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Deforestation is associated with increased atmospheric CO2 and alterations to the surface energy and mass balances that can lead to local and global climate changes. Previous modelling studies show that the global surface air temperature (SAT) response to deforestation depends on latitude, with most simulations showing that high latitude deforestation results in cooling, low latitude deforestation causes warming and that the mid latitude response is mixed. These earlier conclusions are based on simulated large scal land cover change, with complete removal of trees from whole latitude bands. Using a global climate model we examine the effects of removing fractions of 5% to 100% of forested areas in the high, mid and low latitudes. All high latitude deforestation scenarios reduce mean global SAT, the opposite occurring for low latitude deforestation, although a decrease in SAT is simulated over low latitude deforested areas. Mid latitude SAT response is mixed. In all simulations deforested areas tend to become drier and have lower SAT, although soil temperatures increase over deforested mid and low latitude grid cells. For high latitude deforestation fractions of 45% and above, larger net primary productivity, in conjunction with colder and drier conditions after deforestation cause an increase in soil carbon large enough to produce a net decrease of atmospheric CO2. Our results reveal the complex interactions between soil carbon dynamics and other climate subsystems in the energy partition responses to land cover change.

Forest harvesting induces a step change in the climatic variables (temperature and moisture), that control carbon dioxide (CO2) production arising from soil organic matter decomposition within soils. Efforts to examine these vertically complex relationships in situ within soil profiles are lacking. In this study we examined how the climatic controls on CO2 production change within vertically distinct layers of the soil profile in intact and clearcut forest soils of a humid temperate forest system of Atlantic Canada. We measured mineral soil temperature (0, 5, 10, 20, 50 and 100 cm depth) and moisture (0-15 cm and 30-60 cm depth), along with CO2 surface efflux and subsurface concentrations (0, 2.5, 5, 10, 20, 35, 50, 75 and 100 cm depth) in 1 m deep soil pits at 4 sites represented by two forest-clearcut pairs over a complete annual cycle. We examined relationships between surface efflux at each site, and soil heat, moisture, and mineral soil CO2 production. Following clearcut harvesting we observed increases in temperature through depth (1-2°C annually; often in excess of 4°C in summer and spring), alongside increases in soil moisture (30%). We observed a systematic breakdown in the expected exponential relationship between CO2 production and heat with mineral soil depth, consistent with an increase in the role moisture plays in constraining CO2 production. These findings should be considered in efforts to model and characterize mineral soil organic matter decomposition in harvested forest soils.

Subsurface temperature profiles measured in boreholes are one of the important archives of paleoclimate data for reconstructing the climate of the past 2000 years. Subsurface temperatures are a function of past ground surface temperatures (GST), however GSTs are influenced both by changes in land-use and changes in regional climate. Thus the history of deforestation at borehole sampling locations represents a potential uncertainty in the reconstructed temperature history at the site. Here a fully coupled Earth system model is used estimate the magnitude of the subsurface temperature anomaly from deforestation events from a global perspective. The model simulations suggest that warming of the ground surface is the dominant response to deforestation, consistent with the limited field data that exist. The magnitude of the temperature anomaly varies by environment with a global average anomaly of 0.85 °C with a range of −0.48 °C to 1.78 °C. The warming originates from a reduction in the efficiency of turbulent energy flux to the atmosphere overcompensating an increase in albedo. Overall our simulations suggest that deforestation has a large impact on subsurface temperatures for centuries following deforestation and thus GST reconstructions should take into account previous deforestation events.

The energy imbalance at the top of the atmosphere over the last century has caused an accumulation of heat within the ocean, the continental subsurface, the atmosphere and the cryosphere. Although ∼90 % of the energy gained by the climate system has been stored in the ocean, the other components of the Earth heat inventory cannot be neglected due to their influence on associated climate processes dependent on heat storage, such as sea level rise and permafrost stability. However, there has not been a comprehensive assessment of the heat inventory within global climate simulations yet. Here, we explore the ability of 30 advanced general circulation models (GCMs) from the fifth phase of the Coupled Model Intercomparison Project (CMIP5) to simulate the distribution of heat within the Earth's energy reservoirs for the period 1972–2005 of the Common Era. CMIP5 GCMs simulate an average heat storage of 247±172 ZJ (96±4 % of total heat content) in the ocean, 5±9 ZJ (2±3 %) in the continental subsurface, 2±3 ZJ (1±1 %) in the cryosphere and 2±2 ZJ (1±1 %) in the atmosphere. However, the CMIP5 ensemble overestimates the ocean heat content by 83 ZJ and underestimates the continental heat storage by 9 ZJ and the cryosphere heat content by 5 ZJ, in comparison with recent observations. The representation of terrestrial ice masses and the continental subsurface, as well as the response of each model to the external forcing, should be improved in order to obtain better representations of the Earth heat inventory and the partition of heat among climate subsystems in global transient climate simulations.

Several paleoclimatic reconstructions have indicated that the mid-Holocene (6,000 years before present) was characterized by stronger east-west temperature contrast and lower El Niño Southern Oscillation (ENSO) variability relative to the present day. While climate models show a reduction in ENSO variability, they underestimate this reduction compared to paleoclimate reconstructions. Further, the drivers behind these changes remain unclear. Here we use five global climate models to show that incorporating vegetation changes over northern Africa during the mid-Holocene amplifies the orbitally-driven strengthening of the West African Monsoon, warms the tropical north Atlantic, and nudges it to an Atlantic Niño-like mean state. Changes over the Atlantic lead to a La Niña-like mean state over the tropical Pacific, with reductions in interannual variability amplified by up to 18% in the Niño3.4 region due to the Green Sahara alone. Our work highlights the importance of the Atlantic influence on ENSO and provides paleoclimatic evidence for this synergistic teleconnection. Incorporating mid-Holocene vegetation changes over northern Africa amplifies Atlantic-driven teleconnections that shift the tropical Pacific toward a La Niña-like mean state and reduce El Niño-Southern Oscillation variability by up to 18%, according to simulations using global climate models.

Temperature changes at the Earthʼs surface propagate and are recorded underground as perturbations to the equilibrium thermal regime associated with the heat flow from the Earthʼs interior. Borehole climatology is concerned with the analysis and interpretation of these downward propagating subsurface temperature anomalies in terms of surface climate. Proper determination of the steady-state geothermal regime is therefore crucial because it is the reference against which climate-induced subsurface temperature anomalies are estimated. Here, we examine the effects of data noise on the determination of the steady-state geothermal regime of the subsurface and the subsequent impact on estimates of ground surface temperature (GST) history and heat gain. We carry out a series of Monte Carlo experiments using 1000 Gaussian noise realizations and depth sections of 100 and 200 m as for steady-state estimates depth intervals, as well as a range of data sampling intervals from 10 m to 0.02 m. Results indicate that typical uncertainties for 50 year averages are on the order of 0.02 K for the most recent 100 year period. These uncertainties grow with decreasing sampling intervals, reaching about 0.1 K for a 10 m sampling interval under identical conditions and target period. Uncertainties increase for progressively older periods, reaching 0.3 K at 500 years before present for a 10 m sampling interval. The uncertainties in reconstructed GST histories for the Northern Hemisphere for the most recent 50 year period can reach a maximum of in some areas. We suggest that continuous logging should be the preferred approach when measuring geothermal data for climate reconstructions, and that for those using the International Heat Flow Commission database for borehole climatology, the steady-state thermal conditions should be estimated from boreholes as deep as possible and using a large fitting depth range (∼100 m).

An assessment of the soil and bedrock thermal structure of the Sierra de Guadarrama, in central Spain, is provided using subsurface and ground surface temperature data coming from four deep (20 m) monitoring profiles belonging to the Guadarrama Monitoring Network (GuMNet) and two shallow profiles (1 m) from the Spanish Meteorology Service (Agencia Estatal de Meteorología, AEMET) covering the time spans of 2015– 2021 and 1989–2018, respectively. An evaluation of air and ground surface temperature coupling showed that soil insulation due to snow cover is the main source of seasonal decoupling, being especially relevant in winter at high-altitude sites. Temperature propagation in the subsurface was characterized by assuming a heat conductive regime by considering apparent thermal diffusivity values derived from the amplitude attenuation and phase shift of the annual cycle with depth. This methodology was further extended to consider the attenuation of all harmonics in the spectral domain, which allowed for analysis of thermal diffusivity from high-frequency changes in the soil near the surface at short timescales. For the deep profiles, the apparent thermal diffusivity ranges from 1 to 1.3×10−6 m2 s −1, which is consistent with values for gneiss and granite, the major bedrock components in the Sierra de Guadarrama. However, thermal diffusivity is lower and more heterogeneous in the soil layers close to the surface (0.4–0.8 × 10−6 m2 s −1). An increase in diffusivity with depth was observed that was generally larger in the soil–bedrock transition at 4–8 m depth. The outcomes are relevant for the understanding of soil thermodynamics in relation to other soil properties. Results with the spectral method suggest that changes in near-surface thermal diffusivity are related to changes in soil moisture content, which makes it a potential tool to gain information about soil drought and water resource availability from soil temperature data.

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.

Human-induced atmospheric composition changes cause a radiative imbalance at the top of the atmosphere which is driving global warming. This Earth energy imbalance (EEI) is the most critical number defining the prospects for continued global warming and climate change. Understanding the heat gain of the Earth system – and particularly how much and where the heat is distributed – is fundamental to understanding how this affects warming ocean, atmosphere and land; rising surface temperature; sea level; and loss of grounded and floating ice, which are fundamental concerns for society. This study is a Global Climate Observing System (GCOS) concerted international effort to update the Earth heat inventory and presents an updated assessment of ocean warming estimates as well as new and updated estimates of heat gain in the atmosphere, cryosphere and land over the period 1960–2018. The study obtains a consistent long-term Earth system heat gain over the period 1971–2018, with a total heat gain of 358±37 ZJ, which is equivalent to a global heating rate of 0.47±0.1 W m−2. Over the period 1971–2018 (2010–2018), the majority of heat gain is reported for the global ocean with 89 % (90 %), with 52 % for both periods in the upper 700 m depth, 28 % (30 %) for the 700–2000 m depth layer and 9 % (8 %) below 2000 m depth. Heat gain over land amounts to 6 % (5 %) over these periods, 4 % (3 %) is available for the melting of grounded and floating ice, and 1 % (2 %) is available for atmospheric warming. Our results also show that EEI is not only continuing, but also increasing: the EEI amounts to 0.87±0.12 W m−2 during 2010–2018. Stabilization of climate, the goal of the universally agreed United Nations Framework Convention on Climate Change (UNFCCC) in 1992 and the Paris Agreement in 2015, requires that EEI be reduced to approximately zero to achieve Earth's system quasi-equilibrium. The amount of CO2 in the atmosphere would need to be reduced from 410 to 353 ppm to increase heat radiation to space by 0.87 W m−2, bringing Earth back towards energy balance. This simple number, EEI, is the most fundamental metric that the scientific community and public must be aware of as the measure of how well the world is doing in the task of bringing climate change under control, and we call for an implementation of the EEI into the global stocktake based on best available science. Continued quantification and reduced uncertainties in the Earth heat inventory can be best achieved through the maintenance of the current global climate observing system, its extension into areas of gaps in the sampling, and the establishment of an international framework for concerted multidisciplinary research of the Earth heat inventory as presented in this study. This Earth heat inventory is published at the German Climate Computing Centre (DKRZ, https://www.dkrz.de/, last access: 7 August 2020) under the DOI https://doi.org/10.26050/WDCC/GCOS_EHI_EXP_v2 (von Schuckmann et al., 2020).

A number of studies have assessed possible climate change impacts on the Lyme disease vector, . However, most have used surface air temperature from only one climate model simulation and/or one emission scenario, representing only one possible climate future. We quantified effects of different Representative Concentration Pathway (RCP) and climate model outputs on the projected future changes in the basic reproduction number (R ) of to explore uncertainties in future R estimates. We used surface air temperature generated by a complete set of General Circulation Models from the Coupled Model Intercomparison Project Phase 5 (CMIP5) to hindcast historical (1971-2000), and to forecast future effects of climate change on the R of for the periods 2011-2040 and 2041-2070. Increases in the multimodel mean values estimated for both future periods, relative to 1971-2000, were statistically significant under all RCP scenarios for all of Nova Scotia, areas of New Brunswick and Quebec, Ontario south of 47°N, and Manitoba south of 52°N. When comparing RCP scenarios, only the estimated R mean values between RCP6.0 and RCP8.5 showed statistically significant differences for any future time period. Our results highlight the potential for climate change to have an effect on future Lyme disease risk in Canada even if the Paris Agreement's goal to keep global warming below 2°C is achieved, although mitigation reducing emissions from RCP8.5 levels to those of RCP6.0 or less would be expected to slow tick invasion after the 2030s. https://doi.org/10.1289/EHP57.