a view of ut clouds and relative humidity using airs, calipso, and cloudsat by brian h. kahn

A view of UT clouds and relative humidity using AIRS, CALIPSO, and

CloudSat

by

Brian H. Kahn

Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA

presented at:

HIRDLS Science Team Meeting Wednesday January 30th, 2880

NCAR, Boulder, CO

Thin cirrus retrievals in the tropics via AIRS

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TC (K)

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Normalized Frequency

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De ( ) µm

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• Retrieval based on Yue et al. (2007), J. Atmos. Sci.

• Results presented in Kahn et al. (2007), Atmos. Chem. Phys. Discuss.

Thin cirrus + RHI retrievals via AIRS

• RHI calculation following Gettelman et al. (2006), J. Climate

• Results presented in Kahn et al. (2007), Atmos. Chem. Phys. Discuss.

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RHic (%)

(B)

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( ) A

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Motivation – Inter-hemispheric differences in UT RHI

Gettelman et al. (2006), J. Climate

• What are the causes and implications?

Cirrus nucleation + aerosol differences, dynamic variability reflected in T(z), variability in q(z)? Others?

An illustration of AIRS RHI + CloudSat/CALIPSO cloud profiles

CloudSat/CALIPSO ground track

Cirrus observed by CloudSat/CALIPSO

Products used:• RHI (AIRS)• Cloud profiles (CSat + CAL)• IWC (CSat)• Cloud type (CSat)

AIRS RHI: Vertical structure, higher RHI @ cloud top

RHI limited to: (1) q > 15 ppmv(2) T ≤ 243 K(3) Quality Flag = “Best” or “Good”

AIRS RHI most useful in broken/thin Cirrus & clear sky

Purple: CirrusBlue: AltostratusRed: CumulusDark Red: Nimbostratus

AIRS RHI & CloudSat IWC anti-correlated

• Variability from scene-to-scene

• Information about cirrus formation/evolution?

RHI & IWC anti-correlated for 5 days of data

• Anti-correlation of IWC and RHI consistent with some in situ aircraft spirals (e.g. MIDCIX campaign)

• 25–50% of Cirrus with IWC ≤ 1–10 mg m3 is supersaturated

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RHI

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IWC bins ( mg m3 )

RHI dependent on cloud/clear sky & season

• All distributions are global (July 2006 and January 2007)

• Note January ‘07 has smaller dynamic range in RHI

• CALIPSO RHI closer to clear sky: thin Cirrus produces low RHI bias

• Kahn et al. (2007), Atmos Chem. Phys. Discuss.

Hemispheric & seasonal variance in RHI

SH Cloudy Sky RHI

• RHI less variable in SH

• Similar differences for CALIPSO-centric view of clouds & clear sky

• What controls the variability?

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PDF

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RHI

CSat_All_SH_normdjf CSat_All_SH_normjja CSat_All_SH_normmam CSat_All_SH_normson

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RHI

CSat_All_NH_normdjf CSat_All_NH_normjja CSat_All_NH_normmam CSat_All_NH_normson

NH Cloudy Sky RHI

Hemispheric & seasonal variance in T and RHI

NH 1 Temperature variability

• Width of PDFs between T and RHI correspond: dynamical control of RHI PDF?

• Similar view using CALIPSO-observed clouds & clear sky

• BUT: nice correspondence not true in SH (not shown)

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RHI

CSat_All_NH_normdjf CSat_All_NH_normjja CSat_All_NH_normmam CSat_All_NH_normson

NH Cloudy Sky RHI

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Normalized PDF

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1–sigma Temperature (K)

sig_NH_ta_all_pres_djf_cld sig_NH_ta_all_pres_jja_cld sig_NH_ta_all_pres_mam_cld sig_NH_ta_all_pres_son_cld

Take Home Messages & (Near) Future Work

• Combined A-train observations reveal global-scale, long-term insights

• AIRS cirrus + RHI PDFs reveal physical relationships consistent with other measurements

• Hemispheric/seasonal differences modulate RHI distributions within cloud and clear sky

• T variability appears to have asymmetric hemispheric correspondence with RHI PDFs

Important to constrain dynamical influences to detect other controlling factors in RHI

• Continued investigation into linkage between T and q variability, and seasonal/hemispheric characteristics of RHI PDFs

Acknowledgments: AIRS, CloudSat, CALIPSO science, algorithm and processing teams, NASA post-doctoral program (NPP), and NASA radiation sciences program for funding support