The impact of large-scale atmospheric patterns on Heatwaves in summer Northern China based on Self-Organizing Map

2020 ◽  
Author(s):  
Chen Shi ◽  
Wang Kaicun ◽  
Zhou Chunlüe
Keyword(s):  
Atmospheric Circulation ◽  
Large Scale ◽  
Stepwise Regression ◽  
Northern China ◽  
Subtropical High ◽  
Self Organizing Map ◽  
Okhotsk Sea ◽  
Circulation Patterns ◽  
The Impact ◽  
Self Organizing

<p>Heatwave is affected by large-scale atmospheric circulation on temperature-related climates in the context of global warming. Recently Northern China have experienced an increase in heatwaves which is partly due to the atmospheric circulation. This study aims to address the influence clearly. Northern China heatwaves are computed on excess hot factor (EHF) and the five EHF indexes are studied afterwards to get a picture of heatwaves in summer Northern China. China circulation patterns are classified into nine typical circulation patterns on self-organizing map (SOM) which then can be described quantitatively by pattern factors: frequency, persistence and maximum persistence. Pearson correlation analysis and stepwise regression analysis are applied for exploring the impact. Results show the spatial pattern of the times of individual heatwave event (HWN) and the days of the longest heatwave duration (HWD) are high value everywhere in Northern China. The overall EHF indexes all rising in time series (P<0.05) and the regional heatwave occurrence have trends of 0.79 day per year (P<0.05). However, the factors of the patterns show inconspicuous tendency. Two patterns with significant correlations (P<0.05) are proved to be suggestive of Okhotsk Sea high and West Pacific Subtropical High. It declares that the Okhotsk Sea high favors Northern China heatwave occurrence rather than subtropical high: the warm center over Okhotsk Sea transfer heat upper and west, generating the high temperature and persist high pressure system, causing heatwave happening in summer Northern China. The two related atmospheric circulation patterns explain 38% of the heatwave occurrence based on stepwise regression model, the Okhotsk Sea high gets the coefficient of 0.443 and the subtropical high is -0.347.  </p>

scholarly journals Temporal Variability of Drought in Nine Agricultural Regions of China and the Influence of Atmospheric Circulation

Atmosphere ◽  
2020 ◽  
Vol 11 (9) ◽  
pp. 990
Author(s):  
Haowei Sun ◽  
Haiying Hu ◽  
Zhaoli Wang ◽  
Chengguang Lai
Keyword(s):  
Atmospheric Circulation ◽  
Southern China ◽  
Northern China ◽  
Chinese Mainland ◽  
Subtropical High ◽  
Trade Wind ◽  
Severe Drought ◽  
The Chinese Mainland ◽  
Agricultural Regions ◽  
The Impact

In recent decades, the severe drought across agricultural regions of China has had significant impact on agriculture. The standardized precipitation evapotranspiration index (SPEI) has been widely used for drought analyses; however, SPEI is prone to be affected by potential evapotranspiration (PET). We thus examined the correlations between soil moisture anomalies and the SPEI calculated by the Thornthwaite, Hargreaves, and Penman–Monteith (PM) equations to select the most suitable for drought research. Additionally, the Mann–Kendall and wavelet analysis were used to investigate drought trends and to analyze and the impact of atmospheric circulation on drought in China from 1961 to 2018. The results showed that (1) PET obtained from the PM equation is the most suitable for SPEI calculation; (2) there were significant wetting trends in Northern China and the whole Chinese mainland and most of the wetting mutation points occurred in the 1970s and 1980s and the significant inter-annual oscillations period in the Chinese mainland was 2–4 years; (3) the Chinese mainland and Northern China are strongly influenced by West Pacific Trade Wind, while Western Pacific Subtropical High Intensity and Pacific Subtropical High Area have primary impact on Southern China.

The impact of atmospheric circulation on wind energy resource using self-organizing maps

2021 ◽  
Author(s):  
Kostas Philippopoulos ◽  
Chris G. Tzanis
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Atmospheric Circulation ◽  
Large Scale ◽  
Synoptic Climatology ◽  
Energy Potential ◽  
Self Organizing Maps ◽  
Wind Energy Potential ◽  
The Impact ◽  
Self Organizing

<p>The sensitivity of wind to the Earth’s energy budget and the changes it causes in the climate system has a significant impact on the wind energy sector. The scope of this work is to examine the association of atmospheric circulation with the wind speed distribution characteristics on different timescales over Greece. Emphasis is given to the effect of specific regimes on the wind speed distributions at different locations. The work is based on using synoptic climatology as a tool for providing information regarding wind variability. This approach allows a more detailed description of the effect of changes in large-scale atmospheric circulation on wind energy potential. The atmospheric classification methodology, upon the selection of relevant atmospheric variables and domains, includes a Principal Components Analysis for dimension reduction purposes and subsequently, the classification is performed using an artificial neural network and in particular self-organizing maps. In the resulting feature map, the neighboring nodes are inter-connected and each one is associated with the composites of the selected large-scale variables. Upon the assignment and the characterization of each day in one of the resulting patterns, a daily catalog is constructed and frequency analysis is performed. In the context of estimating wind energy potential variability for each atmospheric pattern, the fit of multiple probability functions to the surface wind speed frequency distributions is performed. The most suitable function is selected based on a set of difference and correlation statistical measures, along with the use of goodness-of-fit statistical tests. The study employs the ERA5 reanalysis dataset with a 0.25° spatial resolution from 1979/01/01 up to 2019/12/31 and the wind field data are extracted at the 10m and the 100m levels. The approach could be valuable to the wind energy industry and can provide the required scientific understanding for the optimal siting of Wind Energy Conversion Systems considering the atmospheric circulation and the electricity interconnection infrastructure in the region. Considering the emerging issue of energy safety, accurate wind energy production estimates can contribute towards the establishment of wind as the primary energy source and in meeting the increasing energy demand.</p>

scholarly journals Three distinct atmospheric circulation patterns associated with high temperature extremes in South Korea

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Han-Kyoung Kim ◽  
Byung-Kwon Moon ◽  
Maeng-Ki Kim ◽  
Jong-Yeon Park ◽  
Yu-Kyung Hyun
Keyword(s):  
High Temperature ◽  
South Korea ◽  
Atmospheric Circulation ◽  
Large Scale ◽  
Negative Impact ◽  
Wave Train ◽  
Self Organizing Map ◽  
Atmospheric Circulation Patterns ◽  
Circulation Patterns ◽  
Extreme High Temperature

AbstractThe negative impact of extreme high-temperature days (EHDs) on people’s livelihood has increased over the past decades. Therefore, an improved understanding of the fundamental mechanisms of EHDs is imperative to mitigate this impact. Herein, we classify the large-scale atmospheric circulation patterns associated with EHDs that occurred in South Korea from 1982 to 2018 using a self-organizing map (SOM) and investigate the dynamic mechanism for each cluster pattern through composite analysis. A common feature of all SOM clusters is the positive geopotential height (GPH) anomaly over the Korean Peninsula, which provides favorable conditions for EHDs through adiabatic warming caused by anomalous downward motion. Results show that Cluster 1 (C1) is related to the eastward-propagating wave train in the mid-latitude Northern Hemisphere, while Cluster 2 (C2) and 3 (C3) are influenced by a northward-propagating wave train forced by enhanced convection in the subtropical western North Pacific (WNP). Compared to C2, C3 exhibits strong and eastward-extended enhanced convection over the subtropical WNP, which generates an anomalous high-pressure system over the southern part of the Kamchatka Peninsula, reinforcing EHDs via atmospheric blocking. Our results can contribute to the understanding of East Asia climate variability because wave trains influence the climate dynamics of this region.

scholarly journals Geospatial Analysis of Extreme Weather Events in Nigeria (1985–2015) Using Self-Organizing Maps

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Adeoluwa Akande ◽  
Ana Cristina Costa ◽  
Jorge Mateu ◽  
Roberto Henriques
Keyword(s):  
Extreme Precipitation ◽  
Large Scale ◽  
Northern Region ◽  
Extreme Weather Events ◽  
Self Organizing Map ◽  
Spatial And Temporal Patterns ◽  
Self Organizing Maps ◽  
The North ◽  
Precipitation Regimes ◽  
Self Organizing

The explosion of data in the information age has provided an opportunity to explore the possibility of characterizing the climate patterns using data mining techniques. Nigeria has a unique tropical climate with two precipitation regimes: low precipitation in the north leading to aridity and desertification and high precipitation in parts of the southwest and southeast leading to large scale flooding. In this research, four indices have been used to characterize the intensity, frequency, and amount of rainfall over Nigeria. A type of Artificial Neural Network called the self-organizing map has been used to reduce the multiplicity of dimensions and produce four unique zones characterizing extreme precipitation conditions in Nigeria. This approach allowed for the assessment of spatial and temporal patterns in extreme precipitation in the last three decades. Precipitation properties in each cluster are discussed. The cluster closest to the Atlantic has high values of precipitation intensity, frequency, and duration, whereas the cluster closest to the Sahara Desert has low values. A significant increasing trend has been observed in the frequency of rainy days at the center of the northern region of Nigeria.

Analysing the Residential Market in Trójmiasto Using Self-Organizing Map

2021 ◽  
Author(s):  
Olgun Aydin ◽  
Krystian Zielinski
Keyword(s):  
Multidimensional Data ◽  
Residential Property ◽  
Self Organizing Map ◽  
Property Market ◽  
Residential Properties ◽  
Price Trends ◽  
Residential Market ◽  
Key Aspects ◽  
The Impact ◽  
Self Organizing

Although the residential property market has strong connections with various sectors, such as construction, logistics, and investment, it works through different dynamics than do other markets; thus, it can be analysed from various perspectives. Researchers and investors are mostly interested in price trends, the impact of external factors on residential property prices, and price prediction. When analysing price trends, it is beneficial to consider multidimensional data that contain attributes of residential properties, such as number of rooms, number of bathrooms, floor number, total floors, and size, as well as proximity to public transport, shops, and banks. Knowing a neighbourhood's key aspects and properties could help investors, real estate development companies, and people looking to buy or rent properties to investigate similar neighbourhoods that may have unusual price trends. In this study, the self-organizing map method was applied to residential property listings in the Trójmiasto area of Poland, where the residential market has recently been quite active. The study aims to group together neighbourhoods and subregions to find similarities between them in terms of price trends and stock. Moreover, this study presents relationships between attributes of residential properties.

Spark-GHSOM: Growing Hierarchical Self-Organizing Map for large scale mixed attribute datasets

2019 ◽  
Vol 496 ◽  
pp. 572-591 ◽  
Author(s):  
Ameya Malondkar ◽  
Roberto Corizzo ◽  
Iluju Kiringa ◽  
Michelangelo Ceci ◽  
Nathalie Japkowicz
Keyword(s):  
Large Scale ◽  
Self Organizing Map ◽  
Self Organizing

scholarly journals Impact of climate change on groundwater point discharge: backflooding of karstic springs (Loiret, France)

2011 ◽  
Vol 8 (2) ◽  
pp. 2235-2262
Author(s):  
E. Joigneaux ◽  
P. Albéric ◽  
H. Pauwels ◽  
C. Pagé ◽  
L. Terray ◽  
...  
Keyword(s):  
Climate Change ◽  
Surface Water ◽  
Groundwater Quality ◽  
Atmospheric Circulation ◽  
Large Scale ◽  
Weather Type ◽  
Future Climate Change ◽  
Impact Of Climate Change ◽  
The Impact ◽  
Large Scale Atmospheric Circulation

Abstract. Under certain hydrological conditions it is possible for spring flow in karst systems to be reversed. When this occurs, the resulting invasion by surface water, i.e. the backflooding, represents a serious threat to groundwater quality because the surface water could well be contaminated. Here we examine the possible impact of future climate change on the occurrences of backflooding in a specific karst system, having first established the occurrence of such events in the selected study area over the past 40 yr. It would appear that backflooding has been more frequent since the 1980s, and that it is apparently linked to river flow variability on the pluri-annual scale. The avenue that we adopt here for studying recent and future variations of these events is based on a downscaling algorithm relating large-scale atmospheric circulation to local precipitation spatial patterns. The large-scale atmospheric circulation is viewed as a set of quasi-stationary and recurrent states, called weather types, and its variability as the transition between them. Based on a set of climate model projections, simulated changes in weather-type occurrence for the end of the century suggests that backflooding events can be expected to decrease in 2075–2099. If such is the case, then the potential risk for groundwater quality in the area will be greatly reduced compared to the current situation. Finally, our results also show the potential interest of the weather-type based downscaling approach for examining the impact of climate change on hydrological systems.

scholarly journals Impact of COVID-19 Lockdown and Atmospheric Circulation on the Air Quality in Wuhan During Early 2020

2021 ◽  
Vol 299 ◽  
pp. 02011
Author(s):  
Youyong Xie ◽  
Xiefei Zhi
Keyword(s):  
Air Quality ◽  
Atmospheric Circulation ◽  
Air Pollutants ◽  
General Circulation ◽  
Circulation Pattern ◽  
Atmospheric Circulation Patterns ◽  
Atmospheric General Circulation ◽  
Circulation Patterns ◽  
The Impact

Previous studies indicated that the air quality was improved in Wuhan during COVID-19 lockdown. However, the impact of atmospheric general circulation on the changes of air quality has not been taken into account. The present study aims to discuss the improvement of air quality in Wuhan and its possible reasons during COVID-19 lockdown. The results showed that all air pollutants except O3 decreased in Wuhan during early 2020. The occurrence days of A, C, W and NW types’ circulation pattern during early 2020 are more than those during the same period of 1979-2020. The occurrence days of SW type’s circulation pattern is slightly less than those during early 1979-2020. With more occurrence days of these dominant atmospheric circulation patterns, the number of polluted days could rise in Wuhan during early 2020. Nevertheless, this scenario didn’t occur. The COVID-19 lockdown did improve the air quality in Wuhan during early 2020.

scholarly journals The Role of Synoptic Cyclones for the Formation of Arctic Summer Circulation Patterns as Clustered by Self-Organizing Maps

Atmosphere ◽  
2019 ◽  
Vol 10 (8) ◽  
pp. 474 ◽  
Author(s):  
Min-Hee Lee ◽  
Joo-Hong Kim
Keyword(s):  
Arctic Ocean ◽  
Large Scale ◽  
The Arctic ◽  
Cyclone Activity ◽  
Summer Circulation ◽  
Self Organizing Maps ◽  
Weather Patterns ◽  
Atmospheric Circulation Patterns ◽  
Circulation Patterns ◽  
Self Organizing

Contribution of extra-tropical synoptic cyclones to the formation of mean summer atmospheric circulation patterns in the Arctic domain (≥60° N) was investigated by clustering dominant Arctic circulation patterns based on daily mean sea-level pressure using self-organizing maps (SOMs). Three SOM patterns were identified; one pattern had prevalent low-pressure anomalies in the Arctic Circle (SOM1), while two exhibited opposite dipoles with primary high-pressure anomalies covering the Arctic Ocean (SOM2 and SOM3). The time series of their occurrence frequencies demonstrated the largest inter-annual variation in SOM1, a slight decreasing trend in SOM2, and the abrupt upswing after 2007 in SOM3. Analyses of synoptic cyclone activity using the cyclone track data confirmed the vital contribution of synoptic cyclones to the formation of large-scale patterns. Arctic cyclone activity was enhanced in the SOM1, which was consistent with the meridional temperature gradient increases over the land–Arctic ocean boundaries co-located with major cyclone pathways. The composite daily synoptic evolution of each SOM revealed that all three SOMs persisted for less than five days on average. These evolutionary short-term weather patterns have substantial variability at inter-annual and longer timescales. Therefore, the synoptic-scale activity is central to forming the seasonal-mean climate of the Arctic.

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