Long-term trends in tourism climate index scores for 40 stations across Iran: the role of climate change and influence on tourism sustainability

2015 ◽  
Vol 60 (1) ◽  
pp. 33-52 ◽  
Author(s):  
Gholamreza Roshan ◽  
Robabe Yousefi ◽  
Jennifer M. Fitchett
2018 ◽  
Vol 20 (2) ◽  
pp. 291-303 ◽  

In this study, Mieczkowski's Tourism Climate Index (TCI) was used for Iran to investigate the climate change impacts on outdoor human comfort. The long-term data covering a network of 153 stations were used to compute TCI under baseline conditions (1981–2015) and a climate change scenario (HadCM3-A1B) for 2016-2045. In this study LARS-WG was used for downscaling of large spatial resolution GCM outputs to a finer spatial resolution. User-friendly and multi-platform software which is called ITCIC (Iran Tourism Climate Index Calculator) was designed to calculate TCI. The spatial distribution of TCI for baseline and climate change conditions was investigated and the covered area by each TCI class was calculated by using ArcGIS 10. The annual distributions of TCI were investigated based on Scott and McBoyle (2001) Models. Also, a suite of multiple linear and non-linear regression models was used to determine the relationship between TCI, latitudes, longitudes and elevations of regions. Root mean square error (RMSE), mean error (ME), mean absolute relative error (MARE) and coefficient of determination (R2) were used to evaluate the modeling accuracy. The best time and regions for outdoor activities in the base and future periods were determined. Comparison of the covered area by each TCI class in the base and future periods showed that the climate change occurrence was led to improving climate comfort. The results of error evaluation criteria showed that non-linear regression was appropriate for all month except January and October.


2019 ◽  
Vol 25 (2) ◽  
pp. 496-508 ◽  
Author(s):  
Dalia MAHMOUD ◽  
◽  
Gamil GAMAL ◽  
Tarek ABOU EL SEOUD ◽  
◽  
...  

Author(s):  
James ROSE

ABSTRACT Within the context of the work and achievements of James Croll, this paper reviews the records of direct observations of glacial landforms and sediments made by Charles Lyell, Archibald and James Geikie and James Croll himself, in order to evaluate their contributions to the sciences of glacial geology and Quaternary environmental change. The paper outlines the social and physical environment of Croll's youth and contrasts this with the status and experiences of Lyell and the Geikies. It also outlines the character and role of the ‘Glasgow School’ of geologists, who stimulated Croll's interest into the causes of climate change and directed his focus to the glacial and ‘interglacial’ deposits of central Scotland. Contributions are outlined in chronological order, drawing attention to: (i) Lyell's high-quality observations and interpretations of glacial features in Glen Clova and Strathmore and his subsequent rejection of the glacial theory in favour of processes attributed to floating icebergs; (ii) the significant impact of Archibald Geikie's 1863 paper on the ‘glacial drift of Scotland’, which firmly established the land-ice theory; (iii) the fact that, despite James Croll's inherent dislike of geology and fieldwork, he provided high-quality descriptions and interpretations of the landforms and sediments of central Scotland in order to test his theory of climate change; and (iv) the great communication skills of James Geikie, enhanced by contacts and evidence from around the world. It is concluded that whilst direct observations of glacial landforms and sediments were critical to the long-term development of the study of glaciation, the acceptance of this theory was dependent also upon the skills, personality and status of the Geikies and Croll, who developed and promoted the concepts. Sadly, the subsequent rejection of the land-ice concept by Lyell resulted in the same factors challenging the acceptance of the glacial theory.


Author(s):  
Ye Yuan ◽  
Stefan Härer ◽  
Tobias Ottenheym ◽  
Gourav Misra ◽  
Alissa Lüpke ◽  
...  

AbstractPhenology serves as a major indicator of ongoing climate change. Long-term phenological observations are critically important for tracking and communicating these changes. The phenological observation network across Germany is operated by the National Meteorological Service with a major contribution from volunteering activities. However, the number of observers has strongly decreased for the last decades, possibly resulting in increasing uncertainties when extracting reliable phenological information from map interpolation. We studied uncertainties in interpolated maps from decreasing phenological records, by comparing long-term trends based on grid-based interpolated and station-wise observed time series, as well as their correlations with temperature. Interpolated maps in spring were characterized by the largest spatial variabilities across Bavaria, Germany, with respective lowest interpolated uncertainties. Long-term phenological trends for both interpolations and observations exhibited mean advances of −0.2 to −0.3 days year−1 for spring and summer, while late autumn and winter showed a delay of around 0.1 days year−1. Throughout the year, temperature sensitivities were consistently stronger for interpolated time series than observations. Such a better representation of regional phenology by interpolation was equally supported by satellite-derived phenological indices. Nevertheless, simulation of observer numbers indicated that a decline to less than 40% leads to a strong decrease in interpolation accuracy. To better understand the risk of declining phenological observations and to motivate volunteer observers, a Shiny app is proposed to visualize spatial and temporal phenological patterns across Bavaria and their links to climate change–induced temperature changes.


2013 ◽  
Vol 3 (12) ◽  
pp. 4183-4196 ◽  
Author(s):  
Maartje J. Klapwijk ◽  
György Csóka ◽  
Anikó Hirka ◽  
Christer Björkman

2017 ◽  
Vol 56 (10) ◽  
pp. 2869-2881
Author(s):  
Janel Hanrahan ◽  
Alexandria Maynard ◽  
Sarah Y. Murphy ◽  
Colton Zercher ◽  
Allison Fitzpatrick

AbstractAs demand for renewable energy grows, so does the need for an improved understanding of renewable energy sources. Paradoxically, the climate change mitigation strategy of fossil fuel divestment is in itself subject to shifts in weather patterns resulting from climate change. This is particularly true with solar power, which depends on local cloud cover. However, because observed shortwave radiation data usually span a decade or less, persistent long-term trends may not be identified. A simple linear regression model is created here using diurnal temperature range (DTR) during 2002–15 as a predictor variable to estimate long-term shortwave radiation (SR) values in the northeastern United States. Using an extended DTR dataset, SR values are computed for 1956–2015. Statistically significant decreases in shortwave radiation are identified that are dominated by changes during the summer months. Because this coincides with the season of greatest insolation and the highest potential for energy production, financial implications may be large for the solar energy industry if such trends persist into the future.


Hydrobiologia ◽  
2018 ◽  
Vol 822 (1) ◽  
pp. 85-109 ◽  
Author(s):  
John R. Beaver ◽  
Janet E. Kirsch ◽  
Claudia E. Tausz ◽  
Erin E. Samples ◽  
Thomas R. Renicker ◽  
...  

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