Atmospheric Boundary Layer over Land, Ocean, and Ice. Xubin Zeng, Michael Brunke, Josh Welty, Patrick Broxton University of Arizona
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1 Atmospheric Boundary Layer over Land, Ocean, and Ice Xubin Zeng, Michael Brunke, Josh Welty, Patrick Broxton University of Arizona 24 October 2017 Future of ABL Observations Workshop Warrenton, Virginia 1
2 Outline 1. ABL over oceans 2. Land-ABL-clouds interaction 3. Humidity inversion over polar regions 4. Snow impact on seasonal prediction 5. Overarching science question First light image released from GOES-R (GOES-16) 2
3 1. ABL over oceans Zeng et al. (2004) importance of measurements over a seasonal cycle Need of more model vertical layers in ABL 26 layers 52 layers 104 layers 20 m Clear Median (m) IQR (m) Correlation Cloudy Median (m) IQR (m) Correlation ABL heights Dark: radiosondes with IQRs Light: NCAR climate model
4 (a) (b) 1.0 Ship 0.8 ASTEX (sfc.) FIRE RACE Cloud thickness (m) Cloud fraction TIWE (sfc.) ASTEX (air) CloudSat/ CALIPSO or CloudSat/ MODIS CloudSat/ CALIPSO or CloudSat/ MODIS (adjusted) CAM3.1 CloudSat/CALIPSO or CloudSat/MODIS frequency 0.2 CAM LWP (g m -2 ) LWP (g m -2 ) Brunke et al. (2010) Surface-based measurements are important for the evaluation of both satellite products and climate models
5 2. Land-ABL-cloud-precipitation interactions Importance of measuring turbulent & radiative fluxes as well as precipitation & thermodynamic variables 2002 JJAS ARM + STAGE IV Green Wetter Soil Welty et al. (2017 Orange Drier Soil in preparation)
6 3. Specific humidity inversion over polar regions Humidity inversion q-inversion strength This is one difference in ABL between polar regions and lower latitudes More measurements are needed to reduce reanalysis differences Brunke et al. (2015)
7 Connection to Various Processes (MERRA) Averaged over all grids over Arctic for layers where q inversion exists Turbulence is more important in summer than in winter Horizontal wind measurements are needed to quantify q advection 7
8 4. Snow impact on CFS seasonal prediction Broxton et al. (2017) Apr 1 st minus Jan 1 st forecast of model quantities for Apr-Jun averaged from Importance of measuring global SWE from remote sensing 8
9 dswe, dt2m, dsst difference between Jan 1 st and Apr 1 st forecasts of SWE, T2m, and SST Temporal correlation (from ) between dswe on Apr 1 st and Apr-Jun dt2m (grid-to-grid); correlation between Apr-Jun dsst (over oceans > 30 o N) and Apr-Jun dt2m Over Land, SWE affects other variables (e.g. T2M) in April- June more strongly than do SSTs, whose influence is mostly felt on the edges of continents 9
10 5. Overarching science question Q: What observations are needed (over land, ocean, and ice) to make meaningful progress in understanding and modeling global ABL? ABL horizontal wind: Satellite: Doppler lidar wind profiling & hyperspectral infrared sounding Ground: near-surface microwave scatterometer wind over ocean, ground-based wind profiling, and vertical profiles from radiosondes & commercial aircraft measurements during taking off and landing. ABL Temperature and humidity: Satellite: microwave and hyperspectral infrared sounding with GNSS radio occultation Ground: ground based systems (e.g., Raman lidar) and vertical profiles from radiosondes and commercial aircraft measurements during taking off and landing ABL measurements need to resolve the diurnal cycle and cover the seasonal cycle We need to bring various observations together in a dynamically consistent way through data assimilation and numerical modeling 10
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