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Project: GCOS Earth Heat Inventory - A study under the Global Climate Observing System (GCOS) concerted international effort to update the Earth heat inventory (EHI), and presents an updated international assessment of ocean warming estimates, and new and updated estimates of heat gain in the atmosphere, cryosphere and land over the period from 1960 to present. Summary: The file “GCOS_EHI_1960-2020_Earth_Heat_Inventory_Ocean_Heat_Content_data.nc” contains a consistent long-term Earth system heat inventory over the period 1960-2020. Human-induced atmospheric composition changes cause a radiative imbalance at the top-of-atmosphere which is driving global warming. Understanding the heat gain of the Earth system from this accumulated heat – and particularly how much and where the heat is distributed in the Earth system - is fundamental to understanding how this affects warming oceans, atmosphere and land, rising temperatures and sea level, and loss of grounded and floating ice, which are fundamental concerns for society. This dataset is based on a study under the Global Climate Observing System (GCOS) concerted international effort to update the Earth heat inventory published in von Schuckmann et al. (2020), and presents an updated international assessment of ocean warming estimates, and new and updated estimates of heat gain in the atmosphere, cryosphere and land over the period 1960-2020. The dataset also contains estimates for global ocean heat content over 1960-2020 for different depth layers, i.e., 0-300m, 0-700m, 700-2000m, 0-2000m, 2000-bottom, which are described in von Schuckmann et al. (2022). This version includes an update of heat storage of global ocean heat content, where one additional product (Li et al., 2022) had been included to the initial estimate. The Earth heat inventory had been updated accordingly, considering also the update for continental heat content (Cuesta-Valero et al., 2023).

This study investigates the trends in economic damages caused by three types of inland floods (flash flood, flood, and heavy rain) in the United States and the variations in related hazard and vulnerability indicators between 1996 and 2016. We explore the underlying mechanisms based on a survey-based dataset maintained by the National Oceanic and Atmospheric Administration (NOAA) National Weather Service. An annual average of 6518 flood occurrences was reported, which caused economic damages of 3351 million USD per year. Flash flood and flood contributed to 53% and 32% of total occurrences and was associated with a larger share of damaging events (SDE). Results show that the higher impacts by flood and flash flood on property and crop are partly attributed to the greater intensity of rainfall. In addition, flood has the highest unit cost of damages. Notably, despite an upward tendency in economic damages by flash floods, no evident change trend is observed for inland floods as a whole. Further analysis shows changes in economic damages by heavy rain and flash flood are mainly governed by the increased annual frequency and hazard intensity, but the change of trend in their vulnerability indicators (i.e., SDE and Damage Per Event (DPE)) is not obvious. Regarding floods, it was not possible to attribute the variations in economic losses to hazard and vulnerability, as no significant tendency is found except for an increasing SDE. Despite limitations of length of records, data collection, and methodology, the difference in economic impacts and the related hazard and vulnerability revealed in this study can help better target future adaptation and mitigation measures.

Abstract. Climate change has precipitated recurrent extreme events and emerged as an imposing global challenge, exerting profound and far-reaching impacts on both the environment and human existence. The Universal Thermal Climate Index (UTCI), serving as an important approach to human comfort assessment, plays a pivotal role in gauging how the human adapts to meteorological conditions and copes with thermal and cold stress. However, the existing UTCI datasets still grapple with limitations in terms of data availability, hindering their effective application across diverse domains. We have produced the GloUTCI-M, a monthly UTCI dataset boasting global coverage, an extensive time series spanning from March 2000 to October 2022, and a high spatial resolution of 1 km. This dataset is the product of a comprehensive approach leveraging multiple data sources and advanced machine learning models. Our findings underscore the superior predictive capabilities of CatBoost in forecasting UTCI (MAE = 0.747 °C, RMSE = 0.943 °C, R2 = 0.994) when compared to machine learning models such as XGBoost and LightGBM. Utilizing GloUTCI-M, the geographical boundaries of cold stress and thermal stress areas on a global scale were effectively delineated. Over the span of 2001 to 2021, the mean annual global UTCI registers at 17.24 °C, with a pronounced upward trend. Countries like Russia and Brazil emerge as key contributors to the mean annual global UTCI increase, while countries like China and India exert a more inhibitory influence on this trend. Furthermore, in contrast to existing UTCI datasets, GloUTCI-M excels at portraying UTCI distribution at finer spatial resolutions, augmenting data accuracy. This dataset enhances our capacity to evaluate thermal stress experienced by the human, offering substantial prospects across a wide array of applications. The GloUTCI-M is publicly available at https://doi.org/10.5281/zenodo.8310513 (Yang et al., 2023).

Despite the fact that it is the total crop production that shapes future food supply rather than one of its single component, previous studies have mainly focused on the changes in crop yield. It is possible that recent gains in crop production are mainly due to improvement of yield rather than growth of harvest area. However, it remains unclear about the geographical patterns of their relative contributions at fine scales and the possible mechanisms. Analysis of US maize production shows that maize production has increased significantly at a rate of 2.1%/year during 1980-2010. Although yield is the dominant factor contributing to production growth for the country as a whole, the importance of harvest area has become more evident with time. In 56% of US's maize growing counties, harvest area has also contributed more than yield to production changes. High spatial correlation between the change rates of harvest area and production is observed (R = 0.96), while a weak relation (R = 0.21) is found between the spatial patterns of yield and production. This suggests that harvest area has exerted the dominant role in modulating the spatial distribution pattern of maize production changes. Further analysis suggests that yield and harvest area respond differently to climate variability, which has great implications for adaptation strategies. Comparing 11 state-of-the-art crop model simulations against census data reveals large bias in the simulated spatial patterns of maize production. Nevertheless, such bias can be reduced substantially by incorporating the observed dynamics of harvest area, pointing to a potential pathway for future model improvement. This study highlights the importance of accounting for harvest area dynamics in assessing agricultural production empirically or with crop models.

Terrestrial ecosystems, occupying 28.26% of Earth's surface, are extensively at risk from droughts, which is likely to propagate into human communities owing to loss of vital services. Ecosystem risk also tends to fluctuate within anthropogenically-forced nonstationary environments, raising considerable concerns about effectiveness of mitigation strategies. This study aims to assess dynamic ecosystem risk induced by droughts and identify risk hotspots. Bivariate nonstationary drought frequency was initially derived as a hazard component of risk. By coupling vegetation coverage and biomass quantity, a two-dimensional exposure indicator was developed. Trivariate likelihood of vegetation decline was calculated under arbitrary droughts to intuitively determine ecosystem vulnerability. Ultimately, time-variant drought frequency, exposure and vulnerability were multiplied to derive dynamic ecosystem risk, followed by hotspot and attribution analyses. Risk assessment implemented in the drought-prevalent Pearl River basin (PRB) of China during 1982-2017 showed that meteorological droughts in eastern and western margins, although less frequent, were prolonged and aggravated in contrast to prevalence of less persistent and severe droughts in the middle. In 86.12% of the PRB, ecosystem exposure maintains high levels (0.62). Relatively high vulnerability (>0.5) occurs in water-demanding agroecosystems, exhibiting a northwest-southeast-directed extension. A 0.1-degree risk atlas unveils that high and medium risks occupy 18.96% and 37.99% of the PRB, while risks are magnified in the north. The most pressing hotspots with high risk continuing to escalate reside in the East River and Hongliu River basins. Our results provide knowledge of composition, spatio-temporal variability and driving mechanism of drought-induced ecosystem risk, which will assist in risk-based mitigation prioritization.

Project: GCOS Earth Heat Inventory - A study under the Global Climate Observing System (GCOS) concerted international effort to update the Earth heat inventory (EHI), and presents an updated international assessment of ocean warming estimates, and new and updated estimates of heat gain in the atmosphere, cryosphere and land over the period from 1960 to present. Summary: The file “GCOS_EHI_1960-2020_Continental_Heat_Content_data.nc” presents an updated estimate of the global continental heat storage for the period 1960-2020. For the first time, the continental heat storage is assessed as composed by: ground heat storage due to changes in subsurface temperatures, inland water heat storage due to the warming of inland water bodies, and permafrost heat storage due to thawing of ground ice in the Arctic. Furthermore, we argue that all three components of the continental heat storage should be monitored independently of their relative magnitude, as heat gain in the three components alters several important climate phenomena affecting society and ecosystems. This file contains the total continental heat storage relative to 1960. The ground heat storage has been estimated by inverting 1079 subsurface temperature profiles form the Xibalbá database (https://figshare.com/articles/dataset/Xibalb_Underground_Temperature_Database/13516487) and a bootstrap technique to aggregate the Singular Value Decomposition (SVD) inversions of each profile (Cuesta-Valero et al., 2022a). The data are used in Cuesta-Valero et al. (2022b) and von Schuckmann et al. (2022).

Project: GCOS Earth Heat Inventory - A study under the Global Climate Observing System (GCOS) concerted international effort to update the Earth heat inventory (EHI), and presents an updated international assessment of ocean warming estimates, and new and updated estimates of heat gain in the atmosphere, cryosphere and land over the period from 1960 to present. Summary: The file “GCOS_EHI_1960-2020_Continental_Heat_Content_data.nc” presents an updated estimate of the global continental heat storage for the period 1960-2020. For the first time, the continental heat storage is assessed as composed by: ground heat storage due to changes in subsurface temperatures, inland water heat storage due to the warming of inland water bodies, and permafrost heat storage due to thawing of ground ice in the Arctic. Furthermore, we argue that all three components of the continental heat storage should be monitored independently of their relative magnitude, as heat gain in the three components alters several important climate phenomena affecting society and ecosystems. This file contains the total continental heat storage relative to 1960. The ground heat storage has been estimated by inverting 1079 subsurface temperature profiles form the Xibalbá database (https://figshare.com/articles/dataset/Xibalb_Underground_Temperature_Database/13516487) and a bootstrap technique to aggregate the Singular Value Decomposition (SVD) inversions of each profile (Cuesta-Valero et al., 2022a). The data are used in Cuesta-Valero et al. (2022b) and von Schuckmann et al. (2022). This version includes an update of continental heat content uncertainty, where the standard deviation has been corrected from the precedent version to consider properly the value from permafrost heat storage uncertainty.

Project: GCOS Earth Heat Inventory - A study under the Global Climate Observing System (GCOS) concerted international effort to update the Earth heat inventory (EHI), and presents an updated international assessment of ocean warming estimates, and new and updated estimates of heat gain in the atmosphere, cryosphere and land over the period from 1960 to present. Summary: The file “GCOS_EHI_1960-2020_Earth_Heat_Inventory_Ocean_Heat_Content_data.nc” contains a consistent long-term Earth system heat inventory over the period 1960-2020. Human-induced atmospheric composition changes cause a radiative imbalance at the top-of-atmosphere which is driving global warming. Understanding the heat gain of the Earth system from this accumulated heat – and particularly how much and where the heat is distributed in the Earth system - is fundamental to understanding how this affects warming oceans, atmosphere and land, rising temperatures and sea level, and loss of grounded and floating ice, which are fundamental concerns for society. This dataset is based on a study under the Global Climate Observing System (GCOS) concerted international effort to update the Earth heat inventory published in von Schuckmann et al. (2020), and presents an updated international assessment of ocean warming estimates, and new and updated estimates of heat gain in the atmosphere, cryosphere and land over the period 1960-2020. The dataset also contains estimates for global ocean heat content over 1960-2020 for different depth layers, i.e., 0-300m, 0-700m, 700-2000m, 0-2000m, 2000-bottom, which are described in von Schuckmann et al. (2022).

AbstractThe land–river interface (LRI) is important for sustainable development. The environmental processes that define the LRI support the natural capital and ecosystem services that are linked directly to multiple Sustainable Development Goals (SDGs). However, existing approaches to scale up or down SDG targets and link them to natural capital are insufficient for the two-way human–environment interactions that exist in the LRI. Therefore, this study proposes a place-based approach to interpret the SDG framework to support sustainable land/water management, by (i) identifying key priorities for sustainable development through a normative content analysis of the SDG targets, and (ii) illustrating these priorities and associated challenges within the LRI, based on a literature review and case-studies on human–environment interactions. The content analysis identifies three overarching sustainable development priorities: (i) ensuring improved access to resources and services provided by the LRI, (ii) strengthening the resilience of the LRI to deal with social and natural shocks, and (iii) increasing resource efficiency. The review of the current state of LRIs across the world confirms that these are indeed priority areas for sustainable development. Yet, the challenges of attaining the sustainable development priorities in the LRI are also illustrated with three examples of development-related processes. Urbanisation, dam construction, and aggregate mining occur within specific zones of the LRI (land, land–river, river, respectively), but their impacts can compromise sustainable development across the entire LRI and beyond. The existence of these unintended impacts highlights the need to consider the geomorphic, hydrological, and ecological processes within the LRI and how they interact with human activity. Identifying the place-based priorities and challenges for sustainable development will help achieve the SDGs without compromising the functions and services of the LRI.