Total Column Water Vapour from the Split-Window Bands for EarthCARE
MSI and its Possible Applications
ESA-JAXA Pre-Launch EarthCARE Science and Validation Workshop 13 - 17 November 2023

J. El Kassar1 , C. Carbajal Henken1 , R. Preusker1
November 14, 2023
1

Freie Universität Berlin, Institute of Meteorology, Berlin, Germany

Why include TCWV as parameter retrieved from MSI?

• water vapour (WV) is the key ingredient in cloud formation and weather: humidity-aerosol-cloudinteractions• WV absorbs across a wide range of wavelengths and plays crucial role in the radiation budget• a warmer/hotter atmosphere can hold more WV: more extreme precipitation and positive
feedback in radiative forcing... and MSI features a band sensitive to moisture at 12 µm relative to 11 µm!

1Physical BackgroundWhy can we ”see” WV in the thermal-infrared (TIR)?

• water vapour more effiently absorbing at 12 µm: colder signal in the ”dirty” band• split-window difference (swd) correlates with total column water vapour content (TCWV)

1simulated with RTTOV v12, Saunders, R. et al. 2018, Geosci. Model Dev.
2

Why can we ”see” WV in the thermal-infrared (TIR)?

• water vapour more effiently absorbing at 12 µm: colder signal in the ”dirty” band• split-window difference (swd) correlates with total column water vapour content (TCWV)

1simulated with RTTOV v12, Saunders, R. et al. 2018, Geosci. Model Dev.
2

Algorithm DescriptionImpact on observations in the split window

Three main influence factors (for clear-sky cases!) over land surfaces:
1. atmospheric temperature and humidity profile
2. surface emissivity
3. surface temperature
We use the CAMEL emissivity atlas included in RTTOV to approximate the emissivity. Profiles aretaken from numerical weather prediction. Thus, with RTTOV we can create a forward function:
F (TCWV , Tskin ) → (BTclean , BTclean − BTdirty )3

Adjustment of atmospheric profiles• TCWV scales the full humidity profile• TSkin scales the layer temperature closest to surfacepressure
tcwv (i1 )q(i1 ) = q(i0 ) · R 0q(i0 )p(1)surftbottom (i1 ) = tskin (i1 ) − (tskin (i0 ) − tpsurf (i0 ))(2)

4The TIR TCWV Algorithm

Short Description:• forward model: simulates BTclean , BTclean − BTdirty from TCW , Tskin• inverse model: optimal estimation1 (Rodgers 2000) ⇒ iterative change of TCWV and Tskin• prior knowledge/first guess of profiles is based on ERA5 forecasts• additional info (e.g. wind speed) also from ERA5 forecasts
Algorithm has been applied on
Meteosat Second Generation - Spinning Enhanced Visible and Infrared Imager (MSG-SEVIRI)1andSentinel 3 - Sea and Land Surface Temperature Radiometer (S3 SLSTR)→ flexible retrieval framework which can be adapted for EarthCARE MSI

1El Kassar et al. 2021, Atmos.
5

Caveats of the TIR TCWV AlgorithmLess sensitivity to...
• humidity concentrated at the very lowest level• significant humidity amounts above 500 hPa• very low surface temperatures• thick boundary layers with no vertical temperature gradient... if the sensitivity is much lower, the NWP first guess is not altered!
However, over thin cirrus the algorithm overestimates the water vapour content: good cloud mask
necessary!
⇒ the algorithm is more of an update/sharpening of first guess atmospheric profiles(from 0.25◦ to 0.5 km !)6

Exemplary Results of TIR TCWVMSG SEVIRI TCWIV: Validation over Germany for 3 Years, mostly land surfaces:

TCWV in mkg2 and GNSS TCWV on top1,2

3 years worth of matchups: slight wet bias

1

El Kassar et al. 2021, Atmos.
1
Gendt et al. 2004, J. Meteorol. Soc. Japan
7

Sentinel 3 SLSTR TCWV at 1km resolution• TIR TCWV provides more detail on atmsopheric moisture content• sensitive enough to reveal lee waves over the Meditteranean• cloud mask is needed to filter erroneously high values

8Sentinel 3 SLSTR TCWV at 1km resolution: zoom in⇒ at 1 km resolution small scale TCWV patterns revealed! Cannot wait for MSI’s 0.5 km

9Applications...

• TCWV prior to cloud formation → aerosols?
• inflow of low level humidity into clouds → change in cloud microphysics?
• surrounding TCWV around dissipating clouds
• ...

10

Summary and Outlook

Summary/Conclusions• a TIR TCWV product could well complement the EarthCARE (MSI) products• a reasonable accuracy and precision can be achieved using the split window alone• fine details in TCWV fields can be revealed• low sensitivity to TCWV under specific conditions → in this case just use NWP
Outlook• global validation study of the algorithm S3 SLSTR11