201 research outputs found
“I Will Rise Again”: The Life and Legacy of the U.S.S. Monitor
No full textAbout the author:
Declan Riley Kunkel is an award winning writer, author, and consultant. Originally from Fort Worth, Texas, Declan writes about history, politics, and philosophy. He is pursing a degree in history at Yale
Declan Kiberd. The Irish Writer and the World
No full textThe Irish author and the world is a collection of nineteen articles originally published by Declan Kiberd between 1978 and 2003. A note on the text specifies that the articles have not been altered in order to be included in this volume. They are not arranged in chronological order, which is accounted for in the introduction. The introductory chapter gives useful information on the political and cultural context – either specifically Irish or more global – in which the articles were originall..
Declan Kiberd. The Irish Writer and the World
No full textThe Irish author and the world is a collection of nineteen articles originally published by Declan Kiberd between 1978 and 2003. A note on the text specifies that the articles have not been altered in order to be included in this volume. They are not arranged in chronological order, which is accounted for in the introduction. The introductory chapter gives useful information on the political and cultural context – either specifically Irish or more global – in which the articles were originall..
Nowcasting lightning occurrence from commonly available meteorological parameters using machine learning techniques
No full textArticle Open Access Published: 08 November 2019 Nowcasting lightning occurrence from commonly available meteorological parameters using machine learning techniques Amirhossein Mostajabi, Declan L. Finney, Marcos Rubinstein & Farhad Rachidi npj Climate and Atmospheric Science volume 2, Article number: 41 (2019) Cite this article Article metrics 71 Altmetric Metrics details Abstract Lightning discharges in the atmosphere owe their existence to the combination of complex dynamic and microphysical processes. Knowledge discovery and data mining methods can be used for seeking characteristics of data and their teleconnections in complex data clusters. We have used machine learning techniques to successfully hindcast nearby and distant lightning hazards by looking at single-site observations of meteorological parameters. We developed a four-parameter model based on four commonly available surface weather variables (air pressure at station level (QFE), air temperature, relative humidity, and wind speed). The produced warnings are validated using the data from lightning location systems. Evaluation results show that the model has statistically considerable predictive skill for lead times up to 30 min. Furthermore, the importance of the input parameters fits with the broad physical understanding of surface processes driving thunderstorms (e.g., the surface temperature and the relative humidity will be important factors for the instability and moisture availability of the thunderstorm environment). The model also improves upon three competitive baselines for generating lightning warnings: (i) a simple but objective baseline forecast, based on the persistence method, (ii) the widely-used method based on a threshold of the vertical electrostatic field magnitude at ground level, and, finally (iii) a scheme based on CAPE threshold. Apart from discussing the prediction skill of the model, data mining techniques are also used to compare the patterns of data distribution, both spatially and temporally among the stations. The results encourage further analysis on how mining techniques could contribute to further our understanding of lightning dependencies on atmospheric parameters.SCI-STI-F
Present-day and future lightning, and its impact on tropospheric chemistry
No full textLightning represents a key interaction with climate through its production of
nitrogen oxides (NOx) which lead to ozone production. These NOx emissions are
generally calculated interactively in chemistry-climate models but there has been
little development of the representation of the lightning processes since the 1990s.
In most models the parametrisation of lightning is based upon simulated cloud-top
height. The aims of the thesis are: to explore existing schemes, and develop
a new process-based scheme, to parametrise lightning; to use a new process-based
lightning scheme to give insights regarding the role of lightning NOx in
tropospheric chemistry; and to use alternative lightning schemes to improve the
understanding of the response of lightning to climate change, and the consequent
impacts on tropospheric chemistry.
First, a new lightning parametrisation is developed using reanalysis data and
satellite lightning observations which is based on upward cloud ice flux. This
parametrisation is more closely linked to thunderstorm charging theory. It greatly
improves the simulated zonal distribution of lightning compared to the cloud-top
height approach, which overestimates lightning in the tropics. The new lightning
scheme is then implemented in a chemistry-climate model, the UK Chemistry
and Aerosol model (UKCA). It is evaluated against ozone sonde measurements
with broad global coverage and improves the simulation of the annual cycle of
upper tropospheric ozone concentration, compared to ozone simulated with the
cloud-top height approach. This improvement in simulated ozone is attributed to
the change in ozone production associated with the improved zonal distribution
of simulated lightning.
Subsequently, data from a chemistry-climate model intercomparison project (ACCMIP)
are used to study the state-of-the-art in lightning NOx parametrisation
along with its response to climate change. It is found that the models using the
cloud-top height approach produce a very similar response of lightning NOx to
changes in global mean surface temperature of +0.44± 0.05 TgNK-1, for a baseline
emission of 5 TgN yr-1. However, two models using two alternative lightning
schemes produce a weaker and a negative response of lightning to climate change.
Finally, simulations in a future climate scenario for year 2100 in the UKCA model
were performed with the cloud-top height and the ice flux parametrisations. The
lightning response to climate change when using the cloud-top height scheme is
in good agreement with the positive response found in the multi-model results
of the cloud-top height approach. However, the new ice flux approach suggests
that lightning will decrease in future. These opposing responses introduce large
uncertainty into the projections of tropospheric ozone and methane lifetime in the
future scenario. An analysis of the radiative forcing from these two species also
shows the large uncertainty in the individual methane and ozone radiative forcings
in the future. Due to the opposite effect that lightning NOx has on methane (loss)
and ozone (production) the net radiative forcing effect of lightning in present-day
and future is found to be close to zero. However, there is a small positive feedback
suggested by the results of the cloud-top height approach, whereas no feedback is
evident with the ice flux approach.
These results show there are large and crucial uncertainties introduced by
lightning parametrisation choice, not only in terms of the actual lightning
distribution but also atmospheric composition and radiative forcing. The new
ice-based parametrisation developed here offers a good alternative to the widely-used
approach and can be used in future to model lightning and develop the
understanding of associated uncertainties
Global fraction of lightning fires and burned area from lightning
No full textThis dataset contains the global fraction of lightning fires and burned area from lightning, and associated uncertainties, at 0.5 degree resolution. The dataset is representative for contemporary fire regimes (between 2001 and 2020). The dataset is based on a statistical model with three geospatial predictor variables: the seasonal correlation between lightning and burned area, the seasonal correlation between fire weather and burned area, and the fraction of low impact land. These variables are derivatives from remote sensing products. The statistical model was calibrated and validated with fire cause reference data from seven different parts of the world: USA including Alaska, Canada, Portugal, southern France, Yakutia (Russia), Victoria (Australia) and Tasmania (Australia). The statistical model explained 53 % of the variability in the reference data for the fraction of lightning fires, and 39 % for the burned area from lightning. All other relevant datasets from the study, processed to 0.5 degree resolution, are also provided. These include burned land, seasonal correlation between lightning and burned area, seasonal correlation between fire weather and burned area, low impact land, fire cause reference data, intact forests, fire-related forest loss, carbon combustion and future lightning projections
In the Company of Strangers
No full textRuby and Cat's friendship was forged on an English dockside sixty years ago when, as terrified children, they were shipped off to Australia. It was a friendship that was supposed to last a lifetime but when news of Cat's death reaches Ruby in London, it comes after years of estrangement. Declan too has drifted away from Cat but is forced back to her lavendar farm, Benson's Reach, by the terms of her will. He turns to his troubled friend Alice, who is desperate for a refuge. Can the magic of Benson's Reach triumph over the hurt of the past? Or is Cat's duty-laden legacy simply too much for Ruby and Declan to keep alive?" - Back cover
Review of "The Winter's Tale", Dir. Declan Donnellan for Cheek by Jowl, Silk Street Theatre, London Barbican, 2017
No full textThis is the author accepted manuscript. The final version is available from Johns Hopkins University Press via the DOI in this record.Review of The Winter’s Tale. Presented by Cheek by Jowl, at the Silk Street Theatre, Barbican, London, UK. April 5-22, 2017. Directed by Declan Donnellan. Designed by Nick Ormerod. Lighting design by Judith Greenwood. Music and sound design by Paddy Cunneen. With Grace Andrews (Emilia/Time), Joseph Black (Cleomenes), David Carr (Camillo), Tom Cawte (Mamillius), Ryan Donaldson (Autolycus), Guy Hughes (Dion), Orlando James (Leontes), Sam McArdle (Young Shepherd), Eleanor McLoughlin (Perdita), Peter Moreton (Old Shepherd/Antigonus), Natalie Radmall-Quirke (Hermione/Dorcas), Joy Richardson (Paulina/Mopsa), Edward Sayer (Polixenes), and Sam Woolf (Florizel)
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