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Aerosol Concentration and Hurricanes over the Northern Indian Ocean (NIO) Jeff Nelson, James Belanger, Laura Griffith EAS 4740: Atmospheric Chemistry Dr. Yuhang Wang Outline of Presentation Discuss recent studies that suggest aerosols such as black carbon are changing atmospheric stability and sea surface temperatures (SSTs). Discuss recent trends in tropical cyclone activity and SSTs in the Northern Indian Ocean (NIO). Is there any evidence to support a connection between aerosol changes and tropical circulation changes e.g. monsoon and hurricane formation? Background Information on Black Carbon Black carbon (BC) is very important because it absorbs visible light, heats the air, and contributes to global warming. BC emissions result from incomplete combustion of coal, biofuels, diesel engines, and biomass burning. Increasing population in India and China have caused an increase in BC emissions throughout South Asia. During the dry season, anthropogenic BC is transported into the NIO and envelope the region in a 3 km thick brown cloud layer. INDOEX Background INDOEX addresses questions of climate change that are of high priority and of great value to the US and the international community. The project's goal was to study natural and anthropogenic climate forcing by aerosols and feedbacks on regional and global climate. The experiment was conducted in a region of the Indian Ocean where clean southerly air masses meet dirty continental masses. http://www-indoex.ucsd.edu/7 Pollution Statistics over Asia Graph to the right shows a dramatic increase in Asian emissions specifically of NOx Can be extrapolated to see the scale of emissions over recent years. Alles, D. 20054 Air Pollution Over China Alles, D. 20054 Black Carbon Statistics Shown are aerosol particles over Asia and Africa from December 8-12, 2004. Small particles are red and larger particles are gold. The red particles are due to the burning of vegetation and other sources which indicates large amounts of black carbon in the area. Alles, D. 20054 Black Carbon Statistics (cont.) The whiter patches indicate the presence of more black carbon. In China, this is mostly due to the significant amount of industry in the region. Over Africa, the white patch is due to agricultural burning. Also, one can see that the highest concentration of black carbon exists over eastern Asia. Alles, D. 20054 Black Carbon Effects 1. This map shows cooling of 0.5 to 1.0 degrees Celsius (0.9-1.8 degrees Fahrenheit) occurring over China, and warming temperatures throughout the rest of the world (in yellow). 2. The blue colors indicate regions in which the simulations yield a tendency for increased rainfall by as much as 10 inches over the summer. Other regions (brown colors) have decreased rainfall by as much as several inches or more. 3. Shows the decrease in solar energy reaching the ground (in black) during the summer months (June, July and August). Yellow shows were the sunlight has increased. www.gsfc.nasa.gov/5 Black Carbon Effect (cont.) Upper figure shows the effect on albedo due to black carbon. An outline of India is evident. Lower figure shows surface cooling also due to black carbon. Most cooler regions are over land masses and close to coast lines. A strong relationship can be seen between albedo and surface cooling. NASA Earth Observatory6 Black Carbon Effect (cont.) Upper graph shows aerosol coverage over southeastern Asia, with the lightest colors indicating the highest concentration of aerosols. The lower graph shows the amount of atmospheric warming due to black carbon emissions. Another good correlation can be seen between higher concentrations of aerosols and warmer atmospheric temperatures due to black carbon absorbing solar radiation. NASA Earth Observatory6 Impact of Black Carbon on Radiative Forcings Ramanathan et al.1 Time Series of Emission and Forcing terms for annual mean conditions in South Asia and NIO. Note: Results are from model simulations using NCAR PCM with INDOEX Black Carbon and Sulfate concentrations. Impact of Black Carbon on Radiative Forcings Cont’d Simulated JJA change in net radiation (NR) at the top of the atmosphere (TOA) → 6 W/m2 over NIO Simulated JJA change in net radiation (NR) for surface → -17 W/m2 over NIO Menon et al.2 Note: Results are from model simulations using GISS with INDOEX Black Carbon and Sulfate concentrations. Impact of Black Carbon on Atmospheric Temperatures Ramanathan et al.1 Simulated and observed surface temperature changes during the dry season (October to May). Blue curve includes: greenhouse gases and sulfate aerosol emissions. Red curve includes: GHG’s, SO4, and black carbon emissions. Note: Results are from model simulations using NCAR PCM with INDOEX Black Carbon and Sulfate concentrations along with greenhouse gas concentrations. Impact of Black Carbon on Atmospheric Stability Ramanathan et al.1 Vertical profile of simulated temperature trends over India with black carbon emissions shown with red curve. Blue Bar = vertically averaged temperature of the troposphere using microwave sounding unit (MSU) observations ~ 0.7 ± 0.2 K. Red Bar = vertically integrated simulation of atmospheric temperature ~ 0.46 ± 0.2 K. 0.3 K 0.27 K Note: Results are from model simulations using NCAR PCM with INDOEX Black Carbon and Sulfate concentrations along with greenhouse gas concentrations. Impact of Black Carbon on Tropical Cloudiness With the addition of black carbon and haze into the model simulation, tropical cloudiness decreases throughout the diurnal profile. Ackerman et al.9 Note: Results are from model simulations using ATEX meteorology data along with black carbon concentrations from INDOEX for 1998 and 1999. Impact of Black Carbon on Surface Evaporation Ramanathan et al.1 Annual mean latent heat fluxes for the ABC_1998 simulations. Figure C shows the change between the 1995-2005 average and the 1930-1950 average. Regions such as the Bay of Bengal show the greatest decrease in latent heat flux and surface evaporation. Note: Results are from model simulations using NCAR PCM with INDOEX Black Carbon and Sulfate concentrations along with greenhouse gas concentrations. Impact of Black Carbon on Sea Surface Temperatures The •Blue simulated line shows SSTthe trends SST show increasing that the trend ABC influenced counteracts onlythe by influence Greenhouse of the gases GHGs and and Sulfate. Sulfate in the NIO : •Trend •Red line is positive shows the at all SST latitudes increasing due to trend the forcing influenced of GHGs. by •The Greenhouse NIO warms gases, lessSulfate, than theand SIOAtmospheric because of Black the ABC Carbon influence. •Green line shows observed SST trend. SST trend for 1930-2000 for the Indian Ocean for pre-monsoon season March to June, in relation to latitude. Ramanathan et al.1 Trends in Sea Surface Temperatures Running 5-year mean of SST during the respective hurricane seasons for the six principal ocean basins. Webster et al.8 Sea Surface Temperature Trends in Bay of Bengal In the Bay of Bengal region, an overall positive anomaly trend is observed from 1970-2005. However, SSTs in this region show smaller positive change than the surrounding areas. Courtesy of Climate Diagnostics Center Impact of Black Carbon on Vertical Motion The combination of the increase of rising motions south of the equator and the subsidence in the NIO leads to the southward shift of the monsoon circulation. Figure shows change in meridional circulation due to the ABC from 1985 to 2000 for June and July. Red indicates increased sinking motions, and blue indicates increased rising motions. Ramanathan et al.1 Why is all of this important? By investigating black carbon’s influence on environmental variables, we have attempted to establish a link between BC emissions and NIO tropical cyclonic activity. Ingredients for Hurricane Formation Ingredients for a Cyclone Warm SSTs, T>25oC or 79oF Deep moisture at low levels Light winds throughout Troposphere Convergence and triggering mechanism ITCZ Tropical Wave Weak Frontal Boundary Courtesy of www.nhoem.state.nh.us Convective Instability of the Second Kind (CISK) CISK is a popular theory that explains how thunderstorms can evolve and organize into hurricanes. This cycle repeats itself, each time Surface air intensifying the storm until other spirals into the The decreased factors act to weaken it. center ofpressure a low surface pressure causes a larger system, pressurecreating gradient, convergence. leading to surface convergence. Since warm air is less dense than cooler air, the warmer air expands, ultimately causing the surface Increased pressure tosurface decrease. convergence allows moist air rises, to rise.it This As air aircools then condenses and into clouds, moisture releasing more latent heat. condenses, releasing latent heat. Courtesy of http://library.thinkquest.org Trends in Hurricane Frequency Graph displays regional time series for 1970-2004 for the total number of hurricanes. Thin lines indicate annual statistics. Dark lines show 5year running averages. Since the mid 1980s, overall hurricane frequency in the NIO has decreased. Webster et al.8 Conclusions and Take Home Message Since 1970, black carbon emissions have influenced the North Indian Ocean Sea Surface Temperatures Vertical Motion Low-level Moisture Tropical Clouds Cyclone Frequency Due to fast-paced industrialization, per capita emissions of black carbon are expected to triple by 2020. References 1. Ramanathan, V., C. Chung, D. Kim, T. Bettge, L.. Buja, J. T. Kiehl, W. M. Washington, Q. Fu, D. R. Sikka, and M. Wild, PNAS, 102, 5326-2333 (2005). 2. Menon, S., J. Hansen, L. Nazarenko, and L. Yunfeng, Science, 297, 2250 (2002). 3. Krishnamurti, T.N. et al, Tellus, 50B, 512-542, (1998). 4. Alles, D., Asian Air Pollution, (2005). 5. Goddard Space Flight Center, http://www.gsfc.nasa.gov/topstory/20020822blackcarbon.html, (2002). 6. Herring, D., NASA Earth Observatory, http://earthobservatory.nasa.gov/Newsroom/NasaNews/2001/20010813505 0.html, (1999). 7. http://www-indoex.ucsd.edu/, (1999). 8. Webster, P., G. J. Holland, J. A. Curry, and H. R. Chang, Science, 309, 18441846 (2005). 9. Ackerman, A. S., O. B. Toon, D. E. Stevens, A. J. Heymsfield, V. Ramanathan, E. J. Welton, Science, 288, 1042-1047 (2000).