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We thank the authors (hereafter referred to as CCC) for providing us an opportunity to clarify some points of our original paper. CCC list in their abstract three "key points"that we respond to in this Reply. The first comment is the central one and the most developed. It deals mainly with discussion of features of methods of spectral analysis, mainly SSA. We have quoted the sub‐parts of that comment as items 1a to 1k. The replies to comments/key points 2 and 3 are shorter. We disagree with most of the comments by CCC and explain why. We conclude that we have successfully countered CCC's criticism and shown many of their points to be unsubstantiated. The main problem seems to reside in differences concerning the literature on Singular Spectral Analysis and our use of it. Much of our response to the comments can be found in textbooks and review papers on SSA and time series analysis; we quote extensively, both in our original paper and in this response to CCC, Golyandina and Zhigljavsky (2013). Key Points: We find compelling results showing a significant co‐variability between sunspot numbers and global temperature.We do not have a mechanism to explain that forcing: it remains to be found. We do not discuss further the parts of CCC on mechanisms.The trends of temperature and sunspots (first SSA component) are similar; the second component results in an opposite trend in the last 30 years. [ABSTRACT FROM AUTHOR]

Instrumental data from the pre–Industrial Revolution period are important to -understand climate change. In this paper, the observations made by the French missionary J. Amiot in present-day central Beijing during 1757–62 were processed and analyzed. The observations represent the earliest continuous dataset of meteorological records found in China that have been digitized recently. Comparisons between the Amiot annual temperature range and extreme values with modern observations showed that the observations were read at approximately 0800 and 1500 local solar time (LST) in a well-ventilated outdoor site. The daily maximum, minimum, and mean temperatures (T-max, T-min, and T-mean, respectively) during 1757–62 were determined by examining the relationship between temperature at 0800 and 1500 LST and T-max, T-min, and T-mean in modern reference series. Nearly 260 years ago, Beijing's climate was typical of an inland temperate monsoon zone with annual T-mean, annual mean T-max, and annual mean T-min being 11.5°, 17.8°, and 6.1°C, respectively; further, the temperatures did not vary considerably from the 1951–1980 temperatures, but differed evidently compared to relatively recent decades (1981–2020). The difference was larger than the magnitudes of global and regional temperature changes. Thus, climate warming since the pre–Industrial Revolution period in the urban areas of Beijing has dominantly occurred over the last four decades. Uncertainties related to the thermometer and observational conditions 260 years ago and the interpolation method used have also been discussed in this paper. [ABSTRACT FROM AUTHOR]

Climate change affects every continent, country, city, and sector. The extent of these effects is governed by the period over which they occur, the rate of global warming, and the mitigation actions employed. One of the sectors most affected by climate change is aviation. Climate change may result in mandatory rules such as airport closures, airline route changes, increased operational expenses, and new legal duties, among several other things. Weather events caused by climate change are projected to impact the aviation industry immediately. Storms and excessive temperatures can cause delays, cancellations, and infrastructure disruptions. In the long term, gradual but more permanent effects can occur in temperature change or global sea-level rise, changes in passenger demand, the new aviation hubs, the loss of existing attraction points, and economic repercussions such as infrastructure damage or loss. The effects of climate change restrictions on the aviation sector, particularly airports, are analyzed in this paper. The consequences of rising water levels on airports and future scenarios are examined and projected. Through sample modeling, the future scenarios that a few airports are likely to encounter have been investigated using statistical data. This study uses the Coastline Paradox-based tool to model future global sea level rises. The study's findings are based on projections for 2050-2200. The study, the effects of climate change on aviation have been examined, and airports that will be out of use due to global sea-level rise have been estimated. One of the aims of the study is to raise awareness of aviation authorities and corporations about these devastating consequences and to contribute to their necessary preparations and precautions. The study looked at airports in Europe and America recognized as aviation centers. The applied working techniques and analyses are described in depth. [ABSTRACT FROM AUTHOR]

Cement is one of the highest energy-consuming and emission generating industries around the world. To reduce greenhouse emissions, several mitigation measures have been proposed, and their effectiveness is estimated. However, estimates of the global temperature change potential of the cement industry have seldom been performed. Hence, in this study, we propose a new framework that estimates CO2 emissions and other seven pollutants to estimate temperature change potential from the cement industry. The underlying framework uses system dynamics, where the effectiveness of four mitigation measures, i.e., a shift in demand, newer methodologies to produce clinker, use of energy efficiency improvements, and implementation of renewable energy, are explored. The results indicate that renewable sources of energy show highest mitigation potential. The cement industry has contributed to an increase in 2 mK temperature since 1990, which is likely to grow up to 14.8 mK by 2050 if no mitigation measures are applied. Energy efficiency improvements by extensions of perform achieve and trade scheme can reduce 0.33 mK from the Indian cement industry. This paper provides a unique opportunity for estimating temperature influence of the cement industry, which can be further implemented for other countries. [ABSTRACT FROM AUTHOR]

An increase in energy demand and consumption is one of the significant challenges of the world community. Global climate change and temperature rise can significantly affect energy demand, especially in the building sector. Green passive design strategies (GPDS) such as green roof and green wall are considered a passive energy-saving technology which can deal with further climate change in near future. This paper compares the energy demand and CO2 emissions of a building with different structural scenarios during the current (2000–2019) and future climatic conditions (the 2050s) in two hot-dry (Kerman) and hot-humid (BandarAbbas) climate samples in Iran. The base case, green roof, and green wall modeling of the selected building have been developed by DesignBuilder software. Results revealed that 61% of the annual energy consumption of Kerman is related to the heating sector, while it will be changed to 47% under the effect of climate change and based on RCP2.6. However, 99% of the annual energy consumption of BandarAbbas belongs to cooling demand and it will not change by 2050s. Also, the maximum heating and cooling energy demand were calculated for the base building. Based on the results, green wall has more efficiency in optimizing total energy consumption compared to green roof in both climate types. On the other hand, GPDS are more efficient to optimize heating energy demand in comparison with cooling energy demand. Furthermore, the green wall strategy has better performance in reducing CO2 emissions as well. Accordingly, CO2 emissions reduce in Kerman by 2.73% and 2.93% by the implementation of the green wall during the observation period and 2050s, respectively. Meanwhile, this strategy can reduce CO2 emissions by only 1% per year in BandarAbbas during all studied periods. [ABSTRACT FROM AUTHOR]

This paper aims to better understand why there was a global warming pause in 2000–2015 and why the global mean surface temperature (GMST) has risen again in recent years. We present and statistically analyze substantial time-series observed datasets of global lower-stratospheric temperature (GLST), troposphere–stratosphere temperature climatology, global land surface air temperature, GMST, sea ice extent (SIE) and snow cover extent (SCE), combined with modeled calculations of GLSTs and GMSTs. The observed and analyzed results show that GLST/SCE has stabilized since the mid-1990s with no significant change over the past two and a half decades. Upper-stratospheric warming at high latitudes has been observed and GMST or global land surface air temperature has reached a plateau since the mid-2000s with the removal of natural effects. In marked contrast, continued drastic warmings at the coasts of polar regions (particularly Russia and Alaska) are observed and well explained by the sea-ice-loss warming amplification mechanism. The calculated GMSTs by the parameter-free quantum-physics warming model of halogenated greenhouse gases (GHGs) show excellent agreement with the observed GMSTs after the natural El Niño southern oscillation and volcanic effects are removed. These results have provided strong evidence for the dominant warming mechanism of anthropogenic halogenated GHGs. The results also call for closer scrutiny of the assumptions made in current climate models. [ABSTRACT FROM AUTHOR]

This paper documents the experimental setup and general features of the coupled historical and future climate simulations with the first version of the US Department of Energy (DOE) Energy Exascale Earth System Model (E3SMv1.0). The future projected climate characteristics of E3SMv1.0 at the highest emission scenario (SSP5-8.5) designed in the Scenario Model Intercomparison Project (ScenarioMIP) and the SSP5-8.5 greenhouse gas (GHG) only forcing experiment are analyzed with a focus on regional responses of atmosphere, ocean, sea ice, and land. Due to its high equilibrium climate sensitivity (ECS of 5.3 K), E3SMv1.0 is one of the Coupled Model Intercomparison Project phase 6 (CMIP6) models with the largest surface warming by the end of the 21st century under the high-emission SSP5-8.5 scenario. The global mean precipitation change is highly correlated with the global temperature change, while the spatial pattern of the change in runoff is consistent with the precipitation changes. The oceanic mixed layer generally shoals throughout the global ocean. The annual mean Atlantic meridional overturning circulation (AMOC) is overly weak with a slower change from ∼11 to ∼6 Sv (Sverdrup) relative to other CMIP6 models. The sea ice, especially in the Northern Hemisphere, decreases rapidly with large seasonal variability. We detect a significant polar amplification in E3SMv1.0 from the atmosphere, ocean, and sea ice. Comparing the SSP5-8.5 all-forcing experiment with the GHG-only experiment, we find that the unmasking of the aerosol effects due to the decline of the aerosol loading in the future projection period causes transient accelerated warming in the all-forcing experiment in the first half of the 21st century. While the oceanic climate response is mainly controlled by the GHG forcing, the land runoff response is impacted primarily by forcings other than GHG over certain regions, e.g., southern North America, southern Africa, central Africa, and eastern Asia. However, the importance of the GHG forcing on the land runoff changes grows in the future climate projection period compared to the historical period. [ABSTRACT FROM AUTHOR]

Over the last century, the global mean surface air temperature (SAT) has experienced two periods of warming slowdown (hiatuses), namely 1940–1975 and 1998–2012, as well as showing well-defined interdecadal oscillations. Previous studies have focused mainly on the most recent hiatus, and little is known about the period between 1940 and 1975. From the point of view of the sea surface temperature (SST), there are two aspects of interest; i.e., the climatological SST and SST variability. In this paper, observational and modelling evidence is used to show that, compared with the climatological SST, SST variability has been the main cause of the slowdown in rate of increase in SAT since 1940. In addition, the observational data and simulation results show that SST variability had a greater impact on the slowdown in rate of increase in SAT from 1940 to 1975 (− 1.2 × 10−3 °C/year) than from 1998 to 2012 (− 5.7 × 10−3 °C/year). The SAT change over the period 1940–1975 (1.0 × 10−4 °C/year) was less affected by the climatological SST forcing experiment than that over the period 1998–2012 (− 5.0 × 10−4 °C/year). Comparing with 1940–1975, the SAT change over the period 1998–2012 was much affected by the global SAT long-term warming. The distributions of wind stress and atmospheric pressure both indicate that, although the eastern Pacific Ocean played an important role in influencing the global SAT trend between 1998 and 2012, it made little contribution to changes in global SAT between 1940 and 1975. In addition, from the perspective of seasonality, the interdecadal variation of SAT over these two periods was a seasonally dependent phenomenon. Over the period 1940–1975, the annual SAT trend essentially followed the summer SAT trend, whereas between 1998 and 2012, winter was the dominant season of annual SAT change. [ABSTRACT FROM AUTHOR]

Rice husk ash (RHA) is a highly active pozzolanic material produced by the controlled combustion of rice husks, which is widely used as a mineral admixture for the production of high performance concrete. The addition of rice husk ash has a complex effect on cement hydration. Current models do not account for all these complex effects. In this paper, by considering factors such as the dilution and chemical effect of rice husk ash on the composite cementing system, as well as the absorption and release of water by the porous structure of rice husk ash, a hydration kinetic model of RHA cement cementitious system is established. Taking water cement ratio, ambient temperature, RHA particle fineness and dosage as variable parameters, the model calculation is compared with the experimental results. It is proved that the model can simulate the hydration process of cement cementitious system with RHA and can be used to predict the hydration degree of cement cementitious system with age. The results show that the degree of hydration of the RHA-cement cementing system is directly proportional to the water-cement ratio, ambient temperature and specific surface area. The research can provide a basis for the application of rice husk ash in cement, and at the same time achieve the purpose of improving the economy of cement and saving resources. [ABSTRACT FROM AUTHOR]

In this paper, we show that the projected global temperature change from CMIP5 models is remarkably similar to that obtained using simple regression models relating the global temperature to the atmospheric concentrations of CO2. This result is strengthened when we consider the projections obtained using the CMIP6 models. [ABSTRACT FROM AUTHOR]

Climate change has been recognised as an important policy issue that affects nature and socio-economic systems of all continents and oceans over the last few decades. In order to achieve the ambitious goal of ‘keeping a global temperature rise to less than 2 degrees Celsius above pre-industrial levels’ by the Paris Agreement agreed at COP 21 in 2015, formulation and implementation of climate change policies, especially mitigation ones to reduce greenhouse gas (GHG) emissions have been recently advanced all over the world. Russia, as one of the largest energy-resource rich countries and GHG emitters, has been also in the process of modernisation towards a low-carbon society, especially after the occurrence of global financial crisis in 2008-2009. Under this circumstance, the formulation and implementation of climate change policies have recently begun in earnest in Russia through its signature on and ratification of the Paris Agreement effective in 2016. These policies in Russia, however, often end in failure. In this context, this present paper firstly clarifies the current situation of climate change and its causes such as GHG and air pollutants emissions in Russia, followed by the critical consideration of previous studies on this global thematic issue. By revisiting the formulation and implementation process of Russian climate change policies with a special focus on its multi-stakeholders, this paper tries to explain why these policies are not materialised in Russia, that is, factors influencing on its policy failure. Throughout a series of analysis, it becomes clear in this paper that Russian environmental administration has been weakened whilst the government spending with environmental purposes on a downward trend in Russia after starting market transition in the 1990s. This paper also derives that institutional arrangements in the governmental committees enable Russian oil and gas companies to do lobbying for reflecting their interests on relevant policies. Besides, it becomes unveiled that residents and civil society organisations (CSOs), as one of representative protesters demanding policy reforms through social movements, have an insignificant influence on climate change policies in the case of Russia. This paper then concludes that these factors are crucial propositions given to Russian climate change policies to materialise its transition towards a low-carbon society as well as big challenges to be overcome for its future sustainable growth. [ABSTRACT FROM AUTHOR]

Carbon capture, utilization, and storage (CCUS) is believed to be the most promising technology to mitigate climate change and global temperature rise. As an effective method for reducing carbon emissions, carbon dioxide (CO 2) storage on the seabed can be achieved by injecting captured CO 2 from offshore platforms into subsea storage sites, such as the sediment layers, depleted oil and gas reservoirs and deep saline aquifers, thereby permanently removing it from the atmosphere. Additionally, hundreds to thousands of meters of seawater above seabed storage layers provide naturally high seawater pressure and abundant barrier settings that can reduce leakage risk. Consequently, this has become an ideal storage location for long-term CO 2 storage. In order to thoroughly investigate the mechanism and potential of marine CO 2 storage and promote further development of CCUS, this paper provides a comprehensive description of theoretical research of marine CO 2 geological storage, including storage mechanisms, storage capacity, wellbore flow, CO 2 migration, cap rocks integrity and CO 2 leakage monitoring. The implementation status of global engineering projects is summarized. Currently, there are relatively few successful marine storage projects globally, with the majority of others still in the research and testing stages. Finally, the challenges and prospects of marine CO 2 storage are also discussed. This review demonstrates the enormous potential and promising future of marine CO 2 storage, but there are also leakage risks. It can be avoided through in-depth theoretical research to clarify the entire process of storage mechanisms and take corresponding technological measures. Ultimately, a new technology for large-scale efficient injection and enhanced storage of marine CO 2 storage will be formed. • Marine CO 2 storage has enormous potential and promising prospects. • The flow of CO 2 in the storage reservoir will cause phase change, heat transfer, storage leakage, etc. • Remote monitoring technology can prevent CO 2 leakage. • Storage projects require adequate funding and policy support. [ABSTRACT FROM AUTHOR]

Extreme climate events are hotspots in global change. However, research on the changes in future compound events and population exposure is still limited. Leveraging from the data of the sixth phase of the Coupled Model Intercomparison Project (CMIP6), this paper aims to analyze the temporal and spatial changes of global compound temperature and precipitation extreme events in the future. We also predict the risk of population exposure and quantify the contribution of different factors to exposure. The results show that: (1) In the next 80 years, compound hot-dry event (CHDE) will increase at a rate of 0.02, 0.03, and 0.08 days per decade under the three scenarios of SSP1–2.6, SSP2–4.5 and SSP5–8.5, respectively. By comparison, compound hot-humidity event (CHHE) shows a downward trend under the three scenarios, with a downward rate of 0.01, 0.02, and 0.11 days per decade, respectively. (2) Under the SSP1–2.6 and SSP2–4.5 scenarios, CHDE and CHHE have two or more mutation points. Under the SSP5–8.5 scenario, CHDE shows a significant upward and CHHE shows a significant downward trend in the middle and late 21st century. These two indices exhibit periodic changes in all three scenarios (3) South Asia, West Asia, and Northeast Africa have higher CHDE values, while regions with higher CHHE values are located in North Asia and Greenland. (4) Climate change is a major factor affecting population exposure. For CHDE, climate, population, and their synergistic effects contribute about 75%, 20%, and 5% to the exposure, respectively. For CHHE, the contributions of these three factors are 85%, 10%, and 5% respectively. These findings provide scientific guidance for the rational formulation of population policies, the effective avoidance of climate disaster risks and the protection of human health. • Frequency of hot-dry events and hot-humidity events will increase and decrease, respectively, in the future. • There are abrupt points and periodicity in the future time series of compound temperature and precipitation extremes. • Asia is projected to have the greatest exposure and climate change contributes the most to exposure. [ABSTRACT FROM AUTHOR]

The use of different primary energy sources in human society has led to two major polluting emissions in the environment: energy (mostly heat), and chemical substances (mostly carbon dioxide). In this paper, a new approach, based on the similarity between sensible heat and CO2 transfer properties, was used to determine the effect of anthropogenic heat release on the global air temperature. The total global anthropogenic emissions of sensible heat were divided into two separate streams: directly transferred to: (1) water and land, and (2) to the atmosphere. The direct emissions of heat to the atmosphere during the industrial era (years 1850-2018) were determined and their effect on the change of global atmospheric temperature was calculated. The global atmospheric temperature increase caused by anthropogenic heat emissions was estimated. The resulting calculations showed that at least half of the actual atmospheric temperature rise recorded during the last 170-year period, was due to the anthropogenic heat release. These results suggest that the temperature change of the atmosphere (global warming) is strongly affected by anthropogenic heat emissions. [ABSTRACT FROM AUTHOR]

This paper is an introduction to the new package in R called smoots (smoothing time series), developed for data-driven local polynomial smoothing of trend-stationary time series. Functions for data-driven estimation of the first and second derivatives of the trend are also built-in. It is first applied to monthly changes of the global temperature. The quarterly US-GDP series shows that this package can also be well applied to a semiparametric multiplicative component model for non-negative time series via the log-transformation. Furthermore, we introduced a semiparametric Log-GARCH and a semiparametric Log-ACD model, which can be easily estimated by the smoots package. Of course, this package applies to suitable time series from any other research area. The smoots package also provides a useful tool for teaching time series analysis, because many practical time series follow an additive or a multiplicative component model. [ABSTRACT FROM AUTHOR]

This paper documents the experimental setup and general features of the coupled historical and future climate simulations with the first version of the U.S. Department of Energy (DOE) Energy Exascale Earth System Model (E3SMv1.0). The future projected climate characteristics of E3SMv1.0 at the highest emission scenario (SSP5-8.5) designed in the Scenario Model Intercomparison Project (ScenarioMIP) and the SSP5-8.5 greenhouse gas (GHG) only forcing experiment are analyzed with a focus on regional responses of atmosphere, ocean, sea-ice, and land. Due to its high climate sensitivity, E3SMv1.0 is one of the CMIP6 models with the largest surface warming by the end of the 21st century under the high-emission SSP5-8.5 scenario. The global mean precipitation change is highly correlated to the global temperature change, while the spatial pattern of the change in runoff responds to the precipitation changes. The oceanic mixed layer generally shoals throughout the global ocean. The sea ice, especially in the Northern Hemisphere, rapidly decreases with large seasonal variability. The annual mean AMOC is overly weak with a slower change relative to other CMIP6 models. We detect a significant polar amplification in E3SMv1.0 from the atmosphere, ocean, and sea ice. Comparing the SSP5-8.5 all-forcing experiment with the GHG-only experiment, we find that the unmasking of the aerosol effects due to the decline of the aerosol loading in the future projection period causes accelerated warming in SSP5-8.5 all-forcing experiment. While the oceanic climate response is mainly controlled by the GHG forcing, the land runoff response is impacted primarily by forcings other than GHG over certain regions. However, the importance of the GHG forcing on the land runoff changes grows in the future climate projection period compared to the historical period. [ABSTRACT FROM AUTHOR]

The climate impact of bioenergy is commonly quantified in terms of CO2 equivalents, using a fixed 100‐year global warming potential as an equivalency metric. This method has been criticized for the inability to appropriately address emissions timing and the focus on a single impact metric, which may lead to inaccurate or incomplete quantification of the climate impact of bioenergy production. In this study, we introduce Dynamic Relative Climate Impact (DRCI) curves, a novel approach to visualize and quantify the climate impact of bioenergy systems over time. The DRCI approach offers the flexibility to analyze system performance for different value judgments regarding the impact category (e.g., emissions, radiative forcing, and temperature change), equivalency metric, and analytical time horizon. The DRCI curves constructed for fourteen bioenergy systems illustrate how value judgments affect the merit order of bioenergy systems, because they alter the importance of one‐time (associated with land use change emissions) versus sustained (associated with carbon debt or foregone sequestration) emission fluxes and short‐ versus long‐lived climate forcers. Best practices for bioenergy production (irrespective of value judgments) include high feedstock yields, high conversion efficiencies, and the application of carbon capture and storage. Furthermore, this study provides examples of production contexts in which the risk of land use change emissions, carbon debt, or foregone sequestration can be mitigated. For example, the risk of indirect land use change emissions can be mitigated by accompanying bioenergy production with increasing agricultural yields. Moreover, production contexts in which the counterfactual scenario yields immediate or additional climate impacts can provide significant climate benefits. This paper is accompanied by an Excel‐based calculation tool to reproduce the calculation steps outlined in this paper and construct DRCI curves for bioenergy systems of choice. Dynamic Relative Climate Impact (DRCI) curves are a novel approach to quantify the climate impact of bioenergy systems over time. The DRCI approach offers the flexibility to analyze system performance for different value judgments regarding the impact category, equivalency metric, and analytical time horizon. The DRCI curves for four bioenergy systems illustrated in this figure show how the aforementioned value judgments can lead to alternative conclusions about the (relative) performance of bioenergy systems. [ABSTRACT FROM AUTHOR]

This paper is concerned with the stability analysis of bridged single walled carbon nanotubes (SWCNT) under temperature changes. A molecular structural mechanics model is utilized to investigate the free vibration frequencies and thermal buckling of SWCNT. In comparison with most of the previous studies, a temperature-variable thermal-expansion-coefficient is used that is negative under a certain temperature. Also thermal variation of Young's modulus of the CNTs is considered. Several studies are performed to investigate the critical temperature change due to heating and cooling of SWCNTs with different chiralities and slenderness ratios and the stability boundaries are determined. [ABSTRACT FROM AUTHOR]

The article discusses a research about the use of tree rings in providing information about the amount of snow or rainfall. It references a study by Kerstin Treydte and colleagues published within the issue. They concluded that the latter part of the twentieth century was by far the wettest period, suggesting that humans may play a role in the climate of the world.

The COVID‐19 pandemic led to dramatic changes in economic activity in 2020. We use estimates of emission changes for 2020 in two Earth System Models (ESMs) to simulate the impacts of the COVID‐19 economic changes. Ensembles of nudged simulations are used to separate small signals from meteorological variability. Reductions in aerosol and precursor emissions, chiefly black carbon and sulfate (SO4), led to reductions in total anthropogenic aerosol cooling through aerosol‐cloud interactions. The average overall Effective Radiative Forcing (ERF) peaks at +0.29 ± 0.15 Wm−2 in spring 2020. Changes in cloud properties are smaller than observed changes during 2020. Impacts of these changes on regional land surface temperature range up to +0.3 K. The peak impact of these aerosol changes on global surface temperature is very small (+0.03 K). However, the aerosol changes are the largest contribution to radiative forcing and temperature changes as a result of COVID‐19 affected emissions, larger than ozone, CO2 and contrail effects. Plain Language Summary: The COVID‐19 pandemic changed emissions of gases and particulates. These gases and particulates affect climate. In general, human emissions of particles cool the planet by scattering away sunlight in the clear sky and by making clouds brighter to reflect sunlight away from the earth. This paper focuses on understanding how changes to emissions of particulates (aerosols) affect climate. We use estimates of emissions changes for 2020 in two climate models to simulate the impacts of the COVID‐19 induced emission changes. We tightly constrain the models by forcing the winds to match observed winds for 2020. COVID‐19 induced lockdowns led to reductions in aerosol and precursor emissions, chiefly soot or black carbon and sulfate (SO4). This is found to reduce the human caused aerosol cooling: creating a small net warming effect on the earth in spring 2020. Changes in cloud properties are smaller than observed changes during 2020. The impact of these changes on regional land surface temperature is small (maximum +0.3 K). The impact of aerosol changes on global surface temperature is very small and lasts over several years. However, the aerosol changes are the largest contribution to COVID‐19 affected emissions induced radiative forcing and temperature changes, larger than ozone, CO2 and contrail effects. Key Points: COVID‐19 induced lockdowns significantly altered emissions of aerosols, leading to simulated changes in cloud properties in two Earth System ModelsAerosol Cloud Interactions from reduced emissions result in significant increases in radiative forcing, up to +0.29 ± 0.15 Wm−2Aerosol radiative forcing reductions are the largest contributor to surface temperature changes [ABSTRACT FROM AUTHOR]

The second version of the Chinese Academy of Sciences Earth System Model (CAS-ESM2.0) is participating in the Flux-Anomaly-Forced Model Intercomparison Project (FAFMIP) experiments in phase 6 of the Coupled Model Intercomparison Project (CMIP6). The purpose of FAFMIP is to understand and reduce the uncertainty of ocean climate changes in response to increased CO2 forcing in atmosphere-ocean general circulation models (AOGCMs), including the simulations of ocean heat content (OHC) change, ocean circulation change, and sea level rise due to thermal expansion. FAFMIP experiments (including faf-heat, faf-stress, faf-water, faf-all, faf-passiveheat, faf-heat-NA50pct and faf-heat-NA0ct) have been conducted. All of the experiments were integrated over a 70-year period and the corresponding data have been uploaded to the Earth System Grid Federation data server for CMIP6 users to download. This paper describes the experimental design and model datasets and evaluates the preliminary results of CAS-ESM2.0 simulations of ocean climate changes in the FAFMIP experiments. The simulations of the changes in global ocean temperature, Atlantic Meridional Overturning Circulation (AMOC), OHC., and dynamic sea level (DSL), are all reasonably reproduced. [ABSTRACT FROM AUTHOR]

In this paper, the field measurements results are presented on the stack ventilation effect. The paper presents the results of performance (air change rate ACH) natural ventilation for building with inlet gap measured for the transitional season (between heating and summer season). The measurements were performed during a windless time. The house was located in northern Poland, in a cold climate region. The measurement system measured local climate conditions, indoor climate conditions and air velocities in vent inlet and outlet. In this paper, the discharge coefficient was checked. The discharge coefficient of 0.83 was higher than the discharge coefficient of 0.6 which was usually assumed for small rectangular openings during the natural ventilation. In a wind absence when the stack effect acted only, the air change rate (ACH) slightly exceeded the standard minimum value. [ABSTRACT FROM AUTHOR]

This paper describes a four-step process to guide national governments in formulating and explaining greenhouse gas (GHG) emissions reduction targets in their Nationally Determined Contributions (NDCs) under the Paris Agreement. The NDC pledges in aggregate are intended to achieve the Paris Agreement's warming limit goal to hold the increase in the global temperature to well below 2°C and to pursue efforts to limit the temperature increase to 1.5°C. Nations also agreed in the Paris Agreement that their mitigation pledges would be based on equity and common but differentiated responsibilities and respective capabilities, in the light of different national circumstances. This paper describes the four steps that are required to fulfil these commitments, and to ensure that the NDCs are sufficiently transparent to allow the Paris Agreement's 'stocktake' process and 'transparency mechanism' to achieve their goal of increasing the NDCs' ambition and fairness. The four steps are necessary to implement the legal obligations of the parties under the UNFCCC and the Paris Agreement. These four steps are: (i) Select a global warming limit to be achieved by the GHG emissions reduction target; (2) Identify a global carbon budget consistent with achieving the global warming limit at an acceptable probability; (3) Determine the national fair share of the global carbon budget based upon equity and common but differentiated responsibilities and respective capabilities; and, (4) Specify the annual rate of national GHG emissions reductions on the pathway to net zero emissions. [ABSTRACT FROM AUTHOR]

This paper presents the temperature dependence of solar cell characteristics by laboratory measurements in case of cooled and non-cooled solar cells. The voltage and current level of electricity, provided by solar cells are highly influenced by the temperature change. The output voltage level of both an idle and a loaded solar cell is decreased by the temperature increase which also leads to power decrease and efficiency deterioration. The intensity increase of the irradiating light linearly increase the current, provided by the power cell which highly increase the temperature of the solar cell and that leads to voltage decrease and efficiency deterioration too. To prevent these processes it is needed to reduce the temperature of the solar cells. The measured characteristic curves at different temperatures are presented in this paper. [ABSTRACT FROM AUTHOR]

To accurately measure in situ stresses using overcore techniques, the key is to find the relationship between the stresses and measured strains on the wellbore wall and on the core at two stages, i.e. before and after overcoring. For gas shales, where there exist large pressure and temperature changes, we developed an analytical model for the stage before overcoring to study the evolution of all field variables, i.e. temperature, pressure, stress, strain and displacement (TPSSD), when an inclined wellbore is drilled in an infinite and homogenous thermo-poro-elastic media (THM) subjected to three far-field principal stresses, whose axes may not coincide with the horizontal and vertical planes. In that paper we investigated the thermal and poro-elastic effects on the strain changes around and especially at the wellbore wall. As an extension of the previous work. In this paper, we describe an analytical model to give the mechanical responses of the wellbore and core for the stage after overcoring. Strain changes at the wellbore wall are examined in detail because these are measured by the overcore method. By using the analytical solutions presented at a specific time and the strains before overcoring as an initial state, the transient solutions for the evolution of temperature, pressure, stress, strain and displacement (TPSSD) are obtained so that for the two critical stages before and after overcoring a reasonable estimate of the in situ stresses can be obtained. As well as the strain changes, the temperature and pressure at the wellbore wall, which vary with time, are also required to find in situ stresses in the inverse model. Fortunately, their effects become progressively less important with time due to the small size of overcored sample. The critical time is calculated when the thermal and porous effects can be ignored. Two cases, i.e. constant and exponentially time-varying temperature boundary conditions, are investigated. [ABSTRACT FROM AUTHOR]

We present an unprecedented set of high‐resolution climate simulations, consisting of a 500‐year pre‐industrial control simulation and a 250‐year historical and future climate simulation from 1850 to 2100. A high‐resolution configuration of the Community Earth System Model version 1.3 (CESM1.3) is used for the simulations with a nominal horizontal resolution of 0.25° for the atmosphere and land models and 0.1° for the ocean and sea‐ice models. At these resolutions, the model permits tropical cyclones and ocean mesoscale eddies, allowing interactions between these synoptic and mesoscale phenomena with large‐scale circulations. An overview of the results from these simulations is provided with a focus on model drift, mean climate, internal modes of variability, representation of the historical and future climates, and extreme events. Comparisons are made to solutions from an identical set of simulations using the standard resolution (nominal 1°) CESM1.3 and to available observations for the historical period to address some key scientific questions concerning the impact and benefit of increasing model horizontal resolution in climate simulations. An emerging prominent feature of the high‐resolution pre‐industrial simulation is the intermittent occurrence of polynyas in the Weddell Sea and its interaction with an Interdecadal Pacific Oscillation. Overall, high‐resolution simulations show significant improvements in representing global mean temperature changes, seasonal cycle of sea‐surface temperature and mixed layer depth, extreme events and in relationships between extreme events and climate modes. Plain Language Summary: Although the current generation of climate models has demonstrated high fidelity in simulating and projecting global temperature change, these models show large uncertainties when it comes to questions concerning how rising global temperatures will impact local weather conditions. This is because the resolution (~100 km) at which the majority of climate models simulate the climate is not fine enough to resolve these small‐scale regional features. Conducting long‐term (multi‐centuries) high‐resolution (~10 km) climate simulations has been a great challenge for the research community due to the extremely high computational demands. Through international collaboration, we are able to address this challenge by delivering an unprecedented set of multi‐century high‐resolution climate simulations using the Community Earth System Model (CESM), capable of directly representing tropical cyclones and extreme rainfall events. In this paper, we give an overall assessment of the value and benefit of the high‐resolution CESM climate simulations by making a direct comparison to an identical set of low‐resolution CESM simulations. We showcase some of the major improvements of the high‐resolution CESM in simulating global mean temperature changes, seasonal cycle of sea‐surface temperature, and extreme events, such as tropical cyclones and relationships between tropical cyclones and El Niño‐Southern Oscillation. Key Points: An unprecedented set of multi‐century high‐resolution Community Earth System Model (CESM) simulations is describedHigh‐resolution CESM simulations reveal a potential role of Southern Ocean polynyas in multidecadal climate variabilityHigh‐resolution CESM exhibits significantly improved simulations of extreme events, such as tropical cyclones and atmospheric rivers [ABSTRACT FROM AUTHOR]

Given current emissions trends an increase in global temperatures in excess of 2°C is highly likely in the coming century. In this context, it seems increasingly probable that states may consider solar geoengineering as a stop-gap climate response. Solar geoengineering refers to measures that aim to alleviate some measure of global warming by intentionally increasing the amount of the sun's energy that is reflected into space. Currently the two most discussed solar geoengineering techniques involve either marine cloud brightening or dispersing aerosols in the stratosphere. These techniques could be relatively inexpensive, are within the technological capacities (after a brief period of development) of technologically-advanced countries, and could have an almost immediate impact on temperatures. Yet, while solar geoengineering might potentially be utilised to manage some climate-linked security threats, it itself would create new security challenges. Consequently, this paper explores potential international security implications for Australia if a regional state, or group of states, initiates a solar geoengineering program. We conclude that since solar geoengineering is unlikely to become a first-order international issue, disputation over solar geoengineering will likely reflect, or act as a proxy for, wider patterns of state interaction. However, scenarios in which China and the United States take different positions, or in which there are divisions among regional powers, such as Indonesia, Malaysia, India and Singapore would pose the greatest threat to Australia's national security. [ABSTRACT FROM AUTHOR]

How climate change will unfold in the years to come is a central topic in today's environmental debate, in particular at the regional level. While projections using large ensembles of global climate models consistently indicate a future decrease in summer precipitation over southern Europe and an increase over northern Europe, individual models substantially modulate these distinct signals of change in precipitation. So far model improvements and higher resolution from regional downscaling have not been seen as able to resolve these disagreements. In this paper we assess whether 2 decades of investments in large ensembles of downscaling experiments with regional climate model simulations for Europe have contributed to a more robust model assessment of the future climate at a range of geographical scales. We study climate change projections of European seasonal temperature and precipitation using an ensemble-suite comprised by all readily available pan-European regional model projections for the twenty-first-century, representing increasing model resolution from ~ 50 to ~ 12 km grid distance, as well as lateral boundary and sea surface temperature conditions from a variety of global model simulations. Employing a simple scaling with global mean temperature change we identify emerging robust signals of future seasonal temperature and precipitation changes also found to resemble current observed trends, where these are judged to be statistically significant. [ABSTRACT FROM AUTHOR]

In view of severe changes in temperature during different seasons in cold areas of northern China, the decay of battery capacity of electric vehicles poses a problem. This paper uses an electric bus power system with semi-active hybrid energy storage system (HESS) as the research object and proposes a convex power distribution strategy to optimize the battery current that represents degradation of battery capacity based on the analysis of semi-empirical LiFePO4 battery life decline model. Simulation results show that, at a room temperature of 25 °C, during a daily trip organized by the Harbin City Driving Cycle including four cycle lines and four charging phases, the percentage of battery degradation was 9.6 × 10-3%. According to the average temperature of different months in Harbin, the percentage of battery degradation of the power distribution strategy proposed in this paper is 3.15% in one year; the electric bus can operate for 6.4 years until its capacity reduces to 80% of its initial value, and it can operate for 0.51 year more than the rule-based power distribution strategy. [ABSTRACT FROM AUTHOR]

This paper examines the performance of three climate re-analysis datasets in Angola, namely the ERA-40, NCEP-r1 and JRA-55, by comparing annual and seasonal estimates of precipitation, surface air temperature and evaporation with ground observation measurements. The observational dataset describes a region poorly covered by international climate databases and it is believed that most of its data have not been used in the data assimilation procedures of the climate models. This paper therefore provides a fresh look at the performance of these climate re-analysis datasets in a vast area where distance and civil war have hindered ground monitoring efforts. The re-analysis exercises offer better temperature estimates than precipitation estimates. When offered, the evaporation estimates from all three products are very poor. The three products are able to describe the main features of the spatial distribution of average annual precipitation and temperature, but struggle to reproduce the temporal changes of these variables. The results from a set of performance criteria show that the correlation between the observed ground measurements and re-analysis estimates is poor overall and the NSE values indicate that the average measured value at each location is usually a better estimate than the re-analysis estimate.EDITOR A. CastellarinASSOCIATE EDITOR S. Kanae [ABSTRACT FROM AUTHOR]

In a recent paper, Gupta et al., (2015), analyzed whether sunspot numbers cause global temperatures based on monthly data covering the period 1880:1–2013:9. The authors find that standard time domain Granger causality test fails to reject the null hypothesis that sunspot numbers do not cause global temperatures for both full and sub-samples, namely 1880:1–1936:2, ​1936:3–1986:11 and 1986:12–2013:9 (identified based on tests of structural breaks). However, frequency domain causality test detects predictability for the full-sample at short (2–2.6 months) cycle lengths, but not the sub-samples. But since, full-sample causality cannot be relied upon due to structural breaks, Gupta et al., (2015) conclude that the evidence of causality running from sunspot numbers to global temperatures is weak and inconclusive. Given the importance of the issue of global warming, our current paper aims to revisit this issue of whether sunspot numbers cause global temperatures, using the same data set and sub-samples used by Gupta et al., (2015), based on an nonparametric Singular Spectrum Analysis (SSA)-based causality test. Based on this test, we however, show that sunspot numbers have predictive ability for global temperatures for the three sub-samples, over and above the full-sample. Thus, generally speaking, our non-parametric SSA-based causality test outperformed both time domain and frequency domain causality tests and highlighted that sunspot numbers have always been important in predicting global temperatures. [ABSTRACT FROM AUTHOR]

Germination is a high-risk phase in a plant's life cycle and is directly regulated by temperature. Seeds germinate over a range of temperatures within which there is an optimum temperature, with thresholds above and below which no germination occurs. Rapid changes in temperature associated with global warming may cause a disconnect between temperatures a seed experiences and temperatures over which germination can occur. This paper explores the temperature dimension of the germination niche of eight herbaceous species from South West Western Australia as part of a broader assessment of endemic native species at risk of decline under global warming. The data obtained from germination studies on a temperature gradient plate were used to populate models to predict optimum germination responses (mean time to germination, germination timing and success) under current (1950–2000 averages) and future (2070 high greenhouse gas emission) temperature scenarios. The species exhibited a mix of germination responses, often with high tolerance to high diurnal temperatures. A number of species did not reach their full potential within the experimental period, indicating the presence of dormancy not overcome due to temperature alone. Modelling revealed that for some species the opportunity for germination may decline due to rising temperatures, but for others there would be little change, though a shift in germination timing may be expected. This approach to identifying extinction risk contributes tangibly to efforts to predict plant responses to environmental change and can help prioritize species for management actions, direct limited resources towards further investigations and supplement bioclimatic modelling. [ABSTRACT FROM AUTHOR]

This paper examined the temperature changes from the COordinated Regional climate Downscaling Experiment (CORDEX) over the Middle East and North Africa (MENA) domain called CORDEX-MENA. The focus is on the Arabian Peninsula in the 21st century, using data from three Coupled Model Intercomparison Project Phase 5 (CMIP5) models downscaled by RegCM4, a regional climate model. The analysis includes surface observations along with RegCM4 simulations and changes in threshold based on extreme temperature at the end of the 21st century relative to the base period (1971–2000). Irrespective of the driving CMIP5 models, the RegCM4 simulations show enhanced future temperature changes for RCP8.5 as compared to RCP4.5. The Arabian Peninsula will warm at a faster rate (0.83°C per decade) as compared to the entire domain (0.79°C per decade) for RCP8.5 during the period 2071–2100. Moreover, the number of hot days (Tmax ≥ 50°C) (cold nights: Tmin ≤ 5°C) will increase (decrease) faster in the Arabian Peninsula as compared to the entire domain. This increase (decrease) of hot days (cold nights) will be more prominent in the far future (2071–2100) as compared to the near future (2021–2050) period. Moreover, the future changes in temperature over the main cities in Saudi Arabia are also projected. The RegCM4-based temperature simulation data from two suitable CMIP5 models are recommended as a useful database for further climate-change-related studies. [ABSTRACT FROM AUTHOR]

Abstract Biomass has often been regarded as a promising renewable energy resource to mitigate climate change. However, what will be the impact on global surface temperature if biomass replace fossil fuel remain unclear. This paper, through a case study in Uttar Pradesh, India address this issue by assessing biomass resource potential to reduce fossil fuel demand and mitigate climate change. Impact of biomass power related GHG emissions on global surface temperature is estimated using the Absolute Global Temperature change Potential (AGTP) climate metric. Uttar Pradesh can produce 71 Mt surplus biomass annually, equivalent to 7298 MW power. Power density of biomass range between 0.10 and 0.25 Wm-2. Significant amount of GHG emissions reduction is possible if biomass replace fossil fuel as a power source in the region. Annual GHG emissions associated with 1 MWh of power derived from coal, natural gas and biomass would cause 4.10 × 10−7, 2.40 × 10−7 and 1.25 × 10−7 mK rise in global surface temperature, 100 years after an initial emission, indicating potential of biomass power to mitigate climate change. Variation in spatio-temporal distribution and low power density could be delimiting factors in large-scale deployment of biomass power. Graphical abstract Image 1 Highlights • Biomass resources and power potentials are assessed for Uttar Pradesh, India. • GHG emissions from biomass power is assessed and compared with fossil fuels. • Climatic impact of power generation is assessed via novel climate metric. • Biomass power can mitigate climate change by replacing fossil fuels. • Spatio-temporal variability and low power density are limitations of biomass. [ABSTRACT FROM AUTHOR]

The phase shift between changes in the global surface temperature Tg and atmospheric CO2 content has been shown earlier not to characterize causal relationships in the Earth system in the general case. Specifically, the sign of this phase shift under nongreenhouse radiative forcing changes depends on the time scale of this forcing. This paper analyzes the phase shift between changes in the global surface temperature Tg and the atmospheric CO2 content under synchronous external emissions of carbon dioxide and methane into the atmosphere on the basis of numerical experiments with the IAP RAS climatic model and a conceptual climate model with carbon cycle. For a sufficiently large time scale of external forcing, the changes in lag relative to the corresponding changes in Tg. [ABSTRACT FROM AUTHOR]

During the analysis of solar activity impact on climate, the emphasis is placed on temperature changes. Earth's atmosphere is a dynamical system with a complex variability in space and time. Due to the fact that caves in Karst preserve the long term environmental changes, the investigation of the in-caves' atmospheric parameters and their variations with time becomes very important in the last quarter of century. In this paper we investigate the temporal evolution of the temperature and pressure of the ground atmospheric layer in the region of two Bulgarian caves: Snezhanka (Pazardjik region) and Uhlovitsa (Smolyan region), during the period 2005-2017. We show that thermal and mass exchange of the caves' air with the environment has significant temporal variations. On annual basis the thermodynamical parameters of the observed caves behaves as a barotropic fluid, in which the air density depends only on atmospheric pressure. As a result, the temporal evolution of in-caves' pressure and temperature change synchronously with time. The observed 11-year signal could be attributed to the heliospheric modulation of galactic cosmic ray (GCR) intensity, which modulates the ozone and humidity near the tropopause and correspondingly the strength of the atmospheric greenhouse effect. Our study helps to clarify the influence of helio-geophysical factors on the state of the lower atmosphere. [ABSTRACT FROM AUTHOR]

Over the past hundred years, remarkable changes occurred around global climate. Two significant characteristics of climate changes are temperature mutation and warming hiatus, which led to a variety of extreme climate events of all scales, such as in the north of China. Therefore, revealing the features and rules of temperature mutation and warming hiatus in northern China could provide some basis to deeply understand climate changes, prevent and mitigate disasters as well as improve ecological environment in northern China and in the whole world. Based on the seasonal (monthly) average minimum temperature, average temperature and average maximum temperature data at 357 meteorological stations in northern China and surrounding areas during 1951-2014, this paper analyzes the spatio- temporal variation of three types of seasonal temperature (the average minimum temperature, average temperature and average maximum temperature) mutation and warming hiatus over northern China by using Mann-Kendall test, slide t test and other methods. The results indicate: according to the average minimum temperature, average temperature and average maximum temperature, the abrupt change of temperature and warming hiatus became late and the cycle from abrupt change to warming hiatus became short as the latitude reduces. In spring and winter, the temperature mutation and warming hiatus in the Northeast China were the earliest (1970s- 1980s, 1993- 2002), in North China were the second and in the Northwest China were the latest (1990s-2000s, 1996- 2010). While in summer and autumn, the temperature mutation and warming hiatus in North China were the earliest, in Northeast China were the second and in Northwest China were the latest (1990s- 2010s). There was little distinction among areas in warming hiatus year. Meteorological stations with no mutation and no hiatus were centralized in mountainous regions, high- latitude areas and southern part of North China Plain where the surrounding areas were relatively late in mutation and warming hiatus. The mutations and warming hiatus of same kinds of temperature became late in the order of winter (1981- 1990), spring, autumn and summer (1994-2008) and winter (1995-2008), autumn, summer and spring (1998-2010). The cycle from temperature mutated to warming hiatus became short in the sequence of winter, spring, autumn and summer, during which the average minimum temperature period was the longest in winter (9- 24 a). The average minimum temperature mutated earliest in spring, summer and winter, which occurred during 1972-1999, 1987-1999 and 1971-2000, the average temperature was the second to mutate, while the average maximum temperature was the latest to mutate which occurred during 1975- 2008, 1994- 2008, 1972- 2006. However, in autumn, the mutation of the average temperature was the earliest (1982-2001), the mutation of the lowest average temperature was the second, and the mutation of the highest average temperature was the latest (1987-2001). The warming hiatus of the average minimum temperature, average temperature and average maximum temperature in spring and summer became late successively, which were during 1994- 2008, 1997-2008 and 1997-2010, respectively, while the sequence was opposite in autumn and winter. The lengths of periods from temperature mutation to warming hiatus in each season in order were that of the average minimum temperature (9-18 a), that of the average temperature and that of the average maximum temperature (5- 12 a). In particular, the three kinds of temperatures all mutated earliest in the southern of North China in summer, which is inconsistent with the rule in the whole area that the mutation became late as latitude decreases, and the temperature at most stations in this area did not mutate, which is also inconsistent with the general rule in the whole area. [ABSTRACT FROM AUTHOR]

The concept of vulnerability is well established in the climate change literature, underpinning significant research effort. The ability of vulnerability research to capture the complexities of climate-society dynamics has been increasingly questioned, however. In this paper, we identify, characterize, and evaluate concerns over the use of vulnerability approaches in the climate change field based on a review of peer-reviewed articles published since 1990 (n = 587). Seven concerns are identified: neglect of social drivers, promotion of a static understanding of human-environment interactions, vagueness about the concept of vulnerability, neglect of cross-scale interactions, passive and negative framing, limited influence on decision-making, and limited collaboration across disciplines. Examining each concern against trends in the literature, we find some of these concerns weakly justified, but others pose valid challenges to vulnerability research. Efforts to revitalize vulnerability research are needed, with priority areas including developing the next generation of empirical studies, catalyzing collaboration across disciplines to leverage and build on the strengths of divergent intellectual traditions involved in vulnerability research, and linking research to the practical realities of decision-making. [ABSTRACT FROM AUTHOR]

In this paper we analyse whether (anthropometric) CO 2 can forecast global temperature anomaly (GT) over an annual out-of-sample period of 1907–2012, which corresponds to an initial in-sample of 1880–1906. For our purpose, we use 12 parametric and nonparametric univariate (of GT only) and multivariate (including both GT and CO 2 ) models. Our results show that the Horizontal Multivariate Singular Spectral Analysis (HMSSA) techniques (both Recurrent (-R) and Vector (-V)) consistently outperform the other competing models. More importantly, from the performance of the HMSSA-V model we find conclusive evidence that CO 2 can forecast GT, and also predict its direction of change. Our results highlight the superiority of the nonparametric approach of SSA, which in turn, allows us to handle any statistical process: linear or nonlinear, stationary or non-stationary, Gaussian or non-Gaussian. [ABSTRACT FROM AUTHOR]

Accurate predictions of drought events to plan and manage the adverse effects of drought on agriculture and the environment requires tools that precisely predict standardized drought metrics. Improving on the World Meteorological Organization approved Standardized Precipitation Index (SPI), the multi-scalar Standardized Precipitation and Evapotranspiration Index ( SPE I), a variant of the SPI, is a relatively recent drought index, which takes into account the impacts of temperature change on overall dryness, along with precipitation and evapotranspiration effects. In this paper, an extreme learning machine (ELM) model was applied to predict SPE I in a drought-prone region in eastern Australia, and the quality of the model's performance was compared to that of a multiple linear regression (MLR), an artificial neural network (ANN), and a least support vector regression (LSSVR) model. The SPE I data were derived from climatic variables recorded at six weather stations between January 1915 and December 2012. Model performance was evaluated by means of the normalized root mean square error (NRMSE), normalized mean absolute error (NMAE), coefficients of determination (r 2 ), and the Nash-Sutcliffe efficiency coefficient (NASH) in the testing period. Results showed that the ELM and ANN models outperformed the MLR and LSSVR models, and all four models revealed a greater predictive accuracy for the 12-month compared to the 3-month SPE I predictions. For the 12-month SPE I predictions, optimal models had r 2 that ranged from 0.668 for the LSSVR model (Station 6) to 0.894 for the ANN model (Station 4). The good agreement between observed and predicted SPE I at different locations within the study region indicated the potential of the developed models to contribute to a more thorough understanding of potential future drought-risks in eastern Australia, and their applicability to drought assessments over multiple timescales. The models and findings have useful implications for water resources assessment in drought-prone regions. [ABSTRACT FROM AUTHOR]

Hydrological sensitivity is the change in global-mean precipitation per degree of global-mean temperature change. This paper shows that the hydrological sensitivity of the response to anthropogenic aerosol forcing is distinct from that of the combined response to all other forcings and that this difference is sufficient to infer the associated cooling in global-mean temperature. This result is demonstrated using temperature and precipitation data generated by climate models and is robust across different climate models. Remarkably, greenhouse gas warming and aerosol cooling can be estimated in a model without using any spatial or temporal gradient information in the response, provided temperature data are augmented by precipitation data. Over the late twentieth century, the hydrological sensitivities of climate models differ significantly from that of observations. Whether this discrepancy can be attributed to observational error, which is substantial as different estimates of global-mean precipitation are not even significantly correlated with each other, or to model error is unclear. The results highlight the urgency to construct accurate estimates of global precipitation from past observations and for reducing model uncertainty in hydrological sensitivity. This paper also clarifies that previous estimates of hydrological sensitivity are limited in that standard regression methods neglect temperature-precipitation relations that occur through internal variability. An alternative method for estimating hydrological sensitivity that overcomes this limitation is presented. [ABSTRACT FROM AUTHOR]

This paper analyses the kinematic parameters and the positioning accuracy of robot end effectors influenced by temperature factors. Temperature factors include robot self-heating and environmental temperature changes. This paper also builds the thermal distribution model and deformation model using finite element theory. A thermal compensation strategy is presented to validate the significant correlation between the robot kinematics parameters and previous thermal models mentioned above. It is convenient and suitable for industrial field. Thermal compensation is experimentally proved to adjust the position error of the end effectors by less than 0.1 mm. [ABSTRACT FROM AUTHOR]

The changes and oscillations in air temperature during the second half of the 20th and in the early 21st century, have become one of the major concerns of almost all scientific disciplines. Such changes are noticeable both at the local and global level. The objective of this paper is to point out that the changes of this climate element can also be detected at the local level. The research underlying this paper is, in terms of territory, limited to the Sokobanja basin in Eastern Serbia. The analysis relies on the data on air temperature for the period 1946-2012 taken from the Meteorological weather station located in Sokobanja. The obtained data were processed in line with the recommendations of the World Meteorological Organization. The evidenced statistically significant changes in air temperature were examined using the following statistical tests: Pettit test, Standard Normal Homogeneity test, Buishand range test, and von Neumann test. [ABSTRACT FROM AUTHOR]

Integrated assessment models and coupled earth system models both have their limitations in understanding the interactions between human activity and the physical earth system. In this paper, a new human-earth system model, BNU-HESM1.0, constructed by combining the economic and climate damage components of the Dynamic Integrated Model of Climate Change and Economy to the BNU-ESM model, is introduced. The ability of BNU-HESM1.0 in simulating the global CO concentration and surface temperature is also evaluated. We find that, compared to observation, BNU-HESM1.0 underestimates the global CO concentration and its rising trend during 1965-2005, due to the uncertainty in the economic components. However, the surface temperature simulated by BNU-HESM1.0 is much closer to observation, resulting from the overestimates of surface temperature by the original BNU-ESM model. The uncertainty of BNU-ESM falls within the range of present earth system uncertainty, so it is the economic and climate damage component of BNU-HESM1.0 that needs to be improved through further study. However, the main purpose of this paper is to introduce a new approach to investigate the complex relationship between human activity and the earth system. It is hoped that it will inspire further ideas that prove valuable in guiding human activities appropriate for a sustainable future climate. [ABSTRACT FROM AUTHOR]