Regional Surface Temperature Research Articles

Downturn in scaling of UK extreme rainfall with temperature for future hottest days

Extreme daily precipitation is thought to increase with warming at a rate of 6.5% per K. High-resolution simulations for the southern UK show this scaling for present conditions, but above 22 °C this scaling fails owing to changes in dynamics. Extreme daily precipitation is thought to increase with temperature at a rate of 6.5% per K according to the Clausius–Clapeyron relationship between temperature and saturation vapour pressure1. A wide range of scaling relationships has been observed globally for extreme daily and hourly precipitation, with evidence of scaling above 6.5% per K for sub-daily extreme precipitation in some regions2,3,4. Only high-resolution climate models can simulate this scaling relationship5. Here we examine the scaling of hourly extreme precipitation intensities in a future climate using experiments with a model for the southern UK with kilometre-scale resolution6. Our model simulates the present-day scaling relationship at 6.5% per K, in agreement with observations. The simulated overall future increase in extreme precipitation follows the same relationship. However, UK extreme precipitation intensities decline at temperatures above about 22 °C—a temperature range that is not well sampled in the present-day integration—as a result of a more frequent occurrence of anticyclonic weather systems. Anticyclones produce more days with strong daytime heating, but are not favourable to the development of deep intense convective storms. We conclude that future extreme hourly precipitation intensities cannot simply be extrapolated from present-day temperature scaling, and demonstrate the pitfalls of using regional surface temperature as a scaling variable.

Dynamics of Land Surface Temperature in the Central Tien Shan Mountains

Permafrost conditions in mountain ranges are sensitive to regional land surface temperature (LST), among other factors. To explore that relationship, this study carried out 3 steps: (1) validated Moderate Resolution Imaging Spectroradiometer 1-km daily LST data using data measured in situ, (2) used the Harmonic Analysis of Time Series (HANTS) algorithm for fitting and removing the influence of clouds, and (3) analyzed the spatial and temporal characteristics of LST dynamics in the central Tien Shan mountain range based on remote-sensing data improved by covariance and empirical orthogonal function analysis. The results indicate that the in situ data present a basic reference for rebuilding invalid values in the retrieved data, and the data gap in daily LST products can be logically reconstructed with the HANTS algorithm. Major long-term and large-scale patterns can be well extracted with the reconstructed LST data. The most dynamic and sensitive LST areas occurred in the buffers around the periglacial are...

Atmospheric responses to the redistribution of anthropogenic aerosols

AbstractThe geographical shift of global anthropogenic aerosols from the developed countries to the Asian continent since the 1980s could potentially perturb the regional and global climate due to aerosol‐cloud‐radiation interactions. We use an atmospheric general circulation model with different aerosol scenarios to investigate the radiative and microphysical effects of anthropogenic aerosols from different regions on the radiation budget, precipitation, and large‐scale circulations. An experiment contrasting anthropogenic aerosol scenarios in 1970 and 2010 shows that the altered cloud reflectivity and solar extinction by aerosols results in regional surface temperature cooling in East and South Asia, and warming in the US and Europe, respectively. These aerosol‐induced temperature changes are consistent with the relative temperature trends from 1980 to 2010 over different regions in the reanalysis data. A reduced meridional streamfunction and zonal winds over the tropics as well as a poleward shift of the jet stream suggest weakened and expanded tropical circulations, which are induced by the redistributed aerosols through a relaxing of the meridional temperature gradient. Consequently, precipitation is suppressed in the deep tropics and enhanced in the subtropics. Our assessments of the aerosol effects over the different regions suggest that the increasing Asian pollution accounts for the weakening of the tropics circulation, while the decreasing pollution in Europe and US tends to shift the circulation systems southward. Moreover, the aerosol indirect forcing is predominant over the total aerosol forcing in magnitude, while aerosol radiative and microphysical effects jointly shape the meridional energy distributions and modulate the circulation systems.

Reconstruction of the Peretolchin Glacier fluctuation (East Sayan) during the 20th century inferred from the bottom sediments of proglacial Lake Ekhoi

We present results of study of the bottom sediments of proglacial Lake Ekhoi, which is fed with the Peretolchin Glacier meltwater (East Sayan). The bottom deposit sequence, formed from 1885 to 2013, was investigated with a year-season time resolution, using X-ray fluorescence with synchrotron radiation (with and without scanning), the Fourier-transform infrared (FTIR) analysis, and color processing of core photos. The depth-age model of the core was based on counting of annual laminate layers with control by 210Pb, 137Cs, 238U, and 226Ra chronology. Intense glacier thawing was calculated from the amount of clastic matter supplied by the glacier meltwater into the lake. The elemental composition of the bottom sediments includes three groups reflecting periods of displacement of the glacier front and the intensity of evolution of aquatic biota. The first group of elements (Ca, K, Ti, Fe, and Mn) characterizes the supply of clastic matter without serious changes in the glacier edges. The second group (Ni, Cu, Br, and U) is responsible for the intensity of evolution of aquatic biota. Finally, the third group (Rb, Sr, Zr, Nb, Y, and Th) can describe the intensity of displacement of the glacier front. Intensive glacier thawing has proceeded since 1920; however, the glacier retreat was insignificant till 1947. From 1947 to 1970, the glacier rapidly retreated, especially in the period 1953–1970. This was induced by steady high regional summer surface temperature in 1938–1970. The following glacier retreat was during 1980–2000, synchronously with the global temperature anomaly in the Northern Hemisphere. Since 2000, the melting has slowed.

Interacting components of the top‐of‐atmosphere energy balance affect changes in regional surface temperature

AbstractThe role of interactions between components of the top‐of‐atmosphere (TOA) energy balance in determining regional surface temperature changes, such as polar amplification, is examined in diffusive energy balance model (EBM) simulations. These interactions have implications for the interpretation of local feedback analyses when they are applied to regional surface temperature changes. Local feedback analysis succeeds at accounting for the EBM‐simulated temperature change given the changes in the radiative forcing, atmospheric energy transport, and radiative feedbacks. However, the inferences about the effect of individual components of the TOA energy balance on regional temperature changes do not account for EBM simulations in which individual components are prescribed or “locked.” As changes in one component of the TOA energy balance affect others, unambiguous attribution statements relating changes in regional temperature or its intermodel spread to individual terms in the TOA energy balance cannot be made.

Assessment of Bias Assumptions for Climate Models

Abstract Climate scenarios make implicit or explicit assumptions about the extrapolation of climate model biases from current to future time periods. Such assumptions are inevitable because of the lack of future observations. This manuscript reviews different bias assumptions found in the literature and provides measures to assess their validity. The authors explicitly separate climate change from multidecadal variability to systematically analyze climate model biases in seasonal and regional surface temperature averages, using global and regional climate models (GCMs and RCMs) from the Ensemble-Based Predictions of Climate Changes and Their Impacts (ENSEMBLES) project over Europe. For centennial time scales, it is found that a linear bias extrapolation for GCMs is best supported by the analysis: that is, it is generally not correct to assume that model biases are independent of the climate state. Results also show that RCMs behave markedly differently when forced with different drivers. RCM and GCM biases are not additive, and there is a significant interaction component in the bias of the RCM–GCM model chain that depends on both the RCM and GCM considered. This result questions previous studies that deduce biases (and ultimately projections) in RCM–GCM combinations from reanalysis-driven simulations. The authors suggest that the aforementioned interaction component derives from the refined RCM representation of dynamical and physical processes in the lower troposphere, which may nonlinearly depend upon the larger-scale circulation stemming from the driving GCM. The authors’ analyses also show that RCMs provide added value and that the combined RCM–GCM approach yields, in general, smaller biases in seasonal surface temperature and interannual variability, particularly in summer and even for spatial scales that are, in principle, well resolved by the GCMs.

Influence of Amazonian deforestation on the future evolution of regional surface fluxes, circulation, surface temperature and precipitation

The extent of the Amazon rainforest is projected to drastically decrease in future decades because of land-use changes. Previous climate modelling studies have found that the biogeophysical effects of future Amazonian deforestation will likely increase surface temperatures and reduce precipitation locally. However, the magnitude of these changes and the potential existence of tipping points in the underlying relationships is still highly uncertain. Using a regional climate model at a resolution of about 50 km over the South American continent, we perform four ERA-interim-driven simulations with prescribed land cover maps corresponding to present-day vegetation, two deforestation scenarios for the twenty-first century, and a totally-deforested Amazon case. In response to projected land cover changes for 2100, we find an annual mean surface temperature increase of \(0.5\,^{\circ }\hbox {C}\) over the Amazonian region and an annual mean decrease in rainfall of 0.17 mm/day compared to present-day conditions. These estimates reach \(0.8\,^{\circ }\hbox {C}\) and 0.22 mm/day in the total-deforestation case. We also compare our results to those from 28 previous (regional and global) climate modelling experiments. We show that the historical development of climate models did not modify the median estimate of the Amazonian climate sensitivity to deforestation, but led to a reduction of its uncertainty. Our results suggest that the biogeophysical effects of deforestation alone are unlikely to lead to a tipping point in the evolution of the regional climate under present-day climate conditions. However, the conducted synthesis of the literature reveals that this behaviour may be model-dependent, and the greenhouse gas-induced climate forcing and biogeochemical feedbacks should also be taken into account to fully assess the future climate of this region.

Characterizing the Climate Feedback Pattern in the NCAR CCSM3-SOM Using Hourly Data

Abstract The climate feedback–response analysis method (CFRAM) was applied to 10-yr hourly output of the NCAR Community Climate System Model, version 3, using the slab ocean model (CCSM3-SOM), to analyze the strength and spatial distribution of climate feedbacks and to characterize their contributions to the global and regional surface temperature Ts changes in response to a doubling of CO2. The global mean bias in the sum of partial Ts changes associated with the CO2 forcing, and each feedback derived with the CFRAM analysis is about 2% of Ts change obtained directly from the CCSM3-SOM simulations. The pattern correlation between the two is 0.94, indicating that the CFRAM analysis using hourly model output is accurate and thus is appropriate for quantifying the contributions of climate feedback to the formation of global and regional warming patterns. For global mean Ts, the largest contributor to the warming is water vapor feedback, followed by the direct CO2 forcing and albedo feedback. The albedo feedback exhibits the largest spatial variation, followed by shortwave cloud feedback. In terms of pattern correlation and RMS difference with the modeled global surface warming, longwave cloud feedback contributes the most. On zonal average, albedo feedback is the largest contributor to the stronger warming in high latitudes than in the tropics. The longwave cloud feedback further amplifies the latitudinal warming contrast. Both the land–ocean warming difference and contributions of climate feedbacks to it vary with latitude. Equatorward of 50°, shortwave cloud feedback and dynamical advection are the two largest contributors. The land–ocean warming difference on the hemispheric scale is mainly attributable to longwave cloud feedback and convection.

Observations of urban boundary layer structure during a strong urban heat island event

It has long been known that the urban surface energy balance is different to that of a rural surface, and that heating of the urban surface after sunset gives rise to the Urban Heat Island (UHI). Less well known is how flow and turbulence structure above the urban surface are changed during different phases of the urban boundary layer (UBL). This paper presents new observations above both an urban and rural surface and investigates how much UBL structure deviates from classical behaviour. A 5-day, low wind, cloudless, high pressure period over London, UK, was chosen for analysis, during which there was a strong UHI. Boundary layer evolution for both sites was determined by the diurnal cycle in sensible heat flux, with an extended decay period of approximately 4 h for the convective UBL. This is referred to as the “Urban Convective Island” as the surrounding rural area was already stable at this time. Mixing height magnitude depended on the combination of regional temperature profiles and surface temperature. Given the daytime UHI intensity of \(1.5\,^\circ \mathrm{C}\), combined with multiple inversions in the temperature profile, urban and rural mixing heights underwent opposite trends over the period, resulting in a factor of three height difference by the fifth day. Nocturnal jets undergoing inertial oscillations were observed aloft in the urban wind profile as soon as the rural boundary layer became stable: clear jet maxima over the urban surface only emerged once the UBL had become stable. This was due to mixing during the Urban Convective Island reducing shear. Analysis of turbulent moments (variance, skewness and kurtosis) showed “upside-down” boundary layer characteristics on some mornings during initial rapid growth of the convective UBL. During the “Urban Convective Island” phase, turbulence structure still resembled a classical convective boundary layer but with some influence from shear aloft, depending on jet strength. These results demonstrate that appropriate choice of Doppler lidar scan patterns can give detailed profiles of UBL flow. Insights drawn from the observations have implications for accuracy of boundary conditions when simulating urban flow and dispersion, as the UBL is clearly the result of processes driven not only by local surface conditions but also regional atmospheric structure.

Research on the Relationship of Surface Temperature and Urban Heat Island Using the Thermal Infrared Remote Sensing Image

The temperature of the earth's land surface plays a very import ant role in the land-air interactions. It is critical parameters in the research of global change. Therefore, the use of satellite remote sensing data for surface temperature retrieval has become an important task of the study. Regional surface temperature is an important parameter of thermal energy distribution in the region, to obtain which is the most convenient and effective method. Thermal infrared remote sensing is an important area, and from thermal infrared remote sensing image information extracting temperature is a prerequisite for applying thermal infrared remote sensing technology .Based on remote sensing image data reading, radiometric calibration, regional cropping pretreatment; Then Landsat band 6 inversion of surface brightness temperature, It introduces the effect of the urban heat island using Landsat remote sensing ,having obtained the changes of spatial distribution of surface temperature, and prospects for future development in this field.

North Atlantic Multidecadal SST Oscillation: External forcing versus internal variability

The Atlantic Multi-decadal Oscillation (AMO) depicts the swings of North Atlantic basin-wide sea surface temperature (SST) between warm and cold phases on a multi-decadal time scale. The 20th Century instrumental record indicates a relative cold period in the beginning of the 20th Century, a warm period in the 1940s and 50s, another cold period in the 1970s and 80s, followed by the recent warming period. These multi-decadal temperature swings coincide with an upward warming trend throughout the 20th Century. One of the central questions concerning these changes is whether they were caused by human activities, including aerosols and greenhouse gas forcing, or whether they reflect some combination between natural factors and human activity. Using both observations and CMIP3 model simulations, we argue that the overall changes are due to the combination of natural multidecadal variability and anthropogenic forcing. We also examine the regional surface temperature, precipitation, and atmospheric circulation features associated with the externally forced and internal North Atlantic SST multidecadal variability using both 20th Century observations and CMIP3 model simulations of the 20th, 21st, and pre-industrial forcing.

Evidence of a large cooling between 1690 and 1740 AD in southern Africa

A 350-year-long, well-dated δ18O stalagmite record from the summer rainfall region in South Africa is positively correlated with regional air surface temperatures at interannual time scales. The coldest period documented in this record occurred between 1690 and 1740, slightly lagging the Maunder Minimum (1645–1710). A temperature reconstruction, based on the correlation between regional surface temperatures and the stalagmite δ18O variations, indicates that parts of this period could have been as much as 1.4°C colder than today. Significant cycles of 22, 11 and 4.8 years demonstrate that the solar magnetic and the El Niño-Southern Oscillation cycle could be important drivers of multidecadal to interannual climate variability in this region. The observation that the most important driver of stalagmite δ18O on interannual time scales from this subtropical region is regional surface temperature cautions against deterministic interpretations of δ18O variations in low-latitude stalagmites as mainly driven by the amount of precipitation.

A Physically Based Spatial Expansion Algorithm for Surface Air Temperature and Humidity

An algorithm was developed to expand the surface air temperature and air humidity to a larger spatial domain, based on the fact that the variation of surface air temperature and air humidity is controlled jointly by the local turbulence and the horizontal advection. This study proposed an algorithm which considers the advective driving force outside the thermal balance system and the turbulent driving force and radiant driving force inside the thermal balance system. The surface air temperature is determined by a combination of the surface observations and the regional land surface temperature observed from a satellite. The average absolute difference of the algorithm is 0.65 degree and 0.31 mb, respectively, for surface air temperature and humidity expansion, which provides a promising approach to downscale the two surface meteorological variables.

Utilization of MATLAB to Realize LST Retrieval and Thematic Mapping from FY-3/MERSI Data

Currently,application-oriented researches on the data of Medium Resolution Spectral Imager(MERSI),which is on board China's new generation polar orbit meteorological satellite FY-3,are very insufficient,due to the reason that the data as a new source have been delivered only since 2008.With the normal operation of FY-3 satellite system,it is necessary to develop an operational module for FY-3/MERSI regional land surface temperature(LST) retrieval and its post-processing,since LST is required for a wide variety of scientific studies but FY-3/MERSI's operational LST products have not yet been provided by National Satellite Meteorological Center(NSMC).Based on an analysis of FY-3/MERSI L1 data's HDF5 format and its channel characteristics,the authors selected the generalized single-channel algorithm developed by Jimenez-Mu n～oz Sobrino to directly realize the LST retrieval at 250 m spatial resolution with MATLAB programming and the thematic mapping of LST derivative products.This paper describes the parametric processes of LST retrieval algorithm in detail,which include radiometric calibration,cloud detection,estimation of two intermediate parameters-surface emissivity and atmospheric water vapor,and calculation of thermal indexes from LST.On these bases,an automatic flowchart for FY-3/MERSI LST retrieval and thematic mapping was established.Experimental results of this flowchart applied in Shanghai thermal environmental monitoring show that it can process FY-3/MERSI L1 data in a fast,real-time and automatic way,thus suitable for operational products producing and sharing,with the saving of human resources.It is also proved that FY-3/MERSI data and various forms of LST products can reveal the spatial pattern of Shanghai thermal field and the urban heat island effect more finely and intuitively.

Climate response of the South Asian monsoon system to anthropogenic aerosols

The equilibrium climate response to the total effects (direct, indirect and semi‐direct effects) of aerosols arising from anthropogenic and biomass burning emissions on the South Asian summer monsoon system is studied using a coupled atmosphere‐slab ocean model. Our results suggest that anthropogenic and biomass burning aerosols generally induce a reduction in mean summer monsoon precipitation over most parts of the Indian subcontinent, strongest along the western coastline of the Indian peninsula and eastern Nepal region, but modest increases also occur over the north western part of the subcontinent. While most of the noted reduction in precipitation is triggered by increased emissions of aerosols from anthropogenic activities, modest increases in the north west are mostly associated with decreases in local emissions of aerosols from forest fire and grass fire sources. Anthropogenic aerosols from outside Asia also contribute to the overall reduction in precipitation but the dominant contribution comes from aerosol sources within Asia. Local emissions play a more important role in the total rainfall response to anthropogenic aerosol sources during the early monsoon period, whereas both local as well as remote emissions of aerosols play almost equally important roles during the later part of the monsoon period. While precipitation responses are primarily driven by local aerosol forcing, regional surface temperature changes over the region are strongly influenced by anthropogenic aerosols from sources further away (non‐local changes). Changes in local anthropogenic organic and black carbon emissions by as much as a factor of two (preserving their ratio) produce the same basic signatures in the model's summer monsoon temperature and precipitation responses.

Spatial asymmetry of temperature trends over India and possible role of aerosols

Dissimilarities in temperature trends in space and time over the Indian region have been examined to look for signatures of aerosols’ influence. Separate temperature time series for North and South India were constructed for dry (November–May) and wet (June–October) seasons. Temperature trend for the entire period 1901–2007 and different subperiods of 1901–1950, 1951–1990, 1971–2007, and 1991–2007 have been examined to isolate the aerosol and other greenhouse gas influences on temperatures. Maximum (daytime) temperatures during dry season corresponding to North and South India show significant warming trend of 0.8 and 1.0 °C per hundred years during the period 1901–2007, while minimum temperature shows nebulous trend of 0.2 and 0.3 °C per hundred years over North and South India, respectively. During the wet season, maximum temperature shows nearly half of dry season maximum temperature warming trend. However, asymmetry is observed in dry season maximum temperature trend during post-industrial period 1951–1990 wherein the North/South India shows decreasing/increasing trends, while during the recent period 1991–2007 trends are uniformly positive for both the regions. Spatial and temporal asymmetry in observed trends clearly point to the role of aerosols in lowering temperature trends over northern India. Atmospheric aerosols could cause a negative climate forcing that can modulate the regional surface temperature trends in a significant way. As this forcing acts differentially on day and night temperatures, trends in diurnal temperature range (DTR) provide a direct assessment of impacts of aerosols on temperature trends. Time series of diurnal temperature range for dry and wet seasons have been examined separately for North and South India. Over North India, the DTR for dry season has increased gradually during the period 1901–1970 and thereafter showed decreasing trend, while trends in temperature range over Southern India were almost opposite in phase with North India. The aerosol and greenhouse gases seem to play an important role in the spatial and temporal variability of temperature range over India.

Long tails in regional surface temperature probability distributions with implications for extremes under global warming

Prior work has shown that probability distributions of column water vapor and several passive tropospheric chemical tracers exhibit longer‐than‐Gaussian (approximately exponential) tails. The tracer‐advection prototypes explaining the formation of these long‐tailed distributions motivate exploration of observed surface temperature distributions for non‐Gaussian tails. Stations with long records in various climate regimes in National Climatic Data Center Global Surface Summary of Day observations are used to examine tail characteristics for daily average, maximum and minimum surface temperature probability distributions. Each is examined for departures from a Gaussian fit to the core (here approximated as the portion of the distribution exceeding 30% of the maximum). While the core conforms to Gaussian for most distributions, roughly half the cases exhibit non‐Gaussian tails in both winter and summer seasons. Most of these are asymmetric, with a long, roughly exponential, tail on only one side. The shape of the tail has substantial implications for potential changes in extreme event occurrences under global warming. Here the change in the probability of exceeding a given threshold temperature is quantified in the simplest case of a shift in the present‐day observed distribution. Surface temperature distributions with long tails have a much smaller change in threshold exceedances (smaller increases for high‐side and smaller decreases for low‐side exceedances relative to exceedances in current climate) under a given warming than do near‐Gaussian distributions. This implies that models used to estimate changes in extreme event occurrences due to global warming should be verified regionally for accuracy of simulations of probability distribution tails.

Inhibitory Effects of Far-Infrared Ray-Emitting Belts on Primary Dysmenorrhea

This study investigated the therapeutic effect of the far-infrared ray-emitting belt (FIRB) in the management of primary dysmenorrhea in female patients. Forty adolescent females with primary dysmenorrhea were enrolled in the study. Quantitative measurements were taken during the menstruation. Several parameters were measured and compared, including temperature, abdominal blood flow, heart rate variability, and pain assessment. Statistical analysis shows that treatment with FIRB had significant efficiency in increasing regional surface temperature and abdominal blood flow, widening standard deviation of normal-to-normal RR intervals, and reducing VRS and NRS pain scores. The application of an FIRB appears to alleviate dysmenorrhea.

Improving the representation of river–groundwater interactions in land surface modeling at the regional scale: Observational evidence and parameterization applied in the Community Land Model

Summary Groundwater is an important component of the hydrological cycle, included in many land surface models to provide a lower boundary condition for soil moisture, which in turn plays a key role in the land–vegetation–atmosphere interactions and the ecosystem dynamics. In regional-scale climate applications land surface models (LSMs) are commonly coupled to atmospheric models to close the surface energy, mass and carbon balance. LSMs in these applications are used to resolve the momentum, heat, water and carbon vertical fluxes, accounting for the effect of vegetation, soil type and other surface parameters, while lack of adequate resolution prevents using them to resolve horizontal sub-grid processes. Specifically, LSMs resolve the large-scale runoff production associated with infiltration excess and sub-grid groundwater convergence, but they neglect the effect from loosing streams to groundwater. Through the analysis of observed data of soil moisture obtained from the Oklahoma Mesoscale Network stations and land surface temperature derived from MODIS we provide evidence that the regional scale soil moisture and surface temperature patterns are affected by the rivers. This is demonstrated on the basis of simulations from a land surface model (i.e., Community Land Model – CLM, version 3.5). We show that the model cannot reproduce the features of the observed soil moisture and temperature spatial patterns that are related to the underlying mechanism of reinfiltration of river water to groundwater. Therefore, we implement a simple parameterization of this process in CLM showing the ability to reproduce the soil moisture and surface temperature spatial variabilities that relate to the river distribution at regional scale. The CLM with this new parameterization is used to evaluate impacts of the improved representation of river–groundwater interactions on the simulated water cycle parameters and the surface energy budget at the regional scale.

Sensitivity of atmospheric CO<sub>2</sub> and climate to explosive volcanic eruptions

Abstract. Impacts of low-latitude, explosive volcanic eruptions on climate and the carbon cycle are quantified by forcing a comprehensive, fully coupled carbon cycle-climate model with pulse-like stratospheric aerosol optical depth changes. The model represents the radiative and dynamical response of the climate system to volcanic eruptions and simulates a decrease of global and regional atmospheric surface temperature, regionally distinct changes in precipitation, a positive phase of the North Atlantic Oscillation, and a decrease in atmospheric CO2 after volcanic eruptions. The volcanic-induced cooling reduces overturning rates in tropical soils, which dominates over reduced litter input due to soil moisture decrease, resulting in higher land carbon inventories for several decades. The perturbation in the ocean carbon inventory changes sign from an initial weak carbon sink to a carbon source. Positive carbon and negative temperature anomalies in subsurface waters last up to several decades. The multi-decadal decrease in atmospheric CO2 yields a small additional radiative forcing that amplifies the cooling and perturbs the Earth System on longer time scales than the atmospheric residence time of volcanic aerosols. In addition, century-scale global warming simulations with and without volcanic eruptions over the historical period show that the ocean integrates volcanic radiative cooling and responds for different physical and biogeochemical parameters such as steric sea level or dissolved oxygen. Results from a suite of sensitivity simulations with different magnitudes of stratospheric aerosol optical depth changes and from global warming simulations show that the carbon cycle-climate sensitivity γ, expressed as change in atmospheric CO2 per unit change in global mean surface temperature, depends on the magnitude and temporal evolution of the perturbation, and time scale of interest. On decadal time scales, modeled γ is several times larger for a Pinatubo-like eruption than for the industrial period and for a high emission, 21st century scenario.