Global LIDAR Remote Sensing of Stratospheric Aerosols and Comparison with WACCM/CARMA

Transcription

1 Global LIDAR Remote Sensing of Stratospheric Aerosols and Comparison with WACCM/CARMA CESM Whole Atmosphere Working Group Meeting February 2011 National Center for Atmospheric Research Boulder, Colorado Acknowledge: Dr. Michael Mills and Jason English for basis of current working model. Ryan R. Neely III Advisors: Susan Solomon, Brian Toon, Jeff Thayer and Michael Hardesty

2 Introduction The stratospheric aerosol layer has not been perturbed by a major volcano since Pinatubo in Recent lidar observations have shown trends in the amount of background aerosol. Hofmann at al. (2009) suggested a renewed modeling effort to understand the background layer. Here we start by comparing lidar data to a base run of WACCM coupled with CARMA to look at seasonal cycles in stratospheric aerosols. First study of its type with dust and sulfate aerosol model.

3 Motivation Seasonal Cycles What causes them? +4.8%/yr Trends What is driving decadal trends? Pollution? Volcanoes? +6.3%/yr

4 Rayleigh/Mie LIDAR Δr Δt/2 N(λ,z)=N L (λ)[β(λ,z) R] A z 2 exp[ 2 z 0 α(λ,z ) dz ][η(λ)g(λ,z)] + N B (λ,z)( β Scatter (λ,z)=β aerosol (λ,z)+β molecule (λ,z)

5 Backscatter β(532nm, π,z)=π Backscatter equation depends on: Particle Radius Size distribution Index of refraction Comes from lidar data by inverting lidar equation Model backscatter calculated directly from model output size distribution and assuming an index of refraction(allowed to vary with H2SO4 content) 0 r 2 Q π ( m, x)n(r, z)dr x = 2πr λ

6 Lidar Sites in this Study Boulder, CO Lauder, New Zealand Mauna Loa, HI

7 Lidar Records Mauna Loa, HI Integrated Backscatter from 25 to 30km Integrated Aerosol Backscatter (1E 6 1/sr) Mauna Loa,HI Lidar Integrated Aerosol Backscatter (1E 6 1/sr) Records from Using Trop+(25km MeanTrop) to Trop+(30km MeanTrop) Integrated Aerosol Backscatter(IABS) Smoothed Integrated Aerosol Backscatter(SIABS) Sum of Sines Fit without Annual Component, RMSE: 2.3, RSQR:0.7 Pure Seasonal Cycle(Residual of Linear Fit to Sine Fit without Annual Component) Longterm Linear Trend, %/yr,rmse:2.3, RSQR:0.2 Residual Linear Trend, %/yr,rmse:2.3, RSQR:0.2 Sine Fit of Pure Season Cycle, RMSE:2.1, RSQR:0.6 +3%/yr Trend 5 Seasonal Cycle Information: Period: days Season Cycle Percent Change: 20.3 % Peak Offset from Start of Year: days Year Winter Peak, 20.3% Seasonal Change

8 Integrated Aerosol Backscatter (1E 6 1/sr) Lauder,NZ Integrated Backscatter from 25 to 30km Lauder,NZ Lidar Integrated Aerosol Backscatter (1E 6 1/sr) Records from Using Trop+(25km MeanTrop) to Trop+(30km MeanTrop) Integrated Aerosol Backscatter(IABS) Smoothed Integrated Aerosol Backscatter(SIABS) +4%/yr Trend Sum of Sines Fit without Annual Component, RMSE: 3.0, RSQR:0.6 Pure Seasonal Cycle(Residual of Linear Fit to Sine Fit without Annual Component) Longterm Linear Trend, %/yr,rmse:2.3, RSQR:0.1 Residual Linear Trend, %/yr,rmse:2.3, RSQR:0.1 Sine Fit of Pure Season Cycle, RMSE:2.9, RSQR:0.5 Seasonal Cycle Information: Period: days Season Cycle Percent Change: 37.3 % Peak Offset from Start of Year: days Year Winter(July) Peak, 37% Seasonal Change

9 Integrated Aerosol Backscatter (1E 6 1/sr) Boulder,CO Integrated Backscatter from 25 to 30km Boulder,CO Lidar Integrated Aerosol Backscatter (1E 6 1/sr) Records from Using Trop+(25km MeanTrop) to Trop+(30km MeanTrop) Integrated Aerosol Backscatter(IABS) Smoothed Integrated Aerosol Backscatter(SIABS) +6%/yr Trend Sum of Sines Fit without Annual Component, RMSE: 1.6, RSQR:0.8 Pure Seasonal Cycle(Residual of Linear Fit to Sine Fit without Annual Component) Longterm Linear Trend, %/yr,rmse:1.2, RSQR:0.5 Residual Linear Trend, %/yr,rmse:1.2, RSQR:0.5 Sine Fit of Pure Season Cycle, RMSE:1.5, RSQR:0.7 5 Seasonal Cycle Information: Period: days Season Cycle Percent Change: 34.8 % Peak Offset from Start of Year: days Year Winter Peak, 35% Seasonal Change

10 WACCM Setup WACCM version x5 degree resolution 66 vertical levels Model top near 140 km Vertical spacing of km in the stratosphere 25 year run, averaging last 10 years

11 WACCM Setup The main sulfur sources for stratospheric aerosols in the model are OCS and SO2. The OCS field is a lower boundary condition of 510 pptv. SO2 input is based on the work of Smith et al. (2011) and was adapted for use in WACCM by Dr. J. F. Lamarque. Emission data should be representative of background aerosol period. Figure 1.11: January SO 2 Surface Emissions Figure 1.12: July SO 2 Surface Emissions

12 CARMA Setup Thirty-six bins (dry radii from 0.2nm to 1100nm) each for: Pure sulfates(1) Mixed sulfates(sulfate aerosols with dust cores)(2) Meteoritic dust(3) (Similar to Bardeen et al 2008) Mass bins are set to be equal for all 3 groups of particles. Thus, when a dust particle nucleates into the mixed sulfate group, there is no difference in mass to be accounted for by gas exchange. Fourth group of the dust cores keeps track of the dust cores after forming mixed sulfates.

13 Lauder Comparison Lauder Seasonal Profile Comparison Lidar DJF WACCM DJF Lidar MAM WACCM MAM Lidar JJA WACCM JJA Lidar SON WACCM SON WACCM Annual Mean Rayleigh Altitude(km) Backscatter (km 1 sr 1 )

14 Mauna Loa Comparison Mauna Loa Seasonal Profile Comparison Lidar DJF WACCM DJF Lidar MAM WACCM MAM Lidar JJA WACCM JJA Lidar SON WACCM SON WACCM Annual Mean Rayleigh Altitude(km) Backscatter (km 1 sr 1 )

15 Boulder Comparison Boulder Seasonal Profile Comparison Lidar DJF WACCM DJF Lidar MAM WACCM MAM Lidar JJA WACCM JJA Lidar SON WACCM SON WACCM Annual Mean Rayleigh Altitude(km) Backscatter (km 1 sr 1 )

16 Peak to Peak Comparison Backscatter Peak Lidar Data Model Boulder December November Mauna Loa December December Lauder July June

17 Zonal Mean Seasonal Cycle WACCM Dust Sulfur January minus July Zonal Mean Backscatter at 532nm 35 January Minus July Zonal Mean Backscatter at 532nm x Altitude(km) Latitude 5 km 1 sr 1

18 Correlation of Seasonal Cycle Integrated Backscatter from 20 to 36km(1/sr) Integrated Backscatter( sr 1 ) 9 x 10 8 Lauder Boulder Mauna Loa Lauder Summer with N2O WACCM Dust Sulfur Monthly Integrated Backscatter Versus N 2 O from 20km to 36km Boulder Summer 6 Winter Text Winter Summer N 2 O(ppm) N2O(ppm) integrated from 20 to 36km Mauna Loa 9 Model Month Winter

19 Proposed Seasonal Cycle Diabatic Circulation Mean Location of the Subtropical Tropospheric Jet Mechanism Quasi-Isentropic Eddy Transport Strongest in winter hemisphere Mean Slope of Vertically Stratified Tracer (N2O, Aerosols) Mean Tropopause Adapted from Holton (1986).

20 Summary of Results Lidar data and model agree well but work needs to be done on amplitude of seasonal cycle. Seasonal cycles are observed to be due to the seasonal shifts in quasi-isentropic transport created by planetary wave breaking. Interesting features in the poles and the lower stratosphere still need to be examined.

21 Future Work Will continue to make model better, especially in higher regions. Change input files to create trends in SO2 emissions and simulate small volcanoes to examine how these affect the aerosol layer.