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Constraining the climate crisis requires urgent action to reduce anthropogenic emissions while simultaneously removing carbon dioxide from the atmosphere. Improved information about the maximum magnitude and spatial distribution of opportunities for additional land-based removals of CO₂ is needed to guide on-the-ground decision-making about where to implement climate change mitigation strategies. Here, we present a globally consistent spatial dataset (approximately 500-m resolution) of current, potential, and unrealized potential carbon storage in woody plant biomass and soil organic matter. We also provide a framework for prioritizing actions related to the restoration, management, and maintenance of woody carbon stocks and associated soils. By comparing current to potential carbon storage, while excluding areas critical to food production and human habitation, we find 287 petagrams (PgC) of unrealized potential storage opportunity, of which 78% (224 PgC) is in biomass and 22% (63 PgC) is in soil. Improved management of existing forests may offer nearly three-fourths (206 PgC) of the total unrealized potential, with the majority (71%) concentrated in tropical ecosystems. However, climate change is a source of considerable uncertainty. While additional research is needed to understand the impact of natural disturbances and biophysical feedbacks, we project that the potential for additional carbon storage in woody biomass will increase (+17%) by 2050 despite projected decreases (−12%) in the tropics. Our results establish an absolute reference point and conceptual framework for national and jurisdictional prioritization of locations and actions to increase land-based carbon storage.

Large interannual variations in the measured growth rate of atmospheric carbon dioxide (CO2) originate primarily from fluctuations in carbon uptake by land ecosystems13. It remains uncertain, however, to what extent temperature and water availability control the carbon balance of land ecosystems across spatial and temporal scales314. Here we use empirical models based on eddy covariance data15 and process-based models16,17 to investigate the effect of changes in temperature and water availability on gross primary productivity (GPP), terrestrial ecosystem respiration (TER) and net ecosystem exchange (NEE) at local and global scales. We find that water availability is the dominant driver of the local interannual variability in GPP and TER. To a lesser extent this is true also for NEE at the local scale, but when integrated globally, temporal NEE variability is mostly driven by temperature fluctuations. We suggest that this apparent paradox can be explained by two compensatory water effects. Temporal water-driven GPP and TER variations compensate locally, dampening water-driven NEE variability. Spatial water availability anomalies also compensate, leaving a dominant temperature signal in the year-to-year fluctuations of the land carbon sink. These findings help to reconcile seemingly contradictory reports regarding the importance of temperature and water in controlling the interannual variability of the terrestrial carbon balance36,9,11,12,14. Our study indicates that spatial climate covariation drives the global carbon cycle response.

As the greatest water user in the world, the agricultural sector is vulnerable to changes in climate and water resource availability. Understanding the impact of these changes on crop yield is critical in order to achieve and maintain global food security. We analyze output from an ensemble of Agricultural Model Intercomparison and Improvement Project models to project the probability of rice, soybean, maize, and wheat yield failures across global and national breadbaskets through mid-century. The probability of crop yield failures is projected to be as much as 4.5 times higher by 2030 and up to 25 times higher by 2050 across global breadbaskets. Crop failures are projected to be more likely when effects of CO 2 fertilization are ignored. We utilize the open-source Aqueduct Water Risk Atlas to create a Water Scarcity Index composed of ten hydrological variables. The index reveals high water scarcity across crop breadbaskets in India, China, and the United States. If the ability to irrigate breadbaskets was eliminated due to water scarcity, the likelihood of crop failures would increase. Shifts in breadbaskets may cross national borders as crop yields will increase in Canada and decrease in the US as a response to a changing climate. Our analysis highlights top producing agricultural regions that have historically provided the global food system with large quantities of one or more major crops, but will face challenges in continuing to do so due to climate change and growing water scarcity.

Climate simulation-based scenarios are routinely used to characterize a range of plausible climate futures. Despite some recent progress on bending the emissions curve, RCP8.5, the most aggressive scenario in assumed fossil fuel use for global climate models, will continue to serve as a useful tool for quantifying physical climate risk, especially over near- to midterm policy-relevant time horizons. Not only are the emissions consistent with RCP8.5 in close agreementwith historical total cumulative CO₂ emissions (within 1%), but RCP8.5 is also the best match out to midcentury under current and stated policies with still highly plausible levels of CO₂ emissions in 2100.

NASA has launched the decade-long Arctic-Boreal Vulnerability Experiment (ABoVE). While the initial phases focus on field and airborne data collection, early integration with modeling activities is important to benefit future modeling syntheses. We compiled feedback from ecosystem modeling teams on key data needs, which encompass carbon biogeochemistry, vegetation, permafrost, hydrology, and disturbance dynamics. A suite of variables was identified as part of this activity with a critical requirement that they are collected concurrently and representatively over space and time. Individual projects in ABoVE may not capture all these needs, and thus there is both demand and opportunity for the augmentation of field observations, and synthesis of the observations that are collected, to ensure that science questions and integrated modeling activities are successfully implemented.

Warming temperatures in the Northern Hemisphere have enhanced terrestrial productivity. Despite the warming trend, North America has experienced more frequent and more intense cold weather events during winters and springs. These events have been linked to anomalous Arctic warming since 1990, and may affect terrestrial processes. Here we analyse multiple observation data sets and numerical model simulations to evaluate links between Arctic temperatures and primary productivity in North America. We find that positive springtime temperature anomalies in the Arctic have led to negative anomalies in gross primary productivity over most of North America during the last three decades, which amount to a net productivity decline of 0.31 PgC yr −1 across the continent. This decline is mainly explained by two factors: severe cold conditions in northern North America and lower precipitation in the South Central United States. In addition, United States crop-yield data reveal that during years experiencing anomalous warming in the Arctic, yields declined by approximately 1 to 4% on average, with individual states experiencing declines of up to 20%. We conclude that the strengthening of Arctic warming anomalies in the past decades has remotely reduced productivity over North America. Anomalous Arctic warming has been linked to colder North American winters. Analyses of weather and productivity observations reveal that Arctic–North American teleconnections reduce gross primary productivity in the US.

Forest gross primary production (GPP) is influenced by the interplay between climate conditions and atmospheric CO2 levels, which interact in complex ways, generating both compensating and amplifying effects. In this study, eddy covariance flux measurements from 50 forest ecosystems were integrated with simulations from 14 terrestrial biosphere models to investigate how climate conditions and atmospheric CO2 concentrations regulate forest GPP. This approach bridges site-level observations with biome-scale model estimates to develop a global understanding. Our findings suggest that in boreal and cold temperate regions, temperature primarily constrains the enhancement of the CO2 fertilization on forest GPP; however, warming and higher atmospheric CO2 levels are projected to alleviate these limitations. In tropical forests, CO2 fertilization strongly enhances GPP, but this benefit will be counterbalanced by the adverse impacts of projected climate warming. Consequently, the interplay between climate and atmospheric CO2 in affecting forest GPP is dynamic and subject to continual change.

The Arctic–boreal zone (ABZ) is experiencing amplified warming, actively changing biogeochemical cycling of vegetation and soils. The land-to-atmosphere fluxes of CO2 in the ABZ have the potential to increase in magnitude and feedback to the climate causing additional large-scale warming. The ability to model and predict this vulnerability is critical to preparation for a warming world, but Earth system models have biases that may hinder understanding of the rapidly changing ABZ carbon fluxes. Here we investigate circumpolar carbon cycling represented by the Community Land Model 5 (CLM5.0) with a focus on seasonal gross primary productivity (GPP) in plant functional types (PFTs). We benchmark model results using data from satellite remote sensing products and eddy covariance towers. We find consistent biases in CLM5.0 relative to observational constraints: (1) the onset of deciduous plant productivity to be late; (2) the offset of productivity to lag and remain abnormally high for all PFTs in fall; (3) a high bias of grass, shrub, and needleleaf evergreen tree productivity; and (4) an underestimation of productivity of deciduous trees. Based on these biases, we focus on model development of alternate phenology, photosynthesis schemes, and carbon allocation parameters at eddy covariance tower sites. Although our improvements are focused on productivity, our final model recommendation results in other component CO2 fluxes, e.g., net ecosystem exchange (NEE) and terrestrial ecosystem respiration (TER), that are more consistent with observations. Results suggest that algorithms developed for lower latitudes and more temperate environments can be inaccurate when extrapolated to the ABZ, and that many land surface models may not accurately represent carbon cycling and its recent rapid changes in high-latitude ecosystems, especially when analyzed by individual PFTs.

Climate change has increased forest fire extent in temperate and boreal North America. Here, we quantified the contribution of anthropogenic climate change to human mortality and economic burden from exposure to wildfire particulate matter at the county and state level across the contiguous US (2006 to 2020) by integrating climate projections, climate-wildfire models, wildfire smoke models, and emission and health impact modeling. Climate change contributed to approximately 15,000 wildfire particulate matter deaths over 15 years with interannual variability ranging from 130 (95% confidence interval: 64, 190) to 5100 (95% confidence interval: 2500, 7500) deaths and a cumulative economic burden of $160 billion. Approximately 34% of the additional deaths attributable to climate change occurred in 2020, costing $58 billion. The economic burden was highest in California, Oregon, and Washington. We suggest that absent abrupt changes in climate trajectories, land management, and population, the indirect impacts of climate change on human-health through wildfire smoke will escalate. Climate change contributed to 15,000 wildfire particulate matter deaths in the United States between 2006 and 2020, with a cumulative economic burden of $160 billion, according to observation-based modelling of climate, wildfire particulate matter, health, and economic impacts

Climate variability associated with the El Niño-Southern Oscillation (ENSO) and its consequent impacts on land carbon sink interannual variability have been used as a basis for investigating carbon cycle responses to climate variability more broadly, and to inform the sensitivity of the tropical carbon budget to climate change. Past studies have presented opposing views about whether temperature or precipitation is the primary factor driving the response of the land carbon sink to ENSO. Here, we show that the dominant driver varies with ENSO phase. Whereas tropical temperature explains sink dynamics following El Niño conditions (rTG,P = 0.59, p < 0.01), the post La Niña sink is driven largely by tropical precipitation (rPG,T = −0.46, p = 0.04). This finding points to an ENSO-phase-dependent interplay between water availability and temperature in controlling the carbon uptake response to climate variations in tropical ecosystems. We further find that none of a suite of ten contemporary terrestrial biosphere models captures these ENSO-phase-dependent responses, highlighting a key uncertainty in modeling climate impacts on the future of the global land carbon sink.