Measurement‐based estimation of the spatial gradient of aerosol radiative forcing

This paper diagnoses the spatial mean and the spatial gradient of the aerosol radiative forcing in comparison with those of well‐mixed green‐house gases (GHG). Unlike GHG, aerosols have much greater spatial heterogeneity in their radiative forcing. The heterogeneous diabatic heating can modulate the gradient in horizontal pressure field and atmospheric circulations, thus altering the regional climate. For this, we diagnose the Normalized Gradient of Radiative Forcing (NGoRF), as a fraction of the present global heterogeneous insolation attributed to human activity. Although the GHG has a larger forcing (+1.7 Wm−2) as measured than those of aerosol direct (−1.59 Wm−2) and possible indirect effect (−1.38 Wm−2) in terms of a spatially averaged top‐of‐atmosphere value, the aerosol direct and indirect effects have far greater NGoRF values (∼0.18) than that of GHG (∼0.003).

[1]  Edward Hanna.  Radiative forcing of climate change: expanding the concept and addressing uncertainties. By the National Research Council (NRC). National Academies Press, Washington DC, USA, 2005. 207 pp. Paperback , 2007 .

[2]  Yoram J. Kaufman,et al.  Satellite‐based assessment of marine low cloud variability associated with aerosol, atmospheric stability, and the diurnal cycle , 2006 .

[3]  K. Lau,et al.  Asian summer monsoon anomalies induced by aerosol direct forcing: the role of the Tibetan Plateau , 2006 .

[4]  M. Chin,et al.  Aerosol anthropogenic component estimated from satellite data , 2005 .

[5]  M. Chin,et al.  A review of measurement-based assessments of the aerosol direct radiative effect and forcing , 2005 .

[6]  Ilan Koren,et al.  The effect of smoke, dust, and pollution aerosol on shallow cloud development over the Atlantic Ocean. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[7]  S. Emori,et al.  Simulation of climate response to aerosol direct and indirect effects with aerosol transport‐radiation model , 2005 .

[8]  Yoram J. Kaufman,et al.  Aerosol distribution in the Northern Hemisphere during ACE‐Asia: Results from global model, satellite observations, and Sun photometer measurements , 2004 .

[9]  William L. Smith,et al.  A parameterization of ocean surface albedo , 2004 .

[10]  Ilan Koren,et al.  Measurement of the Effect of Amazon Smoke on Inhibition of Cloud Formation , 2004, Science.

[11]  Yoram J. Kaufman,et al.  Direct radiative effect of aerosols as determined from a combination of MODIS retrievals and GOCART simulations , 2004 .

[12]  Sonoyo Mukai,et al.  A study of the direct and indirect effects of aerosols using global satellite data sets of aerosol and cloud parameters , 2003 .

[13]  J. Hansen,et al.  Climate Effects of Black Carbon Aerosols in China and India , 2002, Science.

[14]  E. Feil,et al.  Climate Effects of Black Carbon Aerosols in China and India , 2002 .

[15]  V. Ramanathan,et al.  Aerosols, Climate, and the Hydrological Cycle , 2001, Science.

[16]  P. Koepke,et al.  Optical Properties of Aerosols and Clouds: The Software Package OPAC , 1998 .

[17]  Q. Fu,et al.  Parameterization of the Radiative Properties of Cirrus Clouds , 1993 .

[18]  A. E. Gill.  Atmosphere-Ocean Dynamics , 1982 .

[19]  L. J. Cox.  Optical Properties of the Atmosphere , 1979 .

[20]  D. Murcray.  Optical Properties of the Atmosphere , 1968 .