Sources of Uncertainties in Climate Forcing by Black Carbon Aerosol over Indian Region Using Regional Climate Model

The models of the atmospheric Black Carbon (BC) cycle are highly uncertain and the results are difficult to evaluate as they are influenced by emission inventories, the inclusion of BC ageing processes that can change BC lifetime and wet deposition that is the most uncertain process in the models. The objective of this study is to understand the various sources of uncertainties in climate models and to quantify the uncertainty in Climate Forcing due to the treatment of BC (emission and transport) in Regional Climate Model (RegCM 4.1). The methodology adopted in this study utilized emission data of June and December 2001 obtained from EDGAR. The comparative study was done between the estimated surface Radiative forcing for BC with the results obtained in similar studies done for Bangalore in December 2001 and 5 year averaged value for June and December for Kanpur. The effects on the surface temperature, surface pressure and daily precipitation rate were estimated for the months of June and December 2001 to quantify the response of the atmosphere to BC forcing in Climate models. The study concludes that the uncertainties involved in the climate models due to BC emission inventories are due to the underestimation of the emissions in EDGAR database as compared to the other emission inventories for Indian region. It was observed that the BC aerosols in atmosphere are responsible for surface cooling over the Indian region. The reduced surface temperatures in the Bay of Bengal, Arabian Sea and over Indian region act to reduce the surface pressure and precipitation over maximum parts of India.

[1]  B. DeAngelo,et al.  Bounding the role of black carbon in the climate system: A scientific assessment , 2013 .

[2]  T. Storelvmo.  Uncertainties in aerosol direct and indirect effects attributed to uncertainties in convective transport parameterizations , 2012 .

[3]  Matthias Karl,et al.  Sources of uncertainties in modelling black carbon at the global scale , 2009 .

[4]  V. Ramanathan,et al.  Global and regional climate changes due to black carbon , 2008 .

[5]  S. Tripathi,et al.  Aerosol direct radiative effects over Kanpur in the Indo‐Gangetic basin, northern India: Long‐term (2001–2005) observations and implications to regional climate , 2008 .

[6]  Olivier Boucher,et al.  Aerosol absorption and radiative forcing , 2006 .

[7]  Jeremy S. Pal,et al.  Introduction to the TAC special issue: The RegCNET network , 2006 .

[8]  Menas Kafatos,et al.  Variability of aerosol optical depth and aerosol forcing over India , 2006 .

[9]  B. N. Holben,et al.  Retrieval of black carbon and specific absorption over Kanpur city, northern India during 2001-2003 using AERONET data , 2006 .

[10]  Axel Lauer,et al.  © Author(s) 2006. This work is licensed under a Creative Commons License. Atmospheric Chemistry and Physics Analysis and quantification of the diversities of aerosol life cycles , 2022 .

[11]  U. Lohmann,et al.  Black carbon ageing in the Canadian Centre for Climate modelling and analysis atmospheric general circulation model , 2005 .

[12]  D. Streets,et al.  A technology‐based global inventory of black and organic carbon emissions from combustion , 2004 .

[13]  J. Seinfeld,et al.  Parameterization of cloud droplet formation in global climate models , 2003 .

[14]  M. Jacobson.  Control of fossil‐fuel particulate black carbon and organic matter, possibly the most effective method of slowing global warming , 2002 .

[15]  S. Babu,et al.  Aerosol radiative forcing due to enhanced black carbon at an urban site in India , 2002 .

[16]  C. Venkataraman,et al.  Inventory of aerosol and sulphur dioxide emissions from India: I—Fossil fuel combustion , 2002 .

[17]  J. Wilson,et al.  A global black carbon aerosol model , 1996 .