Squall Detection and Analysis From Historical Satellite Data

2019 ◽  
Author(s):  
L. Renac ◽  
D. P. Hurdle ◽  
F. J. M. Enet ◽  
J. De Vroom
Keyword(s):  
Satellite Data ◽  
Measurement Data ◽  
Extreme Value Analysis ◽  
Intermediate Water ◽  
Design Data ◽  
Value Analysis ◽  
Design Values ◽  
The Impact ◽  
Long Term Measurement

Abstract Thunderstorms and squalls (fronts of contiguous thunderstorms) are associated with short but intense local winds that have a great impact on operability or design conditions for moored ship operations in the coastal zone. The brevity and local scale of such events makes them difficult to capture using standard measurement data and usually requires dedicated long-term measurement campaigns. Because the standard measurements available are usually based on 10-minute averages taken once an hour, such data is often not available. In the absence of conventional measured data, the use of satellite data can provide useful design data if analyzed and applied with caution. We present two case studies (West Africa and Brazil) where squalls have been identified in satellite data and used for extreme value analysis (EVA) to support the design of intermediate water depth mooring systems. The detection of squalls is confirmed with satellite imagery and the handling of this data for the EVA is presented in detail with assumptions made and the sensitivity of the results to these assumptions. The impact on design values is also discussed for both geographic locations.

scholarly journals A Statistical Modeling Methodology for Long-Term Wind Generation and Power Ramp Simulations in New Generation Locations

Energies ◽  
2018 ◽  
Vol 11 (9) ◽  
pp. 2442 ◽  
Author(s):  
Jussi Ekström ◽  
Matti Koivisto ◽  
Ilkka Mellin ◽  
Robert Millar ◽  
Matti Lehtonen
Keyword(s):  
Power Generation ◽  
Wind Power ◽  
Statistical Modeling ◽  
Renewable Energy Sources ◽  
Measurement Data ◽  
Wind Power Generation ◽  
System Level ◽  
Wind Generation ◽  
The Impact

In future power systems, a large share of the energy will be generated with wind power plants (WPPs) and other renewable energy sources. With the increasing wind power penetration, the variability of the net generation in the system increases. Consequently, it is imperative to be able to assess and model the behavior of the WPP generation in detail. This paper presents an improved methodology for the detailed statistical modeling of wind power generation from multiple new WPPs without measurement data. A vector autoregressive based methodology, which can be applied to long-term Monte Carlo simulations of existing and new WPPs, is proposed. The proposed model improves the performance of the existing methodology and can more accurately analyze the temporal correlation structure of aggregated wind generation at the system level. This enables the model to assess the impact of new WPPs on the wind power ramp rates in a power system. To evaluate the performance of the proposed methodology, it is verified against hourly wind speed measurements from six locations in Finland and the aggregated wind power generation from Finland in 2015. Furthermore, a case study analyzing the impact of the geographical distribution of WPPs on wind power ramps is included.

scholarly journals Long-Term and Seasonal Trends in Global Wave Height Extremes Derived from ERA-5 Reanalysis Data

2020 ◽  
Vol 8 (12) ◽  
pp. 1015
Author(s):  
Alicia Takbash ◽  
Ian R. Young
Keyword(s):  
Southern Hemisphere ◽  
Wave Height ◽  
Significant Wave Height ◽  
Reanalysis Data ◽  
Extreme Value Analysis ◽  
Winter Storms ◽  
Value Analysis ◽  
Weather Forecasts ◽  
Significant Wave

A non-stationary extreme value analysis of 41 years (1979–2019) of global ERA5 (European Centre for Medium-Range Weather Forecasts Reanalysis) significant wave height data is undertaken to investigate trends in the values of 100-year significant wave height, Hs100. The analysis shows that there has been a statistically significant increase in the value of Hs100 over large regions of the Southern Hemisphere. There have also been smaller decreases in Hs100 in the Northern Hemisphere, although the related trends are generally not statistically significant. The increases in the Southern Hemisphere are a result of an increase in either the frequency or intensity of winter storms, particularly in the Southern Ocean.

scholarly journals Determining Extreme Still Water Levels for Design and Planning Purposes Incorporating Sea Level Rise: Sydney, Australia

Atmosphere ◽  
2022 ◽  
Vol 13 (1) ◽  
pp. 95
Author(s):  
Phil J. Watson
Keyword(s):  
Sea Level Rise ◽  
Water Level ◽  
Sea Level ◽  
Tide Gauge ◽  
Water Levels ◽  
Extreme Value Analysis ◽  
Tide Gauge Record ◽  
Value Analysis ◽  
Mean Sea Level ◽  
The Impact

This paper provides an Extreme Value Analysis (EVA) of the hourly water level record at Fort Denison dating back to 1915 to understand the statistical likelihood of the combination of high predicted tides and the more dynamic influences that can drive ocean water levels higher at the coast. The analysis is based on the Peaks-Over-Threshold (POT) method using a fitted Generalised Pareto Distribution (GPD) function to estimate extreme hourly heights above mean sea level. The analysis highlights the impact of the 1974 East Coast Low event and rarity of the associated measured water level above mean sea level at Sydney, with an estimated return period exceeding 1000 years. Extreme hourly predictions are integrated with future projections of sea level rise to provide estimates of relevant still water levels at 2050, 2070 and 2100 for a range of return periods (1 to 1000 years) for use in coastal zone management, design, and sea level rise adaptation planning along the NSW coastline. The analytical procedures described provide a step-by-step guide for practitioners on how to develop similar baseline information from any long tide gauge record and the associated limitations and key sensitivities that must be understood and appreciated in applying EVA.

Comparison of the Long-Term Trends of the Largest Waves in the Ice-Free Arctic Waters From Different Reanalysis Products

2018 ◽  
Author(s):  
Takuji Waseda ◽  
Takehiko Nose ◽  
Adrean Webb
Keyword(s):  
Arctic Ocean ◽  
The Arctic ◽  
Extreme Value Analysis ◽  
Positive Trend ◽  
Value Analysis ◽  
The Arctic Ocean ◽  
Ship Route ◽  
Long Term Trends ◽  
Horizontal Grid

The long-term trends of the expected largest waves in the ice-free Arctic waters from Laptev to Beaufort Seas was studied analyzing the ERA-interim reanalysis from 1979 to 2016. The analysis showed that the positive trend is largest in October and increased almost 70 cm in 38 years. For ships navigating the Northern Ship Route, it is important to know what the possible largest waves to expect during its cruise. In view of conducting the extreme value analysis, the uncertainty of the largest wave needs to be validated. However, the observation in the Arctic Ocean is limited. We, therefore, rely on the reanalysis wave products in the Arctic Ocean, whose uncertainty is yet to be determined. ERA-Interim and ERA-5 are compared in the Laptev, the East Siberian, Chukchi and Beaufort Seas. The comparison is relevant as the two products differ in its horizontal grid resolution and availability of the satellite altimeter significant wave height data assimilation. During 2010–2016 when the ERA5 is available, only a small difference from ERA-Interim was detected in the mean. However, the expected largest waves in the domain tended to be large for the ERA-5, 8% normalized bias. The tendency was quite similar with a high correlation of 0.98.

scholarly journals The use of QBO, ENSO, and NAO perturbations in the evaluation of GOME-2 MetOp A total ozone measurements

2019 ◽  
Vol 12 (2) ◽  
pp. 987-1011
Author(s):  
Kostas Eleftheratos ◽  
Christos S. Zerefos ◽  
Dimitris S. Balis ◽  
Maria-Elissavet Koukouli ◽  
John Kapsomenakis ◽  
...  
Keyword(s):  
Satellite Data ◽  
Total Ozone ◽  
Southern Oscillation ◽  
Model Calculations ◽  
Ozone Data ◽  
Ozone Monitoring ◽  
Mean Differences ◽  
The Tropics ◽  
The Impact

Abstract. In this work we present evidence that quasi-cyclical perturbations in total ozone (quasi-biennial oscillation – QBO, El Niño–Southern Oscillation – ENSO, and North Atlantic Oscillation – NAO) can be used as independent proxies in evaluating Global Ozone Monitoring Experiment (GOME) 2 aboard MetOp A (GOME-2A) satellite total ozone data, using ground-based (GB) measurements, other satellite data, and chemical transport model calculations. The analysis is performed in the frame of the validation strategy on longer time scales within the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Satellite Application Facility on Atmospheric Composition Monitoring (AC SAF) project, covering the period 2007–2016. Comparison of GOME-2A total ozone with ground observations shows mean differences of about -0.7±1.4 % in the tropics (0–30∘), about +0.1±2.1 % in the mid-latitudes (30–60∘), and about +2.5±3.2 % and 0.0±4.3 % over the northern and southern high latitudes (60–80∘), respectively. In general, we find that GOME-2A total ozone data depict the QBO–ENSO–NAO natural fluctuations in concurrence with the co-located solar backscatter ultraviolet radiometer (SBUV), GOME-type Total Ozone Essential Climate Variable (GTO-ECV; composed of total ozone observations from GOME, SCIAMACHY – SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY, GOME-2A, and OMI – ozone monitoring instrument, combined into one homogeneous time series), and ground-based observations. Total ozone from GOME-2A is well correlated with the QBO (highest correlation in the tropics of +0.8) in agreement with SBUV, GTO-ECV, and GB data which also give the highest correlation in the tropics. The differences between deseazonalized GOME-2A and GB total ozone in the tropics are within ±1 %. These differences were tested further as to their correlations with the QBO. The differences had practically no QBO signal, providing an independent test of the stability of the long-term variability of the satellite data. Correlations between GOME-2A total ozone and the Southern Oscillation Index (SOI) were studied over the tropical Pacific Ocean after removing seasonal, QBO, and solar-cycle-related variability. Correlations between ozone and the SOI are on the order of +0.5, consistent with SBUV and GB observations. Differences between GOME-2A and GB measurements at the station of Samoa (American Samoa; 14.25∘ S, 170.6∘ W) are within ±1.9 %. We also studied the impact of the NAO on total ozone in the northern mid-latitudes in winter. We find very good agreement between GOME-2A and GB observations over Canada and Europe as to their NAO-related variability, with mean differences reaching the ±1 % levels. The agreement and small differences which were found between the independently produced total ozone datasets as to the influence of the QBO, ENSO, and NAO show the importance of these climatological proxies as additional tool for monitoring the long-term stability of satellite–ground-truth biases.

Vertical distribution of greenhouse gases above Western Siberia by the long-term measurement data

2009 ◽  
Vol 22 (3) ◽  
pp. 316-324 ◽  
Author(s):  
M. Yu. Arshinov ◽  
B. D. Belan ◽  
D. K. Davydov ◽  
G. Inouye ◽  
Sh. Maksyutov ◽  
...  
Keyword(s):  
Vertical Distribution ◽  
Greenhouse Gases ◽  
Western Siberia ◽  
Measurement Data ◽  
Long Term Measurement

scholarly journals Log Truck Value Analysis from Increased Rail Usage

Forests ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 677
Author(s):  
Sangpil Ko ◽  
Pasi Lautala ◽  
Kuilin Zhang
Keyword(s):  
Case Studies ◽  
Raw Materials ◽  
Forest Products ◽  
Forest Products Industry ◽  
Upper Midwest ◽  
Time Efficiency ◽  
Value Analysis ◽  
Fuel Prices ◽  
The Impact

Over the past several decades, the transportation of raw materials (logs) has increasingly shifted from the railway to trucks. However, the long-term sustainability of this shift is being questioned due to the shortage of truck drivers, fluctuation of fuel prices, and changes in hours of service laws. The industry is interested in the possibility to shift more logs back to the railway but the impact of such a shift on truckers has not been investigated. This study attempted to quantify the impact of such a change on the operations of log truckers by calculating time efficiency (percentage of daily hours of service for revenue activities) and value efficiency (average loaded versus total ton-kilometers per day) between a truck only and multimodal (truck/rail) alternatives. We used actual data from the forest products industry companies and truck performance data from an earlier study to investigate the impact through case studies in four different locations of the upper Midwest, US. The results of our analysis revealed that in three out of our four case studies, re-routing log movements through rail yard/siding improved the time efficiency and value efficiency. Finally, our sensitivity analysis found that increases in average truck speed and maximum hours or service had higher impact on multimodal transportation than in truck-only system.

Does Research-Based Professional Development Make a Difference? A Longitudinal Investigation of Teacher Learning in Technology Integration

2009 ◽  
Vol 111 (5) ◽  
pp. 1195-1241 ◽  
Author(s):  
Chrystalla Mouza
Keyword(s):  
Professional Development ◽  
Teacher Learning ◽  
Professional Growth ◽  
Development Program ◽  
Multiple Sources ◽  
Design Data ◽  
The Impact ◽  
Over Time ◽  
Continual Learning

Background/Context Although there is a growing body of literature on the characteristics of effective professional development, there is little direct evidence on the extent to which these characteristics influence teacher learning and practice. In particular, few studies exist to date that demonstrate the impact of technology-focused professional development on teacher learning and practice. Even fewer studies have examined teacher learning for more than a year to understand the sustainability and growth of professional development gains. Purpose The purpose of this study is to examine the long-term impact of research-based professional development on teacher learning and practice with respect to technology. Analysis is based on data collected from 7 urban teachers 2 years after their participation in a yearlong, technology-focused professional development program. Follow-up data are compared with data collected by the author during the teachers’ participation in professional development to (1) investigate the sustainability and growth of teachers’ learning, (2) identify the conditions that facilitated or hindered teachers’ capacity to further develop their thinking, knowledge, and practice with regard to technology, and (3) map the trajectory of teachers’ learning over a 3-year period. Research Design The study employed a qualitative multiple case study design. Data were collected from multiple sources that included teacher interviews, surveys, classroom observations, and collection of artifacts. Two outcomes were defined as critical measures of long-term learning: sustainability and growth. Findings/Results Results indicated that participation in research-based professional development fostered sustained changes in teachers’ educational technology knowledge, ability to design and implement technology-supported experiences for students, and beliefs toward teaching and learning with technology. In two cases, these changes became the basis for continual learning and led to ongoing professional growth. Further, findings revealed three factors that influenced teacher learning over time: (1) student characteristics, (2) access to resources, and (3) social support and opportunities for collaboration with peers. Conclusions/Recommendations Findings of the study suggest that participation in professional development that is grounded in the currently accepted best practices can impact teacher learning and practice. They also offer insights into the process by which teachers modify their knowledge, practices, and beliefs and the conditions that influence learning over time. Further, they provide new lenses for analyzing teacher learning that suggest looking more closely into the interactive relationship between practices and beliefs, as well as the ways in which classroom experience influences continual learning and change.

scholarly journals Night-sky imaging as a potential tool for characterization of total lumen output from small and medium-sized cities

2020 ◽  
Vol 494 (4) ◽  
pp. 5008-5017
Author(s):  
S Wallner ◽  
M Kocifaj ◽  
L Komar ◽  
H A Solano-Lamphar
Keyword(s):  
Satellite Data ◽  
Light Emitting ◽  
Large Cities ◽  
Major Interest ◽  
Night Sky ◽  
Lighting Systems ◽  
The Impact

ABSTRACT In this article, the asymptotic formula developed in past work and applied to predict skyglow due to distant sources was evolved, with the objective of characterizing small and medium-sized cities in the observer's surroundings. To enable this, a combination of theoretical computations and in situ measurements is needed, aiming to distinguish between dominant and smaller light-emitting sources, with the latter usually being camouflaged when measuring the night sky. Furthermore, for numerical modelling of skyglow, few of the most important parameters, specifically the amount of total lumens installed and radiated to the upward hemisphere, can be derived. Astronomical observatories, in particular, can profit from this concept, since they are usually situated far away from large cities but can still be surrounded by smaller villages and towns. We present a detailed description of how theoretical computations are combined with all-sky photometry in order to obtain the properties mentioned. Results are compared with satellite data, showing that, regarding approximations undertaken for processing, they are comparable, underlining the functionality of our approach. The idea of including in situ observations enables us to quantify the impact of small and medium-sized cities globally and independent of location, as long as measurements were conducted outside light domes. In addition, the presented work may be of major interest to the light-pollution community if conducting long-term observations of cities, since the quality of commonly used satellite data is going to decrease in the future, due to blindness in short wavelengths and upcoming conversions of public lighting systems to blue-enlightened LEDs.

Bias and Uncertainty in the Estimation of Extreme Wave Heights and Crests

2009 ◽  
Author(s):  
Richard Gibson ◽  
Colin Grant ◽  
George Z. Forristall ◽  
Rory Smyth ◽  
Peter Owrid ◽  
...  
Keyword(s):  
North Sea ◽  
Extreme Value ◽  
Accurate Prediction ◽  
Design Parameters ◽  
Extreme Value Analysis ◽  
Extreme Wave ◽  
Data Set ◽  
Value Analysis ◽  
Design Values ◽  
Wave Heights

The accurate prediction of extreme wave heights and crests is important to the design of offshore structures. For example, knowledge of the extreme crest elevation is required to set the deck elevation of the topside of a jacket structure. However, methods of extreme value analysis have an inherent bias, and the manner in which they are applied affects this bias. Furthermore, there is uncertainty in the design parameters at the time of design and the possibility that the predictions will change during the life of the structure. This paper is concerned with the accurate prediction of design values that incorporate uncertainty. In the first part of this paper the details of commonly applied extreme value analysis techniques are examined. This is achieved through analysis of simulated data of known distribution. In particular it is the application of least squares minimisation routines that is investigated; however, comparisons are made with maximum likelihood estimation. From this, preferred approaches to the analysis are recommended and their advantages and disadvantages discussed. The methods are applied to the analysis of a North Sea data set and the implications for the design values ascertained. In the second part of the paper Bayesian inference is used to consider the effect of uncertainty in the predicted wave heights and crest elevations. The practical implications are determined by the analysis of a measured North Sea data set.

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