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How Does NCEP/CPC Make Operational Monthly and Seasonal Forecasts?. Huug van den Dool (CPC) CPC, June 23, 2011/ Oct 2011/ Feb 15, 2012 / UoMDMay,2,2012/ Aug2012/ Dec,12,2012/UoMDApril24,2013/ May22,2013,/Nov20,2013/April,23,2014/. Assorted Underlying Issues. Which tools are used…

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how does ncep cpc make operational monthly and seasonal forecasts
How Does NCEP/CPC Make Operational Monthly and Seasonal Forecasts?

Huug van den Dool (CPC)

CPC, June 23, 2011/ Oct 2011/ Feb 15, 2012

/ UoMDMay,2,2012/ Aug2012/ Dec,12,2012/UoMDApril24,2013/

May22,2013,/Nov20,2013/April,23,2014/

assorted underlying issues
Assorted Underlying Issues
  • Which tools are used…
  • How do these tools work?
  • How are tools combined???
  • Dynamical vs Empirical Tools
  • Skill of tools and OFFICIAL
  • How easily can a new tool be included?
  • US, yes, but occasional global perspective
  • Physical attributions
menu of cpc predictions
Menu of CPC predictions:

6-10 day (daily)

Week 2 (daily)

Monthly (monthly + update)

Seasonal (monthly)

Other (hazards, drought monitor, drought outlook, MJO, UV-index, degree days, POE, SST) (some are ‘briefings’)

Operational forecasts (‘OFFICIAL’) and informal forecast tools (too many to list)

http://www.cpc.ncep.noaa.gov/products/predictions/90day/tools/briefing/index.pri.html

example
EXAMPLE

P

U

B

L

I

C

L

Y

I

S

S

U

E

D

O

F

F

I

C

I

A

L

F

O

R

E

C

A

S

T

slide8
EMP

EMP

EMP

EMP

N/A

DYN

CON

CON

EMP

DYN

slide9
SMLR

CCA

OCN

LAN

OLD-OTLK

CFSV1

LFQ

ECP

IRI

ECA

CON

9

(15 CASES: 1950, 54, 55, 56, 64, 68, 71, 74, 75, 76, 85, 89, 99, 00, 08)

slide10
Element  US-T US-P SST US-soil moisture Method:CCA X X X OCN X X CFS X X X XSMLR X XECCA X XConsolidation X X X Constr Analog X X X XMarkov X ENSO Composite X X Other (GCM) models (IRI, ECHAM, NCAR,  N(I)MME): X X CCA = Canonical Correlation AnalysisOCN = Optimal Climate NormalsCFS = Climate Forecast System (Coupled Ocean-Atmosphere Model)SMLR = Stepwise Multiple Linear RegressionCON = Consolidation
slide14
About OCN. Two contrasting views:- Climate = average weather in the past- Climate is the ‘expectation’ of the future30 year WMO normals: 1961-1990; 1971-2000; 1981-2010 etcOCN = Optimal Climate Normals: Last K year average. All seasons/locations pooled: K=10 is optimal (for US T).Forecast for Jan 2015 (K=10) = (Jan05+Jan06+... Jan14)/10. – WMO-normalplus a skill evaluation for some 50+ years.Why does OCN work?1) climate is not constant (K would be infinity for constant climate)2) recent averages are better3) somewhat shorter averages are better (for T)see Huang et al 1996. J.Climate. 9, 809-817.
slide15
OCN has become the bearer of most of the skill, see also EOCN method (Peng et al), or other alternatives of projecting normals forward.
slide17
G

H

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slide18
[email protected]

Preview of 2010s, 4 years only

ncep s climate forecast system now called cfs v2
NCEP’s Climate Forecast System, now called CFS v2
  • MRFb9x, CMP12/14, 1995 onward (Leetmaa, Ji etc). Tropical Pacific only.
  • SFM 2000 onward (Kanamitsu et al
  • CFSv1, Aug 2004, Saha et al 2006. Almost global ocean
  • CFSR, Saha et al 2010
  • CFSv2, March 2011. Global ocean, interactive sea-ice, increases in CO2. Saha et al 2014.
ncep s climate forecast system now called cfs v21
NCEP’s Climate Forecast System, now called CFS v2

<--

Out of date diagram.

Still instructive

major verification issues
Major Verification Issues

‘a-priori’ verification (used to be rare)

After the fact (fairly normal and traditional)

slide24
After the fact…..

Source Peitao Peng

slide25
(Seasonal) Forecasts are useless unless accompanied by a reliable a-priori skill estimate.Solution: develop a 50+ year track record for each tool. 1950-present.(Admittedly we need 5000 years)
slide28
OFFicial Forecast(element, lead, location, initial month) = a * A + b * B + c * C +…Honest hindcast required 1950-present. Covariance (A,B), (A,C), (B,C), and(A, obs), (B, obs), (C, obs) allows solution for a, b, c (element, lead, location, initial month)
slide30
Fig.7.6: The skill (ACX100) of forecasting NINO34 SST by the CA method for the period 1956-2005. The plot has the target season in the horizontal and the lead in the vertical. Example: NINO34 in rolling seasons 2 and 3 (JFM and FMA) are predicted slightly better than 0.7 at lead 8 months. An 8 month lead JFM forecast is made at the end of April of the previous year. A 1-2-1 smoothing was applied in the vertical to reduce noise.

CA skill 1956-2005

slide31
M. Peña Mendez and H. van den Dool, 2008:

Consolidation of Multi-Method Forecasts at CPC.

J. Climate, 21, 6521–6538.

Unger, D., H. van den Dool, E. O’Lenic and D. Collins, 2009: Ensemble Regression.

Monthly Weather Review, 137, 2365-2379.

(1) CTB, (2) why do we need ‘consolidation’?

slide34
SEC

SEC and CV

3CVRE

slide42
See also:

O’Lenic, E.A., D.A. Unger, M.S. Halpert, and K.S. Pelman, 2008: Developments in Operational Long-Range Prediction at CPC.Wea. Forecasting, 23, 496–515.

slide43
Empirical tools can be comprehensive! (Thanks to reanalysis, among other things). And very economical.Constructed Analogue(next 2 slides)
slide44
Given an Initial Condition, SSTIC (s, t0) at time t0 . We express SSTIC (s, t0) as a linear combination of all fields in the historical library, i.e.

2012 or 2013

  • SSTIC (s, t0) ~= SSTCA(s) = Σ α(t) SST(s,t) (1)

t=1956 or 1957

(CA=constructed Analogue)

  • The determination of the weights α(t) is non-trivial, but except for some pathological cases, a set of (57) weights α(t) can always be found so as to satisfy the left hand side of (1), for any SSTIC , to within a tolerance ε.
slide45
Equation (1) is purely diagnostic. We now submit that given the initial condition we can make a forecast with some skill by

2012 or 2013

  • XF (s, t0+Δt) = Σ α(t) X(s, t +Δt) (2)

t=1956 or 1957

Where X is any variable (soil moisture, temperature, precipitation)

  • The calculation for (2) is trivial, the underlying assumptions are not. We ‘persist’ the weights α(t) resulting from (1) and linearly combine the X(s,t+Δt) so as to arrive at a forecast to which XIC (s, t0) will evolve over Δt.
slide46
CA-weights in

March 2014

slide48
Z500

SST

CA

T2m

Precip

slide49
SST

Z500

CFS

T2m

Precip

Source: Wanqiu Wang

physical attributions of forecast skill
Physical attributions of Forecast Skill
  • Global SST, mainly ENSO. Tele-connections needed.
  • Trends, mainly (??) global change
  • Distribution of soil moisture anomalies
slide51
Website for display of NMME&IMMENMME=National Multi-Model EnsembleIMME=International Multi-Model Ensemble
  • http://origin.cpc.ncep.noaa.gov/products/NMME/
please attend
Please attend
  • Friday 2pm June 14
  • Tuesday 1:30pm June 18

Two meetings to Discuss the Seasonal Forecast.

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