Understanding the main drivers of runoff components and contributions of precipitation and temperature have important implications for water-limited inland basins, where snow and glacier melt provide essential inputs to surface runoff. To quantify the impact of temperature and precipitation changes on river runoff in the Tarim River basin (TRB), the Hydrologiska Byrans Vattenbalansavdeling (HBV)-light model, which contains a glacier routine process, was applied to analyze the change in runoff composition. Runoff in the headstream parts of the TRB was more sensitive to temperature than to precipitation. In the TRB, overall, rainfall generated 41.22% of the total runoff, while snow and glacier meltwater generated 20.72% and 38.06%, respectively. These values indicate that temperature exerted more major effects on runoff than did precipitation. Runoff compositions were different in the various subbasins and may have been caused by different glacier coverages. The runoff volumes generated by rainfall, snowmelt, glacier melt was almost equal in the Aksu River subbasin. In the Yarkand and Hotan River subbasins, glacier meltwater was the main supplier of runoff, accounting for 46.72% and 58.73%, respectively. In the Kaidu-Kongque River subbasin, 80.86% was fed by rainfall and 19.14% was fed by snowmelt. In the TRB, runoff generated by rainfall was the dominant component in spring, autumn, winter, while glacier melt runoff was the dominant component in summer. Runoff in the TRB significantly increased during 1961–2016; additionally, 56.49% of the increase in runoff was contributed by temperature changes, and 43.51% was contributed by precipitation changes. In spring, the runoff increase in the TRB was mainly caused by the precipitation increase, opposite result in summer and autumn. Contribution of temperature was negative in winter. Our findings have important implications for water resource management in high mountainous regions and for similar river basins in which melting glaciers strongly impact the hydrological cycle.

The Large Field of View Airborne Infrared Scanner is a newly developed multi-spectral instrument that collects images from the near-infrared to long-wave infrared channels. Its data can be used for land surface temperature (LST) retrieval and environmental monitoring. Before data application, quality assessment is an essential procedure for a new instrument. In this paper, based on the data collected by the scanner near the Yellow River in Henan Province, the geometric and radiometric qualities of the images are first evaluated. The absolute geolocation accuracy of the ten bands of the scanner is approximately 5.1 m. The ground sampling distance is found to be varied with the whisk angles of the scanner and the spatial resolution of the images. The band-to-band registration accuracy between band one and the other nine bands is approximately 0.25 m. The length and angle deformations of the ten bands are approximately 0.67% and 0.3°, respectively. The signal-to-noise ratio (SNR) and relative radiometric calibration accuracy of bands 4, 9, and 10 are relatively better than those of the other bands. Secondly, the radiative transfer equation (RTE) method is used to retrieve the LST from the data of the scanner. Measurements of in situ samples are collected to evaluate the retrieved LST. Neglecting the samples with unreasonable retrieved LST, the bias and RMSE between in situ LST measured by CE312 radiometer and retrieved LST are −0.22 K and 0.94 K, and the bias and RMSE are 0.27 K and 1.59 K for the InfReC R500-D thermal imager, respectively. Overall, the images of the Large Field of View Airborne Infrared Scanner yield a relatively satisfactory accuracy for both LST retrieval and geometric and radiometric qualities.

Considering snowmelt in mountainous areas as the important source of streamflow, the snow accumulation/melting processes are vital for accurate simulation of the hydrological regimes. The lack of snow-related data and its uncertainties/conceptual ambiguity in snowpack modeling are the different challenges of developing hydro-climatological models. To tackle these challenges, Global Gridded Snow Products (GGSPs) are introduced, which effectively simplify the identification of the spatial characteristics of snow hydrological variables. This research aims to investigate the performance of multi-source GGSPs using multi-stage calibration strategies in hydrological modeling. The used GGSPs were Snow-Covered Area (SCA) and Snow Water Equivalent (SWE), implemented individually or jointly to calibrate an appropriate water balance model. The study area was a mountainous watershed located in Western Iran with a considerable contribution of snowmelt to the generated streamflow. The results showed that using GGSPs as complementary information in the calibration process, besides streamflow time series, could improve the modeling accuracy compared to the conventional calibration, which is only based on streamflow data. The SCA with NSE, KGE, and RMSE values varying within the ranges of 0.47–0.57, 0.54–0.65, and 4–6.88, respectively, outperformed the SWE with the corresponding metrics of 0.36–0.59, 0.47–0.60, and 5.22–7.46, respectively, in simulating the total streamflow of the watershed. In addition to the superiority of the SCA over SWE, the two-stage calibration strategy reduced the number of optimized parameters in each stage and the dependency of internal processes on the streamflow and improved the accuracy of the results compared with the conventional calibration strategy. On the other hand, the consistent contribution of snowmelt to the total generated streamflow (ranging from 0.9 to 1.47) and the ratio of snow melting to snowfall (ranging from 0.925 to 1.041) in different calibration strategies and models resulted in a reliable simulation of the model.

In this study, the movement of the maximum wind of Typhoon Rammasun (2014) was measured by the radial movement of the maximum symmetric rotational kinetic energy. The weather research and forecasting (WRF) model was used to simulate Typhoon Rammasun, and validated simulation data for the lower troposphere were analyzed to examine the physical processes responsible for the radial movement of the maximum wind. The radii, where maximum symmetric rotational kinetic energy and its maximum tendency were located, were compared to explain radial movement. The tendency in the lower troposphere is controlled by the flux convergence of symmetric rotational kinetic energy and the conversion from symmetric divergent kinetic energy to symmetric rotational kinetic energy, as well as frictional dissipation in the symmetric rotational kinetic energy budget. The inward movement before rapid intensification (RI) resulted from radial flux convergence; cyclonic circulation develops while moving inward. Stationary maximum symmetric rotational kinetic energy and RI were caused by the conversion, which was observed to be proportional to the symmetric rotational kinetic energy. Landfall increased terrain-induced friction dissipation, which led to outward movement and ended the RI.

Spatial modeling of ore grades is frequently impacted by the local variation in geological domains such as lithological characteristics, rock types, and geological formations. Disregarding this information may lead to biased results in the final ore grade block model, subsequently impacting the downstream processes in a mining chain project. In the current practice of ore body evaluation, which is known as stochastic cascade/hierarchical geostatistical modeling, the geological domain is first characterized, and then, within the geological model, the ore grades of interest are evaluated. This practice may be unrealistic in the case when the variability in ore grade across the boundary is gradual, following a smooth transition. To reproduce such characteristics, the cross dependence that exists between the ore grade and geological formations is considered in the conventional joint simulation between continuous and categorical variables. However, when using this approach, only one ore variable is considered, and its relationship with other ore grades that may be available at the sample location is ignored. In this study, an alternative approach to jointly model two cross-correlated ore grades and one categorical variable (i.e., geological domains) with soft contact relationships that exist among the geological domains is proposed. The statistical and geostatistical tools are provided for variogram inference, Gibbs sampling, and conditional cosimulation. The algorithm is also tested by applying it to a Cu deposit, where the geological formations are managed by the local and spatial distribution of two cross-correlated ore grades, Cu and Au, throughout the deposit. The results show that the proposed algorithm outperforms other geostatistical techniques in terms of global and local reproduction of statistical parameters.

Trace elements and rare earth elements (REEs) of two kinds of organic facies samples representing marginal and more basin-center deposits from Pleistocene lacustrine mudstones in the central Qaidam Basin were studied to understand the provenance, palaeotectonic setting, hydrothermal activity, palaeoredox conditions and sedimentary rate. The results show that the lacustrine mudstones were mainly derived from felsic sources with little contribution from ancient crustal sediments and no ultramafic (ophiolitic) source. The mudstones were deposited in a continental island arc tectonic setting, which is consistent with the tectonic evolution of the Cenozoic basin. Both two organic facies samples were hydrothermal in origin based on the ternary diagram of Ni–Zn–Co and normalized REE patterns. However, this does not mean that the water column in paleolake was affected by hydrothermal fluids in situ. This signal might indicate hydrothermal origins from hot springs related to active faults around the basin rather than the deep hydrothermal fluids entering the sediments via deep faculties based on the comprehensive analyses of normalized REE patterns, negative Eu_anom (Eu anomaly), Y/Ho, Sm/Yb, and Eu/Sm. Redox proxies including U/Th, Ni/Co, and Mn_anom values, are more sensitive for the studied samples indicating that most of the organic facies A samples were deposited under an oxygen-depleted condition, while the organic facies B samples were deposited under oxygen-rich conditions. Redox proxies of Ce_anom values are unavailable for the organic facies B samples due to hypersaline environments, and V/Cr and V/(V + Ni) are invalid for the organic facies A samples, possibly because of their organism composition. The low La_n/Yb_n values indicate high sedimentation rates, which is consistent with the average sedimentation rates of approximately 0.43 to 1.1 km/Ma. However, the La_n/Yb_n is more likely affected by the provenance of the studied samples, so it should be used with caution.

Quartz is an important mineral component in the Late Ordovician – Early Silurian Wufeng-Longmaxi Formation with various forms and sources and has a significant impact on the properties of shale gas reservoirs. In this study, geochemical analysis, scanning electron microscopy (SEM) observation, and rock mechanics testing were performed on shale samples from the Wufeng-Longmaxi Formation in north-western Hunan, South China. Quartz is classified into four types based on morphological features and cathodoluminescence (CL) images under SEM – terrigenous detrital quartz, quartz overgrowths, biogenic skeletal quartz and microquartz. The quartz in Upper Longmaxi Formation is predominantly of terrigenous origin and contains a small amount of quartz formed by clay transformation. The quartz in the Wufeng-Lower Longmaxi Formation is predominantly biogenic. The biogenic quartz has a direct effect on organic matter (OM) abundance, pore structure and brittleness. It is indicated by the positive correlation with TOC content and biogenic Ba content that biogenic quartz-rich strata have high paleoproductivity. The rigid frameworks formed by biogenic quartz during the early diagenesis stage facilitated the preservation of the primary pores. The interparticle pores of biogenic quartz are the space for OM preservation and migration, creating conditions for the development of OM pores. Additionally, the calculated brittleness index (BI) shows a positive correlation with biogenic quartz content, indicating that layers rich in biogenic quartz are more conducive to fracture. Therefore, the Wufeng-Lower Longmaxi Formation has higher OM content, porosity and represents a more favorable exploration and development target.

The eastern Tarim Basin (Tadong Area) has gained wide attentions on large-scale marine carbonate reservoirs in Cambrian-Ordovician due to significant hydrocarbon discoveries. A systematic analysis combining thin sections, cores, wireline logs, and seismic data is conducted on Cambrian-Ordovician carbonate platform in the whole eastern Tarim Basin, including Gucheng area, Majiaer area, and western Luobopo rise (Luoxi area). The results show that 8 sub-facies and more than 10 microfacies are developed including open platform, restricted/semi-restricted platform, reef-shoal around platform margin, drowned platform, foreslope, neritic platform, and deep-water basin. As both key areas for hosting petroleum reserves during the Cambrian and Ordovician, the Luoxi area is dominated by deep-water basin facies, while the Gucheng area is dominated by neritic platform facies and deep-water basin facies during the Lower Cambrian. The deposition evolution during the whole Cambrian is dominated by slope facies and deep-water facies, platform margin facies, and platform facies. In contrast, it is dominated by open platform facies during the whole Ordovician. The depositional evolution of carbonate platform is mainly controlled by paleo-geomorphology and sea-level changes. The distribution of paleo-geomorphologic units plays an important role in controlling types and distributions of carbonate platform facies. The transgression assists in growth of reef-shoal complex and lime mud mound in the Early Ordovician. However, with neritic platform and slope being to disappeared, in the Middle Ordovician, platform margin facies are well developed in Gucheng Area. Platform facies and deep-water basin facies are widely distributed. Finally, carbonate platform is drowned due to sea level rising in the Late Ordovician. The depositional evolution of carbonate platform coinciding falling and rising of sea-level changes can be beneficial for appropriate carbonate reservoirs identification and petroleum exploration.

Many types of sedimentary systems occur in the middle of the third member of the Shahejie Formation (E₂S₃²) of the Paleogene in the Dongying Sag east of the Bohai Bay Basin. Due to the topography and material supply, traction and gravity flow depositions are intertwined in this area, and the sand body types are complex and diverse, making it challenging to improve the accuracy of their description and prediction and restricting oil reservoir exploration and development. Therefore, this paper documents our systematic study of the sedimentary characteristics of the southern slope of Dongying Depression, the formation mechanism of different sand body types, and the prediction of sand body distribution. First, according to the coring well’s single-well facies and vertical rock sequence, nine single lithofacies types and five lithofacies association types were identified. Combined with the well logging facies marks of all wells, the depositional models of delta and gravity flow depositional systems were established in the study area. Then, the gravity flow was divided into slip, collapse, debris flow, and turbidity flow according to its development mechanism. Finally, the distribution law of the gravity flow sedimentary facies type was predicted. Gravity flow sliding deposits are primarily distributed near the delta front, slump and clastic flow deposits are distributed near the far slope, and turbidity current deposits are distributed at the far slope. With the gradual shrinkage of the water body in the north-west direction and the continuous advancement of the river delta, the gravity flow sand body gradually disappears in the late E₂S₃² and transits to delta plain deposition.

Amplitude variation with offset and azimuth (AVOA) inversion is a mainstream method for predicting and evaluating fracture parameters of conventional oil and gas reservoirs. However, its application to coal seams is limited because of the specificity of the equivalent media model for coal—also, the traditional seismic acquisition system employed in coal fields falls within a narrow azimuth. In this study, we initially derived a P‒P wave reflection coefficient approximation formula for coal seams, which is directly expressed in terms of fracture parameters using the Schoenberg linear-slide model and Hudson model. We analyzed the P‒P wave reflection coefficient’s response to the fracture parameters using a two-layer forward model. Accordingly, we designed a two-step inversion workflow for AVOA inversion of the fracture parameters. Thereafter, high-density wide-azimuth pre-stack 3D seismic data were utilized for inverting the fracture density and strike of the target coal seam. The inversion accuracy was constrained by Student’s t-distribution testing. The analysis and validation of the inversion results revealed that the relative fracture density corresponds to fault locations, with the strike of the fractures and faults mainly at 0°. Therefore, the AVOA inversion method and technical workflow proposed here can be used to efficiently predict and evaluate fracture parameters of coal seams.

Pores and fractures are important components of flow channels in coal-measure gas reservoirs. While considerable studies have been conducted on pore structure evolution, very few studies have investigated the fracture distribution and self-similarity characteristics. To reveal the characteristics of fracture distribution in coal and shale reservoirs, computed tomography studies were performed on 15 coal and shale samples from the Shanxi and Taiyuan formations. The results show that the fracture distribution of samples of the same lithology differs significantly, and the fracture distribution heterogeneity of shale samples is much higher than that of coal samples. In shale, the heterogeneity of fracture distribution is mainly caused by pores and fractures smaller than 2 μm in the z-direction, with relatively little contributions from pores and fractures in the x and y directions. However, the heterogeneity of fracture distribution in coal is mainly controlled by pores and fractures larger than 2 μm in all directions, and the difference between the three directions is minor. It was shown that a great number of microscopic pores and fractures contribute to the highest fractions of porosity in different lithological samples. This method is useful for determining the fracture distribution characteristics in shale and coal-measure gas reservoir.

Fog may continue to inhibit industry in the future. Here, we focused on a specific advection fog event in Shanghai, China, and applied a pseudo global warming method to examine advection fog under the RCP8.5 high-emission scenario. The method involved downscaling the future atmospheric conditions over the ensemble average of 19 global climate models from the fifth phase of the Coupled Model Intercomparison Project (CMIP5). We used the Weather Research and Forecasting Model coupled with a single-layer urban canopy model (WRF‒UCM) to run four sensitivity experiments and examined the advection fog and its relationship to changes in meteorological conditions. The results showed that: 1) The advection fog event tended to remain in Shanghai despite global warming; 2) advection fog will not change greatly in the future; however, the onset and dissipation times will change slightly; 3) relative humidity (RH) locally increases prior to the onset of the advection fog, and decreases at the dissipating stage, despite the current and future experiments having the same RH initial and boundary conditions; 4) a small increase in surface air temperature and an increase in RH contribute to the early advection fog onset, and vice versa. Windspeed facilitates the early onset and dissipation of advection fog.

Monthly precipitation over north China in August (NCAP) is the second highest in the year, and it is important to understand its driving mechanisms to facilitate reliable forecasting. The NCAP displays a significant decadal variability of a cycle about 10-year and negatively correlates with the July north-east North Atlantic Tripole (NAT) over the decadal timescales. This study shows that the Eurasian decadal teleconnection (EAT) acts as a bridge that links the July NAT with NCAP decadal variability. This coupled ocean–atmosphere bridge (COAB) mechanism, through which the July NAT influences the decadal variability of NCAP, can be summarized as follows. The cumulative effect of the NAT drives the EAT to adjust atmospheric circulation over north China and the surrounding regions, and so regulates precipitation in north China by influencing local water vapor transport. When the July NAT is in a negative (positive) phase, the EAT pattern has a positive (negative) pattern, which promotes (weakens) the transmission of water vapor from the sea in the south-east to north China, thus increasing (decreasing) NCAP over decadal timescales. The decadal NCAP model established based on the July NAT can effectively predict the NCAP decadal variability, illustrating that the July NAT can be implicated as a predictor of the NCAP decadal variability.

Land use planning is one of the basic principles of sustainable development in a region and in a country. The main objective of this paper is to test a new model of land use planning in order to evaluate ecological suitability and prioritize different land uses in Jahrom County placed in Fars Province, Iran. Hence two main steps were prepared for the new model of Eco-Socio-economic Model of Land Use Planning (EMOLUP). Step 1 includes ecological capability evaluation of different land uses including forest, rangeland, agriculture, conservation, and development. This step is composed of the geometric mean method instead of the Boolean method; and step 2 includes land use planning and prioritizing for the various uses mentioned above. This step is composed of intersecting ecological capability maps and land use planning, based on two scenarios (economic and social). It was compared with qualitative and current quantitative methods. Also, current land use is employed for calibrating and modifying the models. The results of ecological suitability evaluation showed that the EMOLUP model has more accuracy in the process of comparison than other current methods. Accordingly, revised method using the geometric mean (with overall accuracy > 72 and kappa index > 0.55 for all land uses and rangeland with overall accuracy = 32 and kappa index = 0.02) is better than Boolean models, and the method of the calibrated geometric mean (with overall accuracy > 87 and kappa index > 0.73 for all land uses) is the best among different used models. It should be noted that the arithmetic mean has the lowest accuracy (with overall accuracy < 45 and kappa index < 0.24 for all land uses). Also, the results of prioritizing and land use planning showed that the quantitative method with two socio-economic scenarios (result based on average of EPM erosion model = 0.3 that means 30% of modification in whole study area land uses) is the best method for land use planning in the study area.

Based on the latest China-Russia input-output data sets over the period from 2007 to 2015, this study quantified the flow of embodied carbon emissions in China-Russia trade using the emission embodied in bilateral trade (EEBT) approach. In addition, the structural decomposition analysis (SDA) was employed to identify the potential driving factors that affect embodied carbon in imports and exports. The results showed as follow. 1) China was a net exporter of carbon emissions in bilateral trade between China and Russia during 2007–2015. Despite that the bilateral trade scale had expanded considerably, the net export volume of CO₂ from China to Russia decreased from 13.21 Mt in 2007 to 4.45 Mt in 2015. 2) From the perspective of different sectors, the metal manufacturing and the chemical sectors of China and Russia were the main sources of CO₂ emissions. 3) In terms of driving factors, it was found that the carbon emission coefficient was the main reason for contributing to embodied emission reduction. Moreover, the contribution rate of carbon emission coefficient to reduce the carbon emissions in imports reached to 95.26%, as well as 108.22% in exports. The bilateral trade scale was the main driver for the increase in embodied carbon emissions, and the contribution rate to embodied carbon emissions in imports and exports were 14.80% and 65.17%, respectively. 4) This study argued that China and Russia should further optimize the energy structure and improve the energy efficiency and intermediate technology in the future.

We present a study on validation of the National Institute for Environmental Studies Transport Model (NIES TM) by comparing to observed vertical profiles of atmospheric CO₂. The model uses a hybrid sigma-isentropic (σ–θ) vertical coordinate that employs both terrain-following and isentropic parts switched smoothly in the stratosphere. The model transport is driven by reanalyzed meteorological fields and designed to simulate seasonal and diurnal cycles, synoptic variations, and spatial distributions of atmospheric chemical constituents in the troposphere. The model simulations were run for combination of biosphere, fossil fuel, air-ocean exchange, biomass burning and inverse correction fluxes of carbon dioxide (CO₂) by GOSAT Level 4 product. We compared the NIES TM simulated fluxes with data from the HIAPER Pole-to-Pole Observations (HIPPO) Merged 10-s Meteorology, Atmospheric Chemistry, and Aerosol Data, including HIPPO-1, HIPPO-2 and HIPPO-3 from 128.0°E to 84.0°W, and 87.0°N to 67.2°S. The simulation results were compared with CO₂ observations made in January and November, 2009, and March and April, 2010. The analysis attests that the model is sufficient to simulate vertical profiles with errors within 1–2 ppmv, except for the lower stratosphere in the Northern hemisphere high latitudes.

The characteristics of the mesoscale gravity waves during a snowfall event on November 30, 2018 over the Ili Valley and the northern slope of the Tianshan Mountains are analyzed based on the Weather Research and Forecasting model simulation. The vertical distribution of Ro is similar to that of the residual of the nonlinear balance equation (\mathrm{\Delta }NBE), with their high-value areas located over the leeward slope and the fluctuations extending upwardly with time, indicating the characteristics of strong ageostrophy and non-equilibrium of atmospheric motions. In addition, the Ro and \mathrm{\Delta }NBE are first developed in the lower layers over the leeward slope, revealing that the generation of the gravity waves is closely related to the topography. Thus, the topographic uplifting greatly affects this snowfall, and the ageostrophic motion in the whole troposphere and the lower stratosphere, as well as the unbalanced motions between convergence and divergence over the peak and the leeward slope are conductive to the development of the inertia-gravity waves. In terms of the horizontal scale of the gravity waves, the Barnes’ band-pass filter is applied to separate the mesoscale waves and the synoptic-scale basic flow. The vertical distributions of the vorticity and divergence perturbations have a phase difference of π/2, indicating the polarization state of gravity waves. The analyses on the sources and sinks of gravity waves by the non-hydrostatic wave equation show that the main forcing term for orographic gravity waves is the second-order nonlinear term, whose magnitude mainly depends on the nonlinear thermal forcing. This term is mainly related to the vertical transport of potential temperature perturbations. During the snowfall, the potential temperature perturbations are mainly caused by the topographic relief and the release of condensation latent heat. Therefore, the gravity waves in this snowfall are caused by the topographic forcing and condensation latent heating.

The magnitude and distribution of observation innovations, which have an important impact on the analyzed accuracy, are critical variables in data assimilation. Variational quality control (VarQC) based on the contaminated Gaussian distribution (CGD) of observation innovations is now widely used in data assimilation, owing to the more reasonable representation of the probability density function of innovations that can sufficiently absorb observations by assigning different weights iteratively. However, the inaccurate parameters prevent VarQC from showing the advantages it should have in the GRAPES (Global/Regional Assimilation and PrEdiction System) m3DVAR system. Consequently, the parameter optimization methods are considerable critical studies to improve VarQC. In this paper, we describe two probable CGDs to include the non-Gaussian distribution of actual observation errors, Gaussian plus flat distribution and Huber norm distribution. The potential optimization methods of the parameters are introduced in detail for different VarQCs. With different parameter configurations, the optimization analysis shows that the Gaussian plus flat distribution and the Huber norm distribution are more consistent with the long-tail distribution of actual innovations compared to the Gaussian distribution. The VarQC’s cost and gradient functions with Huber norm distribution are more reasonable, while the VarQC’s cost function with Gaussian plus flat distribution may converge on different minimums due to its non-concave properties. The weight functions of two VarQCs gradually decrease with the increase of innovation but show different shapes, and the VarQC with Huber norm distribution shows more elasticity to assimilate the observations with a high contamination rate. Moreover, we reveal a general derivation relationship between the CGDs and VarQCs. A novel schematic interpretation that classifies the assimilated data into three categories in VarQC is presented. They are conducive to the development of a new VarQC method in the future.

Quantitative assessment of natural internal variability and externally forced responses of Northern Hemisphere (NH) temperatures is necessary for understanding and attributing climate change signals during past warm and cold periods. However, it remains a challenge to distinguish the robust internally generated variability from the observed variability. Here, large-ensemble (70 member) simulations, Energy Balance Model simulation, temperature ensemble reconstruction, and three dominant external forcings (volcanic, solar, and greenhouse gas) were combined to estimate the internal variability of NH summer (June–August) temperatures over the past 2000 years (1–2000 CE). Results indicate that the Medieval Climate Anomaly was predominantly attributed to centennial-scale internal oscillation, accounting for an estimated 104% of the warming anomaly. In contrast, the Current Warm Period is influenced mainly by external forcing, contributing up to 90% of the warming anomaly. Internal temperature variability offsets cooling by volcanic eruptions during the Late Antique Little Ice Age. These findings have important implications for the attribution of past climate variability and improvement of future climate projections.