# Presentation: 376960

## Oceanic Surface Wind in Satellite Retrievals, NCEP Reanalyses, GFS, and CFS

- Sarah Marquardt, Wanqiu Wang, and Pingping Xie

## Background

- Surface wind is a critical variable in the coupling between atmosphere and ocean.  It directly affects
- Latent and sensible heat fluxes
- Momentum flux
- Substantial SST errors in the coupled models, such as CFS, are related to errors in surface wind
- Validation of coupled atmosphere-ocean models needs
- Global coverage of surface wind observations
- Diagnosis of the reliability of observations

## CFS 4-mo lead SST forecast mean error (K)

- Is the cold bias in equatorial Pacific due to erroneous surface winds?
- What are the impacts of surface winds on the southeastern Pacific warm bias in addition to the known excessive local solar radiation?

**Notes:**
Mention that there are two major biases first: the equatorial Pacific cold bias and southeastern Pacific warm bias.
Previous work has shown that errors in radiation contribute to one half of total SEP warm SST bias.

## Objectives

- Estimate uncertainty of the surface wind fields in satellite retrievals
- Examine the dependability of NCEP GDAS, CDAS1, CDAS2
- Diagnose errors in surface wind fields in NCEP GFS and CFS

**Notes:**
2 methods to estimate uncertainty of satellite obs: intercomparison between 4 satellite products and comparison between satellite and in situ

## Data (10-m wind)

- Satellite retrievals (2000-2007)
- RSS QuikScat wind Version 3a
- JPL QuikScat wind Product 109
- RSS SSMI wind Version 6
- NCDC Blended Winds Version 1.2
- In situ observations (2000-2004)
- FSU in situ wind FSU3 Version 1
- Reanalyses (2000-2007)
- GDAS (2002-2007)
- CDAS1
- CDAS2
- NCEP model simulations (Version 2003)
- GFS (2000-2007)
- CFS 0 mo. lead, init. 21st 1999-2006

## Uncertainty in satellite retrievals

## Spatial distribution of all observations is very similar 
NCDC winds are slightly faster in the tropics, SSMI winds are slightly slower in N.H.
Spread among retrievals is generally less than 0.4 m/s except for west coast of continents

- Spatial distribution of all observations is very similar
- NCDC winds are slightly faster in the tropics, SSMI winds are slightly slower in N.H.
- Spread among retrievals is generally less than 0.4 m/s except for west coast of continents

**Annual mean wind speed (m/s)**

**Notes:**
1st method to estimate uncertainty of satellite obs.  Bias with NCDC is likely to due rain contamination.  NCDC wind direction is also erroneous (from R2).

## QuikScat vs FSU moored buoy

-  Bias and rms error are smaller and correlation is higher in the tropics
- - QuikScat wind speed mean error is generally less than 1 m/s in the tropics but can be over 1 m/s too high near the extratropics

**Notes:**
2nd method to estimate uncertainty of satellite obs.

## Uncertainty of Observations

- Satellite – FSU Moored Buoys

|  | RSS | JPL | SSMI | NCDC |
| --- | --- | --- | --- | --- |
| Mean
(-20,20) Bias
RMSD
Corr | 6.17
0.48
0.68
0.91 | 6.25
0.53
0.71
0.89 | 6.23
0.50
0.75
0.88 | 6.42
0.77
0.88
0.84 |
| Mean
(20,60) Bias
RMSD
Corr | 7.81
1.71
1.29
0.79 | 7.86
1.67
1.25
0.79 | 7.70
1.43
1.32
0.77 | 7.76
1.87
1.29
0.77 |

- Bias and rms error are smaller and correlation is higher in the tropics
- Mean wind speed error is about 0.5 m/s (9% of total) in the tropics and about 1.6 m/s outside the tropics
- All satellite retrievals are comparable.  RSS QuikScat slightly better in the tropics, SSMI is better in NH

**Uncertainty of Observations**

## Dependability of NCEP reanalyses

- OBS = Mean of RSS, JPL, and SSMI

## GDAS wind matches observations very well

CDAS1 is too slow in the lower latitudes and CDAS2 is too fast in mid to high latitudes

- CDAS1 is too slow in the lower latitudes and CDAS2 is too fast in mid to high latitudes

**Annual mean wind speed (m/s)**

## GDAS wind matches observations very well
CDAS1 (CDAS2) wind too slow (fast) in southeastern Pacific
CDAS1 and CDAS2 have wind direction errors along the coast

- GDAS wind matches observations very well
- CDAS1 (CDAS2) wind too slow (fast) in southeastern Pacific
- CDAS1 and CDAS2 have wind direction errors along the coast

**Seasonal mean wind vector (m/s)**

## All three NCEP products are too fast near the coast

Slow bias along the coast in CDAS1 and CDAS2

- All three NCEP products are too fast near the coast
- Slow bias along the coast in CDAS1 and CDAS2

-                 FMA                               ASO

**Seasonal mean wind speed (m/s)**

## Zonal mean wind speed (m/s)

**Zonal mean wind speed (m/s)**

## Surface wind errors in NCEP models

- OBS = Mean of RSS, JPL, and SSMI

## GFS and CFS winds are very similar

Both models are too weak north and south of the equator in the Pacific but too strong in eastern  equatorial Pacific

GFS is too weak in the extratropics

- Both models are too weak north and south of the equator in the Pacific but too strong in eastern  equatorial Pacific
- GFS is too weak in the extratropics

**Annual mean wind speed (m/s)**

## 
Some errors in wind direction exist along 30S in GFS in FMA

Wind direction is accurate along the coast in FMA but inaccurate in JJA.  Model winds are easterly instead of southerly.

- Some errors in wind direction exist along 30S in GFS in FMA
- Wind direction is accurate along the coast in FMA but inaccurate in JJA.  Model winds are easterly instead of southerly.

**Seasonal mean wind vector (m/s)**

## GFS and CFS winds are too strong along the equator throughout the year

Wind differences are largest in ASO, the same months where the cold SST bias is largest in the CFS forecast

- GFS and CFS winds are too strong along the equator throughout the year
- Wind differences are largest in ASO, the same months where the cold SST bias is largest in the CFS forecast

**Seasonal mean wind (m/s)**

-                 FMA                                ASO

## 
Too strong easterlies persist through the 1 mo lead forecast

Cold SST bias increases in size and magnitude

Evolution of equatorial CFS wind speed indicates a cancellation of errors: SST induced westerlies cancel too strong easterlies

- Too strong easterlies persist through the 1 mo lead forecast
- Cold SST bias increases in size and magnitude
- Evolution of equatorial CFS wind speed indicates a cancellation of errors: SST induced westerlies cancel too strong easterlies

**Wind effects on SST**

**Notes:**
There is a 1 month lag in cold SST bias intensification and the effects are cumulative. The change in CFS wind speed errors with time is due to the fact that the CFS is coupled and is a balance of different errors.  Wind speed in the CFS decreases over time because of the warm bias.  The decrease in wind speed along the equator results from the adjustment of the wind due to the change in the SST gradient.  Westerly winds develop at the surface in response to SST gradient (and resulting pressure gradient).  There is a cancellation of errors, positive west-east SST gradient error reduces errors in wind speed which is too strong with realistic SSTs.  Correct the warm bias and wind errors would be even worse.

## CFS 4-mo lead SST forecast mean error (K)

**CFS 4-mo lead SST forecast mean error (K)**

- Too strong easterlies in GFS likely the reason for cold SST bias in the CFS forecast for the months of ASON
- Impact of wind errors on SEP warm bias is not clear

**Notes:**
GFS and CFS winds are too strong (cooler SST) but direction is wrong (easterly instead of southerly - warmer SST) so relationship between surface wind and the SE Pacific warm bias is not clear.  Further experiments need to be done using GDAS or observed winds to drive the ocean to determine the actual effect of surface wind on SST.

## Equation described by Crosby et al (1993)
CDAS1, CDAS2, GDAS:  Vector correlation generally over 0.6, lowest correlations occur over the cold tongues of the eastern tropical Pacific and Atlantic 
GFS:  Vector correlation is highest in the tropics

- Equation described by Crosby et al (1993)
- CDAS1, CDAS2, GDAS:  Vector correlation generally over 0.6, lowest correlations occur over the cold tongues of the eastern tropical Pacific and Atlantic
- GFS:  Vector correlation is highest in the tropics

**Vector Correlation**

**Notes:**
A perfect vector correlation occurs if the 2 datasets are identical, differ by a constant speed and/or direction.  In tropics the wind is driven by SST which is why GFS is good (used observed SST), in extratropics SST is driven by wind (which is unpredictable) so correlation is bad.

## Summary

- Uncertainty of time mean wind speed in satellite observations is about 0.5 m/s in the tropics and 1 m/s in the extratropics
- GDAS winds are very accurate
- CDAS1 is too slow in the tropics and CDAS2 is too fast in the mid latitudes;  both have wind direction errors along the west coasts of South America and Africa
- GFS and CFS winds are too strong in the Southeast Pacific and the eastern equatorial Pacific;  there are wind direction errors along the west coast of South America.
- Too strong easterlies in ASO in the GFS are associated with the eastern equatorial cold SST bias in the CFS forecast for ASON

**Notes:**
Bullet 4:  The impact of winds on Southeast Pacific warm bias is not clear without further experiments driving CFS with GDAS or observed winds.

## Additional Figures

## Vector Correlation =

- Tr

- Equation described by Crosby et al (1993)

- Covariance matrix of dataset 1

- Covariance matrices of datasets 1 and 2

**Notes:**
Equation is a generalization of the square of the 1-D correlation coefficient. It is computed from the covariance or cross-covariance matrices of each dataset. E11 is the covariance matrix of dataset 1, E12 is the covariance matrix of dataset 1 and dataset 2, etc. When expanded covariances of all 4 components are computed.

## Slide 25

## RMS error between observations and GDAS is about 0.3 m/s
RMS errors are largest in the tropics and extratropics

- RMS errors are largest in the tropics and extratropics

**RMS differences of annual mean climatology**

## GFS and CFS wind stress is too strong near the coast between equator and 25S
GFS is too strong in ASO along the equator while CFS is too weak
The too weak CFS wind speed in the equatorial Pacific is associated with the southeastern Pacific SST warm bias
Too strong easterlies in GFS likely the reason for cold SST bias in the CFS forecast for the months of ASON

- GFS is too strong in ASO along the equator while CFS is too weak
- The too weak CFS wind speed in the equatorial Pacific is associated with the southeastern Pacific SST warm bias
- Too strong easterlies in GFS likely the reason for cold SST bias in the CFS forecast for the months of ASON

**Seasonal mean wind pseudo stress**

**Notes:**
Remember the CFS here is free run which is a balance of different errors.  GFS wind is more relevant to CFS hindcast.  The SEP warm bias is not due to surface wind error?