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An Assessment of the CFS real-time forecasts for 2005-2011

Wanqiu Wang, Mingyue Chen, and Arun Kumar

CPC/NCEP/NOAA

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- CFS continues producing delayed transition between ENSO phases; PDF correction improves the forecasts (slides 6/7/8)

CFS reproduced Indian dipole mode index (DMI) variability in for 2007. But for other years, either the sign or the timing or both were erroneous; CFS forecast correct sign of MDR SST index but with weaker amplitude (slide 6)

- The CFS forecasted T2m, precipitation and Z200 distributions in the tropics and over the North America similar to the observed for DJF 2010/2011, consistent with atmospheric response to tropical SST anomalies; For JJA 2010, forecast of T2m over the central and eastern United States are too cold (slides 9 &10)

- ENSO has been in a low variability and low predictability regime during the last few years (slides 12-14)

- The CFS forecast shows better precipitation skill over land compared to hindcast (slide 16)

- The CFS produces a cold bias in northern extratropics during warm seasons due to wet initial soil moisture in R2, lowering T2m forecast skill T2m (slides 16-19, 21-23)

- There exists a mean cold bias over the globe during the forecast period (slide 24)

Summary

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- Real-time skill against the hindcast

- Long-term skill variability

- Impact of initial condition

- Systematic errors

Relevance

Diagnostics/monitoring of CFS real-time forecasts

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Outline

1. CFS forecast for 2010

2. Skills of CFS forecasts during 2005-2010

3. Systematic errors in the forecast

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1. CFS forecast for 2010

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Nino34

DMI

MDR

SST indices

Nino34 Persists and amplifies

existing anomalies

Delayed transition of ENSO phases at longer lead-time

DMI More realistic DMI for 2007

& 2006. 2011 forecast is good for L0 and L3.

Bad forecast for 2005, 2008, and 2010

MDR Amplitude too weak

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8See http://origin.cpc.ncep.noaa.gov/products/people/wwang/cfs_fcst/PDFcorrection.html for an explanation of the PDF correction

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Forecast for DJF 2011/2012

Both the CFS and AMIP simulation captured observed precipitation and Z200 anomalies in the subtropics and tropics

The forecasted and simulated z200 in the mid-high latitudes are quite unrealistic.

The models failed to reproduce observed overwhelming warmth over most of the North America.

Obs CFS 0-mo lead AMIP (DJ)CFS 1-mo lead

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Forecast for JJA 2011Obs CFS 0-mo lead AMIPCFS 1-mo lead

CFS and AMIP simulation produced a reasonable distribution of the tropical precipitation. Tropical Z200 anomalies are qeak in both the observation and forecast.

The observed spatial pattern of T2m over NH land is much better reproduced in AMIP. The CFS did not capture the observed warm anomalies in the central eastern United States, likely due to the too wet initial soil moisture (slides 22-23).

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2. CFS forecast skill

-SST

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2005-2011forecastSST temporal correlation

1981-2004 hindcast

Lower forecast skill tropical eastern Pacific at longer lead-time

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Nino34 SST temporal correlation

Why is Nino3.4 forecast skill at longer lead time not as good ?

(1981-2004)(2005-2011)

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Most of the real time forecast period is in a low predictability regime

The skill depends on amplitude of tropical interannual variability

Global mean correlation

Nino34 correlation

Nino34 STDV

Statistics for sliding 4-year windows

Beginning of the 4-year window

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2. CFS forecast skill

-Atmospheric fields

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Temporal correlation2005-2011 forecast 1981-2004 hindcast

• Higher Z200 skill in northern high-latitudes• Higher precipitation skill over land• Lower T2m skill in over NH land

T2M

Prec

Z200

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2005-2011 forecast 2005-2011 AMIPTemporal correlation

T2M

Prec

Z200

• Higher precipitation skill over land and in Indian Ocean• Higher Z200 skill in northern high-latitudes• Similar T2M skill.

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Pattern correlation over tropical ocean

Pacific Higher skill compared to IO

and ATL oceans

Comparable between CFS forecast and AMIP

Seasonal variation

Indian Ocean Higher skill in CFS during

spring and summer forecast – air/sea coupling important

Atlantic Higher SST skill between

JFM2005 and FMA 2007 and after DJF 2009/2010

Lower rainfall skill in both forecast and AMIP even when SST skill is high – low predictability

20S-20N

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Pattern correlation over N.H. land

Higher CFS precipitation skill in 2005-2008

Good CFS and AMIP skill during 2007/2008 La Nino winter

Lower T2M skill during summers

20N-80N

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3. Systemetic errors- Cold summers

- Mean bias

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JJA T2m2005 2006 2007 2008

Observation

2009

CFS keeps producing negative anomalies in central or eastern North America where observed anomalies are more changeable from year to year.

2010 2011

1-mo-lead Forecast

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JJA T2M and May soil moisture

2005-2011 average Obs

JJA T2M

CFS

JJA T2M

AMIP

JJA T2M

R2

May SM

- Errors in forecast T2m appear to be related to initial wet SM anomalie

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- Initial soil moisture during the forecast period remains well above normal

May soil moisture over North America from R2

40N-60N average

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- Cold T2m and SST, and negative Z200 bias

- Possible causes:

- Lack of increasing greenhouse gases

- Lack of realistic sea ice coverage

- Initial soil moisture

2005-2011 mean bias2-month-lead forecast