{"id":267791,"date":"2023-07-16T20:34:02","date_gmt":"2023-07-16T18:34:02","guid":{"rendered":"https:\/\/climatescience.press\/?p=267791"},"modified":"2023-07-16T20:34:05","modified_gmt":"2023-07-16T18:34:05","slug":"new-2023-inmcm-ras-climate-model-first-results","status":"publish","type":"post","link":"https:\/\/climatescience.press\/?p=267791","title":{"rendered":"New 2023 INMCM RAS Climate Model First\u00a0Results"},"content":{"rendered":"\n
\"\"<\/figure>\n\n\n\n

<\/p>\n\n\n\n

From Science Matters<\/a><\/p>\n\n\n\n

By\u00a0Ron Clutz<\/a><\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

Previous posts (linked at end) discuss how the\u00a0climate model from RAS<\/strong>\u00a0(Russian Academy of Science) has evolved through several versions. The interest arose because of its greater\u00a0ability to replicate the past temperature history.<\/strong>\u00a0The model is part of the CMIP program which will soon go the next step to CMIP7, and is one of the first to test with a new climate simulation.<\/p>\n\n\n\n

This synopsis is made possible thanks to the\u00a0lead author, Evgeny M. Volodin, providing me with a copy<\/strong>\u00a0of the\u00a0article published May 11, 2023 in Izvestiya, Atmospheric and Oceanic Physics.<\/strong>\u00a0Those with institutional research credentials can access the paper at\u00a0Simulation of Present-Day Climate with the INMCM60 Model<\/strong><\/a>\u00a0by E. M. Volodin, et al. (2023). Excerpts are in italics with my bolds and added images and comment.<\/p>\n\n\n\n

<\/p>\n\n\n\n

Abstract<\/strong><\/em><\/h5>\n\n\n\n

A simulation of the present-day climate with a\u00a0new version of<\/strong>\u00a0the climate model developed at the Institute of Numerical Mathematics of the Russian Academy of Sciences\u00a0(INM RAS)<\/strong>\u00a0is considered. This model differs from the previous version by a\u00a0change in the cloud and condensation scheme<\/strong>, which leads to a\u00a0higher sensitivity to the increase in \u0421\u041e2.<\/strong>\u00a0The\u00a0changes<\/strong>\u00a0are\u00a0also<\/strong>\u00a0included in the calculation of aerosol evolution, the aerosol indirect effect, land snow, atmospheric boundary-layer parameterization, and some other schemes.<\/em><\/p>\n\n\n\n

The model is capable of reproducing near-surface air temperature, precipitation, sea-level pressure,\u00a0cloud radiative forcing, and other parameters better than the previous version.<\/strong>\u00a0The largest improvement can be seen in the simulation of temperature in the tropical troposphere and at the polar tropopause and surface temperature of the Southern Ocean. The simulation of climate changes in 1850 2021 by the two model versions is discussed.<\/em><\/p>\n\n\n\n

<\/p>\n\n\n\n

Introduction<\/strong><\/em><\/h5>\n\n\n\n

A new version has been developed on the basis of the climate system model described in [1]. It was shown [2] that introducing\u00a0changes only to the cloud parameterization would produce climate models with different equilibrium sensitivities to a doubling of \u0421\u041e2<\/strong>, in a range of 1.8 to 4.1 K. The INMCM48 version has the lowest sensitivity of 1.8 K among Coupled Model Intercomparison Project Phase 6 (CMIP6) models. The natural question then arises as to\u00a0how<\/strong>\u00a0parameterization changes that increase the equilibrium sensitivity\u00a0affect the simulation of modern climate and of its changes observed in recent decades.<\/strong><\/em><\/p>\n\n\n\n

The INMCM48 version simulates modern climate quite well, but it has some systematic biases common to many of the current climate models, and biases specific only to this model<\/strong>. For example,\u00a0most climate models overestimate surface temperatures<\/strong>\u00a0and near surface air temperatures\u00a0at southern midlatitudes and off the east coast of the tropical Pacific and Atlantic oceans<\/strong>\u00a0and\u00a0underestimate surface air temperatures in the Arctic<\/strong>\u00a0(see, e.g., [3]). A\u00a0typical error<\/strong>\u00a0of many current models, as well as of INMCM48, is the\u00a0cold polar tropopause and the warm tropical tropopause<\/strong>, resulting in an\u00a0overestimation of the westerlies<\/strong>\u00a0in the midlatitude stratosphere.\u00a0Possible<\/strong>\u00a0sources of such systematic biases are the\u00a0errors in the simulation of cloud amount and optical properties.<\/strong><\/em><\/p>\n\n\n\n

In the next version,\u00a0therefore, changes were first made in cloud parameterization<\/strong>. Furthermore, the\u00a0INMCM48 exhibited systematic biases<\/strong>\u00a0specific solely to it. These are, for example, the\u00a0overestimation of sea-level pressure<\/strong>, as well as of geopotential at any level in the troposphere,\u00a0over the North Pacific.<\/strong>\u00a0The likely reason for such biases seems to be related to\u00a0errors in the heat sources located southward, over the tropical Pacific<\/strong>.<\/em><\/p>\n\n\n\n

In this study, it is shown how changes in physical parameterizations,
including clouds, affect systematic biases in the simulation of
modern climate and its changes observed in recent decades.<\/mark><\/strong><\/em><\/p>\n\n\n\n

<\/p>\n\n\n\n

Model and Numerical Experiments<\/strong><\/em><\/h5>\n\n\n\n

The INMCM60 model, like the previous INMCM48 [1], consists of three major components: atmospheric dynamics, aerosol evolution, and ocean dynamics.<\/strong> The atmospheric component incorporates a land model including surface, vegetation, and soil.<\/strong> The oceanic<\/strong> component also<\/strong> encompasses a sea-ice evolution model<\/strong>. Both versions in the atmosphere<\/strong> have a spatial 2\u00b0 \u00d7 1\u00b0 longitude-by-latitude resolution and 21 vertical levels up to 10 hPa<\/strong>. In the ocean, the resolution is 1\u00b0 \u00d7 0.5\u00b0 and 40 levels.<\/strong><\/em><\/p>\n\n\n\n

The following changes have been introduced into the model
compared to INMCM48.<\/mark><\/strong><\/em><\/p>\n\n\n\n

Parameterization of clouds and large-scale condensation<\/strong>\u00a0is identical to that described in [4], except that\u00a0tuning parameters<\/strong>\u00a0of this parameterization\u00a0differ<\/strong>\u00a0from any of the versions outlined in [3], being, however, closest to version 4. The main difference from it is that the\u00a0cloud water flux<\/strong>\u00a0rating boundary-layer clouds is estimated not only for reasons of boundary-layer turbulence development, but\u00a0also from the condition of moist instability<\/strong>, which, under deep convection, results in fewer clouds in the boundary layer and more in the upper troposphere.\u00a0The equilibrium sensitivity of such a version to a doubling of atmospheric \u0421\u041e2 is about 3.3 K.<\/strong><\/em><\/p>\n\n\n\n

The\u00a0aerosol scheme<\/strong>\u00a0has also been updated by including a\u00a0change in the calculation of natural emissions of sulfate aerosol [5] and wet scavenging<\/strong>, as well as the\u00a0influence of aerosol concentration on the cloud droplet radius<\/strong>, i.e., the first indirect effect [6]. Numerical values of the constants, however, were taken to be a little different from those used in [5]. Additionally, the\u00a0improved scheme of snow evolution<\/strong>\u00a0taking into account refreezing and the calculation of the snow albedo [7] were introduced to the model. The calculation of universal functions in the atmospheric boundary layer in stable stratification has also been changed: in the latest model version, such functions assume turbulence at even large gradient Richardson numbers [8].<\/em><\/p>\n\n\n\n

A numerical model experiment to simulate a preindustrial climate was run for
180 years,\u00a0not including\u00a0the 200 years when equilibrium was reached.<\/mark><\/strong><\/em><\/p>\n\n\n\n

All climate forcings in this experiment were held at their 1850 level. Along with a preindustrial experiment, a numerical experiment was run to simulate climate change in 1850\u20132029, for which forcings for 1850\u20132014 were prescribed consistent with observational estimates [9], while forcings for 2015\u20132029 were set according to the Shared Socioeconomic Pathway (SSP3-7.0) scenario [10].<\/p>\n\n\n\n

To verify the simulation of present-day climate, the\u00a0data<\/strong>\u00a0from the experiment with a realistic forcing change\u00a0for 1985\u20132014 were used and compared against<\/strong>\u00a0the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis fifth generation (ERA5) data [11], the Global Precipitation Climatology Project, version 2.3 (GPCP 2.3) precipitation data [12], and the Clouds and the Earth\u2019s Radiant Energy System (CERES) Energy Balanced and Fitted Edition 4.1 (CERES-EBAF 4.1) top-of-atmosphere (TOA) outgoing radiation fluxes [13].<\/em><\/p>\n\n\n\n

The root-mean-square deviation<\/strong>\u00a0of the annual and monthly averages of modeled and observed fields was used as a\u00a0measure for the deviation of model data from observations<\/strong>, for which the observed fields were interpolated into a model grid. For calculating the sea-level pressure and 850-hPa temperature errors, grid points with a height over 1500 m were excluded. The modeled surface air temperatures were compared with the Met Office Hadley Center\/Climatic Research Unit version 5\u00a0\u00a0(HadCRUT5) dataset [14].<\/em><\/p>\n\n\n\n

<\/p>\n\n\n\n

Results<\/strong><\/em><\/h5>\n\n\n\n

Below are some results of the present-day climate simulation. Because\u00a0changes<\/strong>\u00a0in the model\u00a0were<\/strong>\u00a0introduced\u00a0mainly into the scheme of atmospheric dynamics and land surface<\/strong>\u00a0and there were no essential changes in the oceanic component, we shall restrict our discussion to atmospheric dynamics.<\/em><\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

Table 1 demonstrates that the norms of errors in most fields were reduced.<\/strong>\u00a0Changing the calculation of cloud cover and properties has\u00a0improved the cloud radiative forcing,<\/strong>\u00a0and the norm of errors for\u00a0both longwave and shortwave forcing decreased by 10\u201320% in the new version compared to its predecessor. The global average of short-wave cloud radiative forcing is \u201347.7 W\/m2 in the new version, \u201340.5 W\/m2 in the previous version, and about \u201347 W\/m2 in CERES-EBAF. The average TOA longwave radiative forcing is 29.5 W\/m2 in the new version, 23.2 W\/m2 in the previous version, and 28 W\/m2 in CERES-EBAF. Thus, the\u00a0average longwave and shortwave cloud radiative forcing in the new model version has proven to be much closer to observations<\/strong>\u00a0than in the previous version.<\/em><\/p>\n\n\n\n

From Table 1, the norm of the systematic\u00a0bias<\/strong>\u00a0has\u00a0decreased significantly for 850-hPa temperatures and 500-hPa geopotential height.<\/strong>\u00a0It was reduced mainly because average values of these fields approached observations, whereas the\u00a0averages of both fields in INMCM48 were underestimated.<\/strong><\/em><\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

Figure 3 Volodin et al (2023)<\/em><\/p>\n\n\n\n

We now consider the simulation of climate changes for 1850\u20132021. The\u00a05-year mean surface temperature from HadCRUT5\u00a0<\/strong>(black), INMCM48\u00a0<\/strong>(blue), and INMCM60\u00a0<\/strong>(red)\u00a0is shown in Fig. 3.<\/strong>\u00a0The\u00a0average for the period 1850 to 1899 is subtracted for each of the three datasets<\/strong>. The model data are slightly extended to the future, so that the most recent value matches the 2025\u20132029 average. It can be seen that\u00a0warming in both versions by 2010 is about 1 K<\/strong>, approximately consistent with observations. The observed climate changes, such as\u00a0the warmer 1940s and 1950s<\/strong>\u00a0and the slower warming, or even a small\u00a0cooling, in the 1960s and 1970s<\/strong>, are also obtained in both model versions. However, the\u00a0warming after 2010\u20132014 turns out to be far larger<\/strong>\u00a0in the new version than in the previous one, with differences reaching 0.5 K in 2025\u20132029. The discrepancies between the two versions are most distinct in the rate of temperature rise\u00a0from 1990\u20131994 to 2025\u20132029. In INMCM48, the temperature rises by about 0.8 K, while the increase for INMCM60 is about 1.5 K.<\/strong>\u00a0The discrepancy appears to have been caused primarily by a different sensitivity of the models, but\u00a0a substantial contribution may also come from natural variability<\/strong>, so a\u00a0more reliable conclusion<\/strong>\u00a0could be made\u00a0only by running ensemble numerical experiments.<\/strong><\/em><\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

Figure 4 Volodin et al. (2023)<\/em><\/p>\n\n\n\n

Figure 4 displays the\u00a0difference in surface air temperature from HadCRUT5<\/strong>\u00a0(top), the new version\u00a0<\/strong>(midddle)\u00a0, and the\u00a0previous version\u00a0<\/strong>(bottom)\u00a0in 2000\u20132021 and 1979\u20131999.<\/strong>\u00a0It is the interval where the warming was the largest, as is seen in Fig. 3. The observational data show that the\u00a0largest warming, above 2 K, was in the Arctic,<\/strong>\u00a0there was a warming of about\u00a01 K in the Northern Hemisphere midlatitudes,<\/strong>\u00a0and there was\u00a0hardly any warming over the Southern Ocean.<\/strong>\u00a0The pattern associated with a transition of the Pacific Decadal Oscillation (PDO) from the positive phase to the negative one appears over the Pacific Ocean. The\u00a0new model version simulates a temperature rise at high and middle northern latitudes<\/strong>\u00a0more closely to observations, whereas the previous version underestimates the rise in temperature in that region.<\/em><\/p>\n\n\n\n

At the same time,\u00a0over the tropical oceans<\/strong>\u00a0where the observed warming is small, the data from the previous model version agree better with observations, while the\u00a0new version overestimates warming.<\/strong>\u00a0Both models failed<\/strong>\u00a0to reproduce the Pacific Ocean temperature changes resulting from a positive to negative\u00a0phase transition of PDO<\/strong>, as well as near\u00a0zero temperature changes at southern midlatitudes.\u00a0\u00a0<\/strong>Large differences of temperature change in the\u00a0Atlantic sector of the Arctic,<\/strong>\u00a0where there is some temperature decrease in the INMCM48 model and\u00a0substantial increase in the INMCM60,<\/strong>\u00a0are\u00a0most probably<\/strong>\u00a0caused by\u00a0natural climate fluctuations<\/strong>\u00a0in this region, so a\u00a0reliable conclusion<\/strong>\u00a0regarding the response of these model versions to observed forcing could also be drawn here\u00a0only by running ensemble numerical experiments.<\/strong><\/em><\/p>\n\n\n\n

<\/p>\n\n\n\n

Conclusions<\/strong><\/em><\/h5>\n\n\n\n

The INMCM60 climate model is able to simulate present-day climate better than the previous version<\/strong> The largest decrease can be seen in systematic biases connected with an overestimation of surface temperatures at southern midlatitudes, an underestimation of surface air temperatures in the Arctic, and an underestimation of polar tropopause and tropospheric temperatures in the tropics. The simulation of the cloud radiative forcing has also improved.<\/strong><\/em><\/p>\n\n\n\n

Despite different equilibrium sensitivities to doubled \u0421\u041e2,\u00a0both model versions show approximately the same global warming by 2010\u20132015, similar to observations<\/strong>. However,\u00a0projections<\/strong>\u00a0of global temperature for\u00a02025\u20132029 already differ<\/strong>\u00a0between the two model versions by about 0.5 K. A more reliable conclusion regarding the difference in the simulation of current climate changes by the two model versions could have been made by running\u00a0ensemble simulations<\/strong>, but this is\u00a0likely to be done later<\/strong>\u00a0because of the large amount of computational time and computer resources it will take.<\/em><\/p>\n\n\n\n

<\/p>\n\n\n\n

My Comments<\/strong><\/h5>\n\n\n\n
    \n
  1. \u00a0Note that\u00a0INMCM60 runs hotter<\/strong>\u00a0than version 48 and HadCRUT5. However, as the author points out, this is\u00a0only a single simulation run,<\/strong>\u00a0and a truer result will come later from an ensemble of multiple runs. There were several other references to tetnative findings awaiting ensemble runs yet to be done.
    For example see the comparable ensemble performance of the previous version (then referred to as INMCM5)<\/li>\n<\/ol>\n\n\n\n
    \"\"<\/figure>\n\n\n\n

    Figure 1. The 5-year mean GMST (K) anomaly with respect to 1850\u20131899 for HadCRUTv4 (thick solid black); model mean (thick solid red). Dashed thin lines represent data from individual model runs: 1 \u2013 purple, 2 \u2013 dark blue, 3 \u2013 blue, 4 \u2013 green, 5 \u2013 yellow, 6 \u2013 orange, 7 \u2013 magenta. In this and the next figures numbers on the time axis indicate the first year of the 5-year mean.\u00a0<\/p>\n\n\n\n

    2.\u00a0 Secondly, this study confirms the warming impacts of cloud parameters that appear in\u00a0all the CMIP6 models<\/strong>. They all\u00a0run hotter primarily because of changes in cloud settings.<\/strong>\u00a0The author explains how\u00a0INMCM60 performance improved<\/strong>\u00a0in various respects,\u00a0but it came with increased CO2 sensitivity.<\/strong>\u00a0That value rose from 1.8C per doubling to 3.3C, shifting the model from lowest to middle of the range of CMIP6 models. (See\u00a0Climate Models: Good, Bad and Ugly<\/strong><\/a>)<\/p>\n\n\n\n

    \"\"<\/figure>\n\n\n\n

    Figure 8: Warming in the tropical troposphere according to the CMIP6 models. Trends 1979\u20132014 (except the rightmost model, which is to 2007), for 20\u00b0N\u201320\u00b0S, 300\u2013200 hPa.<\/p>\n\n\n\n

    3.\u00a0 Thirdly, the\u00a0temperature record standard has<\/strong>\u00a0changed with\u00a0a warming bias<\/strong>. See below from\u00a0Clive Best comparison between HadCrut 4.6 and HadCrut 5.<\/strong><\/a><\/p>\n\n\n\n

    \"\"<\/figure>\n\n\n\n

    The HadCRUT5 data show about a 0.1C increase in annual global temperatures compared to HadCRUT4.6. There are two reasons for this.<\/em><\/p>\n\n\n\n

    The change in sea surface temperatures moving from HadSST3 to HadSST4<\/em>
    The interpolation of nearby station data into previously empty grid cells.<\/em><\/p>\n\n\n\n

    Here I look into how large each effect is. Shown above is a comparison of HadCRUt4.6 with HadCRUT5.<\/em><\/p>\n\n\n\n

    Coincidentally or not, with the temperature standard shifting to HadCrut 5, model parameters shifted to show more warming to match. Skeptics of climate models are not encouraged by seeing warming added into the temperature record, followed by models tuned to increase CO2 warming.<\/p>\n\n\n\n

    4. The additional\u00a0warming<\/strong>\u00a0in both the model and in HadCRUT5 is\u00a0mostly located in the Arctic.<\/strong>\u00a0However, those observations include a warming bias derived from using datasets of anomalies rather than actual temperature readings.<\/p>\n\n\n

    \n
    \"\"\/<\/figure>\n<\/div>\n\n\n

    Clive Best provides this animation of recent monthly temperature anomalies which demonstrates how most variability in anomalies occur over northern continents.<\/p>\n\n\n\n

    <\/p>\n\n\n\n

    See\u00a0Temperature Misunderstandings<\/strong><\/a><\/p>\n\n\n\n

    The main problem with all the\u00a0existing observational datasets<\/strong>\u00a0is that they don\u2019t actually measure the global temperature at all. Instead they\u00a0measure the global average temperature \u2018anomaly\u2019.<\/strong>\u00a0. .The use of anomalies introduces a new bias because\u00a0they are<\/strong>\u00a0now\u00a0dominated by the larger \u2018anomalies\u2019 occurring at cold places in high latitudes.<\/strong>\u00a0The reason for this is obvious, because all extreme seasonal variations in temperature occur in northern continents, with the exception of Antarctica.\u00a0Increases in anomalies are mainly due to an increase in the minimum winter temperatures, especially near the arctic circle.<\/strong><\/em><\/p>\n\n\n\n

    A study of temperature trends recorded at weather stations around the Arctic showed the same pattern as the rest of NH.\u00a0 See\u00a0Arctic Warming Unalarming<\/strong><\/a><\/p>\n\n\n\n

    5. The CMIP program specifies that participating\u00a0models include CO2 forcing and exclude solar forcing.<\/strong>\u00a0Aerosols are the main parameter for tuning models to match. Scafetta has shown recently that models perform better when a solar forcing proxy is included. See\u00a0Empirical Proof Sun Driving Climate (Scafetta 2023)<\/strong><\/a><\/p>\n\n\n\n

    \u2022 The role of the Sun in climate change is hotly debated with diverse models.<\/em><\/p>\n\n\n\n

    \u2022 The Earth\u2019s climate is likely influenced by the Sun through a variety of physical mechanisms.<\/em><\/p>\n\n\n\n

    \u2022 Balanced multi-proxy solar records were created and their climate effect assessed.<\/em><\/p>\n\n\n\n

    \u2022 Factors other than direct TSI forcing account for around 80% of the solar influence on the climate.<\/em><\/p>\n\n\n\n

    \u2022 Important solar-climate mechanisms must be investigated before developing reliable GCMs.<\/em><\/p>\n\n\n\n

    This issue may well become crucial if we go into a cooling period due to a drop in solar activity.<\/p>\n\n\n\n

    <\/p>\n\n\n\n

    Summation<\/strong><\/h5>\n\n\n\n

    I appreciate very much the diligence and candor shown by the INM team in pursuing this monumental modeling challenge. The many complexities are evident, as well as the exacting attention to details in the attempt to dynamically and realistically represent Earth\u2019s climate. It is also clear that clouds continue to be a major obstacle to model performance, both hindcasting and forecasting. I look forward to their future results.<\/p>\n\n\n\n

    <\/p>\n\n\n\n

    Resources<\/strong><\/h5>\n\n\n\n

    Top Climate Model Gets Better<\/strong><\/a><\/p>\n\n\n\n

    Best Climate Model: Mild Warming Forecasted<\/strong><\/a><\/p>\n\n\n\n

    Temperatures According to Climate Models<\/strong><\/a><\/p>\n\n\n\n

    <\/p>\n","protected":false},"excerpt":{"rendered":"

    The many complexities are evident, as well as the exacting attention to details in the attempt to dynamically and realistically represent Earth\u2019s climate. It is also clear that clouds continue to be a major obstacle to model performance, both hindcasting and forecasting. I look forward to their future results.<\/p>\n","protected":false},"author":121246920,"featured_media":267815,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_coblocks_attr":"","_coblocks_dimensions":"","_coblocks_responsive_height":"","_coblocks_accordion_ie_support":"","_crdt_document":"","advanced_seo_description":"","jetpack_seo_html_title":"","jetpack_seo_noindex":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2},"jetpack_post_was_ever_published":false},"categories":[1],"tags":[691821126,691821129,691821124,691818076,691821125,691821131,691821128,691821130],"class_list":{"0":"post-267791","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","6":"hentry","7":"category-uncategorized","8":"tag-aerosol-evolution","9":"tag-atmospheric-dynamics","10":"tag-climate-model-from-ras-russian-academy-of-science","11":"tag-co2","12":"tag-inmcm48-version","13":"tag-inmcm60-model","14":"tag-land-snow","15":"tag-ocean-dynamics","17":"fallback-thumbnail"},"jetpack_publicize_connections":[],"jetpack_featured_media_url":"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2023\/07\/image-492.png?fit=1425%2C985&ssl=1","jetpack_likes_enabled":true,"jetpack_sharing_enabled":true,"jetpack_shortlink":"https:\/\/wp.me\/paxLW1-17Fd","jetpack-related-posts":[{"id":304416,"url":"https:\/\/climatescience.press\/?p=304416","url_meta":{"origin":267791,"position":0},"title":"Top Climate Model Improved to Show ENSO\u00a0Skill","author":"uwe.roland.gross","date":"26\/02\/2024","format":false,"excerpt":"Previous posts (linked at end) discuss how the\u00a0climate model from RAS (Russian Academy of Science)\u00a0has evolved through several versions. The interest arose because of its\u00a0greater ability to replicate the past temperature history.\u00a0","rel":"","context":"In \"climate model\"","block_context":{"text":"climate model","link":"https:\/\/climatescience.press\/?tag=climate-model"},"img":{"alt_text":"","src":"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2024\/02\/0ENSO_schematic_large.png?fit=1200%2C807&ssl=1&resize=350%2C200","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2024\/02\/0ENSO_schematic_large.png?fit=1200%2C807&ssl=1&resize=350%2C200 1x, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2024\/02\/0ENSO_schematic_large.png?fit=1200%2C807&ssl=1&resize=525%2C300 1.5x, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2024\/02\/0ENSO_schematic_large.png?fit=1200%2C807&ssl=1&resize=700%2C400 2x, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2024\/02\/0ENSO_schematic_large.png?fit=1200%2C807&ssl=1&resize=1050%2C600 3x"},"classes":[]},{"id":284074,"url":"https:\/\/climatescience.press\/?p=284074","url_meta":{"origin":267791,"position":1},"title":"Arctic Scientist at Russian Academy of Sciences declares: \u2018Warming is about to end\u2019 & \u2018We will inevitably transition to an unfavorable cold\u2019 period around 2030","author":"uwe.roland.gross","date":"19\/10\/2023","format":false,"excerpt":"\u201cWarming is about to end. And the cause is not humans, but the interplay between the Sun and Earth. Currently, we are in a favorable period, but we will inevitably transition to an unfavorable [cold] one ... around 2030-2035.\u201d Andrei Fedotov From ClimateDepot Polar specialist Andrey Fedotov of the Siberian\u2026","rel":"","context":"In \"Andrey Fedotov\"","block_context":{"text":"Andrey Fedotov","link":"https:\/\/climatescience.press\/?tag=andrey-fedotov"},"img":{"alt_text":"","src":"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2023\/10\/00image-536-1024x724-2.webp?fit=1024%2C724&ssl=1&resize=350%2C200","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2023\/10\/00image-536-1024x724-2.webp?fit=1024%2C724&ssl=1&resize=350%2C200 1x, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2023\/10\/00image-536-1024x724-2.webp?fit=1024%2C724&ssl=1&resize=525%2C300 1.5x, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2023\/10\/00image-536-1024x724-2.webp?fit=1024%2C724&ssl=1&resize=700%2C400 2x"},"classes":[]},{"id":290377,"url":"https:\/\/climatescience.press\/?p=290377","url_meta":{"origin":267791,"position":2},"title":"Leading Russian Polar Scientist: Cooling Begins In 2030\u2026Climate Crisis A \u2018Globalist Scam\u2019","author":"uwe.roland.gross","date":"07\/12\/2023","format":false,"excerpt":"From NoTricksZone By\u00a0P Gosselin\u00a0on\u00a06. December 2023 A top polar scientist interviewed by the Russian Academy of Sciences says we need to prepare for serious global cooling, to begin by 2030-2035. Cites studies of Lake Baikal and historic climate epochs. Andrey Fedotov. Photo: Siberian Branch of the Russian Academy of Sciences.\u2026","rel":"","context":"In \"2030-2035\"","block_context":{"text":"2030-2035","link":"https:\/\/climatescience.press\/?tag=2030-2035"},"img":{"alt_text":"","src":"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2023\/12\/image-163.png?fit=1200%2C675&ssl=1&resize=350%2C200","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2023\/12\/image-163.png?fit=1200%2C675&ssl=1&resize=350%2C200 1x, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2023\/12\/image-163.png?fit=1200%2C675&ssl=1&resize=525%2C300 1.5x, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2023\/12\/image-163.png?fit=1200%2C675&ssl=1&resize=700%2C400 2x, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2023\/12\/image-163.png?fit=1200%2C675&ssl=1&resize=1050%2C600 3x"},"classes":[]},{"id":258204,"url":"https:\/\/climatescience.press\/?p=258204","url_meta":{"origin":267791,"position":3},"title":"Today’s ocean models can only simulate less than 5% of the currents at 1,000-meter depth","author":"uwe.roland.gross","date":"20\/05\/2023","format":false,"excerpt":"Ocean motion plays a key role in the Earth's energy and climate systems. In recent decades, ocean science has made great strides in providing general estimates of large-scale ocean motion. However, there are still many dynamic mechanisms that are not fully understood or resolved.","rel":"","context":"In \"Climate change\"","block_context":{"text":"Climate change","link":"https:\/\/climatescience.press\/?tag=climate-change"},"img":{"alt_text":"","src":"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2023\/05\/0deep_ocean.png?fit=1200%2C857&ssl=1&resize=350%2C200","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2023\/05\/0deep_ocean.png?fit=1200%2C857&ssl=1&resize=350%2C200 1x, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2023\/05\/0deep_ocean.png?fit=1200%2C857&ssl=1&resize=525%2C300 1.5x, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2023\/05\/0deep_ocean.png?fit=1200%2C857&ssl=1&resize=700%2C400 2x, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2023\/05\/0deep_ocean.png?fit=1200%2C857&ssl=1&resize=1050%2C600 3x"},"classes":[]},{"id":341219,"url":"https:\/\/climatescience.press\/?p=341219","url_meta":{"origin":267791,"position":4},"title":"Latest INM Climate Model Projections Triggered by Scenario\u00a0Inputs","author":"uwe.roland.gross","date":"31\/08\/2024","format":false,"excerpt":"The latest climate simulation from the Russian INM was published in April 2024: Simulation of climate changes in Northern Eurasia by two versions of the INM RAS Earth system model. The paper includes discussing how results are driven greatly by processing of cloud factors.\u00a0 But first for context readers should\u2026","rel":"","context":"In \"Aerosol Emissions\"","block_context":{"text":"Aerosol Emissions","link":"https:\/\/climatescience.press\/?tag=aerosol-emissions-2"},"img":{"alt_text":"","src":"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2024\/08\/0variables-climate-models-Earth-forces-behaviour-materials.webp?fit=1163%2C1200&ssl=1&resize=350%2C200","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2024\/08\/0variables-climate-models-Earth-forces-behaviour-materials.webp?fit=1163%2C1200&ssl=1&resize=350%2C200 1x, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2024\/08\/0variables-climate-models-Earth-forces-behaviour-materials.webp?fit=1163%2C1200&ssl=1&resize=525%2C300 1.5x, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2024\/08\/0variables-climate-models-Earth-forces-behaviour-materials.webp?fit=1163%2C1200&ssl=1&resize=700%2C400 2x, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2024\/08\/0variables-climate-models-Earth-forces-behaviour-materials.webp?fit=1163%2C1200&ssl=1&resize=1050%2C600 3x"},"classes":[]},{"id":415575,"url":"https:\/\/climatescience.press\/?p=415575","url_meta":{"origin":267791,"position":5},"title":"Study: 2010 Russian Heat Wave NOT caused by \u2018climate change\u2019","author":"uwe.roland.gross","date":"01\/12\/2025","format":false,"excerpt":"The Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6) states that the global surface temperature has risen markedly since the pre-industrial era. This warming has led to more frequent and intense extreme heat events over most continents. In summer 2010, western Russia was hit by a record-breaking heatwave,\u2026","rel":"","context":"In \"climate propaganda\"","block_context":{"text":"climate propaganda","link":"https:\/\/climatescience.press\/?tag=climate-propaganda"},"img":{"alt_text":"","src":"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2025\/12\/0Screenshot-2025-12-01-160743.png?fit=1200%2C672&ssl=1&resize=350%2C200","width":350,"height":200,"srcset":"https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2025\/12\/0Screenshot-2025-12-01-160743.png?fit=1200%2C672&ssl=1&resize=350%2C200 1x, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2025\/12\/0Screenshot-2025-12-01-160743.png?fit=1200%2C672&ssl=1&resize=525%2C300 1.5x, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2025\/12\/0Screenshot-2025-12-01-160743.png?fit=1200%2C672&ssl=1&resize=700%2C400 2x, https:\/\/i0.wp.com\/climatescience.press\/wp-content\/uploads\/2025\/12\/0Screenshot-2025-12-01-160743.png?fit=1200%2C672&ssl=1&resize=1050%2C600 3x"},"classes":[]}],"_links":{"self":[{"href":"https:\/\/climatescience.press\/index.php?rest_route=\/wp\/v2\/posts\/267791","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/climatescience.press\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/climatescience.press\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/climatescience.press\/index.php?rest_route=\/wp\/v2\/users\/121246920"}],"replies":[{"embeddable":true,"href":"https:\/\/climatescience.press\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=267791"}],"version-history":[{"count":18,"href":"https:\/\/climatescience.press\/index.php?rest_route=\/wp\/v2\/posts\/267791\/revisions"}],"predecessor-version":[{"id":267817,"href":"https:\/\/climatescience.press\/index.php?rest_route=\/wp\/v2\/posts\/267791\/revisions\/267817"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/climatescience.press\/index.php?rest_route=\/wp\/v2\/media\/267815"}],"wp:attachment":[{"href":"https:\/\/climatescience.press\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=267791"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/climatescience.press\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=267791"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/climatescience.press\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=267791"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}