How does ncep cpc make operational monthly and seasonal forecasts
Download
1 / 52

How Does NCEP/CPC Make Operational Monthly and Seasonal Forecasts? - PowerPoint PPT Presentation


  • 125 Views
  • Uploaded on

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…

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about ' How Does NCEP/CPC Make Operational Monthly and Seasonal Forecasts?' - locke


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
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 Forecasts?

  • 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: Forecasts?

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 Forecasts?

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



EMP Forecasts?

EMP

EMP

EMP

N/A

DYN

CON

CON

EMP

DYN


SMLR Forecasts?

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)


Element Forecasts? 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


About Forecasts?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.


OCN has become the bearer of most of the skill, Forecasts?see also EOCN method (Peng et al), or other alternatives of projecting normals forward.


G Forecasts?

H

C

N

-

C

A

M

S

F

A

N

2

0

0

8

  • [email protected]



Ncep s climate forecast system now called cfs v2
NCEP’s Climate Forecast System, now called CFS v2 Forecasts?

  • 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 Forecasts?

<--

Out of date diagram.

Still instructive


Major verification issues
Major Verification Issues Forecasts?

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

After the fact (fairly normal and traditional)


After the fact….. Forecasts?

Source Peitao Peng


(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)


Consolidation
Consolidation reliable a-priori skill estimate.


--------- OUT TO 1.5 YEARS ------- reliable a-priori skill estimate.


OFFicial Forecast(element, lead, location, initial month) = reliable a-priori skill estimate.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)


CFS v1 skill 1982-2003 reliable a-priori skill estimate.


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


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

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’?


(Delsole 2007) 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.


SEC 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.

SEC and CV

3CVRE


See also: 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.

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.


Empirical tools can be comprehensive! (Thanks to reanalysis, among other things). And very economical.Constructed Analogue(next 2 slides)


  • Given an Initial Condition, SST among other things).IC (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.


  • 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.


CA-weights in the initial condition we can make a forecast with some skill by

March 2014


Z500 the initial condition we can make a forecast with some skill by

SST

CA

T2m

Precip


SST the initial condition we can make a forecast with some skill by

Z500

CFS

T2m

Precip

Source: Wanqiu Wang


Physical attributions of forecast skill
Physical attributions of Forecast Skill the initial condition we can make a forecast with some skill by

  • Global SST, mainly ENSO. Tele-connections needed.

  • Trends, mainly (??) global change

  • Distribution of soil moisture anomalies


Website for display of NMME&IMME the initial condition we can make a forecast with some skill by NMME=National Multi-Model EnsembleIMME=International Multi-Model Ensemble

  • http://origin.cpc.ncep.noaa.gov/products/NMME/


Please attend
Please attend the initial condition we can make a forecast with some skill by

  • Friday 2pm June 14

  • Tuesday 1:30pm June 18

    Two meetings to Discuss the Seasonal Forecast.


ad