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Understanding the response of the Earth system to varying concentrations of carbon dioxide (CO2) is critical for projecting possible future climate change and for providing insight into mitigation and adaptation strategies in the near future. In this study, we generate a dataset by conducting an experiment involving carbon dioxide removal (CDR)—a potential way to suppress global warming—using the Chinese Academy of Sciences Earth System Model version 2.0 (CAS-ESM2.0). A preliminary evaluation is provided. The model is integrated from 200–340 years as a 1% yr−1 CO2 concentration increase experiment, and then to ~478 years as a carbon dioxide removal experiment until CO2 returns to its original value. Finally, another 80 years is integrated in which CO2 is kept constant. Changes in the 2-m temperature, precipitation, sea surface temperature, ocean temperature, Atlantic meridional overturning circulation (AMOC), and sea surface height are all analyzed. In the ramp-up period, the global mean 2-m temperature and precipitation both increase while the AMOC weakens. Values of all the above variables change in the opposite direction in the ramp-down period, with a delayed peak relative to the CO2 peak. After CO2 returns to its original value, the global mean 2-m temperature is still ~1 K higher than in the original state, and precipitation is ~0.07 mm d−1 higher. At the end of the simulation, there is a ~0.5°C increase in ocean temperature and a 1 Sv weakening of the AMOC. Our model simulation produces similar results to those of comparable experiments previously reported in the literature. [ABSTRACT FROM AUTHOR]

The northern-high-latitude permafrost contains almost twice the carbon content of the atmosphere, and it is widely considered to be a non-linear and tipping element in the earth's climate system under global warming. Solar geoengineering is a means of mitigating temperature rise and reduces some of the associated climate impacts by increasing the planetary albedo; the permafrost thaw is expected to be moderated under slower temperature rise. We analyze the permafrost response as simulated by five fully coupled earth system models (ESMs) and one offline land surface model under four future scenarios; two solar geoengineering scenarios (G6solar and G6sulfur) based on the high-emission scenario (ssp585) restore the global temperature from the ssp585 levels to the moderate-mitigation scenario (ssp245) levels via solar dimming and stratospheric aerosol injection. G6solar and G6sulfur can slow the northern-high-latitude permafrost degradation but cannot restore the permafrost states from ssp585 to those under ssp245. G6solar and G6sulfur tend to produce a deeper active layer than ssp245 and expose more thawed soil organic carbon (SOC) due to robust residual high-latitude warming, especially over northern Eurasia. G6solar and G6sulfur preserve more SOC of 4.6 ± 4.6 and 3.4 ± 4.8 Pg C (coupled ESM simulations) or 16.4 ± 4.7 and 12.3 ± 7.9 Pg C (offline land surface model simulations), respectively, than ssp585 in the northern near-surface permafrost region. The turnover times of SOC decline slower under G6solar and G6sulfur than ssp585 but faster than ssp245. The permafrost carbon–climate feedback is expected to be weaker under solar geoengineering. [ABSTRACT FROM AUTHOR]

The atmospheric carbon dioxide (CO2) concentration has been increasing rapidly since the Industrial Revolution, which has led to unequivocal global warming and crucial environmental change. It is extremely important to investigate the interactions among atmospheric CO2, the physical climate system, and the carbon cycle of the underlying surface for a better understanding of the Earth system. Earth system models are widely used to investigate these interactions via coupled carbon-climate simulations. The Chinese Academy of Sciences Earth System Model version 2 (CAS-ESM2.0) has successfully fixed a two-way coupling of atmospheric CO2 with the climate and carbon cycle on land and in the ocean. Using CAS-ESM2.0, we conducted a coupled carbon-climate simulation by following the CMIP6 proposal of a historical emissions-driven experiment. This paper examines the modeled CO2 by comparison with observed CO2 at the sites of Mauna Loa and Barrow, and the Greenhouse Gases Observing Satellite (GOSAT) CO2 product. The results showed that CAS-ESM2.0 agrees very well with observations in reproducing the increasing trend of annual CO2 during the period 1850–2014, and in capturing the seasonal cycle of CO2 at the two baseline sites, as well as over northern high latitudes. These agreements illustrate a good ability of CAS-ESM2.0 in simulating carbon-climate interactions, even though uncertainties remain in the processes involved. This paper reports an important stage of the development of CAS-ESM with the coupling of carbon and climate, which will provide significant scientific support for climate research and China's goal of carbon neutrality. [ABSTRACT FROM AUTHOR]

Terrestrial ecosystems are an important part of Earth systems, and they are undergoing remarkable changes in response to global warming. This study investigates the response of the terrestrial vegetation distribution and carbon fluxes to global warming by using the new dynamic global vegetation model in the second version of the Chinese Academy of Sciences (CAS) Earth System Model (CAS-ESM2). We conducted two sets of simulations, a present-day simulation and a future simulation, which were forced by the present-day climate during 1981–2000 and the future climate during 2081–2100, respectively, as derived from RCP8.5 outputs in CMIP5. CO2 concentration is kept constant in all simulations to isolate CO2-fertilization effects. The results show an overall increase in vegetation coverage in response to global warming, which is the net result of the greening in the mid-high latitudes and the browning in the tropics. The results also show an enhancement in carbon fluxes in response to global warming, including gross primary productivity, net primary productivity, and autotrophic respiration. We found that the changes in vegetation coverage were significantly correlated with changes in surface air temperature, reflecting the dominant role of temperature, while the changes in carbon fluxes were caused by the combined effects of leaf area index, temperature, and precipitation. This study applies the CAS-ESM2 to investigate the response of terrestrial ecosystems to climate warming. Even though the interpretation of the results is limited by isolating CO2-fertilization effects, this application is still beneficial for adding to our understanding of vegetation processes and to further improve upon model parameterizations. [ABSTRACT FROM AUTHOR]

Two parallel sets of numerical experiments (an ozone-hole simulation and a non-ozone-hole simulation) were performed to investigate the effect of ozone depletion on surface temperature change using the second spectral version of the Flexible Global Ocean-Atmosphere-Land System model (FGOALS-s2), focusing on the eastern Antarctica (EA) continent in austral summer. First, we evaluated the ability of the model to simulate the EA surface cooling, and found the model can successfully reproduce the cooling trend of the EA surface, as well as the circulation change circling the South Pole in the past 30 years. Second, we compared the two experiments and discovered that the ozone depletion causes the cooling trend and strengthens the circumpolar westerly flow. We further investigated the causes of the EA surface cooling associated with the ozone hole and found two major contributors. The first is the ozone-hole direct radiation effect (DRE) upon the surface that happens because the decrease of the downward longwave (LW) radiation overcomes the increase of the downward shortwave (SW) radiation under clear sky. The second is the cloud radiation effect (CRE) induced by ozone depletion, which happens because the decreased downward SW radiation overcomes the increased downward LW radiation in the case of increased cloud. Although the CRE is theoretically opposite to the DRE, their final net effect makes comparable contributions to the EA surface cooling. Compared with the surface radiation budget, the surface heat flux budgets have a much smaller contribution. We additionally note that the CRE is basically ascribed to the circulation change. [ABSTRACT FROM AUTHOR]

The dust emission parameterization in the Chinese Academy of Sciences Earth System Model version 2 (CAS‐ESM2) is described with emphasis on the implementation process and simulations of global dust cycle and East Asia dust event statistics. The parameterization is based on the scheme of Shao (2004; http://doi.org/10.1029/2003JD004372) which considers two major dust emission mechanisms, namely, saltation bombardment and aggregation disintegration. Shao (2004; http://doi.org/10.1029/2003JD004372) scheme was well tested against field observations and has been widely used in regional dust modeling. Here this scheme is implemented into a global climate model for the first time and thus provides an independent solution for simulating global dust emissions. With this scheme, CAS‐ESM2 reasonably simulates the main dust emission regions in the Earth and reproduces the observations of dust deposition flux and surface dust concentrations at most stations. Compared to the synoptic records of dust events, the model also captures the general patterns and seasonal variations of dust activities in East Asia. However, the model underestimates the frequency of strong dust events (instantaneous surface dust concentrations >1,000 μg m−3) due to the weaker surface winds simulated by the model. The model tends to simulate much weaker and longer‐lasting dust events in Eastern Sources (35–49°N, 94–126.5°E) of northern China, suggesting the weaker and slower‐moving synoptic weather systems associated with dust events in the model. Overall CAS‐ESM2 performs well in simulating the key aspects of global dust distribution and East Asian dust events, yet some biases remain to be improved. Plain Language Summary: Dust emitted from the bare soil is an important aerosol type, and dust cycle links the various components of Earth System including atmosphere, land, and oceans. Therefore, dust emission is an essential part of Earth system. In this study, we develop a dust emission module for Chinese Academy of Sciences Earth System Model version 2 (CAS‐ESM2) to simulate the global dust emission. The module incorporates advanced mechanisms of dust emission physics. The results show that with this module, CAS‐ESM2 reproduces well the global distribution of dust aerosol. We also evaluate the model's ability in simulating the individual dust events in terms of dust event frequency, intensity, and duration. We find that the model can reproduce the key regions of dust emission and the highest frequency of dust event in spring in East Asia. However, because the model underestimates surface wind speeds, it simulates weaker and longer‐lasting dust events. Overall CAS‐ESM2 provides a new and promising solution to simulate global dust emission, although there are still some biases for further improvements. Key Points: Chinese Academy of Sciences Earth System Model version 2 (CAS‐ESM2) with a physically based dust emission scheme provides a new and promising solution to simulate global dust emissionsCAS‐ESM2 captures the main global dust emission regions and reproduces observed dust depositions and surface dust concentrationsThe weaker dust events are compensated by overestimated dust event frequency and duration to produce reasonable means in East Asia [ABSTRACT FROM AUTHOR]

Atmospheric aerosols can change vegetation photosynthesis through the effects of aerosols on radiation, which will affect the peak carbon dioxide emissions and carbon neutrality at global scales. In this study, we quantify the aerosol-induced direct radiation forcing (ADRF) in China from 2001 to 2014 based on the radiation flux simulation used by the Fu-Liou radiation transfer model under with-aerosols and no-aerosols scenarios. Using the radiation simulation results, we modify the atmospheric forcing datasets to drive Community Land Model 4.5 (CLM4.5) to gain the changes in carbon fluxes in China caused by ADRF. The results show that these two models are accurate in estimating radiation (R2 = 0.78–0.88) and carbon fluxes (R2 = 0.73–0.75) in China. High levels of ADRFs were captured in China, especially with increasing diffuse fraction, resulting in the diffusing fertilization effect occurring in most areas of China. The ADRF can increase cumulative gross primary productivity (GPP) and total ecosystem respiration (ER) by 3.20 gC m−2 and 5.13 gC m−2 per year, respectively. From 2001 to 2014, the diffusing fertilization effects experienced trends of increasing first and then decreasing. However, ADRFs in some regions of China show negative effects on carbon fluxes due to vulnerable vegetation functional types and high aerosol loading. The ADRF will also enable soil temperature decreases and volumetric soil water increases, which is closely related to changes in carbon fluxes. Meanwhile, due to changes in soil water and heat conditions, N 2 O and CH 4 production will also be disturbed, and ADRF increases the global warming potential (GWP) for both greenhouse gases. This phenomenon indicated that atmospheric aerosol pollution control is far-reaching significance for peaking carbon dioxide emissions before 2030. • Fu-Liou and CLM4.5 model can simulate radiation fluxes and carbon fluxes accurately in China; •Aerosol-induced direct radiative forcing can increase cumulative gross primary productivity and total ecosystem respiration in China; •Responses of carbon fluxes to changes of soil hydrothermal conditions caused by aerosol-induced direct radiative forcing is significant in most regional ecosystems in China; •Aerosol-induced radiative forcing could increase the N 2 O and CH 4 global warming potential in China from 2001 to 2014. [ABSTRACT FROM AUTHOR]

The second version of Chinese Academy of Sciences Earth System Model (CAS‐ESM 2) is described with emphasis on the development process, strength and weakness, and climate sensitivities in simulations of the Coupled Model Intercomparison Project (CMIP6) DECK experiments. CAS‐ESM 2 was built as a numerical model to simulate both the physical climate system as well as atmospheric chemistry and carbon cycle. It is a newcomer in the international modeling community to provide sufficiently independent solutions of climate simulations from those of other models. Performances of the model in simulating the basic states of the radiation budget of the atmosphere and ocean, precipitation, circulations, variabilities, and the twentieth century warming are presented. Model biases and their possible causes are discussed. Strength includes horizontal heat transport in the atmosphere and oceans, vertical profile of the Atlantic Meridional Overturning Circulation; weakness includes the double intertropical convergence zone (ITCZ) and stronger amplitude of the El Niño–Southern Oscillation (ENSO) that are also common in many other models. The simulated the twentieth century warming shares a similar discrepancy with observations as in several other models—less warming in the 1920s and stronger cooling in the 1960s than in observation—at the time when there was a steep increase of anthropogenic aerosols. As a result, the twentieth century warming is about 60% of the observed warming despite that the model simulated a similar slope of warming trend after 1980 to observation. The model has an equilibrium climate sensitivity of 3.4 K with a positive cloud feedback from the shortwave radiation. Plain Language Summary: This paper describes the second version of Chinese Academy of Sciences Earth System Model (CAS‐ESM 2) along with simulation results from the Coupled Model Intercomparison Project (CMIP6) DECK experiments. Performances of the model in simulating the radiation budget of the atmosphere and ocean, precipitation, circulations, variabilities, and the twentieth century warming are presented. The simulated the twentieth century warming shares a similar discrepancy with observations as in several other models—less warming in the 1920s and stronger cooling in the 1960s than in observation—at the time when there was a steep increase of anthropogenic aerosols. As a result, the twentieth century warming is about 60% of the observed warming despite that the model simulated a similar slope of warming trend after 1980 to observation. Key Points: The second version of Chinese Academy of Sciences Earth System Model (CAS‐ESM 2) is describedStrength and weakness of the model simulations from the CMIP6 DECK experiments are described along possible causesThe model has an equilibrium climate sensitivity of 3.4 K with a positive cloud feedback from the shortwave radiation [ABSTRACT FROM AUTHOR]

Predicting the changes in teleconnection patterns and related hydroclimate extremes can provide vital information necessary to adapt to the effects of the El Niño–Southern Oscillation (ENSO). This study uses the outputs of global climate models to assess the changes in ENSO-related dry/wet patterns and the frequency of severe dry/wet events. The results show anomalous precipitation responding asymmetrically to La Niña and El Niño, indicating the teleconnections may not simply be strengthened. A "dry to drier, wet to wetter" annual anomalous precipitation pattern was projected during La Niña phases in some regions, with drier conditions over southern North America, southern South America, and southern central Asia, and wetter conditions in Southeast Asia and Australia. These results are robust, with agreement from the 26 models and from a subset of 8 models selected for their good performance in capturing observed patterns. However, we did not observe a similar strengthening of anomalous precipitation during future El Niño phases, for which the uncertainties in the projected influences are large. Under the RCP4.5 emissions scenario, 45 river basins under El Niño conditions and 39 river basins under La Niña conditions were predicted to experience an increase in the frequency of severe dry events; similarly, 59 river basins under El Niño conditions and 61 river basins under La Niña conditions were predicted to have an increase in the frequency of severe wet events, suggesting a likely increase in the risk of floods. Our results highlight the implications of changes in ENSO patterns for natural hazards, disaster management, and engineering infrastructure. [ABSTRACT FROM AUTHOR]

This study investigates and compares soil moisture and hydrology projections of broadly used land models with permafrost processes and highlights the causes and impacts of permafrost zone soil moisture projections. Climate models project warmer temperatures and increases in precipitation (P) which will intensify evapotranspiration (ET) and runoff in land models. However, this study shows that most models project a long-term drying of the surface soil (0–20 cm) for the permafrost region despite increases in the net air–surface water flux (P -ET). Drying is generally explained by infiltration of moisture to deeper soil layers as the active layer deepens or permafrost thaws completely. Although most models agree on drying, the projections vary strongly in magnitude and spatial pattern. Land models tend to agree with decadal runoff trends but underestimate runoff volume when compared to gauge data across the major Arctic river basins, potentially indicating model structural limitations. Coordinated efforts to address the ongoing challenges presented in this study will help reduce uncertainty in our capability to predict the future Arctic hydrological state and associated land–atmosphere biogeochemical processes across spatial and temporal scales. [ABSTRACT FROM AUTHOR]

Rapid warming has led to an aggregated environmental degradation over the Tibetan Plateau (TP) in the last few decades, including accelerated glacier retreat, early snowmelt, permafrost degradation, and forest fire occurrence. Attribution of this warming in recent decades has mainly been focused on anthropogenic forcing. Yet, linkages to the Atlantic multidecadal variability (AMV), an essential part of the climate system causing decadal to centennial fluctuations of temperature, remains poorly understood for the TP, especially at long time scales. Using well-replicated tree-ring width records, we reconstructed 358 years of summer minimum temperature (MinT) of the whole TP. This reconstruction matches the recent warming signal recorded since the 1980s, and captures 63% of the variance in 1950–2005 instrumental records. A teleconnection from the North Atlantic to the TP is further identified based in observations and simulations with an atmospheric general circulation model (AGCM). We propose that half of the multidecadal variability of TP summer MinT can be explained by the AMV over the past three and a half centuries. Both observations and AGCM simulations indicate that the AMV warm phase induces a zonal dipole response in sea level pressure across the Atlantic–Eurasia region, with anomalously high surface pressure and corresponding downward atmospheric motion over the TP. We propose that the descending motion during warm AMV phases causes negative rainfall and positive temperature anomalies over the TP. Our findings highlight that the AMV plays a role in the multidecadal temperature variability over the TP. [ABSTRACT FROM AUTHOR]

The effects of heat stress are spatially heterogeneous owing to local variations in climate response, population density, and social conditions. Using global climate and impact models from the Inter-Sectoral Impact Model Intercomparison Project, our analysis shows that the frequency and intensity of heat events increase, especially in tropical regions (geographic perspective) and developing countries (national perspective), even with global warming held to the 1.5 °C target. An additional 0.5 °C increase to the 2 °C warming target leads to >15% of global land area becoming exposed to levels of heat stress that affect human health; almost all countries in Europe will be subject to increased fire danger, with the duration of the fire season lasting 3.3 days longer; 106 countries are projected to experience an increase in the wheat production-damage index. Globally, about 38%, 50%, 46%, 36%, and 48% of the increases in exposure to health threats, wildfire, crop heat stress for soybeans, wheat, and maize could be avoided by constraining global warming to 1.5 °C rather than 2 °C. With high emissions, these impacts will continue to intensify over time, extending to almost all countries by the end of the 21st century: >95% of countries will face exposure to health-related heat stress, with India and Brazil ranked highest for integrated heat-stress exposure. The magnitude of the changes in fire season length and wildfire frequency are projected to increase substantially over 74% global land, with particularly strong effects in the United States, Canada, Brazil, China, Australia, and Russia. Our study should help facilitate climate policies that account for international variations in the heat-related threats posed by climate change. • We assessed the influences of 1.5 °C and 2.0 °C warmings on the multiple sectors. • 0.5 °C less warming would help avoid ~38% of the health-related heat exposure. • 0.5 °C less warming would help avoid ~50% of the exposure to wildfire. • 0.5 °C less warming would help avoid ~48% of the maize-related heat exposure. • Developing countries are likely to experience greater exposure to heat extremes. [ABSTRACT FROM AUTHOR]

Highlights • Yield per hectare of sweet sorghum are influence by temperature and precipitation. • Xinjiang and Inner Mongolia are suitable for planting sweet sorghum. • The 2020 and 2050 biofuel goal can be satisfied by certain scenarios in this paper. • Climate change and land-use change are critical to energy crop development plan. Abstract Biofuel from energy crops will play an important role in supplying carbon-neutral fuel for the transport sector. However, there are large uncertainties regarding energy crop development and the energy crop potential and distribution need to be evaluated more comprehensively and systematically. In this study, we propose an integrated approach using the AquaCrop model, a geographic information system approach, and a scenario analysis and we conduct a land availability assessment with multiple factors including climate change, land use, soil, topography, regional crop management, and technological improvement to shed light on the potential production, distribution, and temporal-spatial variation of land suitable for sweet sorghum production in China. We evaluate a full range of spatial scales from 1-km resolution to a national assessment in four representative concentration pathways from 2010 to 2100. The results show that most provinces can plant sweet sorghum. The most suitable provinces for sweet sorghum production are Xinjiang, Heilongjiang, Jilin, Inner Mongolia, Yunnan, and Sichuan. The biofuel potential of sweet sorghum in high-slope farmland (0.30–0.73 EJ) and marginal land (11.98–15.18 EJ) can satisfy the biofuel goal in 2020 (0.12 EJ) and 2050 (6.70–8.60 EJ). Climate change and land-use change are critical factors influencing for the current implementation and long-term planning of energy crops in China. [ABSTRACT FROM AUTHOR]

Understanding the past variability in atmospheric moisture associated with global warming is essential for reducing the uncertainties in climate projections. Such understanding is especially necessary in the Asian monsoon region in the context of increasing anthropogenic forcing. Here, we average four tree-ring width chronologies from the southeastern Tibetan Plateau (TP) over their common intervals and reconstruct the variability in regional relative humidity (RH) from the previous May to the current March over 1751-2005. In contrast to the summer drying associated with centennial-scale warming and the weakening of the Asian summer monsoon, our RH reconstruction shows no significant centennial trend from the 1820s through the 2000s. This absence of a consistent signal is due to the combined effects of contrasting moisture trends during the monsoonal and non-monsoonal seasons, which are controlled by summer monsoon precipitation and local convective precipitation, respectively. The interannual and decadal variability of our RH reconstruction is modulated by El Niño-Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO); however, these links are unstable over time. Two rapid increases in moisture are found to have occurred around the 1820s and 1980s; the latter increase caused the variability in RH during the 1980s-2000s to be the largest over the entire reconstruction period. [ABSTRACT FROM AUTHOR]

In the past several decades, dynamic global vegetation models (DGVMs) have been the most widely used and appropriate tool at the global scale to investigate vegetation-climate interactions. At the Institute of Atmospheric Physics, a new version of DGVM (IAP-DGVM) has been developed and coupled to the Common Land Model (CoLM) within the framework of the Chinese Academy of Sciences’ Earth System Model (CAS-ESM). This work reports the performance of IAP-DGVM through comparisons with that of the default DGVM of CoLM (CoLM-DGVM) and observations. With respect to CoLMDGVM, IAP-DGVM simulated fewer tropical trees, more “needleleaf evergreen boreal tree” and “broadleaf deciduous boreal shrub”, and a better representation of grasses. These contributed to a more realistic vegetation distribution in IAP-DGVM, including spatial patterns, total areas, and compositions. Moreover, IAP-DGVM also produced more accurate carbon fluxes than CoLM-DGVM when compared with observational estimates. Gross primary productivity and net primary production in IAP-DGVM were in better agreement with observations than those of CoLM-DGVM, and the tropical pattern of fire carbon emissions in IAP-DGVM was much more consistent with the observation than that in CoLM-DGVM. The leaf area index simulated by IAP-DGVM was closer to the observation than that of CoLM-DGVM; however, both simulated values about twice as large as in the observation. This evaluation provides valuable information for the application of CAS-ESM, as well as for other model communities in terms of a comparative benchmark. [ABSTRACT FROM AUTHOR]

Water and carbon fluxes simulated by 12 Earth system models (ESMs) that participated in phase 5 of the Coupled Model Intercomparison Project (CMIP5) over several recent decades were evaluated using three functional constraints that are derived from both model simulations, or four global datasets, and 736 site-year measurements. Three functional constraints are ecosystem water-use efficiency (WUE), light-use efficiency (LUE), and the partitioning of precipitation P into evapotranspiration (ET) and runoff based on the Budyko framework. Although values of these three constraints varied significantly with time scale and should be quite conservative if being averaged over multiple decades, the results showed that both WUE and LUE simulated by the ensemble mean of 12 ESMs were generally lower than the site measurements. Simulations by the ESMs were generally consistent with the broad pattern of energy-controlled ET under wet conditions and soil water-controlled ET under dry conditions, as described by the Budyko framework. However, the value of the parameter in the Budyko framework ω, obtained from fitting the Budyko curve to the ensemble model simulation (1.74), was larger than the best-fit value of ω to the observed data (1.28). Globally, the ensemble mean of multiple models, although performing better than any individual model simulations, still underestimated the observed WUE and LUE, and overestimated the ratio of ET to P, as a result of overestimation in ET and underestimation in gross primary production (GPP). The results suggest that future model development should focus on improving the algorithms of the partitioning of precipitation into ecosystem ET and runoff, and the coupling of water and carbon cycles for different land- use types. [ABSTRACT FROM AUTHOR]

The recent IPCC reports state that continued anthropogenic greenhouse gas emissions are changing the climate, threatening "severe, pervasive and irreversible" impacts. Slow progress in emissions reduction to mitigate climate change is resulting in increased attention to what is called geoengineering, climate engineering, or climate intervention - deliberate interventions to counter climate change that seek to either modify the Earth's radiation budget or remove greenhouse gases such as CO2 from the atmosphere. When focused on CO2, the latter of these categories is called carbon dioxide removal (CDR). Future emission scenarios that stay well below 2 °C, and all emission scenarios that do not exceed 1.5 °C warming by the year 2100, require some form of CDR. At present, there is little consensus on the climate impacts and atmospheric CO2 reduction efficacy of the different types of proposed CDR. To address this need, the Carbon Dioxide Removal Model Intercomparison Project (or CDRMIP) was initiated. This project brings together models of the Earth system in a common framework to explore the potential, impacts, and challenges of CDR. Here, we describe the first set of CDRMIP experiments, which are formally part of the 6th Coupled Model Intercomparison Project (CMIP6). These experiments are designed to address questions concerning CDR-induced climate "reversibility", the response of the Earth system to direct atmospheric CO2 removal (direct air capture and storage), and the CDR potential and impacts of afforestation and reforestation, as well as ocean alkalinization. [ABSTRACT FROM AUTHOR]

Dengue fever is one of the most serious vector-borne infectious diseases, especially in Guangzhou, China. Dengue viruses and their vectors Aedes albopictus are sensitive to climate change primarily in relation to weather factors. Previous research has mainly focused on identifying the relationship between climate factors and dengue cases, or developing dengue case models with some non-climate factors. However, there has been little research addressing the modeling and projection of dengue cases only from the perspective of climate change. This study considered this topic using long time series data (1998–2014). First, sensitive weather factors were identified through meta-analysis that included literature review screening, lagged analysis, and collinear analysis. Then, key factors that included monthly average temperature at a lag of two months, and monthly average relative humidity and monthly average precipitation at lags of three months were determined. Second, time series Poisson analysis was used with the generalized additive model approach to develop a dengue model based on key weather factors for January 1998 to December 2012. Data from January 2013 to July 2014 were used to validate that the model was reliable and reasonable. Finally, future weather data (January 2020 to December 2070) were input into the model to project the occurrence of dengue cases under different climate scenarios (RCP 2.6 and RCP 8.5). Longer time series analysis and scientifically selected weather variables were used to develop a dengue model to ensure reliability. The projections suggested that seasonal disease control (especially in summer and fall) and mitigation of greenhouse gas emissions could help reduce the incidence of dengue fever. The results of this study hope to provide a scientifically theoretical basis for the prevention and control of dengue fever in Guangzhou. [ABSTRACT FROM AUTHOR]

We evaluate the effectiveness and the regional inequalities of solar radiation management (SRM) in compensating for simultaneous changes in temperature and precipitation caused by increased greenhouse gas concentrations. We analyze the results from Earth System Models under four Geoengineering Model Intercomparison Project (GeoMIP) experiments with a modified form of the Residual Climate Response approach. Each experiment produces 50 model yrs of simulations: 13 models completed experiment G1 (offsetting 4 × CO 2 via solar reduction); 12 models completed experiment G2 (offsetting CO 2 that increased by 1% per year); 3 models completed experiment G3 (offsetting increasing radiative forcing under RCP4.5 with increasing stratospheric aerosol); and 7 models completed experiment G4 (injection of 5 Tg SO 2 a − 1 into the stratosphere). The regional inequalities in temperature and precipitation compensation for experiments G1 , G3 and G4 are significantly different from their corresponding noise backgrounds for most models, but for G2 they are not significantly different from noise. Differences in the regional inequalities and the actual effectiveness among the four SRM scenarios are not significant for many models. However, in more than half of the models, the effectiveness for temperature in the solar dimming geoengineering scenarios ( G1 and G2 ) is significantly higher than that in the SO 2 geoengineering scenarios ( G3 and G4 ). The effectiveness of the four SRM experiments in compensating for temperature change is considerably higher than for precipitation. The methodology used highlights that a large across-model variation in the treatment of key geoengineering processes (such as stratospheric aerosols) and the quantification of damage caused by climate change creates significant uncertainties in any strategies to achieve optimal compensation effectiveness across different regions. [ABSTRACT FROM AUTHOR]

Precipitation-induced sensible heat (HPR) which is transferred between the land surface and rainwater can be extremely large during a heavy precipitation event. Thus, the local surface temperature can be sharply altered on an hourly to daily timescale. However, HPR is commonly neglected in current land surface models because of its small magnitude on long timescales. As a consequence, the simulated land-surface air temperature (TLSA) may be biased. In this study, we use satellite and reanalysis data sets to estimate HPR on the global scale, and we use CESM1 (with CAM4 physics and the prescribed sea surface temperature) to investigate the effect of HPR on TLSA simulations over the second half of the 20th century. Our results show that the reanalysis-estimated HPR is largest over Intertropical Convergence Zone (ITCZ) regions, with seasonal mean values of −0.22 W m−2 (−2.31 to 0.29 W m−2) in DJF and −0.28 W m−2 (−2.89 to 0.24 W m−2) in JJA. These values are consistent with the model-simulated HPR patterns. In DJF, the HPR leads to a weaker equator-pole surface heating difference and therefore, weakens northern stationary waves. The consequent changes of the heat and moisture advection result in noticeable TLSA warming effects (for example, +0.53 K over northern Eurasia and +0.46 K over central North America) and cooling effects (for example, −0.62 K over Alaska and −0.42 K over central Asia) at regional scales. These temperature changes help to reduce the TLSA biases in the model. In JJA, the TLSA changes slightly because of the weak stationary wave responses during the northern summer. [ABSTRACT FROM AUTHOR]

The process of solar radiative transfer at the land surface is important to energy, water, and carbon balance, especially for vegetated areas. Currently the most commonly used two-stream model considers the plant functional types (PFTs) within a grid to be independent of each other and their leaves to be horizontally homogeneous. This assumption is unrealistic in most cases. To consider canopy three-dimensional (3D) structural effects, a new framework of 3D canopy radiative transfer model was developed and validated by numerical simulations and shows a good agreement. A comparison with the two-stream model in the offline Community Land Model (CLM4.0) shows that an increase of canopy absorption mainly happens with sparse vegetation or with multilayer canopies with a large sun zenith angle θsun and is due to increases of the ground and sky shadows and of the optical pathlength because of the shadow overlapping between bushes and canopy layers. A decrease of canopy absorption occurs in densely vegetated areas with small θsun. For a one-layer canopy, these decreases are due to crown shape effects that enhance the transmission through the canopy edge. For a multilayer canopy, aside from these shape effects, transmission is also increased by the decreased ground shadow due to the shadow overlapping between layers. Ground absorption usually changes with opposite sign as that of the canopy absorption. Somewhat lower albedos are found over most vegetated areas throughout the year. The 3D model also affects the calculation of the fraction of sunlit leaves and their corresponding absorption. [ABSTRACT FROM AUTHOR]

Earth System Models (ESMs) are fundamental tools for understanding climate-carbon feedback. An ESM version of the Flexible Global Ocean-Atmosphere-Land System model (FGOALS) was recently developed within the IPCC AR5 Coupled Model Intercomparison Project Phase 5 (CMIP5) modeling framework, and we describe the development of this model through the coupling of a dynamic global vegetation and terrestrial carbon model with FGOALS-s2. The performance of the coupled model is evaluated as follows. The simulated global total terrestrial gross primary production (GPP) is 124.4 PgC yr and net primary production (NPP) is 50.9 PgC yr. The entire terrestrial carbon pools contain about 2009.9 PgC, comprising 628.2 PgC and 1381.6 PgC in vegetation and soil pools, respectively. Spatially, in the tropics, the seasonal cycle of NPP and net ecosystem production (NEP) exhibits a dipole mode across the equator due to migration of the monsoon rainbelt, while the seasonal cycle is not so significant in Leaf Area Index (LAI). In the subtropics, especially in the East Asian monsoon region, the seasonal cycle is obvious due to changes in temperature and precipitation from boreal winter to summer. Vegetation productivity in the northern mid-high latitudes is too low, possibly due to low soil moisture there. On the interannual timescale, the terrestrial ecosystem shows a strong response to ENSO. The model-simulated Niño3.4 index and total terrestrial NEP are both characterized by a broad spectral peak in the range of 2-7 years. Further analysis indicates their correlation coefficient reaches −0.7 when NEP lags the Niño3.4 index for about 1-2 months. [ABSTRACT FROM AUTHOR]

A comprehensive 30×30 arc-second resolution gridded soil characteristics data set of China has been developed for use in the land surface modeling. It includes physical and chemical attributes of soils derived from 8979 soil profiles and the Soil Map of China (1:1,000,000). We used the polygon linkage method to derive the spatial distribution of soil properties. The profile attribute database and soil map are linked under the framework of the Genetic Soil Classification of China which avoids uncertainty in taxon referencing. Quality control information (i.e., sample size, soil classification level, linkage level, search radius and texture) is included to provide 'confidence' information for the derived soil parameters. The data set includes 28 attributes for 8 vertical layers at the spatial resolution of 30×30 arc-seconds. Based on this data set, the estimated storage of soil organic carbon in the upper 1 m of soil is 72.5 Pg, total N is 6.6 Pg, total P is 4.5 Pg, total K is 169.9 Pg, alkali-hydrolysable N is 0.55 Pg, available P is 0.03 Pg, and available K is 0.61 Pg. These estimates are reasonable compared with previous studies. The distributions of soil properties are consistent with common knowledge of Chinese soil scientists and the spatial variations over large areas are well represented. The data set can be incorporated into land models to better represent the role of soils in hydrological and biogeochemical cycles in China. [ABSTRACT FROM AUTHOR]

Abstract: Land surface and climate modelling requires continuous and consistent Leaf Area Index (LAI). High spatiotemporal resolution and long-time record data are more in demand nowadays and will continue to be in the future. MODIS LAI products meet these requirements to some degree. However, due to the presence of cloud and seasonal snow cover, the instrument problems and the uncertainties of retrieval algorithm, the current MODIS LAI products are spatially and temporally discontinuous and inconsistent, which limits their application in land surface and climate modelling. To improve the MODIS LAI products on a global scale, we considered the characteristics of the MODIS LAI data and made the best use of quality control (QC) information, and developed an integrated two-step method to derive the improved MODIS LAI products effectively and efficiently on a global scale. First, we used the modified temporal spatial filter (mTSF) method taking advantage of background values and QC information at each pixel to do a simple data assimilation for relatively low quality data. Then we applied the post processing-TIMESAT (A software package to analyze time-series of satellite sensor data) Savitzky–Golay (SG) filter to get the final result. We implemented the method to 10years of the MODIS Collection 5 LAI data. In comparison with the LAI reference maps and the MODIS LAI data, our results showed that the improved MODIS LAI data are closer to the LAI reference maps in magnitude and also more continuous and consistent in both time-series and spatial domains. In addition, simple statistics were used to evaluate the differences between the MODIS LAI and the improved MODIS LAI. [Copyright &y& Elsevier]

• A two-stage model combined with the latest MODIS AOD (C6.1) is used to reconstruct historical PM 2.5 concentration records; • This model showed excellent performance on estimating monthly, seasonal and annual PM 2.5. • All the city clusters have showed decreasing trends by 7.83%–26.35% on PM 2.5 concentrations in recent years. • 1- to 2-year lagged effect was found for internal governance and co-governance from surrounding areas in Chinese city clusters on PM 2.5. The PM 2.5 concentration is an important evaluation index for the global Sustainable Development Goals (SDGs) for its negative impacts on human health. Last decade, several fine particulate pollution episodes occurred in the vast area of China. In response to this, the Chinese government has stepped up efforts to tackle air pollution. In this paper, the temporal trends of PM 2.5 and the quantitative potential impact of environmental governance on PM 2.5 are analyzed for China. Due to the lack of historical records, a two-stage model was used to estimate the historical PM 2.5 concentrations, combined with the newly released satellite-based aerosol optical depth (AOD) product (MODIS Collection 6.1) and other data. The estimated PM 2.5 concentrations showed strong consistency with the surface observations. Furthermore, significant seasonal variations existed in the PM 2.5 concentrations and the temporal trends were captured, especially in city clusters. Then eight major city clusters were selected as typical samples. All the city clusters showed decrease trends in recent years, with PM 2.5 concentrations in these regions decreased by 0.269–1.604 μg m−3 year−1. From 2006 to 2017, the annual PM 2.5 concentrations decreased by 7.83%–26.35% in the major city clusters among China. Technological innovation and environmental governance play an important role in the decrease of PM 2.5. In order to quantify the influence of governance, environmental regulation intensity and synergy were applied as the indicators of the internal governance and co-governance in each city cluster. In most city clusters, PM 2.5 concentrations were significantly negatively correlated with regional internal governance and co-governance (R = −0.596 to −0.930, p < 0.05), and the effect on PM 2.5 lasted for several years. However, 1- to 2-year lagged effect was found for governance, which means that the regulatory measures should be enhanced to decrease PM 2.5 in the future to achieve the SDGs in China. [ABSTRACT FROM AUTHOR]

Geoengineering, the deliberate large-scale manipulation of earth's energy balance to counteract global warming, is an attractive proposition for sparsely populated deserts. We use the BNU and UVic Earth system models to simulate the effects of irrigating deserts under the RCP8.5 scenario. Previous studies focused on increasing desert albedo to reduce global warming; in contrast we examine how extending afforestation and ecological projects, that successfully improve regional environments, fair for geoengineering purposes. As expected desert irrigation allows vegetation to grow, with bare soil or grass gradually becoming shrub or tree covered, with increases in terrestrial carbon storage of 90.3 Pg C (UVic-ESCM) - 143.9 Pg C (BNU-ESM). Irrigating global deserts makes the land surface temperature decrease by 0.48 °C and land precipitation increase by 100 mm yr−1. In the irrigated areas, BNU-ESM simulates significant cooling of up to 4.2 °C owing to the increases in low cloud and latent heat which counteract the warming effect due to decreased surface albedo. Large volumes of water would be required to maintain global desert irrigation, equivalent 10 mm/year of global sea level (BNU-ESM) compensate for evapotranspiration losses. Differences in climate responses between the deserts prompt research into tailored albedo-irrigation schemes. [ABSTRACT FROM AUTHOR]