SOLAR FORCING IN THE HINDCAST SIMULATIONS (REF-C1, REF-C3, 1960-2010)

Daily spectrally resolved solar irradiance data from the NRLSSI model (Lean et al., 2005) which have been used in previous CCMVal and CMIP5 experiments are recommended. In addition the inclusion of atmospheric ionization by solar protons (and related HOx and NOx productions) are strongly encouraged by using the GOES-based ionization rate data set and a methodology to derive HOx and NOx production rates from Jackman et al. (2009). Models capable to consider indirect particle effects by inclusion of an Ap-parameterized auroral source or upper boundary condition are encouraged to do so. The description and links to the forcing data sets are provided below.

Forcing Sources (SSI, particles)

NRLSSI (Lean et al., 2005, for CCMI: REF-C1, REF-C3)

Variations in the total solar irradiance (TSI), the so-called "solar constant", over a solar cycle are small (0.08%) (e.g., Fröhlich, 2000). However, variations in the ultraviolet (UV) part of the solar spectrum, which is important for ozone production and middle atmosphere heating, range from 8% at 200nm to about 5% from 220nm to 260nm, 0.5% around 300nm, and 0.1% above 400nm (e.g., Lean et al., 1997; Woods and Rottman, 2002). Much larger variations are observed at shorter wavelengths (over 50% at 120nm, 10-15% from 140-200nm), which are mainly absorbed in the higher atmosphere (mesosphere and thermosphere).

To account for the highly variable and wavelength-dependent changes in solar irradiance, daily spectrally resolved solar irradiance data from 1 Jan 1950 to 31 Dec 2010 (in mW/m2/nm) are provided by Judith Lean. The data were derived with the method described in Lean et al. (1997), Lean (2001), and Lean et al. (2005). A short description of how the data were (re)constructed can be found here (this description is still valid for the extended timeseries through 2011!).

Each modelling group is required to integrate these data over the individual wavelength intervals in their

  • radiation scheme (to adjust the shortwave heating rates) and
  • chemistry scheme (to adjust the photolysis rates).

It is recommended to use the provided solar flux data directly (integrated over the respective intervals in the radiation and chemistry schemes), rather than a parameterization with the F10.7cm radio flux. The absolute scale of the solar spectral irradiance reconstruction is such that the integral matches the PMOD composite – to transfer the time series to the TIM scale, multiply each spectral band by 0.9965 (note that this factor is much smaller than the absolute uncertainties in the solar spectral irradiance measurements). Similarly when using the TSI values, they have to be multiplied by 0.9965 too.

The data files are in ascii format and zipped. To unzip use "gunzip file.gz".

Each of the ascii files is organized as follows:

header ... wavelength grid centers ... wavelength bands width (1 nm bins from 0 to 750 nm, 5 nm bins from 750 to 5000 nm, 10nm bins from 5000 to 10000 nm, 50 nm bins from 10000 to 100000 nm) ... Spectral irradiance (mW/m2/nm) daily for years indicated in the file name YEAR MONTH DAY TSI in W/m2 solar flux data ... YEAR MONTH DAY+1 TSI in W/m2

The following data set is recommended for use in the CCMI reference runs as well as any other solar cycle studies. Please note that the solar irradiance is the energy incident at 1 AU - so the variations in distance of the earth's orbit around the sun have been removed - this is true for all irradiance data. You have to account for the distance in your model. For Lyman-alpha irradiance it is recommended to use the respective values at 121.5nm.

Data:

  1. Time period: 1950-1999 for UV/VIS/IR (wavelength range: 120.5nm-99975.0nm)
  2. Time period: 2000-2011 for UV/VIS/IR (wavelength range: 120.5nm-99975.0nm)
  3. Time period: 1950-2006 for EUV (wavelength range: 0.5nm-119.5nm)
  4. Time period: 1950-2012 for EUV (wavelength range: 0.5nm-119.5nm)

Particles (ionization data set)

Energetic particle precipitation (EPP) is known to cause significant interannual variability in the polar atmosphere either by stratospheric NOx and HOx productions caused by very high-energetic protons from solar eruptions (direct effects) or by polar winter descent of NOx produced by particle-induced ionization in the mesosphere and lower thermosphere (indirect effects). We recommend the inclusion of atmospheric ionization by solar protons (and related HOx and NOx productions) in models with interactive stratospheric chemistry by using the GOES-based daily proton ionization data set of Jackman et al., 2009. A methodology to derive HOx and NOx production rates from this data set as well as a description about the structure of the data can be found here. Note that proton ionization data covers the time period 1963-2013. Missing data for the first years of REF-C1/C3 simulations (1960-2010) should be set to zero.

Data:

  1. ionization data set (1963-2013, tar.gz file)

Solar protons are responsible for only a fraction of particle-induced variability in the stratosphere, which is dominated by indirect effects. Models capable to consider indirect effects by inclusion of an Ap-parameterized auroral source or upper boundary condition are encouraged to do so.

Data: (netcdf, can be read with an IDL reader)

  1. daily and 3-hourly Ap data

Ap data corresponding to the 1932-2011 period has been taken from ftp://ftp.ngdc.noaa.gov/STP/GEOMAGNETIC_DATA/INDICES/KP_AP. Ap data before 1932 (used in SEN_C2_Solartrend) has been constructed on basis of scaled aa data (http://isgi.latmos.ipsl.fr/source/indices/aa/) with Ap=aa*0.795-3.76 (determined by linear regression to Ap in the period 1932-2012).

Important progress has been made in recent years in constraining the EPP-NOx amount descended into the stratosphere and its dependence on geomagnetic activity by satellite-borne NOx observations. Derived EPP-NOx flux parameterizations allow for consideration of EPP indirect effects in models with an upper lid located in the upper stratosphere/mesosphere. A dedicated SOLARIS-HEPPA study is planned for careful evaluation of such parameterizations and their implementations. It is envisaged to provide consolidated recommendations for the use of EPP-NOx flux parameterizations for CCMI phase 2.

Example: How to extract forcings for simulation day 2.2.2002 (doy=33)

  • i) extract SSI data for YEAR=2002 MONTH=2 DAY=2 from the Lean data set.
  • ii) extract proton forcing data for YEAR=2002 DOY=33.
  • iii) extract AP with IDL reader: Ap=get_Ap('ref',year=2002,month=2,day=2,path='your_nc_path/') for daily Ap or get_Ap('ref',year=2002,month=2,day=2,path='your_nc_path/',/hourly) for a 6 element array containing 3-hourly Ap values. Note that the argument 'ref' has to be specified in all REF simulations! The reader supports different input time formats (year, month,day, doy, Julian), see source code. If required, change the directory 'your_nc_path/' where the file Ap_REF.nc is located.

Please note: Research groups that do not have their own coupled ocean-atmosphere model and therefore use SSTs/SICs from an RCP 6.0 CMIP5 simulation have to make sure that they use the same solar forcing which has been used for the CMIP5 simulations so that the SSTs/SICs and the atmosphere use the same solar forcing!

FUTURE PROJECTIONS: Reference simulation 2 (REF-C2, 2010 to 2100)

For the future solar forcing data, we recommend similar to CCMVal-2 to repeat a sequence of the last four solar cycles (20-23) as shown in the following table. Since data from 1960-2010 have been used for the REF-C1 simulations (see data sets provided above) we use observed values until December 16th 2011 and start the repetition to reconstruct future solar cycles afterwards. The corresponding dates to be used for each simulation day are provided.

Data (netcdf, can be read with this IDL reader):

  1. dates_REF_C2.nc

REF-C2 Solar Cycle

Figure 1: Extended Sunspot Number and Ap index for the REF-C2 simulation.

Note that the repetition of the last four solar cycles is not compliant with the recommendation for CMIP5, where a repetition of solar cycle 23 was recommended but has been used by only a small number of modeling groups. Proton forcing (ionization data of the 1967-2007 period (SC 20-23)) and Ap data as described for REF-C1 should be repeated over the last solar cycles in consonance with the SSI data.

Example: How to extract forcings for simulation day 2.2.2050 (doy=33)

  • i) get reference date for SSI and proton forcing with IDL reader: ref_date=get_refdate('ref',year=2050,month=2,day=2,path='your_nc_path/') for a 3 element array [ref_year, ref_month, ref_date] or ref_doy=get_refdate('ref',year=2050,month=2,day=2,/refdoy,path='your_nc_path/') for a 2 element array [ref_year, ref_doy]. You will obtain ref_date=[1985, 2, 13] and ref_doy=[1985, 43]. Note that the argument 'ref' has to be specified in all REF simulations! The reader supports different time formats (date, doy, Julian), see source code. Change the argument 'your_nc_path' to the directory name where the file dates_REF_C2.nc is located.
  • ii) extract SSI data for YEAR=1985 MONTH=2 DAY=13 from the Lean data set.
  • iii) extract proton forcing data for YEAR=1985 DOY=43.
  • iv) extract AP with IDL reader: Ap=get_Ap('ref',year=2050,month=2,day=2,path='your_nc_path/'). Use keyword /hourly for 3-hourly values (see example a3). Note that the argument 'ref' has to be specified in all REF simulations! The reader supports different input time formats (year, month,day, doy, Julian), see source code. If required, change the directory 'your_nc_path/' where the file Ap_REF.nc is located.

Scenario simulation 1 (SEN-C1-SSI, 1960-2010, REF-C1 with a different SSI forcing data set)

SEN-C1-SSI with the SATIRE data set (Krivova et al., 2006) is designed to address the sensitivity of the atmospheric response to a higher UV forcing than in the standard NRLSSI data set (Lean et al., 2005) used so far for all model experiments within CCMVal and CMIP5. The larger UV forcing has consequences not only for atmospheric heating but also for ozone chemistry. It is therefore important to understand the atmospheric impacts of those different SSI data sets in a consistent and coordinated way in a number of CCMs as recently highlighted by Ermolli et al. (2012).

SSI data: SATIRE (Krivova et al., 2006; for CCMI: SEN-C1-SSI). A description of the SATIRE data can be found in this document

Data:

  1. SATIRE_S_T_SSI_v20130304.ncdf
  2. SATIRE_S_T_TSI_v20130304.ncdf

Particle (for CCMI: SEN-C1-SSI)

Please use the same particle forcing as described for the REF-C1 simulations above! To extract forcings e.g. for simulation day 2.2.2002 (doy=33), follow the same steps as above but using the Satire SSI data set in step ii).

Scenario simulation 2 (SEN-C2-SolarTrend, 1960-2100, REF-C2 but with a trend in future solar cycle)

SEN-C2-SolarTrend (1960-2100, REF-C2 but with a trend in future solar cycle) aims at looking at the effects of a possible new grand minimum in solar activity. Predictions of the solar cycle are extremely difficult and uncertain but it is known that the sun will get out of its grand maximum which peaked in the mid-20th century. There is a lot of research currently going on whether or not the sun will run into a new Maunder Minimum like period and whether and how this could may be counteract the recent global warming. To avoid speculations and put research on a firm ground a simulation with a future trend in the solar cycle amplitudes will be prescribed and the atmospheric response will be investigated. This future trend will be based on past cycles which will be repeated in reversed order (cycles 20, 18, 17, 16, 15, 14, 13, 12). The corresponding dates to be used for each simulation day are provided.

Data (netcdf, can be read with this IDL reader):

  1. dates_SEN_solar_trend.nc

SSI data: NRLSSI (Lean et al., 2005; for CCMI: SEN-C2-SolarTrend)

The historical daily SSI data are provided in 4 different files:

  1. spectra_1882_1900d_cb_22Jan13.txt.zip
  2. spectra_1900_1925d_cb_22Jan13.txt.zip
  3. spectra_1925_1950d_cb_22Jan13.txt.zip
  4. spectra_1975_2000d_cb_22Jan13.txt.zip

Particle (for CCMI: SEN-C2-SolarTrend)

Please use the same particle forcing as described for the REF-C2 simulations above

Example: How to extract forcings for simulation day 2.2.2050 (doy=33)

  • i) get reference date for SSI forcing with IDL reader: ref_date=get_refdate('solartrend',year=2050,month=2,day=2,path='your_nc_path/') for a 3 element array [ref_year, ref_month, ref_date]. You will obtain ref_date=[1932, 3, 4]. Note that the argument 'solartrend' has to be specified here! The reader supports different time formats (date, doy, Julian), see source code. Change the argument 'your_nc_path' to the directory name where the file dates_SEN_solar_trend.nc is located.
  • ii) extract SSI data for YEAR=1932 MONTH=3 DAY=4 from the Lean data set.
  • iii) get reference date for proton forcing with IDL reader: ref_doy=get_refdate('ref',year=2050,month=2,day=2,/refdoy,path='your_nc_path/') for a 2 element array [ref_year, ref_doy]. You will obtain ref_doy=[1985,43]. Note that the argument 'ref' has to be specified here! The reader supports different time formats (date, doy, Julian), see source code. Change the argument 'your_nc_path' to the directory name where the file dates_REF_C2.nc is located.
  • iv) extract proton forcing data for YEAR=1985 DOY=43.
  • v) extract AP with IDL reader: Ap=get_Ap('solartrend',year=2050,month=2,day=2,path='../your_nc_path/'). Use keyword /hourly for 3-hourly values (see example above). Note that the argument 'solartrend' has to be specified here! The reader supports different input time formats (year, month,day, doy, Julian), see source code. If required, change the directory 'your_nc_path/' where the file Ap_SEN_solar_trend.nc is located.

SEN-C2 Solar Trend

Figure 2: Extended Sunspot Number and Ap index for the SEN-C2 Solar Trend simulation.