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In order to investigate the impact of increasing the vertical resolution of the initial field on the 12–24 h forecasts of the TRAMS (Tropical Regional Atmosphere Model System) model, this study conducted numerical experiments focusing on a typical coastal warm sector rainfall event that occurred in the South China. The findings indicate that increasing the vertical resolution of the initial field led to improved simulation of coastal convection during the 0–12 h period. However, spurious convection was observed over the sea surface and continued to intensify in the 12–24 h period. Subsequent analysis revealed that the spurious convection is primarily associated with the hydrostatic adjustment of initial potential temperature in the TRAMS model. The hydrostatic adjustment leads to a reduction in the stability of the initial temperature stratification in the lower layers of the model, particularly when the number of vertical layers in the initial field increased from 17 to 32. A noticeable spurious unstable layer emerged between 0–200 m over the sea surface, triggering false convection. Further investigation revealed that the area where this unstable stratification occurs over the sea is situated below the height of the lowest level of the input analysis field (1000 hPa), indicating that the spurious disturbances are caused by an unreasonable vertical extrapolation process. Therefore, the findings of this study indicate that the extrapolation calculations using cubic splines in the initialization module of the TRAMS model introduce significant errors. Moreover, these errors increase with the enhancement of the vertical resolution of the initial field, which limits the improvement in model forecasting that could be achieved by increasing the vertical resolution of the initial field. We found that increasing the vertical resolution of the initial field in the TRAMS model led to spurious convection. This spurious convection is triggered by a false unstable layer near the surface. The computational errors during the hydrostatic adjustment of the initial perturbed potential temperature resulted in this false unstable layer.

During boreal winter, the invasion of cold air can lead to remarkable temperature drops in East Asia which can result in serious socioeconomic impacts. Here, we find that the intensity of strong synoptic cold days in the East China Sea and Indochina Peninsula are increasing. The enhanced synoptic cold days in these two regions are attributed to surface warming over the South China Sea and Philippine Sea (SCSPS). The oceanic forcing of the SCSPS on the synoptic cold days in the two regions is verified by numerical simulation. The warming of the SCSPS enhances the baroclinicity, which intensifies meridional wind and cold advection on synoptic timescales. This leads to a more extended region that is subject to the influence of cold invasion.

To improve the radar data assimilation scheme for the high‐resolution Tropical Regional Atmospheric Model System (TRAMS) model, this study investigates the sensitivity of simulating a warm‐sector rainfall event in southern China to different radar reflectivity retrieval methods and incremental updating strategies. The findings indicate that the ice cloud retrieval (ICR) method yields more reasonable cloud hydrometeors. However, the impact of different retrieval methods is minimal without corresponding adjustments to the dynamic field. Further assimilation of the wind field effectively reduced the overestimated south winds and successfully simulated the observed low‐level convergence in northern Guangdong, significantly improving precipitation forecasts. Both incremental analysis update (IAU) and Nudging methods were able to adjust the forecast to better match the observations, with IAU performing slightly better. These findings are beneficial for further improving the forecast accuracy of precipitation intensity. Extending the IAU relaxation time from 4 to 10 min has almost no impact on the actual forecasting. However, prioritizing the adjustment of the wind field through time‐dependent IAU weighting factors, the impact of cloud particle adjustments on the dynamical field can be avoided (e.g., the drag caused by the sinking of cloud particles may offset the upward motion induced by dynamical convergence adjustments). This allows for more realistic low‐level wind convergence and precipitation forecasts to be obtained. Overall, the ICR method for retrieving cloud hydrometeors, combined with the IAU method using time‐dependent distribution weighting factors appears to be a more suitable option for the radar data assimilation scheme in TRAMS model. Key Points The impact of different radar reflectivity retrieval methods is minimal when the dynamic field is not adjusted correspondingly Incremental analysis update (IAU) incremental updating method can adjust the value of forecast variables slightly closer to observations than Nudging method An IAU strategy with variable‐dependent timing is tested and proved to be beneficial for producing quality nowcasting forecasts

El Niño induces an anomalous lower-tropospheric anticyclone over the tropical Northwest Pacific (NWP), accompanied by suppressed local convection and rainfall. The tropical NWP anomalies persist until the following summer, with major effects on the Asian summer monsoons. Based on the phase 5 of the Coupled Model Intercomparison Project (CMIP5) multi-model ensemble, this study finds that climate models commonly underestimate this El Niño-NWP teleconnection with too weak tropical NWP anticyclone and rainfall anomalies in post-El Niño summers, potentially limiting the models’ skill in seasonal prediction of the Asian summer monsoons. The analyses show that such underestimated NWP anomalies in post-El Niño summers in CMIP5 models can be traced back to the well-known excessive equatorial Pacific cold tongue error in the mean. Models with an excessive westward extension of Pacific cold tongue tend to displace westward the simulated pattern of El Niño-related warm SST anomalies along the equator. The warm SST biases over the western Pacific in CMIP5 models would enhance the local atmospheric convection/rainfall and induce low-level cyclonic circulation anomalies over the tropical NWP with a Gill-type Rossby wave response, resulting in the commonly underestimated NWP anticyclone and rainfall anomalies during post-El Niño summers. The present results, along with our previous finding that the equatorial cold tongue bias would distort the projections of tropical Pacific warming pattern under increased greenhouse gas scenario, imply that reducing equatorial cold tongue bias in models can substantially improve climate simulation and prediction/projection for the tropical Pacific and Asian monsoons.

In this study, the interdecadal variability of the relationship between ENSO and winter synoptic temperature variability (STV) over the Asian–Pacific–American region is investigated based on observational data from 1951 to 2018. An interdecadal shift in the ENSO–STV relationship occurred in the 1980s over Eastern China, changing from significant in period 1 (P1; 1951–87) to insignificant in period 2 (P2; 1988–2018). But the ENSO–STV relationship is significantly stable over North America for the whole period. In addition, a possible reason for this interdecadal shift in the ENSO–STV relationship over Eastern China is also investigated. During P1, the ENSO pattern is significantly correlated to the temperature gradient over Northeast Asia, which is the key region influencing the intensification of extratropical eddies. The intensification of extratropical eddies over Northeast Asia is directly associated with the magnitude of STV over Eastern China. But in P2, the ENSO pattern is not related to the temperature over Northeast Asia. Therefore, the change in the ENSO pattern from P1 to P2 contributes to the interdecadal shift in the ENSO–STV relationship in the 1980s over Eastern China by influencing the temperature gradient over Northeast Asia, while ENSO can influence the temperature gradient over North America for the whole period. Furthermore, the possible role of the ENSO patterns in P1 and P2 is also examined by using an atmospheric general circulation model, highlighting that the pattern of SST variation is a determining factor in regulating STV in different regions.

In this study, the relationship between AO and winter synoptic temperature variability (STV) over the Northern Hemisphere is examined in 34 CMIP5/CMIP6 model outputs. With significant model bias around the North Pacific and North Atlantic, most models fail to capture the correct AO–STV pattern in historical simulations compared to observations. To investigate the bias of AO–STV relationship simulations, AO-related processes for the connection between AO and winter STV are examined in high pattern score (HPS) models and low pattern score (LPS) models, respectively. Furthermore, the bias of AO impact can be traced back to AO pattern simulations. On the one hand, compared to observations, HPS models can overall capture the intensity in the North Pacific and North Atlantic center of AO. On the other hand, LPS models tend to overestimate the North Pacific center and underestimate the North Atlantic center. In addition, similar to historical simulations, a robust AO–STV relationship can still be found over the Northern Hemisphere in future projections based on HPS models. Meanwhile, the uncertainty of the projected AO–STV relationship in the multimodel ensemble is confined mainly to the North Pacific, consistent with the large diversity of intensity over the North Pacific center of AO, which is related to the uncertainty of the relationship between AO and regional mode variability.

In this study, the relationship between ENSO and winter synoptic temperature variability (STV) over the Asian–Pacific–American region is examined in 26 CMIP5/6 model outputs. Compared to observations, most models fail to simulate the correct ENSO–STV relationship in historical simulations. To investigate the possible bias in the ENSO–STV simulations, two possible processes for the connection between ENSO and winter STV are examined in high pattern score (HPS) models and low pattern score (LPS) models, respectively. On the one hand, both HPS and LPS models can overall reproduce a reasonable relationship between STV and the mean-flow conditions supporting extratropical eddy development. On the other hand, only HPS models can well capture the relationship between ENSO and the development of extratropical eddies, while LPS models fail to simulate this feature, indicating that the bias in the simulated ENSO–STV relationship among CMIP5/6 models can be traced back to ENSO simulation. Furthermore, the bias of the ENSO simulation is characterized by an unreasonable SST pattern bias, with an excessive westward extension of warm SST anomalies over the western Pacific and weak warm SST anomalies over the equatorial central-eastern Pacific, resulting in the underestimation of the zonal SST anomaly gradient among models. Therefore, the ENSO pattern bias induces an unrealistic circulation and temperature gradient over the Asian–Pacific–American region, affecting the simulations of the ENSO–STV connection. In addition, the ENSO–STV relationship over the Asian–Pacific–American region is still robust in future projections based on HPS models, providing implications for the selection of future climate predictors.

In winter 2018/19, southeastern coastal China experienced extreme warm temperatures that were due to a weak East Asian winter monsoon. On the basis of observations from 10 meteorological stations and reanalysis data, the large-scale circulation patterns associated with this extreme warm winter and the possible driving mechanism of its related sea surface temperature (SST) anomalies are investigated in this study. During this winter, many places in this region reached their highest winter mean temperature record and had more extreme warm days and fewer extreme cold days relative to climatology. According to the circulation patterns during winter 2018/19, several large-scale circulation conditions associated mainly with the weak East Asian winter monsoon are identified: the eastward shift of the Siberian high and a shallower East Asian trough, which is related to the low blocking frequency over the Aleutian region, are both unfavorable for cold-air intrusion southward. Meanwhile, strong low-level southerly wind anomalies over southeastern China are related mainly to the 2018/19 El Niño event. Furthermore, the possible role of SST anomalies over the North Atlantic and tropical western Pacific Oceans is examined by using an atmospheric general circulation model, suggesting that both the “tripole pattern” of North Atlantic SST and tropical western Pacific SST anomalies in winter 2018/19 played a role in influencing the East Asian trough. The combined effect of all of these factors seems to be responsible for this extreme warm winter over southeastern coastal China.

This study investigates bidecadal variation and trends in the winter East Asian trough (EAT) intensity for the period from 1958 to 2020. The EAT intensity index, calculated with the JRA55 reanalysis, demonstrates bidecadal variation, which is closely related to the intensity of cold advection in East Asia that affects northeast China, the Korean Peninsula, and Japan. In addition, it is noted that the positive phase of the Arctic Oscillation (AO) plays an important role in suppressing EAT intensity, particularly on a bidecadal time scale. On the other hand, a warm anomaly in the west Pacific can enhance the intensity of the EAT, which is also reproduced by numerical simulation. The influence of a significant warming trend in the west Pacific and a weak positive trend in the AO on the EAT intensity and the East Asian winter monsoon is investigated. Warming in the west Pacific supports a strengthening of EAT intensity, cooling in northeast Asia, and enhancement of easterly wind in the subtropical west Pacific. A weak positive AO trend plays an insignificant role in affecting the trend of EAT intensity, but it supports warming in northeast Asia.

Background This study aimed to investigate functions of GLP-1R agonist by liraglutide (LIRA) and revealing the mechanism related to AGEs/RAGE in chondrocytes. Methods To illustrate potential effect of GLP-1R agonist on AGEs induced chondrocytes, chondrocytes were administrated by AGEs with LIRA and GLP-1R inhibitor exendin. Inflammatory factors were assessed using ELISA. Real-time PCR was used to evaluate the catabolic activity MMPs and ADAMTS mRNA level, as well as anabolic activity (aggrecan and collagen II). RAGE expression was investigated by Western blotting. TUNEL, caspase3 activity and immunofluorescence were performed to test the apoptotic activity. Results Our results showed that treatment with LIRA at > 100 nM attenuated the AGE-induced chondrocyte viability. Western bolt demonstrated that GLP-1R activation by LIRA treatment reduced RAGE protein expression compared with the AGEs groups. ELISA showed that LIRA hindered the AGEs-induced production of inflammatory cytokines (IL-6, IL-12 and TNF-α) in primary chondrocytes. AGEs induced catabolism levels (MMP-1, -3, -13 and ADAMTS-4, 5) are also attenuated by LIRA, causing the retention of more extracellular matrix (Aggrecan and Collagen II). TUNEL, caspase3 activity and immunofluorescence results indicated that LIRA inhibited the AGEs-induced production of inflammatory cytokines in primary chondrocytes and attenuated the caspase 3 level, leading to the reduced apoptotic activity. All the protective effects are reversed by exendin (GLP-1R blockers). Conclusions The present study demonstrates for the first time that LIRA, an agonist for GLP-1R which is commonly used in type 2 diabetes reverses AGEs induced chondrocyte inflammation and apoptosis through suppressing RAGE signaling, contributing to reduced catabolism and retention of more extracellular matrix. The above results indicate the possible effect of GLP-1R agonist on treating OA.