Dominant modes of interannual variability of extreme high‐temperature events in eastern China during summer and associated mechanisms

Extreme climate events frequently exert serious effects on terrestrial vegetation activity. However, these effects are still uncertain in widely distributed areas with different climate zones. Transect analysis is important to understand how terrestrial vegetation responds to climate change, especially extreme climate events, by substituting space for time. In this paper, seven extreme climate indices and the Normalized Difference Vegetation Index (NDVI) are employed to examine changes in the extreme climate events and vegetation activity. To reduce the uncertainty of the NDVI, two satellite-derived NDVI datasets, including the third generation Global Inventory Monitoring and Modeling System (GIMMS-3g) NDVI dataset and the NDVI from the National Oceanic and Atmospheric Administration (NOAA) satellites on Star Web Servers (SWS), were employed to capture changes in vegetation activity. The impacts of climate extremes on vegetation activity were then assessed over the period of 1982–2012 using the North–South Transect of Eastern China (NSTEC) as a case. The results show that vegetation activity was overall strengthened from 1982 to 2012 in the NSTEC. In addition, extreme high temperature events revealed an increased trend of approximately 5.15 days per decade, while a weakened trend (not significant) was found in extreme cold temperature events. The strengthened vegetation activities could be associated with enhanced extreme high temperature events and weakened extreme cold temperature events over the past decades in most of the NSTEC. Despite this, inversed changes were also found locally between vegetation activity and extreme climate events (e.g., in the Northeast Plain). These phenomena could be associated with differences in vegetation type, human activity, as well as the combined effects of the frequency and intensity of extreme climate events. This study highlights the importance of accounting for the vital roles of extreme climate effects on vegetation activity.

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

Journal of Climate ◽

10.1175/jcli-d-21-0431.1 ◽

2021 ◽

pp. 1-51

Keyword(s):

High Temperature ◽

Interannual Variability ◽

North Atlantic ◽

Wave Train ◽

Dipole Mode ◽

The North ◽

Atmospheric Wave ◽

Extreme High Temperature ◽

The Indian Ocean ◽

The North Atlantic

Abstract 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.

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

10.21203/rs.3.rs-1230879/v1 ◽

2022 ◽

Author(s):

Wei Jin ◽

Wei Zhang ◽

Jie Hu ◽

Jiazhen Chen ◽

Bin Weng ◽

...

Keyword(s):

Deep Learning ◽

High Temperature ◽

Language Processing ◽

Spatial Information ◽

Eastern China ◽

Extended Period ◽

Absolute Error ◽

Probabilistic Forecasting ◽

Prediction Probability ◽

Extreme High Temperature

Abstract 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.

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Response analysis of HTPB propellant under extreme high temperature conditions

IOP Conference Series Earth and Environmental Science ◽

10.1088/1755-1315/769/4/042057 ◽

2021 ◽

Vol 769 (4) ◽

pp. 042057

Author(s):

TianPeng Li ◽

Bang Lu ◽

ZhenTao An

Keyword(s):

High Temperature ◽

Response Analysis ◽

Temperature Conditions ◽

Extreme High Temperature ◽

Htpb Propellant

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Host choice, settling and folding leaf behaviors of the larval rice leaf folder under heat stress

Bulletin of Entomological Research ◽

10.1017/s0007485316000584 ◽

2016 ◽

Vol 106 (6) ◽

pp. 809-817 ◽

Cited By ~ 6

Author(s):

M.A. Bodlah ◽

A.-X. Zhu ◽

X.-D. Liu

Keyword(s):

Heat Stress ◽

High Temperature ◽

Host Choice ◽

Cnaphalocrocis Medinalis ◽

Behavioral Traits ◽

The Third ◽

Rice Leaf ◽

Rice Leaf Folder ◽

Extreme High Temperature ◽

Third Instar Larvae

AbstractExtreme high-temperature events are the key factor to determine population dynamics of the rice leaf folder,Cnaphalocrocis medinalis(Guenée), in summer. Although we know that adult of this insect can migrate to avoid heat stress, the behavioral response of larva to high temperature is still unclear. Therefore, impacts of high temperature on behavioral traits ofC. medinalisincluding host choice, settling and folding leaf were observed. The results revealed that these behavioral traits were clearly influenced by high temperature. The larvae preferred maize leaves rather than rice and wheat at normal temperature of 27°C, but larvae experienced a higher temperature of 37 or 40°C for 4 h preferred rice leaves rather than maize and wheat. Capacity of young larvae to find host leaves or settle on the upper surface of leaves significantly reduced when they were treated by high temperature. High temperature of 40°C reduced the leaf-folding capacity of the third instar larvae, but no effects were observed on the fourth and fifth instar larvae. Short-term heat acclimation could not improve the capacity of the third instar larvae to make leaf fold under 40°C.

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Different responses of scleractinian coral Acropora pruinosa from Weizhou Island during extreme high temperature events

Coral Reefs ◽

10.1007/s00338-021-02182-y ◽

2021 ◽

Author(s):

Xiaopeng Yu ◽

Kefu Yu ◽

Biao Chen ◽

Zhiheng Liao ◽

Jiayuan Liang ◽

...

Keyword(s):

High Temperature ◽

Scleractinian Coral ◽

Extreme High Temperature

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Review of “FTIR time series of tropospheric HCN in eastern China: seasonality, interannual variability and source attribution” by Sun et al.

10.5194/acp-2019-736-rc2 ◽

2020 ◽

Author(s):

Anonymous

Keyword(s):

Time Series ◽

Interannual Variability ◽

Eastern China ◽

Source Attribution

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

Atmosphere ◽

10.3390/atmos12101265 ◽

2021 ◽

Vol 12 (10) ◽

pp. 1265

Author(s):

Hangcheng Ge ◽

Gang Zeng ◽

Vedaste Iyakaremye ◽

Xiaoye Yang ◽

Zongming Wang

Keyword(s):

High Temperature ◽

Atmospheric Circulation ◽

Yellow River ◽

Wave Train ◽

The Yellow River ◽

South Asian High ◽

Opposite Pattern ◽

Extreme High Temperature ◽

Circulation Anomalies ◽

Atmospheric Circulation Anomalies

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.

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