Assessment of long-term simulations with various observations for better understanding of aerosol effects on radiation “brightening” in the US. Chuen-Meei.

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Assessment of long-term simulations with various observations for better understanding of aerosol effects on radiation “brightening” in the US. Chuen-Meei Gan, Jonathan Pleim, Rohit Mathur, Christian Hogrefe, Charles N. Long, Jia Xing, David Wong, Robert Gilliam, Shawn Roselle and Chao Wei 1

Objective The main goal of this project is to investigate the changes in anthropogenic emissions of SO 2 and NO x over the past 21 years ( ) across the United States (US), their impacts on anthropogenic aerosol loading over North America, and subsequent impacts on regional radiation budgets. 2

Overview of coupled WRF-CMAQ model with feedback (fb) and without feedback (nfb) WRFv3.4 & CMAQv5.02 Simulation period: Resolution: 36 km, 1-hour Nudging coefficients (lower than typical nudging coefficients of standard run): guv: gt: gq: PBLACM2 (Pleim 2007) MicrophysicsMorrison 2-moment ChemistryCarbon Bond 05 Surface layerPleim-Xiu CumulusKain-Fritsch (new Eta) RadiationRRTMG Land UseNLCD 50 Emissions: Jia Xing, Jonathan Pleim, Rohit Mathur, George Pouliot, Christian Hogrefe, Chuen-Meei Gan, and Chao We., “Historical gaseous and primary aerosol emissions in the United States from 1990–2010”, Atmos. Chem. Phys., 13, , doi: /acp , Poster Session 2 Emissions Inventories, Models, and Processes 26. Jia Xing - Development and validation of long-term emission inventories in the United States from 1990 to

Observations Overview  Surface networks used in this study: SURFRAD, ARM, CASTNET & IMPROVE.  Variables of interest: SO 4, NO x, PM 2.5, AOD and SW radiation.  Analysis region is seperated by 100 o into East (i.e. bon, psu, gwn & sgp) and West (i.e. fpk, tbl & dra) of USA. Reference: Chuen-Meei Gan, Jonathan Pleim, Rohit Mathur, Christian Hogrefe, Charles Long, Jia Xing, Shawn Roselle and Chao Wei: “Assessment of the effect of air pollution controls on trends in shortwave radiation over the United States from 1995 through 2010 from multiple observation networks”, Atmos. Chem. Phys., 14, , doi: /acp , A complete analysis of observed trends was presented in Gan et al

CASTNET Comparison (time series) WEST EAST 5

CASTNET Comparison CASTNET SO4 16 years CASTNET SO2 16 years CASTNET NO3 16 years Model agreed well with observations especially the last 10 years comparisons. Model is able to characterize the observed SO2 and SO4 trends. Similar trends are shown in the emission trends (i.e. decreasing).

IMPROVE Comparison (time series) WEST EAST 7

IMPROVE Comparison IMPROVE SO4 16 years IMPROVE NO3 16 years In general, the surface measured concentrations agreed well with the model predictions (16-10 years comparison) for both networks especially SO4. This finding shows that model is able to replicate the long-term trends which give confident in examining the aerosol direct effect. 8

SURFRAD Aerosol Optical Depth (AOD) SURFRAD AOD 16 years Both simulations and observations show a decreasing trend in eastern US and an slightly increasing trend in western US. This is because many control programs under the CAA were aimed at reducing the pollution concentrations mainly in the developed area but the pollution concentrations were low at the rural western monitors from the beginning. This finding shows that the implementation of CAA does affect the US in particular eastern US. As a result of the reduction of particulate matter, the AOD is reduced over the past 16 years. WEST EAST 14 yrs obs16 yrs sim10 yrs obs10 yrs sim14 yrs obs16 yrs sim10 yrs obs10 yrs sim

SURFRAD Shortwave (SW) Radiation (Rad) with Feedback (FB) WEST EAST SURFRAD all-sky SW rad 16 years SURFRAD clear-sky SW rad 16 years Brightening effect 10

SURFRAD Clear-sky Direct & Diffuse SW Rad (FB) WEST EAST SURFRAD clear-sky direct SW rad 16 years SURFRAD clear-sky diffuse SW rad 16 years The observed clear- sky diffuse SW rad is increasing which is opposite of what would be expected if changes in clear-sky rad were just attributable to changes in the aerosol direct effect. 11

Annual mean of AOD versus clear-sky SW radiation between SURFRAD Comparison For all-sky SW radiation, the "brightening" occurs at the same time that cloudiness exhibits a decreasing trend suggesting the possibility that indirect effects of decreasing aerosols may be a contributing factor. However, trends in cloud cover can have many other reasons. The clear-sky SW radiation may be associated at least in part with a decrease in aerosols, particularly in the eastern US where substantial reductions in anthropogenic emissions of SO 2 and NO x, resulted from the implementation of CAA. However, analysis of the clear-sky diffuse SW radiation shows that the radiative impacts of decreasing aerosol concentrations are confounded by other factors. WEST EAST 16 yrs obs16 yrs sim10 yrs obs10 yrs sim16 yrs obs16 yrs sim10 yrs obs10 yrs sim SW SWC SW DIR SW DIF SWC DIR SWC DIF AOD

Contrail effect on SW radiation Monthly US system (international and domestic) aircraft airborne flight hours for the period January 1996 through December 2010 for the sum of passenger and cargo flights. (source: US Bureau of transportation Statistics) Figure 12: US Airways and Delta combined domestic routes. (source: As a result of the increasing air traffic, the contrails persistence can potentially increase the diffuse radiation. Characterization of contrails or ice cloud properties (crystal shapes, contrail altitude and etc.) are important. Other factors: “clear-sky” definition, aerosol semi-direct and indirect effect and other cloud effects. WEST EAST 13

SURFRAD clear-sky SW Rad (FB vs. NFB) WEST EAST 14

Conclusion  In general, the coupled WRF-CMAQ model is capable to replicate the observed trends in surface concentration and AOD especially the last 10 years. This finding illustrates the importance of the accuracy of the emission.  In conclusion, this analysis suggest that there was a SW radiation “brightening” over the past 16 years in the US especially in the east but less apparent in the west.  The western US could be influenced by local terrain influences as well as episodic long-range pollution transport which may contribute to the lack of a clear association between trends in aerosol burden and surface radiation at these locations.  However, analysis of the clear-sky diffuse SW radiation shows that the radiative impacts of decreasing aerosol concentrations are confounded by other factors.  There are several possible interpretations to resolve this seeming contradiction such as increasing contrails from air traffic, classification of “clear-sky” conditions in the radiation retrieval methodology and indirect aerosol and other cloud effects.  On going tests: Ice clouds simulation tests to identify inconsistencies in observed diffuse radiation. 15

Thank you! Questions? Acknowledgment: This research was performed while Chuen-Meei Gan held a National Research Council Research Associateship Award at US EPA. The research presented in this study was supported through an interagency agreement between the US Department of Energy (funding IA DE-SC ) and the US Environmental Protection Agency (funding IA RW ). The author also would like thank John Augustine from NOAA-SURFRAD for his support and assistance in obtaining the SURFRAD data. Dr. Long acknowledges the support of the Climate Change Research Division of the US Department of Energy as part of the Atmospheric System Research (ASR) Program. *Special thanks to all the co-authors for their contributions and support. 16

Extra Slides 17

Case study: SW Rad Aerosol Forcing Mean aerosol SW Radiative Forcing W/m 2 /year dTRFaer (Eqt1)Obs SW trendObs SWC trend Aug et al obs_east obs_west model_east_16yrs model_west_16yrs BON_aeronet bon_surfrad So (extraterrestrial downward SW flux at the TOA at 40 o N) = 343 W/m 2 α is computed SURFRAD network mean surface albedo of continental aerosols = Δτ is the measured change in 500-nm AOD g is the typical asymmetry parameter for continental aerosols = 0.87 ω o is a representative single scattering albedo of continental aerosol =