ITS1.10/CL0.1.9 | Addressing and understanding climate forcing and uncertainties in CMIP: Key insights and future directions
EDI
Addressing and understanding climate forcing and uncertainties in CMIP: Key insights and future directions
AGU and WMO
Convener: Lina TeckentrupECSECS | Co-conveners: Thomas AubryECSECS, Michaela I. Hegglin, Yiwen LiECSECS, Camilla MathisonECSECS, Julia MindlinECSECS, Alexander J. WinklerECSECS
Orals
| Wed, 17 Apr, 14:00–18:00 (CEST)
 
Room N2
Posters on site
| Attendance Wed, 17 Apr, 10:45–12:30 (CEST) | Display Wed, 17 Apr, 08:30–12:30
 
Hall X5
Orals |
Wed, 14:00
Wed, 10:45
The Coupled Model Intercomparison Project (CMIP) advances climate system understanding, but Earth System Models (ESM) exhibit disparities, particularly in responses to forcings and system coupling. As the IPCC relies on CMIP to provide information for policy decisions, a multidisciplinary approach is crucial to address uncertainties across the full CMIP production line. This session invites studies on climate forcings, climate responses, uncertainties in forcing agents, and model disparities in CMIP projections.

We welcome diverse climate-forcing research, including historical and future, anthropogenic and natural forcing development, idealized Earth System Model studies, observational evaluations, and works spanning all climate system components. Topics may include identifying disparities in CMIP ESMs, quantifying uncertainties, and addressing key scientific priorities for future model development. Contributions on opportunities, challenges, and constraints in using CMIP output for impact research, especially at regional scales, are encouraged.
This session ultimately aims at fostering collaboration among climate scientists, observationalists and modelers to address climate change challenges. Convened by WCRP CMIP Forcing Task Team and Fresh Eyes on CMIP, it aims to enhance understanding of CMIP uncertainties and prepare for CMIP6Plus and CMIP7 climate-forcing datasets.

Orals: Wed, 17 Apr | Room N2

Chairpersons: Thomas Aubry, Michaela I. Hegglin, Julia Mindlin
Climate forcing: quantifying the roles and responses of anthropogenic and natural climate drivers
14:00–14:05
14:05–14:25
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EGU24-9994
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solicited
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Highlight
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On-site presentation
Guido van der Werf and Margreet van Marle

Fires impact a suite of radiative forcing agents but fire is one of the most challenging sources of emissions to model due to a large degree of stochasticism and a wide range of climatic and human influences that can both increase and decrease the occurrence of fires. Although many Earth system models now account for fires, there is still a need for a coherent and consistent community dataset to intercompare and constrain models. We developed a historic dataset combining satellite data over the past two decades with proxy data and fire models for use in CMIP6. Since then, new satellite data has indicated that global burned area may be much higher than previously thought and several regional datasets have shed light on the question whether fire emissions are now higher or not than in the pre-industrial era. We show how the latest insight and developments will be used to construct an updated fire emissions dataset for CMIP7, and show which fire categories carry the largest uncertainty, both for the past and into the future.

How to cite: van der Werf, G. and van Marle, M.: Biomass burning emissions since the pre-industrial and into the future; progress and challenges, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9994, https://doi.org/10.5194/egusphere-egu24-9994, 2024.

14:25–14:35
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EGU24-7042
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ECS
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Virtual presentation
Jia-Rui Shi, Susan Wijffels, Young-Oh Kwon, Lynne Talley, and Sarah Gille

Modelled water-mass changes in the North Pacific thermocline from CMIP6, both in the subsurface and at the surface, reveal the impact of the competition between anthropogenic aerosols and greenhouse gases (GHGs) over the past 6 decades. The aerosol effect overwhelms the GHG effect during 1950-1985 in driving salinity changes on density surfaces, while after 1985 the GHG effect dominates. These subsurface water-mass changes are traced back to changes at the surface, of which ~70% stems from the migration of density surface outcrops, equatorward due to regional cooling by anthropogenic aerosols and subsequent poleward due to warming by GHGs. Ocean subduction connects these surface outcrop changes to the main thermocline. Both observations and models reveal this transition in climate forcing around 1985 and highlight the important role of anthropogenic aerosol climate forcing on our oceans’ water masses.

How to cite: Shi, J.-R., Wijffels, S., Kwon, Y.-O., Talley, L., and Gille, S.: The Competition Between Anthropogenic Aerosol and Greenhouse Gas Forcing is Revealed by North Pacific Water-mass Changes, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7042, https://doi.org/10.5194/egusphere-egu24-7042, 2024.

14:35–14:45
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EGU24-6774
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On-site presentation
Douglas Kinnison, Daniel Marsh, and Simone Tilmes

The solar forcing dataset prepared for the 6th round of the Coupled Model Intercomparison Project (CMIP6) has been used extensively in climate model experiments. Recently, an International Space Science Institute (ISSI) Working Group was established to revisit the solar forcing recommendations in order to define a roadmap for building a revised solar forcing dataset for the upcoming 7th round of CMIP (Funke et al., 2023). This new dataset will introduce changes in the radiative forcing of climate either directly, or indirectly via changes in atmospheric composition. In CMIP6, the solar forcing consisted of both a total solar irradiance (TSI), along with a spectrally resolved solar irradiance (SSI). The TSI for solar minimum was set to 1360.8±0.5Wm-2 and the SSI covered the 10nm to 100mm spectral region. A similar approach is proposed for CMIP7 except for two major aspects of the reconstruction: 1) the definition of the reference spectrum for the quite Sun; 2) the temporal variability. The major difference between the proposed CMIP7 SSI quite sun reference spectrum and that used for CMIP6 is the spectral shape. The new SSI spectrum has an irradiance that is 1-5% higher in the visible band and lower by 1-2% in the Near-IR wavelength range (1000-2000nm). The solar temporal variability in the CMIP6 and CMIP7 reconstructions are based on both the NRLSSI2 and SATIRE reconstructions. These reconstructions have been improved in preparation for CMIP7 and the aim is for both reconstructions to use the same reference spectrum and be driven by the same solar proxies. In this work we used the Whole Atmosphere Community Climate Model (WACCM) to examine the chemical and climate implications of the proposed CMIP7 solar forcing updates compared to the CMIP6 approach. WACCM is a chemistry-climate model that extends from the surface to 140km. The horizontal resolution is ~1degree. WACCM has a detailed representation of chemical and dynamical processes from the troposphere through the lower thermosphere. We examined the “chemical only” impacts of the solar forcing choice by running WACCM in the specified dynamics mode using NASA Modern-Era Retrospective analysis for Research and Applications Version 2 (MERRA2). The “climate” impacts were derived by running the model with interactive dynamics coupled to a deep ocean. Conclusions from this work will support the development of the next version of WACCM for participation in the CMIP7 assessment.

Funke, B., Dudok de Wit, T., Ermolli, I., Haberreiter, M., Kinnison, D., Marsh, D., Nesse, H., Seppälä, A., Sinnhuber, M., and Usoskin, I.: Towards the definition of a solar forcing dataset for CMIP7, Geosci. Model Dev. Discuss. https://doi.org/10.5194/gmd-2023-100.

 

How to cite: Kinnison, D., Marsh, D., and Tilmes, S.: Evaluation of the chemistry and climate impact of the new solar forcing dataset for CMIP7 using the Whole Atmosphere Community Climate Model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6774, https://doi.org/10.5194/egusphere-egu24-6774, 2024.

14:45–14:55
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EGU24-5200
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On-site presentation
Stephanie Fiedler, Sabine Bischof, Natalia Sudarchikova, Rachel M. Hoesly, and Steven J. Smith

Anthropogenic aerosol forcing is quantitatively uncertain affecting the ability to constrain the climate response to anthropogenic perturbations. Climate models participating in the Coupled Model Intercomparison Project (CMIP) use different methods to incorporate direct and cloud-mediated aerosol effects. Some models in CMIP6 used prescribed anthropogenic aerosol optical properties and associated effects on cloud droplet number concentrations from the Simple Plumes parameterization fitted to the Max-Planck-Institute for Meteorology’s Aerosol Climatology version 2 (MACv2-SP). MACv2-SP was originally designed for the use in a subset of experiments for the Radiative Forcing Model Intercomparison Project to better understand the model diversity in aerosol forcing (Fiedler et al., 2023). The final uptake of MACv2-SP for research was, however, much broader. In the context of CMIP, the implementation of MACv2-SP in several climate models led to the request for new MACv2-SP input data that are consistent with updated emissions, e.g., in the framework of CovidMIP (Fiedler et al., 2021) and now in preparation for CMIP7 via the CMIP Climate Forcings Task Team. Moreover, MACv2-SP also serves in creating seasonal and decadal predictions, and satellite products.

We will therefore derive and freely provide new data for the anthropogenic aerosol optical properties and their cloud-mediated effects based on newly available emissions. The next data version of MACv2-SP is currently in preparation for interests in using CMIP6plus compliant boundary data. It will use the historical emission data for aerosols and their precursors from the new release of the Community Emission Data System (CEDS), which will be published at the beginning of 2024. The new emissions will allow us to revise and extent the historical data for MACv2-SP to include years after 2014. Expected changes compared to the MACv2-SP data used in CMIP6 are improved aerosol optical depth over some land regions in recent years, where the observations developed differently compared to assumptions in the scenarios. We will further translate uncertainty in the emission data to expected differences in the aerosol forcing. In addition to the new data for CMIP6plus, a new development of the simple plumes approach will be made for an assessment of the radiative forcing and climate response to aerosols from severe wild fires in recent years that are not represented by CMIP6 models.

Fiedler, S., Wyser, K., Rogelj, J. and van Noije, T. (2021) Radiative effects of reduced aerosol emissions during the COVID-19 pandemic and the future recovery.  Atmospheric Research, 264 . Art.Nr. 105866. DOI 10.1016/j.atmosres.2021.105866.

Fiedler, S., van Noije, T., Smith, C. J., Boucher, O., Dufresne, J., Kirkevåg, A., Olivié, D., Pinto, R., Reerink, T., Sima, A. and Schulz, M. (2023) Historical Changes and Reasons for Model Differences in Anthropogenic Aerosol Forcing in CMIP6. Geophysical Research Letters, 50 (15). Art.Nr. e2023GL104848. DOI 10.1029/2023GL104848.

How to cite: Fiedler, S., Bischof, S., Sudarchikova, N., Hoesly, R. M., and Smith, S. J.: Anthropogenic aerosol forcing in CMIP from prescribed optical and cloud microphysical properties, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5200, https://doi.org/10.5194/egusphere-egu24-5200, 2024.

14:55–15:05
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EGU24-1657
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On-site presentation
Gregor C. Leckebusch, Kelvin S. Ng, and Kevin I. Hodges

Given the significant socioeconomic impact of the East Asian Summer Monsoon (EASM), a critical area of investigation involves comprehending how the EASM and, consequently, the hydrological cycle over East Asia might change in future climates. To address this inquiry, reliable climate models must be employed. While assessments of model performance commonly concentrate on the generated precipitation amounts during the EASM period, it is important to note that the representation of dynamical components such as the Mei-yu front (MYF) are not frequently investigated. As model outputs may be correct for incorrect reasons, the dynamical components of the EASM might be misrepresented.
In this investigation, we scrutinized the representation of the MYF in historical simulations of 38 CMIP6 models from May to August, comparing them to ERA5. Our findings reveal that numerous CMIP6 models encounter difficulties in reproducing the climatology of the MYF similar to observations. By sub-sampling models based on the meridional position bias of the MYF in May, we identified distinct monthly variations within these groupings. Additionally, the origins of these biases were examined. Our study stresses the link between the misrepresentation of MYF climatology in CMIP6 models and the depiction of the North Pacific High, particularly its western edge. The implications of these discoveries are also explored. 

How to cite: Leckebusch, G. C., Ng, K. S., and Hodges, K. I.: Climatological Evaluation of the Mei-yu Front Representation in CMIP6, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1657, https://doi.org/10.5194/egusphere-egu24-1657, 2024.

15:05–15:15
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EGU24-20254
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On-site presentation
Kirstin Krüger, Herman Fuglestvedt, Zhihong Zhuo, and Andrea Burke

Reconstructions of past volcanic forcing rely on the assumption that the stratospheric sulphur loading from eruptions in the pre-satellite era is directly proportional to the sulphate flux recorded in polar ice sheets. The scaling factors, known as "transfer functions," used for this calculation are currently based on the Antarctic sulphate flux following the 1991 Pinatubo eruption, radioactivity in Greenland ice from nuclear weapon tests, and model simulations of two high-latitude eruptions. However, recent studies have shown that ice sheet deposition of volcanic sulphate varies significantly as a function of both eruptive parameters and the background atmospheric state, presenting an opportunity to enhance the accuracy and reliability of volcanic forcing reconstructions through improving the use of transfer functions.

 

Here, we investigate how the transfer function depends on eruption parameters and background conditions. Using simulations with the Earth system model CESM2-WACCM6, we explore a wide range of parameters, including eruption magnitude, latitude, plume composition, season, and plume height. By understanding the relationships between eruption parameters and resulting polar sulphate fluxes, we aim to improve the transfer function estimate used in the volcanic forcing for CMIP6 and shed light on the associated uncertainties.

How to cite: Krüger, K., Fuglestvedt, H., Zhuo, Z., and Burke, A.: Uncertainties of past volcanic forcing - Modelling the impacts of eruption parameters and atmospheric background conditions, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20254, https://doi.org/10.5194/egusphere-egu24-20254, 2024.

15:15–15:25
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EGU24-19839
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ECS
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On-site presentation
Hera Guðlaugsdóttir, Yannick Peings, Davide Zanchettin, and Guðrún Magnúsdóttir

Given the fact that many Icelandic volcanic systems are on the verge of an eruption, producing some of the largest volcanic eruptions over the past millennia, e.g., Öræfajökull, Bárðabunga, Grímsvötn and the Katla system, it is important to be able to predict potential changes in Northern Hemisphere (NH) climate variability in the following years after an NH eruption in due time. Recent volcanic activity in Iceland, e.g., Holuhraun 2014-2015 and Reykjanes/Geldingadalur 2021-2023, further demonstrates this urgency.

With the aim to contribute to improving the forcasting and adaptation strategies for the North Atlantic region we, as a first step, forced an Earth System Model (CESM1.2.2) with an idealized long-lasting high-latitude volcanic eruption to quantify i) the response within the stratospheric polar vortex and ii) the resulting response within the coupled climate system in the Northern Hemisphere (NH) by assessing the first 15 years following the eruption focusing on the winter (DJF) response. Here results will be presented showing evidence of sudden stratospheric warming events and a deceleration of the stratospheric polar vortex occurring in the second and third post-volcanic winter. This is identified in the temperature and zonal winds at 50hPa as a result of the large modelled surface cooling in the NH where Eliassen-Palmer wave flux calculations further support these findings. The strong stratospheric response identified further influences surface climate throughout the continental NH in the first 5 years following this event via the NAO. Our result suggest that two competing mechanisms are at work during these first years, partly explaining this long-lasting short-term response. The long-term impact is identified as a change in regional surface temperature and sea ice variability as well as a general strengthening of the AMOC, reaching a maximum in winter 2 and remaining positive throughout the run.

How to cite: Guðlaugsdóttir, H., Peings, Y., Zanchettin, D., and Magnúsdóttir, G.: Modelling the climate response following idealized long-lasting high latitude volcanic eruptions: The stratospheric response and resulting implications for North Atlantic surface weather, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19839, https://doi.org/10.5194/egusphere-egu24-19839, 2024.

15:25–15:35
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EGU24-2964
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Highlight
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On-site presentation
Shili Yang

The reversibility of a wide range of components of the earth system was investigated by comparing forward and time-reversed 
historical and future simulations of a coupled earth system model known as the Beijing Normal University earth system 
model. Many characteristics of the climate system, including the surface temperature, ocean heat content (OHC), convective 
precipitation, total runof, ground evaporation, soil moisture, sea ice extent, and Atlantic Meridional Overturning Circulation, 
did not fully return to their initial values when the historical or future natural and anthropogenic forcing agents were reversed. 
The surface temperature and OHC declines lagged behind the decline in greenhouse gases (GHGs). Reverses in other variables occurred in direct response to the decline in GHGs. The sea level increased, even after all of the forces returned to the 
original values. Furthermore, most of the climate variables did not return to their original values because of thermal inertial. 
The end states of variables, other than those related to thermal storage, mainly depended on the original state of the natural 
and anthropogenic forces, and were unafected by the future growth rate of the GHGs. The climate policy implication of this 
study is that climate change cannot be completely reversed even if all the external forces are returned to their initial values

How to cite: Yang, S.: Reversibility of historical and future climate change with a complex earth system model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2964, https://doi.org/10.5194/egusphere-egu24-2964, 2024.

15:35–15:45
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EGU24-1711
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Virtual presentation
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Hideo Shiogama, Shinichiro Fujimori, Tomoko Hasegawa, Michiya Hayashi, Yukiko Hirabayashi, Tomoo Ogura, Toshichika Iizumi, Kiyoshi Takahashi, and Toshihiko Takemura

Because recent mitigation efforts have made the upper-end scenario of the future GHG concentration (SSP5-8.5) highly unlikely, SSP3-7.0 has received attention as an alternative high-end scenario for impacts, adaptation, and vulnerability (IAV) studies. However, the ‘distinctiveness’ of SSP3-7.0 may not be well-recognized by the IAV community. When the integrated assessment model (IAM) community developed the SSP-RCPs, they did not anticipate the limelight on SSP3-7.0 for IAV studies because SSP3-7.0 was the ‘distinctive’ scenario regarding to aerosol emissions (and land-use land cover changes). Aerosol emissions increase or change little in SSP3-7.0 due to the assumption of a lenient air quality policy, while they decrease in the other SSP-RCPs of CMIP6 and all the RCPs of CMIP5. This distinctive high-aerosol-emission design of SSP3-7.0 was intended to enable climate model (CM) researchers to investigate influences of extreme aerosol emissions on climate. Here we show that large aerosol emissions in SSP3-7.0 significantly suppress future increases in precipitation. We recommend IAV researchers to compare impact simulations at the same warming level between SSP3-7.0 and SSP5-8.5 to examine the effects of aerosols in the case that such analyses are adequate. We also recommend ScenarioMIP for CMIP7 to exclude scenarios with extreme policies of aerosols (and land-use land-cover changes) from Tier 1 experiments and instead include them in Tier 2.

 

Reference: Shiogama, H., et al. Nat. Clim. Chang. 13, 1276–1278 (2023). https://doi.org/10.1038/s41558-023-01883-2

How to cite: Shiogama, H., Fujimori, S., Hasegawa, T., Hayashi, M., Hirabayashi, Y., Ogura, T., Iizumi, T., Takahashi, K., and Takemura, T.: Recognizing distinctiveness of SSP3-7.0 for use in impact assessments, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1711, https://doi.org/10.5194/egusphere-egu24-1711, 2024.

Coffee break
Chairpersons: Lina Teckentrup, Yiwen Li, Alexander J. Winkler
Addressing and Understanding Uncertainties in CMIP: Key Insights and Future Directions
16:15–16:20
16:20–16:30
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EGU24-2903
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On-site presentation
Hervé Douville

Despite the early warnings of the scientific community in general and of the IPCC in particular, we have entered decades in which climate models are no longer black boxes as the consequences of past emissions of greenhouse gases are emerging rapidly in multiple climate records. This unprecedented situation is likely to change our methods and our view of the respective roles of models and observations in understanding recent and predicting future climate change, regardless of the considered emission scenario. Among the key questions raised are the role of observations in model tuning versus projection constraining and the design of future model intercomparison projects. These questions will be illustrated by several recent studies aimed at constraining CMIP6 projections and, hopefully, with a fresh although critical look on the forthcoming CMIP7 project.

How to cite: Douville, H.: Confronting Earth System Model Trends with Observations: The Good, the Bad, and the Ugly, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2903, https://doi.org/10.5194/egusphere-egu24-2903, 2024.

16:30–16:40
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EGU24-10136
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ECS
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On-site presentation
Cedric Gacial Ngoungue Langue, Hélène Brogniez, and Philippe Naveau

Water vapor is one of the fundamental atmospheric components, and as such, is one  Essential Climate Variable  (ECV) monitored by the Global Climate Observing System. In this work, the global water vapor Climate Data Record (CDR) generated within the ESA Water Vapor climate change initiative project (WV_cci) is used as reference (daily, 0.1°, 2003-2014) to evaluate a sample of the Coupled Model Intercomparison Project phase 6 (CMIP6) as well as the fifth generation ECMWF reanalysis (ERA5), with a focus on temporal signal decomposition. This temporal decomposition is performed using multi-resolution analysis (MRA). MRA is a mathematical tool which consists of decomposing a signal into its subcomponents on different time scales. Using this tool, the representation of the total column water vapor over the tropics in the CMIP6 models and ERA5 can be assessed separately from daily to annual and decadal time scales, including monthly and seasonal time scales. This approach is powerful for the  identification of  the relevant time scales for which CMIP6 predictions are most reliable. Hence, at the global-tropical scale, the MRA decomposition of the water vapor signal shows a good correlation between CMIP6 and WV_cci on both seasonal (2 - 8 months) and annual (1 - 1.4 year) time scales. Using a linear regression, we attempt to reconstruct the WV_cci signal using the CMIP6 models and ERA5 as explanatory variables based on the correlation found between the products and WV_cci at each level of decomposition. Such reconstruction highlights the scales of variability that are closest to the observed one. The presentation will detail the MRA approach and the most prominent results, as well as an extension to other parameters linked to atmospheric water vapor distribution, namely cloud cover and types and sea surface temperature. 

How to cite: Ngoungue Langue, C. G., Brogniez, H., and Naveau, P.: CMIP6 models evaluation using multi-resolution analysis and satellite observations : study of the atmospheric water vapor , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10136, https://doi.org/10.5194/egusphere-egu24-10136, 2024.

16:40–16:50
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EGU24-5527
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On-site presentation
Ranjini Swaminathan, Jacob Schewe, Jeremy Walton, Klaus Zimmermann, Richard Betts, Chantelle Burton, Chris Jones, Colin Jones, Matthias Mengel, Christopher Reyer, Andrew Turner, and Katja Weigel

Climate risk assessments must account for a wide range of possible future changes, so scientists often use many climate models in order to fully explore the range of potential changes in regional climates and their impacts. Many of the latest-generation global climate models have high values of effective climate sensitivity (EffCS), which are unlikely according to independent estimates of EffCS. It has been argued that these “hot” models are unrealistic and should therefore be excluded from analyses of climate change impacts. However, whether this would really improve regional impact assessments, or actually make them worse, is unclear. Here we show that there is no universal relationship between EffCS and projected changes in important climatic impact drivers. Analysing three different impacts - heavy rainfall, meteorological drought, and fire weather in important world regions, we find a significant correlation with EffCS only in some regions and for some metrics. Moreover, even in those cases, internal variability has a larger effect on projected changes than has EffCS. This means that impact studies should not select climate models based solely on their EffCS, which does not help constrain projections and may potentially neglect realistic impacts in models deemed “unrealistic” on the basis of their sensitivity. We recommend that model selection or filtering must be based on a more specific evaluation of models vis-à-vis the impact of interest.

How to cite: Swaminathan, R., Schewe, J., Walton, J., Zimmermann, K., Betts, R., Burton, C., Jones, C., Jones, C., Mengel, M., Reyer, C., Turner, A., and Weigel, K.: Regional impacts poorly constrained by climate sensitivity , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5527, https://doi.org/10.5194/egusphere-egu24-5527, 2024.

16:50–17:00
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EGU24-10567
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On-site presentation
Yiqi Luo

Large uncertainty in model predictions of land carbon responses to climate change has been ubiquitously demonstrated in model intercomparison projects (MIPs). The large uncertainty become a major impediment in advancing climate change prediction. Thus, it is imperative to identify sources of the uncertainty before we can fully understand and address the uncertainty issue. In this presentation, I show a novel matrix approach to analytically pin down the sources of model uncertainty in predicting carbon dynamics in response to rising atmospheric CO2 concentration and increasing temperature. We developed a matrix-based MIP by converting the carbon cycle module of eight land models (i.e., TEM, CENTURY4, DALEC2, TECO, FBDC, CASA, CLM5 and ORCHIDEE) into eight matrix models. In response to rising atmospheric CO2 concentration and increasing temperature, predicted ecosystem net primary production (NPP), net ecosystem production (NEP), and net ecosystem carbon storage spread among the eight models as simulations go over time. We applied the traceability analysis method to decompose simulated carbon dynamics to their traceable components according to the matrix equations. Our analysis indicates that the uncertainty among the eight models was mainly due to inter-model difference in baseline carbon residence time and environmental scalar. Once the sources of model uncertainty were identified, we sequentially standardized model parameters to shrink simulated ecosystem carbon storage and NEP to almost none. Our study demonstrates that the sources of uncertainty in carbon cycle modeling can be precisely traced to model structures and parameters, regardless of their complexity, so that the uncertainty issue for MIPs can be precisely understood and well addressed.

How to cite: Luo, Y.: Uncertainty spreading and shrinking among eight land carbon cycle models in response to climate change, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10567, https://doi.org/10.5194/egusphere-egu24-10567, 2024.

17:00–17:10
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EGU24-14596
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ECS
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On-site presentation
Jonathan Beverley, Matthew Newman, and Andrew Hoell

Questions regarding the uncertainty of trends in both historical and projected climate model simulations have been limited by uncertainty about the relative importance of internal variability and external forcing to trends over the relatively short observational record. For example, is the discrepancy between historically simulated tropical Pacific trends (El Niño-like) and observations (broadly, La Niña-like) over recent decades a reflection of sampling issues or model error in internal variability and/or forced global responses (either locally or remotely, such as from the Southern Ocean)? At the same time, it is known that systematic operational seasonal forecast errors (e.g., westward shift of ENSO) are dominated by model errors that develop quite quickly, on the order of a few months of forecast lead time.

Here, we suggest that climate model trend errors can be usefully investigated by examining their rapid development within seasonal hindcast datasets. We show that many apparent climate simulation trend discrepancies are evident in trends computed from monthly seasonal hindcasts over the 1994-2016 period for a suite of operational initialised forecast models from C3S and NMME, and in many cases are well developed even at short lead times. These hindcasts use models similar to CMIP-class models and include the same CMIP historical external forcings, but critically are initialised with observations, removing uncertainty related to internal variability. We find these trend errors in many different regions worldwide for several key variables, including sea surface temperature, precipitation and sea level pressure, and investigate their seasonal dependence as well. Notably, we find tropical Pacific "El Niño-like" SST trend errors in all seasons but spring, and related surface pressure, temperature, and precipitation errors in autumn and spring, especially in the North America region. We also find errors in Southern Ocean SSTs, which develop less rapidly than the tropical Pacific SST errors or their global teleconnections.

We suggest that these hindcast trend errors reflect sensitivity of the model mean biases to the changing radiative forcing, rather than a forced response. That is, similarity between errors in free running simulations and hindcasts is a result of the seasonal forecast models quickly transitioning from nature’s attractor to the climate model attractor, particularly in the atmospheric model component. This suggests that we might be able to better diagnose the climate model trend errors by looking at the early development of the forecast trend error in the seasonal forecast models.

How to cite: Beverley, J., Newman, M., and Hoell, A.: Rapid development of systematic trend errors in seasonal forecasts and their connection to CMIP6 trend errors, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14596, https://doi.org/10.5194/egusphere-egu24-14596, 2024.

17:10–17:20
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EGU24-5895
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ECS
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On-site presentation
Timothée Bourgeois, Olivier Torres, Friederike Fröb, Aurich Jeltsch-Thömmes, Giang T. Tran, Jörg Schwinger, Thomas L. Frölicher, Fortunat Joos, David Keller, Andreas Oschlies, and Laurent Bopp

Tipping points are thresholds beyond which large, abrupt and possibly irreversible changes in the climate system or in large scale ecosystems would occur. The crossing of such tipping points under anthropogenic forcing poses a threat to biodiversity, food security, and human societies. However, due to the complexity of the processes involved, it remains notoriously difficult to determine exact thresholds that need to be avoided to stay within a “safe operating space” for humanity. Here, we map, for a variety of mitigation metrics, the crossing of thresholds, which we define to represent a wide range of deviations from the unperturbed state. We assess the crossing of these thresholds in a wide range of plausible future emission pathways: two climate mitigation scenarios (one with a strong overshoot) and one no-mitigation high-emissions scenario. These scenarios are simulated by the latest generation of Earth system models and by two Earth system models of intermediate complexity, for which we created large perturbed-parameter ensembles. Using this comprehensive model database we provide estimates of when and at which warming level 4 mitigation targets (thresholds) for 14 different impact metrics are exceeded along with an assessment of uncertainties. We find that under the high-emissions scenario, even the highest thresholds for many of the impact metrics are exceeded with high confidence, such as the expansion of ocean areas that are undersaturated with respect to aragonite, decreases in plankton biomass, Arctic summer sea ice extent, strength of the Atlantic meridional overturning circulation (AMOC), and subsurface oxygen concentration. The risk of exceeding a given mitigation target decreases under low-emissions and overshoot scenarios. Yet, exceedance of ambitious targets for aragonite undersaturation, Arctic summer sea ice extent, and steric sea level rise (SSLR) are projected to be difficult to avoid (high confidence) even under the low-emissions scenario. The overshoot scenario reduces the risk of exceeding mitigation targets related to Arctic summer sea ice extent, SSLR, AMOC and plankton biomass compared to the high-emissions scenario, particularly in the long-term. Uncertainties in Earth system model projections of net primary production prevent us from concluding on the risk of mitigation target exceedance for this impact metric.

How to cite: Bourgeois, T., Torres, O., Fröb, F., Jeltsch-Thömmes, A., Tran, G. T., Schwinger, J., Frölicher, T. L., Joos, F., Keller, D., Oschlies, A., and Bopp, L.: Pathways for avoiding ocean biogeochemical damage: Mitigation targets, mitigation options, and projections, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5895, https://doi.org/10.5194/egusphere-egu24-5895, 2024.

17:20–17:30
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EGU24-10382
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ECS
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Virtual presentation
Kwatra Sadhvi, Matthieu Lengaigne, Jérôme Vialard, Vincent Danielli, Gopika Suresh, and Suresh Iyyappan

Surface air-sea feedbacks play a pivotal role in modulating the amplitude of global ocean warming. Zhang and Li (2014, ZL14) introduced a simple theoretical framework to identify the driving processes responsible for the Sea Surface Temperature (SST) increase under global warming. This method involves decomposing changes in latent and upwelling longwave surface heat fluxes into two parts: one tied to direct atmospheric forcing and the other directly associated with local (SST) changes, termed feedback. Applying this heat budget equation across 53 CMIP5 and 6 models underscores the pivotal role of increased surface downwelling longwave radiation (DLR) in steering the amplitude of future global ocean warming. However, ZL14 solely considered DLR as a direct forcing, overlooking its substantial feedback response to surface warming.

In this study, we employ a novel methodology from Shakespeare and Roderick (2022, SR22) to decompose DLR changes into a direct radiative forcing and SST-related feedbacks, evaluating the implications of integrating the DLR feedback in the ZL14 framework. Our analysis is in line with SR22’s findings across 5 CMIP5 models, our results across 53 models indicate that roughly 90% of DLR increase emerges from feedbacks associated with the rising SST. The large ocean heat capacity transfers warming to the overlying atmosphere, increasing its DLR primarily through direct air temperature increase and the increasing greenhouse effect associated with increased water vapour.

Incorporating the DLR feedback in ZL14 framework yields a dominant effect of latent heat flux forcing on global ocean warming for both multi-model mean and intermodel diversity. This latent heat flux forcing is related to the evaporative cooling modulation associated with projected changes in the surface atmospheric circulation, and is highly correlated with the magnitude of the global average warming. This underscores the substantial influence of projected atmospheric circulation changes on the level of global average warming.

How to cite: Sadhvi, K., Lengaigne, M., Vialard, J., Danielli, V., Suresh, G., and Iyyappan, S.: A key role of surface atmospheric circulation changes in setting global ocean warming magnitude, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10382, https://doi.org/10.5194/egusphere-egu24-10382, 2024.

17:30–17:40
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EGU24-6750
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ECS
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On-site presentation
Peer Nowack and Duncan Watson-Parris

Global climate change projections, such as those from the Coupled Model Intercomparison Project phase 6 (CMIP6), are still subject to substantial modelling uncertainties. A variety of Emergent Constraints (ECs) have been suggested to address these uncertainties, but remain heavily debated in the scientific community. Still, the central idea behind ECs to relate future projections to already observable quantities has no real substitute.

Here we discuss machine learning (ML) approaches for new types of controlling factor analyses (CFA) as a promising alternative. The principal idea is to use ML to find climate-invariant relationships in historical data, which also hold approximately under strong climate change scenarios. On the basis of existing big data archives such as those from the CMIPs, these climate-invariant relationships can be validated in perfect-climate-model frameworks.

From a ML perspective, we argue that CFA are promising for three reasons: (a) they can be objectively validated both for present-day data and future data and (b) they provide more direct - by design physically-plausible - links between historical observations and potential future climates compared to ECs and (c) they can take higher dimensional relationships into account that better characterize the still complex nature of large-scale emerging relationships. We highlight these advantages for three examples in the form of constraints on climate feedback mechanisms (clouds [1], stratospheric water vapour [2]) and forcings (aerosol-cloud interactions).

References:

1. Ceppi P. and Nowack P. Observational evidence that cloud feedback amplifies global warming, Proceedings of the National Academy of Sciences 118 (30), e2026290118 (2021). https://doi.org/10.1073/pnas.2026290118

2. Nowack P., Ceppi P., Davis S.M., Chiodo G., Ball W., Diallo M.A., Hassler B., Jia Y., Keeble J., and Joshi M. Response of stratospheric water vapour to warming constrained by satellite observations, Nature Geoscience 16, 577-583 (2023). https://doi.org/10.1038/s41561-023-01183-6

How to cite: Nowack, P. and Watson-Parris, D.: Why all emergent constraints are wrong but some are useful - a machine learning perspective, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6750, https://doi.org/10.5194/egusphere-egu24-6750, 2024.

17:40–17:50
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EGU24-111
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ECS
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On-site presentation
Álvaro Salazar, Marcus Thatcher, Katerina Goubanova, Patricio Bernal, Julio Guitérrez, and Francisco Squeo

Precipitation and near-surface temperature from an ensemble of 36 new state‐of‐the‐art climate models under the Coupled Model Inter‐comparison Project phase 6 (CMIP6) are evaluated over Chile´s climate. The analysis is focused on four distinct climatic subregions: Northern Chile, Central Chile, Northern Patagonia, and Southern Patagonia. Over each of the subregions, first, we evaluate the performance of individual global climate models (GCMs) against a suit of precipitation and temperature observation-based gridded datasets over the historical period (1986-2014) and then we analyze the models’ projections for the end of the century (2080-2099) for four different shared socioeconomic pathways scenarios (SSP). Although the models are characterized by general wet and warm mean bias, they reproduce realistically the main spatiotemporal climatic variability over different subregions. However, none of the models is best across all subregions for both precipitation and temperature. Moreover, among the best performing models defined based on the Taylor skill score, one finds the so-called “hot models” likely exhibiting an overestimated climate sensitivity, which suggests caution in using these models for accessing future climate change in Chile. We found robust (90% of models agree in the direction of change) projected end-of-the-century reductions in mean annual precipitation for Central Chile (~-20% to ~-40%) and Northern Patagonia (~-10% to ~-30%) under scenario SSP585, but changes are strong from scenario SSP245 onwards, where precipitation is reduced by 10-20%. Northern Chile and Southern Patagonia show non-robust changes in precipitation across the models. Yet, future near-surface temperature warming presented high inter-model agreement across subregions, where the greatest increments occurred along the Andes Mountains. Northern Chile displays the strongest increment of up to ~6°C in SSP585, followed by Central Chile (up to ~5°C). Both Northern and Southern Patagonia show a corresponding increment by up to ~4°C. We also briefly discuss about the environmental and socio-economic implications of these future changes for Chile.

How to cite: Salazar, Á., Thatcher, M., Goubanova, K., Bernal, P., Guitérrez, J., and Squeo, F.: CMIP6 precipitation and temperature projections for Chile, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-111, https://doi.org/10.5194/egusphere-egu24-111, 2024.

17:50–18:00
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EGU24-7159
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On-site presentation
Venkata Reddy Keesara, Eswar Sai Buri, and Loukika Kotapati Narayanaswamy

Regional climate modelling has evolved significantly, offering versatile applications across various scales and resolutions. This study aims to provide a comprehensive framework for selecting top five Climate Models at each grid for climate variables in the Munneru River Basin, comes under Lower Krishna River Basin, India. Employing the NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP) datasets, which are derived from General Circulation Model (GCM) runs under the Coupled Model Intercomparison Project Phase 6 (CMIP6), is compared with the observed precipitation, maximum, and minimum temperature datasets obtained from the Indian Meteorological Department (IMD). These datasets have a spatial resolution of (0.25° × 0.25°) and available from 1970 to 2014. The methodology adopted in this study uses advanced statistical techniques to evaluate the performance of the CMIP6 models. The study incorporates Multicriterion Decision-Making Techniques (MCDM) and Group Decision-Making (GDM) methodologies within the Reliable-Ensemble Averaging (REA) framework. MIROC-ES2L, GISS-E2-1-G and TaiESM1 are the top ranked models for precipitation data. Whereas, BCC-CSM2-MR, ACCESS-ESM1-5 and GFDL-CM4_gr2 obtained as most suitable RCMs for maximum temperature data. For minimum temperature data, MIROC-ES2L, KIOST-ESM and MIROC6 obtained as top ranked CMIP6 models. The projected climate variables, including precipitation, maximum temperature and minimum temperatures, under three distinct Shared Socioeconomic Pathways (SSP) scenarios: SSP 245, SSP 370 and SSP 585 extending up to the year 2100. The spatio-temporal analysis encompasses key climate parameters, identifying trends, variations, and potential anomalies in the Munneru River Basin. This study contributes to the broader context of regional climate modelling research and enhances our understanding of the Munneru River Basin's climate dynamics. The research findings presented in this study aim to understand the methodological advancements in regional climate modelling, performance assessments of CMIP6 models and the application of CMIP6 models in regional process studies.

How to cite: Keesara, V. R., Buri, E. S., and Kotapati Narayanaswamy, L.: Unveiling the Subjectivity in Ranking of NEX-GDDP-CMIP6 Climate Models Over Munneru River Basin, India, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7159, https://doi.org/10.5194/egusphere-egu24-7159, 2024.

Posters on site: Wed, 17 Apr, 10:45–12:30 | Hall X5

Display time: Wed, 17 Apr 08:30–Wed, 17 Apr 12:30
Chairpersons: Lina Teckentrup, Thomas Aubry, Alexander J. Winkler
X5.104
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EGU24-597
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ECS
Evaluation and Projection of Diurnal Temperature Range in Maize Cultivation Areas in China Based on CMIP6 Models
(withdrawn)
Wenqiang Xie and Xiaodong Yan
X5.105
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EGU24-1411
Holger Pohlmann and Wolfgang A. Müller

The origin of multi-decadal climate variability in the North Atlantic is under debate. The variability could be caused by oceanic internal variability or by external anthropogenic or natural forcing. We have produced a set of single-forcing historical simulations with the Max Planck Institute - Earth System Model (MPI-ESM) in low resolution (LR). The historical-like simulations consists of 30 ensemble members and the external forcing is from the Coupled Model Intercomparison phase 6 (CMIP6). Each set of simulation is forced by either only greenhouse-gases, total ozone, solar insolation, anthropogenic aerosols or volcanic aerosols. We present first results of our attribution of the climate signals in the North Atlantic region to the different single forcings.

How to cite: Pohlmann, H. and Müller, W. A.: The North Atlantic climate variability in single-forcing large ensemble simulations with MPI-ESM-LR, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1411, https://doi.org/10.5194/egusphere-egu24-1411, 2024.

X5.106
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EGU24-4371
Hongwei Li

Untangling the impact of anthropogenic forcing on drought is particularly essential for climate change mitigation. Previous studies have indicated that anthropogenic forcing exacerbates drought, raising concerns about global drought evolution, yet little is known about the impact of anthropogenic forcing on drought evolution through anthropogenic greenhouse gases (GHGs) and aerosol (AER). We integrated standardized precipitation evapotranspiration index (SPEI) data under different experiments to study drought development with Coupled Model Intercomparison Project Phase 6 (CMIP6) global climate models (GCMs). Subsequently, we conducted sensitivity analyses to quantify the changes in drought sensitivity to anthropogenic greenhouse gas (DSG) and aerosol (DSA) from 1900 to 2014. Our findings reveal different effects of AER and GHGs on drought trends during three periods. Specifically, GHGs slightly increased global drought severity in the early 20th century. Conversely, from 1956 to 1982, the drought-mitigating effects of AER surpassed the drought-enhancing effects of GHGs, and the global was humidified. Then, from 1982 to 2014, the trends of increasing DSG and decreasing DSA suggest that an important global shift is taking place. GHG re-emerged as the primary driver, thus leading to increased drought severity. Taken together, these findings elucidate how anthropogenic forcing impacts global drought severity through drought-enhancing effects of GHGs and drought-mitigating effects of AER, which provides new insights into understanding the risk of anthropogenic impacts on global drought.

How to cite: Li, H.: Anthropogenic forcing inconsistently exacerbates global drought, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4371, https://doi.org/10.5194/egusphere-egu24-4371, 2024.

X5.107
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EGU24-1855
Tian Tian and Shuting Yang

The IPCC’s 2021 assessment suggested that substantial emissions reduction and limiting global temperature rise to well below 2.0°C could prevent the complete loss of Arctic sea ice in this century. However, these assessments come with large uncertainties. Recent research projects a summer ice-free Arctic by the 2050s even under a low emission scenario by constraining future sea ice area with satellite-derived sea ice concentration (SIC) since 1979. Notably, the climate models in these assessments commonly underestimate the accelerated Arctic warming and the pace of sea ice melting, particularly over the last two decades. Moreover, recent studies indicate that in a warming climate, the thinning of sea ice and snow over sea ice may intensify surface warming, thereby accelerating the melting.

In this study, we leverage the increasing availability of observations and recent reanalysis data for Arctic-wide sea ice to investigate the link between changes in sea ice thickness (SIT), sea ice concentration (SIC), and Arctic warming. We employ these datasets to evaluate biases in historical periods and uncertainties in future scenarios within the CMIP6 multi-model ensemble for SIT and SIC. We further investigate the relationship between the thinning of sea ice and the snow layer on sea ice and surface temperature changes on a basin or regional scale. The findings are then used to constrain projected Arctic changes. Our study aims to gain some insights into the impact of model biases in the Arctic on projected climate projections, crucial for decision-making in a changing climate.

How to cite: Tian, T. and Yang, S.: The impact of sea ice thickness biases on the projected summer sea ice-free Arctic in CMIP6 ensemble experiments , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1855, https://doi.org/10.5194/egusphere-egu24-1855, 2024.

X5.108
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EGU24-2368
Guzailinuer Yasen, Qi Liu, and Weidong Guo

Day-to-day (DTD) temperature variability is an important characteristic of air temperature, which significantly affects human health and ecosystems. However, the changing trend of DTD under recent climate warming and its causes need to be further explored. Here, Using daily temperature observations, we examine the spatial heterogeneity of DTD and its long-term trends in the United States (US) over the last 26 years and find a significant increase in winter DTD in the central and eastern United States during the study period. In addition, by using the observed data and The Coupled Model Intercomparison Project Phase 6 (CMIP6) multi-model simulations, we further demonstrate that cleaner air leads to significant changes in DTD. Specifically, by comparing the contributions of greenhouse gases, anthropogenic aerosols, natural forcing, and total forcing, it is concluded that the reduction of anthropogenic aerosol concentrations in the United States after 1997 led to enhanced DTD . Of the 32 members used in this study, nearly 60% show positive trends in the DTD index during 1997–2022 in the historical simulations. The trends for the ensemble members range from -0.06 to 0.08 °C ·decade-1  with an ensemble mean of 0.008°C· decade-1 which encompasses the trend derived from the observations (0.08 °C·decade-1 ) . The historical simulations reasonably capture the observed DTD trends except with a weaker magnitude. The increasing trend is also evident in the anthropogenic-aerosol-only historical simulations, where about 56% of the 32members show positive trends, with an ensemble mean of 0.01 °C·decade-1. While contrary to the results of the anthropogenic-aerosol-only historical simulations (hist-aer), there was negative trends In the natural-only historical (hist-nat) and the greenhouse-gas-only historical (hist-GHG) simulations, only about 44% and 47% of the members showed the positive trends, The trend for the ensemble mean is -0.013/-0.015°C·decade-1 for the hist-nat / hist-GHG simulations. Therefore, the positive trend of the DTD index can be attributed to the anthropogenic aerosols , while the negative trend of which can be attributed to the natural forcing and greenhouse gas forcing. The observed DTD enhancement over 1997-2022 is dominated by the effect of anthropogenic aerosols, while natural forcing and GHGS partially counteract the effect of anthropogenic aerosols. That is, Based on climate modeling experiments, we demonstrate that the reduced aerosol emissions in US can contribute to the enhanced trend of DTD in USA.

How to cite: Yasen, G., Liu, Q., and Guo, W.: Changes in Day-to-day temperature variability in United States driven by cleaner air, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2368, https://doi.org/10.5194/egusphere-egu24-2368, 2024.

X5.109
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EGU24-6364
Helene Hewitt and John Dunne and the CMIP Panel and IPO

Over four decades, CMIP has driven massive improvements in the modelled representation of the Earth system, whilst also seeing huge growth in its scope and complexity. In its most recent phase, CMIP6, a broad spectrum of questions continues to be answered across twenty-four individual model intercomparison projects (MIPs). This science improves process understanding and assesses the climate’s response to forcing, systematic biases, variability, and predictability in line with WCRP Scientific Objectives. CMIP and its associated data infrastructure have become essential to the Intergovernmental Panel on Climate Change (IPCC) and other international and national climate assessments, increasingly including the downstream mitigation, impacts, and adaptation communities.

However, despite the invaluable science produced from CMIP6 data, many challenges were still faced by the model data providers, the data delivery infrastructure, and users, which need to be addressed moving forwards. A specific challenge in CMIP6 was the burden placed on the modelling centres, in part due to the large number of requested experiments and delays in the preparation of the CMIP6 forcing datasets and climate data request.

The CMIP structure is evolving into a continuous, community-based climate modelling programme to tackle key and timely climate science questions and facilitate delivery of relevant multi-model simulations. This activity will be supported by the design of experimental protocols, an infrastructure that supports data publication and access, and quasi-operational extension of historical forcings.  A subset of experiments is proposed to be fast-tracked to deliver climate information for national and international climate assessments and informing policy and decision making. The CMIP governing panels are coordinating community activities to reduce the burden placed on modelling centres, continue to enhance novel and innovative scientific activities, and maximise computational efficiencies, whilst continuing to deliver impactful climate model data.

How to cite: Hewitt, H. and Dunne, J. and the CMIP Panel and IPO: Evolving The Coupled Model Intercomparison Project (CMIP) To Better Support The Climate Community And Future Climate Assessments, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6364, https://doi.org/10.5194/egusphere-egu24-6364, 2024.

X5.110
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EGU24-7881
Wenhao Jiang and Huopo Chen

The influence of anthropogenic (ANT) activity and the other external factors on extreme temperature changes over the mid–high latitudes of Asia are analysed using the different forcing simulations from the Coupled Model Intercomparison Project Phase 6 (CMIP6) models. The optimal fingerprinting technique and the probability ratio (PR) are employed to detect and quantify the influences of the external forcings on extreme temperature changes, which include annual maximum daily maximum temperature (TXx), annual minimum daily minimum temperature (TNn). Results indicate that TXx and TNn have increased from 1979 to 2014, and the simulations from historical (anthropogenic plus natural; ALL), greenhouse gas (GHG), and anthropogenic (ANT) experiments reasonably reproduce the spatiotemporal characteristics of extreme temperatures. Based on the optimal fingerprinting method, the impact of ANT forcing, in which GHG forcing is critical, can be detected in the changes of warm extremes and cold extremes. ANT and NAT forcings are separately detectable for warm extremes. GHG forcing can be separated from other ANT forcings for cold extremes but not warm extremes. Furthermore, the analysis applying the PR method shows that the probability of observed warm extremes that occur once in 20 years over the mid–high latitudes of Asia has risen by approximately three times owing to the anthropogenic influence, whereas the cold extremes became once in 50 years. Briefly, the increased anthropogenic activity has exacerbated the warm extremes and soothed the cold extremes over the mid–high latitudes of Asia during the past decades.

How to cite: Jiang, W. and Chen, H.: Anthropogenic influence on extreme temperature changes over the mid–high latitudes of Asia, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7881, https://doi.org/10.5194/egusphere-egu24-7881, 2024.

X5.111
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EGU24-8659
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ECS
Rafaila Nikola Mourgela, Eirini Boleti, Konstantinos Seiradakis, Klaus Wyser, Phillipe Le Sager, Angelos Gkouvousis, and Apostolos Voulgarakis

The occurrence of more frequent and extensive wildfires is a widely discussed potential consequence of climate change, stemming from a vicious cycle of cause and effect in which wildfires are taking part. Global and regional wildfire patterns and changes are driven by climate-related factors such as land cover, heat waves, and rainfall patterns. Wildfires can, in turn, cause climate perturbations through the emissions of greenhouse gases and aerosols, and through the alteration of landscapes. For these reasons, understanding wildfires and their interactions with the Earth’s atmosphere is crucial for assessing a potentially important climate feedback.

The current study focuses on the interconnection between wildfires and the atmosphere, and more precisely on the radiative effect of wildfire emissions on a global scale. To achieve this, simulations using the EC-Earth Earth System Model (ESM) were employed. More specifically, a 30-year atmosphere-only (fixed-SST) control simulation was performed for the pre-industrial period, and repeated with the wildfire aerosol emissions set to present-day values. Using the output of these simulations, we estimate the global effective radiative forcing (ERF) of wildfire-emitted aerosols from pre-industrial times to the present day. We also identify which regions experience stronger forcing from wildfire emissions, and separate the role of black carbon and organic carbon in driving this forcing. Finally, we identify mechanisms that lead to fast atmospheric adjustments following wildfire emissions, including changes in temperatures, humidity, precipitation, and clouds. This analysis contributes to the better understanding of the historical evolution of radiative forcing and the role of wildfires in the climate system.

 

How to cite: Mourgela, R. N., Boleti, E., Seiradakis, K., Wyser, K., Le Sager, P., Gkouvousis, A., and Voulgarakis, A.: Studying the pre-industrial to present-day radiative forcing from wildfire aerosols using EC-Earth, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8659, https://doi.org/10.5194/egusphere-egu24-8659, 2024.

X5.112
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EGU24-8690
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ECS
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Estela Monteiro and Nadine Mengis

Anthropogenic activities have disrupted the energy balance of the planet since preindustrial era through, among other drivers, the emission of various greenhouse gases and aerosols. The largest uncertainty to current climate forcing and future projections relates to the effect of aerosols. Their different impacts on the planet’s radiative balance, that is, with direct radiative and indirect cloud interaction forcing, need to be considered accurately in simple policy-informing climate models. Especially in the context of high ambition mitigation scenarios, variability in the future development of spatiotemporal aerosol forcing will have a relatively large impact on climate projections. Accordingly, an accurate inclusion of the relevant processes onto the modeling scheme, such as the spatiotemporal level of detail chosen when accounting for aerosol forcing in simple(r) climate models must be carefully considered.

Here we explore the impact of different aerosols implementation schemes in an intermediate complexity Earth system model configuration with an energy moisture balance model (UVic ESCM, version 2.10). While the global mean forcing is the same for all scenarios, we vary spatial and temporal resolution of optical depth maps or implement aerosol forcing as direct radiative forcing to the Earth system. These schemes are applied to relevant ambitious mitigation scenarios aiming at temperature stabilization, which will become especially relevant in the upcoming CMIP exercises. Using a newly developed assessment framework, we will provide insights into the impacts of this model implementation choice onto future temperature development, the carbon cycle and heat uptake processes. Ultimately these insights aim to improve, constrain and design better scenario simulations that are both applicable and relevant to the scientific and decision-making communities.

How to cite: Monteiro, E. and Mengis, N.: How your aerosol implementation choices affect your model’s climate system response, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8690, https://doi.org/10.5194/egusphere-egu24-8690, 2024.

X5.113
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EGU24-9312
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ECS
Thomas Aubry, Anja Schmidt, Mahesh Kovilakam, Matthew Toohey, and Michael Sigl

Explosive volcanic eruptions injecting gases and aerosols into the stratosphere are a key natural driver of climate variability at annual to centennial timescales. They are thus one of the forcings considered by the Coupled Model Intercomparison Project (CMIP) Climate Forcings Task Team, in charge of identifying and implementing the next generation forcings for current and future generations of Earth System models. This presentation will provide an overview of ongoing work to produce volcanic forcing datasets for phase 7 of CMIP (CMIP7).

The datasets we produce will cover the period from 1750 to 2022 at version 1 to meet to the need of modelling groups who might run extended historical simulations starting in 1750 instead of 1850. We are producing one volcanic stratospheric sulfur emission dataset catering for the needs of models which have a prognostic interactive stratospheric aerosol scheme, as well as a stratospheric sulfate aerosol optical property dataset required by models that cannot interactively simulate stratospheric sufate aerosols. For the satellite era (from 1979 onwards), sulfur emissions and sufate aerosol optical properties are based on NASA’s MSVOLSO2L4 and GloSSAC datasets, respectively. For the pre-satellite era (1750-1978), the emission dataset is based on ice-core datasets complemented by the geological record, whereas the aerosol optical property dataset is directly derived from emissions using the latest version of the Easy Volcanic Aerosol (EVA) model. This ensures methodological consistency between our emission and optical property datasets, further enhanced by the fact that EVA is calibrated using the same datasets we use for the satellite era. Our choice of methods aims to maximize consistency with methodologies used in individual model intercomparison projects (e.g. PMIP and VolMIP). A major focus of our task team is to produce well-documented datasets, which includes extensive meta-data and flags, detailed documentation, and provision of open-access scripts used to create the datasets, which should facilitate future development and operationalization by the community. We also discuss the most critical challenges for providing accurate volcanic forcing datasets, including the under-recording of small-to-moderate magnitude eruptions before the satellite era, and the Hunga Tonga-Hunga Ha'apai 2022 eruptions, which injected relatively small amounts of sulfur, but 150 Tg of water into the stratosphere.

How to cite: Aubry, T., Schmidt, A., Kovilakam, M., Toohey, M., and Sigl, M.: Historical volcanic sulfur emissions and stratospheric sulfate aerosol optical properties for CMIP7, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9312, https://doi.org/10.5194/egusphere-egu24-9312, 2024.

X5.114
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EGU24-11255
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ECS
|
Charlotte Lange and Johannes Quaas

So-called “radiative" or "rapid" adjustments describe the surface-temperature-independent response of the climate state to an instantaneous radiative forcing. However, the term “rapid” can be misleading since various processes are considered adjustments, which appear on timescales of hours (e.g. aerosol-cloud-interactions) to month (e.g. stratospheric temperature change) or even longer timescales (e.g. adjustments of biosphere and cryosphere). On time scales of months and longer, differentiating between adjustments and feedbacks becomes increasingly difficult. Depending on the scientific method the definition of “adjustments” and which processes are considered can vary. Nevertheless, a good understanding of these processes is crucial for improving climate models and advance our general understanding of how the Earth climate system reacts to a forcing.

The abrupt-solm4p experiment from CFMIP (Cloud Forcing Model Intercomparison Project) from CMIP6 (Coupled Model Intercomparison Project phase 6) simulates an instantaneous reduction of the solar constant by 4% branching from a pre-industrial control run on 01/01/1850. We analysed changes in geographical distribution as well as global mean temporal development of various climate variables (e.g. surface and atmospheric temperature, precipitation, humidity), different cloud properties (e.g. cloud cover, column integrated liquid and ice water), as well as radiative fluxes at top of atmosphere and the cloud radiative effect. The different variables were evaluated on timescales of hours, days, months and up to 150 years after the onset of forcing, in order to learn more about the timing of different adjustment processes. Four different models participated in the abrupt-solm4p experiment. Their outputs were compared and possible source of differences discussed. During the first hours all models unanimously simulate decreasing surface and atmospheric temperature, especially strong in the Antarctica, which experiences 24hr irradiation at the onset of forcing. In the beginning, the stratospheric cooling is strongest. The moderate cooling of the troposphere leads to increased condensation and thereby increased cloud cover, even in Northern latitudes, that do not directly experience the forcing, and strengthened precipitation in the tropics. 

In a next step, we plan to compare the results from abrupt-solm4p (CFMIP) to simulations of a homogeneous stratospheric sulfate scattering-layer and to the volc-pinatubo-full-experiment (VolMIP). We expect some similarities between the simulated adjustments in these experiments, because in all three cases, incoming solar radiation is reduced in the troposphere and at surface level. However, more realistic experiments, like the volc-pinatubo experiment are expected to show more complex adjustments and the comparison to more simplified experiments like abrupt-solm4p might provide valuable insights to adjustment processes after volcanic eruptions.

How to cite: Lange, C. and Quaas, J.: Radiative adjustments after a 4%-reduction of the solar constant, based on data from the abrupt-solm4p experiment (CFMIP from CMIP6), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11255, https://doi.org/10.5194/egusphere-egu24-11255, 2024.

X5.115
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EGU24-12768
Andrea Burke, Herman Fuglestvedt, Liz Thomas, Lauren Marshall, and Kirstin Krüger

Records of the volcanic forcing of climate prior to the satellite era depend on scaling the flux of sulfate deposited on polar ice sheets­ using a ‘transfer function’, a number calibrated based on radioactivity in Greenland from thermonuclear testing as well as Antarctic sulfate flux records from the 1991 Pinatubo eruption (e.g. Gao et al., 2007). For high latitude eruptions, this transfer function is based solely on model simulations of sulfate flux to Greenland from the Icelandic Laki eruption in 1783 and the Alaskan Katmai/Novarupta eruption in 1912 (Gao et al., 2007).  Since the initial determination of this transfer function, the number of ice cores containing sulfate from the Pinatubo eruption has increased eight-fold, and sulfur isotope measurements at high resolution over sulfate peaks in the ice has allowed for discrimination between stratospheric sulfate and sulfate transported at lower levels in the atmosphere from different sources (e.g. Burke et al., 2023). Here we revisit the estimation of the transfer function in light of these new data-based constraints from eruptions in the 20th century, and we reassess the uncertainty associated with the application of a single transfer function across volcanic eruptions in the past.

 

Gao, C., Oman, L., Robock, A. and Stenchikov, G.L., 2007. Atmospheric volcanic loading derived from bipolar ice cores: Accounting for the spatial distribution of volcanic deposition. Journal of Geophysical Research: Atmospheres112(D9).

Burke, A., Innes, H.M., Crick, L., Anchukaitis, K.J., Byrne, M.P., Hutchison, W., McConnell, J.R., Moore, K.A., Rae, J.W., Sigl, M. and Wilson, R., 2023. High sensitivity of summer temperatures to stratospheric sulfur loading from volcanoes in the Northern Hemisphere. Proceedings of the National Academy of Sciences120(47), p.e2221810120.

How to cite: Burke, A., Fuglestvedt, H., Thomas, L., Marshall, L., and Krüger, K.: Revisiting the ‘transfer function’ of stratospheric sulfur loading from volcanic sulfate deposited on polar ice sheets, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12768, https://doi.org/10.5194/egusphere-egu24-12768, 2024.

X5.116
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EGU24-2173
Ali Khosravi, Zahra Ghorbani, and Yasser Maghsoudi

The southeastern U.S. is frequently impacted by severe thunderstorms, which are known for producing damaging winds, hail, and tornadoes. The National Oceanic and Atmospheric Administration (NOAA) reports that this region experiences the highest frequency of thunderstorms in the country. In recent decades, these storms have shown a trend of increasing both in frequency and intensity. Moreover, the southeastern states are susceptible to hurricanes and tropical storms, which have been intensifying due to warmer ocean temperatures. The escalating severity of these weather events poses significant risks to public safety, infrastructure, and the economy in the southeast. Our proposed study uses advanced satellite technology, specifically Interferometric Synthetic Aperture Radar (InSAR), to map storm-induced flooding and damage from October 2019 to August 2021. This period includes Hurricane Sally, which caused significant destruction in Alabama on September 16, 2020. By analyzing satellite images taken before and after hurricanes, we aim to identify affected areas and assess infrastructural damage. The study employs Sentinel-1 InSAR data processed by the COMET-LiCSAR system and the LiCSBAS processing package, generating surface deformation time series. We also integrate optical images to examine soil moisture and climate changes, correlating them with displacement and radar coherence data from SAR images. This research will classify and discuss the impact of hurricanes on infrastructure and roadways, providing critical information to prioritize emergency response and inform repair and reconstruction planning.

How to cite: Khosravi, A., Ghorbani, Z., and Maghsoudi, Y.: Monitoring Severe Storm Impacts and Climate Trends in the Southeastern US using Satellite-Based Proxy Indicators: A Case Study of Hurricane Sally, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2173, https://doi.org/10.5194/egusphere-egu24-2173, 2024.

X5.117
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EGU24-14986
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ECS
Robin Guillaume-Castel, Benoit Meyssignac, and Rémy Roca

The pattern of surface warming plays a significant role in determining the Earth's response to radiative forcing. Indeed, the Earth's radiative response is intricately linked to the intensity of climate feedbacks, which, in turn, are influenced by the regional distribution of surface warming. Distinct patterns of surface warming lead to divergent equilibrium and transient responses to identical forcing, emphasizing the need to analyse this pattern effect to understand the climate responses to external forcing.

While existing studies have primarily focused on assessing the influence of warming patterns on long-term warming, such as equilibrium climate sensitivity or committed warming, the role of warming patterns in shaping the transient trajectory of global warming remains poorly understood. In this study, we introduce a novel analytical method to quantify the importance of evolving warming patterns on transient global warming.

Our approach involves developing a multivariate global energy budget, which provides a unified framework for interpreting the sensitivity of the radiative response of the Earth to the warming pattern. This framework explicitly separates the radiative response caused by the global mean temperature increase, from the additional response induced by changing temperature patterns.

Using this new energy balance model, we assess the relative contributions of the direct radiative forcing and changing temperature patterns to the global mean temperature change in linearly increasing forcing experiments (1pctCO2) from nine CMIP6 models. We show that the pattern effect consistently dampens global warming in the first 100 years of all simulations studied. Specifically, we quantify that the transient climate response, reached after 70 years of simulations, would be 0.4±0.2K higher (equivalent to a 20±15% increase) if the warming was uniformly distributed (i.e. in the absence of changing warming patterns).

Furthermore, our study demonstrates that distinct models exhibit significantly divergent transient global warming patterns solely due to variations in the pattern effect. Overall, our results highlight the importance of changing warming patterns, specifically through the pattern effect, in influencing decadal-scale transient warming. These findings notably support recent suggestions to incorporate warming pattern uncertainties in future climate projections.

How to cite: Guillaume-Castel, R., Meyssignac, B., and Roca, R.: Assessing the Impact of Changing Warming Patterns on Transient Global Warming: A Multivariate Energy Budget Approach, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14986, https://doi.org/10.5194/egusphere-egu24-14986, 2024.

X5.118
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EGU24-17153
Chu-Yong Chung, Young-Hwa Byun, Hyun Min Sung, Jin-Uk Kim, and Sungbo Shim

The National Institute of Meteorological Sciences in the Korea Meteorological Administration (NIMS/KMA) has been actively contributing to the CMIP program since CMIP3. NIMS participated in CMIP6 through a collaborative effort with the UK Met Office Hadley Centre as part of a mutually agreed scientific plan. Within this collaboration, NIMS utilized the Earth System Model developed by the UK Met Office (UKESM) to generate future climate change scenarios for four distinct Shared Socio-economic Pathways (SSPs). NIMS also employed the KMA Advanced Community Earth (K-ACE) model, a modified version of HadGEM2-AO developed through in-house research, to analyze global climate projections. Five different regional climate models were used for the regional climate simulations: HadGEM3-RA, RegCM4, CCLM, GRIMs, and WRF, organized under the CORDEX-EA (East Asia) program. Furthermore, for the South Korean area, NIMS produced 1km resolution climate change scenario data using the statistical downscaling technique, the Parameter-elevation Relationships on Independent Slopes Model (PRISM)-based Dynamic downscaling Error correction (PRIDE). These projections played a pivotal role in contributing to the preparation of the Sixth Assessment Report (AR6) by the Intergovernmental Panel on Climate Change (IPCC) and provided crucial foundational data for national climate change adaptation efforts.

Currently, NIMS has initiated preparations for CMIP7 participation. In this program, K-ACE will be employed for producing global climate projections, having undergone improvements such as coupling with an ocean-biogeochemistry model, TOPAZ, and modifications to the cloud-aerosol process, among other enhancements. NIMS plans to use a reduced number of RCMs compared to the CMIP6 phase but intends to increase the ensemble members by combining physical processes. Currently under consideration as RCM candidates are WRF and WRF-ROMS. To comprehend the impact of climate change on local-scale heavy rain, a Convection Permitting Model (CPM) with a spatial resolution of about 2.5km can be employed. For the South Korean region, our objective is to produce more high-resolution, detailed climate scenarios through sensitivity experiments and reliability verification studies.

This presentation aims to introduce KMA's Earth System Models, aligning with recent trends and developments outlined in CMIP7, and presenting the overall plans for the generation and utilization of global-regional-local climate projections in line with CMIP7.

How to cite: Chung, C.-Y., Byun, Y.-H., Sung, H. M., Kim, J.-U., and Shim, S.: NIMS/KMA Plans for Climate Change Projection Production and Utilization on CMIP7, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17153, https://doi.org/10.5194/egusphere-egu24-17153, 2024.

X5.119
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EGU24-20011
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ECS
Attribution analysis of streamflow changes based on large-scale hydrological modeling with uncertainties
(withdrawn)
Yu Zhang
X5.120
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EGU24-15167
Observational constraints for long-term climate forcing datasets: What do we know, and what do we need to know 
(withdrawn)
Claire Macintosh