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MJOs and 1991-92 El Nino Late Onset
Zonal Wind Anoms SST Anoms 20C
Depth Anoms
1
1
Nov 90
2
2
Mar 91
3
3
Sep 91
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Annual Mean Precipitation Errors in
HadAM3Sensitivity to Horizontal Resolution
(Neale and Slingo, 2003 J. Clim., 16, 834-838)
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HadAM3 Sensitivity Experiments Impact of
removing the islands of the Maritime Continent
(Neale and Slingo, 2003 J. Clim., 16, 834-838)

• Land grid-points removed and replaced by ocean
  grid-points.
• Increased moisture availability from the sea
  surface leads to enhanced convection and partial
  correction of the model dry bias.
• Note also corrections to models wet bias in
  adjacent areas.

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Global Impacts of Improved Maritime Continent
Heat SourceDJF 500hPa height (m) and Surface
Temperature (K)

• Potential improvements in the Maritime Continent
  heat source can have significant remote effects.
• Related to the generation of Rossby waves by the
  enhanced divergent outflow from the Maritime
  Continent heat source.
• Substantially reduces model systematic error over
  the extra-tropics of the winter hemisphere.
• Emphasizes the importance of considering the
  global context of model systematic error in which
  biases in the tropics may be a key factor.

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CPC Forecast System
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Long-Lead Seasonal Forecasts
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Forecast Maps and Bulletins

• Each month, on the Thursday between the 15th
  21st, CPC issues a set of 13 seasonal outlooks.
• There are two maps for each of the 13 leads, one
  for temperature and one for precipitation for a
  total of 26 maps.
• Each outlook covers a 3-month season, and each
  forecast overlaps the next and prior season by 2
  months.
• Bulletins include the prognostic discussion for
  the seasonal outlook over North America, and, for
  Hawaii.
• The monthly outlook is issued at the same time as
  the seasonal outlook. It consists of a
  temperature and precipitation outlook for a
  single lead, 0.5 months, and the monthly
  bulletin.
• All maps are sent to AWIPS, Family of Services
  and internet.

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Statistical Prediction Tools

• Multiple Linear Regression
• - Predicts a single variable from historical
  and recent observations of two or more
  predictors.
• Canonical Correlation Analysis (CCA)
• Uses recent and historical observations of
  Northern Hemisphere circulation (Z), global sea
  surface temperature (SST), US surface T (Tus) to
  create a set of 5 or 6 EOFs of predictors and
  predictands.
• Looks at cross-correlations between time series
  of predictors and predictands.
• Predicts temporal and spatial patterns from
  patterns.

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Statistical Prediction Tools

• Constructed Analogs (CA)
• Uses recent observations (base) of a single
  variable and historical observations, to
  construct a weighted mean of all prior years
  which best explains the base data. Assumes the
  evolution to subsequent seasons is also best
  explained by the weights used to construct the
  analog to the base.
• Optimal Climate Normals (OCN)
• Uses the difference between the most recent 10
  (15) years of temperature (precipitation)
  observations and the 30-year climatology (i.e.,
  the trend) for a given season as the prediction
  for future occurrences of that season.

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Trend (10-yr mean-minus-30-yr mean) Temperature
for Alaska and CONUSLoop shows 3-month mean T
anomalies expressed as tenths of standard
deviations.JAS, ASO, SON, , MJJ, JJA
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JAS
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ASO
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SON
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OND
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NDJ
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DJF
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JFM
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FMA
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MAM
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AMJ
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MJJ
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JJA
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http//www.cpc.ncep.noaa.gov/products/predictions/
90day/tools/briefing/index.pri.html
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NCEP AGCM Forecasts for DJF 2000-01, 2001-02,
and 2002-03
SST Forcing
Global and NOAM T Fcst
2000-01
2001-02
2002-03
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CCA, OCN, CMP, OFF T Tools DJF2003
OCN
CCA
CMP
OFF
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Probability of Exceedance (POE) Map
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PROBABILITY OF EXCEEDANCE THE SHIFT IN THE
CENTER OF THE DISTRIBUTION IMPLIED BY THE FORECAST
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Verification

• CPC official forecasts and tools are continuously
  verified
• Verification statistics are made available to
  forecasters
• Categorical verifications blunt instrument,
  understandable
• Probabilistic verifications much more
  informative, highlight need for calibration

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Heidke Skill Score

• s ((c-e)/(t-e))100
• c stations correct
• e stations expected correct
• t stations in total

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Categorical Skill Scores of Seasonal
Forecasts0.5 Month-Lead Temperature
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Categorical Skill Scores of Seasonal
Forecasts0.5 Month-Lead Precipitation
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Seasonal forecastSkill CCA
EC stations not scored
EC stations scored as Normal
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Comparison of CCA coverage DJF, MAM, JJA, SON
CCA DJF
CCA MAM
CCA JJA
CCA SON
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(No Transcript)
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(No Transcript)
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(No Transcript)
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6-10 day VerificationOfficial, Automated, 1st
Guess Temperature
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8-14-day Precipitation Accumulation7-,
30-DayBias Bias Correction
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THE END