The Role of Optically Thin Liquid Clouds in the 2012 Greenland Ice Sheet Surface Melt Event

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Dept. AOS & CIMSS
Kyle Nelson - UW-Madison
The Role of Optically Thin
Liquid Clouds in the 2012
Greenland Ice Sheet
Surface Melt Event
Kyle Nelson
Department of Atmospheric and Oceanic Sciences
Cooperative Institute for Meteorological Satellite Studies
University of Wisconsin-Madison

M.S. Thesis Presentation
August 6, 2014

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Introduction
•  July 2012: new record in surface melt
extent over Greenland Ice Sheet (GIS)
•  Observed surface melt over the entire GIS
•  Bennartz et al. (2012): Thin, low-level,
liquid clouds occurred very frequently over
Summit, Greenland when melt occurred
– One factor that warmed surface above
freezing

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Background
Bennartz et al. (2012)

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Surface Melt Extent
From Nghiem et al. (2012)

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Research Questions
•  What range of cloud optical depth (and LWP)
yields a positive surface radiative forcing?
•  What is the sensitivity of cloud base height to
surface radiative forcing?
•  What is the frequency of occurrence of thin
liquid clouds over the GIS in 2012?
•  Did thin, liquid clouds contribute to the July
2012 surface melt event over the entire GIS?

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Methods
•  Radiative transfer modeling
•  Satellite remote sensing
– MYD06 (Col. 5 & 6) Standard Cloud Product
– CALIPSO: CALIOP and IIR
– PATMOS-x MOD02 1.6μm
– Cloud Phase Determination
•  ECMWF ERA Interim Reanalysis

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Cloud Surface Radiative Forcing
ΔFnet = FSW
↓
− FSW
↑
+ FLW
↓
− FLW
↑
FSW,net = FSW
↓
− FSW
↑
FLW,net = FLW
↓
− FLW
↑
CSW =
∂FSW,net
∂a0
Ac
∫ da
CLW =
∂FLW,net
∂a0
Ac
∫ da
Cnet = CSW +CLW
!
•  CSW, CLW & CNET are the
shortwave, longwave,
and net cloud forcing
for the surface
•  FSW,net & FLW,net are the
net shortwave and
longwave fluxes at the
surface
•  Ac is the total cloud
amount
•  a is the cloud fraction

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Solar Zenith Angle vs SRF
Total

Longwave

Shortwave

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Cloud Base Height vs SRF
2 4 6
−250
−200
−150
−100
−50
0
50
100
Cld Base Ht: 0.5km; SZA = 65
Cld Tau
SurfaceRadiativeForcing
2 4 6
−250
−200
−150
−100
−50
0
50
100
Cld Base Ht: 1km; SZA = 65
Cld Tau
2 4 6
−250
−200
−150
−100
−50
0
50
100
Cld Tau
2 4 6
−250
−200
−150
−100
−50
0
50
100
Cld Tau
2 4 6
−250
−200
−150
−100
−50
0
50
100
Cld Tau
2 4 6
−250
−200
−150
−100
−50
0
50
100
Cld Tau
Fresh Snow 4 of 7Fresh Snow 4 of 7Fresh Snow 4 of 7Fresh Snow 4 of 7Fresh Snow 4 of 7Fresh Snow 4 of 7Fresh Snow 4 of 7Fresh Snow 4 of 7Fresh Snow 4 of 7Fresh Snow 4 of 7Fresh Snow 4 of 7Fresh Snow 4 of 7Fresh Snow 4 of 7Fresh Snow 4 of 7Fresh Snow 4 of 7Fresh Snow 4 of 7Fresh Snow 4 of 7Fresh Snow 4 of 7Fresh Snow 4 of 7Fresh Snow 4 of 7Fresh Snow 4 of 7Fresh Snow 4 of 7Fresh Snow 4 of 7Fresh Snow 4 of 7Fresh Snow 4 of 7Fresh Snow 4 of 7Fresh Snow 4 of 7Fresh Snow 4 of 7Fresh Snow 4 of 7Fresh Snow 4 of 7Fresh Snow 4 of 7Fresh Snow 4 of 7Fresh Snow 4 of 7Fresh Snow 4 of 7Fresh Snow 4 of 7Fresh Snow 4 of 7Fresh Snow 4 of 7Fresh Snow 4 of 7Fresh Snow 4 of 7Fresh Snow 4 of 7Fresh Snow 4 of 7Fresh Snow 4 of 7Fresh Snow 4 of 7Fresh Snow 4 of 7Fresh Snow 4 of 7Fresh Snow 4 of 7Fresh Snow 4 of 7Fresh Snow 4 of 7Fresh Snow 4 of 7Fresh Snow 4 of 7Fresh Snow 4 of 7Fresh Snow 4 of 7Fresh Snow 4 of 7Fresh Snow 4 of 7Fresh Snow 4 of 7Fresh Snow 4 of 7Fresh Snow 4 of 7Fresh Snow 4 of 7Fresh Snow 4 of 7Fresh Snow 4 of 7Fresh Snow 4 of 7Fresh Snow 4 of 7Fresh Snow 4 of 7Fresh Snow 4 of 7Fresh Snow 4 of 7Fresh Snow 4 of 7
Total

Longwave

Shortwave

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Summary of Modeled Cloud Forcing
•  Determined range of cloud optical depth
and LWP that contribute to surface
warming
– Optical Depth: 1.5-6.5
– Liquid Water Path: 10-40 g/m2
•  Assuming 10μm particle effective radius
•  Maximum increases with solar zenith angle

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MODIS: Moderate Resolution
Imaging Spectroradiometer
•  Passive sensor,
measuring radiances
at 36 wavelengths
•  Spatial resolutions of
250m to 1km
•  Using Aqua-MODIS,
part of NASA’s A-Train
–  1:30pm local equator
crossing time

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MYD06 Standard Cloud Product
•  Visible and infrared techniques
–  Cloud-particle phase (ice vs. water, clouds vs. snow)
–  Effective cloud-particle radius
–  Cloud optical thickness
•  Infrared only technique
–  Cloud-top temperature
–  Cloud-top height
–  Effective emissivity
–  Cloud phase (ice vs. water, opaque vs. non-opaque)
–  Cloud fraction
•  Visible only technique
–  Cirrus reflectance

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Liquid Clouds vs All Clouds (MODIS), July 2012

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Thin Liquid Clouds vs All Clouds (MODIS), July 2012

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MODIS Optical Depth Distribution

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Liquid Water Path Distribution - MWR

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Matchups: MODIS/CALIOP/IIR
•  Cross-instrument comparison of cloud
optical depth
•  Determine which sensor or combination of
data from different sensors produces a
LWP distribution using ground based
observations from the microwave
radiometer at Summit, Greenland

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CALIPSO: Cloud-Aerosol Lidar and Infrared
Pathfinder Satellite Observations
•  Launched April 28, 2006
•  Part of NASA’s A-Train
•  CALIPSO combines an active LIDAR
instrument with passive infrared and
visible imagers to diagnose the vertical
structure and properties of thin clouds and
aerosols over the globe.

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CALIOP: Cloud-Aerosol Lidar with
Orthogonal Polarization
•  CALIOP is a two-wavelength polarization-
sensitive LIDAR that focuses on the vertical
distributions of clouds and aerosols and their
properties
•  Vertical resolutions of 30m
•  335m ground-spot spacing
•  Level 2 products include
–  Aerosol and cloud feature masks
–  Aerosol subtype
–  Extinction
–  Optical depth

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IIR: Imaging Infrared Radiometer
•  3 channel imaging radiometer in the thermal
infrared
•  Channels at 8.65μm, 10.6μm and 12.05μm
•  IIR measurements are combined with the
LIDAR information enabling the retrieval of
the size of ice particles in semi-transparent
clouds.
•  The pairing of 10.6μm and 12.05μm channels
is sensitive to small particles, while the
8.65μm and 12.05μm channels are more
sensitive to large particles

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CALIOP vs MODIS MYD06

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IIR vs MODIS MYD06

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IIR vs CALIOP

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IIR: Thin Liquid Clouds

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Alternate Methods Needed
•  MODIS Optical Depth
– Standard 2-channel visible retrieval
– Or 1.6μm & 2.1μm
•  MODIS Liquid Water Path
– MODIS effective radius & optical depth
•  All based on visible or infrared channels
– Challenging over highly reflective and cold
surfaces
•  Can we use 1.6μm or 2.1μm channels?

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Issues: MODIS 2-channel Retrievals

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Solution: Single Channel Retrieval

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Solution: PATMOS-x & Look Up Tables
•  Pathfinder Atmospheres – Extended
•  PATMOS-x MOD02 (Terra)
–  Level-1B Calibrated Geolocated Radiances
–  Raw 1.6 micron reflectance
–  Mapped to a .1°x.1° grid
–  One measurement per gridbox per day
•  Measurement closest to NADIR
–  Used in conjunction with a look-up table
•  Work backward from reflectance to optical depth
•  Provided by A. Walther

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PATMOS-x Gridboxes

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Sensitivity to Choice of Re - Liquid

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Was there a significant difference
between July 2011 and July 2012?
•  No melting of the GIS interior in July 2011
•  Melting over the entire GIS in July 2012

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Number of Cloudy Days: July 2011 vs 2012

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Percentage Cloudy – 2°x2° box over Summit
July
2011
July
2012
Calendar Day
1
31
PercentCloudy
100
0
100
0

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July
2011
July
2012
Calendar Day
1
31
FractionofThinCloudsvsAllClouds
100
100
0
Fraction of Thin Clouds – 2°x2° at Summit0

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Cloud Phase Determination
•  PATMOS-x MOD02 3.7μm reflectance
•  Similar method used by Key & Intrieri
(2000) and Pavolonis & Key (2003) with
AVHRR
•  Threshold between ice and liquid cloud
– 3.7μm reflectance >0.07 and
– Cloud top temperature >243K

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Sensitivity to Choice of Re - Liq

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Sensitivity to Choice of Re - Ice

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July
2011
July
2012
Calendar Day
1
31
FractionofThinLiquidCloudsvsAllClouds
100
100
0
Fraction of Thin Liquid Clouds – 2°x2° at Summit0

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Frequency of Liquid vs All Cloud – July 2011 vs 2012

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Frequency of Thin Liq vs All Cloud – July 2011 vs 2012

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To Review:
•  ICECAPS surface and PATMOS-x satellite
data show a high presence of optically
thin, liquid clouds over the GIS during the
record melt event in July 2012
•  In July 2011 and 2012, the frequency of
occurrence and spatial coverage of thin,
liquid clouds was similar

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Another factor in addition to cloud
cover must have influenced the
surface temperature over the GIS to
push the temperature above freezing

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ECMWF ERA Interim
•  Qualitatively assess the general
atmospheric circulation and temperature
advection in the proximity of the GIS
•  Monthly Means at select pressure levels
– Geopotential Height
– Temperature
– U- and V-wind

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Conclusions
•  Optically thin liquid clouds, regardless of cloud
base height, played a key role in the 2012 and
2011 melt events by increasing near-surface
temperatures across the GIS
•  The work of Bennartz et al. (2013) is extended here
by expanding the study domain from a point
observation at Summit to the entirety of
Greenland by leveraging satellite data products
•  Radiative transfer modeling showed that these
optically thin clouds warm the surface during the
day regardless of cloud base height

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Conclusions (cont.)
•  Standard cloud products from the MODIS,
CALIOP and IIR sensors did not reliably detect
optically thin, liquid clouds over ice and snow
•  Frequency of occurrence and geospatial location
of optically thin liquid clouds over the GIS was
found to be nearly identical in July 2011 and 2012
•  With observed melting over almost the entire GIS
in July 2012 (Nghiem 2012), warm air advection is
likely the dominant contributor
–  This agrees with the findings of Bennartz et al. (2013)
and Neff et al. (2014)

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Future Research
•  Frequency of thin, liquid clouds in other years
–  Significant surface melt
–  No surface melt
•  Repeat study over the Arctic Ocean to
determine the role of thin, liquid clouds on
the surface energy budget of sea ice
•  Expand the time domain to the entire MODIS
satellite record to establish a 15+ year
climatology of location and frequency of
occurrence of optically thin liquid clouds in
the Arctic

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Acknowledgements
•  Jeff Key – Research Advisor
•  Steve Ackerman – Academic Advisor
•  Ralf Bennartz
•  Andy Heidinger
•  Andi Walther
•  Denis Botambekov
•  SSEC PEATE Group
•  PATMOS-x Team
•  Tristan L’Ecuyer – MS Committee
•  Grant Petty – MS Committee
•  Mark Kulie
•  Erik Gould
This work was supported
by the NOAA Climate
Data Records Program

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Questions?

Meteorologist | Education & Outreach Specialist
University of Wisconsin-Madison

kyle.nelson@ssec.wisc.edu
@wxkylenelson

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Look Up Table Calculations

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Selected References
•  Ackerman, S., R. Holz, R. Frey, E. Eloranta, B. Maddux, and M. McGill (2008): Cloud
detection with MODIS. Part II: Validation, J. Atmos. Oceanic Technol., 25, 1073–1086, doi:
10.1175/2007JTECHA1053.1.
•  Bennartz, R. et al. (2013): July 2012 Greenland melt extent enhanced by low-level liquid
clouds. Nature Vol. 496, 83-86, doi: 10.1038/nature12002.
•  Curry, J., J. Schramm, W. Rossow and D. Randall, 1996: Overview of Arctic Cloud and
Radiation Characteristics. J. Climate, 9, 1731–1764. doi:
10.1175/1520-0442(1996)009<1731:OOACAR>2.0.CO;2
•  Heidinger, A. et al. (2013): The Pathfinder Atmospheres Extended (PATMOS-X) AVHRR
Climate Data Set. BAMS, doi: 10.1175/BAMS-D-12-00246.1 (in press).
•  Key, J. and A. Schweiger (1998): Tools for atmospheric radiative transfer: Streamer and
FluxNet. Computers and Geosciences, 24(5), 443-451.
•  Key, J. and J. Intrieri (2000): Cloud particle phase determination with the AVHRR. J. Appl.
Meteorol., 39(10), 1797-1805.
•  Neff, W. D. et al. (2013): Continental heat anomalies and the extreme melting of the
Greenland ice surface in 2012 and 1889. Journal of Geophys. Research: Atmospheres. doi:
10.1002/2014JD021470 (in press).
•  Nghiem, S. V. et al. (2012): The extreme melt across the Greenland Ice Sheet in 2012.
Geophys. Res. Lett. 39, L20502, doi: 10.1029/2012GL053611.
•  Shupe, M. D. and J. Intrieri (2004): Cloud radiative forcing of the Arctic surface: the
influence of cloud properties, surface albedo, and solar zenith angle. J. Clim. 17, 616–628.

The Role of Optically Thin Liquid Clouds in the 2012 Greenland Ice Sheet Surface Melt Event

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