AOD AeroNET Assess#
Overview#
This diagnostic evaluates model aerosol optical depth (AOD) against ground based observations from the AeroNET measurement network. Monthly mean AOD data is downloaded from the AeroNET website and formatted (CMORized) using the AERONET downloader and formatter within ESMValTool.
Multiannual seasonal means are calculated from the model output and compared with a multiannual seasonal mean climatology generated from AeroNET observational data. At each AeroNET station the data are screened for validity according to the following default criteria:
1. Monthly means must be generated from at least one AOD observation in that month.
2. Seasonal means for DJF, MAM, JJA and SON must be calculated from three monthly means, i.e. a monthly mean from December January and Feburary.
3. For a given year to be valid, there must be a seasonal mean for each climate season i.e. DJF, MAM, JJA and SON.
4. For a multiannual seasonal means there must be at least five seasonaal means over the time range of interest.
NOTE: The code is designed to be flexible and the default criteria can be changed according to the user’s requirements (see the user settings below).
The evaluation is visualised by plotting model output as 2D filled contours and overlaying AeroNET observations at model grid cells co-located with the AeroNET measurement stations. Statistical data (root mean square error) is generated using AeroNET observations at model grid cells co-located with the AeroNET measurement stations.
Available recipes and diagnostics#
Recipes are stored in esmvaltool/recipes/
recipe_aod_aeronet_assess.yml
Diagnostics are stored in esmvaltool/diag_scripts/aerosols/
aod_aeronet_assess.py: Plot the AOD evaluation.
aero_utils.py: Utility functions commonly used by aerosol assessment routines.
User settings in recipe#
Script aod_aeronet_assess.py
Required settings for script
wavel: The wavelength of interest for the evaluation, currently set up for 440nm
min_days_per_mon: The minimum number of days used to calculate the AOD monthly mean
min_mon_per_seas: The minimum number of seasons used to calculate each seasonal mean. This must be between 1 and 3.
min_seas_per_year: The minimum number of seasonal means in each year. This must be between 1 and 4.
min_seas_per_clim: The minimum number of seasonal means used to calculate the multiannual seasonal mean. This must be btween 1 and the number of years of available AeroNET data.
Optional settings for script
None
Required settings for variables
None
Optional settings for variables
None
Required settings for preprocessor
None
Optional settings for preprocessor
None
Color tables
brewer_Spectral_11
Variables#
od440aer (atmos, monthly mean, longitude latitude time)
Observations and reformat scripts#
Note: (1) obs4MIPs data can be used directly without any preprocessing; (2) see headers of reformat scripts for non-obs4MIPs data for download instructions.
The AeroNET data is downloaded from the AeroNET website using the downloader:
$ esmvaltool data download AERONET.The AeroNET data is formatteed (CMORized) using the formatter:
$ esmvaltool data format AERONET.
References#
Holben B.N., T.F.Eck, I.Slutsker, D.Tanre, J.P.Buis, A.Setzer, E.Vermote, J.A.Reagan, Y.Kaufman, T.Nakajima, F.Lavenu, I.Jankowiak, and A.Smirnov, 1998: AERONET - A federated instrument network and data archive for aerosol characterization, Rem. Sens. Environ., 66, 1-16.
Holben, B.N., D.Tanre, A.Smirnov, T.F.Eck, I.Slutsker, N.Abuhassan, W.W.Newcomb, J.Schafer, B.Chatenet, F.Lavenue, Y.J.Kaufman, J.Vande Castle, A.Setzer, B.Markham, D.Clark, R.Frouin, R.Halthore, A.Karnieli, N.T.O’Neill, C.Pietras, R.T.Pinker, K.Voss, and G.Zibordi, 2001: An emerging ground-based aerosol climatology: Aerosol Optical Depth from AERONET, J. Geophys. Res., 106, 12 067-12 097.
Mulcahy, J. P., Johnson, C., Jones, C. G., Povey, A. C., Scott, C. E., Sellar, A., Turnock, S. T., Woodhouse, M. T., Abraham, N. L., Andrews, M. B., Bellouin, N., Browse, J., Carslaw, K. S., Dalvi, M., Folberth, G. A., Glover, M., Grosvenor, D. P., Hardacre, C., Hill, R., Johnson, B., Jones, A., Kipling, Z., Mann, G., Mollard, J., O’Connor, F. M., Palmiéri, J., Reddington, C., Rumbold, S. T., Richardson, M., Schitgens, N. A. J., Stier, P., Stringer, M., Tang, Y., Walton, J., Woodward, S., and Yool. A.: Description and evaluation of aerosol in UKESM1 and HadGEM3-GC3.1 CMIP6 historical simulations, Geosci. Model Dev., 13, 6383–6423, 2020
Example plots#
Fig. 77 Evaluation of AOD at 440 nm from UKESM1 historical ensemble member r1i1p1f2 against the AeroNET climatology from ground-based observations for Dec-Jan-Feb. The multiannual seasonal mean is calculated for the model data for the period 1994-2014. The model output is overlaid with the observational climatology.#
Fig. 78 Evaluation of AOD at 440 nm from UKESM1 historical ensemble member r1i1p1f2 against the AeroNET climatology from ground-based observations for Mar_Apr_May. The multiannual seasonal mean is calculated for the model data for the period 1994-2014. The model output is overlaid with the observational climatology.#
Fig. 79 Evaluation of AOD at 440 nm from UKESM1 historical ensemble member r1i1p1f2 against the AeroNET climatology from ground-based observations for Jun-Jul-Aug. The multiannual seasonal mean is calculated for the model data for the period 1994-2014. The model output is overlaid with the observational climatology.#
Fig. 80 Evaluation of AOD at 440 nm from UKESM1 historical ensemble member r1i1p1f2 against the AeroNET climatology from ground-based observations for Sep-Oct-Nov. The multiannual seasonal mean is calculated for the model data for the period 1994-2014. The model output is overlaid with the observational climatology.#
Fig. 81 Evaluation of AOD at 440 nm from UKESM1 historical ensemble member r1i1p1f2 against the AeroNET climatology from ground-based observations for Dec-Jan-Feb, Mar_Apr_May, Jun-Jul-Aug and Sep-Oct-Nov. The multiannual seasonal mean is calculated for the model data for the period 1994-2014.#