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SORCE MEETING – 20-22 Sept 2006
Wed 20 Sept – Gary Rottman Chair
Tom Wood (new PI) SORCE Overview – Measurements, Instrucments, Future
SSI = Solar Spectral Irradiance
TSI = Total Solar Irradiance = ntegrated over all wavelengths
S’ = 342 W/m2 for S = I = 1368 – 1371 W/m2
UV absorption and scattering dominated by atomic and molecular species
Visible – near IR mostly due to water (clouds) and aerosols
Climate forcings 1850-present (level of understanding) – Jim Hansen – Proc NAS 1998 –
high GG, low aerosols and solar
INSTRUMENTS
TIM = Total Irradiance Monitor (Greg Kopp)
SIM = Spectral Irradiance Monitor 200-2700 nm (Jerry Harder)
SOLSTICE 115-320 nm (Bill McClinktock, Matry Snow, big friendly guy)
XPS = XUV photometer system 0.1-27 and __ (Tom Woods, balding, glasses, Kevin
Kline)
25 Jan 2003 – 2008
(TIME instrument sees 10-100 nm – different NASA instrument)
TIM/TSI: very stable record – no problems, no anomalies. 4 bolometers, 1 used daily, 3
for calibration. Degradation due to daily exposure is well characterized.
SIM operating nominally – strongest degradation in UV, less in IR, improvements in
progress. Deg. In Prism and diode, dependent on wavelength and time.
SOLSTICE grating spectrometer with PM tubes – little degradation – functioning
nominally except for an entrance slit anomaly in Jan 2006 (switch between stellar and
solar got stuck briefly) Will leave Solstice A in only solar position. Solstice B can still
do stellar calibrations. Little degradation – less than 3% per year.
XPS – no degradation – functioning nominally. Limiting filter wheel movement since its
anomaly in Dec 2005 - stopped moving 41 hours, seems ok now, but staying in position
6 to be safe. Calibrate once a month by moving to position 4.
New XPS flare algorithm has less variability, more physics-based, agrees better with other
measurements. Spectral shape much less in 4-14 nm range.
All data available at SORCE website and LASP.colorado.edu/lisird/
Future: Nothing planned to 2012 at this point! SORCE extended to 2012? Glory 20072012? NPOESS canceled – maybe delayed from 2013 to 2016? Was to run to 2040. Has
money to integrate instruments but not to build them. Recycle SORCE instruments?
SORCE funded through 2008. NASA review this spring wil consider extension to 2012.
Started near solar max, hope to extend to next solar max.
Important to overlap instruments in time, calibrate.
DETAILS of spectral variability:
Photospheric vis (500 nm) usually out of phase with chromospheric UV (Mg II) – rarely in
phase, when not dominated by sunspots.
Long-wavelength spectrum matches Planck derivative for sun 0.4 K higher
Greg Kopp, LASP (delicate, curly fair hair) TSI – the incoming side of the equation
TSI = received by Earth. Large decrease (0.34%) in Oct 2003 due to large sunspot.
COOL MOVIE!
Earth’s radiation and energy balance diagram – everyon euses one by Kiehl and
Trenberth 1997: Kiehl, J. T. and Trenberth, K. E., 1997
Bull. Amer. Meteor. Soc., 78, 197-208.
8 instruments measured solar irradiance in past 3 decades – TIM has lowest stated
uncertainty (350 ppm)
Meeting last year between the several instrument teams. Most have multiple channels.
How much inter-instrument consistency between channels? Cavity variations…
sometimes exceed stated uncertainties (in ACRIM), lower uncertainties in TSI (301 ppm)
TIM’s greatest uncertainty in power application method – pulsed, not DC.
Advantage? narrow incoming aperture, broader aperture close to detector. This could
cause a systematic underestimation of TSI by TIM, systematic overestimation by others.
Aim for 0.01% accuracy. (100 ppm) Glory is building TSI radiometer facility to
compare TSI instruments on an absolute scale (when they come down? Before they go
up? Ground-based units?)
DeToma and White 2006 Sol Phys fitting TSI records – Empirical modeling – TIM best
fit
Q: How well does SSI fit with TSI? TSI pretty stable at 1361-2 W/m2, SSI varies at
each wavelength depending on sunspots, etc.
SUMMARY:
TIM will next fly on GLORY, but probably not on NPOESS
TIM values 4.5 W/m2 lower than other TSI instruments. Still working on resolving this.
Jerry Harder – Role of VIS-IR / SIM in Climate Science (pearl-built – curly dark hair)
Importance of an absolute solar spectrum and solar variability to Earth radiation and
climate roblems
Intro to SIM instrument
Solar Variability and its impact on Earth Atmosphere
Conclusions and activities
Response to climate is highly wave;ength dependent – need spectrum
Direct surface heating at near UV and longer wavelength
Indirect preocesses - abs UC in stratosphere
Greatest relative var in UV (indirect), greatest absolute var in mid-vis (direct)
Relative uncertainty in solar forcing is large – must be se[parated form anthropogenic
forcings
SIM measures broadband solar spectrum. TSISIM = 96% TSITIM (large fraction of
wavelength range: 200 nm – 3000 nm)
GET HIS PLOT OF SIM – ABSORPTION by atmosphere – RECEIVED at Earth (sent
email) (Wolfson asked about Reflection – Jerry answered – not included – assume it’s at
the equator with atmosephere but no clouds).
Bill McClintock (skinny dark-haired graying – like Becky Leidner)
Outline: 15 yrs of solar UV irradiance obs with UARS and SORCE – morphology and
variance – climate implications
FUV = 0.02 % TSI – declining as we approach solar min – absorbed by O2 in
thermosphere, which expands significantly at solar max
MUV = 3.4 % TSI – emitted by photosphere – pretty steady despite approach to solar
min - abs by O3 in stratosphere – strong correlations Chandra and McPeters 1994
MG II h&k emission – tracks UV irradiance variability – chromospheric emission lines –
¼ of chromospheric emission! – highly correlated with FUV
MgII index = core/wing emission – largely independent of instrument degradation –
shows 10-25% variation on solar rotation time scales
FUV irradiance comes mostly from transition region – correlated with 27 day rotation
not well-correlated with coronal activity (e.g. F10.7 = proxy for coronal emission
or optically thin emissions, which exhibit limb brightening)
UV monitoring is NOT included on NPOESS. SORCE/SOLSTICE is NASA’s last
planned UV irradiance expt.
Marty Snow – the role of spectral resolution in the MgII Index (big jolly guy)
Rotational variability = Max/Min of MgII index – strong variability near 280 nm
associated with (a sunspot?)
Wings go up when core goes down – blocking of photospheric emission
Ex: pick absorption? core at 280 and emission? wings at 276 and 284
Ratio of core/wings – removes instrumental effects
Plot vs date, compare to time-resolved Solstice spectrum
SORCE/Solstice can measure this many times per day:
Normal scans every half hour on most orbits
Quick scans (5 min)
Mini scans - just around MgII (2.5 min)
Rapid scans (47 s) only emission core, since wings change slowly
One hour per day they do a high-cadence scan.
Q: Can this give space-weather data to SEC?
Session 2 - Radiative Energy Budget
Chair: Peter Paluski - previous session – photons entering the atmosphere –
Now – photons leaving the atmosphere
Bruce Wielicki couldn’t make it
Norm Loeb (nice little engineer type - black polo shirt) - Determination of the Earth's
Radiation Budget from CERES
CERES = Clouds and the Earth’s Radiant Energy System
Raschke showed discrepancies in GCM’s downward solar flux – embarrassing (Global
Climate Modelers – we have only one Sun)
Clouds, Radiation, and Climate – largest uncertainty in global climate sensitivity over the
next century is CLOUD FEEDBACK – can amplify or dampen global warming
Cloud feedback shown to be linear (ref?)
Uncertainties / errors:
 instrument calibration (absolute and relative)
 spectral sampling (want broadband radiative flux)
 spatial sampling
 angle sampling
 temporal sampling (need to capture diurnal variability)
CERES= broadband satellite radiometer (0.3-5 micrometer, 0.3-200, 8-12), 20 km
footprint, global coverage each day
CERES = sensor web = up to 11 instruments on 7 spacecraft – integrate data
Example: Integrated flux at top of atmosphere – angular resolution- DIFFERENT
ALBEDOS inferred from different models, instruments, times?
Need to interpolate and average fluxes, spatially and temporally
Bottom lines: uncertainties of 5-10 W/m2 at top of atmosphere (less uncertainty over
smaller regions). Hope to get down to 3.
SEAWIFS spacecraft http://oceancolor.gsfc.nasa.gov/SeaWiFS/
Science – Palle et al – used Earthshine to measure Annual SW (shortwave) TOA flux
anomaly – alarming – tested – not clear that Moon is the ideal platform for measuring
Earth’s radiation
Longwave anomalies – differences between instruments – need overlap
Comparison of radiative anomalies: ISCCP and ERBS consistent with each other.
AVHRR not.
Bottom line: since __, Decrease in SW 3.1, increase in LW 1.6 W/m2, net change -1.5?
Net flux coming in must go into ocean: compare CERES net radiation vs Global ocean
heat storage – BUT Winieki and Lyman et al see ocean cooling of 0.13 - 1.7 W/m2?
Work in progress…
Global 3-yr averages disturbing, despite improvements to algorithms. Still 4W
imbalance for ERBE, getting worse despite consistency checks – still checking…
Aim to provide community with advice for optimal global net flux balance “closure”…
S=1365, S’ = 341.25 W/m2 = SW + LW
Predictions – current papers –
Uncertainties dominated by low clouds
Climate sensitivity linear in cloud radiative forcing
NPOESS just eliminated the CERES follow-on sensor called ERBS
Should fly CERES FM-5 on NPP in 2010 – would delay the most serious gap
issue to 2015.
Still need a plan for broadband global data to 2015.
SUMMARY: CERES > ERBE
 Improved accuracy of ROA fluxes by factor 2-5
 radiative flux profiles for surface, within atmosphere, TOA
 stable data record – 5 yrs – good to 0.02 W/m2 per decade
 consistent with SEAWIFS
 Uncertain future due to revised NPOESS plan.
Peter Pilewskie, LASP (tall Barney Rubble)
Overview of the Radiation budget in the lower atmosphere
Radiative properties of ice clouds
Cirrus clouds may have been cooling more than we thought.
CRYSTAL-FACE experiment – no evidence of small (<5m) ice crystals from
optical remote sensing (9 July 2002) Measurements match predictions without
SIC
Albedo varies in wavelength and time. (SSFR: Solar Spectral Flux
Radiometer)
Net radiative cloud forcing: ERBE shows cooling from stratus, CERES doesn’t?
Application of cloud retrievals to ROA energy budget: how well do the simulated
irradiance fields based on satellite retrieved cloud data… match measured spectra?
Ex: cloud simulated from MAS, lidar, radar data (S. Schmidt).
Use simulated clouds to calculate irradiance (P.Yang) – good match to measurement
Do the same at absorbing wavelengths – not bad
Cloud retrievals in the presence of aerosol layers? Optical thickness…radiative
forcing… “aerosol relative forcing efficiency” is fairly linear with wavelength –
strongest forcing at shortest wavelengths
Ellsworth Dutton (grey beard, full head of hair, distracted look, bolo, high waist,
longwinded) NOAA, Earth System Research Laboratory, Boulder, CO, Surface
Radiation Budget Observations: From instantaneous point measurements to long-term
global means - Progress and Challenges (with emphasis on broadband downdwelling
components)
Same energy budget diagram – OCEAN STORAGE? Noted on bottom – will he discuss
this?
Components of surface radiation budget depend on
*
* long list
For climate applications – models are complex - need systematic confirmation:
Ground-based observations ↔ models ↔ satellite-based data
GEBA = Global Energy Balance Archive from 1919-2003 – needed better resolution
GEWEX, WCRP, SRB, Baseline-Surface Radiation Network (BSRN)… 3600 stationmonths of 1-minute data since June (year?) (P. Stackhouse)
Improving SRB calibration standards… World Radiation Reference 1975, Solar Diffuse
Measurements (11 independent within a few watts of each other), …
Relative temporal variations: compare satellite (CERES) and ground-based
measurements for surface flux… same shapes of time series
GEWEX: downwelling longwave (LWD) radiation measurements show promise for
greenhouse detection studies – (incoming IR) correlates with 2m air temperature –
close to GCM predictions and ISCCP database
Global (solar) dimming? Tom Woods mentioned it earlier… 2004 G. Stanhill et al,
Gilgen et al, Liepert – this guy feels it’s probably not happening – none of these used data
after 1990 – then he looked at his own records and found a “brightening” Wild et al and
Pinker et al, Science 2005
What happened since 2001? Dutton et al JGR 2006 (Looks to me like both
dimming and brightening are within the uncertainties in data, for different instruments.)
South pole solar irradiance correlates with sunspot number! Just for fun…
Tom Ackerman, (portly, bulgy red forehead, trim greying beard) Pacific Northwest
National Lab, Washington; University of Washington, The Radiation Budget of an
Atmospheric Column in the Tropical Western Pacific good rough MODEL
Background:
 Climate model sensitivities to forcing changes vary by factorx3 or more
 Mostly due to clouds and water vapor
 Because cloud models vary
 How can we tell if a given model is simulating cloud-radiation interactions well?
 Does new parameterization improve model performance?
Kiehl and T figure should not be gospel – consistency NE accuracy – could be 20 W off
on any amount.
Model evaluation – need to know radiation budget at TOA, surfrace, absorption in
column, heating rate profile – everywhere, always. Start small – at tropics.
Atmospheric Radiation Measurement Program – Tropical Western Pacific Locale:
Nauru, Manus, Darwin (Australia)
Data sources: TOA geostationary satellite data hourly
Surface – ARM 1-minute solar radiation fluxes – direct and diffuse
Computed fluxes and heating rates from ARM column observations
Calculated heating….
Model output from NCAR Community Atmosphere Model (CAM) with prescribed
observed seasurface temps (SST), with embedded cloud system model (multi-framework
model)
Compare measured with computed fluxes for 110 days –good matches!
Differences: TOA diffs due to ocean surface albedo. Some local cloudiness.
Column absorption 90 W/m2 constant in time for clear sky = TOA – surface
1-day points (hourly data averaged over a day) vary by about 20 W/m2.
Heating increases inside ice clouds, decreases below the clouds
Heating calculations look pretty consistent…
CAM has some funny wiggles from cumulus parameterization for mixing – deviations
from classical moist adiabat. Models can generate excess clouds, or in the wrong places.
Other models have too many clouds, too high, incorrect water path.
He played with model parameters to see what matched data better… ran climate model
as a forecasting model…
Roger Davies, University of Auckland, New Zealand (trim, nearly bald, British manner
and nose) –Constraints on the Interannual Variation of Global and Regional TOA
Radiation Budgets Inferred from MISR Measurements
Climate 101:  T4 = S (1-A) / 4 -…
Most important effect – cloud albedo (shortwave) ,
greenhouse effect (longwave) 45% due to clouds, 33% due to water vapor, … but this is
instantaneous, not radiative-convective equilibrium.
MISR on Terra satellite – observation concept – 9 view angles at earth surface - + 70.5 to
– 70.5 degrees - stereo view … consistent climate data records from 5/2000 to present
NASA’s Multi-angle Imaging SpectroRadiometer (MISR)
http://www-misr.jpl.nasa.gov/
MISR expansive spectral albedo
Earthshine vs CERES – all have shortwave anomalies
What about effective height changes? Reduced high cloud fraction in ITCZ (increased
low cloud fraction)
Spectral albedo anomaly was pretty flat since 2000, but dropped this past year – perhaps
because of reduction of arctic ice?
Effective cloud height anomaly has been dropping, but recently is rising. Several 0.1
W/m2.
Steven Dewitte Royal Meteorological Institute of Belgium, Brussels Time-Space
Complete Measurement of the Earth Radiation Budget (pretty eyes, acne scars, big
young guy) http://gerb.oma.be, http://www.ssd.rl.ac.uk/gerb/, http://ggsps.rl.ac.uk/
Can we put the Earth in a calorimeter? Surround it with satellites and measure
everything.
GERB will measure three spots over Earth for full coverage. Two launched so far, one
over Africa (GERB 1, launched second)
ERB instruments with high spatial resolution: (polar/low orbit) Nimbus, ERBE, ScaRab,
CERES, GERB (Geostationary Earth Radiation Budget experiment)
ARG: Measure reflected solar flux, Emitted thermal flux
Radiation Balance Image – Diurnal cycle – role of clouds – ocean heat storage
First data released March 2006
Tony Slingo (sat by him for lunch, next table at dinner – adult daughter ill, skinny doctor
with GI – trim, graying, nice)
University of Reading, United Kingdom Observations of the Earth’s Radiation Budget
from Geostationary Orbit and from the Surface http://www.esa.int/SPECIALS/MSG/
Meteosat-8 launched 2002 – with first GERB, SEVIRI – both have 15-min time
resolution - great
Meteosat-9 launched 2005 – with second GERB, …
Ruth Comer did Principle Component analysis (better than FT) of diurnal variation of
Outgoing Longwave Radiation (emitted IR)
PC1 shows diurnal cycle of surface temp – nighttime cooling, then rapid warming in
morning
PC2 shows diurnal cycle of clouds – coldest at 1800 hrs, narrower cold period, wider
warm period
http://www.nercessc.ac.uk/~rec/writeups/monitoring_report.pdf#search=%22comer%20meteosat%20prin
ciple%20component%22
Radagast project (Lord of the rings Wizard) http://radagast.nerc-essc.ac.uk/
Radiative Atmospheric Divergence using ARM mobile facility GERB and AMMA
Stations
ARM mobile facility in Niger: radiometers, Radar, aerosol sampling, IR spectrometer,
radiosondes
AMMA = African Monsoon Multidisciplinary Analyses
Staring down on surface to discern structure of clouds, stmosphere. Very dry in summer,
very moist in winter – great place to wait for clouds to change. 30:1 variation in column
water vapor. Monsoon starts in May – dewpoint temperature raises.
Dust layers – biomass layers – aerosols…
Observations of the impact of a major Saharan dust storm on the Earth’s radiation
balance – Slinger et al – submitter to GRL: Dust flows NE → clouds flow down, south
Optical depth up to 3 (can’t see the Sun through it) – lasts for days? Solar fluxes goes
down from 1000 to 700 W/m2? No direct flux – only diffuse flux.
Sally McFarland et al divergence calculations → modeled aerosol sizes (PNNL
collaborator with Tom..)
Great staff operating this mobile facility. Will be there all of 2006. Just coming out of
monsoon into dry season.
Eric Richard – Poster summary
Full spectrum SSI / UV SSI
Claus Fröhlich, Physikalisch-Meteorologisches Observatorium Davos, World Radiation
Center, Switzerland
Comparison of the WRC-85 Solar Spectral Irradiance with RSSV1 and the SPM of
VIRGO/SOHO
Mark Weber, University of Bremen, Germany
Solar UV/Vis/NIR Spectral Irradiance from SCIAMACHY and GOME
Atmospheric instruments – short term solar data – MgII index correlations
Marty Snow, LASP, University of Colorado, Boulder
UARS and SORCE SOLSTICEs: Calibrations and Comparisons
Long-term UV records
Matt DeLand, Science Systems and Applications, Inc., Lanham, MD
Maintaining the Solar UV Database in the 21st Century
Plus his summary from yesterday’s workshop – summary of multiple instruments
High-resolution Synthetic spectra
Robert Kurucz, Harvard-Smithsonian Center for Astrophysics, Cambridge, MA
High Resolution Irradiance Spectrum from 300 to 1000 nm
Ambitious – theoretical?
Juan Fontenla, LASP, University of Colorado, Boulder
The Solar Radiation Physical Modeling System
Semi-empirical
Jeff Morrill, Naval Research Laboratory, Washington, DC
A Model of Long-Term Variability of Solar UV and EUV Irradiance
Rocket data and CaII images – solar surface features – quiet sun and sunspots
Data products
Marty Snow, LASP, University of Colorado, Boulder
The LASP Interactive Solar Irradiance Database (LISIRD), EUV, Xray, several decades
Pancratz – SORCE data & products… Barry Knapp, LASP, University of Colorado,
Boulder SORCE Solar Irradiance Data Products
Miscellaneous
Greg Kopp, LASP, University of Colorado, Boulder
Could You See an Earth-Type Planetary Transit of a Solar-Type Star? Another Use of
TIM Data
Antony Clarke, University of Hawaii, Honolulu
Biomass Burning and Pollution Aerosol over North America: Organic Components and
Their Influence on Spectral Optical Properties and Humidification Response
Guoyong Wen, NASA GEST and NASA GSFC, Baltimore, MD
Deriving Historical TSI Variations from Lunar Borehole Profiles
Julia Saba, Lockheed Martin, ATC Solar & Astrophysics Lab, Greenbelt, MD
Rapid Solar Cycle Onset – Potential New Climate Study Tool?
Longterm SXR flux and sudden intensity rise at cycles 22-23 in just 2 solar rotations
Frank – summary of yesterday’s workshop… TIMED SEE
Julie Sāba – Goddard etc. – global jump in SXR in 1997 just before increase to solar max
– global blossoming of sunspots – looks like global magnetic relaxation event up to
surface – helicity
Thursday morning
Judith Lean – Solar Radiative Forcing – NRL
Solar irradiance variability -> forcing:




observations of total and spectral
* models of sunspot and faculae
* comparisons with sorce and TIM / Sim
Predictions?
Background – Sun to Earth – radiation and particles
Energy balance – Sun heats earth to 255 K – GHG add 33 K
Solar radiative processes depend on geography and altitude
Forcing: S’ = 341.5 W/m2 = 1366/4 – great record back to befoe 1980 – 3 cycles!
Total variation 0.1%, less in longer wavelengths, 10% in UV/XR
Faculae brighten, sunspots darken (close competition, in our middle-aged sun)
Q: How is it different in older stars and younger stars?
Faculae brighter in UV, sunspots brighter in vis-IR
Historical solar activity – longer term variability - climate change
GET HER PLOT OF Be and C14 in Maunder Min and Medieval Max
Longer-term reconstructions – longer-period variations
Wang and Sheehy model slow growth in mean solar flux over centuries…
Solar and anthropogenic climate signals
GISS shows ENSO with land and ocean temps
Pittock 1978 sun-ozone (and climate) connections are “experiments in autosuggestion”
HAH
GISS and GSFC TOMS - Judith combines everything to show effects
http://www.giss.nasa.gov/research/news/20050208/
stratosphere responds to UV – climate coupling – change in ozone profile – increase O3
above 29 km you cause cooling, and vice versa – Lacis et al 1979
Dynamical coupling via wind-wave interactions Shindell et al 2003, Rind et al 2003
USE THESE IN CLASS?
Q: Solar min – NAO centered in different place? (too fast – ask her)
Lean et al 1995 – pre-industrial T rises correlated with solar cycle?
Climate response to radiative forcing: DT = kF
K = climate sensitivity IPCC range 0.2-1.0 C/Wm-2, paleoclimate 0.75
Solar irradiance cycle: DT = 0.1 C, F = 0.15 Wm-2, k = 0.67
More atmophseric than oceanic signal?
Bottom line – uncertainties not only in solar forcing, but also in other forcings and in
models.
SUMMARY – current questions
How and why does solar irradiance vary
Are there variability mechanisms other than spots and faculae
Are long-term changes occurring in addition to the 11-year cycle?
Climate:
How and why does climate respond to wavelength dependent irradiance variations?
What are the roles of land, atmosphere, and oceans, in direct surface heating?
What are the indirect effects of radiative and dynamical vertical atmospheric soupligns
Are solar induced global surface temperature changes limited to 0.1-0.2 c? bond and van
loon thing there may be lager effects, e.g. indirectly due to rainfall…
Mechanisms for significant hydrological cycle responses?
Q: could Maunder Min recur? When?
A: Judith – there is 80 and 210 cycle and few thousand years. Paul Damon tried to put it
together… Sallie Baliunas probability distribution… Yes there will probably be another
one, hard to tell just when
Klaus – reconstructions based on cosmogenic isotopes
Roger Pielke (big bald guy, thin moustache, looks like a Peters, under 50?) Regional and
Global Climate Forcings – The Need to Move Beyond a Focus of the Radiative Forcing
of the Well-Mixed Greenhouse Gases
IPCC assessment is too narrow – radiative forcing understanding for 2000/1750 – there
are a lot of other poorly understood effects, like soot, etc., which contributes to
uncertainty in CO2…
“I disagree with a lot of what Jim Hansen says…”
Ocean heat content is the most robust measure we have: JM Lyman, Willis, Johnson
GRL 2006 in press
http://www.osdpd.noaa.gov/PSB/EPS/SST/climo.html sea surface temperatures
New or under-recognized human climate forcings
Biogeochemical effect of CO2, nitrogen decomposition, 5 more…
New climate change metrics are needed…
Change in proportion between latent and _ heat fluxes – natural landscape provides
potential heat for storms
Change in regional water cycles
Changes in land use change precipitation… ag drains marshes... higher temps 0.6 K (not
GG) and lower min temps (stronger sea breeze drawn to higher peak land temps)
Conclusions
Globally and zonally averaged data are not locally useful.
He’s mad about committee’s he’s been on.
GW NE climate change. Ex: land use -> CC w/o GW
Climate models are bad at predicting climate change
Instead of reducing CO2, focus on a “vulnerability paradigm”, locally tailored. (Fair
enough)
IPCC needs to recognize local human forcings.
(He probably advocates population control)
You have an atmospheric-centric perspective. This is minor.
(Predictably, audience fought with him.)
Mark Weber (small arms) University of Bremen, Germany Solar Variability and its Links
to Ozone-Climate Interaction
Processes responsible for ozone variability: chemistry, solar variability, volcanic
eruption, anthropogenic emission, ENSO, QBO, stratospheric transport… and these
interact.
Coupling between chemistry and transport: O3 buildup in winter due to planetary
wave driving (Brewer-Dobson circulation) GOME TOZ ratio
Ozone hole worst in SH in October
Planetary waves and residual circulation (Dobson): upwelling at lower lats, deceleration
of stratospheric westerlies, down at poles
Strng polar night jets + cold polar strstosphere -> polar O3 loss and reduced transport
Chlorine activation… stratospheric chlorine loading… peaked at 1997
Planetary waves -> warming at tropics
Solar max – warmer stratosphere …
Bill Collins (short curly fair hair, gentle guy, flat face), National Center for Atmospheric
Research
Boulder, CO Radiative Forcing by Greenhouse Gases and its Representation in Global
Models
(studied with Gene Parker, 2 students after Tom Bogdan)
Obs effects for rad effects of GHG
Current estimates of “ since 18th C
Simulation of climatic effects of “
more
…
Harries et al 2001 – changes in brightness of GHG since 1970 – great agreement with
model – CH4 huge, CO2 second- direct radiometric signature
Upward trend in LW emissions from Davos (maybe world leaders will eventually notice)
Radiative effects of GHGs from 18th C to 2005 – well understood, good agreement
between models
Future: uncertainties
Emission scenarios -> climate change scenarios -> climate assessment (next IPCC
coming out in 2007)
Radiative forcing and climate sensitivity – can we calculate it accurately? Not really …
compare GCM codes with radiative (LBL – line by line?) codes… remove differences
between models… he compared 16 groups submitting simulations from 23 AOGCMs to
the IPCC models
Enormous range in surface SW emission (there is one GCM that doesn’t include CO2)
LW differences in models are not large – GHG increase forcing
Forcing by methane or nitrous oxide – none GCM models include it for SW
There are even sign errors in SW from GCMs.
LW good – water vapor on surface dominates everything
(no aerosols – all clear sky)
Summary – no sign errors for ensemble-averages – still quite a lot of work to do
25% uncertainty in forcing
All codes running same IPCC scenario (A1B = business as usual) results in huge
diversity in response for same forcing – looks like different forcings. We appear to be
mixing forcing and response – this confuses our assessment! LW varies x2, SW varies
by sign! X2 or more around 0
Principle causes of errors: Errors in atmospheric transmission.
Transmission is hard to represent mathematically. Ex: optical depth for water vapor has
a huge range, with lots of dips: 10-6 – 104!
http://earthobservatory.nasa.gov/Study/Iris/Images/greenhouse_gas_absorb_rt.gif
His group has developed a better method for modeling transmission – extinction spectra
Will apply to GCMs now…
He showed energy balance diagram with CHANGES over last 10 years due to
MODELING not data. – very good
__ speaking for Cairns– GW will provide 2 W/m2 – a nightlight for every child – but not
on the ground, up in the troposphere
Brian Cairns
Columbia University, New York, NY Using Models and Measurements to Understand
and Constrain the Direct Effect of Aerosols on Climate
Hansen 200 “The Sun’s role in long-term climate change”
Reference changes not to solar forcing but to CO2
Black carbon BC aerosols very important for GW and regional climate
Satellite datasets don’t necessarily agree! Best agreement for high aerosol loads. For
low loads, hard to separate aerosols from clouds… MODIS, AERONET, GOCART…
Sparse datasets, missing stations, …
Even using the same data, different groups come up with rather different TOA and
Surface radiative forcings, using different chemistry model simulations.
Future: NASA Glory mission will be better, with TIM and APS = Aerosol Polarimetry
Sensor (better than MODIS, MISR, POLDER)
Polarization obs less affected by surface
Data: Optical depth – angstrom exponent – single exponent albedo – differentiating
species
Jim Coakley (older guy with glasses, white hair), Mathecon, Segrin, Tahnk, Christensen College of Oeanic and Atomospheric Sciences, Oregon State University, Corvallis The
Aerosol Indirect Effect
Listen folks, it’s clouds we have to worry about, not aerosols, as far as climate goes.
What’s the affect of aerosols on clouds? Models aren’t consistent.
We’re pretty sure we’re in the 2-5 range of climate sensitivity, since the climate’s been
pretty stable for a million years, but how will it change? How does pollution affect
clouds? How does thermodynamics respond to CO2?
Polluted clouds have higher reflectivity than clean clouds.
Pristine clouds have fewer, larger droplets. Clouds with haze have more, smaller,
droplets – brighter.
Aerosol optical depth // cloud droplet effective radius
They can find ship tracks by finding IR, then track droplet size and pollution – both vary
through the day.
Later in day – solar heating – clouds thin – smaller optical depth
Polluted clouds have greater optical depth, less water.
Antony Clarke (white beard, belly, glasses, looks like an academic sailor)
University of Hawaii, Honolulu An Ultra-fine Sea-Salt Flux from Breaking Waves:
Implications for CCN in the Remote Marine Atmosphere
Natural sea-salt is the largest aerosol mass flux, globally – down to 10 nm from breaking
waves …
Measures with tower on shore – different heights – 5m, 10m, 20m
…
Steven Lloyd + colleagues.. APL, Johns Hopkins University
Laurel, MD A 27-Year Composite Dataset of Global UV Effective Reflectivity from the
TOMS and SBUV(/2) Satellite Instruments
Combined 8 datasets to get complete albedo record … remove Rayleigh scattering with
model
Look up at Sun and down at Earth, and take ratio.
Highest and lowest albedo values in 2003, separated by 2 months – why?
Large increase in albedo at 55-60 S – why? Clouds, by process of elimination…
Decadal trends in albedo are significant and should be included in climate models.
KK Tung University of Washington, Seattle Atmosphere’s Response to the 11-Year
Solar Cycle,
Use solar cycle response to constrain climate sensitivity  = dtT/dQ = dT/dF
Coughlin and Tung 2004 – waves of heating and cooling with solar cycle
They decompose atmosphere temperature data into principle components, or IMF. The
4th IMF tracks the 11-yr solar cycle, with solar activity leading.
They derive the climate sensitivity  from their data (0.80 pm 0.19 K/Wm-2), and it
matches that from the Vostock ice core data (0.75 pm 0.25 K/Wm-2), within
uncertainties.
JGR 109, 2004, Coughlan and Tung
Tropical signal of < 1 K understandable from O3 absorption of solar UV
Polar solar warming much larger 10 K in late winter – “only when stratified in phase with
QBO” (LvL, 88) [who is LvL? She?]
Is sudden warming more frequent during solar max? (LvL 82) Is SSW the dynamical
amplifier?
Camp and Tung 2006 address these issues
CONCLUSIONS
DT = 0.17 for each 1 W/m2 of solar constant variation. 0.2K GW in solar max
Response to solar cycle: RSI variation amplified by (water vapor, cloud, ice-albedo
feedback) -> surface warming (g~2-3)
David Halpern (JPL) NASA Headquarters, Washington, DC, with Weller + Plueddermen,
Woods Hole, Ocean-Atmosphere Interfaces in Climate
PLANET OCEAN:
 Upper m of ocean has as much heat as the whole atmosphere
 Ocean absorbs heat produced by GG in atmos
 Ocean redistributes heat via advection (ENSO) and mixing (upper ocean
processes)
Barnett et al, 2005 Science 309, 284 – show how GG have increased ocean heat
(speaker incompletely understands data he presents)
Ocean heating raises sealevel total rise 2.9 mm/yr
http://sealevel.colorado.edu/
ocean heating 2.1 mm/yr
Greenland + Antarctic melt ! 0.8 mm/yr
Ocean redistributes heat via advection (ENSO) and mixing (upper ocean processes)
Halpern 1987 JGR 92, 8197
El Nino →winds - warming
La Nina reverse winds, cooling
Measuring (global, diffuse, SW) radiation – Eppley precision pyranometer (Colbo &
Weller 2006 JAOT) Buoy is supposed to rotate in the water (unless sandstorms anchor
it)
APPLICATIONS:
1. Air-Sea heat flux: warm Gulf Stream loses much heat to cold atmosphere, especially
in winter
SOC annual mean net heat flux – Weller et al have a buoy in the middle of gulf stream
2. check radiation measurements
3 CERES and IMET regression analysis
FRIDAY 22 Sept
Robert Cahalan (gentle portly smart, trim graying beard, longish hair, gave eulogy for
Yoaram) NASA Goddard Space Flight Center, Greenbelt, MD Three-Dimensional Cloud
Properties and Climate I3RC
Budyko 1920-2001 made very close estimates of important climate parameters
early…“the precision of these data is of importance in the study of the climate”
Stratus, deep convection, cirrus… 29 … selection of an infinite variety of cloud forms
“Who then beheld the figures of the louds
Like blooms secluded in the thick marine?”
Walace Stevens 1879-1955
Marine stratocumulus cool the planet - need 3D simulations of heating/cooling
Cloud vortices seen by MISR (von Karman vortex street past an island) – scale grows to
10s of km downstream, and vortices wind up and get more complex- energy flows
upstread and downstream
Future: CloudSat (and CALIPSO?) will see cloud drops (not just rain drops like TRMM)
– better radiative transfer info
THOR pulses a laser at the top of a cloud – 1 km ring pattern of refrected light gives info
about cloud structure in 3D to depth of about 1 km (flying about 10 km above cloud)
Geometrical cloud thickness retrievals
Remote sensing dependson 3D radiative transfer
Climate models depend on 3D cloud structure
Issues with aerosols – how do they interact with clouds? We can only look close to edges
and look for correlations – affected by 3D scatter with cloud – makes it look like there is
more aerosol than there is – some of the brightness is due to size of cloud and scattering
angle
__
Can dynamical cloud models be driven by 3D radiation?
Cloud resolving models have tall narrow columns – light pipes for photons to go up and
down, heating the cloud. What if they can move sideways?
Bill Hei__, UCSB, WRK 3DRT model – daytime convection run – 3 second timestep,
call radiation every 5 sec (should probably call it every half a minute), 3D only in SW,
LW 1D so far…
3D model develops a more realistic cloud, more speed and precip;
1D model cloud collapses, lower speeds and precip
CONCLUSION
Need 3D RT in cloud models – good public models are now available
Ken Jezek, (thick white hair and trim white beard, silver glasses, belly, gregarious) The
Ohio State University, Columbus Recent Changes in Polar Ice Sheets and Sea Ice
Rapid and dramatic changes in ice sheets – well documented indicators of climate change
IGOS = International Global Observing Strategy – subgroup on Cryospheric Research
http://www.igospartners.org/cryosphere.htm
Sea ice – Ice sheets – Seasonal snow cover - .. more Antarctic Ice Sheet – reservoir of fresh water – continental in size – deformed under its
own weight – dramatic variations in surface velocity field = nearly 1% decrease in
antarctic ice shelf extent between 1963 and 1997 – some episodic discharge is normal,
but retreat is observed in most sectors, which is unusual
Larson A broke up in mid-90s, Larson B broke up in 2002 – water gets into cracks and
causes cracks to propagate and fragment
Collapsing ice shelves don’t direcly raise sea level, but stopper in wineglass is removed –
ice shelf buttressed glaciers …
now glacier flow speed increased up to 8x, thinning up to 40 m in 6 months.
(Different from glacier – usu constrained to move through mt walls)
Melt duration days increasing every year, but slight decrease in overall melt index!
intensity in some locations high due to decreased albedo
Ice sheet mass balance from InSAR – Thomas and Rignot 2002 – use radar to calculate
motion of ice sheet
W Antarctic net loss of 48 km3/yr, E Antarctic net gain of 22 km3/yr
Ice sheet elevation changes – altimeters – slight thickening in E, substantiantial thinning
in W (1-2 M/yr – almost doubling speed of glacier in past year or so!)
GREENLAND ICE SHEET is much smaller – 7 m od sea level equivalent (if it were to
melt)
Much melts in summer (60-70%) [then new snow?]
Retreat of Jakobshavn ice stream accelerating – central W Greenland – was stable
between 1953-2000, spectacularly doubled and accelerated recently – 7000 m/yr –
14,0000 km/yr from 2000-2003!!, 120 m thinning between 1997-2003
Observed rapid changes in G and are not predicted by models – nonlinear response
Surface melt in Greenland is increasing (opposite Antarctica) 31% from 1979-2005
(interesting variability)
Ice sheet melt – “aqua velva” lakes form on margin (km wide, m deep) – vent under
glacier chasms – speed up glaciers by lubricating them – ice sheet surges forward
Glaciers and small ice caps – smaller ones may resond more rapidly, nonlinearly
Glaciers retreating worldwide
Virtually every glacier in AK is thinning
GRACE data 2002-2004
http://science.nasa.gov/headlines/y2002/14mar_grace_oceans.htm
Saline Sea Ice cover varies – sind and current driven – regional effects
Perrenial sea ice cover – significant reduction 10% per decade, replaced by younger,
thinner ice, 40% thinner…
IceSat measuring…
Future directions of Cryospheric research – meaure – model – quantify feedbacks- predict
International Polar Year 2007-2008
Steve Rumbold - Reading – Effect of the 11 year solar cycle on stratospheric
temperatures
How can the solar cycle influence the stratosphere? Approach:
Determine radiative component of solar cycle effect (instead of GCM)… Look at MgII
line – 1/6 of effect at stratopause – pretty big
Solar max minus min experiment:
Jose Rial, (argued at dinner that geothermal like in Iceland can solve energy crisis
everywhere – BS) University of North Carolina at Chapel Hill Solar Forcing and Abrupt
Climate Change over the Last 100,000 Years
Using Greenland ice core data – selected some (not all) sharp warming events followed
by cooling – proxy for strength for thermohaline circulation
Can insolation variations (due to Milankovich cycle) drive abrupt climate change? Looks
like no – M is very long, abrupt changes are very short period.
GRIP HF spectra – 4000 years is the main period
Tried to simulate abrupt climate change using two climate models – ECBilt Clio and
SVO
ECBilt Clio (intermediate complexity coupled GCM) 250 model years / day (fast)
atmosphere and ocean layers, sea ice, does a decent job reproducing SST, etc.
Input Holocene BC (for what variable?) and got T oscillations of the right shape,
sea ice anticorrelated (OK), THC strength, strong warming in NH, weak cooling in SH
Interpretation – nonlinear oscillation of the THC
Overlay Milankovitch driver - Long smooth amplitude modulation of spiky events –
compare with GRIPss09sea
SVO (Zero-Dimensional, few diffeq) Salzman-van der Pol Oscillator with Milankovich
forcing – all feedbacks lumped into one number
[Picked SVO because some eigenmodes have spiky shapes…] overlay
Milankovitch and you can get something sort of similar [no physics?]
“We have some confidence that these things are happening”
CONCLUSIONS
Orbital changes in insolation influence the TIMING of abrupt climate change bu
modifying the duration of warming pulses through frequency modulatin of THC’s free
oscillations.
Rapid sea ice advance and retreat control the abruptness…
http://www.geosci.unc.edu/faculty/rial/PaperforSc2NEW.pdf
Dominique Crommelynck The observation of the Earth radiation budget – a set of
challenges
Meteorology in space – Sun is easy, Earth is difficult [ high variability in space, time,
colors, difficult sampling, large angular sampling; reflects, absorbs, and emits flux
Nimbus, ERBE, Scarab, CERES, GERB
Sun – ACRIM, PM06, ERBE, DIARAD agree – TIM is less – why?
Earth sampling:
Polar orbits: global earth - synchronous, drifting, poor temporal sampling (every 12 h per
place), need 4 satellites for 3 r periodic obs
Geostationary orbits – partial earth – good temporal sampling (every 5 min) – local and
regional climate – 3 satellites for full Earth coverage at Equator – more for overlapping
These are complementary – data should be coherent
Observation instruments
Polar orbits: Radiometers – scanning telescopes –
(neat old ONERA idea: black or reflective spherical satellite with triaxial accelerometer
to measure effects of radiation – assuming all acceleration due to radiation!)
Geostationary orbits: 3-axis stabilized sat., spin-stab sat, … many more
Radiance corrections…
CONCLUSION – to put the Earth into a calorimeter – need international cooperation and
strategy – respecting different methodologies – results should match – focus on
metrology