scholarly journals Dominant climate drivers of wintertime severe particulate pollution in North China

2021 ◽  
Author(s):  
Jiandong Li ◽  
Xin Hao ◽  
Hong Liao ◽  
Yuhang Wang ◽  
Wenju Cai ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
North China ◽  
Climate Models ◽  
Lower Troposphere ◽  
Temperature Inversion ◽  
Teleconnection Pattern ◽  
Arctic Sea Ice ◽  
Sea Surface ◽  
Particulate Pollution

Abstract Severe particulate pollution days (SPPDs, characterized by a daily mean PM2.5 concentration exceeding 150 μg m-3), which are extremely harmful to human health and the environment, occurred frequently in North China during the boreal winters of 2013–2019. SPPDs generally occur under conducive weather patterns (CWPs) characterized by a weakened East Asian Trough in the mid-troposphere, reduced winter northerlies in the lower troposphere, and a temperature inversion at the surface. The occurrence of CWPs has been attributed to variations in numerous climate factors (e.g., Arctic sea ice cover, sea surface temperature, and atmospheric teleconnections), but the dominant climate drivers remain inconclusive. Here, we show that the East Atlantic-West Russia (EA/WR) teleconnection pattern and the Victoria Mode (VM) of sea surface temperature anomalies are the first and second dominant climate drivers, respectively, leading to CWPs in North China through the zonal and meridional propagations of Rossby waves and explaining 36.3% and 18.5%, respectively, of the observed wintertime SPPDs in Beijing-Tianjin-Hebei. Our results suggest that, with the help of seasonal forecast from climate models, the indices of the EA/WR and VM can be used to predict wintertime SPPDs over Beijing-Tianjin-Hebei.

scholarly journals Increasing persistent haze in Beijing: potential impacts of weakening East Asian winter monsoons associated with northwestern Pacific sea surface temperature trends

2018 ◽  
Vol 18 (5) ◽  
pp. 3173-3183 ◽  
Author(s):  
Lin Pei ◽  
Zhongwei Yan ◽  
Zhaobin Sun ◽  
Shiguang Miao ◽  
Yao Yao
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Large Scale ◽  
North China ◽  
East Asian ◽  
Lower Troposphere ◽  
Sea Surface ◽  
Pollutant Emissions ◽  
Northwestern Pacific ◽  
Positive Trend

Abstract. Over the past decades, Beijing, the capital city of China, has encountered increasingly frequent persistent haze events (PHE). While the increased pollutant emissions are considered as the most important reason, changes in regional atmospheric circulations associated with large-scale climate warming also play a role. In this study, we find a significant positive trend of PHE in Beijing for the winters from 1980 to 2016 based on updated daily observations. This trend is closely related to an increasing frequency of extreme anomalous southerly episodes in North China, a weakened East Asian trough in the mid-troposphere and a northward shift of the East Asian jet stream in the upper troposphere. These conditions together depict a weakened East Asian winter monsoon (EAWM) system, which is then found to be associated with an anomalous warm, high-pressure system in the middle–lower troposphere over the northwestern Pacific. A practical EAWM index is defined as the seasonal meridional wind anomaly at 850 hPa in winter over North China. Over the period 1900–2016, this EAWM index is positively correlated with the sea surface temperature anomalies over the northwestern Pacific, which indicates a wavy positive trend, with an enhanced positive phase since the mid-1980s. Our results suggest an observation-based mechanism linking the increase in PHE in Beijing with large-scale climatic warming through changes in the typical regional atmospheric circulation.

scholarly journals CMIP6 model-based analog forecasting for the seasonal prediction of sea surface temperature in the offshore area of China

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Weiying Peng ◽  
Quanliang Chen ◽  
Shijie Zhou ◽  
Ping Huang
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Climate Models ◽  
Global Climate Models ◽  
Sea Surface ◽  
Seasonal Forecasts ◽  
Initial State ◽  
Initial Field ◽  
Offshore Area ◽  
Model Based

AbstractSeasonal forecasts at lead times of 1–12 months for sea surface temperature (SST) anomalies (SSTAs) in the offshore area of China are a considerable challenge for climate prediction in China. Previous research suggests that a model-based analog forecasting (MAF) method based on the simulations of coupled global climate models provide skillful climate forecasts of tropical Indo-Pacific SSTAs. This MAF method selects the model-simulated cases close to the observed initial state as a model-analog ensemble, and then uses the subsequent evolution of the SSTA to generate the forecasts. In this study, the MAF method is applied to the offshore area of China (0°–45°N, 105°–135°E) based on the simulations of 23 models from phase 6 of the Coupled Model Intercomparison Project (CMIP6) for the period 1981–2010. By optimizing the key factors in the MAF method, we suggest that the optimal initial field for the analog criteria should be concentrated in the western North Pacific. The multi-model ensemble of the optimized MAF prediction using these 23 CMIP6 models shows anomaly correlation coefficients exceeding 0.6 at the 3-month lead time, which is much improved relative to previous SST-initialized hindcasts and appears practical for operational forecasting.

scholarly journals Interannual Variability and Trends in Sea Surface Temperature, Lower and Middle Atmosphere Temperature at Different Latitudes for 1980–2019

Atmosphere ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 454
Author(s):  
Andrew R. Jakovlev ◽  
Sergei P. Smyshlyaev ◽  
Vener Y. Galin
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Lower Stratosphere ◽  
Middle Atmosphere ◽  
Southern Oscillation ◽  
Lower Troposphere ◽  
Reanalysis Data ◽  
Sea Surface ◽  
The Arctic ◽  
The Impact

The influence of sea-surface temperature (SST) on the lower troposphere and lower stratosphere temperature in the tropical, middle, and polar latitudes is studied for 1980–2019 based on the MERRA2, ERA5, and Met Office reanalysis data, and numerical modeling with a chemistry-climate model (CCM) of the lower and middle atmosphere. The variability of SST is analyzed according to Met Office and ERA5 data, while the variability of atmospheric temperature is investigated according to MERRA2 and ERA5 data. Analysis of sea surface temperature trends based on reanalysis data revealed that a significant positive SST trend of about 0.1 degrees per decade is observed over the globe. In the middle latitudes of the Northern Hemisphere, the trend (about 0.2 degrees per decade) is 2 times higher than the global average, and 5 times higher than in the Southern Hemisphere (about 0.04 degrees per decade). At polar latitudes, opposite SST trends are observed in the Arctic (positive) and Antarctic (negative). The impact of the El Niño Southern Oscillation phenomenon on the temperature of the lower and middle atmosphere in the middle and polar latitudes of the Northern and Southern Hemispheres is discussed. To assess the relative influence of SST, CO2, and other greenhouse gases’ variability on the temperature of the lower troposphere and lower stratosphere, numerical calculations with a CCM were performed for several scenarios of accounting for the SST and carbon dioxide variability. The results of numerical experiments with a CCM demonstrated that the influence of SST prevails in the troposphere, while for the stratosphere, an increase in the CO2 content plays the most important role.

scholarly journals On the Interpretation of the North Atlantic Averaged Sea Surface Temperature

2020 ◽  
Vol 33 (14) ◽  
pp. 6025-6045
Author(s):  
Jing Sun ◽  
Mojib Latif ◽  
Wonsun Park ◽  
Taewook Park
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
North Atlantic ◽  
Climate Models ◽  
Ocean Dynamics ◽  
Sea Surface ◽  
The North ◽  
Sst Variability ◽  
The North Atlantic ◽  
Different Time Scales

AbstractThe North Atlantic (NA) basin-averaged sea surface temperature (NASST) is often used as an index to study climate variability in the NA sector. However, there is still some debate on what drives it. Based on observations and climate models, an analysis of the different influences on the NASST index and its low-pass filtered version, the Atlantic multidecadal oscillation (AMO) index, is provided. In particular, the relationships of the two indices with some of its mechanistic drivers including the Atlantic meridional overturning circulation (AMOC) are investigated. In observations, the NASST index accounts for significant SST variability over the tropical and subpolar NA. The NASST index is shown to lump together SST variability originating from different mechanisms operating on different time scales. The AMO index emphasizes the subpolar SST variability. In the climate models, the SST-anomaly pattern associated with the NASST index is similar. The AMO index, however, only represents pronounced SST variability over the extratropical NA, and this variability is significantly linked to the AMOC. There is a sensitivity of this linkage to the cold NA SST bias observed in many climate models. Models suffering from a large cold bias exhibit a relatively weak linkage between the AMOC and AMO and vice versa. Finally, the basin-averaged SST in its unfiltered form, which has been used to question a strong influence of ocean dynamics on NA SST variability, mixes together multiple types of variability occurring on different time scales and therefore underemphasizes the role of ocean dynamics in the multidecadal variability of NA SSTs.

scholarly journals Do Climate Models Capture the Tropical Influences on North Pacific Sea Surface Temperature Variability?

2011 ◽  
Vol 24 (23) ◽  
pp. 6203-6209 ◽  
Author(s):  
Fabian Lienert ◽  
John C. Fyfe ◽  
William J. Merryfield
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
North Pacific ◽  
Climate Models ◽  
Southern Oscillation ◽  
Temperature Variability ◽  
Sea Surface ◽  
Model Errors ◽  
The North ◽  
The North Pacific

Abstract This study evaluates the ability of global climate models to reproduce observed tropical influences on North Pacific Ocean sea surface temperature variability. In an ensemble of climate models, the study finds that the simulated North Pacific response to El Niño–Southern Oscillation (ENSO) forcing is systematically delayed relative to the observed response because of winter and spring mixed layers in the North Pacific that are too deep and air–sea feedbacks that are too weak. Model biases in mixed layer depth and air–sea feedbacks are also associated with a model mean ENSO-related signal in the North Pacific whose amplitude is overestimated by about 30%. The study also shows that simulated North Pacific variability has more power at lower frequencies than is observed because of model errors originating in the tropics and extratropics. Implications of these results for predictions on seasonal, decadal, and longer time scales are discussed.

South Atlantic sea surface temperature anomalies and air-sea interactions: stochastic models

1994 ◽  
Vol 12 (9) ◽  
pp. 903-909
Author(s):  
S. G. Dobrovolski
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Climate Models ◽  
South Atlantic ◽  
Entropy Method ◽  
Sea Surface ◽  
Temperature Anomalies ◽  
Leading Role ◽  
Sea Surface Temperature Anomalies ◽  
Dynamic Stochastic

Abstract. Data on the South Atlantic monthly sea surface temperature anomalies (SSTA) are analysed using the maximum-entropy method. It is shown that the Markov first-order process can describe, to a first approximation, SSTA series. The region of maximum SSTA values coincides with the zone of maximum residual white noise values (sub-Antarctic hydrological front). The theory of dynamic-stochastic climate models is applied to estimate the variability of South Atlantic SSTA and air-sea interactions. The Adem model is used as a deterministic block of the dynamic-stochastic model. Experiments show satisfactorily the SSTA intensification in the sub-Antarctic front zone, with appropriate standard deviations, and demonstrate the leading role of the abnormal drift currents in these processes.

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