A view of UT clouds and relative humidity using AIRS, CALIPSO, and CloudSat by Brian H. Kahn
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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
description
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. - PowerPoint PPT Presentation
Transcript of 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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0.100.080.060.040.020.00
Normalized Frequency
0.0 ≤ τ < 0.1 0.1 ≤ τ < 0.25 0.25 ≤ τ < 0.5 0.5 ≤ τ < 0.75 0.75 ≤ τ ≤ 1.0
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De ( ) µm
0.0 ≤ τ < 0.1 0.1 ≤ τ < 0.25 0.25 ≤ τ < 0.5 0.5 ≤ τ < 0.75 0.75 ≤ τ ≤ 1.0
• 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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0.0 < τ ≤ 0.1 0.1 < τ ≤ 0.25 0.25 < τ ≤ 0.5 0.5 < τ ≤ 0.75 0.75 < τ ≤ 1.0
( ) A
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RHic (%)
( ) D
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
0.1–0.3 0.3–1.0 1–3 3–10 10–30 30–100
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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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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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
