Using the Residual Network Module to Correct the Sub-Seasonal High Temperature Forecast

The high temperature forecast of the sub-season is a severe challenge. Currently, the residual structure has achieved good results in the field of computer vision attributed to the excellent feature extraction ability. However, it has not been introduced in the domain of sub-seasonal forecasting. Here, we develop multi-module daily deterministic and probabilistic forecast models by the residual structure and finally establish a complete set of sub-seasonal high temperature forecasting system in the eastern part of China. The experimental results indicate that our method is effective and outperforms the European hindcast results in all aspects: absolute error, anomaly correlation coefficient, and other indicators are optimized by 8–50%, and the equitable threat score is improved by up to 400%. We conclude that the residual network has a sharper insight into the high temperature in sub-seasonal high temperature forecasting compared to traditional methods and convolutional networks, thus enabling more effective early warnings of extreme high temperature weather.

Transformer for Sub-Seasonal Extreme High Temperature Probabilistic Forecasting Over Eastern China

Sub-seasonal high temperature forecasting is significant for early warning of extreme heat weather. Currently, deep learning methods, especially Transformer, have been successfully applied to the meteorological field. Relying on the excellent global feature extraction capability in natural language processing, Transformer may be useful to improve the ability in extended periods. To explore this, we introduce the Transformer and propose a Transformer-based model, called Transformer to High Temperature (T2T). In the details of the model, we successively discuss the use of the Transformer and the position encoding in T2T to continuously optimize the model structure in an experimental manner. In the dataset, the multi-version data fusion method is proposed to further improve the prediction of the model with reasonable expansion of the dataset. The performance of well-desinged model (T2T) is verified against the European Centre for Medium-Range Weather Forecasts (ECMWF) and Multi-Layer Perceptron (MLP) at each grid of the 100.5°E to 138°E, 21°N to 54°N domain for the April to October of 2016-2019. For case study initiated from 2 June 2018, the results indicated that T2T is significantly better than ECMWF and MLP, with smaller absolute error and more reliable probabilistic forecast for the extreme high event happened during the third week. Over all, the deterministic forecast of T2T is superior to MLP and ECMWF due to ability of utilize spatial information of grids. T2T also provided a better calibrated probability of high temperature and a sharper prediction probability density function than MLP and ECMWF. All in all, T2T can meet the operational requirements for extended period forecasting of extreme high temperature. Furthermore, our research can provide experience on the development of deep learning in this field and achieve the continuous progress of seamless forecasting systems.

Increased Interannual Variability in the Dipole Mode of Extreme High-temperature Events over East China during Summer after the Early 1990s and Associated Mechanisms

The dominant mode of the interannual variability in the frequency of extreme high-temperature events (FEHE) during summer over eastern China showed a dipole mode with reversed anomalies of FEHE over northeastern and southern China. This study found that the interannual variability of this dipole mode underwent an interdecadal increase after the early 1990s. The anomalous atmospheric circulation responsible for the FEHE dipole mode was associated with the air-sea interaction over the western tropical Pacific and North Atlantic. Due to the weakened correlation between the SST in the tropical Pacific and in the Indian Ocean after the early 1990s, a meridional atmospheric wave train induced by the anomalous SST around the Maritime continent (MCSST) was intensified during 1994–2013, which was also contributed by the increased interannual variability of MCSST. However, under the influence of the anomalous SST in the Indian Ocean concurrent with the anomalous MCSST, the meridional wave train was weakened and contributed less to the dipole mode during 1972–1993. In addition, the dipole mode was associated with the atmospheric wave trains at middle-high latitude, which were different during the two periods and related to different air-sea interaction in the North Atlantic. The interannual variability of the dipole mode induced by the associated SST anomalies in the North Atlantic during 1994–2013 was significantly larger than that during 1972–1993. Therefore, the interannual variability of the dipole mode was increased after the early 1990s.

Contrasting Trends of Surface PM2.5, O3, and NO2 and Their Relationships with Meteorological Parameters in Typical Coastal and Inland Cities in the Yangtze River Delta

The contrasting trends of surface particulate matter (PM2.5), ozone (O3), and nitrogen dioxide (NO2) and their relationships with meteorological parameters from 2015 to 2019 were investigated in the coastal city of Shanghai (SH) and the inland city of Hefei (HF), located in the Yangtze River Delta (YRD). In both cities, PM2.5 declined substantially, while O3 and NO2 showed peak values during 2017 when the most frequent extreme high-temperature events occurred. Wind speed was correlated most negatively with PM2.5 and NO2 concentrations, while surface temperature and relative humidity were most closely related to O3. All of the studied pollutants were reduced by rainfall scavenging, with the greatest reduction seen in PM2.5, followed by NO2 and O3. By contrast, air pollutants in the two cities were moderately strongly correlated, although PM2.5 concentrations were much lower and Ox (O3 + NO2) concentrations were higher in SH. Additionally, complex air pollution hours occurred more frequently in SH. Air pollutant concentrations changed more with wind direction in SH. A more effective washout effect was observed in HF, likely due to the more frequent strong convection and thunderstorms in inland areas. This research suggests pertinent air quality control measures should be designed accordingly for specific geographical locations.

North China Plain as a hot spot of ozone pollution exacerbated by extreme high temperatures

A large population in China has been increasingly exposed to both severe ozone (O3) pollution and extreme heat under global warming. Here, the spatiotemporal characteristics of coupled extremes in surface O3 and heat (OPCs) over China are investigated using surface observations, a process-based chemical transport model (GEOS-Chem), and multi-model simulations from Phase 6 of the Coupled Model Intercomparison Project (CMIP6). North China Plain (NCP, 37–41° N; 114–120° E) is identified as a hot spot of OPCs, where more than half of the O3 pollution days are accompanied by high temperature extremes. OPCs over NCP exceed 40 days during 2014–2019, exhibiting an increasing trend. Both O3 concentrations and temperatures are elevated during OPCs compared to O3 pollution days occurring individually (OPIs). Therefore, OPCs impose more severe health impacts to human than OPIs, but the stronger health effects are mainly driven by the higher temperatures. GEOS-Chem simulations further reveal that enhanced chemical production resulting from hot and stable atmospheric condition under anomalous weather pattern primarily contributes to the exacerbated O3 levels during OPCs. In the future, CMIP6 projections suggest increased occurrences of OPCs over NCP in the middle of this century, but by the end of this century, OPCs may decrease or increase depending on the pollutant emission scenarios. However, for all future scenarios, extreme high temperature will play an increasingly important role in modulating O3 pollution in a warming climate.

Variations in Summer Extreme High-Temperature Events over Northern Asia and the Possible Mechanisms

In this study, interannual and interdecadal variations in the extreme high-temperature event (EHE) frequency over Northern Asia (NA) and the associated possible mechanisms are explored. On an interannual timescale, the first two empirical orthogonal function modes of the NA EHE frequency exhibit meridional dipole pattern (EOF1) and diagonal tripolar pattern (EOF2), respectively. The higher NA EHE frequency is related to anomalous local highs, reduced middle-low clouds and more solar radiation. The warmer ground further heats the overlying atmosphere through longwave radiation and sensible heat. The warm temperature advections in lower troposphere and the drier soil conditions also favor higher EHE frequency. Further analysis reveals that the EOF1 mode is related to the Polar-Eurasian teleconnection pattern (POL), while the EOF2 mode is associated with North Atlantic Oscillation (NAO) and Pacific-Japan/East Asia-Pacific pattern (PJ/EAP). The fitted EHE frequency based on the atmospheric factors (POL, NAO and PJ/EAP) can explain the interannual variation in the regionally averaged EHE frequency by 33.8%. Furthermore, three anomalous sea surface temperature (SST) patterns over the North Atlantic-Mediterranean Sea region and around the Maritime Continent are associated with the two EHE modes by intensifying the pronounced atmospheric teleconnections. Analysis on the simulation of five models in the Atmospheric Model Intercomparison Project experiment further confirms the impact of the pronounced SST patterns on the POL, NAO and PJ/EAP. In addition, NA EHE frequency experienced a significant interdecadal increase around the mid-1990s, which could be associated with the phase shift of the Atlantic Multidecadal Oscillation and long-term global warming trend.

Extremely thermophilic endospores germinate and metabolise organic carbon in sediments heated to above 80°C

Endospores of thermophilic bacteria are widespread in cold seabed environments where they remain dormant during initial burial in accumulating sediments. The temperature increase during sedimentation can be simulated in experimental heating of sediments, resulting in the temperature-dependent activation of different endospore populations from the microbial seed bank. Here we investigated the response of endospore populations to heating at extreme high temperature (80– 99°C). Metabolites for germination and organic matter degradation (dipicolinic acid and organic acids) revealed both endospore germination and subsequent metabolism at ≥80°C. Endospore-forming Firmicutes with the genomic potential for organic carbon and nitrogen transformation were recovered by genome-resolved metagenomics. Genomes from Symbiobacteriales, Thermosediminibacteriales, Moorellales and Calditerricolales encode multiple mechanisms for high temperature degradation of sedimentary organic carbon and features of necromass that accumulate during sediment burial including saccharides, amino and nucleic acids. The results provide insight into the metabolism of novel carbon cycling microorganisms activated at high temperature, and suggest that extremely thermophilic Firmicutes dispersed in the ocean are poised to germinate in response to sediment heating during burial and transform a wide range of organic substrates.

Evolution, Transport Characteristics, and Potential Source Regions of PM2.5 and O3 Pollution in a Coastal City of China during 2015–2020

The evolution, transport characteristics, and potential source regions of PM2.5 and O3 were investigated from 1 January 2015 to 31 December 2020 in the coastal city of Nantong. The annual mean PM2.5 concentration declined obviously over the entire study period, and was 34.7 μg/m3 in 2020. O3 had a relatively smooth decreasing trend, but rebounded greatly during 2017 when the most frequent extreme high-temperature events occurred. Similar trends were observed for PM2.5 and O3 polluted hours. No PM2.5-O3 complex air pollution happened in 2019 and 2020, likely suggesting the preliminary results from the implementation of emission controls. Notable differences in transport pathways and frequencies were observed from the backward trajectory clusters in four seasons in Nantong. Clusters with the largest percentage of polluted PM2.5 and O3 trajectories were transported mostly over short distances rather than long distances. Analysis involving the potential source contribution function (PSCF) and concentration weighted trajectory (CWT) showed that PM2.5 polluted sources were from the adjacent western and northwestern provinces, whereas the influence of eastern marine sources was relatively small. O3 had a greatly different spatial distribution of polluted source regions from PM2.5, mostly covering the North China Plain, the Bohai Sea, and the Yellow Sea.

Comparison of Atmospheric Circulation Anomalies between Dry and Wet Extreme High-Temperature Days in the Middle and Lower Reaches of the Yellow River

Many previous studies have reported that atmospheric circulation anomalies are generally the direct cause of extreme high-temperature (EHT). However, the atmospheric circulation anomalies of EHT days with different humidity and the differences between them are less often discussed, while humidity plays an important role in how people feel in a high-temperature environment. Therefore, this study uses 1961–2016 CN05.1 daily observational data and NCEP/NCAR reanalysis data to classify summer EHT days in China into dry and wet. Furthermore, we investigate the atmospheric circulation anomalies associated with the dry and wet EHT days in the middle and lower reaches of the Yellow River (MLRYR). The results reveal that dry EHT days are likely to be caused by adiabatic heating from anomalous subsidence, while wet EHT days are more likely caused by the low-latitude water vapor and heat anomalies brought by the Western Pacific Subtropical High (WPSH). This may be due to a remarkable westward/southward/narrowed extension of the Continental High (CH)/WPSH/South Asian High (SAH) accompanied by an occurrence of dry EHT day. The opposite pattern is observed for wet EHT days. Moreover, a wave train like the Silk Road pattern from the midlatitudes could affect the dry EHT days, while wet EHT days are more likely to be affected by a wave train from high latitudes. Knowing the specific characteristics of dry and wet EHT days and their associated atmospheric circulations could offer new insights into disaster risk prevention and reduction.