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Long-term, ground-based daily global solar radiation (DGSR) at Zhongshan Station in Antarctica can quantitatively reveal the basic characteristics of Earth's surface radiation balance and validate satellite data for the Antarctic region. The fixed station was established in 1989, and conventional radiation observations started much later in 2008. In this study, a random forest (RF) model for estimating DGSR is developed using ground meteorological observation data, and a high-precision, long-term DGSR dataset is constructed. Then, the trend of DGSR from 1990 to 2019 at Zhongshan Station, Antarctica is analyzed. The RF model, which performs better than other models, shows a desirable performance of DGSR hindcast estimation with an R2 of 0.984, root-mean-square error of 1.377 MJ m−2, and mean absolute error of 0.828 MJ m−2. The trend of DGSR annual anomalies increases during 1990–2004 and then begins to decrease after 2004. Note that the maximum value of annual anomalies occurs during approximately 2004/05 and is mainly related to the days with precipitation (especially those related to good weather during the polar day period) at this station. In addition to clouds and water vapor, bad weather conditions (such as snowfall, which can result in low visibility and then decreased sunshine duration and solar radiation) are the other major factors affecting solar radiation at this station. The high-precision, long-term estimated DGSR dataset enables further study and understanding of the role of Antarctica in global climate change and the interactions between snow, ice, and atmosphere. [ABSTRACT FROM AUTHOR]

The risk of water erosion in mainland China is intensifying due to climate change. A high-precision rainfall erosivity dataset is crucial for revealing the spatiotemporal patterns of rainfall erosivity and identifying key areas of water erosion. However, due to the insufficient spatiotemporal resolution of historical precipitation data, there are certain biases in the estimation of rainfall erosivity in China, especially in regions with complex terrain and climatic conditions. Over the past decade, the China Meteorological Administration has continuously improved its ground-based meteorological observation capabilities, forming a dense network of ground-based observation stations. These high-precision precipitation data provide a solid foundation for quantifying the patterns of rainfall erosivity in China. In this study, we first performed rigorous quality control on the 1-minute ground observation precipitation data from nearly 70,000 stations nationwide from 2014 to 2022, ultimately selecting 60,129 available stations. Using the precipitation data from these stations, we calculated event rainfall erosivity and generated a national mean annual rainfall erosivity dataset with a spatial resolution of 0.25°. This dataset shows that the mean annual rainfall erosivity in mainland China is approximately 1241 MJ·mm·ha−1·h−1·yr−1, with areas exceeding 4000 MJ·mm·ha−1·h−1·yr−1 mainly concentrated in the southern China and southern Tibetan Plateau. Compared to our study, previously released datasets overestimate China's mean annual rainfall erosivity by 31 %~65 %, and there are significant differences in performance across different river basins. In summary, the release of this dataset facilitates a more accurate assessment of the current water erosion intensity in China. The dataset is available from the National Tibetan Plateau/Third Pole Environment Data Center (https://doi.org/10.11888/Terre.tpdc.301206 ; Chen, 2024). [ABSTRACT FROM AUTHOR]

The occurrence of Supraglacial Lakes (SGLs) may influence the signals acquired with microwave radiometers, which may result in a degree of uncertainty when employing microwave radiometer data for the detection of surface melt. Accurate monitoring of surface melting requires a reasonable assessment of this uncertainty. However, there is a scarcity of research in this field. Therefore, in this study, we computed surface melt in the vicinity of Automatic Weather Stations (AWSs) by employing Defense Meteorological Satellite Program (DMSP) Ka-band data and Soil Moisture and Ocean Salinity (SMOS) satellite L-band data and extracted SGL pixels by utilizing Sentinel-2 data. A comparison between surface melt results derived from AWS air temperature estimates and those obtained with remote sensing inversion in the two different bands was conducted for sites below the mean snowline elevation during the summers of 2016 to 2020. Compared with sites with no SGLs, the commission error (CO) of DMSP morning and evening data at sites where these water bodies were present increased by 36% and 30%, respectively, and the number of days with CO increased by 12 and 3 days, respectively. The omission error (OM) of SMOS morning and evening data increased by 33% and 32%, respectively, and the number of days with OM increased by 17 and 21 days, respectively. Identifying the source of error is a prerequisite for the improvement of surface melt algorithms, for which this study provides a basis. [ABSTRACT FROM AUTHOR]

The strengths and weakness of the Twentieth-Century Reanalysis (20CR), the Pilot reanalysis of the twentieth-century (ERA-20C), a coupled twentieth-century climate reanalysis product (CERA-20C), and an ensemble of ten twentieth-century atmospheric model integrations (ERA-20CM), are examined for Antarctic snow accumulation based on 3265 Antarctic multi-year averaged surface mass balance observations and 79 ice core snow accumulation time series, which provides an independent estimate because they are not assimilated into the reanalyses and not used to force ERA-20CM. The ECMWF "Interim" reanalysis (ERA-Interim) and two regional climate models (RACMO2 and MAR) are also used as a complementary analysis. Despite the magnitude discrepancy between simulations and observations, large-scale spatial variability in multi-year averaged snow accumulation observations are reasonably well reproduced by all the twentieth century datasets. The four datasets capture a large fraction (> 40%) of the interannual variability in the ice core snow accumulation composite over the Antarctic Peninsula from 1901 to 2010. However, none of the twentieth century datasets alone is able to explain > 20% of variance in ice core records at the other Antarctic regions during the twentieth century. Even for the modern satellite era (from 1979 onwards), their performance for Antarctic snow accumulation is still poorer, relative to ERA-Interim, RACMO2 and MAR. Considerable inhomogeneities and spurious changes in atmospheric circulation are found in these datasets, and thus the precipitation minus evaporation/sublimation (P–E) changes and trends during the past 100 years are largely artificial over Antarctica. [ABSTRACT FROM AUTHOR]

As the Arctic continues to warm faster than the global average, the Greenland ice sheet faces a warmer future without restrictions on greenhouse gas emissions. In this study, 24 CMIP5 and 21 CMIP6 models were used to analyze projections of precipitation, 2 m or near-surface air temperature (T2m), and 500 hPa geopotential height (Z 500) over Greenland under medium and high emission scenarios. The multi-model ensemble means indicate that CMIP6 is a warmer output with more precipitation in Greenland under medium and high emission scenarios relative to CMIP5. At the end of the 21st century (2071–2100), annual integrated precipitation in Greenland under RCP8.5 (SSP58.5) is projected to increase by 277.9 (281.3) Gt relative to the 1986–2005 climatological mean, with a significant positive trend of 38.5 (42.9) Gt/dec (p < 0.05) post-2020, approximately twice that under RCP4.5 (SSP24.5). Under high emission scenarios, T2m will steadily increase by 5.2 (5.7) °C at the end of the 21st century and the northern amplifying effect of warming is more intense. In this context, northeast Greenland will increase the highest precipitation, with a trend of >30 mm/dec during 2020–2100. The Z 500 rises higher from southeast to northwest Greenland due to global warming under medium and high emission scenarios. Model and scenario uncertainties are major sources of uncertainty at the end of the 21st century. Compared to CMIP5, the model uncertainty of CMIP6 decreases more but remained higher at the end of this century. The projections of northern Greenland are more reliable than those of other regions, with a lower total fractional uncertainty and a greater signal-to-noise ratio. Furthermore, we did not find an additional T2m increase due to internal variability. Under medium and high emission scenarios, Greenland near surface air warming is major owed to global warming. Considering the importance of current circulation anomalies and after removing the artificial increase in Z 500 , the decrease in ΔZ 500 indicates that future warming has been underestimated under medium and high emission scenarios. • Under high emission scenarios, CMIP6 performs warmer and wetter relative to CMIP5. • The northern amplifying effect of warming is more significant under RCP8.5 (SSP58.5). • Compared to CMIP5, model uncertainty of CMIP6 decreases more but remained higher. • In CMIP5 and CMIP6, the Greenland warming is major due to global warming. [ABSTRACT FROM AUTHOR]

The quality-controlled monthly air temperature records from 32 manned stations and 10 automatic weather stations are used to assess the performance of Climate Forecast System Reanalysis (CFSR), the ECMWF "Interim" reanalysis (ERA-Interim), the Japan Meteorological Agency 55-year Reanalysis (JRA-55), the Modern-Era Retrospective Analysis for Research and Applications 2 (MERRA-2), and four twentieth century reanalysis data sets (20CR, ERA-20C, CERA-20C and ERA-20CM). The performance of the datasets for Antarctic air temperature differs on different time scales and with glaciological regime. In general, these datasets have higher mean absolute error (MAE) in the winter months and lower MAE in the summer months. Overall, MERRA-2 presents highest performance for monthly air temperature values, with MAE <2 °C at any month. ERA-Interim best represents the inter-annual variability in monthly air temperature for the 1979–2010 period. In the 20th century datasets, changes in temperature prior to 1979 are more uncertain than variability after 1979. Furthermore, substantial inhomogeneities occur in the 20th century datasets, and as a result, their temperature trends are found to be largely spurious. • Reanalysis's performance for Antarctic air temperature varies by location and time. • MERRA-2 performs best for the monthly air temperature observations. • Considerable inhomogeneities are found in the 20th century reanalysis datasets. [ABSTRACT FROM AUTHOR]

Arctic sea ice loss and the associated enhanced warming has been related to midlatitude weather and climate changes through modulate meridional temperature gradients linked to circulation. However, contrasting lines of evidence result in low confidence in the influence of Arctic warming on midlatitude climate. This study examines the additional perspectives that palaeoclimate evidence provides on the decadal relationship between autumn sea ice extent (SIE) in the Barents-Kara (B-K) Seas and extreme cold wave events (ECWEs) in southern China. Reconstruction of the winter Cold Index and SIE in the B-K Seas from 1289 to 2017 shows that a significant anti-phase relationship occurred during most periods of decreasing SIE, indicating that cold winters are more likely in low SIE years due to the "bridge" role of the North Atlantic Oscillation and Siberian High. It is confirmed that the recent increase in ECWEs in southern China is closely related to the sea ice decline in the B-K Seas. However, our results show that the linkage is unstable, especially in high SIE periods, and it is probably modulated by atmospheric internal variability. [ABSTRACT FROM AUTHOR]

During the recent four decades since 1980, a series of modern climate satellites were launched, allowing for the measurement and record-keeping of multiple climate parameters, especially over the polar regions where traditional observations are difficult to obtain. China has been actively engaging in polar expeditions. Many observations were conducted during this period, accompanied by improved Earth climate models, leading to a series of insightful understandings concerning Arctic and Antarctic climate changes. Here, we review the recent progress China has made concerning Arctic and Antarctic climate change research over the past decade. The Arctic temperature increase is much higher than the global-mean warming rate, associated with a rapid decline in sea ice, a phenomenon called the Arctic Amplification. The Antarctic climate changes showed a zonally asymmetric pattern over the past four decades, with most of the fastest changes occurring over West Antarctica and the Antarctic Peninsula. The Arctic and Antarctic climate changes were driven by anthropogenic greenhouse gas emissions and ozone loss, while tropical-polar teleconnections play important roles in driving the regional climate changes and extreme events over the polar regions. Polar climate changes may also feedback to the entire Earth climate system. The adjustment of the circulation in both the troposphere and the stratosphere contributed to the interactions between the polar climate changes and lower latitudes. Climate change has also driven rapid Arctic and Southern ocean acidification. Chinese researchers have made a series of advances in understanding these processes, as reviewed in this paper. [ABSTRACT FROM AUTHOR]

"Earth summit mission 2022" is one of the landmark scientific research activities of the Second Tibetan Plateau Scientific Expedition and Research (STEP). This scientific expedition firstly used advanced technology and methods to detect vertical meteorological elements and produce forecasts for mountain climbing. The "Earth summit mission 2022" Qomolangma scientific expedition exceeded an altitude of over 8000 meters for the first time and carried out a comprehensive scientific investigation mission on the summit of Mt. Qomolangma. Among the participants, the westerly-monsoon synergy and influence team stationed in the Mt. Qomolangma region had two tasks: 1) detecting the vertical structure of the atmosphere for parameters such as wind, temperature, humidity, and pressure with advanced instruments for high-altitude detection at the Mt. Qomolangma base camp; and 2) observing extreme weather processes to ensure that members of the mountaineering team could successfully reach the top. Through this scientific expedition, a better understanding of the vertical structure and weather characteristics of the complex area of Mt. Qomolangma is gained. [ABSTRACT FROM AUTHOR]

A new meteorological dataset derived from records of Antarctic automatic weather stations (here called the AntAWS dataset) at 3 h, daily and monthly resolutions including quality control information is presented here. This dataset integrates the measurements of air temperature, air pressure, relative humidity, and wind speed and direction from 267 Antarctic AWSs obtained from 1980 to 2021. The AWS spatial distribution remains heterogeneous, with the majority of instruments located in near-coastal areas and only a few inland on the East Antarctic Plateau. Among these 267 AWSs, 63 have been operating for more than 20 years and 27 of them in excess of more than 30 years. Of the five meteorological parameters, the measurements of air temperature have the best continuity and the highest data integrity. The overarching aim of this comprehensive compilation of AWS observations is to make these data easily and widely accessible for efficient use in local, regional and continental studies; it may be accessed at 10.48567/key7-ch19 (Wang et al., 2022). This dataset is invaluable for improved characterization of the surface climatology across the Antarctic continent, to improve our understanding of Antarctic surface snow–atmosphere interactions including precipitation events associated with atmospheric rivers and to evaluate regional climate models or meteorological reanalysis products. [ABSTRACT FROM AUTHOR]

Mount Qomolangma, known as the "Roof of the World," holds significant importance in exploring the vertical characteristics of the atmosphere, providing insights into high-altitude atmospheric features, and improving numerical models for forecasting downstream regions. Ground-based microwave radiometers (GWR) enable continuous profiling of atmospheric conditions in the troposphere, complementing radiosonde and satellite observations. This study explores the performance of the MWP967KV GWR installed at Qomolangma Base Camp by comparison with concurrent radiosonde measurements. The assessment covers GWR's atmospheric radiative brightness temperatures (T b) detection capability, accuracy of atmospheric parameter retrievals, and uncertainties in atmospheric parameters under different weather conditions. Using MonoRTM to calculate simulated T b from radiosonde, the results indicate a high precision of GWR's T b observations, showing a strong correlation (R ≈ 0.99) and a deviation of merely 2.4 K compared to simulated T b. Moreover, GWR exhibits high reliability in temperature (R ≈ 0.98) and water vapor density (ρ v) (R ≈ 0.91) observations, while the accuracy of relative humidity (RH) measurements requires improvement (R ≈ 0.55). The GWR observations are affected by clouds, precipitation, and surrounding Qomolangma mountain ridges, leading to significant uncertainties in atmospheric parameter retrievals between 2000 m to 6000 m above ground level. Additionally, GWR's sensitivity to temperature variations is limited, resulting in missed detections of temperature inversion. Despite these limitations, this study offers crucial insights into meteorological observations at high altitudes using GWR. These findings hold substantial implications for meteorological research and mountaineering activities in high-altitude regions. • The world's highest observation experiment of microwave radiometer. • Microwave radiometer's brightness temperature yielded an R of 0.99 and a bias of 2.4 K. • Microwave radiometer retrieved temperature and vapor density exhibited reliability. • Uncertainties in microwave radiometer under rainy, clear and cloudy conditions. [ABSTRACT FROM AUTHOR]

• The new model, developed to project future changes in rainfall erosivity, incorporates the ratio of modeled precipitation from future to historical periods as the dependent variable. • Under the Shared Socio-Economic Pathway (SSP) 5–8.5 scenario, there's an expectation of a 2.5% rise in annual rainfall erosivity during the mid-century and 6.4% towards the end, relative to the 2000–2010 baseline. • CMIP6 models present a more significant increase in future rainfall erosivity and demonstrate a higher lever of agreement in multi-model projections, compared to CMIP5 models. Quantifying future changes in rainfall erosivity is essential to address potential water erosion risks. This study reveals a significant power function relationship between rainfall erosivity and precipitation both globally and across various climatic zones. Building on this foundation, new empirical models were developed to project relative changes in rainfall erosivity. These models, predicted on the understanding that General Circulation Models (GCMs) provide more accurate predictions of climate change trends than exact meteorological values, utilizes the ratio of modeled historical precipitation to future precipitation under various scenarios as the variable, formulated as a power function. Data from three GCMs runs from both the Coupled Model Intercomparison Project phase 5 (CMIP5) and CMIP6–including historical, mid-term, and long-term periods–were employed. The analysis suggests that by the end of the 21st century, global annual rainfall erosivity could increase by 2.6% under the Shared Socio-Economic Pathway (SSP)1–2.6 scenario, by 3.5% under SSP2-4.5, and by a significant 6.4% under SSP5-8.5, relative to the 2000–2010 baseline. Furthermore, over 76% of the global land area is projected to experience an increase in rainfall erosivity over the century. Regions with projected changes in rainfall erosivity, whether increase or decrease, are likely to face more pronounced changes from mid-century onwards. The CMIP6 exhibits improved model consistency over its predecessor, CMIP5, indicating a greater water erosion risk as global warming progresses. These projections offer insights for strategies to combat soil degradation due to climate changes. [ABSTRACT FROM AUTHOR]

Precipitation with different phases can exert different influences on the Antarctic mass balance. Using the observational rain and snow days from the Great Wall Station, ERA-interim reanalysis, and other data, this study investigates the mechanisms governing the year-to-year variability of precipitation phase (i.e., rainfall and snowfall) over the northern Antarctic Peninsula (AP) during austral summer (December, January, and February; abbreviated as DJF) for the period 1985–2016. The results reveal that the rainfall and snowfall anomalies are controlled mainly by the change in the proportion of precipitation occurring as rain and snow, and the latter is strongly influenced by the change in air temperature. Through regulating the air temperature, different atmospheric circulation anomalies affect the variability of the rainfall and snowfall over the northern AP during summer. Specifically, a circulation pattern with an anomalous anticyclone over the Malvinas Islands and an anomalous cyclone over the Amundsen–Bellingshausen Seas (ABS) can increase summer rainfall, whereas an anomalous cyclone over the Weddell Sea facilitates more snowfall. The summertime atmospheric circulation anomalies, which modulate the variability of rainfall over the northern AP, are primarily caused by an atmospheric teleconnection pattern persisting from austral spring (September–November, SON) to summer. Such a persistent teleconnection pattern can be attributed to the long-time maintenance of sea surface temperature anomalies due to air-sea interaction processes. • The atmospheric circulation anomalies can affect the variability of summer precipitation phase over the northern Antarctic Peninsula. • Atmospheric circulation anomalies governing the change in the rainfall can be caused by a long-time persisting atmospheric teleconnection pattern from spring to summer. • The maintenance of the atmospheric circulation anomalies can be attributed to the interseasonal persistence of the SST anomalies. [ABSTRACT FROM AUTHOR]

Near-surface wind speed observations from 30 manned meteorological stations and 26 automatic weather stations over the Antarctic Ice Sheet are used to examine the robustness of wind speed climatology in six recent global reanalysis products: the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), the Japan Meteorological Agency 55-Year Reanalysis (JRA-55), the Climate Forecast System Reanalysis (CFSR), the National Centers for Environmental Prediction–U.S. Department of Energy (DOE) Reanalysis 2 (NCEP2), and the European Centre for Medium-Range Weather Forecasts (ECMWF) interim reanalysis (ERA-Interim) and fifth-generation reanalysis (ERA5). Their skills for representing near-surface wind speeds vary by season, with better performance in summer than in winter. At the regional scale, all reanalysis datasets perform more poorly for the magnitude, but better for their year-to-year changes in wind regimes in the escarpment than the coastal and plateau regions. By comparison, ERA5 has the best performance for the monthly averaged wind speed magnitude and the interannual variability of the near-surface wind speed from 1979 onward. Intercomparison exhibits high and significant correlations for annual and seasonal wind speed Antarctic-wide averages from different datasets during their overlapping timespans (1980–2018), despite some regional disagreements between the different reanalyses. Furthermore, all of the reanalyses show positive trends of the annual and summer wind speeds for the 1980–2018 period, which are linked with positive polarity of the southern annular mode. [ABSTRACT FROM AUTHOR]

The response of vegetation to past global warming, as revealed by geological records, can provide insights into future changes. We used pollen records to reconstruct spatial changes in the boundary between steppe and forest/forest-steppe for the Last Glacial Maximum (LGM), mid-Holocene, Last Interglacial (LIG), and mid-Pliocene, representing major changes in global temperature. The results showed that in the region east of 110° E, the trend of the boundary between steppe and forest/forest-steppe rotated anticlockwise by around 30°, 5° and 10°, during the warm periods of the mid-Holocene, LIG, and mid-Pliocene, relative to the LGM, mid-Holocene, and LIG, respectively. However, in the region west of 110° E, the boundary remained stationary during the mid-Holocene compared with the LGM, while it shifted northward during the LIG relative to the mid-Holocene, and it shifted southward during the mid-Pliocene relative to the LIG. Overall, our results indicate an enhanced east-west climatic contrast in northern China under past global warming. Climate simulation results showed that the warming-induced northward shift and westward extension of the western Pacific subtropical high promoted the northwestward displacement of the East-Asian monsoon rainfall belt. This suggests that in the future, under a warmer climate, the eastern region of northern China will become wetter, and that the extent of sandy desert will decrease. • The southern boundary of steppe in northern China rotated anticlockwise with warming. • The western Pacific subtropical high (WPSH) expanded during past warm intervals. • The expansion of the WPSH increased precipitation in northern China. • Global warming enhanced the east–west climatic contrast in northern China. • The area of sandy deserts in the eastern China will decrease under a warm climate. [ABSTRACT FROM AUTHOR]

In recent years, increasing moisture over the Arctic and subarctic regions shows that the Arctic is experiencing wetting conditions, and poleward atmospheric moisture transport (PAMT) plays a vital role in the atmosphere-ice/snow interactions in the Arctic. To identify the effect of PAMT on the surface energy balance (SEB) for the Arctic glacier, meteorological data from an automatic weather station (AWS) at 377 m a.s.l. on the Austre Lovénbreen glacier, as well as the ERA5 reanalysis data from 30 April 2014 to 30 April 2015, were analyzed in this paper. Our results show that the net shortwave radiation (S net) (18 W m−2, 55%), turbulent sensible (H) (14 W m−2, 43%) and subsurface heat flux (G) (1 W m−2, 2%) act as the energy sources, while the net longwave radiation (L net) (−19 W m−2, 56%), melt energy (Q m) (−12 W m−2, 35%) and turbulent latent heat flux (LE) (−3 W m−2, 9%) represent the heat sink. The development process of Atmospheric River (AR), primary form of PAMT, near the Svalbard in February 2015 was revealed according to the total column water vapor, 850 hPa winds and geopotential height fields. Compared to summer, the glacier SEB was more affected in winter by PAMT, leading to a frequent overcast and thus increasing air temperature, moisture, and wind speed, all of which are variables governing the SEB by decreasing H, LE and G less than increasing the L net. Our findings obtained here can help to better understand the diverse SEB change on the high Arctic glacier from the perspective of PAMT and large-scale atmospheric circulations anomalies. [ABSTRACT FROM AUTHOR]

The spatiotemporal distribution pattern of marine-origin matter on the Antarctica ice sheet was used to study variations in the source regions, transport mechanisms and post-depositional influences. We present data on sea salt ions, sulfur components and stable isotopes from surface and snow pit samples collected along the transect route from Zhongshan Station to Dome A during the austral summer in 2012–2013. A general decreasing trend in the accumulation, sea salt ions and sulfur components occurred with increasing distance from the coast and increasing elevation. However, different sources of the marine components, transport pathways and post-depositional influences were responsible for their different spatial distribution patterns. The marine ions in the coastal snow pit varied seasonally, with higher sea salt ion concentrations in the winter and lower concentrations in the summer; the opposite pattern was found for the sulfur compounds. The sea ice area surrounding Antarctica was the main source region for the deposited sea salt and the open sea water for the sulfur compounds. No significant trends in the marine-origin components were detected during the past 3 decades. Several periods of elevated deposition of sea salt ions were associated with lower temperatures (based on δD and δ 18 O) or intensified wind fields. In comparison to the sea salt ions, the sulfur concentrations exhibited the opposite distribution patterns and were associated with changes in the surrounding sea ice extent. [ABSTRACT FROM AUTHOR]

• Locally absent rings can be the proxy to locate tipping points of forest systems. • Pinus tabuliformis suffered increasing locally absent rings since 2000s. • The highest locally absent ring frequency was at the driest distribution margin. • Loally absent ring frequency increased along with tree age and moisture deficit. • Locally absent ring risk would gradually increase in the future. Global climatic change indicates that some climate systems have passed tipping points, e.g. the inner East Asia; however it's still uncertain when the tipping point of forest mortality could be triggered. Absent rings are early warnings of irreversible mortality. They widely exist in Northern Hemisphere forests, but they're locally rare and under-discussed in previous studies. We reported a tree ring network, including 17 collections among the extensive distribution of Pinus tabuliformis in North China. Locally absent rings (LAR) were counted and logistic models were built to determine biotic and abiotic driving forcings of LAR. Pinus tabuliformis suffered increasing LAR frequency in recent decades, and the highest LAR frequency occurred at the driest distributional margin. At the semi-arid region, LAR frequency increased along with increasing age, decreasing previous September moisture, and decreasing May moisture. LAR risk would gradually increase, and older trees would suffer quite high LAR risk in the future. We highlight the connection between frequent LAR and extreme droughts in semi-arid pine forests, and propose that LAR can be a proxy of the potential tipping points of forest systems. [ABSTRACT FROM AUTHOR]

The knowledge of the vertical atmospheric structures in the Arctic Region remains elusive, due largely to sparse long-term continuous profiling observations. Based on the temporally high-resolution (1 s) radiosonde measurements from April 2017 to September 2019 collected at the Ny-Ålesund (11.92°E, 78.92°N) station in the Arctic, we analyzed the characteristics of temperature inversion (TI) and clouds, including the diurnal and seasonal variabilities under different atmospheric circulations. Clouds mainly appear in the lower troposphere, with the largest contribution by double-layer clouds. The seasonal variation of vertical cloud distribution above 7 km seems is closely linked to the seasonal variability of tropopause height. Besides, the diurnal variation of TI frequency exhibits significant seasonality, with a bimodal distribution in the vertical, with stronger TI intensity in summer. The lowest temperatures at the top of bottom of the elevated inversion are observed in winter, whereas the lowest temperature of the surface-based inversion top is observed in spring, which may be related to the seasonal variation of sea surface temperature. The characteristics of cloud and TI are further analyzed under the five typical circulation patterns. It is found that the low-pressure system and southerly wind in front of the trough are favorable for cloud formation in the lower troposphere, while the impact of synoptic pattern on clouds in the upper troposphere seems negligible, likely due to the cold environment. The TI associated with cyclone systems tends to be much thinner and weaker, owning to the conditionally unstable conditions. These findings provide key reference for the vertical structure of the inversion and cloud in the Arctic, which is expected to help improve cloud parameterization in numeric model. • Vertical structures of temperature inversions and clouds were analyzed for different synoptic patterns. • The occurrence of inversion and cloud differs greatly by synoptic patterns. • The inversion and cloud observations are crucial for the studies related to climate in the Arctic. [ABSTRACT FROM AUTHOR]

Refractory black carbon (rBC) aerosols emitted by biomass burning and fossil fuel combustion can cause significant climatic forcing when it deposited on the snow. The Southern Hemisphere (SH) biomass burning emissions represent a significant part of rBC in and around Antarctica. Here we present the spatial and temporal variations of rBC from the surface snow and snow pits samples along the coastal Zhongshan Station (ZSS) to inland Dome A transect in Lambert Glacier region of eastern Antarctica. The geometric mean concentrations of surface snow rBC was 0.017 ± 0.018 ng g−1 and showed higher values in the inland plateau region (900–1248 km, 0.031 ± 0.024 ng g−1) than the coastal region (0–400 km, 0.011 ± 0.005 ng g−1) and there exist similar spatial results for the inland snowpit (0.021 ± 0.017 ng g−1) and coastal snowpit (0.018 ± 0.013 ng g−1). The records from the coastal snowpit (SP-A) show that the rBC from 2009 to 2016 displays weak seasonal variations, while in the inland snowpit (SP–C) the records spans from 1950 to 2015 and showed the rBC concentrations vary and relate with the open biomass burning emission in the Southern Hemisphere. • Spatial and temporal variations of the rBC along the transect from ZSS to Dome A in eastern Antarctica were retrieved. • Higher geometric mean rBC concentrations in the interior section than the coastal section were detected. • Dome A rBC record during 1950 and 2015 shows good relation with the open biomass burning in the Southern Hemisphere. [ABSTRACT FROM AUTHOR]

Accurate and high-resolution sea ice surface temperature (IST) data is of great importance for Arctic climate studies. However, the validation of high-resolution IST data using in situ measurements in polar sea ice regions is lacking. This study assesses the accuracy of three split-window (SW) and two single-channel (SC) methods, based on Landsat 8 thermal infrared imagery at 100 m resolution over Arctic sea ice regions. The SW methods are proposed by Jin et al. (2015) (SW-Jin), Jiménez-Muñoz et al. (2014) (SW-JM), and Du et al. (2015) (SW-Du). The SC methods are proposed by Jiménez-Muñoz et al. (2014) (SC-JM) and Barsi et al. (2003, 2005) (SC-Barsi). IST data derived from 58 scenes of the Landsat 8 images were compared with coincident in situ ice skin temperatures and near-surface air temperatures, as measured by a combination of Ice Mass Balance (IMB) buoys, Snow and Ice Mass Balance Array (SIMBA) buoys, and automatic weather stations. SW-Du offers the best accuracy when compared with the skin temperature (bias: −1.06 K; root mean square error (RMSE): 2.08 K) and near-surface air temperature (bias: -0.98 K; RMSE: 2.17 K). SC-Barsi ranks second, with a bias of −1.55 K and RMSE of 2.40 K for the skin temperature. As for precision, IST from the Moderate Resolution Imaging Spectrometer (MODIS) has best performance (standard deviation (STD): 1.69 K), followed by SW-Du, SW-JM, and SC-Barsi (STD: 1.80 K, 1.82 K, and 1.85 K, respectively). The Landsat IST outperforms the MODIS IST in narrow lead areas, owing to its better spatial resolution, and SW-JM and SC-Barsi methods agree best with the MODIS IST in leads and marginal ice zone scenes, respectively. As all three SW methods are constrained by banding effects with different degrees in a lead scene, they are not recommended to be applied on an image scene with severe banding artifacts. The small bias (1.26 K) and high correlation (0.99) between skin temperature and near-surface air temperature prove the capability of using near-surface air temperature as a substitute for validating a satellite IST data if skin temperature data are not available. • IST from Landsat 8/TIRS images is accurate enough for sea ice related use. • Split window algorithm has better accuracy than single channel method. • Fine resolution IST images can capture small details on sea ice regions. • Banding artifacts in TIRS images still contaminate IST maps. [ABSTRACT FROM AUTHOR]

In this study, a shallow ice core (12.5 m, called LGB) was drilled at the Lambert Glacial Basin, East Antarctica. The major ion and metal elements were measured at 5–6 cm resolution in this shallow core, which covered the period 1990–2017. Therefore, an annual-resolution record of iron (Fe) concentrations and fluxes were reconstructed in this shallow ice core. Although the Fe data is comparable to previous results, our results emphasized that much more dissolved Fe (DFe) from the Cerro Hudson volcanic event (August 1991) was transported to the East Antarctic ice sheet, in comparison with the Pinatubo volcanic event (June 1991). The aeolian dust may be the primary DFe source during 1990–2017. In particular, the DFe variations may be affected by the biomass burning emissions in two periods (1990–1998 and 2014–2017). While total dissolved Fe (TDFe) variations were controlled by the climatic conditions since 2000 because of the temperature (δ18O) decreasing at East Antarctica. These Fe data will be useful to assess the modern bioavailable Fe release for the Antarctica ice sheet. • High resolution DFe (TDFe) data was collected from an East Antarctic shallow core. • The eruption events can provide plenty DFe and stored in Antarctica ice sheet. • Fe variations during 1990–2017 were controlled by natural climatic characteristics. [ABSTRACT FROM AUTHOR]

Measurements from 30 and 31 ice drifters during the seasonal transition from mid-August to late September of 2014 and 2016, respectively, were used to characterize sea ice motion and deformation in the western Arctic Ocean. The dispersion distance for the ice deformation in summer was markedly reduced because the mechanical behavior of sea ice in summer is closer to free drift and more granular compared to that in winter. For unconsolidated sea ice in late summer the logarithmic relationship between deformation and spatial scale is 2.4–3.1 times that for ice under freezing conditions. For 2007 to 2016 late summer (August – September) sea ice compactness in the Arctic was the highest (lowest) in 2014 (2016). Along the trajectories of the 2016 (2014) ice camp, the average 10-m wind speed in August–September was larger (smaller) than that averaged in 1979–2016 by 20% (13%). Relative to the great Arctic cyclone in August 2012, cyclones in summer 2016 had comparable sizes and intensity but with longer persistence. Lower ice compactness coupled with stronger cyclonic activity in late summer 2016 led to increased ice speed and enhanced deformation compared to 2014. Sea ice during late summer 2016 was closer to free drift, resulting in greater homogeneity of the drift field, a larger ice–wind speed ratio, as well as weaker multifractality, localization, and space–time coupling of the deformation field compared to late summer 2014. The localization of ice deformation in late summer 2014 was comparable to that obtained in the freezing season because of the high ice compactness. The enhanced ice dynamics in summer 2016 promoted ice melt and area loss via the positive albedo feedback. • High ice compactness led to strong multifractality and localization of deformation in summer 2014. • Reduced ice concentration together with intense cyclones increased deformation in summer 2016. • Enhanced ice divergence in summer 2016 led to increased absorption of solar radiation by ocean. [ABSTRACT FROM AUTHOR]

A precise Arctic surface air temperature (SAT) dataset, that is regularly updated, has more complete spatial and temporal coverage, and is based on instrumental observations, is critically important for timely monitoring and improving understanding of the rapid change in the Arctic climate. In this study, a new monthly gridded Arctic SAT dataset dated back to 1979 was reconstructed with a deep learning method by combining surface air temperatures from multiple data sources. The source data include the observations from land station of GHCN (Global Historical Climatology Network), ICOADS (International Comprehensive Ocean-Atmosphere Data Set) over the oceans, drifting ice station of Russian NP (North Pole), and buoys of IABP (International Arctic Buoy Programme). The last two are crucial for improving the representation of the in-situ observed temperatures within the Arctic. The newly reconstructed dataset includes monthly Arctic SAT beginning in 1979 and daily Arctic SAT beginning in 2011. This dataset would represent a new improvement in developing observational temperature datasets and can be used for a variety of applications., (© 2023. The Author(s).)

Competing Interests: Conflict of interest The authors declare that they have no conflict of interest.