scholarly journals Using Self-Organizing Maps to Identify Coherent CONUS Precipitation Regions

2019 ◽  
Vol 32 (22) ◽  
pp. 7747-7761 ◽  
Author(s):  
Leif M. Swenson ◽  
Richard Grotjahn
Keyword(s):  
Extreme Events ◽  
Annual Cycle ◽  
Large Scale ◽  
Robust Statistics ◽  
Grid Point ◽  
Future Application ◽  
Self Organizing Maps ◽  
Annual Cycles ◽  
Extreme Precipitation Events ◽  
Self Organizing

Abstract Extreme precipitation events have major societal impacts. These events are rare and can have small spatial scale, making statistical analysis difficult; both factors are mitigated by combining events over a region. A methodology is presented to objectively define “coherent” regions wherein data points have matching annual cycles. Regions are found by training self-organizing maps (SOMs) on the annual cycle of precipitation for each grid point across the contiguous United States (CONUS). Using the annual cycle for our intended application minimizes problems caused by consecutive dry periods and localized extreme events. Multiple criteria are applied to identify useful numbers of regions for our future application. Criteria assess these properties for each region: having many more events than experienced by a single grid point, good connectedness and compactness, and robustness to changing the number of regions. Our methodology is applicable across datasets and is tested here on both reanalysis and gridded observational data. Precipitation regions obtained align with large-scale geographical features and are readily interpretable. Useful numbers of regions balance two conflicting preferences: larger regions contain more events and thereby have more robust statistics, but more compact regions allow weather patterns associated with extreme events to be aggregated with confidence. For 6-h precipitation, 12–15 regions over the CONUS optimize our metrics. The regions obtained are compared against two existing region archetypes. For example, a popular set of regions, based on nine groups of states, has less coherent regions than defining the same number of regions with our SOM methodology.

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.

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.

The characteristics and drivers of climatological precipitation over the Serengeti-Mara region

2020 ◽  
Author(s):  
Josephine Mahony ◽  
Ellen Dyer ◽  
Richard Washington
Keyword(s):  
Annual Cycle ◽  
Large Scale ◽  
Lake Victoria ◽  
Basic Structure ◽  
Local Source ◽  
Land Breeze ◽  
Rainfall Gradient ◽  
Annual Cycles ◽  
Precipitation Patterns ◽  
And Cluster Analysis

<p>The Serengeti National Park is famous for the biological phenomenon of the annual wildebeest migration. This migration is reliant on unique local precipitation conditions: a rainfall gradient stretching across the park, the strength and inclination of which alters from month to month. Given the ecological significance and the complexity of the regional precipitation, a detailed study of the region’s climatology is essential for understanding why these precipitation patterns exist, and whether they are likely to change.</p><p>Using multiple observational datasets, we studied the spatial distribution of annual and monthly climatological precipitation. We carried out harmonic analysis and cluster analysis to identify areas with similar annual cycles. We then examined regional wind, moisture and precipitation patterns on seasonal, monthly and diurnal timescales.</p><p>We found that the large-scale wind circulation patterns dictate the basic structure of the annual cycle over the region. However the shape of the annual cycle was distinctly different in 5 parts of the region, with varying peak rainfall months and dry season rainfall totals. Analysis of the diurnal wind patterns showed that the regional seasonality is strongly augmented by the lake and land breeze from Lake Victoria, and the interactions between this local source of moisture and the complex topography of the East African rift. This leads to a low-level convergence zone between the prevailing large-scale easterlies, and westerlies from Lake Victoria over the Serengeti in the afternoon. This in turn results in the rainfall gradient across the region, the orientation of which changes depending on the mid-tropospheric wind direction.</p>

scholarly journals Projected Seasonal Changes in Large-Scale Global Precipitation and Temperature Extremes Based on the CMIP5 Ensemble

2020 ◽  
Vol 33 (13) ◽  
pp. 5651-5671 ◽  
Author(s):  
Wang Zhan ◽  
Xiaogang He ◽  
Justin Sheffield ◽  
Eric F. Wood
Keyword(s):  
Extreme Events ◽  
Large Scale ◽  
Climate Models ◽  
Spatial Scales ◽  
Extreme Temperature ◽  
Economic Losses ◽  
Temperature And Precipitation ◽  
Extreme Precipitation Events ◽  
The Future ◽  
Precipitation Events

AbstractOver the past decades, significant changes in temperature and precipitation have been observed, including changes in the mean and extremes. It is critical to understand the trends in hydroclimatic extremes and how they may change in the future as they pose substantial threats to society through impacts on agricultural production, economic losses, and human casualties. In this study, we analyzed projected changes in the characteristics, including frequency, seasonal timing, and maximum spatial and temporal extent, as well as severity, of extreme temperature and precipitation events, using the severity–area–duration (SAD) method and based on a suite of 37 climate models archived in phase 5 of the Coupled Model Intercomparison Project (CMIP5). Comparison between the CMIP5 model estimated extreme events and an observation-based dataset [Princeton Global Forcing (PGF)] indicates that climate models have moderate success in reproducing historical statistics of extreme events. Results from the twenty-first-century projections suggest that, on top of the rapid warming indicated by a significant increase in mean temperature, there is an overall wetting trend in the Northern Hemisphere with increasing wet extremes and decreasing dry extremes, whereas the Southern Hemisphere will have more intense wet extremes. The timing of extreme precipitation events will change at different spatial scales, with the largest change occurring in southern Asia. The probability of concurrent dry/hot and wet/hot extremes is projected to increase under both RCP4.5 and RCP8.5 scenarios, whereas little change is detected in the probability of concurrent dry/cold events and only a slight decrease of the joint probability of wet/cold extremes is expected in the future.

A Comparison of CMIP3 Simulations of Precipitation over North America with Observations: Daily Statistics and Circulation Features Accompanying Extreme Events

2013 ◽  
Vol 26 (10) ◽  
pp. 3209-3230 ◽  
Author(s):  
Anthony M. DeAngelis ◽  
Anthony J. Broccoli ◽  
Steven G. Decker
Keyword(s):  
North America ◽  
Extreme Events ◽  
Extreme Precipitation ◽  
Large Scale ◽  
Climate Model ◽  
Heavy Precipitation ◽  
Convective Precipitation ◽  
Southern Mexico ◽  
Extreme Precipitation Events ◽  
Precipitation Events

Abstract Climate model simulations of daily precipitation statistics from the third phase of the Coupled Model Intercomparison Project (CMIP3) were evaluated against precipitation observations from North America over the period 1979–99. The evaluation revealed that the models underestimate the intensity of heavy and extreme precipitation along the Pacific coast, southeastern United States, and southern Mexico, and these biases are robust among the models. The models also overestimate the intensity of light precipitation events over much of North America, resulting in fairly realistic mean precipitation in many places. In contrast, heavy precipitation is simulated realistically over northern and eastern Canada, as is the seasonal cycle of heavy precipitation over a majority of North America. An evaluation of the simulated atmospheric dynamics and thermodynamics associated with extreme precipitation events was also conducted using the North American Regional Reanalysis (NARR). The models were found to capture the large-scale physical mechanisms that generate extreme precipitation realistically, although they tend to overestimate the strength of the associated atmospheric circulation features. This suggests that climate model deficiencies such as insufficient spatial resolution, inadequate representation of convective precipitation, and overly smoothed topography may be more important for biases in simulated heavy precipitation than errors in the large-scale circulation during extreme events.

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 Impact of Atmospheric Circulation on Temperature, Clouds, and Radiation at Summit Station, Greenland, with Self-Organizing Maps

2018 ◽  
Vol 31 (21) ◽  
pp. 8895-8915 ◽  
Author(s):  
Michael R. Gallagher ◽  
Matthew D. Shupe ◽  
Nathaniel B. Miller
Keyword(s):  
Mass Balance ◽  
Atmospheric Circulation ◽  
Radiative Forcing ◽  
Large Scale ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Cloud Formation ◽  
The Arctic ◽  
Self Organizing Maps ◽  
Self Organizing

The Greenland Ice Sheet (GrIS) plays a crucial role in the Arctic climate, and atmospheric conditions are the primary modifier of mass balance. This analysis establishes the relationship between large-scale atmospheric circulation and principal determinants of GrIS mass balance: moisture, cloud properties, radiative forcing, and temperature. Using self-organizing maps (SOMs), observations from the Integrated Characterization of Energy, Clouds, Atmospheric State, and Precipitation at Summit (ICECAPS) project are categorized by daily sea level pressure (SLP) gradient. The results describe in detail how southerly, northerly, and zonal circulation regimes impact observations at Summit Station, Greenland. This southerly regime is linked to large anomalous increases in low-level liquid cloud formation, cloud radiative forcing (CRF), and surface warming at Summit Station. An individual southerly pattern relates to the largest positive anomalies, with the most extreme 25% of cases leading to CRF anomalies above 21 W m−2 and temperature anomalies beyond 8.5°C. Finally, the July 2012 extreme melt event is analyzed, showing that the prolonged ice sheet warming was related to persistence of these southerly circulation patterns, causing an unusually extended period of anomalous CRF and temperature. These results demonstrate a novel methodology, connecting daily atmospheric circulation to a relatively brief record of observations.

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