Monitoring local weather and climate

Author(s):  
Julian C. Mayes ◽  
Nicholas Pepin
2018 ◽  
Vol 28 (7) ◽  
pp. 2349-2353
Author(s):  
Fatbardha Doko

Shakespeare’s tragedies are among the most analyzed and discussed literary works. In his tragedies Shakespeare follows the Aristotelian pattern of drama, so it is easy to notice there all the elements of a tragedy presented in Aristotle’s Poetics. In this paper I will define what climax in literature is and explore the climax of one of the four great tragedies of Shakespeare, that of King Lear. As a masterfully structured play, the central part of the play is the climax itself. But what is the climax of this play, how is it presented, does it have any impact on the characters, how does it change the course of events, etc? Answers to these questions will be given here. As an example of the interactions between men and weather conditions in Shakespeare’s drama, I will explore climate as climax. The climactic moment of the play is the storm, in the 3rd act, when we see the psychological rage of King Lear. Unsurprisingly, Shakespeare exposes the issue of how the local weather durably affects the nature of men as well as by the way their humours are temporarily changed by climate and environment. Yet, I will argue that this issue actually prompts him to reverse traditional points of view in order to show that things also work the other way round. Indeed, in some of his plays, the playwright insists on men’s unfortunate capacities to provoke violent climactic disorders and to generate chaos on earth. So, it is not only the weather and climate that affect the behaviour and humour of people, but the way people feel and behave. The case with King Lear is a perfect example of this problem. The storm that Lear finds himself is actually reflected in his inner state, in his psychological rage due to his disappointment with his two daughters, and facing with the harsh reality for a father, but mostly for being unjust to his younger daughter, Cordelia.


2019 ◽  
Vol 15 (2) ◽  
pp. 477-492
Author(s):  
Gregory Burris ◽  
Jane Washburn ◽  
Omar Lasheen ◽  
Sophia Dorribo ◽  
James B. Elsner ◽  
...  

Abstract. The authors introduce a method for extracting weather and climate data from a historical plantation document. They demonstrate the method on a document from Shirley Plantation in Virginia (USA) covering the period 1816–1842. They show how the resulting data are organized into a spreadsheet that includes direct weather observations and information on various cultivars. They then give three examples showing how the data can be used for climate studies. The first example is a comparison of spring onset between the plantation era and the modern era. A modern median final spring freeze event (for the years 1943–2017) occurs a week earlier than the historical median (for the years 1822–1839). The second analysis involves developing an index for midsummer temperatures from the timing of the first malaria-like symptoms in the plantation population each year. The median day when these symptoms would begin occurring in the modern period is a month and a half earlier than the median day they occurred in the historical period. The final example is a three-point temperature index generated from ordinal weather descriptions in the document. The authors suggest that this type of local weather information from historical archives, either direct from observations or indirect from phenophase timing, can be useful toward a more complete understanding of climates of the past.


2014 ◽  
Vol 4 (2) ◽  
pp. 89-90 ◽  
Author(s):  
Patrick J. Egan ◽  
Megan Mullin

2019 ◽  
Vol 16 ◽  
pp. 57-61
Author(s):  
Olga Toptunova ◽  
Margarita Choulga ◽  
Ekaterina Kurzeneva

Abstract. Lakes affect local weather and climate. This influence should be taken into account in NWP models through parameterization. For the atmospheric simulation, global coverage of lake depth data is essential. To provide such data Global Lake Database (GLDB) has been created. GLDB contains information about lake location (latitude, longitude), water surface area, and lake mean and max depths. The mean depth is provided as a gridded data set.


2018 ◽  
Author(s):  
Gregory Burris ◽  
Jane Washburn ◽  
Omar Lasheen ◽  
Sophia Dorribo ◽  
James B. Elsner ◽  
...  

Abstract. The authors introduce a method for extracting weather and climate data from a historical plantation document. They demonstrate the method on a document from Shirley Plantation in Virginia (USA) covering the period 1816–1842. They show how the resulting data are organized into a spreadsheet that includes direct weather observations and information on various cultivars. They then give two examples showing how the data can be used for climate studies. The first example is a comparison of spring onset between the plantation era and the modern era. Modern median final spring freeze event (for the years 1943–2017) is occurring a week earlier than the historical median (for the years 1822–1839). The second analysis involves developing an index for mid-summer temperatures from the timing of first malaria-like symptoms in the plantation population each year. The median day when these symptoms would begin occurring in the modern period is a month and a half earlier than the median day they occurred in the historical period. The authors suggest that this type of local weather information from historical archives, either direct from observations or indirect from phenophase timing, can be useful toward a more complete understanding of climates of the past.


2018 ◽  
Vol 99 (2) ◽  
pp. 313-336 ◽  
Author(s):  
Rachel James ◽  
Richard Washington ◽  
Babatunde Abiodun ◽  
Gillian Kay ◽  
Joseph Mutemi ◽  
...  

Abstract Climate models are becoming evermore complex and increasingly relied upon to inform climate change adaptation. Yet progress in model development is lagging behind in many of the regions that need the information most, including in Africa. Targeted model development for Africa is crucial and so too is targeted model evaluation. Assessment of model performance in specific regions often follows a “validation” approach, focusing on mean biases, but if models are to be improved, it is important to understand how they simulate regional climate dynamics: to move from validation to process-based evaluation. This evaluation may be different for every region and requires local weather and climate expertise: a “one size fits all” approach could overlook important, region-specific phenomena. So which are the important processes in African regions? And how might they be evaluated? This paper addresses these questions, drawing on the expertise of a team of scientists from Central, East, southern, and West Africa. For each region, the current understanding of climate models is reviewed, and an example of targeted evaluation is provided, including analysis of moist circulations, teleconnections, and modes of variability. A pan-African perspective is also considered, to examine processes operating between regions. The analysis is based on the Met Office Unified Model, but it uses diagnostics that might be applied to other models. These examples are intended to prompt further discussion among climate modelers and African scientists about how to best evaluate models with an African lens, and promote the development of a model evaluation hub for Africa, to fast track understanding of model behavior for this important continent.


Science ◽  
2020 ◽  
Vol 370 (6519) ◽  
pp. eabb1702 ◽  
Author(s):  
Jeremy M. Cohen ◽  
Erin L. Sauer ◽  
Olivia Santiago ◽  
Samuel Spencer ◽  
Jason R. Rohr

Disease outbreaks among wildlife have surged in recent decades alongside climate change, although it remains unclear how climate change alters disease dynamics across different geographic regions. We amassed a global, spatiotemporal dataset describing parasite prevalence across 7346 wildlife populations and 2021 host-parasite combinations, compiling local weather and climate records at each location. We found that hosts from cool and warm climates experienced increased disease risk at abnormally warm and cool temperatures, respectively, as predicted by the thermal mismatch hypothesis. This effect was greatest in ectothermic hosts and similar in terrestrial and freshwater systems. Projections based on climate change models indicate that ectothermic wildlife hosts from temperate and tropical zones may experience sharp increases and moderate reductions in disease risk, respectively, though the magnitude of these changes depends on parasite identity.


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