Abstract The World Weather Research Programme (WWRP)/World Climate Research Programme (WCRP) Subseasonal to Seasonal (S2S) Prediction project was launched in 2013 with the primary goals of improving forecast skill and understanding sources of predictability on the subseasonal time scale (from 2 weeks to a season) around the globe. Particular emphasis was placed on high-impact weather events, on developing coordination among operational centers, and on promoting the use of subseasonal forecasts by the application communities. This 10-yr project ended in December 2023. A key accomplishment was the establishment of a database of subseasonal forecasts, called the S2S database. This database enhanced collaboration between the research and operational communities, enabled studies on a wide range of topics, and contributed to significant advances toward a better understanding of subseasonal predictability and windows of opportunity that contributed to improvements in forecast skill. It was used to train machine learning methods and test their performance in the S2S artificial intelligence/machine learning (AI/ML) prize challenge. The S2S project coorganized several coordinated research experiments to advance understanding of subseasonal predictability and the Real-Time Pilot Initiative that provided real-time access to subseasonal data for 15 application projects. A sequence of training courses sustained over 10 years enhanced the capacity of national meteorological services in the Global South to make subseasonal forecasts. A major legacy of the S2S project was the establishment and designation of the World Meteorological Organization (WMO) Global Producing Centres and Lead Centre for Subseasonal Prediction Multi-Model Ensemble, which will provide real-time subseasonal multimodel ensemble (MME) products to national and regional meteorological services.

AbstractThe boreal summer intraseasonal oscillation (BSISO) is a major mode of sub‐seasonal variability that regulates the summer climate in East Asia. This study investigates the four possible effects of two different time‐scale BSISOs on temperature and precipitation variations in South Korea. When active BSISO convection is positioned over the subtropical western Pacific, it induces anomalous anticyclonic circulation accompanied by subsidence, leading to significant positive temperature anomalies. Conversely, the anomalous cyclonic circulation near the Korean Peninsula, resulting from suppressed convection in the subtropical western Pacific, along with low‐level cold advection anomalies, contributes to a decrease in temperature. The spatial distribution of BSISO convection, which drives precipitation variation, shows a distinctive pattern of three meridionally narrow cells extending from the Philippines to the Korean Peninsula. Suppressed (enhanced) convection to the north of 20°N in the western North Pacific (WNP) promotes the northwestward expansion (eastward contraction) of the WNP Subtropical High in conjunction with a southwesterly (northeasterly) moisture flux anomaly. Furthermore, enhanced (reduced) moisture flux convergence and intensified ascending (descending) motion create favorable conditions for positive (negative) precipitation anomalies in South Korea. The combined effect of BSISOs not only amplifies the mean temperature and precipitation anomalies compared to individual modes but also increases the frequency of warmer, wetter, and drier events. Therefore, monitoring both BSISO modes together is crucial for comprehending and predicting the anomalous summer climate in South Korea.

Assessing the future risk of natural disasters, securing sustainable energy and water resources, and developing strategies for adapting to climate change remain challenging due to the large uncertainties in regional-scale climate projections. Recent efforts to address this issue include km-scale coupled climate model simulations that resolve mesoscale processes in the atmosphere and ocean, as well as their interactions with the large-scale environment and small-scale topographic features. Our presentation shows the first results from a series of global 9 km-scale greenhouse warming simulations using the AWI Climate Model Version 3 which is based on the OpenIFS atmosphere model at TCO1279 resolution and 137 vertical levels and the FESOM2 ocean model at 4-15 km resolution. By comparing a set of consecutive 10-year time-slice simulations forced by the CMIP6 SSP585 scenario with a transient simulation at a lower-resolution (31 km in the OpenIFS), we identify key differences in weather and climate-related phenomena, including tropical cyclones, ENSO, and regional climate change features that can be attributed to km-scale dynamics in clouds and atmospheric circulation patterns. The findings from our cloud-permitting climate simulations provide valuable insights into the role of small-scale processes in the sensitivity of the regional and global climate.

The Bayesian inverse method, combined with measurements of atmospheric carbon dioxide (CO2) and a transport model, can serve as an independent verification approach to improve the precision of emission estimates. This study utilized the Bayesian inverse model, along with ground- and space-based measurements, to validate CO2 emissions in Seoul. A Bayesian inverse modeling framework was developed, integrating crucial input data such as anthropogenic CO2 emissions, biogenic CO2 fluxes, atmospheric CO2 measurements, a Lagrangian transport model, and error covariances for both prior emissions and observations. The averages of posterior emissions decreased after the inversion run, with a correction of approximately -8.69%. This suggests that the prior emissions were overestimated. There was an average 9.7% reduction in posterior emission uncertainties compared to prior uncertainties. The most substantial reductions in uncertainty were observed in areas with concentrated observation sites. The performance of the inverse model was thoroughly investigated through sensitivity analysis, encompassing different background representations, prior uncertainty levels, temporal and spatial uncertainties, and observational network configurations. Additionally, we quantified spatiotemporal changes in CO2 emissions due to COVID-19. The abundance of ground and space observations in Seoul provided robust constraints on urban CO2 emissions, allowing for an objective evaluation of the effectiveness of carbon reduction policies.This work was supported by Korea Environmental Industry & Technology Institute (KEITI) through "Project for developing an observation-based GHG emissions geospatial information map", funded by Korea Ministry of Environment(MOE)(RS-2023-00232066).

The global atmospheric CO2 growth rate is a product of the combined effects of emissions and uptake from both anthropogenic and natural carbon sources. Therefore, an evaluation of the global CO2 growth rate should be preceded to understand the global carbon-climate process. In this study, we analyzed the long-term changes in the global CO2 growth rate from 1991 to 2020, using data from 42 global sites and model simulations to assess recent changes in the global carbon-climate feedback process. Our results indicate that the annual CO2 growth rate has increased by 0.032 ppm yr-2 since the 2000s. A comprehensive assessment of carbon cycle components contributing to atmospheric CO2 growth rate changes reveals that the strengthening of this rate is linked to a decline in terrestrial carbon absorption over the last decade. This decline is primarily associated with a slowdown in the increasing trend of Net Primary Productivity. Consequently, the reduced terrestrial carbon uptake in recent decades contributed to an approximately 3 ppm increase in global CO2 concentration by 2020. Our findings highlight that the vegetation's carbon uptake capacity can no longer offset anthropogenic CO2 emissions, underscoring the importance of achieving global carbon neutrality in climate change mitigation. This work was supported by Korea Environment Industry & Technology Institute(KEITI) through Project for developing an observation-based GHG emissions geospatial information map, funded by Korea Ministry of Environment(MOE) (RS-2023-00232066)

Greenhouse warming is accelerating permafrost thaw and the risk of wildfires in the northern high latitudes. However, the impact of permafrost thaw on Arctic-Subarctic wildfires and the associated release of greenhouse gases and aerosols is less well understood. Here we investigate the effect of future permafrost thaw on Arctic-Subarctic wildfires using the CESM2 large ensemble simulations forced by the SSP3-7.0 greenhouse gas emission scenario. We find that an increase in soil permeability induced by rapid permafrost thawing leads to an abrupt increase in sub-surface runoff and a decrease in soil moisture over the Arctic-Subarctic region. This sudden soil drying causes a significant increase in surface air temperature and a decrease in relative humidity during summer. The resulting soil drying and atmospheric dryness lead to a rapid intensification of wildfires in western Siberia and Canada in the mid-to-late 21st century.

Human life history is characterized by an extended period of immaturity during which there is a disjunction between cerebral and somatic growth rates1. This mode of ontogeny is thought to be essential for the acquisition of advanced cognitive capabilities in a socially complex environment while the brain is still growing2. Key information about when and how this pattern evolved can be gleaned from the teeth of fossil hominins because dental development informs about the pace of life history3–5. Here we show that the first evolutionary steps towards an extended growth phase occurred in the genus Homo at least 1.77 million years ago, before any substantial increase in brain size. We used synchrotron phase-contrast tomography6 to track the microstructural development of the dentition of a subadult early Homo individual from Dmanisi, Georgia. The individual died at the age of 11.4 ± 0.6 years, shortly before reaching dental maturity. Tooth growth rates were high, similar to rates in living great apes. However, the Dmanisi individual showed a human-like delayed formation of the posterior relative to the anterior dentition, and a late growth spurt of the dentition as a whole. The unique combination of great-ape-like and human-like features of dental ontogeny suggests that early Homo had evolved an extended growth phase before a general slow-down in life history, possibly related to biocultural reproduction7 rather than brain growth.