The recipe recipe_snowalbedo.yml computes the springtime snow-albedo feedback values in climate change versus springtime values in the seasonal cycle in transient climate change experiments following Hall and Qu (2006). The strength of the snow-albedo effect is quantified by the variation in net incoming shortwave radiation (Q) with surface air temperature (Ts) due to changes in surface albedo αs:
The diagnostic produces scatterplots of simulated springtime Δαs/ΔTs values in climate change (ordinate) vs. simulated springtime Δαs/ΔTs values in the seasonal cycle (abscissa).
Ordinate values: the change in April αs (future projection - historical) averaged over NH land masses poleward of 30°N is divided by the change in April Ts (future projection - historical) averaged over the same region. The change in αs (or Ts) is defined as the difference between 22nd-century-mean αs: (Ts) and 20th-century-mean αs. Values of αs are weighted by April incoming insolation (It) prior to averaging.
Abscissa values: the seasonal cycle Δαs/ΔTs values, based on 20th century climatological means, are calculated by dividing the difference between April and May αs: averaged over NH continents poleward of 30°N by the difference between April and May Ts averaged over the same area. Values of αs: are weighted by April incoming insolation prior to averaging.
Recipes are stored in recipes/
- recipe_snowalbedo.yml
Diagnostics are stored in diag_scripts/emergent_constraints/
- snowalbedo.ncl: springtime snow-albedo feedback values vs. seasonal cycle
Script snowalbedo.ncl
Required settings for script
- exp_presentday: name of present-day experiment (e.g. "historical")
- exp_future: name of climate change experiment (e.g. "rcp45")
Optional settings for script
- diagminmax: observational uncertainty (min and max)
- legend_outside: create extra file with legend (true, false)
- styleset: e.g. "CMIP5" (if not set, this diagnostic will create its own color table and symbols for plotting)
- suffix: string to be added to output filenames
- xmax: upper limit of x-axis (default = automatic)
- xmin: lower limit of x-axis (default = automatic)
- ymax: upper limit of y-axis (default = automatic)
- ymin: lower limit of y-axis (default = automatic)
Required settings for variables
- ref_model: name of reference data set
Optional settings for variables
none
Required settings (scripts)
none
Optional settings (scripts)
- tas (atmos, monthly mean, longitude latitude time)
- rsdt (atmos, monthly mean, longitude latitude time)
- rsuscs, rsdscs (atmos, monthly mean, longitude latitude time)
- ERA-Interim (tas - esmvaltool/cmorizers/data/formatters/datasets/era_interim.py)
- ISCCP-FH (rsuscs, rsdscs, rsdt - esmvaltool/cmorizers/data/formatters/datasets/isccp_fh.ncl)
- Flato, G., J. Marotzke, B. Abiodun, P. Braconnot, S.C. Chou, W. Collins, P. Cox, F. Driouech, S. Emori, V. Eyring, C. Forest, P. Gleckler, E. Guilyardi,
C. Jakob, V. Kattsov, C. Reason and M. Rummukainen, 2013: Evaluation of Climate Models. In: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Stocker, T.F., D. Qin, G.-K. Plattner, M. Tignor, S.K. Allen, J. Boschung, A. Nauels, Y. Xia, V. Bex and P.M. Midgley (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA.
- Hall, A., and X. Qu, 2006: Using the current seasonal cycle to constrain snow albedo feedback in future climate change, Geophys. Res. Lett., 33, L03502, doi:10.1029/2005GL025127.