United in Science: Reboot climate action
Human-caused climate change has resulted in widespread and rapid changes in the atmosphere, ocean, cryosphere, and biosphere. The year 2023 was the warmest on record by a large margin, with widespread extreme weather. This trend continued in the first half of 2024.
Global greenhouse gas (GHG) emissions rose by 1.2% from 2021 to 2022, reaching 57.4 billion tons of carbon dioxide (CO2) equivalent. Globally averaged surface concentrations of CO2, methane (CH4) and nitrous oxide (N2O) also reached new highs, according to the United in Science report.
When the Paris Agreement was adopted, greenhouse gas emissions were projected to increase by 16% by 2030 relative to 2015. Now, that projected increase is 3%, indicating progress has been made. Yet the emissions gap for 2030 remains high. To limit global warming to below 2 °C and 1.5 °C (above the pre-industrial era), global GHG emissions in 2030 must be reduced by 28% and 42%, respectively, from the levels projected by current policies.
With existing policies and Nationally Determined Contributions (which present national efforts to limit global warming to well below 2 °C), it is estimated that global warming will be kept to a maximum of 3 °C throughout the century. Only in the most optimistic scenario where all conditional NDCs and net-zero pledges are fully achieved, is global warming projected to be limited to 2 °C, with just a 14% chance of limiting global warming to 1.5 °C.
There is an 80% chance that the global mean near-surface temperature in at least one of the next five calendar years will exceed 1.5 °C above pre-industrial levels, and a 47% chance that the 2024-2028 five-year mean will exceed this threshold. The Paris Agreement threshold of 1.5 °C refers to long-term warming averaged over 20 years.
Urgent mitigation action is needed, as is climate adaptation
However, one out of six countries still lacks a national adaptation planning instrument, and a significant finance gap remains, with the flow of international public adaptation finance declining since 2020.
Artificial intelligence and Machine Learning: revolutionizing weather forecasting
Artificial Intelligence (AI) and Machine Learning (ML) can make skillful weather modeling faster, cheaper, and more accessible to lower-income countries with limited computational capacities.
Traditionally, weather forecasting relies on physics-based models through a process known as numerical weather prediction. AI/ML models are trained on reanalysis and observational datasets, making weather forecasting faster and cheaper. Some evaluations have shown the potential of AI/ML for forecasting hazardous events such as tropical cyclones and longer-term predictions of El Niño and La Niña.
There are tremendous opportunities but also many challenges, particularly limited data quality and availability. Current AI/ML models do not include harder-to-predict variables related to the ocean, land, cryosphere, and carbon cycle.
Strong global governance is needed to ensure AI/ML serves the global good. Enhanced transparency will be important for building trust and developing standards for responsible use.
Space-based Earth observations
Incredible advancements in recent decades in space-based Earth observations offer vast opportunities for the future.
High-resolution and high-frequency observations of the Earth system are crucial for effective weather forecasting, climate prediction, and environmental monitoring.
By leveraging public-private partnerships, innovations in space-based Earth observations can be used to enhance weather, climate, water, and related environmental applications.
However, big challenges limit the realization of the full potential of space-based Earth observations in support of global goals. Gaps remain in accurately measuring critical ocean, climate, aerosol, and hydrological variables and in covering sparsely observed areas such as the cryosphere.
Additionally, data accessibility and standardization are a problem, particularly for developing countries. International collaboration, comprehensive governance frameworks for integrated observing systems, and innovative financing models are needed to support space-based Earth observation for weather, climate, water, and related environmental applications.
Bridging virtual and physical realms: leveraging immersive technologies for water and land management
Socioeconomic impacts and climate change are threatening water and land resources, requiring innovative technologies like digital twins, virtual reality, and the metaverse to improve integrated land and water management. These technologies can simulate floods, predict water flow, and enhance decision-making. However, challenges include data availability, funding, governance, and public trust.
Towards pathways to sustainable futures: the role of transdisciplinary approaches
A transdisciplinary approach is needed to address global challenges like climate change, disaster risk reduction, and sustainable development. This involves involving diverse actors, including scientists, policymakers, practitioners, and civil society, to co-create solutions relevant to local contexts. This approach enriches understanding of climate change impacts and strengthens trust in institutions like National Meteorological and Hydrological Services.
A future where everyone is protected by life-saving early warning systems
Multi-hazard early warning systems (MHEWS) are crucial for protecting lives, livelihoods, and the environment, with over half of the world’s countries having MHEWS, but significant gaps remain.
