GEOS-Chem Working Group 2.3 Chemistry-climate interactions Co-chairs: Becky Alexander and Loretta Mickley Pipeline of research New capabilities Weaknesses.

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Presentation transcript:

GEOS-Chem Working Group 2.3 Chemistry-climate interactions Co-chairs: Becky Alexander and Loretta Mickley Pipeline of research New capabilities Weaknesses in GCAP model Technical issues

Pipeline of research:  Climate/ Mediterranean air quality: Study of the effect of climate change on air quality over the Mediterranean, using GEOS-Chem as boundary conditions for a regional model. Giannokopolous, Varotsos.  GCAP Phase 2: Study of the impact of climate on US air quality and mercury deposition. Wu, Yoshitomi, Tai, Sturges, Mickley, Streets, Seinfeld, Pye, Fu, Byun, Kim, Lam, Rind, Jacob. EPA  Oxidation capacity of Last Glacial Maximum: Study of how oxidation capacity of the atmosphere has changed since LGM, using GCAP + observed oxygen isotopes in sulfate from ice cores. Alexander, Sofen, Kaplan, Murray, Mickley. NSF  US aerosols/ climate: Project to look at how trend in aerosols influences regional climate over US. Includes study of both direct and indirect effect. Leibensperger, Mickley. EPRI  Land cover/ climate/ chemistry: Project to look at how changes in climate can affect land cover, which in turn can affect chemistry. Wu, Tai, Kaplan, Mickley, Marais. NASA  Wildfires/ climate/ chemistry: Continuing (?) study of the effect of climate on wildfires in the US and Canada, and the subsequent impact on air quality. Logan, Spracklen, Hudman, Mickley, Rind. EPA (pending)  Climate/ US air quality: Similar to GCAP phase 2, but with an emphasis on regional modeling and with new IPCC scenarios. Mickley, Shindell, various EPA people. EPA

Next few slides are Loretta’s 10-minute talk on GCAP capabilities.

New capabilities of GEOS-Chem for the study of chemistry-climate interactions Loretta J. Mickley, Harvard 1. Application of meteorological fields from past and future climates GISS GCM Physics of the atmosphere Qflux ocean or specified SSTs INPUT GHG and aerosol content Sea level, topography GEOS-Chem Emissions Chemical scheme Deposition met fields We have the ability to apply both future IPCC scenarios + paleo greenhouse gas levels to the GISS GCM (and CCSM3). Alexander, Sofen, Murray, Kaplan, Mickley, Wu, Jacob, Pye, Seinfeld, Liao, Streets, Fu, Byun, Rind, Yoshitomi, Schmidt, Youn CO 2 scenarios

2. Application of changing land cover to GEOS-Chem GEOS-Chem Emissions Chemical scheme Deposition GISS GCM Physics of the atmosphere Qflux ocean or specified SSTs INPUT GHG and aerosol content Sea level, topography LPJ + BIOME4 dynamic vegetation models met fields Vegetation types + leaf area indices change in vegetation type broadleafboreal needleleaf We can apply land cover from future or past (ice age) climates. Wu et al., Wu, Kaplan, Tai, Mickley, Murray, Alexander, Sofen

3. Application of changing area burned to GEOS-Chem GEOS-Chem Emissions Chemical scheme Deposition GISS GCM Physics of the atmosphere Qflux ocean or specified SSTs INPUT GHG and aerosol content Sea level, topography Area burned prediction scheme Uses observed relationships between meteorology and area burned met fields wildfire emissions change in surface OC concentrations  g m -3 We can simulate the effect of changing climate on wildfire emissions. Spracken et al Logan, Spracklen, Hudman, Mickley

4. Archival of finely time-resolved meteorological and chemical fields for use in regional models GEOS-Chem Emissions Chemical scheme Deposition GISS GCM Physics of the atmosphere Qflux ocean or specified SSTs met fields chemistry fields AIR QUALITY This is the basic GCAP (Global Change and Air Pollution) setup. One issue in downscaling global meteorology is how much to nudge regional model within the domain. Jacob, Wu, Pye, Seinfeld, Streets, Rind, Byun, Fu, Kim, Lam, Varotsos, Giannopolous, Nolte, Gilliland, Leung, Gustafson, Mickley Regional climate model Regional chemistry model met fields

5. Past and future emissions inventories available for use in GEOS-Chem IPCC scenarios for ozone precursors, BC, OC (Streets) 1950?-2050 mercury emissions, based on historical fuel use + IPCC storylines (Streets) [need to check this] BC + OC emissions (Bond) EDGAR emissions of NOx and SO  g m -3 Calculated trend in surface sulfate concentrations, Circles show observations from IMPROVE + CASTNET Streets, Leibensperger, Sturges

6. Calculation of the aerosol indirect effect using GEOS-Chem aerosol output. Aerosol-N c Parameterization: m i = [SO 4 = ] + [NO 3 - ] + [SeaSalt] + [OC] GISS-TOMAS NcNc A, B Indirect Effect GEOS-Chem Emissions Chemical scheme Deposition mass aerosols Cloud droplet number We use a parameterization based on the GISS-TOMAS aerosol model to calculate the indirect effect. Leibensperger, Seinfeld, Chen, Adams, Nenes

End of Loretta’s talk from Thurs. a.m. Next: weaknesses, followed by technical issues.

Some current GCAP weaknesses: Surface ozone too high over US (but is better than before!) Aerosol: nitrate too low over US Precipitation: trends may not be reliable over mid-latitudes Misplaced Bermuda High (too far north and east) No dust emission possible in 4x5 Model Drizzle over Canada in summer Others? Some improvements in pipeline: Influence of CO 2 on isoprene emissions (Heald) Improvements in SOA chemical scheme (Pye) Others?

Technical issues for the Chem-Climate Working Group. 1. GCAP model resolution: when is finer better? 2. Interannual variability + ensembles: how can you tell when you have a signal? 3. Need for GCAP wiki. 4. Downscaling to regional climate models: how much nudging is optimal within the regional model domain? 5. Cyclone tracking: how best to show changes in cyclone frequency. 6. Beyond GISS: met fields from other climate models. 7.More?

Model resolution: when is finer better? I will probably have generated GISS 2x2.5 met fields within a year. On our fastest machines, 2x2.5 GCAP takes 1 week/ model year. The 4x5 takes just a couple days. The issue in climate studies is that you usually need to look at several model years to be confident of the signal that you see. Then if you want to do sensitivity studies... Observed GEOS-5 2 years JJA surface ozone at 2 resolutions, using 1990s emissions. Yoshitomi 4x5 2x2.5

Interannual variability + ensembles: how can you tell when you have a signal? Signal could be either: 1)effect of climate on chem or 2)effect of chem on climate How many model years are sufficient? Depends on question asked and the size of the perturbation. Can we come up with any guidelines for the optimal number of model years? Predicted biomass burned by fires in the West, Standardized departure from the mean Spracklen et al., 2009 anomalously cold year in US

Need for a GCAP wiki Everybody likes to do things his/her own way, but it would be good if we had guidelines posted for tasks such as: changing CO 2 in future climate, dealing with tropopause, regridding raw GISS files, setting preindustrial emissions, implementing new land cover, etc. Who will do a first draft? Who will maintain? How will we come up with topics for the first draft?

JJA 1990s temperatures from the GISS-GCM and MM5, mean over 5 summers, Lynn et al. Downscaling from global and regional climate models. Big issue is downscaling of met fields from GISS GCM to regional climate models. If we nudge the regional model only at the boundaries, we miss some important climate signals, like changes in cyclone frequency. If we nudge within the domain, how much is enough nudging? Can we devise some way to determine the optimal degree of within-domain nudging for a chemistry-climate study? Or should we just use smaller model domains to make sure the regional model doesn’t invent its own climate? Regional model nudged only at lateral boundaries.

Instantaneous 2-m Temperature Fields Nudging only at the lateral boundaries leads to cooler (-10 o C) temperatures over Canadian Rockies and throughout Midwest. WRF nudged only at boundaries WRF nudge experiment A WRF nudge experiment B GISS GCM 18 UTC 31 Dec 1949 (30.5 days into simulation) Slide from Tanya Otte.

Downscaling from global and regional climate models: cyclone frequency. Most global models calculate a decline in cyclone frequency in response to climate change and the reduction in meridional temperature gradient, but many regional models seem to fail to capture this trend. Leibensperger et al., 2008 Trend in JJA cyclone number in S. Canada 2050s 1990s July - August Response of tracers of pollution to more persistent stagnation Results are from GISS GCM; regional model using BCs from same GCM shows no change in cyclone frequency. Mickley et al., 2004; Leung and Gustafson, 2005

Eric’s requirements for the identification of a cyclone: Sea level pressure minimum of at least 720 km Duration of at least 24 hours Use 4x daily SLP fields. Storms are tracked by assuming a maximum storm velocity of 120 km/hr. A pressure minimum within UΔt km of a minimum from the previous time step are considered to be the same 720 km 990 mb 1000 mb Some issues: cyclone identification, stagnation criteria Leibensperger, 2008; Bauer and Del Genio, 2007 Cyclone tracking: Cyclone frequency plays a role in determining the duration of stagnation period. Important diagnostic in air quality studies.

Beyond GISS: met fields from other models, e.g. CCSM3... others?? Can we make all met fields available to the community?

Some extras...

Goddard Institute for Space Studies GCM Resolution: 4ºx5º, 23 Vertical Levels (~ 5 in PBL) Q-Flux Ocean (or specified SST) Contains full stratosphere – important to diagnose the transport of ozone from the stratosphere to the troposphere and to simulate the entire climate system Convection scheme of [Del Genio, 1996], with updates. [Rind, et al., 2007]

ENHANCEMENTS IN MONTHLY MEAN SURFACE PM 10, O 3 CONCENTRATIONS AND RESULTING RADIATIVE FORCING 6-20 ppbv 5-30 μg m -3 At the surface – 0.0 (-5.8) At TOA -9.3 – 0.0 (-1.5) W m -2 RADIATIVE FORCING Δ PM 10 (7 μg m -3 ) Δ O 3 (8 ppbv)

Effects of Siberian forest fires on meteorology over East Asia in May 2003: CCSM3 vs. NCEP reanalysis II Δ Surface Air Temp Δ Surface Pressure Δ Precipitable water NCEP R-II anomaly for May 2003 ( climatology) CCSM3 differences (fire-nofire) KhPakg m -2 Statistically 99% significant anomaly data in May 2003