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Achieving global climate goals will require prodigious increases in low-carbon electricity generation, raising concerns about the scale of materials needed and associated environmental impacts. Here, we estimate power generation infrastructure demand for materials and related carbon-dioxide-equivalent (CO2eq) emissions from 2020 to 2050 across 75 different climate-energy scenarios and explore the impact of climate and technology choices upon material demand and carbon emitted. Material demands increase but cumulatively do not exceed geological reserves. However, annual production of neodymium (Nd), dysprosium (Dy), tellurium (Te), fiberglass, and solar-grade polysilicon may need to grow considerably. Cumulative CO2emissions related to materials for electricity infrastructure may be substantial (4–29 Gt CO2eq in 1.5°C scenarios) but consume only a minor share of global carbon budgets (1%–9% of a 320 Gt CO2eq 1.5°C 66% avoidance budget). Our results highlight how technology choices and mitigation scenarios influence the large quantities of materials mobilized during a future power sector decarbonization.

On 22 September 2020, within the backdrop of the COVID-19 global pandemic, China announced its climate goal for peak carbon emissions before 2030 and to reach carbon neutrality before 2060. This carbon-neutral goal is generally considered to cover all anthropogenic greenhouse gases. The planning effort is now in full swing in China, but the pathway to decarbonization is unclear. The needed transition towards non-fossil fuel energy and its impact on China and the world may be more profound than its reform and development over the past 40 years, but the challenges are enormous. Analysis of four representative scenarios shows significant differences in achieving the carbon-neutral goal, particularly the contribution of non-fossil fuel energy sources. The high target values for nuclear, wind, and bioenergy have approached their corresponding resource limitations, with solar energy being the exception, suggesting solar's critical role. We also found that the near-term policies that allow for a gradual transition, followed by more drastic changes after 2030, can eventually reach the carbon-neutral goal and lead to less of a reduction in cumulative emissions, thus inconsistent with the IPCC 1.5°C scenario. The challenges and prospects are discussed in the historical context of China's socio-economic reform, globalization, international collaboration, and development.

The sixth and latest IPCC assessment weights climate models according to how well they reproduce other evidence. Now the rest of the community should do the same.

The Paris Agreement introduced an ambitious goal of limiting warming to 1.5 °C above pre-industrial levels. Here we combine a review of modelled pathways and literature on mitigation strategies, and develop a land-sector roadmap of priority measures and regions that can help to achieve the 1.5 °C temperature goal. Transforming the land sector and deploying measures in agriculture, forestry, wetlands and bioenergy could feasibly and sustainably contribute about 30%, or 15 billion tonnes of carbon dioxide equivalent (GtCO2e) per year, of the global mitigation needed in 2050 to deliver on the 1.5 °C target, but it will require substantially more effort than the 2 °C target. Risks and barriers must be addressed and incentives will be necessary to scale up mitigation while maximizing sustainable development, food security and environmental co-benefits.

Stop using the worst-case scenario for climate warming as the most likely outcome — more-realistic baselines make for better policy.

Analysis of climate pledges by nations at the COP26 meeting indicates that such commitments could ensure that global warming does not exceed 2 ºC before 2100 — but only if backed up by short-term policies.

Tipping elements are components of the Earth system which may respond nonlinearly to anthropogenic climate change by transitioning toward substantially different long‐term states upon passing key thresholds or “tipping points.” In some cases, such changes could produce additional greenhouse gas emissions or radiative forcing that could compound global warming. Improved understanding of tipping elements is important for predicting future climate risks and their impacts. Here we review mechanisms, predictions, impacts, and knowledge gaps associated with 10 notable Earth system components proposed to be tipping elements. We evaluate which tipping elements are approaching critical thresholds and whether shifts may manifest rapidly or over longer timescales. Some tipping elements have a higher risk of crossing tipping points under middle‐of‐the‐road emissions pathways and will possibly affect major ecosystems, climate patterns, and/or carbon cycling within the 21st century. However, literature assessing different emissions scenarios indicates a strong potential to reduce impacts associated with many tipping elements through climate change mitigation. The studies synthesized in our review suggest most tipping elements do not possess the potential for abrupt future change within years, and some proposed tipping elements may not exhibit tipping behavior, rather responding more predictably and directly to the magnitude of forcing. Nevertheless, uncertainties remain associated with many tipping elements, highlighting an acute need for further research and modeling to better constrain risks. In recent years, discussions of climate change have shown growing interest in “tipping elements” of the Earth system, also imprecisely referred to as “tipping points.” This refers to Earth system components like the tropical rainforests of Amazonia or the Greenland and Antarctic ice sheets which may exhibit large‐scale, long‐term changes upon reaching critical global warming, greenhouse gas, or other thresholds. Once such thresholds are passed, some tipping elements could in turn produce additional greenhouse gas emissions or change the Earth's energy balance in ways that moderately reinforce warming. In this review, we summarize the current state of scientific knowledge on 10 systems that some have referred to as potential tipping elements of the climate system. We describe the mechanisms important to each system, highlight the response of these systems to climate change so far, and explain the dynamics of potential future changes that these systems could undergo in response to further climate change. Overall, even considering remaining scientific uncertainties, tipping elements will influence future climate change and may involve major impacts on ecosystems, climate patterns, and the carbon cycle starting later this century. Aggressive efforts to stabilize climate change could significantly reduce such impacts. Many tipping elements have uncertain thresholds, which could be crossed this century if human emissions and impacts remain unabatedMany tipping elements significant to global climate may exhibit slower onset behavior, responding to climate forcing over a century or moreEmissions pathways and climate model uncertainties may dominate over tipping elements in determining overall multi‐century warming Many tipping elements have uncertain thresholds, which could be crossed this century if human emissions and impacts remain unabated Many tipping elements significant to global climate may exhibit slower onset behavior, responding to climate forcing over a century or more Emissions pathways and climate model uncertainties may dominate over tipping elements in determining overall multi‐century warming

Numerous inhomogeneities including station moves, instrument changes, and time of observation changes in the U.S. Historical Climatological Network (USHCN) complicate the assessment of long-term temperature trends. Detection and correction of inhomogeneities in raw temperature records have been undertaken by NOAA and other groups using automated pairwise neighbor comparison approaches, but these have proven controversial due to the large trend impact of homogenization in the United States. The new U.S. Climate Reference Network (USCRN) provides a homogenous set of surface temperature observations that can serve as an effective empirical test of adjustments to raw USHCN stations. By comparing nearby pairs of USHCN and USCRN stations, we find that adjustments make both trends and monthly anomalies from USHCN stations much more similar to those of neighboring USCRN stations for the period from 2004 to 2015 when the networks overlap. These results improve our confidence in the reliability of homogenized surface temperature records. The USCRN allows us to assess the efficacy of temperature data homogenization when networks overlapHomogenization makes stations more similar in trend and anomalies to proximate USCRN stationsVariation in trends over distance much more similar to USCRN posthomogenization

The level of agreement between climate model simulations and observed surface temperature change is a topic of scientific and policy concern. While the Earth system continues to accumulate energy due to anthropogenic and other radiative forcings, estimates of recent surface temperature evolution fall at the lower end of climate model projections. Global mean temperatures from climate model simulations are typically calculated using surface air temperatures, while the corresponding observations are based on a blend of air and sea surface temperatures. This work quantifies a systematic bias in model‐observation comparisons arising from differential warming rates between sea surface temperatures and surface air temperatures over oceans. A further bias arises from the treatment of temperatures in regions where the sea ice boundary has changed. Applying the methodology of the HadCRUT4 record to climate model temperature fields accounts for 38% of the discrepancy in trend between models and observations over the period 1975–2014. There is a systematic bias in model‐observation comparisons from blending air and sea temperaturesA further bias arises from using anomalies in regions where the sea ice boundary has changedCorrecting these accounts for a quarter to half of the discrepancy between models and observations

The authors comment on the demand by climate change skeptics to release electronic mail (email) messages amidst allegations that scientists are manipulating data and suppressing critics. Topics covered include emails offering materials that can be taken out of context to give a misleading impression, comparing climate change data with observations and to replicate it by experiment as a real test of claim and experimental replication, not a political investigation as the best way to verify data.

An analysis of the record of sea surface temperature reveals that some climate variations that are thought to have occurred in the North Atlantic and the North Pacific oceans are an artefact of changes in measurement approaches. Adjustments to measurements of sea surface temperature.

Retrospectively comparing future model projections to observations provides a robust and independent test of model skill. Here we analyze the performance of climate models published between 1970 and 2007 in projecting future global mean surface temperature (GMST) changes. Models are compared to observations based on both the change in GMST over time and the change in GMST over the change in external forcing. The latter approach accounts for mismatches in model forcings, a potential source of error in model projections independent of the accuracy of model physics. We find that climate models published over the past five decades were skillful in predicting subsequent GMST changes, with most models examined showing warming consistent with observations, particularly when mismatches between model‐projected and observationally estimated forcings were taken into account. Climate models provide an important way to understand future changes in the Earth's climate. In this paper we undertake a thorough evaluation of the performance of various climate models published between the early 1970s and the late 2000s. Specifically, we look at how well models project global warming in the years after they were published by comparing them to observed temperature changes. Model projections rely on two things to accurately match observations: accurate modeling of climate physics and accurate assumptions around future emissions of CO2and other factors affecting the climate. The best physics‐based model will still be inaccurate if it is driven by future changes in emissions that differ from reality. To account for this, we look at how the relationship between temperature and atmospheric CO2(and other climate drivers) differs between models and observations. We find that climate models published over the past five decades were generally quite accurate in predicting global warming in the years after publication, particularly when accounting for differences between modeled and actual changes in atmospheric CO2and other climate drivers. This research should help resolve public confusion around the performance of past climate modeling efforts and increases our confidence that models are accurately projecting global warming. Evaluation of uninitialized multidecadal climate model future projection performance provides a concrete test of model skillThe quasi‐linear relationship between model/observed forcings and temperature change is used to control for errors in projected forcingModel simulations published between 1970 and 2007 were skillful in projecting future global mean surface warming