Cloud fraction in midlatitude cyclones: observations vs models

Catherine Naud, Columbia UniversityCollaborators: James Booth (Columbia), Tony Del Genio

(GISS), Derek Posselt (Michigan Univ.), Sue van den Heever (CSU)

NASA-Terraqua NNX11AH22G, CloudSat NNX10AM20G

SH cloudiness in models

• Trenberth and Fasullo (2010): too much solar absorption in the southern oceans in CMIP3 models => less clouds when compared with ISCCP in 40-60oS band

• What about reanalysis ERA-interim and MERRA?• Cloud fraction exceeds 80% in most of SH oceans according to MODIS =>

lower in reanalysis & ISCCP10-year mean cloud cover: MODIS-Terra & ISCCP ERA-interim and MERRA

SH clouds in extratropical cyclones

Large frequency of occurrence of extratropical cyclones in SH oceans=> can models represent cyclone cloud fractions?

Cyclone number per month per 10ox10o region

• Useful tool: cyclone centered cloud fraction composites

• Collect 4 summers (NDJFM) of extratropical cyclone locations in SH

• Associate daily MODIS, MISR and L2 CloudSat-CALIPSO cloud fraction to each cyclone

• Average in cyclone centered grid

Comparison with ERA-interim and MERRA

- Apply same technique on 2D total cloud fraction from ERA-interim and MERRA (same period)

- Analyze SH summer cyclones

- Compare to MODIS and MISR

Cloud fraction:- At least 90% along warm

front and poleward of the low

- At least 70% within cyclones- Both ERA-interim and

MERRA produce less clouds- More drastic with MERRA

South pole^||||||||||||||

Equator

Observed Cloud fraction in SH summer cyclones

Observational uncertainty:MODIS vs MISR vs CloudSat-CALIPSO: mostly within 5% except for poleward edgePoleward: MISR less than other two datasetsEquatorward: MISR > CloudSat-CALIPSO > MODIS Impact of optical thickness, broken clouds, daytime vs day+night,…

CloudSat-CALIPSO minus MISR MODIS minus MISR MODIS minus CloudSat-CALIPSO

See Naud et al., submitted to JGR 2013

Difference in cloud fraction: SH summer

Differences where larger than diff(MODIS-MISR)ERA-interim 8-14% underestimate, west and equatorward of the lowMERRA ~20-35%, largest to the west of the low MODIS CTP, CTT and MISR CTH indicate spatial correlation between ERA-I bias and CTT and between MERRA bias and CTP/CTHDifference with obs. and between each other=> Large scale issue or parameterization?

Problem linked to large scale?- 850 hPa horizontal winds: very similar

between the two reanalysis and close to MISR cloud-top wind

- Same thing for 850 hPa vertical velocities

No obvious correlation with dynamics or moistureIssue probably with parameterizationsCloud misrepresented in MERRA at the back of cold front:-low-level clouds (MISR CTH < 2.5 km, CTP > 740 mb)-Mostly liquid: MODIS liquid cloud fraction > ice fraction < 30% -Possibly broken cloudsProblem with PBL or cloud or shallow convection scheme?

PBLH & LTS

- PBL heights: ERA-i > MERRA everywhere in cyclones, with max difference in equator-west quadrant BUT difference definition

- LTS: theta_700 – Theta_surf=> virtually identical between ERA-interim and MERRA=> LTS < 15 K where larger MERRA bias

Cumulus ill-represented in MERRA? Shallow convection the issue?

Fig. 6, Bodas-Salcedo et al. 2012: ISCCP cloud regimes

Conclusions and future work• Both ERA-interim and MERRA underestimate cloud fractions in SH

cyclones• ERA-interim bias 8-14%, low bias largest for MERRA 20-35% and

max bias coincides with region of low, liquid and broken clouds• Consistent with:

- Williams et al. (2013): find lack of clouds at back of cold fronts in collection of GCMs- Bodas-Salcedo et al. (JCLI 2012): UK Met Office model has similar problem, not enough clouds at back of cold front (stratocumulus clouds and ‘transition’ regime in ISCCP cloud regimes), improved through modification of boundary layer scheme- New PBL scheme in GISS-modelE2 (i.e. deeper PBL) improves SH cloud cover

Are PBLH really different between the 2 models: profiles of θe hint at 200 m difference, would affect stratocumulus cover

Or is the shallow convection different? hit the limit of compositing usefulness