INSTITUTE OF ATMOSPHERIC PHYSICS, CHINESE ACADEMY OF SCIENCES
CREDIT: HAI ZHI
Salinity changes the ocean stratification by affecting the density, which has a certain impact on the thermodynamic processes of the ocean, and then modulates sea surface salinity variations. With the development of numerical models in recent years, climate models have become an important tool for studying the mechanism of climate change and predicting climate change. It is feasible and necessary to study the underlay mechanisms of variation in El Niño–Southern Oscillation (ENSO) by examining the temporal and spatial characteristics of sea surface salinity in the tropical Pacific. The Coupled Model Intercomparison Projects (CMIPs) were initiated by the Working Group on Coupled Modeling (WGCM) of the World Climate Research Program (WCRP) in 1995. With the rapid development and growth of global ocean–atmosphere models, the CMIPs provide the basis for multimodel assessments that reveal differences between models and observations.
With Prof. Hai Zhi from Nanjing University of Information Science and Technology, as the first author, and Prof. Pengfei Lin from the Institute of Atmospheric Physics, Chinese Academy of Sciences, as the corresponding author, led a study in which CMIP data were used to compare model outputs and observations to effectively evaluate model simulations, and to obtain strengths and weaknesses of individual models and the differences between the models. These results have been recently published in Atmospheric and Oceanic Science Letters.
By comparing CMIP5 and CMIP6 simulations of the sea surface salinity and freshwater flux response to ENSO in the tropical Pacific, it is shown that both CMIP5 and CMIP6 can better simulate the spatial distribution of sea surface salinity and freshwater flux variability associated with ENSO. Compared with the CMIP5 models, the interannual variabilities in sea surface salinity and freshwater flux simulated by the CMIP6 models show greater improvement in some regions, correcting the underestimation of the spatial relationship between the variability of sea surface salinity and freshwater flux in the central-western Pacific and ENSO. However, some CMIP6 models overestimate the strength of the interannual variability of sea surface salinity. The CMIP5 and CMIP6 models still have large uncertainties in simulating the interannual variation of sea surface salinity, and the related physical processes need to be improved.
“The results of our study, as part of the evaluation of CMIP, can be used as an assessment of the simulation results of CMIP5- and CMIP6-related models for the interannual vaariabilities in salinity and freshwater flux in the tropical Pacific, and can provide an important reference for the study of the impact of ENSO on global climate”, says Prof. Zhi.
JOURNAL
Atmospheric and Oceanic Science Letters
DOI
ARTICLE TITLE
Interannual variability of the sea surface salinity and its related freshwater flux in the tropical Pacific: A comparison of CMIP5 and CMIP6
ARTICLE PUBLICATION DATE
15-Feb-2022
Climate models are simply claptrap. They actually embody the idea that heat can be absorbed through an ocean surface and materialise at 2000m depth inside centuries – just tripe.
Globally, ocean surface temperature is the inverse of the net surface radiated heat uptake.
Ocean surfaces are warmest when their net radiated heat uptake is at its minimum in July. They are transferring less heat to the land masses so more surface regulates to the 30C limit.
More ocean heat directly relates to reduced net evaporation and reduced freshwater runoff from land – a trend no climate has right.
No CMIP6 model replicates the Nino34 region. Attached is ACCESS-ESM1 correlation with Nino34.
Suggesting that CMIP6 models are better than than CMIP5 models simply indicates the very low bar that climate models achieve. Comparing climate models is akin to comparing cow pats. The latter may provide some insight into the health of a herd. The former is flight of fancy.
If you actually know what you’re trying to say, you certainly don’t express yourself very well.
I think his first sentence covers what he’s trying to say.
And I agree.
I think it is the fact that what I so eloquently stated is counter intuitive. Globally, the more sunlight oceans absorb at the surface, the cooler the surface gets. The reason is that it is impossible to warm an ocean through the surface by surface heating. More heat accelerates evaporation and the deep oceans are literally an endless source of chilled water while sea ice is being formed in the high latitudes and flowing to lower latitudes through the pole-equatorial channels in both hemispheres.
More sunlight increases evaporation and that causes surface cooling as deep chilled water upwells.
More heat retention in the oceans is a sign of reducing net evaporation. It is not the result of sunlight somehow getting to 2000m as the models embody – the magic of so-called diapycnal diffusion that no one has adequately quantified.
Can you make the case that the net change is cooling? After all, when a pot of water is on the stove, increasing the heat increases the evaporation, which carries heat away. Yet, the pot eventually boils.
Much upwelling is a result of winds blowing the surface water away from the shore.
Many months with a p>0.5, does that mean the model does worse than a 50:50 guess?
“The CMIP5 and CMIP6 models still have large uncertainties in simulating the interannual variation of sea surface salinity, and the related physical processes need to be improved.” And so therefore not fit for purpose.
“Climate models are simply claptrap.”
Well stated. And the question is, are climate models coming out of a Chinese study going to state anything other than the affirmative that we need more renewables to fight climate change?
Marketing, brought to you by ‘the science’. So it must be true. /s
Actually … surprisingly, the pH of cow-pats is an important tool … in the feedlot to prevent acidosis—caused by feeding too high fines too soon for the pen.
If cow poo can provide useful information, what is a more apt phrase of derision for the uselessness of climate models?
Pension contributions?
Quote:Salinity changes the ocean stratification by affecting the density, which has a certain impact on the thermodynamic processes of the ocean, and then modulates sea surface salinity variations.
what?
¿Salinity changes the salinity?
And the whole rest of what we see/read here is similar garbage.
Either:
Or the Chinese and the Russians want us to believe the models, so we commit economic suicide, so they can march into the free world and take over.
I’m finding it increasingly difficult to differentiate between climate alarmism and treason.
“Treason against the United States, shall consist only in levying War against them, or in adhering to their Enemies, giving them Aid and Comfort.“
Article III, Section 3, Clause 1, U.S. Constitution.
“‘somebody’ s taking a piss”
Well THAT will screw with ocean salinity, at levels close to what the change of CO2 will do to the Earths temperature.
Either they have improved the ability to predict climate change or they have not. “Improving” a piece of the whole is beside the point, did they make the whole better or not? Since they insist on already knowing the answer first (CO2 is the control knob) and then working backwards into making the data fit (all the data adjustments) I am convinced they will never have an accurate working model.
I’m glad to see that the Chinese know how to waste their money on climate change crap too.
I had thought they just used fossil fuels to manufacture poor quality goods and “renewable energy” products for export.
You can roll a turd in glitter in an attempt to make it more acceptable, but it will always remain a turd.
Does this mean that all the prevous fearmongering was based on a faulty model?
“a faulty mode”
Well actually multiple faulty models that are so faulty that they need to be averaged together to hide the fact that they are all individually faulty, except, apparently the Russian model that is way closer to reality than any of the other models and thus is Russian disinformation.
When a gifted automotive engineer fine tunes an engine then s/he has oodles of experience and intimate knowledge of what needs to be done and why.
When climate scientists and their programmers design a climate model then the first thing to satisfy is that the design is fit for purpose. How do you test that for a climate model? And that is just stage one.
It is clear to me as a computer professional that there are deep flaws in that conceptual design phase of a working and accurate climate model or even in the very idea that an accurate climate model is even possible without having machines that can handle randomness to perfection. Computers are logical and much of life just isn’t.
The first part of coding anything in science is that you must understand and be able to write down all the relevant physics equations first.
That clearly is not the case. If it were we would only need one model.
“ climate models have become an important tool for…”
…getting the desired answer and keeping the narrative on track
“ climate models have become an important tool for…”
…keeping the grant money coming in.
At least for the Gulf of Mexico the science is not settled, unless something amazingly brilliant has happened in the last generation. “A surprising feature of these results is that, even with a significantly improved dataset, the exact time of separation of a ring remains elusive……It is well known that determining the true uncertainty of geophysical spectra is fraught with problems. We often deal more with hope than with confidence.” These are rings from the Loop Current coming in the Yucatan Strait, variably up near Mississippi Delta and out the Florida one which can end almost anywhere in the Gulf. Despite the river whose salinity can be detected during heavy floods in the current the GOM is an evaporative basin.
From Sturges, W. and R. Leben. 2000. Frequency of ring separations from the Loop Current in the Gulf of Mexico: A revised estimate. Journal of Physical Oceanography. 30:1814-1819. https://doi.org/10.1175/1520-0485(2000)030<1814:FORSFT>2.0.CO;2