Assessing the Ecological Impact of the
Antarctic Ozone Hole
Using Multi-sensor Satellite Data
Dan Lubin, Scripps Institution of Oceanography
Kevin Arrigo, Dept. of Geophysics, Stanford University
Osmund Holm-Hansen, Scripps Institution of Oceanography
Enhancement of UV Flux at Antarctic Surface
nm -1 )
-2
Palmer Station
McMurdo Station
Ushuaia, Argentina
Barrow, AK
San Diego, CA
http://www.biospherical.com
Palmer Station UV Solar Spectra
spectral irradiane (microwatts cm
•Measured since 1988
•NSF UV Monitoring Program
10
2
101
100
10-1
10-2
10
Day 296 16:00 Z (210 DU, ovc)
Day 326 13:00 Z (334 DU, clear)
Day 296 Theoretical Clear Sky
-3
10-4
290
300
310
320
330
wavelength (nm)
340
350
360
The Antarctic Marine Food Web
Higher Predators
(leopard seals, orcas)
Grazing by Krill
(Euphausia superba)
Primary Production
Field Work on Ecological Effects
•Began in late 1980s, primarily at Palmer Station, west of
Antarctic Peninsula
•Smith et al. (Science, 1990) ICECOLORS: 2-4%
reduction in primary production in marginal ice zone
(MIZ)
•Holm-Hansen et al. (Photochem. Photobiol., 1993),
reduction < 1% integrated over entire Southern Ocean
Need for Satellite-Based Assessment
•Comprehensive field work is expensive, limited in time
and place.
•Previous estimates of total impact on Southern Ocean
primary production are rough extrapolations from point
measurements to larger areas.
•Satellite data now offer complete coverage of the
Southern Ocean for evaluating key forcing factors.
Surface UVR Algorithm Development
co-locating TOMS, AVHRR, SSM/I in 3 regions
•Sea ice more influential
than clouds on TOA UV
radiance.
•Parameterization of UV sea
ice albedo as function of sea
ice concentration.
•Method developed to use
TOMS and SSM/I alone.
•see Lubin and Morrow,
JGRd (2001).
AVHRR
cloud ID using
near-IR (3.5 mm)
channel
1 Aug
1992
A 1 Sep
1992
B
1 Oct
1992
C 1 Nov
1992
D
1 Dec
1992
E 1 Jan
1992
F
Seasonal
variability in sea
ice concentration
0
10
20
30
40
50
60
70
Sea ice concentration (%)
80
90
100
Total Column Ozone
from TOMS
Sea Ice Concentration
from SSM/I
Cloud Effective Optical Depth
from TOMS Reflectivity
UV-A (315-400 nm) Flux
from d-Eddington model
UV-B (280-315 nm) Flux
from d-Eddington model
Action Spectra
10
-2
biological weighting function
10 -3
Photoinhibtion in Antarctic
Phytoplankton (Neale et al., 1998)
10 -4
10 -5
10 -6
10 -7
10 -8
280
Erythema
(McKinlay & Diffey, 1987)
300
320
340
360
380
wavelength (nm)
400
420
Biologically Weighted Flux
(photoinhibition in phytoplankton)
Comparison with Palmer Station
UV Monitor Data
1200
1200
A
B
y = 1.005x - 10.354
R2 = 0.88
1000
900
800
600
600
400
300
200
Measured
Modeled
0
0
Oct 1992
Nov 1992
Date
Dec 1992
0
300
600
900
1200
Measured 305 nm daily dose (J m -2 nm -1 )
Geographic Assessment of Enhanced UV Fluxes
• Spectral flux weighted by action spectrum for
photoinhibition in Antarctic phytoplankton
• Define climatological UVR:
– in terms of mean cloud attenuation, sea ice, 1979 total ozone
– evaluate 20-year standard deviation s
• Enhancement: where photoinhibition flux exceeds
climatological mean by 2s or more
• Geographically significant enhancement: where the
enhanced fluxes intersect biomass as determined by
SeaWiFS
• Lubin et al., GRL 2004
UVR Enhancement at Palmer Station, Spring 1992
B. Criteria for Enhanced UVR
-2
A. Comparison with NSF UV Monitor
dose rate (weighted W m
305 nm flux (W m -2 nm -1 )
0.06
)
0.0016
satellite
measured
0.05
0.04
0.03
0.02
0.01
0
240
260
280
300
320
day number of 1992
340
360
0.0012
0.0010
0.0008
0.0006
0.0004
0.0002
240
C. Total Column Ozone
1992
1979
concentration (%)
Dobson units
280
300
320
day number of 1992
340
360
100
350
300
250
200
150
100
240
260
D. Sea Ice Concentration
450
400
1992 satellite dose
climatological satellite dose
climatological dose + 1.96 sigma
clear sky dose
0.0014
260
280
300
320
day number of 1992
340
360
1992
climatological
80
60
40
20
0
240
260
280
300
320
day number of 1992
340
360
Use of SeaWiFS to Locate
Phytoplankton Biomass
Fraction of Southern Ocean Biomass
Under Enhanced UV Photoinhibition Flux
monthly average biomass fraction
35
September
October
November
December
30
25
20
15
10
5
0
80
85
90
year
95
UVR Enhancements by Southern Ocean Sector
Lubin et al., GRL 2004
A. Pre-Discovery Years
50
surface biomass fraction (%)
1979
1981
1983
1985
60
40
30
20
10
0
-180
70
surface biomass fraction (%)
70
-120
-60
0
60
bin center longitude
120
50
40
30
20
10
70
1992
1994
1996
50
40
30
20
10
0
-180
-120
-60
0
60
bin center longitude
120
180
1987
1988
1989
1990
60
C. Early-Mid 1990s
60
B. Post-Discovery Years
0
-180
180
surface biomass fraction (%)
surface biomass fraction (%)
70
-120
-60
0
60
bin center longitude
120
180
D. Late 1990s
1997
1998
1999
60
50
40
30
20
10
0
-180
-120
-60
0
60
bin center longitude
120
180
Spectral Flux at the Sea Surface
Ed (,0,t)  1 d Edd (,0  ,t)  1  i Edi ( ,0 ,t)
sin 2 (   w ) tan 2 (   w ) 
dr  0.5  2


2
sin (   w ) tan (   w ) 
• Edd and Edi are direct and diffuse components
• surface reflection divided into direct and diffuse components,
both of which are sum of specular reflection and reflectance
from sea foam
• sea foam reflectance a function of wind stress
• Fresnel’s law for specular reflection
In-Water Optics

Ed (z)  Ed (0 )e
K (z)z
Kd (z)  Kdw  K dp (z)  K dDet (z)  KdCD OM (z)
• Beer’s law for spectral flux penetration
• Diffuse attenuation coefficient Kd(z) partitioned
into components describing attenuation by pure
water, phytoplankton, detritus, and chromophoric
dissolved organic matter.
In-Water Optics - Components
•Pure Water: coefficents
from Smith & Baker (1981)
•Plankton (chlorophyll)
from Sathyendranath et al.
(1989)
•Detritus from work by
Arrigo et al. (1998)
•CDOM from work by
Mitchell and Holm-Hansen
(1991); Arrigo et al. (1998)
Kdw(z) 
bbw(z)  aw(z)
m
bbp (z)  a p (z)Chla(z)
*
Kdp (z) 
m
S (   400)
KdDet (z) 
aDet (440, z)e 1
KdCD OM(z) 
m
aCDOM (400,z)e
m
S 2 (  400)
Phytoplankton Production
• G is phytoplankton growth rate
(d-1) calculated from
PP(z,t)  G(z,t) C Chla Beff (z,t)
temperature and light
availability
• C/Chl a is the phytoplankton
C:Chl a mass ratio (50)
• Beff is effective phytoplankton
concentration
• G is modeled in terms of a

 PUR(z,t) 

kT( z) 
G(z,t)  G0 e
1 exp 
temperature-dependent


E

k



maximum rate and a light
limitation term


Cumulative Exposure to UVR
• Throughout the day, the
physiological inactivation B (z,t)  B (z,t  t)e  Hi nh (z,t )
eff
of algal biomass (effective eff
biomass Beff) is expressed
t
700nm
by reducing Beff with
Hihn (z,t)  t 0  280nm A( )Ed (, z,t)ddt
increasing UVR exposure.
• At dawn, Beff(z,t) is set =
Chl a (z,t)
• Vertical mixing: simulated
by averaging Beff over
MLD, then applying this
average to each layer
within MLD
Comparison with Field Observations:
% decrease in C-fixation relative to no UVR
MODEL
64 S, 72 W
ICECOLORS
1979
1992
ozone hole
1990
+UVA+UVB
55
59
4
56-77
+UVA
48
21
48
30
0
9
45-65
8-20
40
36
11
43
36
16
3
0
5
35-80
15-42
21-60
Surface
+UVB
5 m depth
+UVA+UVB
+UVA
+UVB
Beff (mg Chl a m-3 )
Hinh
0
Station A
59.19 S, 56.89 E
04 October
•Photoinhibition dose Hinh
varies with time and depth,
30% greater in exp. run than
control at surface
•Assess individual
contributions of UV-B and
UV-A
•Substantial UV-A
contribution to Hinh and Beff
•Panel B: 1979 (control)
•Panel C: 1992 (exp.)
0
0.05
0.10
0.15
0
5
5
10
10
15
15
20
0.05
20
25
A
30
0
0
1992,
1979,
1992,
1979,
1992,
1979,
UVA+B
UVA+B
UVA
UVA
UVB
UVB
Beff (mg Chl a m -3 )
0.05
0.10
0.15
0
0.20
B
0
0.15
0.20
12:00
12:30
13:00
13:30
14:00
14:30
15:00
25
30
0.10
Daily production (mg C m -3 )
0.5 1.0 1.5 2.0 2.5
3.0
0
10
5
20
30
10
40
15
50
60
20
25
30
C
12:00
12:30
13:00
13:30
14:00
14:30
15:00
70
80
90
100
D
1992,
1979,
1992,
1979,
1992,
1979,
1992,
1979,
UVA+B
UVA+B
UVA
UVA
UVB
UVB
No UV
No UV
Total Change in
Primary Production
350
A
300
Temporal Variation in
Primary Production Loss
over Southern Ocean
250
200
150
100
1979
1992
50
0
0.7
B
R = 0.85
25
0.6
20
0.5
0.4
15
0.3
10
0.2
0.1
% loss in production
0.0
5
% decrease in ozone
-0.1
Aug
Sep
Oct
Date
Nov
Dec
0
Major Conclusion of Small Impact
•
•
•
•
Surface UVR-induced losses of primary production can be several percent,
with large UV-B component
When integrated to 0.1% light depth, loss of primary production throughout
Southern Ocean, due to enhanced UV-B, is < 0.25%
Major reasons: strong UV-B attenuation with depth, location of most ozone
depletion over Antarctic continent, temporal mismatch between maximum
ozone loss and maximum phytoplankton abundance
Several sensitivity analyses did not alter this conclusion:
–
–
–
–
–
–
–
changing MLD and mixing time
temperature dependence of primary production
Photoacclimation parameter Ek, specifying saturation of photosynthesis
detrital and CDOM absorption
phytoplankton absorption
variability in Action Spectrum
Instantaneous versus cumulative exposure to UVR
Necessary Future Work
•Improve parameterizations throughout model
in-water radiative transfer, processes very near sea ice
•Repeat experiments for even deeper and longer-lasting ozone
holes of late 1990s
•Consider regional ecosystem effects