The Need For Meteoritic Dust In The Stratosphere

Transcription

1 Global LIDAR Remote Sensing of Stratospheric Aerosols and Comparison with WACCM/CARMA: The Need For Meteoritic Dust In The Stratosphere CESM Whole Atmosphere Working Group Meeting 23 June 2011 Breckenridge, Colorado Acknowledge: Dr. Michael Mills and Jason English for basis of current working model. Ryan R. Neely III (PhD Candidate, CU-Boulder) Advisors: Susan Solomon, Brian Toon, Jeff Thayer, Karen Rosenlof and Michael Hardesty

2 Why? 1.00 Mauna Loa Apparent Transmission 1.0 Transmission Optical Depth Monthly Maximum Annual High Average Agung Feugo El Chichon Pinatubo R. Neely III Empirical Clean Value Mauna Loa Aerosol Optical Depth Satellite (Tropics, >15 km) Lidar (Stratospheric) PFR Transmission Transmission Mauna Loa Lidar Transmission Satellite (Tropics, >15km) PFR Variability of stratospheric aerosol has an impact on the global radiation budget

3 Research Questions Goal: Understand Variability in Stratospheric Aerosol Seasonal cycles? Long-term trends? How will I answer these: Observations Lidar Modeling WACCM/CARMA Boulder Lidar (R. Neely III) Pleiades Supercomputer (NASA AMES)

4 35 Lidar Datasets Altitude (km) Lauder Mauna Loa Backscatter (km -1 sr -1 ) 5 0 Altitude (km) Year Boulder Boulder Year Backscatter (km -1 sr -1 ) 5 0 Year

5 Sources of Stratospheric Aerosols Mesosphere Meteoritic Dust Stratosphere SO2 Stratospheric Aerosol Layer Troposphere OCS SO2 OCS SO2 OCS DMS Surface Volcanic Terrestrial Biomass Burning Industrial Marine

6 WACCM Setup NCAR s WACCM version x5 degree resolution 66 vertical levels Model top near 140 km Vertical spacing of km in the stratosphere 3D chemical transport Model for OZone And Related chemical Tracers (MOZART)(Horowitz et al. 2003) Sulfur chemistry includes seven sulfur species: SO2, SO3, SO, H2SO4, CS2 and OCS (English et al., 2011(ACPD)) NCAR s Bluefire Supercomputer 25 year run, using last 10 years for comparison to observations.

7 Sulfur Emissions Setup Total SO2 in Bottom Level of Model During January SO 2 Emission data representative of background aerosol period(smith et al. (2010) and English et al., 2011(ACPD)). OCS field is a lower boundary condition of 510 pptv.

8 35 WACCM January Zonal Mean SO2 WACCM Dust Sulfur January Mean SO Altitude(km) Latitude log(ppt) S N

9 CARMA Setup Aerosol Size Distributions created by thirty-six bins (dry radii from 0.2 nm to 1100 nm) each for: Pure sulfates (English et al., in prep, 2011) Community Aerosol and Radiation Model for Atmospheres Meteoritic dust (Bardeen et al. 2008) Mixed sulfates (sulfate aerosols with dust cores) 140 km 105 km 70 km Meteoritic Dust Input 35 km 0 km Latitude

10 Comparison With In Situ Observations Murphy et al.(2007) Mean Murphy et al.(2007) WACCM/CARMA Altitude(km) Total Mass Fraction of Meteoritic Sulfate Percent of Total Aerosol

11 10 0 SOFIE and Pure Sulfate Model Comparison Dust Sulfate Model, Pure Sulfate Model and SOFIE Comparison Need Daily Avergaed SOFIE Retrievals From Hervig et al Pure Sulfate Model Dust Sulfate Model with Zeroed Dust Initial Condisitons Dust Sulfate Model SOFIE SOFIE Precision Pressure (hpa) 10 1 Dust Sulfate model And SOFIE agree within the model variability and measurement precision 10 2 Dashed lines represent 90% Confidence Interval Pure Sulfate model(from English et al. (2011)) And Dust-Sulfate Model With No Dust agree within the model variability Extinction (1/km)

12 Lidar Comparison Lauder, NZ Model With Dust βtotal=βpure Sulfate+βixed Sulfate+βDust WACCM Lidar SAGE II Rayleigh Model Without Dust βtotal=βpure Sulfate+βixed Sulfate

13 Lidar Comparison Boulder, CO Model With Dust βtotal=βpure Sulfate+βixed Sulfate+βDust (Same as Results Shown Previously) WACCM Lidar SAGE II Rayleigh Model Without Dust βtotal=βpure Sulfate+βixed Sulfate

14 Summary First global microphysical model of stratospheric aerosols to include current sulfur emissions and meteoritic dust Comparison to observations show: 1. Agreement within the natural variation of the observations in the lower aerosol layer that is dominated by sulfate aerosols. 2. Meteoritic dust is needed to fully characterize the upper aerosol layer. 3. Inclusion of meteoritic dust is needed within lidar retrievals Errors associated with the lidar retrievals need to be addressed before further comparison and analysis of trends can be made. Observations Modeling Observations Correlation of the WACCM aerosols and N2O suggest the observed seasonal cycle of stratospheric aerosols is consistent

15 Future Work: Trends? re 2a shows the Mauna Loa Observatory Nd:YAG lidar 25 km integrated backscatter data from 1994, when the began operating, to early The data have been Possible theories: yzed using the technique of Thoning et al. [1989] to oth the remove the seasonal variation, and deter1. data, Anthropogenic emissions (Hofmann et al. the trend2009)? curve and growth rate (determined by differting the deseasonalized trend curves). There is a biennial 2. insmall episodic volcanic (Vernier et ponent the deseasonalized trend in injections Figure 2a, likely les to at the (a) al. Mauna Loa Observatory (b) Boulder, Colorado. ed quasi-biennial oscillationand (QBO) in tropical 2009)? kscatter plus molecular backscatter) the the molecular s, as will(aerosol be discussed later. From 1994 to to 1996 Strengthening of stratospheric circulation ular scattering. The Figure 1aeruption shows the seasonal cycle y of 3. aerosol from theinset 1991inPinatubo dominates (Butchart et al., 1997]. 2006;From Niwano 2009)? ata [Barnes and Hofmann, 1996ettoal., 2000 was a slightly decreasing trend at Mauna Loa, bly due to remnants of the Pinatubo eruption. Howafter 2000 there is a decidedly increasing aerosol scatter trend. The magnitude of the aerosol backscatter at Mauna Loa Observatory varies with altitude. The mum trend occurs in the km region with an km age value of 4.8% per year, and about 3.3% per year the total column for the period (the dard error in determining these trends is about ±5% e trend value). Figure 2b, for the km range at der, indicates an increasing average trend of 6.3% per for the period. It is important to note that the seasonal increase in sol backscatter (summer to winter) is about 2.5 times r than the backscatter magnitude of the Therefore, the trend would be difficult to detect by method that cannot resolve the seasonal variation. We not aware of other surface-based or satellite lidar or lite limb extinction instruments that have reported Mauna Loa +4.8%/yr Adapted from Hofmann at al. (2009) Boulder km +6.3%/yr

16 Thank You David Oonk

17 Adapted from Bates et al. 1992

18 Lidar Retrieval Error Derivable Backscatter Boulder Retrieval Comparison Calibrated from 40 45km Calibrated from 35 40km Calibrated from 30 35km Boulder Retrieval Comparison Calibrated from 40 45km Calibrated from 35 40km Calibrated from 30 35km Altitude (km) 30 Altitude (km) Rayleigh Backscatter Ratio ((A+M)/M) Backscatter Ratio [(A+M)/M] Backscatter (km 1 sr 1 ) Backscatter(1/km 1/sr)

19 Osiris =alt omi=how much Then put in if then logic in mo sad Get kathrine to do emission stuff Compiler switch Intro models Show comparison of models Show from ells calc that is is 1-2% and not radiatively that important Show sofie Show lidar and show how this small error can propagate using russel math