Download presentation
Presentation is loading. Please wait.
Published byLucas Hodges Modified over 6 years ago
1
A Comparison of Regional and Global Models during VOCALS
Matthew C. Wyant, Robert Wood, Christopher S. Bretherton, Department of Atmospheric Sciences, Seattle, Washington, USA and VOCA Modeling Groups Introduction Mean 20S profiles VOCA Experiment Setup Mean 20S profiles PreVOCA Simulations cover the REx field project period: Oct. -15 Nov Most models are run in short (1-3 day) forecast mode. Horizontally gridded data was submitted from a coarse larger domain or a fine inner domain or both domains. Capable models include aerosol species: SO4, sea salt, dust, black carbon, organic carbon Emissions of aerosol and gas species are specified in a standard protocol for regional models. Many participating models use their own surface emissions formulas. Sulfate Aerosol Mass at 950 hPa Pressure [hPa] PreVOCA compared 15 regional, weather forecast, and climate models (in forecast mode) for October 2006 in the VOCALS region. Many models had large errors in distribution of low cloud cover, though ECMWF and UKMO performed well. Most models produced a marine BL too shallow near the coast at 20S. However, most models qualitatively captured diurnal and day-to-day variability of the cloud and BL despite mean biases. In general, global models outperformed regional models. The VOCA experiment is designed to compare models in the VOCALS region for the REx period of intensive airplane and ship observations. VOCA has more of a focus on aerosols, aerosol and chemical transport, and aerosol-cloud interactions than PreVOCA. Some of the main research questions for VOCA are: Observed Droplet Number VOCA Goals Bretherton et al. (2010) Many models show a substantial drop off in droplet number away from the coast as is observed. Models’ vertical distribution of droplet number is surprisingly diverse. Do models simulate the variation of droplet concentration Nd along 20S? Is anthropogenic sulfate the main contributor to geographic Nd variation? What controls Nd in remote ocean regions? What is the simulated indirect effect due to anthropogenic aerosols perturbing clouds and net TOA radiative flux in the VOCALS domain? Fine Domain CoarseDomain 1x10-10 kg/kg Many models’ DMS concentrations are much higher than observed (note that observations don’t cover the full diurnal cycle). Mean Low Cloud Fraction Most models over-predict sulfate mass. Most models under-predict CCN concentrations (0.1% supersaturation) both in the boundary layer and above the boundary layer. Mean Liquid Water Path Observed DMS MODIS Total Cloud Fraction AMSR LWP [kg/m2] 20S CCN (950 hPa) Observed Droplet Number Low cloud fraction varies strongly between models. Some models under-predict coastal low cloud cover. Many models over-predict clouds in the tropics away from the South American coast. Liquid water path also strongly varies between models. Few models show good agreement with observations. Mean model biases in CCN dominate the comparison. Observed excursions from coast of higher droplet number concentrations are matched by higher than average modeled CCN concentrations for many models. Solid colors are MODIS, symbols are aircraft measurements. See Bretherton et al. (2010) VOCA Participating Models Participating Institution Model Name Model Type Horizontal Resolution [km] inner/outer Vertical levels below 700hPa Aerosol Advection Aerosol-cloud Interaction VOCA Participants COLA RSM Regional 25 9 J. Manganello IPRC/SOEST IRAM 1.2 30 12 Yes A. Lauer NRL COAMPS 5 15/45 7 X. Hong PNNL WRF-Chem 3.2.1 51 Q. Yang Scripps SCOAR 20/100 D. Putrasahan UCLA WRF 3.1.1 31 A.Hall U. Iowa WRF-Chem UIOWA 3.3 47 P. Saide U. Washington COSMO 25/100 21 A. Muhlbauer 15 R. George U. Wisconsin Milwaukee WRF-CLUBB (WRF 3.1.1) 26 L. Grant ECMWF 36R1 Global Forecast 18 J.-J.Morcrette UKMO MetUM 7.5 50 20 J. Mulcahy GFDL AM3 Global Climate 200 Y. Lin LMD LMDZ 5v2 59 11 F. Codron NCAR CAM4 / CAM5 5 / 9 C. Hannay AGCM v7.1 3 H. Xiao Cloud Liquid Water at 20S Longitude Longitude g/kg Pressure [hPa] Acknowledgements This work is only possible through the collaborative efforts of all VOCA modeling participants. The emissions data set for VOCA was provided by Scott Spak of the University of Iowa. This work was supported by NSF Grant ATM Conclusions Pressure [hPa] At 20S, boundary layer depth away from the coast also differs strongly between models. Pressure [hPa] Large model biases in cloud fraction, liquid water path, and boundary layer depth are present in most models, similar to the PreVOCA study. Models show large biases in aerosol and chemical concentrations. Models can reproduce timing of excursions of continental air into the offshore boundary layer. We will be analyzing a geo-engeering component of the VOCA experiment with cloud droplet number artificially adjusted to 375 cm-3. References Allen, G. and co-authors, 2011: South East Pacific atmospheric composition and variability sampled along 20S during VOCALS-Rex, Atmos. Chem. Phys., 11, Bretherton, C. S., R. Wood, R. C. George, D. Leon, G. Allen, and X. Zheng, 2010: Atmos. Chem. Phys., 10, Pressure [hPa] Observed Cloud Top and Base Pressure [hPa] 750 800 Pressure [hPa] Pressure [hPa] 900 1000 Longitude Longitude Longitude Longitude Bretherton et al. (2010)
Similar presentations
© 2025 SlidePlayer.com. Inc.
All rights reserved.