Future temperature growth in Asia is being overestimated by between 3.4% and 11.6%, say researchers

Posted: July 21, 2022 by oldbrew in Analysis, Cycles, modelling, predictions, research, Temperature, Uncertainty
Tags: ,

Monsoon region

A familiar story of inaccurate climate models. The overestimates would undermine various predictions.
– – –
Global climate tools being used to predict future temperature rises and rainfall across Asia are significantly overestimating their potential growth and impact, according to new research.

A study published in Nature Communications suggests predictions by the World Climate Research Program’s Coupled Model Intercomparison Project Phase 6 (CMIP6) are overestimating future temperature growth by between 3.4% and 11.6%, says Phys.org.

Based on revised calculations, an international team of researchers say this could result in the rate of snow cover loss in Asia, notably in the Himalayas, being between 10.5% and 40.2% lower than previously predicted.

As well as the physical effects on the landscape, this, they add, could have significant knock-on effects on both predicted future climate warming and water availability in Asia.

Around half of the world’s population lives in Asia, with environmental scientists and engineers constantly required to estimate the effect of global warming on the hydrological cycle, particularly precipitation in the form of rainfall.

Such estimates are vitally important when it comes to developing both present and future climate change mitigation and water resources management policies.

Alistair Borthwick, Professor of Applied Hydrodynamics at the University of Plymouth and one of the study’s co-authors, said, “Understanding of the relationships between global warming and future rainfall parameters is key to estimating the scale, intensity, and future occurrences of flood and drought events worldwide.

“Using the latest techniques in data analytics, our work has determined empirical relationships called emergent constraints that should enable water experts to provide better forecasts of future precipitation in Asia.”

This study involved researchers based at universities in Amsterdam, Wuhan, Edinburgh, Nanjing, Oxford and Plymouth, and used emergent constraints to evaluate the relationship between temperature growth rates from 1970 to 2014, and rainfall growth rates from 2015 to 2100 across Asia.

Emergent constraints are obtained by discovering trends in data relating to model simulations of the present climate and projections of the future climate.

For such trends to be useful in practice, they should have plausible physical explanations that are verifiable, and evidence be provided that the trends are satisfied by out-of-sample tests.

The results from the new research demonstrate that the CMIP6 models satisfactorily capture precipitation feedback, whereby increased water vapor in wetter conditions imposes a stronger warming effect on temperature.

However, by applying the emergent constraint relationship between simulated historical temperature growth rate and future precipitation growth rate to temperature observations, the uncertainty in future precipitation projections was reduced by up to 31%.

Professor Yuanfang Chai, of Wuhan University and Vrije Universiteit Amsterdam and the study’s lead author, said, “Accurate predictions of future climate change are essential for providing reliable information to plan climate mitigation and adaptation measures. However, projections of Earth System Models are still considered undesirable. By applying the emergent constraint technique, our work successfully reduced the uncertainties of future projections of precipitation, temperature, and snow loss in Asia compared to the original CMIP6 outputs.”

Co-author Dr. Louise Slater, of the University of Oxford, said, “It is important to accurately estimate future climate changes. Our work shows that future increases in rainfall and temperature over Asia are likely to be smaller than previously thought.”

Another Co-author Dr. Yue Yao, of Wuhan University, added, “Our work reveals that previous projections of future temperature and snow loss growth rates are overestimated across Asia. Therefore, the acceleration of future water cycles is expected to be slower. This has positive implications for climate mitigation and adaption.”

Full article here.

  1. […] Future temperature growth in Asia is being overestimated by between 3.4% and 11.6%, say researc… […]

  2. oldbrew says:

    However, projections of Earth System Models are still considered undesirable.

    Is that the Chinese professor’s way of saying they’re no good?

  3. pochas94 says:

    I think Joe sixpack is becoming skeptical of anything a government wacko says.

  4. Phoenix44 says:

    “Emergent constraints are obtained by discovering trends in data relating to model simulations of the present climate and projections of the future climate.”

    How many angels can dance on the head of a pin held by an angel dancing on the head of a pin?

  5. oldbrew says:

    Article- Published: 23 February 2022
    Emergent constraints on future precipitation changes

    Future projections of global mean precipitation change (ΔP) based on Earth-system models have larger uncertainties than projections of global mean temperature changes (ΔT).
    . . .
    On the basis of these significant correlations and observed trends, the variance of ΔP is reduced by 8–30 per cent.

    – – –
    When they dig a bit they’re finding the need for fairly large corrections, with this technique.

  6. oldbrew says:

    Published: 10 May 2022
    Observationally constrained projection of Afro-Asian monsoon precipitation

    Future increase in AfroASM precipitation has been projected by current state-of-the-art climate models, but large inter-model spread exists. Here we show that the projection spread is related to present-day interhemispheric thermal contrast (ITC). Based on 30 models from the Coupled Model Intercomparison Project Phase 6, we find models with a larger ITC trend during 1981–2014 tend to project a greater precipitation increase. Since most models overestimate present-day ITC trends, emergent constraint indicates precipitation increase in constrained projection is reduced to 70% of the raw projection, with the largest reduction in West Africa (49%).


    ‘state-of-the-art climate models, but large inter-model spread exists’ – work that one out.

    ‘most models overestimate present-day ITC trends’ – the state of the art looks poor then?

    When does the penny drop that their unphysical radiative gas model *is* the problem? Or do they plan to scratch around for excuses forever?

  7. ivan says:

    All they are doing is proving that computer models support the old Garbage In equals Garbage Out – something that has been known since the first computers were developed. All their bigger, faster computers do is produce the garbage sooner, they do not make it better.

    Maybe the academic modellers need to ask the industrial modellers how they get better more correct results.

  8. Phoenix44 says:

    Oldbrew, they call it “emergent constraint” but its just the models being wrong. How can most models overestimate present day trends? And if they do how can they possibly be right in the distant future? This is getting messier and messier and calling it silly names and fudging it isn’t going to solve the problems. The models are significantly over-estimating change. The modellers have been told this for years but ignored the warnings. Climate is nowhere near as sensitive to CO2 as they model and positive feedbacks nowhere near as strong. Perhaps some are getting brave enough to say this?

  9. oldbrew says:

    Climate is nowhere near as sensitive to CO2 as they model — Phoenix44

    Indeed, because they have it backwards: CO2 is sensitive to temperature changes. Gases radiate at the temperature they find themselves at. It’s called ‘science’ 🙂


  10. stpaulchuck says:

    more junk modelling used to scare the sheeple and garner billions is grants *spit* I am so worn out with the junk science around AGW (and other crap pseudo science).

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