MLS Cloud Forcing:IWC validation & Cloud Feedback

Determination

MLS Science Team Teleconference:June 15, 2006

Dan FeldmanJonathan Jiang

Hui SuYuk Yung

Cloud Forcing Intro

• Clouds are a prominent radiative feedback mechanism with substantial impact on SW and LW radiative budget– SW, LW impact nearly

balanced currently

• Surface, TOA forcing depends on vertical cloud structure

• Motivation to understand relative roles of liquid and ice clouds under:– Current conditions– Climate change scenarios

Change in TOA CRF from 2 x CO2

for several GCM resultsLe Treut and McAveney, 2000 &IPCC TAR, 2001

Introduction

Cloud feedback & surface temperature

• Cloud forcing and cloud feedbacks operate on many scales

• On regional scales, feedback mechanisms may regulate SSTs– Thermostat hypothesis testing

• “The correct simulation of the mean distribution of cloud cover and radiative fluxes is therefore a necessary but by no means sufficient test of a model’s ability to handle realistically the cloud feedback processes relevant for climate change.” –IPCC TAR

Su et al, 2005

After Stephens et al, 2002

Cloud Properties

AtmosphericCirculation

Radiative &Latent heating

Introduction

Calculation of Cloud Forcing

• Correlated-K RT commonly used in GCMs, reanalyses

• RRTM_LW :– Fluxes: ±0.1 W/m2 relative to LBLRTM– Cooling Rates: ±0.1 K/day in

troposphere, ±0.3 K/day in stratosphere– Liquid, ice water clouds

• RRTM_SW :– Fluxes: ±1.0 W/m2 direct, ±2.0 W/m2

diffuse– DISORT: (4-stream w/δ-M scaling)– Liquid, ice clouds + aerosols

• Fu-Liou:– Longwave flux + correlated-k flux– Shortwave flux

• Parameters relevant to Cloud Forcing calculations

– Cloud Water Path– Particle Diameter– Cloud Fraction– T(z), H2O(z), O3(z)– Appropriate Spatio-Temporal Averaging

TOASFC

TOASFC

TOASFC CLRFTOTFCF __

RT Calculations

Validation Data: CERES

• CERES measures OSR, OLR, and cloud forcing aboard TRMM, TERRA, and AQUA– Shortwave (0.3-5.0 µm)– Total (0.3-50.0 µm)– Window (8-12 µm)

• ES4, ES9 products: monthly gridded data at 2.5x2.5 resolution with ERBE heritage

• FM3 + advanced angular distribution models provide fluxes– ERBE-like accuracy: ±5 W/m2

– SSF accuracy: ±1 W/m2

From http://eosweb.larc.nasa.gov/

From http://lposun.larc.nasa.gov

CERES Data

MLS Standard (IWC, T, H2O,O3) + AIRS L3: 01/2005 vs. CERES

CERES Intercomparison

CERES Intercomparison

MLS Standard (IWC, T, H2O,O3) + AIRS L3: 07/2005 vs. CERES

LW Comparison with ECMWF calculations

ECMWF Intercomparison

Validation Data: ARM Sites• Heavily-instrumented sites at NSA

& TWP include– ARSCL data: active cloud

sounding• Micropulse Lidar• Millimeter-Wave Cloud Radar

– SKYRAD: • Diffuse, Direct SW Irradiance• Downwelling LW Irradiance

– Balloon-borne Sounding System

• Sonde profiles for clear-sky TOA, surface flux

• T(z), H2O(z)• State-of-the-art instrument

calibration so cloud forcing calculations can be validated

Images from www.arm.gov

SKYRAD

MPL MMCR

BBSS

ARM Site Data

CERES-ARM intercomparison: 09/2004 – 12/2004

ARM Data Intercomparison

from http://www-cave.larc.nasa.gov/

ARM Data Intercomparison

MLS-ARM intercomparison: 09/2004 – 12/2004

Conclusions

• Cloud forcing is important to understand– Unbiased monthly estimates required– MLS scanning pattern can provide most inputs for

suffic• MLS IWC product tends to overestimate cloud

forcing as derived from CERES• ECMWF product agrees in LW, SW agreement

with mc-ICA (Pincus et al., 2003) TBD• ARM sites provide surface cloud forcing which

can be readily compared with CERES, MLS surface forcing estimates

Conclusions

Future Work

• Ground-based validation: Baseline Surface Radiation Network

– Direct/diffuse SW downward– LW downward– Radiosonde data– Cloud base height determination

• CLOUDSAT– Radar activated 06/02/06– Operational product specs: TOA,

SRF flux ±10 W/m2 instantaneously

Cloudsat’s first radar profile: 5/20/06 N. Atlantic squall line (from http://cloudsat.atmos.colostate.edu)

GEBA network stations

Future Work

from http://bsrn.ethz.ch

Acknowledgements

• The following individuals/groups have been invaluable for this work: – Frank Li– Duane Waliser– Baijun Tian– Yuk Yung’s IR Group

Acknowledgements

References

• Radiative Transfer References– Fu, Q. and K. N. Liou (1992). "On the Correlated K-Distribution Method for Radiative-Transfer in Nonhomogeneous Atmospheres." Journal of the Atmospheric

Sciences 49(22): 2139-2156.– Fu, Q. A. (1996). "An accurate parameterization of the solar radiative properties of cirrus clouds for climate models." Journal of Climate 9(9): 2058-2082.– Hu, Y. X. and K. Stamnes (1993). "An Accurate Parameterization of the Radiative Properties of Water Clouds Suitable for Use in Climate Models." Journal of Climate

6(4): 728-742.– Mlawer, E. J., S. J. Taubman, et al. (1997). "Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated-k model for the longwave." Journal of

Geophysical Research-Atmospheres 102(D14): 16663-16682.– Pincus, R., H. W. Barker, et al. (2003). "A fast, flexible, approximate technique for computing radiative transfer in inhomogeneous cloud fields." Journal of

Geophysical Research-Atmospheres 108(D13).– Hughes, N. A. and A. Henderson-sellers (1983). "The Effect of Spatial and Temporal Averaging on Sampling Strategies for Cloud Amount Data." Bulletin of the

American Meteorological Society 64(3): 250-257.• Cloud Forcing

– Le Treut, H. and B. McAvaney, 2000: Equilibrium climate change in response to a CO2 doubling: an intercomparison of AGCM simulations coupled to slab oceans. Technical Report, Institut Pierre Simon Laplace, 18, 20 pp.

– IPCC TAR, Chapter 7 (http://www.grida.no/climate/ipcc_tar/wg1/260.htm)– Su, H., W. G. Read, et al. (2006). "Enhanced positive water vapor feedback associated with tropical deep convection: New evidence from Aura MLS." Geophysical

Research Letters 33(5).• AIRS L3 Data:

– AIRS V4 Data Release Description: (http://disc.gsfc.nasa.gov/AIRS/documentation/v4_docs/V4_Data_Release_UG.pdf)• CERES Data:

– Wielicki, B.A.; Barkstrom, B.R.; Harrison, E.F.; Lee, R.B.; Smith, G.L.; Cooper, J.E. 1996: Clouds and the earth’s radiant energy system (CERES): An earth observing system experiment, Bulletin of the American Meteorological Society 77 (5): 853.

– Loeb, N. G., K. Loukachine, et al. (2003). "Angular distribution models for top-of-atmosphere radiative flux estimation from the Clouds and the Earth's Radiant Energy System instrument on the Tropical Rainfall Measuring Mission satellite. Part II: Validation." Journal of Applied Meteorology 42(12): 1748-1769.

• ARM Data:– CERES/ARM Validation Experiment: (http://www-cave.larc.nasa.gov/cave/cave2.0/Pubs.html)

• CloudSat– Stephens, G. L., D. G. Vane, et al. (2002). "The cloudsat mission and the a-train - A new dimension of space-based observations of clouds and precipitation."

Bulletin of the American Meteorological Society 83(12): 1771-1790.– L’Ecuyer, T.S. CLOUDSAT L2 ATBD (2004)

• BSRN– Heimo A., Vernez A. and Wasserfallen P. (1993) Baseline Surface Radiation Network (BSRN). Concept and Implementation of a BSRN Station. WMO/TD-No. 579,

WCRP/WMO.– http://bsrn.ethz.ch/

References