The effects of dust emission on the trans- Pacific transport of Asian dust in the CESM Mingxuan Wu, Xiaohong Liu, Zhien Wang, Kang Yang, Chenglai Wu University of Wyoming Kai Zhang, Hailong Wang Pacific Northwest National Laboratory Tao Luo Anhui Institute of Optics and Fine Mechanics, CAS AMWG/CCWG/WACCM Feb 12 Feb 14, 2018
1. Introduction Dust plays an important role in the Earth s climate system. It directly influences radiation budget by scattering and absorbing shortwave and longwave radiation. Dust can change the size and number concentrations of cloud droplets and ice crystals by acting as cloud condensational nuclei (CCN) and ice nucleating particles (INP). Dust Event in East Asia on MAR 4, 2017
1. Introduction AeroCom Phase I results show that large diversity exists in the simulated dust budgets, although GCMs can reproduce the main aspects of dust cycle (Huneeus et al., 2011). AeroCom Phase II results suggest that models have difficulties in simulating horizontal and vertical transport of North Africa dust across the Atlantic (Kim et al., 2014). How s the capability of CESM in simulating the dust transport across the Pacific? How does dust emission scheme affect the dust transport across the Pacific? Dust emission from CMIP5, courtesy Chenglai Wu
2. Method Model Configuration and Experiments CAM5 setup Configuration: CAM5.3.52, MG microphysics, MAM4, CLM4.0, prescribed SST Runtime period: 2006-08 to 2007-12, last 12 months for analysis Resolution: 1.9 o 2.5 o Meteorology: U, V nudged to ERA-interim Reanalysis Tuned dust emissions, AOD in dusty region (DOD/AOD > 0.5) matches Terra/Aqua MODIS observations. Data collocation, modeled nighttime dust extinction extracted along the CALIPSO track compared with new dust extinction datasets (Luo et al., 2015a, b). Experiments Z03: default experiment, dust emission scheme by Zender et al. (2003) Z03 SGV: considering sub-grid surface wind variability, following Zhang et al. (2016) K14: dust emission scheme by Kok et al. (2014a, b) G01: dust emission scheme by Ginoux et al. (2001)
2. Method Dust Emission Scheme Zender et al., (2003) (default scheme, Z03) Use source function S to shift emissions toward the world s most erodible regions. The total vertical mass flux of dust, F j (kg m -2 s -1 ), from the ground into transport bin j is given by: F j = TSf m α c sρ a u3 s g 1 u t u s Kok et al., (2014a, b) (K14) A new physically based dust emission scheme. Not use source function. The theoretical expression for dust emission is given by: ρ a u 2 2 u t F d = C d f bare f clay u st 2 F p = CSs p u 10m u 10m u t 1 + u t u s u u t C α u st u st0 u st0 Ginoux et al., (2001) (GOCART, G01) Use source function S. The dust flux F p of particle size class p is given by: Zhang et al., (2016) (SGV) Dust emission flux is calculated multiple times using different wind speed samples of a Weibull probability distribution. 2 I i=1 M i,j
2. Method New Dust Extinction Dataset CALIPSO Level 2 products suffer the difficulties in detecting optically thin dust layers, and do not resolve the dust extinctions from the polluted dust aerosol (dust mixing with smoke). New dust retrievals outperform the currently applied detection algorithms (Liu et al., 2008; Omar et al., 2009). Luo et al., Geophys. Res. Lett., 2015
3. Results Dust Extinction Dust extinction cross section (70E-50W, averaged over 20N-50N) ANN MAM JJA Default CAM5 New dust retrievals CAM5 underestimate dust extinction across the Pacific by 1-2 order of magnitude, failing to capture the elevated high value of dust extinction over the Pacific.
3. Results Dust Extinction Dust extinction profile (90E-90W, 30 degrees interval, annual mean) CAM5 with K14 and G01 further underestimate dust extinction over the Pacific, while Z03 SGV slightly increases the dust extinction.
3. Results Aerosol Optical Depth Spatial distributions of AOD compared with MISR/MODIS/CALIPSO AOD from Z03 and Z03 SGV is higher than observations in source regions, while AOD from K14 and G01 is much lower than observations.
3. Results Dust Optical Depth Spatial distributions of DOD compared with MISR/CALIPSO
3. Results AOD/DOD Longtitude gradident of AOD/DOD AOD DOD DOD/AOD Modeled DOD decreases more strongly from source regions to the Pacific and is much lower than observations. Modeled AOD and DOD from K14 and G01 over source regions are lower than observations, while Z03 and Z03 SGV produce higher AOD and DOD. Notable uncertainties also exist between different observation datasets.
3. Results Dust Emission Gobi Taklamakan Dust emission from K14 is more uniform but much lower than Z03 in East Asia, and dust emission from G01 is the lowest.
3. Results Dust Surface Concentration PM10 derived from visibility of meteorological records Gobi Taklamakan Observed sand and dust storm events from 3h obs >160 80-160 40-80 20-40 <20 PM 10 μg m 3 = 10 8 D v 1.418 m Following method by Wang et al., Atmos. Chem. Phys., 2008
3. Results Dust Surface Concentration Dust surface concentrations during sand and dust storm events Modeled dust surface concentrations from all experiments have poor correlations with observations. Mean dust concentrations from Z03 and Z03 SGV are much more close to observations than K14 and G01.
Results Dust Surface Concentration Suspended dust and blowing dust (visibility 1-10km)
Results Dust Surface Concentration Dust storm and severe dust storm (visibility <1km)
4. Summary 1. CAM5 significantly underestimates the trans-pacific dust transport by 1-2 order of magnitude compared with new dust extinction datasets and other satellite observations. 2. Dust emission plays an important role in the trans-pacific dust transport due to its strength and location. K14 and G01 further underestimate dust extinction across the Pacific, while Z03 SGV slightly increases the dust extinction. 3. CAM5 with Z03 produces reasonable dust surface concentrations in source regions, while the correlation is poor. K14 and G01 significantly underestimate dust emission in East Asia based on the comparison with observed dust surface concentrations.