The impact of satellite observations over land and sea-ice surfaces within the ECMWF system Cristina Lupu, Niels Bormann, Reima Eresmaa The WMO 6th Workshop on the Impact of various observing systems in NWP Shanghai, China, May 10-13, 2016

Outline Surface-sensitive MW sounder data IR sounder & imager data Use over land and sea-ice at ECMWF OSEs study impact results FSOI evaluation IR sounder & imager data Impact results and challenges Conclusions

Use of surface-sensitive MW sounder data over land/sea-ice Use of surface-sensitive radiances requires reliable estimates of surface emissivity and skin temperature. Over sea: Accurate fast emissivity model (FASTEM), Sea-surface temperature (SST) Over land + sea-ice: Use surface emissivity retrieved from window channel observations and FG (“dynamic emissivities”, Karbou et al. 2006), complemented by an atlas where required. Chosen window channel should have similar frequency as sounding channels and good surface sensitivity. Skin temperature taken from land-surface model.

OSE study: Channels considered and their use over land/sea-ice Instrument Satellites Snow-free land Snow-covered land Sea-ice AMSU-A (clear-sky) Metop-A, Metop-B, NOAA-15, NOAA-18, NOAA-19 Channels 5-7 Channels 6-7 Channel 5 over N.Hem. ATMS S-NPP Channels 6-8; 18-22 Channels 6-8 - MHS (all-sky) Metop-A, Metop-B, NOAA-18, NOAA-19 Channels 3-5 Channel 3 Channels 3-4 SSMI/S F-17 Channels 9-11 Channels 10-11 Temperature-sounding in red; Humidity-sounding in blue; Channel-dependent orography screening also applied.

OSEs for surface-sensitive MW sounder data over land/sea-ice Experiments over 8 months: 2 June – 30 Sept 2014; 2 Dec 2014 – 31 March 2015 Base: No surface-sensitive MW sounder data over land and sea-ice Base + MW sea-ice: Add surface-sensitive MW sounders over sea-ice (i.e., 5 x AMSU-A, MHS, SSMI/S) Base + MW sea-ice + MW WV land: Add MW humidity sounders over land (i.e., ATMS, 4 x MHS, SSMI/S) Base + MW sea-ice + MW land: Add surface-sensitive MW temperature sounders over land (i.e., data usage as in operations)

Impact over sea-ice and land

Impact of surface-sensitive MW sounders over sea-ice and land Base + MW sea-ice + MW land Base + MW sea-ice vs Base, normalised difference in RMSE for Z 500 hPa, verification against own analysis Bad Good

Impact of surface-sensitive MW sounders over sea-ice and land Normalised change in Stdev error of vector wind, Base + MW sea-ice + MW land vs Base, Strong impact over extra-tropics/higher latitudes. Modest impact in tropics. Good Bad -0.04 -0.02 0.00 0.02 0.04

Short-range forecast impact against other observations Stdev(o-b) normalised by Base, global statistics, 8 months Good Bad Good Bad TEMP-T TEMP-q CONV-VW IASI H2O O3 Window/ lower T

Seasonal dependence of impact of surface-sensitive MW data over sea-ice and land Base + MW sea-ice + MW land Base + MW sea-ice vs Base, normalised difference in RMSE for Z 500 hPa, verification against own analysis June – Sept 2014 Dec 2014 – March 2015

Seasonal dependence of impact of surface-sensitive MW data over land and sea-ice Base + MW sea-ice + MW land Base + MW sea-ice vs Base, normalised difference in RMSE for Z 500 hPa, verification against own analysis. June – Sept 2014 Larger sea-ice extent Dec 2014 – March 2015

Seasonal dependence of impact of surface-sensitive MW data over sea-ice and land Base + MW sea-ice + MW land Base + MW sea-ice vs Base, normalised difference in RMSE for Z 500 hPa, verification against own analysis. June – Sept 2014 Less sea-ice Dec 2014 – March 2015

Seasonal dependence of impact of surface-sensitive MW data over sea-ice and land Base + MW sea-ice + MW land Base + MW sea-ice vs Base, normalised difference in RMSE for Z 500 hPa, verification against own analysis. June – Sept 2014 Less impact in winter: Difficulties due to snow? Sampling? Dec 2014 – March 2015

Seasonal dependence of impact of surface-sensitive MW data over sea-ice and land Normalised change in Stdev error of Z 500 hPa Base + MW sea-ice + MW land vs Base T+48 h 0.15 0.10 0.05 June – Sept 2014 0.00 -0.05 Dec 2014 – March 2015 -0.10 -0.15

Seasonal dependence of impact of surface-sensitive MW data over sea-ice and land Data coverage, MHS channel 4 (Metop-B) Base Base + MW sea-ice + MW land Aug 2014 Difference in sea-ice extent Not used over snow in winter Feb 2015

Impact from temperature and humidity-sounding channels

Impact of surface-sensitive MW humidity and temperature sounders over land Base + MW sea-ice + MW land Base + MW sea-ice + MW WV land vs Base + MW sea-ice, normalised difference in RMSE for Z 500 hPa. Bad Good

Short-range forecast impact against other observations Stdev(o-b) normalised by Base, global statistics, 8 months Good Bad Good Bad TEMP-T TEMP-q CONV-VW IASI H2O O3 Window/ lower T

Seasonal dependence of impact of MW humidity and temperature sounders over land Base + MW sea-ice + MW land Base + MW sea-ice + MW WV land vs Base + MW sea-ice Dec 2014 – March 2015 June – Sept 2014 Bad Good

FSOI: surface-sensitive MW sounders over land and sea-ice 1.53% MW land 1.59% MW seaice 2.27% MW land 0.87% MW seaice

Forecast sensitivity to observations impact (FSOI) - Globe Instr. FSOI %,Land %, Sea-ice AMSU-A 2.39 % 1.22 % ATMS 1.45 % 0.37% T sounding 1.07% q sounding - MHS 1.32 % 1.07 % SSMI/S 0.22 % 0.17 % Total 5.38 % 2.76% T sounding 2.61% q sounding 2.46 %

Conclusions Surface-sensitive MW sounder data over land and sea-ice provide significant positive forecast impact in the operational ECMWF system. Very significant positive impact from data over sea-ice over S. Hemis. Comparable impact from temperature and humidity-sounding channels over land. Results suggest significant seasonal dependence of the forecast impact, most likely due to changes in surface characteristics. N.Hemisphere impact much weaker over winter. Most likely due to limitations in surface emissivity or skin temperature estimation over snow, leading to a more restricted/sub-optimal use. S.Hemisphere impact appears to be linked to sea-ice extent. FSOI evaluation results are well in agreement with the OSEs impact study results.

Operational use of IR sounder data over land and sea-ice IR sounder radiances are currently more exploited over sea than over land: Over sea: ISEM sea-surface emissivity model; Over land: Limited number of channels insensitive to surface emission (emissivity is assigned default value 0.98 - independent of the wavenumber or SZA); a background error of 5K is assumed for the Tskin. Over sea-ice: Limited to channels in the long-wave CO2 absorption band; Instrument Satellites Sea Land Sea-ice IASI Metop-A/B 188 channels No data 162 channels AIRS Aqua 136 channels 48 stratospheric channels 88 channels CrIS S-NPP 77 channels 30 stratospheric channels 52 channels

Impact of operational IR radiances assimilated over land and sea-ice Experiments over 4 months: 2 June – 30 July 2014; 2 Dec 2014 – 23 January 2015 Base + IR seaice + land Base + IR seaice vs Base, normalised difference in RMSE for Z 500 hPa, verification against own analysis Bad Good

Trials to extend the use of advanced IR sounders data over land The set-up over land is just the same as over sea, but not over high orography Instrument Satellites Sea Land Sea-ice IASI Metop-A/B 188 channels 162 channels AIRS Aqua 136 channels 88 channels CrIS S-NPP 77 channels 52 channels Mixed impact on forecast scores (e.g., RMSE Z 500 hPa) and on the background fit to other observations (e.g., MW observations) Bad Good

Way forward The future use of infrared radiances over land is likely to rely on fundamentally different cloud detection and improved handling of skin temperature for satellite data assimilation.

Impact of emissivity modelling on BT simulations emis=atlas emis=0.98 BT differences between IASI observations and simulations RTTOV IR UWiremis land emissivity atlas (Borbas et al., 2007) Window ch. 901.5 cm-1 Assuming constant emissivity, the simulated IASI spectra in the window regions significantly deviate from measurements. Need good a-priori information of emissivity over land !

Surface skin temperature at ECMWF - issues Tskin is not independently observed; Highly reactive in space and time; Polar orbiting satellites have a very biased diurnal sampling of the skin temperature (2 passes per day) Complex to maintain, is changing during minimisation It is an independent variable, separate to the atmospheric temperature and skin temperature at other locations Atmospheric information aliases into Tskin and is “lost” Does not influence the model forecast of skin temperature; Strategy: Evaluate the possibility of moving away from sink variable to a full field control variable. Better characterize the background errors for Tskin.

Strategy for cloud detection over land Large uncertainties in surface emission make the current cloud detection for IR radiances unfit for use over land Cloud detection land using observed TB only So far experimenting with IASI only Initial attempts rely on four super-channels, each super-channel ~10-12 channels (1) Channels in wavenumber range 706—715 cm-1 (2) Channels in wavenumber range 722—740 cm-1 (3) Channels around wavenumber 875 cm-1 (4) Channels around wavenumber 962.5 cm-1 Two checks for presence of cloud in the field-of-view Sounding-channel check using super-channels (1) and (2) Check passed if data falls between these lines Window-channel check using super-channels (3) and (4) Check passed if data falls above these lines Clear Cloudy Clear Cloudy

Locations of clear data on a window channel Sea Snow or ice surface Desert Vegetation Tune the scheme for data over vegetation, desert and snow False alarms: Canada and tropical rainforests? FG-departure clear data (shown over vegetation) Non-gaussianity, cloud-contaminated data getting through?

Conclusions Surface-sensitive MW sounder data over land and sea-ice provide significant positive forecast impact in the operational ECMWF system. Very significant positive impact from data over sea-ice over S. Hemis. Comparable impact from temperature and humidity-sounding channels over land. Results suggest significant seasonal dependence of the forecast impact, most likely due to changes in surface characteristics. N.Hemisphere impact much weaker over winter. Most likely due to limitations in surface emissivity or skin temperature estimation over snow, leading to a more restricted/sub-optimal use. S.Hemisphere impact appears to be linked to sea-ice extent. IR sounder data over land and sea-ice – some progress has been made, but significant challenges persist. Tskin and the cloud detection are the main limiting factors in using more IR satellite sounding data over land.

Seasonal dependence of impact of surface-sensitive MW data over sea-ice and land Data coverage, AMSU-A channel 6 (Metop-B) Base Base + MW sea-ice + MW land Aug 2014 Difference in sea-ice extent Reduced use over snow in winter Feb 2015

Seasonal dependence of impact of surface-sensitive MW data over sea-ice and land Data coverage, AMSU-A channel 6 (Metop-B) Base Base + MW sea-ice + MW land Aug 2014 Some data rejections over Sahara, probably due to skin temperature issues Feb 2015