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--- aerocom:indirect [2013-10-01 19:37:26]
steve.ghan@pnnl.gov
+++ aerocom:indirect [2022-05-31 09:29:31]
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-===== Indirect Effect Experiment Remarks =====
-==== Indirect forcing experiment =====
-======
-== Data submission deadline ==
- *   Submission of results by 1 December 2013
-== Simulation setup ==
- *   Simulation start 1 October 2005 \\
- *   Forcing by AMIP2 sea surface temperature and sea-ice extent \\
- *   Preferred: Nudge toward ECMWF reanalysis winds (not temperature) through 2010 \\
- *   Acceptable: Nudge toward winds from one baseline simulation by your model \\
- *   Less acceptable: No nudging \\
- *   Greenhouse gas concentrations for year 2000 \\
- *   Aerosol direct, semi-direct, and indirect effects taken into account.  \\
- *   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)  \\
- *   hom_2000: present day emissions no heterogeneous nucleation of ice \\
- *   hom_1850: pre-industrial emissions no heterogeneous nucleation of ice \\
- *   fix_2000: present day emissions fixed ice nucleation for T%%<%%-37 C using Cooper (1986) as a f(temperature) \\
- *   fix_1850: pre-industrial emissions fixed ice nucleation for T%%<%%-37 C using Cooper (1986) as f(temperature) \\
-=== Diagnostics ===
- *   All data except COSP diagnostics is to be collected at the AEROCOM server. \\
- *   Groups hold COSP diagnostics until analyst is identified \\
- *   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 \\
- *   All data are 3-dimensional ( lon x lat x time )  \\
- *   filenames aerocom_<ModelName>_<ExperimentName>_<VariableName>_<VerticalCoordinateType>_<Period>_<Frequency>.nc \\
-    where <ModelName> can be chosen such that Model Name, Model version and possibly the institution can be identified. No underscores (_) are allowed in <ModelName>. Use (-) instead. Max 20 characters.
-    <ExperimentName> = all_2000, all_1850, hom_2000, hom_1850, fix_2000, or fix_1850
-    <VariableName> see list below
-    <VerticalCoordinateType> => "Surface", "Column", "ModelLevel"
-    <Period> => "2008", "2010", ...
-    <Frequency> => "timeinvariant","hourly", ,"3hourly", "daily", "monthly"
- *  CFMIP COSP diagnostics provided by COSP do not need to be run through cmor because the names are the same, \\
- *     but please separate files for each variable
-    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.
-(1) 2D diagnostics for evaluation with satellite data
-years (years 2006-2010) of 3-hourly data from the PD run
-======
-^ name 	^ long_name (CF if possible) ^	units ^	description ^
-| od550aer  |	atmosphere_optical_thickness_due_to_aerosol |	1 |	Aerosol optical depth (@ 550 nm) |
-| angstrm |  AOD_Angstrom_exponent | 1 | |
-| aerindex |aerosol_index  | 1  | 	AOD*angstrm
-| 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    |   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 |
-| 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 |
-| 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 |	atmosphere_optical_thickness_due_to_clouds |	1 	| Grid cell mean cloud optical depth |
-| codliq |	atmosphere_optical_thickness_due_to_liquid_clouds |	1 	| Grid cell mean cloud optical depth |
-| codice |	atmosphere_optical_thickness_due_to_ice_clouds |	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  |	W m-2 |	Surface 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's 'true' surface albedo) |
-| 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 |
-=====
-(2) For forcing estimates: as in (1), but monthly-mean fields for both PD and PI simulations
-(3) 3D monthly mean diagnostics
-^ name 	^ long_name (CF if possible) ^	units ^	description ^
-| t | temperature	|	K	| |
-| hus | specific_humidity |	kg/kg	||
-| 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  |	m|	grid cell mean 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	|
-| 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 |
-| 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  | sulfate_aerosol_number_for_homogeneous	|	m-3	|	grid cell mean sulfate aerosol number used for homogeneous aerosol freezing for T<-37C |
-| cirrus_ndust  | dust_aerosol_number_for_heterogeneous	|	m-3	|	grid cell mean dust aerosol number used for heterogeneous aerosol freezing for T<-37C |
-| cirrus_nbc  | BC_aerosol_number_for_heterogeneous	|	m-3	|	grid cell mean BC aerosol number used for heterogeneous aerosol freezing for T<-37C |
-| 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_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_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 \\
--hr snapshots and daily means for 3-month (which?) PD simulation only.
-^ name 	^ long_name (CF if possible) ^	units ^	description ^ comment ^ notes ^
-| t | temperature	|	K	|  each layer |
-| z | altitude          |	m       | each layer |
-| 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  |	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 |	|  |
-| radar  | 94GHz_radar_subcolumn | dBZe  | Radar reflectivity in 70 subcolumns   |
-| fracout | fracout_cloud_flag_subcolumn | 1 | subcolumn cloud flag 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). | |
-| 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  | | |
-=====
-==Sampling of cloud-top quantities==
-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)  \\
-to sample it at cloud base depends on your parameterization of the activation.
-    let i=1,2,...,nx be the index for the horizontal grid-points
-    let k=1,2,...,nz be the index for the vertial levels, with 1 being the uppermost level, and nz the surface level
-naming convention for the 3D input fields:
-    iovl is the flag to select the overlap hypothesis
-    cod3d(nx,nz) cloud optical thickness
-    f3d(nx,nz) cloud fraction
-    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)
-    cdr3d(nx,nz) cloud droplet effective radius
-    icr3d(nx,nz) ice crystal effective radius
-    cdnc3d(nx,nz) cloud droplet number concentration
-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
-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
-			IF ( iovl = maximum ) THEN
-				flag_max = -1.
-				ftmp(i) = MAX( clt(i), f3d(i,k))  ! maximum overlap
-			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) ) ) / &
-   	            ( 1 - MIN( f3d(i,k-1), 1 - thres_cld ) )  ! maximum-random overlap
-			ENDIF
-			ttop(i) = ttop(i) + t3d(i,k) * ( clt(i) - ftmp(i) )*flag_max
-			! ice clouds
-			icr(i) = icr(i) + icr3d(i,k) * ( 1 - phase3d(i,k) ) * ( clt(i) - ftmp(i) )*flag_max
-			icc(i) = icc(i) + ( 1 - phase3d(i,k) ) * ( clt(i) - ftmp(i) )*flag_max
-			! liquid water clouds
-			cdr(i) = cdr(i) + cdr3d(i,j) * phase3d(i,k) * ( clt(i) - ftmp(i) )*flag_max
-			cdnc(i) = cdnc(i) + cdnc3d(i,j) * phase3d(i,k) * ( clt(i) - ftmp(i) )*flag_max
-			lcc(i) = lcc(i) + phase3d(i,k) * ( clt(i) - ftmp(i) )*flag_max
-			clt(i) = ftmp(i)
-		ENDIF ! is there a visible, not-too-small cloud?
-	ENDDO ! loop over k
-	IF ( iovl = random OR iovl = maximum-random ) THEN
-		clt(i) = 1. - clt(i)
-	ENDIF
-ENDDO ! loop over I
-naming convention for the input variables:
-    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
- ==== 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.
- *    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.
- *    ATTENTION: clt(i) has to be initialized to 1 for random or maximum-random overlap assumptions in the "satellite simulator"
- *   CCN definition: Compute CCN using Kohler theory at 0.1 and 0.3 % supersaturation.
-=====