Hemisphere Temperature Research Articles

CMIP6 Models Underestimate Arctic Sea Ice Loss during the Early Twentieth-Century Warming, despite Simulating Large Low-Frequency Sea Ice Variability

Abstract The variability of Arctic sea ice extent (SIE) on interannual and multidecadal time scales is examined in 29 models with historical forcing participating in phase 6 of the Coupled Model Intercomparison Project (CMIP6) and in twentieth-century sea ice reconstructions. Results show that during the historical period with low external forcing (1850–1919), CMIP6 models display relatively good agreement in their representation of interannual sea ice variability (IVSIE) but exhibit pronounced intermodel spread in multidecadal sea ice variability (MVSIE), which is overestimated with respect to sea ice reconstructions and is dominated by model uncertainty in sea ice simulation in the subpolar North Atlantic. We find that this is associated with differences in models’ sensitivity to Northern Hemispheric sea surface temperatures (SSTs). Additionally, we show that while CMIP6 models are generally capable of simulating multidecadal changes in Arctic sea ice from the mid-twentieth century to present day, they tend to underestimate the observed sea ice decline during the early twentieth-century warming (ETCW; 1915–45). These results suggest the need for an improved characterization of the sea ice response to multidecadal climate variability in order to address the sources of model bias and reduce the uncertainty in future projections arising from intermodel spread. Significance Statement The credibility of Arctic sea ice predictions depends on whether climate models are capable of reproducing changes in the past climate, including patterns of sea ice variability which can mask or amplify the response to global warming. This study aims to better understand how latest-generation global climate models simulate interannual and multidecadal variability of Arctic sea ice relative to available observations. We find that models differ in their representation of multidecadal sea ice variability, which is overall larger than in observations. Additionally, models underestimate the sea ice decline during the period of observed warming between 1915 and 1945. Our results suggest that, to achieve better predictions of Arctic sea ice, the realism of low-frequency sea ice variability in models should be improved.

Effect of P2O5 on the viscous flow and crystallisation behaviour of slag in the double slag converter steelmaking process

In the current study, the effect of P2O5 on the viscous flow and crystallisation behaviour of slag in the double slag converter steelmaking process was investigated in laboratory. The results indicated that with the increase of P2O5 content, the softening temperature, hemispherical temperature and flowing temperature of steelmaking slag showed a decreasing trend, however, the viscosity increased. The FactSage thermodynamic software was used to predict the types and contents of crystallisation phases in the crystallisation process of steelmaking slag. It showed that with the increase of P2O5 content, the precipitation content of Ca5P2SiO12 increased, while the precipitation content of melilite decreased. The composition and microstructure of crystallisation phases were analysed using X-ray diffraction and scanning electron microscopy. The phase composition did not change with the increase of P2O5 content, but the diffraction peak intensity of each crystallisation phase was different. Besides, the precipitation of phosphorus-enriched phase was enhanced with the increase of P2O5 content.

A 561-yr (1461-2022 CE) summer temperature reconstruction for Mid-Atlantic-Northeast USA shows connections to volcanic forcing and atmospheric circulation

Contextualizing current increases in Northern Hemisphere temperatures is precluded by the short instrumental record of the past ca. 120 years and the dearth of temperature-sensitive proxy records, particularly at lower latitudes south of <50 °N. We develop a network of 29 blue intensity chronologies derived from tree rings of Tsuga canadensis (L.) Carrière and Picea rubens Sarg. trees distributed across the Mid-Atlantic and Northeast USA (MANE)—a region underrepresented by multi-centennial temperature records. We use this network to reconstruct mean March-September air temperatures back to 1461 CE based on a model that explains 62% of the instrumental temperature variance from 1901−1976 CE. Since 1998 CE, MANE summer temperatures are consistently the warmest within the context of the past 561 years exceeding the 1951−1980 mean of +1.3 °C. Cool summers across MANE were frequently volcanically forced, with significant (p<0.05) temperature departures associated with 80% of the largest tropical (n=13) and extratropical (n=15) eruptions since 1461 CE. Yet, we find that more of the identified cool events in the record were likely unforced by volcanism and either related to stochastic variability or atmospheric circulation via significant associations (p<0.05) to regional, coastal sea-surface temperatures, 500-hpa geopotential height, and 300-hpa meridional and zonal wind vectors. Expanding the MANE network to the west and south and combining it with existing temperature-sensitive proxies across North America is an important next step toward producing a gridded temperature reconstruction field for North America.

The Relative Importance of Antarctic Sea Ice Loss within the Response to Greenhouse Warming

Abstract The response to Antarctic sea ice loss within a coupled modeling framework is examined in comparison to the response to Arctic sea ice loss and within the context of general greenhouse warming. Sea ice loss responses are found to be linear (particularly in response to Antarctic or global sea ice loss) with respect to the degree of imposed perturbation and additive when perturbations are applied in hemispheres separately and concurrently. Globally, and in the tropical Pacific in particular, Antarctic sea ice loss plays a relatively larger role than Arctic sea ice loss in both the atmosphere and the ocean, within the parameters of our experiments. The pattern of response to Antarctic sea ice loss is also found to more closely resemble that of greenhouse warming, again particularly in the tropics. An extension to multiparameter pattern scaling is developed to include a scaling factor for Antarctic change in addition to those for tropical warming and Arctic sea ice loss. The decomposition is applied to the modeled response to Antarctic sea ice loss to break it down into component partial responses that scale with Antarctic, tropical, and Arctic changes. This reveals the aspects of the response that are directly related to Antarctic change, such as an equatorward intensification of tropical precipitation in the Northern Hemisphere, and those that are modified via the induced changes in the tropics and Arctic, such as Northern Hemisphere temperature change. With this, we hope to gain a deeper understanding of the role of each of these changes for the development of physical mechanisms of the response.

Linearity of the Climate Response to Increasingly Strong Tropical Volcanic Eruptions in a Large Ensemble Framework

Abstract Large explosive volcanic eruptions cause short-term climatic impacts on both regional and global scales. Their impact on tropical climate variability, in particular El Niño–Southern Oscillation (ENSO), is still uncertain, as is their combined and separate effect on tropical and global precipitation. Here, we investigate the relationship between large-scale temperature and precipitation and tropical volcanic eruption strength, using 100-member MPI-ESM ensembles for idealized equatorial symmetric Northern Hemisphere summer eruptions of different sulfur emission strengths. Our results show that for idealized tropical eruptions, global and hemispheric mean near-surface temperature and precipitation anomalies are negative and linearly scalable for sulfur emissions between 10 and 40 Tg S. We identify 20 Tg S emission as a threshold where the global ensemble-mean near-surface temperature and precipitation signals exceed the range of internal variability, even though some ensemble members emerge from variability for lower eruption strengths. Seasonal and ensemble mean patterns of near-surface temperature and precipitation anomalies are highly correlated across eruption strengths, in particular for larger emission strengths in the tropics, and strongly modulated by ENSO. There is a tendency to shift toward a warm ENSO phase for the first postvolcanic year as the emission strength increases. Volcanic cooling emerges on a hemisphere-wide scale, while the precipitation response is more localized, and emergence is mainly confined to the tropics and subtropics. Significance Statement The purpose of this study is to investigate at which strength the climate responses of volcanic forcing can be distinguished from the internal climate variability and whether the responses will linearly increase as the emission strengths become stronger. We ran 100-member MPI-ESM ensembles of idealized equatorial volcanic eruptions of different sulfur emission strengths and find that seasonal and ensemble mean patterns of near-surface temperature and precipitation anomalies are distinguishable and linearly scalable for sulfur emissions from 10 to 40 Tg S if their forcing patterns are similar. The identification of volcanic fingerprints is important for seasonal to decadal forecasts in the case of potential future eruptions and could help to prepare society for the regional climatic consequences of such an event.

Design of a hemispherical shell shaped natural ventilation temperature observation instrument.

Atmospheric temperature is fundamental information for various industries, such as production, life, and scientific research. The temperature error induced by the solar rays can reach 1 °C or even higher. A hemispherical shell-shaped atmospheric temperature measuring instrument that can reduce heat pollution and increase air velocity was designed. First, the instrument was optimized using computational fluid dynamics (CFD) software packages. Then, the CFD software packages were employed to quantify the temperature errors of the instrument with varying situations. A neural network model was employed to develop a temperature error correction model that can be targeted for multi-variable changes. This model provides accurate correction data when the influencing factors change continuously. Finally, field experiments were performed. The experimental data analysis indicates that the mean temperature error and the maximum error of the instrument before correction are 0.08 and 0.25 °C, respectively. The root mean square error, the mean absolute error, and the correlation coefficient between measured temperature errors from experiments and corrected temperature errors from the correction model are 0.099, 0.016, and 0.952 °C, respectively. By utilizing a temperature error correction model, the measuring error of the instrument can be minimized to a range between -0.05 and 0.04 °C. Consequently, the instrument is anticipated to enhance temperature measurement accuracy to ∼0.1 °C.

878 Selective Brain Cooling is Possible via CSF Exchange With Double Lumen EVD- Proof of Concept in Porcine Model

INTRODUCTION: Hypothermia is seen as neuroprotective after brain insult (BI). In acute phase after BI it affects brain metabolism by decreasing oxygen and glucose consumption. Hypothermia affects apoptosis and inflammatory mediators. In the later stage of BI, enzyme activation stimulates protein and lipid breakdown, which can be slowed and decreased with hypothermia. In the latest stage of BI hypothermia has shown positive affect in angiogenesis, neurogenesis, synaptogenesis. Hypothermia also reduces vasogenic oedema and blood brain barrier dysfunction. Despite hypothermia´s neuroprotective effect randomized control trials have demonstrated its benefits only limited scenarios - mainly in global ischemia (post-cardiac infarction and ischemia of new-born). Majority of complications related to hypothermia has been due to systemic hypothermia and selective brain cooling has never been demonstrated in large mammals without changes in core temperature of subject. METHODS: We inserted double lumen external ventricular drainage (EVD) into the lateral ventricle of porcine. We added spinal drainage to accelerate CSF exchange to cooled NaCl solution. Brain parenchymal temperature was measured from the contralateral brain hemisphere and the ipsilateral brain hemisphere. RESULTS: Contralateral brain hemisphere temperature dropped by 3.1C from baseline while core temperature changed only by 0.5C. Ipsilateral temperature cooled by 7.5C from baseline to 30.8C, while core temperature was 37.7C. Total time needed to achieve selective cooling was 1.5h. Porcine started to have arrhythmias when brain temperature approached 30.8C. CONCLUSIONS: We are first to describe that selective brain cooling is possible via CSF exchange with double lumen EVD to achieve significant temperature difference between body core and brain. The timing and rate of selective cooling needs to be established as cause of arrhythmias before starting human trials.

Into the Holocene, anatomy of the Younger Dryas cold reversal and preboreal oscillation

During the most recent deglaciation, the upwards trend of warmer Northern Hemisphere (NH) temperatures was punctuated by a rapid and intense return to glacial conditions: the Younger Dryas (YD). The end of this event marks the beginning of the Holocene. Using the University of Toronto version of CCSM4, a model of the climate prior to the YD was created with correct boundary conditions. Various amounts of freshwater forcing were then applied to the Beaufort Gyre for forcing intervals ranging from 1 to 125 years. In several cases, this was sufficient to collapse the Atlantic Meridional Overturning Circulation (AMOC) and cause significant cooling over the NH. Crucially, after the forcing was ceased, the AMOC stayed in an off state for approximately a millennium before mounting a rapid recover to pre-YD levels. This recovery, which permanently reduced the extent of NH sea ice, occurred through the mechanism of a Polynya opening in the Irminger Sea during winter and led to a pronounced “overshoot” of the AMOC, during which NH temperatures were higher than before the YD.

Fluctuations of Qiangyong glacier in southern Tibetan Plateau over the past 500 years recorded by proglacial lacustrine sediments

The glaciers of the Tibetan Plateau have undergone profound changes due to rapid global warming, but the nature of their response to climate change at various settings remains unclear. This study focuses on the analysis (grain sizes, magnetic susceptibility, and element ratios) of a sedimentary core from a proglacial lake (Qiangyong (QY) Co) at the southern Tibetan Plateau, based upon the 210Pb and 137Cs dating, aiming to unveil the fluctuations of the QY glacier over the recent 500 years and its response to global warming. Four pre-1900s distinct glacier advance/cold intervals (C1: 1560s, C2: 1660s, C3: 1760s and C4: 1860s), a minor advance in the 1950s and an extensive glacier retreat since the 2010s were discerned. There are five glacier fluctuation cycles, each spanning approximately 100 years, correlating generally well with the Northern Hemisphere temperature patterns on a century time scale. The glacier advances align with the cold periods, whereas the retreats correspond to the warm intervals. However, coarse grain sizes indicated a marked glacier shrinkage of the QY glacier since the 1920s owing to global warming, over-shading the inherent 100-years fluctuation cyclic variations intrinsic to glaciers. The reason is that after QY glacier has significantly shrunk to higher altitude, the response of the glacier to climate change is no longer as sensitive as at the lower altitude, even under post-industrial-revolution warming. The QY glacier and even the entire Himalayan region will face the threat of glacier melting during the 21st century, but dynamic patterns of glacier retreats in higher Himalayan regions may differ from that in the low-altitude.

A shift towards broader and less persistent Southern Hemisphere temperature anomalies

Temperature anomalies considerably influence the regional climate and weather of the extratropics. By the end of this century, climate models project an intensification of synoptic temperature variability in the Southern Hemisphere mid-latitudes. This intensification, however, comprises temperature anomalies with various length scales and periods, which might respond differently to anthropogenic emissions. Here, we find a shift, in coming decades, towards spatially larger and less persistent temperature anomalies in the Southern Hemisphere mid-latitudes. A shift towards larger length scales is also found during regional extreme heat events. The shift in length scale and duration is found to stem from changes in the meridional heat flux of atmospheric perturbations. Our results emphasize the importance of investigating the length scale and period-dependent changes in the mid-latitude climate, to prevent masking the different impacts of various length scales and periods, and thus provide more accurate climate projections for the mid-latitudes.

An extended exponential SEMIFAR model with application in R

The article at hand provides a detailed description of the esemifar R-package, which is an extension of the already published smoots R-package, enabling the data-driven local-polynomial smoothing of trend-stationary time series with long memory. In this regard, a simple data-driven algorithm is proposed based on the well-known iterative plug-in algorithm for SEMIFAR (semiparametric fractional autoregressive) models. Two new functions for data-driven estimation of the trend and its derivatives in the presence of long memory are introduced. esemifar is applied to various environmental and financial time series with long memory, for example, mean monthly Northern Hemisphere temperature changes, daily observations of the air quality index of London (Britain), quarterly G7-GDP and daily trading volume of the S & P500. It is worth mentioning that this package can be applied to any suitable time series.

Hydrothermal dewatering of low-grade coal: Product evaluation and primary component analysis of ash deposition

The hydrothermal dewatering (HTD) process was carried out using 16 coal samples obtained from several regions in Indonesia. This research aims to identify the dominant parameters that influence ash deposition during coal combustion in a boiler or gasifier due to the HTD process. This research was conducted due to the lack of clear and comprehensive information regarding this issue. Therefore, to understand the effect of HTD on ash deposition, an analysis of the chemical composition of ash and the ash melting temperature (AFT) was carried out. To verify the data obtained from the experimental analysis, statistical methods such as paired sample t-test and primary component analysis were applied to obtain the dominant parameters influencing ash deposition due to HTD. Eight parameters, namely SiO2, Fe2O3, slagging viscosity index (SR), Babcock index (Rs), initial deformation temperature, softening temperature, hemispherical temperature, and fluid temperature under oxidative conditions, have the greatest influence on ash deposition due to the HTD process. Based on the average values of SR and Rs, raw coal and processed coal samples have the same ash deposition trend. On the other hand, based on AFT under oxidation conditions, processed coal has a higher AFT, indicating that the tendency for ash deposition is lower than raw coal. Therefore, the HTD process can be used to improve the quality of low-grade coal. As an implication, low-grade coal, which has not been widely utilized in Indonesia, due to several constraints regarding its characteristics, through the HTD process can be optimized where coal utilization is a bridge towards the use of green energy which is being intensively pursued.

Prediction of ash fusion temperatures of municipal solid waste incinerator ash based on support vector regression

The ash fusion temperatures (AFTs) of the municipal solid waste incinerator (MSWI) ash and slags is the main indicator to judge its slagging characteristics. Support vector regression (SVR) algorithm is more appropriate for creating an AFT prediction model than the classic regression method because it can adjust to a wider range of ash sample types in a wider range of areas by avoiding underfitting and overfitting. In this paper, SVR prediction models for the deformation temperature (IDT), softening temperature (ST), hemisphere temperature (HT), and flow temperature (FT) of ash are constructed using the ash chemical composition and AFTs dataset of coal ash and biomass ash and other ash. The AFTs of fly ash, bottom slag, and other ash in the municipal solid waste incinerator are predicted. With average relative errors of 1.98 % and 3.56 % and maximum relative errors of 5.21 % and 5.2 %, respectively, the results demonstrate that ST and FT have greater prediction accuracy. IDT and HT both provide poor predictions, with maximum relative errors of 14.08 % and 9.36 %, respectively, and average relative errors of 10.06 % and 5.95 %, respectively. Additionally, the impact of removing various numbers of outlier samples from training data on prediction accuracy, and the impact of test sample measures, such as ash composition analysis and AFTs determination, on prediction accuracy are analyzed and examined.

Effects of Proximate Analysis on Coal Ash Fusion Temperatures: An Application of Artificial Neural Network.

The temperature at which coal ash melts has a significant impact on the operation of a coal-fired boiler. The coal ash fusion temperature (AFT) is determined by its chemical composition, although the relationship between the two varies. Therefore, it is important to have mathematical models that can reliably predict the coal AFTs when designing coal-based processes based on their coal ash chemistry and proximate analysis. A computational intelligence model based on the interrelationships between coal properties and AFTs was used to predict the AFTs of the coal investigated. A model that integrates the ash, volatile matter, fixed carbon contents, and ash chemistry as input and the AFT [softening temperature, deformation temperature, hemispherical temperature, and flow temperature] as an output provided the best indicators to predict AFTs. The findings from the models indicate (a) a method for determining the AFTs from the coal properties; (b) a reliable technique to calculate the AFTs by varying the proximate analysis; and (c) a better understanding of the impact, significance, and interactions of coal properties regarding the thermal properties of coal ash. This study creates a predictive model that is easy to use, computer-efficient, and highly accurate in predicting coal AFTs based on their ash chemistry and proximate analysis data.

Volcanic Imprints in Last-Millennium Land Summer Temperatures in the Circum–North Atlantic Area

Abstract Summer cooling is one of the most direct consequences of explosive volcanic eruptions that can affect ecosystems and human societies. Recent studies revealed a multiyear cooling impact on hemispheric and global summer temperatures after tropical eruptions, yet the volcanic responses appear to vary on regional scales. Here, we revisit volcano-induced summer cooling in eastern Canada and northern and central Europe by applying superposed epoch analysis on CMIP6-PMIP4 simulations and millennial temperature reconstructions based on tree-ring density. We then examine potential causes modulating region-specific volcanic impact. While confirming that, on average, tropical eruptions over the last millennium have induced a longer cooling (&gt;4 yr) than eruptions from extratropical Northern Hemisphere in all three North Atlantic regions, we show that the peak magnitude of cooling is stronger in eastern Canada. We also find that the detected volcanic temperature anomalies can be strongly affected by the selection and number of volcanic events and nonvolcanic signals embedded in the climate time series. This study highlights the risks of using highly noisy proxy records to investigate volcanic impacts, especially in regions with strong unforced climate variability. The CMIP6-PMIP4 simulations generally agree with the three reconstructions on the average response to tropical eruptions, but their performance is poorer regarding the production of significant cooling after extratropical eruptions. Our results further suggest that the particular sensitivity to tropical eruptions in eastern Canada is likely related to increased sea ice surrounding Quebec–Labrador associated with the positive Arctic Oscillation and North Atlantic Oscillation formed during the first posteruption winter.

On the statistical distribution of temperature and the classification of extreme events considering season and climate change—an application in Switzerland

With the increased occurrence of hot spells in recent years, there is growing interest in quantifying the recurrence of extreme temperature events. However, pronounced temperature anomalies occur all year round, and a reliable classification in terms of the time of occurrence in the year is needed. In this study, we present a novel approach to classifying daily air temperatures that take into account the seasonal cycle and climate change. We model the distribution of the daily Swiss temperatures using the skewed generalized error distribution with four time-varying parameters, thereby accounting for non-Gaussianity in daily air temperature, while the climatic trend is modeled linearly with smoothed northern hemisphere temperature as an explanatory variable. The daily observations are then transformed into a standard normal distribution. The resultant standardized temperature anomalies are comparable within a year and between years and are used for quantile-based empirical classification. The approach is suitable to classify historical and current extreme temperatures with respect to the temperature range expected at the time of the event. For example, a heat wave occurring at the end of June is classified as less likely to occur than a heat wave of similar intensity occurring in mid-July, as is shown for the two 7-day heat waves that struck Switzerland in the summer of 2019. Furthermore, climate change has increased the probability of hot events and decreased the probability of cold events in recent years. The presented approach thus allows a fair classification of extreme temperatures within a year and between years and offers new possibilities to analyze daily air temperature.

Optimizing the size distribution of zinc borosilicate glass powder by organic solvent and tetradecylphosphonic based wet milling

Zinc borosilicate glass are crucial adhesive medium in modern electronic industry. However, it is still hard to prepare the zinc borosilicate glass with uniform particle size distribution. Herein, narrow particle size distribution and reduced hemispherical point temperature of zinc borosilicate glass was obtained by choosing low polarity, viscosity and surface tension organic solvent as well as surface modifier in the wet ball milling method. It is found that xylene, ethanol and isopropyl alcohol are good liquid medium for wet ball milling. Moreover, tetradecylphosphonic acid (TDPA) as a surface modifier could effectively reduce the formation of surface hydroxyl group in glass powder by the nucleophilic substitution reaction of the phosphonic acid group, showing superb anti-aggregation properties. Therefore, this work provides a general method for controlling particle size distribution of glass powder.

Variations of heat availability in the Western Caucasus in the past 1500 years inferred from a high-resolution record of bromine in the sediment of Lake Karakel

The Caucasus region lacks climate-sensitive chronologies that are continuous, high-resolution and covering more than several centuries at the same time. This paper presents the first high-resolution curve reflecting the variations of heat availability in the Western Caucasus over the past 1500 years. The chronology of bottom sediment of Lake Karakel is based on the two precisely overlapped sediment cores, constrained by ten 14C dates with a temporal resolution of around 3 years. Bromine content in the sediment is interpreted as a proxy for variations of heat availability based on its coherence with the broadleaved tree pollen content in the same deposits. Lake Karakel Br curve showed distinct agreement with hemispheric and regional temperature reconstructions starting from 500 CE, as well as with the tree-ring temperature reconstructions available for the Caucasus. It allowed a constraint of the time frames for the main climatic events in the Western Caucasus during the past 1500 years: Medieval Climate Anomaly (ca. 960–1270 CE) and Little Ice Age with its three separate stages (LIA 1 ca. 1270–1310 and 1370–1410; LIA 2 ca. 1500–1630; LIA 3 ca. 1750–1840). Br-derived variations of heat availability are also supported by the recent cosmogenic glacier moraine dates in the Caucasus.

Temperature variability over Dokriani glacier region, Western Himalaya, India

Long-term climate records which help decipher past climate variability and its impact are scarce in the tough terrain of the Himalayan region. Therefore, in order to fill the climate data gap and understand the glacier climate linkage, we developed a 231 year long (1785–2015 CE) March–June temperature record using ring-width chronology of Himalayan fir (Abies pindrow (Royle ex D.Don) Royle) for the Din Gad valley, Dokriani glacier region, Uttarkashi, Uttarakhand, in the Western Himalaya. The Din Gad, originating from the Dokriani glacier, is a meltwater river contributing to Bhagirathi catchment in the headwaters of the socio-economically vital Ganga River. The 21-year running mean of the temperature record showed 1978–1998 CE as the coldest period followed by 1925–1945 CE, and 1890–1910 CE as the warmest period followed by 1946–1966 CE over the entire time series. The reconstruction matches well with tree-ring based temperature records available from the Garhwal Himalaya. It also shows similarity to tree-ring based temperature reconstructions from the Western Himalaya, Nepal, Tibetan Plateau and Bhutan, thus displaying a regional scale climate signal. The low frequency fluctuation patterns of the March–June temperature also matches with Asia and Northern hemisphere temperature records. Reconstructed March–June temperature record showed a statistically negligible warming temperature trend during 1901–1989 CE in the 20th century. It, however, captured a warming spike from 1990s CE which continues rising into the 21st century, which is also evident in the Northern hemisphere temperature record. Moreover, temperature rise is not anomalous in the past 231 years and well within range of the rest of the series. The present temperature record exclusively from the glacier region revealed a strong linkage with the benchmark Dokriani glacier's winter mass balance (November–April) revealing mass loss (gain) episodes occurred in warm (cool) phases. This first such record from the glacier valleys in Ganga headwaters would be of great value at providing insight into past climate variability and glacier behaviour with respect to climate change in long term perspective, and thus would provide valuable information for water resource management in light of climate change.

Unexpected cold season warming during the Little Ice Age on the northeastern Tibetan Plateau

There is a general agreement that Northern Hemisphere temperatures have cooled over the past two millennia, culminating in the Little Ice Age. However, this understanding partly relies on the compilation of existing proxy records, the majority of which carry a warm season bias such that there is an underrepresentation of cold-season temperatures. Here we report a unique cold-season temperature record based on the alkenone paleothermometer from the northeastern Tibetan Plateau that spans the last two millennia. In contrast to the regional- and hemisphere-scale summer cooling, our reconstruction shows a long-term warming through the Medieval Climate Anomaly into Little Ice Age. We attribute these opposing temperature trends to combined effects of seasonally divergent insolation and North Atlantic subpolar gyre circulation. Our study indicates that the cold season during the Little Ice Age was not the coldest period of the last two millennia at least on the northeastern Tibetan Plateau.