III. Science Questions: Climate Prediction and Climate Model Testing

1:30 – 3:00 Forcing, Sensitivity, and Feedbacks Bill Collins

How CLARREO Applies Stephen Leroy and Michael Mishchenko

3:00 – 3:15 Break

3:15 – 4:45 Climate Trends V. Ramaswamy

How CLARREO Applies Peter PilewskieJoao TeixeiraKevin Bowman

4:45 – 5:00 Discussion

III. Science Questions: Climate Prediction and Climate Model Testing

• Peter Pilewskie: CLARREO Visible and Near-Infrared Studies

• Stephen Leroy: Testing Climate Models with CLARREO: Feedbacks and Equilibrium Sensitivity

• V. Ramaswamy: Radiation spectra at TOA and climate diagnoses

• Mike Mishchenko: Constraining climate models with visible polarized radiances

• Kevin Bowman: Observational constraints on climate feedbacks: A pan-spectral approach

Climate Model Observing System Simulation Experiments

Bill Collins

UC Berkeley and LBL

with A. Lacis (GISS) and V. Ramaswamy (GFDL)and J. Chowdhary, D. Feldman, S. Friedenrich, L. Liu,

V. Oinas, D. Schwarzkopf

Simulation and the CLARREO questions

• Societal objective of the development of an operational climate forecast:

The critical need for climate forecasts that are tested and trusted through …state-of-the-art observations.

• Objectives of OSSE:• Use models as “perfect worlds” to

understand utility of CLARREO for detection and attribution vs. models.

• Prepare climate modeling communityfor direct application of all-sky radiances for evaluation and assimilation.

Climate prediction and its components

IPCC AR4, 2007

ΔT =λΔFΔF =Forcing

λ=FeedbackΔT =Response

Historical radiative forcing

IPCC AR4, 2007

• Probability that historical forcing > 0 is very likely (90%+).• However, confidence in short-lived agents is still low at best.

Forcing scenarios for 21st century

Longwave: The 5 to 95 percentile range of at 2100 is ~50% of the mean.Shortwave: The models do not agree on sign or magnitude of forcing.

IPCC AR4, 2007

Projection of regional temperatures

IPCC AR4, 2007 • Roughly 2/3 of warming by 2030 is from historical changes.

• Uncertainties at 2100 are from physics and emissions.

Uncertain cloud radiative response

• Models do not converge on sign of change in cloud radiative effects.

• Trends in cloud radiative effects have magnitude < 0.2 Wm-2 decade-1.

Change from 1980-1999 to 2080-2099

Change in cloud radiative effects in 21st century: A1B Scenario

IPCC AR4, 2007

Goals of the OSSEs

• Test the detection and attribution of radiative forcings and feedbacks from the CLARREO data:

• Determine feasibility of separating changes in clouds from changes in the rest of the climate system

• In solar wavelengths, examine feasibility of isolating forcings and feedbacks

• Quantify the improvement in detection and attribution skill relative to existing instruments

Role of climate models in OSSEs

• Goals of OSSEs require projections of climate change.

• Sole source of these projections: climate models

• Advantages of climate models for this application:• Identification of forcings for each radiatively active species

• Separation of feedbacks associated with water vapor, lapse rate, clouds

• Tests of CLARREO concept with climate models• To what extent can forcings and feedbacks can be separated and quantified

using simulated CLARREO data?

• What are the time scales for unambiguous detection and attribution?

Application of CLARREO to Models

ForcingForcing Climate SystemClimate System

CLARREOCLARREO AttributedForcing

AttributedForcing

ForcingForcing Climate SystemClimate System

CLARREOCLARREO AttributedFeedbackAttributedFeedback

ForcingProjection

ForcingProjection

FeedbackProjectionFeedbackProjection

Climate ModelsClimate Models

Climate ModelsClimate Models

Schematic of Tests

ForcingForcing Climate ModelsClimate Models

CLARREOEmulator

CLARREOEmulator

SimulatedForcing

SimulatedForcing

Compare

ForcingForcing Climate ModelsClimate Models

CLARREOEmulator

CLARREOEmulator

SimulatedFeedbackSimulatedFeedback

Compare

Model Feedback

Model Feedback

Forcing Projection

Forcing Projection

FeedbackProjectionFeedbackProjection

Individual forcings in Climate Models

IPCC AR4, 2007 MIROC+SPRINTARS

Individual feedbacks in Climate Models

IPCC AR4, 2007

Major steps in Climate OSSEs

1. Conduct OSSEs with 3 models analyzed in the IPCC AR4

2. Add adding two new components to these models :A. Emulators for the shortwave and infrared CLARREO

B. More advanced spectrally resolved treatments of surface spectral albedos

3. Results from emulators serve as surrogate CLARREO data

4. Estimate the forcings and feedbacks from emulators

5. Compare to forcings / feedbacks calculated directly from model physics

Models for Climate OSSEs

Three models for OSSEs: • NASA Goddard Institute for Space Studies (GISS) modelE (Schmidt et al, 2006) • NOAA Geophysical Fluid Dynamics Laboratory (GFDL) Coupled Model CM-2 and CM-2.1 (Delworth et al, 2006) • NCAR Community Climate System Model CCSM3 (Collins et al, 2006).

Model Simulations for Climate OSSEs

Three classes of simulations for OSSEs: • Pre-industrial conditions with constant atmospheric composition • 21st century with the IPCC emissions scenarios• 20th and/or 21st centuries with single forcings, e.g., just CO2(t)

IPCC AR4, 2007

Candidate CLARREO Emulators

MODerate spectral resolution atmospheric TRANSmittance (Modtran4) version 3 (Berk et al, 1999)

Spectral resolution of Modtran4: • 0 to 50,000 cm-1: 1 cm-1 • Blue and UV: 15 cm-1

Relationship to CLARREO: • Infrared: 1X • UV/Blue/NIR: 10-100X

Alternate emulators:• AER, GISS, GFDL, and NCAR LBL codes

Berk et al, 1999

TOA shortwave spectrum

• Profile: AFGL mid-latitude summer with 2000 AD long-lived greenhouse gases.

• Sun-satellite geometry: solar zenith angle = 53o, satellite zenith = 0o.• Spectral parameters: 15 cm-1 resolution with no instrumental convolution.• Radiative transfer code: Modtran 4,

Shortwave spectral forcings

Absolute Forcing Relative Forcing

• Forcing calculations:• CO2: 287 to 574 ppmv (2×CO2-1870)• N2O: 275 to 316 ppbv (2000-1870)• CH4: 806 to 1760 ppbv (2000-1870)• N2O: 100% to 120% PW (2×CO2 feedback)

Primary steps in the OSSE

Phases for the study:

• Linking the CLARREO emulator with the climate models• Adoption of spectral surface emissivity and BDRF models• Simulations for a constant composition to determine the natural variability • Simulations of CLARREO measurements for transient climate change

ModelArchive ModelArchive

CLARREOEmulator

CLARREOEmulator

Emulation ValidationEmulation Validation

Natural variability in the spectra

Huang et al, 2002

25-day Variability, Central Pacific

25-day Variability, Western Pacific

• Goal: quantify signal-to-noise ratios for forcings and feedbacks (cf Leroy et al, 2007)

• .Calculations: pre-industrial conditions for “background” radiance field

• Goal: quantify signal-to-noise ratios for forcings and feedbacks (cf Leroy et al, 2007)

• .Calculations: pre-industrial conditions for “background” radiance field

Issues for the Emulation

• For speed and expediency, we recommend using using the existing IPCC archives for emulation.

• The reason? Centennial length simulations are very expensive.

• The trade-offs:• Highest temporal sampling: daily means of model state• Nominal temporal sampling: monthly means of model state• This precludes reproducing the space-time track of CLARREO’s orbit• For solar, we can reproduce monthly-mean solar zenith (latitude)

• Result: Our results are an upper bound on detection/attribution skill• Our results would reflect perfect diurnal sampling at each grid point.

• Alternate, but remote, possibility: “time-slice” experiments• Advantage: interactive coupling and capture space-time sampling

1950 1960 1970 1980 1990 2000 2010 2020 2030 2040 2050

TimeSlice

TimeSlice

TimeSlice

TimeSlice

Additional Issues for the Emulation

• Atmospheric conditions:• All-sky: predominant condition for 100-km pixels• Clear-sky: sets upper bound for detection-attribution skill for non-cloud forcings and feedbacks

• Detection and attribution: projection onto spectral “basis functions” for single forcings and feedbacks

Anderson et al, 2007

First stage of the OSSE

Objective: Configuration and initiation of the OSSEs •Simulation of CLARREO measurements from IPCC model results, including:

- Calculations for pre-industrial conditions- Calculations for transient climate change with all forcings

• Perform parallel calculations for all-sky and clear-sky conditions

• Estimation of natural (unforced) variability in the simulated CLARREO data

Second stage of the OSSE

Objective: Detection and estimation of radiative forcings • Simulation of CLARREO measurements from IPCC model results, including:

- Calculations for transient climate change from single forcings

• Calculation of spectral signatures of shortwave and longwave forcings from reference radiative transfer calculations

• Estimation of radiative climate forcing from simulated clear-sky CLARREO data- Projection global CLARREO simulations onto single-forcing spectral signatures to isolate time-dependent forcings

• Repeat forcing estimation for all-sky fluxes- Quantify degradation in forcing estimates and time-to-detection from the substitution of all-sky for clear-sky observations

Conclusion of the OSSE

Objective: Detection and estimation of radiative feedbacks • Estimation of radiative climate feedbacks from the simulated CLARREO data

- Estimation of surface-albedo feedbacks for clear and all-sky data- Estimation of water-vapor/lapse-rate feedbacks for clear and all-sky data- Estimation of cloud feedbacks from all-sky data only- Comparison of estimates with feedback estimates derived independently

• Characterize improvements in estimates and time-to-detection relative to existing satellite instruments

Key questions for Climate OSSEs

•Can clear-sky shortwave forcings and feedbacks be detected and quantified using CLARREO data?

•Can all-sky shortwave forcings and feedbacks be detected and quantified using CLARREO data?

•Can all-sky longwave forcings and feedbacks be detected and quantified using CLARREO data?

•To what extent is it possible to isolate forcings and feedbacks associated with changes in specific species and processes in the CLARREO measurements?