Snow depth trends revealed from CMIP6 models conflict with observations

Posted: February 22, 2022 by oldbrew in atmosphere, modelling, predictions, research, Uncertainty, weather
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Erie, Pennsylvania [image credit: UK Met Office]


Another modelling problem to add to the list: ‘The models reproduced decreasing snow depth trends that contradicted the observations’. Will any of this get a mention in next week’s new IPCC report?
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Seasonal snow cover plays an important role in the interactions between ground and atmosphere, including energy and hydrological fluxes, thus influencing climatological and hydrological processes, says Phys.org.

Researchers from the Northwest Institute of Eco-Environment and Resources of the Chinese Academy of Sciences and Lanzhou University evaluated the simulated snow depth from 22 CMIP6 models across high-latitude regions of the Northern Hemisphere over the period 1955–2014 by using a high-quality in situ observational dataset.

Related results were published in the Journal of Climate.

The researchers found that the simulated snow depths showed low accuracy and were biased high, exceeding the observed baseline (1976–2005) on average across the study area.

The models reproduced decreasing snow depth trends that contradicted the observations, although they all indicated an increase in precipitation during the cold season.

The study revealed that the simulated snow depths are insensitive to precipitation but too sensitive to air temperature; these inaccurate sensitivities could explain the discrepancies between the observed and simulated snow depth trends.

Based on these findings, they recommend caution when using and interpreting simulated changes in snow depth and associated impacts.

The CMIP6 models may require more detailed and comprehensive treatments of snow physics to more accurately project snow cover.

Source here.

Comments
  1. oldbrew says:

    CMIP6 – Coupled Model Intercomparison Project Phase 6
    Program for Climate Model Diagnosis & Intercomparison

    Diagnosis of Climate Models
    This Page is Under Construction

    https://pcmdi.llnl.gov/research/diagnostics/index.html

  2. Based on these findings, they recommend caution when using and interpreting simulated changes in snow depth climate and associated impacts.

  3. Phoenix44 says:

    Which means all the forecasts of drought due to diminished snow pack are wrong.

    So it’s not as bad they claim.

    Waiting for the BBC to make that point…

  4. oldbrew says:

    If snow and cloud data are unreliable and/or lacking detail, where does that leave model ‘projections’?

  5. stpaulchuck says:

    typical

  6. oldbrew says:

    too sensitive to air temperature

    Don’t need a researcher to work that out.

  7. ivan says:

    Have any of these climate computer models been through a validation process? If not why are they being used to try and prove anything?

    Non of the models track a real world situation for the simple reason non of the climate ‘scientists’ leave their ivory towers and go out into the real world, I doubt than any of them actually look out of the window, if there is one in the computer centre. Since they live out of contact with reality we shouldn’t expect them to use reality in any of their pronouncements or expect them to mean anything.