scholarly journals Review for ‘Quantifying the impact of synoptic weather types and patterns on energy fluxes of a marginal snowpack’, Schwatz et al. 2020

2020 ◽  
Author(s):  
Anonymous
Keyword(s):  
Energy Fluxes ◽  
Weather Types ◽  
Synoptic Weather ◽  
The Impact

scholarly journals Quantifying the impact of synoptic weather types and patterns on energy fluxes of a marginal snowpack

2020 ◽  
Vol 14 (8) ◽  
pp. 2755-2774
Author(s):  
Andrew J. Schwartz ◽  
Hamish A. McGowan ◽  
Alison Theobald ◽  
Nik Callow
Keyword(s):  
Energy Flux ◽  
Sensible Heat Flux ◽  
Shortwave Radiation ◽  
Positive Energy ◽  
Energy Fluxes ◽  
Weather Types ◽  
Synoptic Type ◽  
Synoptic Weather ◽  
Australian Alps ◽  
The Impact

Abstract. Synoptic weather patterns are investigated for their impact on energy fluxes driving melt of a marginal snowpack in the Snowy Mountains, southeast Australia. K-means clustering applied to ECMWF ERA-Interim data identified common synoptic types and patterns that were then associated with in situ snowpack energy flux measurements. The analysis showed that the largest contribution of energy to the snowpack occurred immediately prior to the passage of cold fronts through increased sensible heat flux as a result of warm air advection (WAA) ahead of the front. Shortwave radiation was found to be the dominant control on positive energy fluxes when individual synoptic weather types were examined. As a result, cloud cover related to each synoptic type was shown to be highly influential on the energy fluxes to the snowpack through its reduction of shortwave radiation and reflection/emission of longwave fluxes. As single-site energy balance measurements of the snowpack were used for this study, caution should be exercised before applying the results to the broader Australian Alps region. However, this research is an important step towards understanding changes in surface energy flux as a result of shifts to the global atmospheric circulation as anthropogenic climate change continues to impact marginal winter snowpacks.

scholarly journals Quantifying the impact of synoptic weather types and patterns on energy fluxes of a marginal snowpack

2020 ◽  
Author(s):  
Andrew Jonathan Schwartz ◽  
Hamish Andrew McGowan ◽  
Alison Theobald ◽  
Nik Callow
Keyword(s):  
Energy Flux ◽  
Sensible Heat Flux ◽  
Shortwave Radiation ◽  
Positive Energy ◽  
Energy Fluxes ◽  
Weather Types ◽  
Synoptic Type ◽  
Surface Energy Flux ◽  
Synoptic Weather ◽  
The Impact

Abstract. Synoptic weather patterns are investigated for their impact on energy fluxes driving melt of a marginal snowpack in the Snowy Mountains, southeast Australia. K-means clustering applied to ECMWF ERA-Interim data identified common synoptic types and patterns that were then associated with in-situ snowpack energy flux measurements. The analysis showed that the largest contribution of energy to the snowpack occurred immediately prior to the passage of cold fronts through increased sensible heat flux as a result of warm air advection (WAA) ahead of the front. Shortwave radiation was found to be the dominant control on positive energy fluxes when individual synoptic weather types were examined. As a result, cloud cover related to each synoptic type was shown to be highly influential on the energy fluxes to the snowpack through its reduction of shortwave radiation and reflection/emission of longwave fluxes. This research is an important step towards understanding changes in surface energy flux as a result of shifts to the global atmospheric circulation as anthropogenic climate change continues to impact marginal winter snowpacks.

scholarly journals Quantifying the impact of synoptic weather types, patterns, and trends on energy fluxes of a marginal snowpack

2019 ◽  
Author(s):  
Andrew Schwartz ◽  
Hamish McGowan ◽  
Alison Theobald ◽  
Nik Callow
Keyword(s):  
Energy Flux ◽  
Southern Oscillation ◽  
Sensible Heat Flux ◽  
Strong Relationship ◽  
Energy Fluxes ◽  
Weather Patterns ◽  
Surface Energy Flux ◽  
Cold Fronts ◽  
Synoptic Weather ◽  
The Impact

Abstract. Synoptic weather patterns and teleconnection relationships across a 39 year climatology are investigated for their impact on energy fluxes driving ablation of a marginal snowpack in the Snowy Mountains, southeast Australia. K-means clustering applied to ECMWF ERA-Interim data identified common synoptic types and patterns that were then associated with in-situ snowpack energy flux measurements. The analysis showed that the largest contribution of energy to the snowpack occurred immediately prior to the passage of cold fronts through increased sensible heat flux as a result of warm air advection (WAA) ahead of the front. Indian Ocean Dipole and Southern Oscillation Index phase combination had a strong relationship with energy flux, with eight of the ten highest annual snowpack energy fluxes occurring during a negative IOD phase and positive SOI phase. Overall, seasonal snowpack energy flux over the 39 year period had a decreasing trend that is likely due to a reduction in the number of precipitation generating cold fronts and associated preceding WAA ahead of precipitation. This research is an important step towards understanding changes in surface energy flux as a result of shifts to the global atmospheric circulation as anthropogenic climate change continues.

scholarly journals Local and synoptic meteorological influences on daily variability in summertime surface ozone in eastern China

2020 ◽  
Vol 20 (1) ◽  
pp. 203-222 ◽  
Author(s):  
Han Han ◽  
Jane Liu ◽  
Lei Shu ◽  
Tijian Wang ◽  
Huiling Yuan
Keyword(s):  
Surface Ozone ◽  
Eastern China ◽  
River Delta ◽  
Daily Maximum ◽  
Ozone Pollution ◽  
Study Region ◽  
Synoptic Weather ◽  
Daily Variability ◽  
Influential Variable ◽  
The Impact

Abstract. Ozone pollution in China is influenced by meteorological processes on multiple scales. Using regression analysis and weather classification, we statistically assess the impacts of local and synoptic meteorology on daily variability in surface ozone in eastern China in summer during 2013–2018. In this period, summertime surface ozone in eastern China (20–42∘ N, 110–130∘ E) is among the highest in the world, with regional means of 73.1 and 114.7 µg m−3, respectively, in daily mean and daily maximum 8 h average. Through developing a multiple linear regression (MLR) model driven by local and synoptic weather factors, we establish a quantitative linkage between the daily mean ozone concentrations and meteorology in the study region. The meteorology described by the MLR can explain ∼43 % of the daily variability in summertime surface ozone across eastern China. Among local meteorological factors, relative humidity is the most influential variable in the center and south of eastern China, including the Yangtze River Delta and the Pearl River Delta regions, while temperature is the most influential variable in the north, covering the Beijing–Tianjin–Hebei region. To further examine the synoptic influence of weather conditions explicitly, six predominant synoptic weather patterns (SWPs) over eastern China in summer are objectively identified using the self-organizing map clustering technique. The six SWPs are formed under the integral influence of the East Asian summer monsoon, the western Pacific subtropical high, the Meiyu front, and the typhoon activities. On average, regionally, two SWPs bring about positive ozone anomalies (1.1 µg m−3 or 1.7 % and 2.7 µg m−3 or 4.6 %), when eastern China is under a weak cyclone system or under the prevailing southerly wind. The impact of SWPs on the daily variability in surface ozone varies largely within eastern China. The maximum impact can reach ±8 µg m−3 or ±16 % of the daily mean in some areas. A combination of the regression and the clustering approaches suggests a strong performance of the MLR in predicting the sensitivity of surface ozone in eastern China to the variation of synoptic weather. Our assessment highlights the importance of meteorology in modulating ozone pollution over China.

scholarly journals Short-Term Associations of Fine Particulate Matter and Synoptic Weather Types with Cardiovascular Mortality: An Ecological Time-Series Study in Shanghai, China

2020 ◽  
Vol 17 (3) ◽  
pp. 1111 ◽  
Author(s):  
Qing Tian ◽  
Mei Li ◽  
Scott Montgomery ◽  
Bo Fang ◽  
Chunfang Wang ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Cardiovascular Mortality ◽  
Fine Particulate Matter ◽  
Weather Conditions ◽  
Cold Weather ◽  
Short Term ◽  
Weather Types ◽  
Synoptic Weather ◽  
Fine Particulate ◽  
Pm2.5 Concentration

Background: Exposures to both ambient fine particulate matter (PM2.5) and extreme weather conditions have been associated with cardiovascular disease (CVD) deaths in numerous epidemiologic studies. However, evidence on the associations with CVD deaths for interaction effects between PM2.5 and weather conditions is still limited. This study aimed to investigate associations of exposures to PM2.5 and weather conditions with cardiovascular mortality, and further to investigate the synergistic or antagonistic effects of ambient air pollutants and synoptic weather types (SWTs). Methods: Information on daily CVD deaths, air pollution, and meteorological conditions between 1 January 2012 and 31 December 2014 was obtained in Shanghai, China. Generalized additive models were used to assess the associations of daily PM2.5 concentrations and meteorological factors with CVD deaths. A 15-day lag analysis was conducted using a polynomial distributed lag model to access the lag patterns for associations with PM2.5. Results: During the study period, the total number of CVD deaths in Shanghai was 59,486, with a daily mean of 54.3 deaths. The average daily PM2.5 concentration was 55.0 µg/m3. Each 10 µg/m3 increase in PM2.5 concentration was associated with a 1.26% (95% confidence interval (CI): 0.40%, 2.12%) increase in CVD mortality. No SWT was statistically significantly associated with CVD deaths. For the interaction between PM2.5 and SWT, statistically significant interactions were found between PM2.5 and cold weather, with risk for PM2.5 in cold dry SWT decreasing by 1.47% (95% CI: 0.54%, 2.39%), and in cold humid SWT the risk decreased by 1.45% (95% CI: 0.52%, 2.36%). In the lag effect analysis, statistically significant positive associations were found for PM2.5 in the 1–3 lag days, while no statistically significant effects were found for other lag day periods. Conclusions: Exposure to PM2.5 was associated with short-term increased risk of cardiovascular deaths with some lag effects, while the cold weather may have an antagonistic effect with PM2.5. However, the ecological study design limited the possibility to identify a causal relationship, so prospective studies with individual level data are warranted.

Kawasaki disease in Spanish paediatric population and synoptic weather types: an observational study

2018 ◽  
Vol 38 (7) ◽  
pp. 1259-1266 ◽  
Author(s):  
Leyre Riancho-Zarrabeitia ◽  
Domingo F. Rasilla ◽  
Dominic Royé ◽  
Pablo Fdez-Arroyabe ◽  
Ana Santurtún
Keyword(s):  
Kawasaki Disease ◽  
Observational Study ◽  
Paediatric Population ◽  
Weather Types ◽  
Synoptic Weather

The Relation Between Cloudiness over the Greenland Icecap and Synoptic Weather Types 1 2

1960 ◽  
Vol 41 (2) ◽  
pp. 68-78
Author(s):  
Clarence A. Carpenter
Keyword(s):  
Cross Section ◽  
Cross Sections ◽  
Grid Point ◽  
Summer Season ◽  
Weather Data ◽  
Weather Types ◽  
Synoptic Weather ◽  
System Type

This paper is a summary of cloudiness over the Greenland icecap route from Sondrestrom Air Base, approximately 67N–51W, to Angmagssalik, approximately 65.5N–37.5W. Four types of synoptic systems were chosen and cloudiness summarized by types both annually and for the summer season. Total cloudiness annually and for the summer season without regard to synoptic types is also presented. Data for this paper consisted of 511 flight cross sections made by Scandinavian Airlines System flight crews in scheduled air service over the icecap route. It is presented in the form of a cross-section grid with isopleths showing the percentage of time cloudiness was observed at each grid point. These cross sections are of particular value in that they are the first source of systematic, observed weather data over this area. An attempt is made to explain icecap cloud distribution by correlation with system type in order to provide a practical forecasting aid for the Greenland air-route forecasters.

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