Extreme cyclones from the mid-latitudes can transport water vapor and heat to the Arctic,affect the Arctic sea ice extent and the thickness of ocean mixing layer,and bring strong winds,low temperatures,rain and snow.Using ERA-5 reanalysis data at 6 h intervals during 1980-2021,extreme cyclones originating from the mid-latitudes of the North Atlantic and entering the Arctic during winter are objectively identified and tracked.In total 130 extreme cyclones are identified and classified.The generation mechanisms behind extreme cyclones with three different tracks,i.e.,west,middle and east,and the reasons for the differences in these tracks after the formation of extreme cyclones are explored.Results show that positive potential vorticity appearing in the lower stratosphere 5-6 d prior to the formation of the extreme cyclones and the downward intrusion of stratospheric positive potential vorticity into the upper troposphere that accelerates the polar front jet provide dynamic conditions favorable for the formation of extreme cyclones.When an extreme cyclone is generated,the upper and lower positive potential vorticity regions are connected,leading to rapid development of the cyclone.Additionally,it is found that the cyclone track after cyclogenesis primarily depends on the transport of warm advection in the lower troposphere.

Current data-driven weather forecasting models demonstrate superior performance yet remain dependent on reanalysis or analysis fields from numerical models, inheriting their systematic errors. To address this constraint, we present FengYuan, an end-to-end global weather forecasting model that directly processes multi-source observational data to generate forecasts. FengYuan employs a modular architecture with two components: a data assimilation module (FengYuan-DA) that integrates observational data from satellites, surface stations, and radiosondes with background fields, and a forecasting module (FengYuan-Forecasting) that generates medium-range global forecasts. The system uses a staged training strategy, first training the FengYuan-Forecasting module on ERA5 reanalysis data, then iteratively optimizing the FengYuan-DA module using the forecasting module outputs. Evaluation on the 2022 test set shows that the FengYuan-Forecasting module achieves performance comparable to state-of-the-art Artificial Intelligence (AI) models and significantly outperforms ECMWF’s Integrated Forecasting System (IFS), with enhanced capabilities for regional forecasting over East Asia. The FengYuan-DA module achieves substantial improvements, showing remarkable spatial consistency with ERA5 reanalysis, low global root-mean-square errors, and effective assimilation of multi-source observational signals. The complete end-to-end system of FengYuan, initialized with FengYuan-DA analysis fields, achieves forecast quality very close to the reanalysis-driven version while consistently outperforming IFS throughout the 10-day forecast period, demonstrating that FengYuan successfully bridges observations to forecasts while maintaining high accuracy.

The North Atlantic constitutes the primary pathway for winter cyclones intruding into the Arctic, and these cyclones are typically much more intense than those formed locally. When extreme cyclones penetrate the Arctic, they transport water vapour and heat to the north, inducing pronounced anomalies in weather and sea ice. Based on objective trajectory analysis, three distinct types of extreme cyclones were identified according to their tracks from the North Atlantic to the Arctic: Type 1 and Type 2 cyclones intrude into the seas west and east of Greenland and the Arctic Ocean, respectively, while Type 3 cyclones migrate along the European continent margin. This research investigates the associated anomalies in Arctic atmospheric circulation and sea ice in response to these trajectories. The results reveal that the three types of extreme cyclones are linked to distinct circulation anomalies, characterised by polar vortex splitting, Arctic Oscillation, and polar vortex displacement. Furthermore, Type 1 and Type 2 cyclones favour warming from troposphere to lower stratosphere, whereas Type 3 cyclones are conducive to cooling in both troposphere and stratosphere. Preliminary analysis suggests that prior to and during the early stages of cyclone development, dynamic wind effects in the lower troposphere drive sea ice southward, reducing sea ice in the polar regions while increasing it in lower latitudes. Moreover, warm air advected northward by the cyclone promotes sea ice loss, whereas the intrusion of cold air in the cyclone's rear sector enhances sea ice formation.

The nocturnal ozone enhancement events (NOE events) have been observed in the Beijing-Tianjin-Hebei region (BTH), China over recent years with frequent ozone pollution during the daytime. However, the characteristics and mechanisms of NOE events in BTH is still insufficiently investigated. This study analyzes the spatiotemporal distribution of NOE events in the BTH region and explores the mechanisms of NOE events in different seasons based on the hourly ozone observation data from 2018 to 2023.The results show that there are 147 NOE events per year in the BTH region over 6 years, mainly occurring from March to September, between the local time 10 pm and 2 am of the next morning. Relative to the 6-year averages of nocturnal ozone concentrations, the majority of the nocturnal hourly ozone concentration increments are between 10 and 20 µg.m−3, accounting for 59

The Atmospheric Infrared Sounder (AIRS) on the Aqua satellite, along with the MWTS/MWHS Synergy (TSHS) sounding system and Atmospheric Vertical Sounder System (VASS) on the Fengyun-3D (FY-3D) satellite, provide high-quality data for studying Arctic temperature change. The generalized cold bias of AIRS is confirmed through horizontal comparisons with Arctic land radiosonde stations. VASS corrects the warm bias of TSHS by incorporating the Hyperspectral Infrared Atmospheric Sounder-I (HIRAS-I). Vertical comparisons demonstrate that AIRS, TSHS, and VASS offer excellent temperature detection from the top of the boundary layer to the lower stratosphere (800–100 hPa). However, the overestimation and errors of stratospheric temperatures by TSHS and VASS increase with altitude (pressures below 60 hPa). Specifically, the warm bias trends at 0.06 K hPa−1, reaching 2.87 K and 2.92 K at 10 hPa. Similarly, RMSE values trend at 0.05 K hPa−1, reaching 3.62 K and 3.69 K at 10 hPa. The low correlation (R ⩾ 0.65) of TSHS near 250 hPa in summer is significantly improved in VASS (R ⩾ 0.78) after adding HIRAS-I. The high vertical resolution due to infrared hyperspectral resolution facilitates the detection of complex temperature junctions. The retrieval error of AIRS in the boundary layer increases with cloudiness, while VASS combines microwave and infrared channel data to reduce the impact of cloud cover. Assessing the Arctic applicability of these three satellite temperature profile products will facilitate their widespread use in the Arctic region, enhance accurate climate change monitoring, and further reveal the mechanisms of Arctic warming.

Accurate simulation of land surface processes is pivotal for advancing climate model fidelity and projecting hydrological and ecological responses to climate change. In this study, we incorporate a dynamic root water uptake scheme (DROOT) into the Beijing Climate Center Climate System Model (BCC-CSM), enabling dynamic root distribution and plant water stress responses. This approach provides a more physiologically realistic representation of root-mediated water uptake than conventional static root parameterizations. Model performance was assessed through simulations spanning 1990–2014, focusing on key variables: soil moisture (SM), latent heat flux (LE), gross primary productivity (GPP), precipitation (PR), 2-m air temperature (T2M), and downward shortwave radiation (SW). Our results demonstrate that DROOT substantially enhances SM simulations, particularly in regions where the original model exhibited significant biases, such as the Amazon and mid-latitude zones. Tropical regions also show marked improvements in LE and GPP simulations. Although DROOT’s influence on PR and SW remains marginal, it effectively mitigates warm biases south of 50°N. Furthermore, the scheme refines vegetation’s role in the land–atmosphere water cycle by intensifying SM-LE coupling in semi-arid regions while attenuating the direct PR-SM relationship. This study highlights the critical role of accurately representing land surface ecohydrological processes in climate modeling.

The generation mechanism of extreme snowfall and convective snowfall in Beijing-Tianjin-Hebei region of China from 20 February to 21 February in 2024 are analyzed with high-resolution observations and the fifth-generation European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric reanalysis data (ERA5) with a 0.25° by 0.25° spatial resolution. Results show that the extreme snowfall occurs under the background of North China backflow snowfall circulation, and 500-700 hPa warm and moist air at altitudes of 500 hPa to 700 hPa rises over a layer of cool, wet air, resulting in the formation of snow. The backflow cold air is deep, the northeast wind extends from ground to 850 hPa height, and the maximum wind speed reaches 10 m·s-1. At the same time, 500-700 hPa southwest air flow is deep and strong, and 700 hPa southwest low-level jet stream center intensity reaches 32 m·s-1. The positive anomaly of meridional wind in the middle layer and the negative anomaly of zonal wind in the lower layer both exceeds 10 times the standard deviation during snowfall, while the strong southerly wind provides ample water vapor. In this event, the total atmospheric precipitable water in North China significantly exceeds the annual average for February. Extremely favorable water vapor conditions, combined with appropriate circulation patterns, leads to severe snowstorms. In addition, the radar map displays characteristics of mixed precipitation echoes, with reflectivity factors appearing in bands and patchy areas that exceed 30 dBZ. On the satellite cloud image, the corresponding cloud top brightness temperature is below -60 ℃. During the same period, the maximum snowfall recorded in 1 h reaches 5.9 mm, surpassing the historical extreme value in February since the station is established. Further analysis reveals that high wind speeds contribute to an increase in vertical wind shear between the mid and lower levels. Before the heavy snowfall occurred, the vertical wind shear between four different levels of the lower atmosphere increases continuously, with the maximum vertical wind shear reaching 35 m·s-1 between 150 m and 4 km. The lateral friction creates eddies that generated dynamic energy and conditional symmetric instability energy. At the same time, the frontogenesis function at the height of 700 hPa is positive, leading to vertical circulation generated by frontogenesis. For moist atmospheres above 700 hPa, the upper branch of the frontal secondary circulation triggers the release of unstable energy, resulting in the formation of elevated convection. Phenomenon results in observed convection, lightning, and short periods of heavy snowfall.

Temperature is a fundamental meteorological factor significantly impacting human life and socio-economic development. This study applies a multi-model fusion technique, integrating three artificial intelligence (AI) methods, to improve temperature forecast accuracy by addressing systematic errors and biases in the European Centre for Medium-Range Weather Forecasts (ECMWF) 2 m temperature predictions for Xiong’an New Area and its upstream regions. Using ECMWF forecast data from January 1, 2018, to December 31, 2021, along with ERA5 reanalysis data, we optimized a Bayesian model averaging (BMA_OP) approach, combining linear regression, LightGBM, and UNet to revise the 2 m temperature forecast. BMA_OP demonstrated improved performance, achieving an overall root-mean-square error (RMSE) of 1.15 °C, an average prediction accuracy of 73

The evaluation of ecological environment quality (EEQ) is an important method to determine regional eco-environment status, and topography, as one of the key factors affecting eco-environment, has an impact on the EEQ by influencing hydrothermal conditions. However, research on the effect of topography on the EEQ still needs to be strengthened, especially in the red soil region of southern China. Therefore, based on the evaluation of the EEQ for Changting County using the remote sensing ecological index (RSEI) combined with Landsat images from 2000 to 2019, the effects of topography on the EEQ were analyzed further. The main findings indicated, firstly, that the average values of topographic factors increased as the EEQ grade raised; secondly, the distribution of the EEQ gradually moved to the lower terrain factor categories as the EEQ grade declined for each study period on the whole; thirdly, the coupling effect of any two topographic factors on the EEQ was greater than the effect of a single topographic factor, and the coupling effect of the aspect with the elevation and topographic position index (TPI) on the EEQ was the most prominent. The main findings of the research can enhance the understanding of the variability of the EEQ and the effects of topography on the EEQ.

The evaluation of ecological environment quality (EEQ) is an important method to measure the quality of ecosystem services. Therefore, the EEQ of Changting County, located in the red soil region of southern China, was assessed by using the remote sensing ecological index (RSEI) based on Landsat images from 1995 to 2019, and its spatiotemporal variability was identified by using the Global Moran’s I index, standard deviational ellipse, and kernel density estimation. The results showed that, firstly, the EEQ degraded from 1995 to 2000, then improved from 2000 to 2019; secondly, the spatial distribution of the RSEI for each study year was not random and had a strong positive correlation; thirdly, the directional distributions of the RSEI for all the grades were almost in the direction of southwest to northeast, and the spatial discrete characteristics of the moderate- and good-grade areas were almost consistent from 1995 to 2019; fourthly, the kernel density distribution of the moderate- and good-grade EEQ was located in towns within the Tingjiang River Basin and in the surroundings of the study area, respectively. This study can help managers to better understand the spatial–temporal variations in the EEQ in the study area, supporting the government in formulating a better ecological restoration strategy.

The increase in intense tropical cyclone (TC) activity across the western North Pacific (WNP) has often been attributed to a warming ocean. However, it is essential to recognize that the tropical WNP region already boasts high temperatures, and a marginal increase in oceanic warmth due to global warming does not exert a significant impact on the potential for TCs to intensify. Here we report that the weakened vertical wind shear is the primary driver behind the escalating trend in TC intensity within the summer monsoon trough of the tropical WNP, while local ocean surface and subsurface thermodynamic factors play a minor role. Through observational diagnoses and numerical simulations, we establish that this weakening of the vertical wind shear is very likely due to the increase in temperature of the Tibetan Plateau. With further warming of the Tibetan Plateau under the Representative Concentration Pathway 4.5 scenario, the projected TCs will likely become stronger.

In summer, the Yangtze River valley (YRV) in central–eastern China frequently suffers consecutive extreme rainfall (CER) events, causing floods and huge damages. On the daily timescale, our previous study has shown that the Pacific–Japan (PJ) teleconnection is related to the CER events over the YRV, and is a source for long-term (lead time of about 10 days) forecasts of CER events. To facilitate extended-range (lead time of about 20 days) prediction of CER, in the present study, we use the band-pass filter for the PJ teleconnection to keep only the prolonged atmospheric circulation information at the intraseasonal timescale and try to identify more advanced precursors for the CER events over the YRV. Power spectrum analysis was implemented on 9-day sliding mean of the precipitation anomalies. It is found that summer precipitation in YRV has significant 10–40-day oscillations, and the CER events over the YRV are affected by the intraseasonal oscillation (ISO) of the PJ teleconnection. When the ISO of the PJ teleconnection enters its positive phase, it is favorable for CER events to occur. Dynamic diagnoses and model experiments demonstrate that the ISO of the PJ teleconnection is attributed to the intraseasonal convective activities and diabatic heating around the Philippines, which generate significant northward energy dispersion and propagation of Rossby waves up to 16 days prior to occurrences of the CER events in the YRV. The ISO of the PJ teleconnection and the convective activities in the tropical South Asia provide significant and earlier precursors for extended-range forecasts of the CER events along the YRV.

Changes in extreme temperatures have more effects on ecosystems and human society than changes in climate averages. As a hotspot of global warming, the Arctic has experienced unprecedented heatwaves recently, which highlights the importance of identifying long-term variations of extreme temperatures. However, spatial unbalance of ob-servations and artificially chosen investigation periods limit our knowledge of extreme temperatures over the Arctic lands. Here, we build a complete and quality-controlled observation network on surface temperature over the Arctic lands and combine in situ and reanalysis data to evaluate changes of extreme temperatures during the period 1979-2020. Our results indicate that 1) the increase in extreme temperatures has accelerated since the 2000s, especially on the coast of Eurasia; 2) the change magnitude for cold events is larger than for warm events, in terms of intensity, frequency, and duration; and 3) increases in warm events only occur locally, for example, Alaska and central Siberia, while decreases in cold events occur throughout the Arctic lands. The long-term trends of extreme temperatures are synchronous with sea ice loss, and patterns of interannual variations are mainly related to the North Atlantic Oscillation. We suggest further efforts toward improvement over North America, especially for Greenland, through sufficient observations and regional models.

The Lofoten Vortex (LV) is a quasi-permanent anticyclonic eddy with the characteristic of periodic regeneration in the Lofoten Basin (LB), which is one of the major areas of deep vertical mixing in the Nordic Sea. Our analysis of the LV contributes to our understanding of the variations in convective mixing in the LB. Based on drifter data and satellite altimeter data, the climatological results show that the LV has the sea surface characteristics of relative stability in terms of its spatial position and significant seasonal variations in its physical characteristics. Combined with the temperature and salinity data of Argo profiles, the vertical structures of the LV are presented here in terms of their spatial distribution and monthly variations. The wavelet analysis of the satellite sea surface temperature (SST) data shows that the period of SST anomaly (SSTA) in the LV sea area is 8–16 years. In the stage marked by a decreasing (increasing) trend of SSTA, the vertical mixing is strengthened (weakened). Current vertical mixing is clearly revealed by the Argo profiles, and the SSTA shows a significant impact of cooling. However, against a background of warming and freshening, this vertical mixing will be greatly weakened in the next increasing trending stage of the SSTA.

The extensive global climate observing system (GCOS) reference upper-air network (GRUAN) datasets provide a chance to validate newly released Atmospheric Infrared Sounder (AIRS) version 7 (v7) products over the Arctic. This manuscript reports on the analysis performed to evaluate errors from AIRS version 6 (v6) and v7 temperature profiles and to characterize the derived low-level temperature inversion (LLI) representativeness in the Arctic region. The AIRS averaging kernel, representing the AIRS measurement sensitivity, is applied to reduce the vertical resolution of the radiosonde profiles for comparison. Due to improved retrieval algorithms, v7 produces smaller biases in the troposphere and suppresses the cold bias in v6. Nevertheless, the profile-averaged root mean square error (RMSE) increased by over 30% in v7, particularly in the winter half-year when v7 showed a larger RMSE below 800 hPa. The AIRS temperature retrieval accuracy is primarily sensitive to surface type and cloud fraction. Compared to v6, v7 has less bias over frozen land and sea ice in different cloud fraction conditions. However, the RMSEs of v7 are more sensitive to the effective cloud fraction (ECF) and are highly influenced by a more significant contribution from nonfrozen land samples. Compared to the kernel-averaged radiosonde profiles, more than 80% of the temperature profiles from v6 and v7 accurately detect LLIs. The discreteness of the AIRS's predefined pressure level results is consistent with the radiosondes only 65% of the time for LLI depth calculation. In contrast, the AIRS can obtain LLI intensity with a relatively high correlation (>0.9). With the AIRS temperature retrieval in the boundary layer further improved, it has the potential to be used as an independent LLI detector in the Arctic region.

In summer, the Yangtze River valley (YRV) in central-eastern China frequently suffers consecutive extreme rainfall (CER) events, which consequently cause floods and huge damages. On daily time scale, our previous study has shown that the Pacific-Japan-like (PJ-like) teleconnection pattern is related to the CER events that occurred over the YRV. The prolonged PJ-like teleconnection provides potential medium- to long-term weather predictability of the CER events. However, the intraseasonal oscillation (ISO) is a source of extended-range weather forecasts of CER events. In the present study, we investigated the relationship between the PJ-like teleconnection pattern and CER events on intraseasonal time scale. Power spectrum analysis was implemented on 9-day sliding mean of precipitation and PJ index anomalies. It is found that the summer precipitation in the YRV and the PJ-like teleconnection have significant 10-40-day oscillations. The CER events over the YRV are affected by the ISO of the PJ-like teleconnection. When the PJ-like teleconnection pattern enters its positive phase, it is favorable to the occurrences of the CER events. The dynamic diagnostics and model experiment demonstrate that the mechanism responsible for the ISO of the PJ-like teleconnection is attributed to the intraseasonal convective activities and diabatic heating, which generate the significant northward energy dispersion and propagation of Rossby waves up to 15 days prior to the occurrences of CER events in the YRV. The intraseasonal variations of the PJ-like teleconnection and convective activities around the Philippines provide significant precursors for medium- to extended-range weather forecasts of CER events along the YRV.

The Huaihe River basin (HRB) is an important economically developed and grain production region in China, which is severely affected by rainfall anomalies, especially extreme rainfall events (EREs). It is crucial to the features of interdecadal change in EREs and the contribution of EREs to summer-mean total rainfall amount (TRA) over the HRB. Using the observational 24-h ac-cumulated rainfall and the reanalysis products from the European Center for Medium-Range Weather Forecast (ECMWF), as well as the methods of composite analysis and Mann–Kendal and running t tests, we revealed that the EREs experienced a significant interdecadal increase from the period 1990–1999 to the period 2000–2009. The EREs, particularly long persistent extreme rainfall events (LPEREs), occurred more frequently over the HRB during the latter period and dominated the interdecadal increase in the summer mean TRA. An anomalous high-pressure ridge and associated anomalous anticyclone appeared around Lake Baikal during the latter period, which led to anomalous northeasterlies along the eastern flank of the anomalous anticyclone, inducing the southward intrusion of cold air flow from higher latitudes and associated anomalous ascent and more active convection over the HRB. As such, more EREs and LPEREs occurred during the latter period. The higher pseudo-equivalent temperatures also support more active convective ascent and relevant more EREs. The results may shed light on further understanding the effect of large-scale atmospheric circulation on the interdecadal variability of EREs over the HRB, helping mitigate the disastrous impacts of EREs on local ecosystems, agriculture, soil erosion, and societies.

Although game-based learning strategies have been used in mathematics education for a period of time, the potential for enhancing students’ learning achievement and math self-efficacy is still being explored. Students need to face complex mathematics concepts and calculations in mathematics courses. Even though using games to learn mathematics may enhance students’ motivation, without efficiently personalized learning guidance, students may not be able to learn well in games. Therefore, adaptive educational games provide opportunities to give students personalized learning content and guidance. The concept-effect relationship is an effective tool for the organization of learning material in developing adaptive diagnostic systems for detecting students’ learning problems. In this study, a concept-effect relationship and an interactive game-based learning system were conducted as an effective tool for the organization of learning material in developing a diagnostic and remedial system for detecting students’ learning problems. An experiment was conducted on an elementary school mathematics course to evaluate the effects of the proposed approach. The experimental results clearly show that the proposed approach not only improves the efficiency of learning achievement for students, but also enhances their learning attitudes and self-efficacy, and reduces their cognitive load in mathematics courses.

We examine the links between the thermal condition of the troposphere over the Tibetan Plateau with the atmospheric circulation and climate over the Eurasian continent. The temperature of the troposphere over the Tibetan Plateau is higher than the temperature in other regions at the same latitude and is consistent with the temperature of the Eurasian troposphere on an interannual timescale. The higher temperature of the troposphere over the Tibetan Plateau leads to anomalous south–north temperature gradients from mid-latitudes over the Eurasian continent to its two flanks, accompanied by anomalous easterly and westerly winds in the upper troposphere in the subtropics and at higher latitudes. Anomalous anticyclonic circulations and subsidence motions appear between the anomalous easterly and westerly winds and contribute to the high surface air temperature over West Asia, Central Asia and East Asia via anomalous vertical temperature advection in the troposphere and change in the amount of solar radiation incident on the surface. The enhanced East Asian summer monsoon associated with the high temperature of the troposphere over the Tibetan Plateau also partly contributes to the high surface air temperature over East Asia via horizontal temperature advection. The westerly wind anomalies in the north of the mid-latitudes over the Eurasian continent indicate the enhancement and northward shift of the mid-latitude westerly jet. This is related to anomalous upward motion and higher precipitation in Northeast China and North China. Sensitivity experiments based on an atmospheric model verify the impact of anomalous tropospheric heating over the Tibetan Plateau in summer on the atmospheric circulation over the Eurasian continent.

Ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) measurements were performed during the summer (13 June–20 August) of 2014 at a rural site in North China Plain. The vertical profiles of aerosol extinction (AE) in the lower troposphere were retrieved to analyze the temporal variations of AE profiles, near-surface AE, and aerosol optical depth (AOD). The average AOD and near-surface AE over the period of study were 0.51 ± 0.26 and 0.33 ± 0.18 km−1 during the effective observation period, respectively. High AE events and elevated AE layers were identified based on the time series of hourly AE profiles, near-surface AEs and AODs. It is found that in addition to the planetary boundary layer height (PBLH) and relative humidity (RH), the variations in the wind field have large impacts on the near-surface AE, AOD, and AE profile. Among 16 wind sectors, higher AOD or AE occur mostly in the directions of the cities upstream. The diurnal variations of the AE profiles, AODs and near-surface AEs are significant and influenced mainly by the source emissions, PBLH, and RH. The AE profile shape from MAX-DOAS measurement is generally in agreement with that from light detection and ranging (lidar) observations, although the AE absolute levels are different. Overall, ground-based MAX-DOAS can serve as a supplement to measure the AE vertical profiles in the lower troposphere.