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aerocom:indirect [2013-10-01 19:49:35]
steve.ghan@pnnl.gov
aerocom:indirect [2014-03-25 14:56:22]
steve.ghan@pnnl.gov
Line 21: Line 21:
    all_2000: simulation PD (present-day): year 2000 IPCC aerosol emissions \\     all_2000: simulation PD (present-day): year 2000 IPCC aerosol emissions \\ 
    all_1850: simulation PI (pre-industrial): year 1850 IPCC aerosol emissions (year 2000 GHG concentration)  \\     all_1850: simulation PI (pre-industrial): year 1850 IPCC aerosol emissions (year 2000 GHG concentration)  \\ 
-   hom_2000: present day emissions no heterogeneous nucleation of ice \\ +   hom_2000: present day emissions no heterogeneous nucleation of ice in cirrus clouds with T%%<%%-37 C\\ 
-   hom_1850: pre-industrial emissions no heterogeneous nucleation of ice \\ +   hom_1850: as in hom_2000, but for pre-industrial emissions \\ 
-   fix_2000: present day emissions fixed ice nucleation for T%%<%%-37 C using Cooper (1986) as a f(temperature) \\ +   fix_2000: present day emissions fixed ice nucleation for T%%<%%-37 C using a constant ice number of 383.6 /L, which is from Cooper (1986) at T=-37C \\ 
-   fix_1850: pre-industrial emissions fixed ice nucleation for T%%<%%-37 C using Cooper (1986) as f(temperature) \\+   fix_1850: as in fix_2000, but for pre-industrial emissions  \\
  
 +
 +== Motivation ==
 +
 +The proposed study is designed to address two key areas of uncertainty: 1) the sensitivity of cloud liquid water path to aerosol, and 2) the competition between heterogeneous and homogeneous nucleation of ice crystals. 
 +
 +To address issue 1), we’ve added daily and monthly diagnostics that can be compared with CloudSat and MODIS retrievals of the relationship between the aerosol optical depth and the probability of precipitation (Wang et al., 2012). 
 +
 +To address issue 2), we’ve added experiments in which heterogeneous nucleation is neglected for T%%<%%-37C, and in which ice nucleation for T%%<%%-37C is a prescribed function of temperature (Cooper, 1986).
 +
 +We also have added a requirement to nudge toward analyzed winds, which we’ve found greatly reduces the noise due to natural variability without significantly inhibiting the cloud response to the aerosol. (Kooperman et al., 2012). Simulations of six years duration each should be sufficient for all experiments. 
 +
 +To facilitate analysis and comparison before the 2013 AeroCom meeting, the results should be submitted to the AeroCom repository by December 1, 2013. Please contact steve.ghan@pnnl.gov and xiaohong.liu@pnnl.gov when your results have been submitted.
 +
 +
 +Cooper, W. A.: Ice initiation in natural clouds. precipitation enhancement – a scientific challenge, Meteor. Mon., 43, 29–32, 1986.
 +
 +Kooperman, G. J., M. S. Pritchard, S. J. Ghan, R. C. J. Sommerville, and L. M. Russell, 2012: Constraining the influence of natural variability to improve estimates of global aerosol indirect effects in a nudged version of the Community Atmosphere Model 5. J. Geophys. Res., 117, doi:10.1029/2012JD018588.
 +
 +Wang, M., S. Ghan, X. Liu, T. L’Ecuyer, K. Zhang, H. Morrison, M. Ovchinnikov, R. Easter, R. Marchand, D. Chand, Y. Qian, and J. E. Penner, 2012: Strong constraints on cloud lifetime effects of aerosol using satellite observations. Geophys. Res. Lett., 39, 15, doi:10.1029/2012GL052204.
  
          
Line 31: Line 50:
  
    All data except COSP diagnostics is to be collected at the AEROCOM server. \\     All data except COSP diagnostics is to be collected at the AEROCOM server. \\ 
-   Groups hold COSP diagnostics until analyst is identified \\+   Groups hold COSP diagnostics and contact Kenta Suzuki (Kentaro.Suzuki@jpl.nasa.gov) for analysis  \\
    follow the aerocom data protocol (http://aerocom.met.no/protocol.html) \\     follow the aerocom data protocol (http://aerocom.met.no/protocol.html) \\ 
    Data in NetCDF format, one variable and year per file with CMOR variable names \\     Data in NetCDF format, one variable and year per file with CMOR variable names \\ 
Line 39: Line 58:
     <ExperimentName> = all_2000, all_1850, hom_2000, hom_1850, fix_2000, or fix_1850      <ExperimentName> = all_2000, all_1850, hom_2000, hom_1850, fix_2000, or fix_1850 
     <VariableName> see list below      <VariableName> see list below 
-    <VerticalCoordinateType> => "Surface", "Column", "ModelLevel" +    <VerticalCoordinateType> => "Surface", "TOA", "Column", "ModelLevel" 
     <Period> => "2008", "2010", ...       <Period> => "2008", "2010", ...  
     <Frequency> => "timeinvariant","hourly", ,"3hourly", "daily", "monthly"      <Frequency> => "timeinvariant","hourly", ,"3hourly", "daily", "monthly" 
Line 51: Line 70:
 (1) 2D diagnostics for evaluation with satellite data (1) 2D diagnostics for evaluation with satellite data
  
-5 years (years 2006-2010) of 3-hourly data from the PD run+5 years (years 2006-2010) of 3-hourly instantaneous data from the PD run
 ====== ======
 ^ name ^ long_name (CF if possible) ^ units ^ description ^ ^ name ^ long_name (CF if possible) ^ units ^ description ^
-| od550aer  | atmosphere_optical_thickness_due_to_aerosol | 1 | Aerosol optical depth (@ 550 nm) | +| od550aer  | atmosphere_optical_thickness_due_to_aerosol | 1 | Aerosol optical depth (@ 550 nm) | 
-| angstrm |  AOD_Angstrom_exponent | 1 | | +| angstrm | AOD_Angstrom_exponent | 1 | | 
-| aerindex |aerosol_index  | 1  |  AOD*angstrm +| aerindex |aerosol_index  | 1  | od550aer*angstrm | 
-| cdr | liquid_cloud-top_droplet_effective_radius | m  | Grid cell mean droplet effective radius at top of liquid water clouds | +| cdr | liquid_cloud-top_droplet_effective_radius | m  | Grid cell mean droplet effective radius at top of liquid water clouds | 
-| cdnc | liquid_cloud_droplet_number_concentration | m-3 | Grid cell mean droplet number concentration in top layer of liquid water clouds | +| cdnc | liquid_cloud_droplet_number_concentration | m-3 | Grid cell mean droplet number concentration in top layer of liquid water clouds | 
-| cdnum  | column_cloud_droplet_number_concentration    |   m-2  |   grid cell mean column total | +| cdnum  | column_cloud_droplet_number_concentration    | m-2  | grid cell mean column total | 
-| icnum  | column_ice_crystal_number_concentration    |   m-2  |   grid cell mean column total | +| icnum  | column_ice_crystal_number_concentration    | m-2  | grid cell mean column total | 
-| clt | cloud_area_fraction | 1 | Fractional cover by all clouds | +| clt | cloud_area_fraction | 1 | Fractional cover by all clouds | 
-| lcc | liquid_cloud_area_fraction  | 1 | Fractional cover by liquid water clouds | +| lcc | liquid_cloud_area_fraction  | 1 | Fractional cover by liquid water clouds | 
-| lwp | atmosphere_cloud_ice_content | kg m-2 | grid cell mean liquid water path for liquid water clouds | +| lwp | atmosphere_cloud_liquid_path | kg m-2 | grid cell mean liquid water path for liquid water clouds | 
-| iwp  | atmosphere_cloud_ice_content | kg m-2 |  grid cell mean ice water path for ice clouds | +| iwp | atmosphere_cloud_ice_path | kg m-2 | grid cell mean ice water path for ice clouds | 
-| icr | cloud-top_ice_crystal_effective_radius |  m | grid cell mean effective radius of crystals at top of ice clouds | +| icr | cloud-top_ice_crystal_effective_radius | m | grid cell mean effective radius of crystals at top of ice clouds | 
-| icc | ice_cloud_area_fraction | 1  | Fractional cover by ice clouds | +| icc | ice_cloud_area_fraction | 1  | Fractional cover by ice clouds | 
-| cod | atmosphere_optical_thickness_due_to_clouds | 1 | Grid cell mean cloud optical depth | +| cod | cloud_optical_depth | 1 | Grid cell mean cloud optical depth | 
-| codliq | atmosphere_optical_thickness_due_to_liquid_clouds | 1 | Grid cell mean cloud optical depth | +| codliq | cloud_optical_depth_due_to_liquid | 1 | Grid cell mean cloud optical depth | 
-| codice | atmosphere_optical_thickness_due_to_ice_clouds | 1 | Grid cell mean cloud optical depth | +| codice | cloud_optical_depth_due_to_ice | 1 | Grid cell mean cloud optical depth | 
-| ccn0.1bl | cloud_condensation_nuclei_0.1_pbl | m-3 | grid-cell mean CCN number concentration at S=0.1% at 1 km above the surface | +| ccn0.1bl | cloud_condensation_nuclei_0.1_pbl | m-3 | CCN number concentration at S=0.1% at 1 km above the surface | 
-| ccn0.3bl | cloud_condensation_nuclei_0.3_pbl | m-3 | grid-cell mean CCN number concentration at S=0.3% at 1 km above the surface | +| ccn0.3bl | cloud_condensation_nuclei_0.3_pbl | m-3 | CCN number concentration at S=0.3% at 1 km above the surface | 
-| colccn.1 | column_cloud_condensation_nuclei_0.1 | m-2 | grid-cell mean column-integrated CCN number concentration at S=0.1% +| colccn.1 | column_cloud_condensation_nuclei_0.1 | m-2 | column-integrated CCN number concentration at S=0.1% 
-| colccn.3 | column_cloud_condensation_nuclei_0.3 | m-2 | grid-cell mean column-integrated CCN number concentration at S=0.3% +| colccn.3 | column_cloud_condensation_nuclei_0.3 | m-2 | column-integrated CCN number concentration at S=0.3% 
-| rsut | toa_upward_shortwave_flux | W m-2 | TOA upward SW flux, all-sky | +| rsut | toa_upward_shortwave_flux | W m-2 | TOA upward SW flux, all-sky | 
-| rsutcs | toa_upward_shortwave_flux_assuming_clear_sky | W m-2 | TOA upward SW flux, clear-sky | +| rsutcs | toa_upward_shortwave_flux_assuming_clear_sky | W m-2 | TOA upward SW flux, clear-sky | 
-| rsutnoa | toa_upward_shortwave_flux_no_aerosol | W m-2 | TOA upward SW flux, all-sky, aerosol removed from calculation | +| rsutnoa | toa_upward_shortwave_flux_no_aerosol | W m-2 | TOA upward SW flux, all-sky, aerosol removed from calculation | 
-| rsutcsnoa | toa_upward_shortwave_flux_clear_sky_no_aerosol |W m-2 | TOA upward SW flux, clear-sky, aerosol removed from calculation | +| rsutcsnoa | toa_upward_shortwave_flux_clear_sky_no_aerosol |W m-2 | TOA upward SW flux, clear-sky, aerosol removed from calculation | 
-| rlut | toa_upward_longwave_flux | W m-2 | TOA upward LW flux, all-sky | +| rlut | toa_upward_longwave_flux | W m-2 | TOA upward LW flux, all-sky | 
-| rlutcs | toa_upward_longwave_flux_assuming_clear_sky | W m-2 | TOA upward LW flux, clear-sky | +| rlutcs | toa_upward_longwave_flux_assuming_clear_sky | W m-2 | TOA upward LW flux, clear-sky | 
-| hfls | surface_upward_latent_heat_flux | W m-2 | Surface latent heat flux | +| hfls | surface_upward_latent_heat_flux | W m-2 | Surface latent heat flux | 
-| hfss | surface_upward_sensible_heat_flux  | W m-2 | Surface sensible heat flux | +| hfss | surface_upward_sensible_heat_flux  | W m-2 | Surface sensible heat flux | 
-| rls | surface_net_downward_longwave_flux_in_air | W m-2 | Net surface LW downward flux | +| rls | surface_net_downward_longwave_flux_in_air | W m-2 | Net surface LW downward flux | 
-| rss | surface_net_downward_shortwave_flux | W m-2 | Net surface SW downward flux | +| rss | surface_net_downward_shortwave_flux | W m-2 | Net surface SW downward flux | 
-| rsds | surface_downwelling_shortwave_flux_in_air | W m-2 | Surface SW downward flux (in order to estimate the model's 'true' surface albedo) | +| rsds | surface_downwelling_shortwave_flux_in_air | W m-2 | Surface SW downward flux (to estimate the model's 'true' surface albedo) | 
-| ttop | air_temperature_at_cloud_top | K | Temperature at top of clouds | +| ttop | air_temperature_at_cloud_top | K | Temperature at top of clouds, weighted by cloud cover 
-| lts | lower_tropospheric_stability | K | Difference in potential temperature between 700 hPa and 1000 hPa | +| lts | lower_tropospheric_stability | K | Difference in potential temperature between 700 hPa and 1000 hPa | 
-| w500  |  vertical_velocity_dpdt_at_500_hPa | hPa s-1 | | +| w500  | vertical_velocity_dpdt_at_500_hPa | hPa s-1 | | 
-| sprecip | stratiform_precipitation_rate |kg m-2 s-1 | grid cell mean at surface | +| sprecip | stratiform_precipitation_rate | kg m-2 s-1 | grid cell mean at surface | 
-| autoconv | column_autoconversion_rate | kg m-2 s-1 | grid cell mean column total | +| autoconv | column_autoconversion_rate | kg m-2 s-1 | grid cell mean column total | 
-| accretn | column_accretion_rate | kg m-2 s-1 | grid cell mean column total |+| accretn | column_accretion_rate | kg m-2 s-1 | grid cell mean column total |
  
 ===== =====
  
-(2) For forcing estimates: as in (1), but monthly-mean fields for both PD and PI simulations+(2) For forcing estimates: as in (1), but monthly-mean fields for both PD and PI simulations, plus a land-ocean mask (0 land, 1 ocean).
  
 (3) 3D monthly mean diagnostics (3) 3D monthly mean diagnostics
  
 ^ name ^ long_name (CF if possible) ^ units ^ description ^ ^ name ^ long_name (CF if possible) ^ units ^ description ^
-| t | temperature | K | |  +| t | temperature | K | each layer |  
-| hus | specific_humidity | kg/kg | |  +| hus | specific_humidity | kg/kg | each layer |  
-| z | altitude          | m       | each layer |  +| z | altitude          | m       | each layer |  
-| airmass | atmosphere_mass_content_of_air    |  kg m-2    each layer  | +| airmass | atmosphere_mass_content_of_air    | kg m-2   | each layer  | 
-| ccn0.1 | cloud_condensation_nuclei_0.1 | m-3 | grid cell mean each layer (S=0.1%) | +| ccn0.1 | cloud_condensation_nuclei_0.1 | m-3 | each layer (S=0.1%) | 
-| ccn0.3 | cloud_condensation_nuclei_0.3 | m-3 | grid cell mean each layer (S=0.3%) | +| ccn0.3 | cloud_condensation_nuclei_0.3 | m-3 | each layer (S=0.3%) | 
-| nc | liquid_cloud_droplet_number_concentration | m-3 | grid cell mean each layer | +| nc | liquid_cloud_droplet_number_concentration | m-3 | grid cell mean each layer | 
-| lwc| cloud_liquid_water_content | kg m-3 | grid cell mean each layer | +| lwc| cloud_liquid_water_content | kg m-3 | grid cell mean each layer | 
-ewl | droplet_effective_radius  | m| grid cell mean each layer | +rel | droplet_effective_radius  | m| grid cell mean each layer | 
-| lccl | liquid_cloud_fraction | 1 | Fractional cover by liquid water clouds each layer | +| lccl | liquid_cloud_fraction | 1 | Fractional cover by liquid water clouds each layer | 
-| wsubc | subgrid_vertical_velocity_for_stratiform | wsubc | m s-1 |  +| wsubc | subgrid_vertical_velocity_for_stratiform | m s-1 |  
-| autocl  | autoconversion_rate | kg m-2 s-1 | layer total in grid cell | +| autocl  | autoconversion_rate | kg m-2 s-1 | layer total in grid cell | 
-| accretl  | accretion_rate | kg m-2 s-1 | layer total in grid cell | +| accretl  | accretion_rate | kg m-2 s-1 | layer total in grid cell | 
-| ni | ice_cloud_crystal_number_concentration | m-3 | grid cell mean each layer | +| ni | ice_cloud_crystal_number_concentration | m-3 | grid cell mean each layer | 
-| iwc | cloud_ice_water_content | kg m-3 | grid cell mean each layer | +| iwc | cloud_ice_water_content | kg m-3 | grid cell mean each layer | 
-| rei | Ice_effective_radius | m | grid cell mean each layer | +| rei | Ice_effective_radius | m | grid cell mean each layer | 
-| iccl  | ice_cloud_fraction | 1 | Fractional cover by ice water clouds each layer | +| iccl  | ice_cloud_fraction | 1 | Fractional cover by ice water clouds each layer | 
-| sati  | ice_supersaturation | 1 | Supersaturation with respect to ice | +| sati  | ice_supersaturation | 1 | Supersaturation with respect to ice | 
-| wsubi  | subgrid_vertical_velocity_for_cirrus | m s-1 | +| wsubi  | subgrid_vertical_velocity_for_cirrus | m s-1 |  | 
-| cirrus_nso4  | sulfate_aerosol_number_for_homogeneous | m-3 | grid cell mean sulfate aerosol number used for homogeneous aerosol freezing for T<-37C +| mmrdu | mass_fraction_of_dust_dry_aerosol_in_air | kg/kg | each layer  | 
-| cirrus_ndust  | dust_aerosol_number_for_heterogeneous | m-3 | grid cell mean dust aerosol number used for heterogeneous aerosol freezing for T<-37C +| mmrbc | mass_fraction_of_black_carbon_dry_aerosol_in_air | kg/kg |each layer  | 
-| cirrus_nbc  | BC_aerosol_number_for_heterogeneous | m-3 | grid cell mean BC aerosol number used for heterogeneous aerosol freezing for T<-37C +| mmrso4 | mass_fraction_of_sulfate_dry_aerosol_in_air | kg/kg | each layer  | 
-| cirrus_nihom  | homogeneous_nucleation_number | m-3 | grid cell mean ice crystal number production from homogeneous aerosol freezing for T<-37C during one model time step | +| cirrus_nso4  | sulfate_aerosol_number_for_homogeneous | m-3 | grid cell mean sulfate aerosol number used for homogeneous aerosol freezing even if ice not nucleated
-| cirrus_nihet  | heterogeneous_nucleation_number | m-3 | grid cell mean ice crystal number production from heterogeneous aerosol freezing for T<-37C during one model time step | +| cirrus_ndust  | dust_aerosol_number_for_heterogeneous | m-3 | grid cell mean dust aerosol number used for heterogeneous aerosol freezing even if ice not nucleated 
-| cirrus_freqhom | homogeneous_nucleation_frequency | 1 | frequency counter of homogeneous aerosol freezing for T<-37C. For each time step, freqhom = 1 if homogeneous ice nucleation happens; otherwise freqhom = 0. Monthly average of this value indicates the homogeneous nucleation frequency. | +| cirrus_nbc  | BC_aerosol_number_for_heterogeneous | m-3 | grid cell mean BC aerosol number used for heterogeneous aerosol freezing even if ice not nucleated 
-| cirrus_freqhet  | heterogeneous_nucleation_frequency | 1 | frequency counter of heterogeneous aerosol freezing for T<-37C. At each model time step, set freqhom = 1 if heterogeneous ice nucleation happens; otherwise freqhom = 0. Monthly average of this value indicates the heterogeneous nucleation frequency. | +| cirrus_nihom  | homogeneous_nucleation_number | m-3 | grid cell mean ice crystal number production from homogeneous aerosol freezing for T%%<%%-37C during one model time step | 
-| mp_hetnuc  | droplet_freezing_rate_by_heterogeneous | m-3 s-1 | grid cell mean freezing rate of cloud droplets in mixed-phase clouds for T>-37C | +| cirrus_nihet  | heterogeneous_nucleation_number | m-3 | grid cell mean ice crystal number production from heterogeneous aerosol freezing for T%%<%%-37C during one model time step | 
-| mp_homnuc  | droplet_freezing_rate_by_homogeneous | m-3 s-1 | grid cell mean instantaneous freezing rate of cloud droplets for T<=-37C |+| cirrus_freqhom | homogeneous_nucleation_frequency | 1 | frequency counter of homogeneous aerosol freezing for T%%<%%-37C. For each time step, freqhom = 1 if homogeneous ice nucleation happens; otherwise freqhom = 0. Monthly average of this value indicates the homogeneous nucleation frequency. | 
 +| cirrus_freqhet  | heterogeneous_nucleation_frequency | 1 | frequency counter of heterogeneous aerosol freezing for T%%<%%-37C. At each model time step, set freqhom = 1 if heterogeneous ice nucleation happens; otherwise freqhom = 0. Monthly average of this value indicates the heterogeneous nucleation frequency. | 
 +| mp_hetnuc  | droplet_freezing_rate_by_heterogeneous | m-3 s-1 | grid cell mean freezing rate of cloud droplets in mixed-phase clouds for T>-37C | 
 +| mp_homnuc  | droplet_freezing_rate_by_homogeneous | m-3 s-1 | grid cell mean instantaneous freezing rate of cloud droplets for T<=-37C |
 ===== =====
  
-(4) Optional CFMIP COSP diagnostics. Highly desirable but optional for now \\  +(4) Optional CFMIP COSP diagnostics. Highly desirable for models with COSP \\  
-3-hr snapshots and daily means for January-March 2008 PD simulation only. +3-hr snapshots and daily means for January-March 2008 PD simulation only.\\ 
 +(a) 2D
 ^ name ^ long_name (CF if possible) ^ units ^ description ^ comment ^ notes ^ ^ name ^ long_name (CF if possible) ^ units ^ description ^ comment ^ notes ^
-temperature | K |  each layer |  +clwmodis modis_liquid_cloud_fraction | 1 | Column fractional cover by liquid water clouds  from modis simulator 
-| z | altitude          | m       | each layer |  +reffclwmodis modis_droplet_effective_radius*clwmodis  | m | grid cell mean  from modis simulator 
-| airmass | atmosphere_mass_content_of_air    |  kg m-2    each layer  | +climodis  modis_ice_cloud_fraction |1 | Column fractional cover by ice water clouds  |from modis simulator |  | 
-| ccn0.1 | cloud_condensation_nuclei_0.1 | m-3 | grid cell mean each layer (S=0.1%) | +reffclimodis modis_ice_effective_radius*climodis grid cell mean  from modis simulator 
-| ccn0.3 | cloud_condensation_nuclei_0.3 | m-3 | grid cell mean each layer (S=0.3%) | +tauwmodis modis_liquid_cloud_optical_thickness*clwmodis | 1 | grid cell mean from modis simulator 
-| nc | liquid_cloud_droplet_number_concentration | m-3 | grid cell mean each layer | +tauimodis modis_ice_cloud_optical_thickness*climodis | 1 | grid cell mean from modis simulator |
-| lwc| cloud_liquid_water_content | kg m-3 | grid cell mean each layer | +
-| ewl | droplet_effective_radius  | m| grid cell mean each layer | +
-| lccl | liquid_cloud_fraction | 1 | Fractional cover by liquid water clouds each layer | +
-| ni | ice_cloud_crystal_number_concentration | m-3 | grid cell mean each layer +
-iwc cloud_ice_water_content | kg m-3 | grid cell mean each layer | +
-| rei | Ice_effective_radius | m | grid cell mean each layer +
-iccl  ice_cloud_fraction | 1 | Fractional cover by ice water clouds each layer | |  | +
-dbze94  | 94GHz_radar_reflectivity_subcolumn | dBZe  | Radar reflectivity each model layer in 70 subcolumns   +
-fracout fracout_cloud_flag_subcolumn 1 | subcolumn cloud flag each model layer in 70 subcolumns 0 clear, 1 strat 2 conv | +
-| clcalipso | cloud_area_fraction_in_atmosphere_layer | % | CALIPSO Cloud Area Fraction | | at 40 height levels +
-clcalipso2   cloud_area_fraction_in_atmosphere_layer | % | CALIPSO Cloud Fraction Undetected by CloudSat | Clouds detected by CALIPSO but below the detectability threshold of CloudSat | at 40 height levels | +
-| cfadDbze94 | histogram_of_equivalent_reflectivity_factor_over_height_above_reference_ellipsoid | 1 | CloudSat Radar Reflectivity CFAD CFADs (Cloud Frequency Altitude Diagrams) are joint height - radar reflectivity  distributions. | 40 levels x 15 bins +
-cfadLidarsr532 histogram_of_backscattering_ratio_over_height_above_reference_ellipsoid | 1 | CALIPSO Scattering Ratio CFAD | CFADs (Cloud Frequency Altitude Diagrams) are joint height - lidar scattering ratio distributions. 40 levels x 15 bins |+
 | parasolRefl | toa_bidirectional_reflectance | 1 | PARASOL Reflectance | Simulated reflectance from PARASOL as seen at the top of the atmosphere for 5 solar zenith angles. Valid only over ocean and for one viewing direction (viewing zenith angle of 30 degrees and relative azimuth angle 320 degrees). | | | parasolRefl | toa_bidirectional_reflectance | 1 | PARASOL Reflectance | Simulated reflectance from PARASOL as seen at the top of the atmosphere for 5 solar zenith angles. Valid only over ocean and for one viewing direction (viewing zenith angle of 30 degrees and relative azimuth angle 320 degrees). | |
 | cltcalipso | cloud_area_fraction | % | CALIPSO Total Cloud Fraction  | | | | cltcalipso | cloud_area_fraction | % | CALIPSO Total Cloud Fraction  | | |
Line 158: Line 167:
 | clhcalipso | cloud_area_fraction_in_atmosphere_layer | % | CALIPSO High Level Cloud Fraction  | | | | clhcalipso | cloud_area_fraction_in_atmosphere_layer | % | CALIPSO High Level Cloud Fraction  | | |
  
 +
 +=====
 +
 +(b) 3D
 +
 +^ name ^ long_name (CF if possible) ^ units ^ description ^ comment ^ notes ^
 +| t | temperature | K | each layer |
 +| z | altitude          | m       | each layer |
 +| pressure | atmospheric_pressure          | Pa  | each layer |
 +| airmass | atmosphere_mass_content_of_air    | kg m-2   | each layer  |
 +| ccn0.1 | cloud_condensation_nuclei_0.1 | m-3 | each layer (S=0.1%) |
 +| ccn0.3 | cloud_condensation_nuclei_0.3 | m-3 | each layer (S=0.3%) |
 +| nc | liquid_cloud_droplet_number_concentration | m-3 | grid cell mean each layer |
 +| lwc| cloud_liquid_water_content | kg m-3 | grid cell mean each layer stratiform cld only|  |
 +| rel | droplet_effective_radius | m | grid cell mean each layer stratiform cld only  |  |
 +| lccl | layer_liquid_cloud_fraction | 1 | Fractional cover by liquid water stratiform clouds each layer |
 +| ni | ice_cloud_crystal_number_concentration | m-3 | grid cell mean each layer |
 +| iwc | cloud_ice_water_content | kg m-3 | grid cell mean each layer stratiform cld only|
 +| rei | ice_effective_radius | m | grid cell mean each layer stratiform cld only |        | |
 +| iccl   | layer_ice_cloud_fraction  | 1 | Fractional cover by ice water stratiform clouds each layer | |  |
 +| dbze94  | 94GHz_radar_reflectivity_subcolumn | dBZe  | Radar reflectivity each model layer in 100 subcolumns   |
 +| fracout | fracout_cloud_flag_subcolumn | 1 | subcolumn cloud flag each model layer in 100 subcolumns 0 clear, 1 strat 2 conv |
 +| clcalipso | cloud_area_fraction_in_atmosphere_layer | % | CALIPSO Cloud Area Fraction |  | at 40 height levels |
 +| clcalipso2   | cloud_area_fraction_in_atmosphere_layer | % | CALIPSO Cloud Fraction Undetected by CloudSat | Clouds detected by CALIPSO but below the detectability threshold of CloudSat | at 40 height levels |
 +| cfadDbze94 | histogram_of_equivalent_reflectivity_factor_over_height_above_reference_ellipsoid | 1 | CloudSat Radar Reflectivity CFAD | CFADs (Cloud Frequency Altitude Diagrams) are joint height - radar reflectivity  distributions. | 40 levels x 15 bins |
 +| cfadLidarsr532 | histogram_of_backscattering_ratio_over_height_above_reference_ellipsoid | 1 | CALIPSO Scattering Ratio CFAD | CFADs (Cloud Frequency Altitude Diagrams) are joint height - lidar scattering ratio distributions. | 40 levels x 15 bins |
  
 ===== =====
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 The idea is to use the cloud overlap assumption (maximum, random, or maximum-random) to estimate which part of the cloud in a  \\ layer can be seen from above. The idea is to use the cloud overlap assumption (maximum, random, or maximum-random) to estimate which part of the cloud in a  \\ layer can be seen from above.
  
-Note: For the CCN, whether to sample it in the same way as CDNC, or use a similar apporach (going from bottom up)  \\  +Note: For the CCN, whether to sample it in the same way as CDNC, or use a similar approach (going from bottom up)  \\  
 to sample it at cloud base depends on your parameterization of the activation. to sample it at cloud base depends on your parameterization of the activation.
  
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     f3d(nx,nz) cloud fraction     f3d(nx,nz) cloud fraction
     t3d(nx,nz) temperature     t3d(nx,nz) temperature
-    phase3d(nx,nz) cloud thermodynamic phase (0: entire cloud consists of ice, 1: entire cloud consists of liquid water, between 0 and 1: mixed-phase) +    phase3d(nx,nz) cloud thermodynamic phase (0: entire cloud consists of ice,  
-    cdr3d(nx,nz) cloud droplet effective radius +    1: entire cloud consists of liquid water, between 0 and 1: mixed-phase) 
-    icr3d(nx,nz) ice crystal effective radius +    phase3d could be from fice3d/f3d where fice3d=ice+mixed phase cloud fraction 
-    cdnc3d(nx,nz) cloud droplet number concentration +    cdr3d(nx,nz) in-cloud  droplet effective radius 
 +    icr3d(nx,nz) in-cloud ice crystal effective radius 
 +    cdnc3d(nx,nz) in-cloud droplet number concentration 
  
 thres_cld = 0.001 \\  thres_cld = 0.001 \\ 
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  ==== Q/A ====  ==== Q/A ====
  
-    2D cloud fields (lwp, iwp, cdr, cdnc, cod): Please compute them from grid-box mean values at each level but DO NOT divide by the total (2D) cloud cover, which will be done in analysis after averaging in time and space. +    2D cloud fields (lwp, iwp, cdr, cdnc, ttop, cod): Please save them as grid-box mean values but DO NOT divide by the total (2D) cloud cover, which will be done in analysis after averaging in time and space. 
                    
     The three months 1 October - 31 December 2005  are thought as spin-up, which can of course be longer. Please choose as overlap assumption the one you use in the radiation scheme.       The three months 1 October - 31 December 2005  are thought as spin-up, which can of course be longer. Please choose as overlap assumption the one you use in the radiation scheme.  
  • aerocom/indirect.txt
  • Last modified: 2022-05-31 09:29:31
  • (external edit)