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The Earth climate system is out of energy balance, and heat has accumulated continuously over the past decades, warming the ocean, the land, the cryosphere, and the atmosphere. According to the Sixth Assessment Report by Working Group I of the Intergovernmental Panel on Climate Change, this planetary warming over multiple decades is human-driven and results in unprecedented and committed changes to the Earth system, with adverse impacts for ecosystems and human systems. The Earth heat inventory provides a measure of the Earth energy imbalance (EEI) and allows for quantifying how much heat has accumulated in the Earth system, as well as where the heat is stored. Here we show that the Earth system has continued to accumulate heat, with 381±61 ZJ accumulated from 1971 to 2020. This is equivalent to a heating rate (i.e., the EEI) of 0.48±0.1 W m−2. The majority, about 89 %, of this heat is stored in the ocean, followed by about 6 % on land, 1 % in the atmosphere, and about 4 % available for melting the cryosphere. Over the most recent period (2006–2020), the EEI amounts to 0.76±0.2 W m−2. The Earth energy imbalance is the most fundamental global climate indicator that the scientific community and the public can use as the measure of how well the world is doing in the task of bringing anthropogenic climate change under control. Moreover, this indicator is highly complementary to other established ones like global mean surface temperature as it represents a robust measure of the rate of climate change and its future commitment. We call for an implementation of the Earth energy imbalance into the Paris Agreement's Global Stocktake based on best available science. The Earth heat inventory in this study, updated from von Schuckmann et al. (2020), is underpinned by worldwide multidisciplinary collaboration and demonstrates the critical importance of concerted international efforts for climate change monitoring and community-based recommendations and we also call for urgently needed actions for enabling continuity, archiving, rescuing, and calibrating efforts to assure improved and long-term monitoring capacity of the global climate observing system. The data for the Earth heat inventory are publicly available, and more details are provided in Table 4.

In this study, a data-driven approach employed by utilizing the product called JRC-Global surface water mapping layers V1.4 on the Google Earth Engine (GEE) to map and monitor the effects of climate change on surface water resources. Key climatic variables affecting water bodies, including air temperature (AT), actual evapotranspiration (ETa), and total precipitation, were analyzed from 2000 to 2021 using the temperature-vegetation index (TVX) and Moderate Resolution Imaging Spectroradiometer (MODIS) products. The findings demonstrate a clear association between global warming and the shrinking of surface water resources in the LUB. According to the results, an increase in AT corresponded to a decrease in water surface area, highlighting the significant influence of AT and ETa on controlling the water surface in the LUB (partial rho of − 0.65 and − 0.68, respectively). Conversely, no significant relationship was found with precipitation and water surface area (partial rho of + 0.25). Notably, the results of the study indicate that over the past four decades, approximately 40% of the water bodies in the LUB remained permanent. This suggests a loss of around 30% of the permanent water resources, which have transitioned into seasonal water bodies, accounting for nearly 13% of the total. This research provides a comprehensive framework for monitoring surface water resource variations and assessing the impact of climate change on water resources. It aids in the development of sustainable water management strategies and plans, supporting the preservation and effective use of water resources.

Monitoring changes in marine phytoplankton is important as they form the foundation of the marine food web and are crucial in the carbon cycle. Often Chlorophyll-a (Chl-a) is used to track changes in phytoplankton, since there are global, regular satellite-derived estimates. However, satellite sensors do not measure Chl-a directly. Instead, Chl-a is estimated from remote sensing reflectance ( R RS ): the ratio of upwelling radiance to the downwelling irradiance at the ocean’s surface. Using a model, we show that R RS in the blue-green spectrum is likely to have a stronger and earlier climate-change-driven signal than Chl-a. This is because R RS has lower natural variability and integrates not only changes to in-water Chl-a, but also alterations in other optically important constituents. Phytoplankton community structure, which strongly affects ocean optics, is likely to show one of the clearest and most rapid signatures of changes to the base of the marine ecosystem. Changes in chlorophyll-a are used as an indirect proxy for monitoring global changes in marine phytoplankton. Here the authors show that remote sensing reflectance ( R RS ), such as the ratio of upwelling versus downwelling light at the ocean’s surface, has a stronger and earlier climate-change-driven signal over the 21st century.

Precise modelling of the influence of climate change on Arabica coffee is limited; there are no data available for indigenous populations of this species. In this study we model the present and future predicted distribution of indigenous Arabica, and identify priorities in order to facilitate appropriate decision making for conservation, monitoring and future research. Using distribution data we perform bioclimatic modelling and examine future distribution with the HadCM3 climate model for three emission scenarios (A1B, A2A, B2A) over three time intervals (2020, 2050, 2080). The models show a profoundly negative influence on indigenous Arabica. In a locality analysis the most favourable outcome is a c. 65% reduction in the number of pre-existing bioclimatically suitable localities, and at worst an almost 100% reduction, by 2080. In an area analysis the most favourable outcome is a 38% reduction in suitable bioclimatic space, and the least favourable a c. 90% reduction, by 2080. Based on known occurrences and ecological tolerances of Arabica, bioclimatic unsuitability would place populations in peril, leading to severe stress and a high risk of extinction. This study establishes a fundamental baseline for assessing the consequences of climate change on wild populations of Arabica coffee. Specifically, it: (1) identifies and categorizes localities and areas that are predicted to be under threat from climate change now and in the short- to medium-term (2020-2050), representing assessment priorities for ex situ conservation; (2) identifies 'core localities' that could have the potential to withstand climate change until at least 2080, and therefore serve as long-term in situ storehouses for coffee genetic resources; (3) provides the location and characterization of target locations (populations) for on-the-ground monitoring of climate change influence. Arabica coffee is confimed as a climate sensitivite species, supporting data and inference that existing plantations will be neagtively impacted by climate change.

Longitudinal assessment of climate vulnerability is essential for understanding the complex factors affecting how people experience and respond to climate change. We report on the first longitudinal assessment of climate vulnerability in the Himalayan region, exploring the evolving landscape, perceptions, and experiences of communities of climate change impacts, vulnerability, and adaptation in Kashmir over an 8-year period from 2017 to 2024. We provide the Himalayan Re-study Framework (HRF) to monitor, characterise, and conceptualise climate change in the Himalayas. Utilising mixed methods, we showcase how climate change is affecting social, economic, political, and environmental dimensions, examining how the impacts of climate change and vulnerability evolve over time, shaping and reshaping how climate risks are experienced and responded to by communities. Our analysis reveals a nuanced understanding of vulnerability, highlighting the impact on communities’ livelihoods and water security, differential impacts on marginalised communities, and the gendered nature of climate change. We examine how certain sections of the population face marginalisation, discrimination, and racism, and how climate change exacerbates these challenges. Kashmir’s vulnerability to climate change extends beyond environmental factors, intertwining with culture, livelihoods, social dynamics, and politics. Climate change continues to compete for attention with immediate political and socio-economic challenges, highlighting the need for integrated approaches to address both environmental and societal issues in Kashmir.

Imaging underwater environments is of great importance to marine sciences, sustainability, climatology, defense, robotics, geology, space exploration, and food security. Despite advances in underwater imaging, most of the ocean and marine organisms remain unobserved and undiscovered. Existing methods for underwater imaging are unsuitable for scalable, long-term, in situ observations because they require tethering for power and communication. Here we describe underwater backscatter imaging, a method for scalable, real-time wireless imaging of underwater environments using fully-submerged battery-free cameras. The cameras power up from harvested acoustic energy, capture color images using ultra-low-power active illumination and a monochrome image sensor, and communicate wirelessly at net-zero-power via acoustic backscatter. We demonstrate wireless battery-free imaging of animals, plants, pollutants, and localization tags in enclosed and open-water environments. The method’s self-sustaining nature makes it desirable for massive, continuous, and long-term ocean deployments with many applications including marine life discovery, submarine surveillance, and underwater climate change monitoring. The authors present an approach to underwater imaging, which does not require tethering or batteries. The low-power camera uses power from harvested acoustic energy and communicates colour images wirelessly via acoustic backscatter.

The management of rangelands, including climate change adaptation strategies, is primarily responsible for stimulating livestock productivity, which consequently improves food security. This paper investigates the impact of climate change adaptations on food security among pastoralists in semi-arid parts of Kenya, who have not received due attention to date. Using an endogenous switching regression model, the current study revealed that pastoralists’ food security increased significantly when they employed measures to adapt to climate change. The study results also showed that wealthier households and those with more livestock were more food-secure than comparatively poorer households or those with less livestock. Furthermore, the study uncovered a high prevalence of food security among more educated households. The paper therefore recommends that, in Kenya’s semi-arid lands, where pastoralism is the primary means of livelihood, policies advocating adaptations to climate change should be strengthened. Also fundamental to building pastoralists’ adaptation strategies are the consistent monitoring of climate change, the use of early warning systems, and the communication of pertinent information to farmers—and particularly to pastoralists.

Soil moisture is central to local climate on land. In situ soil moisture observations are vital for observing vegetation‐relevant root‐zone soil moisture. However, stations included in the International Soil Moisture Network are sparse in regions with strong land‐atmosphere coupling. We apply a machine‐learning‐based procedure for informing future station placement using virtual soil moisture stations in future CMIP6 projections. Stations are placed where the climate is currently most under‐represented. This strategy outperforms random station placement and station placement according to geographical distance. Doubling the current number of stations using this method alleviates the uneven global distribution of stations, increases the skill in the estimation of inter‐annual variability and trends in dry‐season soil moisture, and reduces its differences across climates in future projections. Stations are predominantly placed in tropical climates, especially when optimizing for drying trends. The results can inform future station placement to support climate change mitigation efforts. Plain Language Summary Water stored in the ground as soil moisture is the main water supply for ecosystems and can influence local weather. Ground observations of soil moisture can measure water in deeper soil layers that roots can access. Many stations are collected in the International Soil Moisture Network database. However, this database mainly contains observation stations from the US and Europe. If we were to put additional stations, we should focus on regions and climates that the current network does not sufficiently cover. Locations in model projections of future climate that currently contain a station (“virtual stations”) are used to build a machine‐learning model that predicts soil moisture at locations without stations. We then place new virtual stations where the prediction error of dry‐season soil moisture variability and dry‐season trends is largest. This strategy outperforms randomly placing new stations or placing stations where they are most distant from existing ones. Stations are placed predominantly in the tropics, but prediction improves in all regions. Furthermore, stations are more evenly distributed across the globe, and differences in skill between regions become smaller. This tool can be used to decide where to place future soil moisture stations, which are important for monitoring climate change. Key Points In situ soil moisture observations are distributed unequally across the globe and sparse in regions with strong land‐atmosphere coupling We present a machine‐learning based procedure for informing future station placement using virtual soil moisture stations Doubling the number of stations with this strategy reduces error in soil moisture trends by 0.2–1.4 kg m−2 and reduces global differences

Reducing methane emissions from the oil and gas production infrastructure is a cost-effective way for limiting global warming. In 2019, a measurement campaign in southern Romania found emission rates from the oil and gas sector substantially higher than the nationally reported emissions, with a few high-emitting sources (“super-emitters”) contributing disproportionately to total emissions. In 2021, our follow-up airborne remote sensing campaign, covering over 80 % of production sites, revealed a marked decrease in super-emitters. The observed change in the number of emitters is consistent with an emission reduction by 20 %–60 % from 2019 to 2021. This reduction is likely due to improvements in production infrastructure following the first campaign in 2019. This is further supported by additional site visits, which showed that many of the leaks identified in 2019 had indeed been mitigated. However, our top-down quantification remains higher than the bottom-up emission reports. Our study highlights the importance of measurement-based emission monitoring of climate change mitigation measures and illustrates the value of a multi-scale assessment integrating ground-based observations with large-scale airborne mapping to capture both the primary mode of emission sources and the rare, but significant, super-emitters.

Arctic climate change has already resulted in amplified and accelerated regional warming, or the Arctic amplification. Satellite observations have captured this climate phenomenon in its development and in sufficient spatial details. As such, these observations have been—and still are—indispensable for monitoring of the amplification in this remote and inhospitable region, which is sparsely covered with ground observations. This study synthesizes the key contributions of satellite observations into an understanding and characterization of the amplification. The study reveals that the satellites were able to capture a number of important environmental transitions in the region that both precede and follow the emergence of the apparent amplification. Among those transitions, we find a rapid decline in the multiyear sea ice and subsequent changes in the surface radiation balance. Satellites have witnessed the impact of the amplification on phytoplankton and vegetation productivity as well as on human activity and infrastructure. Satellite missions of the European Space Agency (ESA) are increasingly contributing to amplification monitoring and assessment. The ESA Climate Change Initiative has become an essential provider of long-term climatic-quality remote-sensing data products for essential climate variables. Still, such synthesis has found that additional efforts are needed to improve cross-sensor calibrations and retrieval algorithms and to reduce uncertainties. As the amplification is set to continue into the 21st century, a new generation of satellite instruments with improved revisiting time and spectral and spatial resolutions are in high demand in both research and stakeholders’ communities.