CMSAF water vapour in comparison to radiosondes and CHAMP

CMSAF water vapour in comparison to radiosondes and CHAMP

Ralf Lindau

Water vapour from ATOVS

Global daily fields of Layered Precipitable Water LPW are calculated by kriging method on 90 km resolution.

Advantage of kriging : An error map is available for each field.

Example: 1.10.2004

850 – 700 hPa

Radiosondes

173 GUAN

(GCOS Upper-Air Network) stations well distributed over the globe.

It‘s the resolution, stupid

For any comparison of two data sets resolution is crucial.

If resolutions are not equal, the often actually seriously presented conclusion would be:

The low resolved observations underestimate high values and overestimate low values.

ATOVS fields: Daily , 90 km

Radiosondes: 4 times a day, point measurements

Thus, average the radiosondes over 1 day.

But still Radiosonde data include additionally the spatial variance of daily

means within 90 x 90 km

Variability of Water Vapour

Famous paper:

Lindau, R. and E. Ruprecht, 2000:

SSM/I-derived total vapour content o ver the Baltic Sea

compared to independent data, Met.Zeitschrift, 9, No.2, 117-123.

1 day include 8 mm² of variance 90 by 90 km²

include 3 mm² of variance The spatial variance of temporal means

must be smaller than that of individuals (3 mm²).

October 2004

+ 3.82 mm + 17 %

High correlation: r = 0.95 But wet bias of 3.82 mm²

Happy with correlation ?

Correlation reduction due errors is:

1 - r = e² / (² + e² )

= 7.5 mm² / 225 mm²

= 0.03

More than half of the scatter is explained by random errors in ATOVS and RS.

But there is still the bias....

The error of ATOVS is explicitely calculated within kriging.

The mean error variance for October 2004 and for those 173 gridboxes, where RS data is available is:

e

= 6.19 mm

The error variance of daily means from RS is calculated by:

Internal variance / observ number:

e

= 7.65 mm

Different layers

+ 2.35 mm

+ 21 % + 0.18 mm

+ 5 %

1000 – 850 hPa 700 – 500 hPa

Time series of the bias

The bias is not confined to October 2004.

It persists through

10 month

Discriminating GUAM data

Ocean / Land Height above sea

or is it the ice surface in the Antarctica?

Ocean, Height, Ice ?

+ 2.85 mm + 16 %

+ 1.68 mm + 9 %

- 0.18 mm - 7 %

Different First-guesses

No

NCEP

Different first-guess (taken as basis for the retrieval) result in strong differences.

Example: 1.9.2006, 700-500 hPa

ATOVS vs Radiosondes

No

GME

NCEP

- 0.82 mm - 3 %

+ 3.67 mm + 14 %

+ 7.08 mm + 27 %

The corresponding bias vanishes for „No first guess“

and is doubled, if NCEP is used.

... and what about Champ ?

Example for 1 month of Champ data.

4239 obs/month 1 obs/10 min

Irregularly spreaded over the globe

ATOVS vs Champ

850 – 700 hPa700 – 500 hPa - 3.20 mm

- 15 %

- 0.15 mm - 5 %

+ 0.02 mm + 2 %

Conclusion

ATOVS vs radiosondes

- ATOVS has a wet bias compared to radiosondes.

- Bias is decreasing with height.

- It persists through all discrimination experiments.

- First guesses play an important role for the retrieval.

Champ vs ATOVS

- Champ has dry bias compared to ATOVS

- (thus, seems to agree with RS, but no direct comparison possible)

- Bias is decresing with height.