Causes of growing middle-to-upper tropospheric ozone over the northwest Pacific region by X. Ma, X. Ma, J. Huang, J. Huang, M. I. Hegglin, M. I. Hegglin, P. Jöckel, T. Zhao

“…This study aims to address these gaps by analyzing O<span class="inline-formula">₃</span> soundings at four sites along the northwestern Pacific coastal region over the past 3 decades and by assessing their consistency with an atmospheric chemistry–climate model simulation. Utilizing the European Centre for Medium-Range Weather Forecasts (ECMWF) Hamburg (ECHAM)/Modular Earth Submodel System (MESSy) Atmospheric Chemistry (EMAC) nudged simulations, it is demonstrated that trends between model and ozonesonde measurements are overall consistent, thereby gaining confidence in the model's ability to simulate O<span class="inline-formula">₃</span> trends and confirming the utility of potentially imperfect observational data. …”
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Impact of mineral dust on the global nitrate aerosol direct and indirect radiative effect by A. Milousis, K. Klingmüller, A. P. Tsimpidi, J. F. Kok, M. Kanakidou, M. Kanakidou, M. Kanakidou, A. Nenes, A. Nenes, V. A. Karydis

“…For this purpose, multiyear simulations nudged towards the observed atmospheric circulation were performed with the global atmospheric chemistry and climate model EMAC, while the thermodynamics of the interactions between inorganic aerosols and mineral dust were simulated with the thermodynamic equilibrium model ISORROPIA-lite. …”
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Bias-corrected high-resolution temperature and precipitation projections for Canada by Hebatallah M. Abdelmoaty, Chandra Rupa Rajulapati, Sofia D. Nerantzaki, Simon Michael Papalexiou

“…The SPQM-CMIP6-CAN database encompasses 693 simulations derived from 34 diverse climate models for precipitation. Similarly, for temperature projections, our database comprises 581 simulations from 27 climate models. …”
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Epistemic Uncertainties in Climate Predictions: A Challenge for Practical Decision Making by Rafaela Hillerbrand

“…Most scientists agree that, at least for the time being, unquantified uncertainties are inevitably connected to predictions of climate models. Uncertainties, however, do not justify political inaction. …”
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Emergent constraints on global soil moisture projections under climate change by Lei Yao, Guoyong Leng, Linfei Yu, Hongyi Li, Qiuhong Tang, Andre Python, Jim W. Hall, Xiaoyong Liao, Ji Li, Jiali Qiu, Johannes Quaas, Shengzhi Huang, Yin Jin, Jakob Zscheischler, Jian Peng

“…Such projections are mostly based on climate models, which show large uncertainty (i.e., inter-model spread) partly due to inadequate observational constraint. …”
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Emergence of the North Pacific heat storage pattern delayed by decadal wind-driven redistribution by Jing Duan, Yuanlong Li, Yilong Lyu, Zhao Jing, Fan Wang

“…Abstract Storage of anthropogenic heat in the oceans is spatially inhomogeneous, impacting regional climates and human societies. Climate models project enhanced heat storage in the mid-latitude North Pacific (MNP) and much weaker storage in the tropical Pacific. …”
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Unsupervised Classification of Global Temperature Profiles Based on Gaussian Mixture Models by Xiaotian Ye, Weifeng Zhou

“…The results highlight the significant roles of ocean currents, climatic phenomena, and ecological factors in temperature distribution, providing insights for ocean circulation studies, climate modeling, and marine biodiversity conservation. …”
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Evaluation of biases in mid-to-high-latitude surface snowfall and cloud phase in ERA5 and CMIP6 using satellite observations by F. Hellmuth, T. Carlsen, A. S. Daloz, R. O. David, H. Che, T. Storelvmo

“…Understanding the origin(s) of the biases identified here is, therefore, crucial for improving the overall reliability of climate models.</p>…”
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Technical note: Recommendations for diagnosing cloud feedbacks and rapid cloud adjustments using cloud radiative kernels by M. D. Zelinka, L.-W. Chao, T. A. Myers, T. A. Myers, Y. Qin, S. A. Klein

“…Here, we provide a methodology for properly diagnosing the impact of changing obscuration on cloud feedbacks and adjustments and quantify these effects across climate models. Averaged globally and across global climate models, properly accounting for obscuration leads to weaker positive feedbacks from lower-level clouds and stronger positive feedbacks from upper-level clouds while simultaneously removing a mostly artificial anti-correlation between them. …”
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What Will the European Climate Look Like in the Future? A Climate Analog Analysis Accounting for Dependencies Between Variables by B. Bulut, M. Vrac, N. deNoblet‐Ducoudré

“…The agreement between climate models in the location and degree of similarity of the best analogs decreases as warming intensifies and/or as time approaches the end of the century. …”
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The surface tension and cloud condensation nuclei (CCN) activation of sea spray aerosol particles by J. Kleinheins, N. Shardt, U. Lohmann, C. Marcolli

“…For a quaternary model system of SSA particles, it is shown that high content of hydrophobic organic material (i.e. strong surfactants) in Aitken mode particles does not necessarily prevent good CCN activation but rather facilitates effective activation via surface tension lowering. Since common climate models use parameterizations that are based on classical Köhler theory, these results suggest that the CCN activity of small SSA particles might be underestimated in climate models.…”
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Future Changes in Winter‐Time Extratropical Cyclones Over South Africa From CORDEX‐CORE Simulations by Sandeep Chinta, C. Adam Schlosser, Xiang Gao, Kevin Hodges

“…We utilized three regional climate models, each driven by three different global climate models that simulate both the current climate and a future climate experiencing strong human‐induced warming. …”
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Design, evaluation, and future projections of the NARCliM2.0 CORDEX-CMIP6 Australasia regional climate ensemble by G. Di Virgilio, G. Di Virgilio, J. P. Evans, J. P. Evans, F. Ji, F. Ji, E. Tam, J. Kala, J. Andrys, C. Thomas, D. Choudhury, C. Rocha, S. White, Y. Li, M. El Rafei, R. Goyal, M. L. Riley, J. Lingala

“…<p>NARCliM2.0 (New South Wales and Australian Regional Climate Modelling) comprises two Weather Research and Forecasting (WRF) regional climate models (RCMs) which downscale five Coupled Model Intercomparison Project Phase 6 (CMIP6) global climate models contributing to the Coordinated Regional Downscaling Experiment (CORDEX) over Australasia at 20 km resolution and southeast Australia at 4 km convection-permitting resolution. …”
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Attributing heatwave-related mortality to climate change: a case study of the 2009 Victorian heatwave in Australia by Sarah E Perkins-Kirkpatrick, Linda Selvey, Philipp Aglas-Leitner, Nina Lansbury, Samuel Hundessa, Dáithí Stone, Kristie L Ebi, Nicholas John Osborne

“…Despite the small total number of attributable deaths as per the epidemiological model, six out of eight climate models predicted a statistically significant anthropogenic influence, indicating that climate change increased the heatwave-related mortality impact of this event. …”
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Virtual Laboratories: Mesocosms and Gameworlds by Dustin Breitling

“…Notably, digital gameworlds have expanded their scope beyond simple ecological simulations, incorporating intricate climate models alongside social, political, and historical elements to craft nuanced, evolving virtual environments that attempt to reflect the fragile interconnection of systems on a planetary scale.…”
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Modeling of historical and future changes in temperature and precipitation in the Panj River Basin in Central Asia under the CMIP5 RCP and CMIP6 SSP scenarios by Aminjon Gulakhmadov, Xi Chen, Nekruz Gulahmadov, Muhammmad Rizwan, Manuchekhr Gulakhmadov, Muhammad Umar Nadeem, Moldir Rakhimova, Tie Liu

“…Abstract This study examines the complexities of climate modeling, specifically in the Panj River Basin (PRB) in Central Asia, to evaluate the transition from CMIP5 to CMIP6 models. …”
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Assessment of rainfed wheat productivity in a changing climate in Irbid, Jordan using statistical downscaling and Random Forest Regression prediction under RCP4.5 &amp; 8.5 pathway... by Tasnim Dheif Allah Althalaj, Fayha Muhammed Al-Shibli, Amani Abdullah Alassaf

“…Cumulative Distribution Function and Probability Density Function Curves were plotted to describe the changes over decades based on climate models. Future wheat yields were predicted using the Random Forest Regression model. …”
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Future climate or land use? Attribution of changes in surface runoff in a typical Sahelian landscape by Yonaba, Roland, Mounirou, Lawani Adjadi, Tazen, Fowé, Koïta, Mahamadou, Biaou, Angelbert Chabi, Zouré, Cheick Oumar, Queloz, Pierre, Karambiri, Harouna, Yacouba, Hamma

“…The study uses a combination of land use maps (for current and future periods) and a bias-corrected ensemble of 9 CMIP6 climate models, under two warming scenarios. An increase in rainfall (13.7% to 18.8%) is projected, which is the major contributor to the increase in surface runoff (24.2% to 34.3%). …”
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Using Enstrophy-Based Diagnostics in an Ensemble for Two Blocking Events by Andrew D. Jensen, Anthony R. Lupo

“…However, none of these studies has explored the use of the enstrophy-based diagnostics in weather or climate models with higher horizontal resolution. In this paper, the enstrophy-based diagnostics are used to analyze two blocking events, using data from the ERA-Interim reanalysis data set (0.75° × 0.75°) and also the Global Ensemble Forecast System (GEFS) (1° × 1°). …”
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Machine learning suggests climate and seasonal definitions should change under global warming by Milton Speer, Lance Leslie

“…The poleward contraction of mid-latitude westerly winds is a readily identifiable contributor. Improvements in climate models are expected to more accurately predict future phases of climate drivers. …”
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