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aerocom:indirect [2013-10-01 22:58:48] steve.ghan@pnnl.gov |
aerocom:indirect [2022-05-31 09:29:31] |
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- | ===== Indirect Effect Experiment Remarks ===== | ||
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- | ==== Indirect forcing experiment ===== | ||
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- | ====== | ||
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- | == Data submission deadline == | ||
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- | == Simulation setup == | ||
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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 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_ice_content | 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 | | ||
- | | 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 | grid-cell mean 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 | | ||
- | | colccn.1 | column_cloud_condensation_nuclei_0.1 | m-2 | grid-cell mean 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% | ||
- | | 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 (in order to estimate the model' | ||
- | | ttop | air_temperature_at_cloud_top | K | Temperature at top of clouds | | ||
- | | 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 | grid cell mean each layer (S=0.1%) | | ||
- | | ccn0.3 | cloud_condensation_nuclei_0.3 | m-3 | grid cell mean 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 | wsubc | 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 | | ||
- | | cirrus_nso4 | ||
- | | cirrus_ndust | ||
- | | cirrus_nbc | ||
- | | cirrus_nihom | ||
- | | cirrus_nihet | ||
- | | 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 | ||
- | | mp_hetnuc | ||
- | | mp_homnuc | ||
- | ===== | ||
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- | (4) Optional CFMIP COSP diagnostics. Highly desirable but optional for now \\ | ||
- | 3-hr snapshots and daily means for January-March 2008 PD simulation only. | ||
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- | ^ name ^ long_name (CF if possible) ^ units ^ description ^ comment ^ notes ^ | ||
- | | t | temperature | K | | ||
- | | z | altitude | ||
- | | pressure | atmospheric_pressure | ||
- | | airmass | atmosphere_mass_content_of_air | ||
- | | ccn0.1 | cloud_condensation_nuclei_0.1 | m-3 | grid cell mean each layer (S=0.1%) | | ||
- | | ccn0.3 | cloud_condensation_nuclei_0.3 | m-3 | grid cell mean 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 | | ||
- | | ewl | droplet_effective_radius | ||
- | | 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 | ||
- | | 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 | ||
- | | 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 | | ||
- | | 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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- | ==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 apporach (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, | ||
- | 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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