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- | ATTENTION - THIS WIKI PAGE IS NO LONGER UPDATED - PLEASE GO TO [[http:// | ||
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- | ===== Indirect Effect Experiment Remarks ===== | ||
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- | ==== Indirect forcing experiment ===== | ||
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- | Repository: aerocom-users:/ | ||
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- | ====== | ||
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- | == Data submission deadline == | ||
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- | == Simulation setup == | ||
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- | == Motivation == | ||
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- | The proposed study is designed to address two key areas of uncertainty: | ||
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- | 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). | ||
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- | To address issue 2), we’ve added experiments in which heterogeneous nucleation is neglected for T%%< | ||
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- | 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. | ||
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- | 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. | ||
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- | Cooper, W. A.: Ice initiation in natural clouds. precipitation enhancement – a scientific challenge, Meteor. Mon., 43, 29–32, 1986. | ||
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- | Kooperman, G. J., M. S. Pritchard, S. J. Ghan, R. C. J. Sommerville, | ||
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- | Wang, M., S. Ghan, X. Liu, T. L’Ecuyer, K. Zhang, H. Morrison, M. Ovchinnikov, | ||
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- | === Diagnostics === | ||
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- | In addition to the diagnostics below, it is highly recommended to store the AEROCOM standard and forcing diagnostics, | ||
- | so that the simulations can be analysed for the direct forcing as well, and future more in-depth analyses are possible. | ||
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- | (1) 2D diagnostics for evaluation with satellite data | ||
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- | 5 years (years 2006-2010) of 3-hourly instantaneous data from the PD run | ||
- | ====== | ||
- | ^ name ^ long_name (CF if possible) ^ units ^ description ^ | ||
- | | od550aer | ||
- | | angstrm | AOD_Angstrom_exponent | 1 | | | ||
- | | aerindex |aerosol_index | ||
- | | 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 | | ||
- | | cdnum | column_cloud_droplet_number_concentration | ||
- | | icnum | column_ice_crystal_number_concentration | ||
- | | clt | cloud_area_fraction | 1 | Fractional cover by all clouds | | ||
- | | lcc | liquid_cloud_area_fraction | ||
- | | lwp | atmosphere_cloud_liquid_path | kg m-2 | grid cell mean liquid water path for liquid water 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 | | ||
- | | icc | ice_cloud_area_fraction | 1 | Fractional cover by ice clouds | | ||
- | | cod | cloud_optical_depth | 1 | Grid cell mean cloud optical depth | | ||
- | | codliq | cloud_optical_depth_due_to_liquid | 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 | CCN number concentration at S=0.1% 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 | column-integrated CCN number concentration at S=0.1% | ||
- | | 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 | | ||
- | | 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 | | ||
- | | 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 | | ||
- | | 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 | | ||
- | | hfss | surface_upward_sensible_heat_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 | | ||
- | | rsds | surface_downwelling_shortwave_flux_in_air | W m-2 | Surface SW downward flux (to estimate the model' | ||
- | | 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 | | ||
- | | w500 | vertical_velocity_dpdt_at_500_hPa | hPa s-1 | | | ||
- | | 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 | | ||
- | | accretn | column_accretion_rate | kg m-2 s-1 | grid cell mean column total | | ||
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- | ===== | ||
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- | (2) For forcing estimates: as in (1), but monthly-mean fields for both PD and PI simulations, | ||
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- | (3) 3D monthly mean diagnostics | ||
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- | ^ name ^ long_name (CF if possible) ^ units ^ description ^ | ||
- | | t | temperature | K | each layer | | ||
- | | hus | specific_humidity | kg/kg | each layer | | ||
- | | z | altitude | ||
- | | airmass | atmosphere_mass_content_of_air | ||
- | | 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 | | ||
- | | rel | droplet_effective_radius | ||
- | | lccl | liquid_cloud_fraction | 1 | Fractional cover by liquid water clouds each layer | | ||
- | | wsubc | subgrid_vertical_velocity_for_stratiform | m s-1 | | ||
- | | autocl | ||
- | | accretl | ||
- | | 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 | | ||
- | | sati | ice_supersaturation | 1 | Supersaturation with respect to ice | | ||
- | | wsubi | subgrid_vertical_velocity_for_cirrus | m s-1 | | ||
- | | mmrdu | mass_fraction_of_dust_dry_aerosol_in_air | kg/kg | each layer | | ||
- | | mmrbc | mass_fraction_of_black_carbon_dry_aerosol_in_air | kg/kg |each layer | | ||
- | | mmrso4 | mass_fraction_of_sulfate_dry_aerosol_in_air | kg/kg | each layer | | ||
- | | cirrus_nso4 | ||
- | | cirrus_ndust | ||
- | | cirrus_nbc | ||
- | | cirrus_nihom | ||
- | | cirrus_nihet | ||
- | | cirrus_freqhom | homogeneous_nucleation_frequency | 1 | frequency counter of homogeneous aerosol freezing for T%%< | ||
- | | cirrus_freqhet | ||
- | | mp_hetnuc | ||
- | | mp_homnuc | ||
- | ===== | ||
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- | (4) Optional CFMIP COSP diagnostics. Highly desirable for models with COSP \\ | ||
- | 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 ^ | ||
- | | clwmodis | modis_liquid_cloud_fraction | 1 | Column fractional cover by liquid water clouds | ||
- | | reffclwmodis | modis_droplet_effective_radius*clwmodis | ||
- | | climodis | ||
- | | reffclimodis | modis_ice_effective_radius*climodis | m | grid cell mean | from modis simulator | | ||
- | | tauwmodis | modis_liquid_cloud_optical_thickness*clwmodis | 1 | grid cell mean | from modis simulator | | ||
- | | tauimodis | modis_ice_cloud_optical_thickness*climodis | 1 | grid cell mean | from modis simulator | | ||
- | | 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 | ||
- | | cllcalipso | cloud_area_fraction_in_atmosphere_layer | % | CALIPSO Low Level Cloud Fraction | ||
- | | clmcalipso | cloud_area_fraction_in_atmosphere_layer | % | CALIPSO Middle Level Cloud Fraction | ||
- | | clhcalipso | cloud_area_fraction_in_atmosphere_layer | % | CALIPSO High Level Cloud Fraction | ||
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- | ===== | ||
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- | (b) 3D | ||
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- | ^ name ^ long_name (CF if possible) ^ units ^ description ^ comment ^ notes ^ | ||
- | | t | temperature | K | each layer | | ||
- | | z | altitude | ||
- | | pressure | atmospheric_pressure | ||
- | | airmass | atmosphere_mass_content_of_air | ||
- | | 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 | ||
- | | dbze94 | ||
- | | 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 | ||
- | | 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 | ||
- | | 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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- | ===== | ||
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- | ==Sampling of cloud-top quantities== | ||
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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. | ||
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- | 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. | ||
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- | let i=1, | ||
- | let k=1, | ||
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- | naming convention for the 3D input fields: | ||
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- | iovl is the flag to select the overlap hypothesis | ||
- | cod3d(nx, | ||
- | f3d(nx,nz) cloud fraction | ||
- | t3d(nx,nz) temperature | ||
- | phase3d(nx, | ||
- | 1: entire cloud consists of liquid water, between 0 and 1: mixed-phase) | ||
- | phase3d could be from fice3d/f3d where fice3d=ice+mixed phase cloud fraction | ||
- | cdr3d(nx, | ||
- | icr3d(nx, | ||
- | cdnc3d(nx, | ||
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- | thres_cld = 0.001 \\ | ||
- | thres_cod = 0.3 \\ | ||
- | IF ( iovl = random OR iovl = maximum-random ) THEN | ||
- | clt(i) = 1. | ||
- | ELSE | ||
- | clt(:) = 0 | ||
- | ENDIF \\ | ||
- | icc(:) = 0 \\ | ||
- | lcc(:) = 0 \\ | ||
- | ttop(:) = 0 \\ | ||
- | cdr(:) = 0 \\ | ||
- | icr(:) = 0 \\ | ||
- | cdnc(:) = 0 | ||
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- | DO i=1,nx | ||
- | DO k=2,nz ! assumption: uppermost layer is cloud-free (k=1) | ||
- | IF ( cod3d(i,k) > thres_cod and f3d(i,k) > thres_cld ) THEN ! visible, not-too-small cloud | ||
- | ! flag_max is needed since the vertical integration for maximum overlap is different from the two others: for maximum, clt is the actual cloud cover in the level, for the two others, the actual cloud cover is 1 - clt | ||
- | ! ftmp is total cloud cover seen from above down to the current level | ||
- | ! clt is ftmp from the level just above | ||
- | ! ftmp - clt is thus the additional cloud fraction seen from above in this level | ||
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- | IF ( iovl = maximum ) THEN | ||
- | flag_max = -1. | ||
- | ftmp(i) = MAX( clt(i), f3d(i, | ||
- | ELSEIF ( iovl = random ) THEN | ||
- | flag_max = 1. | ||
- | ftmp(i) = clt(i) * ( 1 - f3d(i,k) ) ! random overlap | ||
- | ELSEIF ( iovl = maximum-random ) THEN | ||
- | flag_max = 1. | ||
- | ftmp(i) = clt(i) * ( 1 - MAX( f3d(i,k), f3d(i,k-1) ) ) / & | ||
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- | ENDIF | ||
- | ttop(i) = ttop(i) + t3d(i,k) * ( clt(i) - ftmp(i) )*flag_max | ||
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- | ! ice clouds | ||
- | icr(i) = icr(i) + icr3d(i,k) * ( 1 - phase3d(i, | ||
- | icc(i) = icc(i) + ( 1 - phase3d(i, | ||
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- | ! liquid water clouds | ||
- | cdr(i) = cdr(i) + cdr3d(i,j) * phase3d(i, | ||
- | cdnc(i) = cdnc(i) + cdnc3d(i,j) * phase3d(i, | ||
- | lcc(i) = lcc(i) + phase3d(i, | ||
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- | clt(i) = ftmp(i) | ||
- | ENDIF ! is there a visible, not-too-small cloud? | ||
- | ENDDO ! loop over k | ||
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- | IF ( iovl = random OR iovl = maximum-random ) THEN | ||
- | clt(i) = 1. - clt(i) | ||
- | ENDIF | ||
- | ENDDO ! loop over I | ||
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- | naming convention for the input variables: | ||
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- | utctime current time of the day in UTC in seconds | ||
- | time_step_len length of model time-step | ||
- | lon(nx) longitude in degrees from 0 to 360 | ||
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- | ==== Q/A ==== | ||
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