Previous CMIP/CMII data

Please let us know if data are missing or links do not work.

Forcing data for Solar protons until 2019, CCMI-2022, CMIP6, CCMI, CMIP5

Solar Proton Fluxes

To study the impact of solar proton events (SPEs), solar proton flux data from 1963 to 2019 (updated June 11, 2020) and a methdology to derive HOx and NOx production rates are provided by Charles Jackman.

Data are available as yearly files including pdf with description: (IonPair_1963-2019.tar.gz).

As of 2018 both the old (IonPair_Year-YYYY.dat, daily average ionization rates on pressure coordinates from Solar Proton Events given in #/cm+3/s) and new (IonPair-gm_Year-YYYY.dat, proton IPR daily averages on pressure coordinates in #/g/s) format are included in the tar file above, covering all years from 1963 to 2019.

CCMI-2022 recommendations

SOLAR FORCING IN THE HINDCAST SIMULATIONS (REF-D1, 1950-2020)

Solar forcing recommendations are based on CMIP6 recommendations Version 3.2 (Matthes et al., 2017, Geosci. Model Dev., 10, doi:10.5194/gmd-10-2247-2017) for the historical experiments (1850-2014). The CMIP6 solar forcing reconstruction for the historical period has been extended to include the period 1/1/2015 - 31/12/2019 using identical methods and approaches that were applied to the original CMIP6 dataset.

The CCMI-2022 solar forcing data includes the following forcing components with daily resolution for the period 1/1/1950 - 31/12/2019:

Irradiance forcing

TSI:     Total solar irradiance
F10.7: F10.7 cm solar radio flux
SSI:    Spectral solar irradiance for 10-100,000 nm range

Particle forcing:

Ap:   Daily planetary Ap-index
Kp:   Daily planetary Kp-index
iprp:  Ion-pair production rate by solar protons
iprg:  Ion-pair production rate by galactic cosmic rays
iprm: Ion-pair production rate by medium-energy electrons

A detailed description of how the data were constructed as well as a “technical” documentation of the files’ structures, dimensions, variable names, etc. can be found here.

More detailed information and auxiliary software packages for data pre-prossessing are available below (CMIP6). 

Data access:

All data are provided in zipped netcdf (HDF5) files. For those models that do require only a subset of the forcings, these are to be selected from the provided files by the user.

Please note that in order to account for solar cycle effects, not only radiative effects but also photochemical effects have to be taken into account!

For consideration of Energetic Particle Precipitation (EPP) in chemistry climate models with upper lid in the mesosphere (i.e., below the EPP source region), a NOy Upper Boundary Condition (UBC) is required in order to account for the EPP indirect effect (polar winter descent of EPP-generated odd nitrogen).

The following package contains a routine for generation of a flux or density NOy-UBC from geomagnetic Ap data which is included in the solar forcing datasets. Output data is written to a netcdf file as daily resolved NOy zonal mean densities (in units of cm-3) or molecular fluxes (in units of cm-2 s-1) on model-specific pressure levels and bin center latitudes. The routine is available in IDL or MATLAB.

MATLAB and IDL EPP-NOy UBC routine (~124MB)

 

Recommendations for CMIP6 solar forcing data

Version 3.2 available (final version)

The final version of the dataset has been published in 

Matthes, K., Funke, B., Anderson, M. E., Barnard, L., Beer, J., Charbonneau, P., Clilverd, M. A., Dudok de Wit, T., Haberreiter, M., Hendry, A., Jackman, C. H., Kretschmar, M., Kruschke, T., Kunze, M., Langematz, U., Marsh, D. R., Maycock, A., Misios, S., Rodger, C. J., Scaife, A. A., Seppälä, A., Shangguan, M., Sinnhuber, M., Tourpali, K., Usoskin, I., van de Kamp, M., Verronen, P. T., and S. Versick, 2017: Solar Forcing for CMIP6 (v3.2). Geosci. Model Dev., 10, doi:10.5194/gmd-10-2247-2017.

30 Nov 2017

An overview of the CMIP6 solar forcing dataset (irradiance as well as particle-related parameters) and guidelines for their usage are given here.

Irradiance forcing

TSI:     Total solar irradiance
F10.7: F10.7 cm solar radio flux
SSI:    Spectral solar irradiance for 10-100,000 nm range

Particle forcing:

Ap:   Daily planetary Ap-index
Kp:   Daily planetary Kp-index
iprp:  Ion-pair production rate by solar protons
iprg:  Ion-pair production rate by galactic cosmic rays
iprm: Ion-pair production rate by medium-energy electrons

Please note the following differences to the solar forcing recommended for CMIP5:

  • New, lower TSI value: 1361.0 ± 0.5 W m−2  (Mamajek et al., 2015).
  • Time-varying solar forcing is provided in one file from 1850-2300 in daily as well as monthly resolution separately
  • Particle forcing (due to protons, medium-energy electrons, and galactic cosmic rays) included in daily resolution files

A detailed description of how the data were constructed as well as a “technical” documentation of the files’ structures, dimensions, variable names, etc. can be found here.

All data are provided in zipped netcdf (HDF5) files. For those models that do require only a subset of the forcings, these are to be selected from the provided files by the user.

Auxililiary software packages for data pre-prossessing are available at the bottom of this page, including:

  • a routine (currently only available in MATLAB) that pre-processes solar irradiance data by selecting only TSI and SSI (plus wavelength information) to integrate the latter over spectral bands to be defined by the user according to the needs of his/her model.
  • A routine (MATLAB and IDL) for generation of a particle-induced NOy upper boundary condition for chemistry-climate models with upper lid at 0.01-1 hPa (based on the Ap index included in the “reference”, “extreme”, and piControl forcing datasets).
  •  A routine (MATLAB) for projection of particle-induced ionization rates (i.e., iprg, iprm, iprp, all provided on geomagnetic latitudes) onto geographic coordinates as function of pressure level and time.

What to prescribe in the CMIP6 pre-industrial control simulation (part of CMIP6 DECK)?

The pre-industrial control forcing (pictrontrol) is constructed of time-averaged historical data (see below) corresponding to 1850-1873 (solar cycle 9+10) mean conditions. See metadata file for more details.

In addition, we provide for sensitivity studies a variable pe-industrial  control forcing which includes an 11-year solar cycle but without longterm trend.  Note that it is not officially part of a CMIP6 MIP proposal.

What to prescribe in transient simulations, such as the DECK AMIP Historical and CMIP6 Historical experiments?

The standard solar forcing dataset recommended for usage is the solar reference scenario dataset which consists of historical reconstructions (1850-2014) and the most likely scenario for future solar forcing (2015-2299; see metadata file for more details) which – unlike CMIP5 future solar forcing – is still variable over time:

Please note that in order to account for solar cycle effects, not only radiative effects but also photochemical effects have to be taken into account!

CMIP6 models that do not have interactive chemistry should in addition to adapting the irradiance changes also prescribe the CMIP6 recommended ozone forcing data set. The solar signal in this ozone dataset is consistent with the CMIP6 solar forcing.

What to prescribe in future simulations (DAMIP, ScenarioMIP, DCPP)?

The future solar forcing recommendation is part of the solar reference scenario (ref) as described above and the outcome of an ISSI team "Scenarios of Future Solar Activity for Climate Modelling" in 2015. The solar reference scenario provides the most likely scenario for future solar forcing (2015-2099) and is described in more detail in Matthes et al., GMD, 2017.

In CMIP5, climate projections were based on a stationary sun scenario, obtained by simply repeating solar cycle 23, which ran from 04/1996 to 06/2008 (Lean and Rind, 2009). In CMIP6, we include a more realistic forcing, and provide two different scenarios:

  1. A reference scenario (ref) with the most likely level of solar forcing, and
  2. an extreme scenario (ext) with an exceptionally low level of activity, corresponding to the lower 5th percentile of all forecasts equivalent to that of a Maunder Minimum. This extreme scenario is meant to be used for sensitivity studies, and is not officially part of a CMIP6 MIP proposal.

For the future period, the solar forcing is derived from the heliospheric potential. We forecast the latter by using 9400 years of reconstruction of solar activity from cosmogenic isotopes (Steinhilber et al., 2012). The reference scenario is the weighted average of 3 forecasts obtained by: (i) analogue forecast (superposed epoch), (ii) deterministic forecast relying on periodicities in the observed heliospheric potential, and (iii) autoregressive model. The forecast skill does not exceed 70 years. Because we provide the most likely scenario, the forcing data does not decay towards a climatological mean, but keeps on varying. We do not provide any extreme scenario with high levels of activity because the Sun just left such an episode (called grand solar maximum), and so is very unlikely to have another. In addition, none of our ensemble of forecasts provides such a scenario above a 1% level (Abreu et al., 2009).

The standard solar forcing dataset recommended for usage is the solar reference scenario (ref) dataset which consists of historical reconstructions (1850-2014) and the most likely scenario for future solar forcing (2015-2299):

Please note that in order to account for solar cycle effects, not only radiative effects but also photochemical effects have to be taken into account! CMIP6 models that do not have interactive chemistry should in addition to adapting the irradiance changes also prescribe the CMIP6 recommended ozone forcing data set. The solar signal in this ozone dataset is consistent with the CMIP6 solar forcing.

Solar forcing datasets for sensitivity studies (not officially part of a CMIP6 MIP proposal)

Some modelling groups might additionally consider a second pi-control simulations with variable 11-year solar cycle variability included but without long-term trend. This time series still has slightly different solar cycle amplitudes and also preserves the variable phase of the solar cycle, however, the solar cycle mean activity level is held constant as compared to the reference scenario (see metadata file for more details):

This dataset is only available with daily resolution and covers the time period  1 Jan 1850 - 9 Sep 2053 (end of solar cycle 27). The dataset can be extended to cover 1000 years by multiple repetition of the solar cycle sequence 12–27.

Some modelling groups might additionally consider in future simulations the solar extreme scenario (ext), which is identical to the reference scenario for the historical period before 31 Dec 2014 but evolves towards a more extreme Maunder minimum-like activity in the future (see metadata file for more details):

Auxililiary software packages for data pre-prossessing

Routine for pre-processing solar irradiance

The SSI data recommended on this website for usage in CMIP6 is provided in high spectral resolution (1nm for 10-750nm range, 5nm for 750-5,000nm, 10nm for 5,000-10,000nm, 50nm for 10,000-100,000nm) as mean irradiance over each bin.

Many (chemistry) climate models require integrated irradiances for each spectral band, while the resolution of their radiation (and/or photolysis) schemes is typically much lower.

This package provides an (hopefully) easy to use routine to convert from one to another.

Given one of the available original input files (netcdf) downloaded from the links above, this routine creates a new netcdf-file containing the integrated SSI for all spectral bands (and all timesteps found in the input file) defined by the user plus the fraction of these bands\' irradiance (SSI_frac) compared to the TSI. As a matter of completeness, TSI is also written to the newly created file, though of course only copied from the original file.

Currently, this routine is available for MATLAB only.

Routine for generation of a EPP-NOy upper boundary condition

For consideration of Energetic Particle Precipitation (EPP) in chemistry climate models with upper lid in the mesosphere (i.e., below the EPP source region), a NOy Upper Boundary Condition (UBC) is required in order to account for the EPP indirect effect (polar winter descent of EPP-generated odd nitrogen).

This package contains a routine for generation of a flux or density NOy-UBC from geomagnetic Ap data which is included in the solar forcing datasets. Output data is written to a netcdf file as daily resolved NOy zonal mean densities (in units of cm-3) or molecular fluxes (in units of cm-2 s-1) on model-specific pressure levels and bin center latitudes. The routine is available in IDL or MATLAB.

Routine for projection of EPP ionization rates onto geographic coordinates

For consideration of solar proton and mid-energy electron precipitation, as well as galactic cosmic rays in chemistry climate models, particle-induced ion pair production rates (variable iprp, iprm, and iprg) are required. These rates, however, are provided on geomagnetic latitudes and need to be projected onto geographic coordinates.

This package contains a routine for time- and pressure level dependent  projection onto geographic coordinates, based on recommended geomagnetic reference field parameters (see metadata file for more details). It is available for MATLAB only.

 

CCMI recommendations

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

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

 

Recommendations for CMIP5 solar forcing data

This section provides links solar irradiance data that should be used in CMIP5 simulations. A description of how the data were reconstructed by Judith Lean can be found here, and some guidelines for their use are also provided. For some models, use of the spectrally-resolved data, which accounts for the wavelength dependent changes in solar irradiance, is unwarranted. For these models, the total irradiance time series should be used.

What to prescribe in the pre-industrial control simulation?

Use the TSI and/or spectrally resolved values for a mean representative of 1850 conditions, i.e. cycle average from year 1844 to 1856. Note that 1850 is a year near the peak of the solar cycle.

What to prescribe in the historic simulation (1850-2008)?

The whole time series (monthly values are available only after 1882).

What to prescribe in the future?

Repeat the last cycle (cycle 23), with values from 1996 to 2008 inclusive mapping to 2009-2021, 2022-2034 etc. Please note that cycle 23 starts in 04/1996 and ends in 06/2008. There have been some concerns that cycle 23 was unusually long and repeating this special cycle would give out of phase behavior of a normal 11-year solar cycle around 2050. Cycle 23 is actually only 12.2 years long not 13 years since it goes from 1996.4 to 2008.6. In Lean and Rind (2009, GRL, doi:2009GL038932) the irradiance was projected forward by just repeating cycle 23. Since it is unknown what the sun will do, there is going to be a lot of uncertainty for future solar irradiance projections. Also the two prior cycles (21 and 22) have been shorter than average - the official times of minima are 05/1976, 08/1986.8, 05/1996.4 and now 06/2008.6 so cycle 21 was only 10.3 years and cycle 22 was 9.6 years - which are not 11 years either! Cycles 21 and 22 have been some of the highest and shortest on record and its quite possible that cycle 23 may be more representative of the future - but of course nobody knows.

Spectrally resolved irradiance for CMIP5 models:

For models that can make sensible use of the spectrally-resolved irradiance, the following data should be used:

Total solar irradiance for CMIP5 models:

For CMIP5 models with a poorly resolved stratosphere and models that are unable to make use of spectrally-resolved data, the following annual mean TSI time series provided by J. Lean should be used: TSI_WLS_ann_1610_2008.txt.

The data files are provided in ascii format and the spectrally resolved data are zipped. Each of the spetrally resolved 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, 10 nm bins from 5000 to 10000 nm, 50 nm bins from 10000 to 100000 nm) ...
Spectral irradiance (mW/m2/nm) monthly or annually for years indicated in the file name
YEAR MONTH TSI in W/m2
solar flux data ...
YEAR MONTH+1 TSI in W/m2
...

Further notes