Spatiotemporal investigation of long-term seasonal temperature variability in Libya

2016 ◽  
Vol 178-179 ◽  
pp. 535-549 ◽  
Author(s):  
S.G. Elsharkawy ◽  
E.S. Elmallah
Keyword(s):  
Temperature Variability ◽  
Seasonal Temperature

scholarly journals Seasonal temperature variability and emergency hospital admissions for respiratory diseases: a population-based cohort study

Thorax ◽  
2018 ◽  
Vol 73 (10) ◽  
pp. 951-958 ◽  
Author(s):  
Shengzhi Sun ◽  
Francine Laden ◽  
Jaime E Hart ◽  
Hong Qiu ◽  
Yan Wang ◽  
...  
Keyword(s):  
Respiratory Diseases ◽  
Hospital Admissions ◽  
Temperature Variability ◽  
Seasonal Temperature ◽  
Short Term ◽  
Emergency Hospital ◽  
Emergency Hospital Admissions ◽  
Mean Temperature

BackgroundClimate change increases global mean temperature and changes short-term (eg, diurnal) and long-term (eg, intraseasonal) temperature variability. Numerous studies have shown that mean temperature and short-term temperature variability are both associated with increased respiratory morbidity or mortality. However, data on the impact of long-term temperature variability are sparse.ObjectiveWe aimed to assess the association of intraseasonal temperature variability with respiratory disease hospitalisations among elders.MethodsWe ascertained the first occurrence of emergency hospital admissions for respiratory diseases in a prospective Chinese elderly cohort of 66 820 older people (≥65 years) with 10–13 years of follow-up. We used an ordinary kriging method based on 22 weather monitoring stations in Hong Kong to spatially interpolate daily ambient temperature for each participant’s residential address. Seasonal temperature variability was defined as the SD of daily mean summer (June–August) or winter (December–February) temperatures. We applied Cox proportional hazards regression with time-varying exposure of seasonal temperature variability to respiratory admissions.ResultsDuring the follow-up time, we ascertained 12 689 cases of incident respiratory diseases, of which 6672 were pneumonia and 3075 were COPD. The HRs per 1°C increase in wintertime temperature variability were 1.20 (95% CI 1.08 to 1.32), 1.15 (1.01 to 1.31) and 1.41 (1.15 to 1.71) for total respiratory diseases, pneumonia and COPD, respectively. The associations were not statistically significant for summertime temperature variability.ConclusionWintertime temperature variability was associated with higher risk of incident respiratory diseases.

An Assessment of Long-Term Temperature Variability in the Sierra de Guadarrama (Spain)

2020 ◽  
Author(s):  
Cristina Vegas Cañas ◽  
J. Fidel González Rouco ◽  
Jorge Navarro Montesinos ◽  
Etor E. Lucio Eceiza ◽  
Elena García Bustamante ◽  
...  
Keyword(s):  
Western Europe ◽  
Climate Model ◽  
Regional Climate ◽  
Monitoring Network ◽  
Horizontal Resolution ◽  
Temperature Variability ◽  
Added Value ◽  
Seasonal Temperature ◽  
Highly Correlated

<p>This work provides a first assessment of temperature variability from interannual to multidecadal timescales in the Sierra de Guadarrama, located in central Spain, from observations and regional climate model (RCM) simulations. Observational data are provided by the Guadarrama Monitoring Network (GuMNet; www.ucm.es/gumnet) at higher altitudes and by the Spanish Meteorological Agency (AEMet) at lower sites. An experiment at high horizontal resolution of 1 km using the Weather Research and Forecasting (WRF) RCM, feeding from ERA Interim inputs, is used. Through model-data comparison, it is shown that the simulations are annually and seasonally highly representative of the observations, although there is a tendency in the model to underestimate observational temperatures, mostly at low altitudes. Results show that WRF provides an added value in relation to the reanalysis, with improved correlation and error metrics relative to observations.</p><p>The analysis of long term trends shows no significant temperature trends in the area during the last 20 years. However, when spanning the analysis to the whole observational period, back to the beginning of the 20th century at some sites, significant annual and seasonal temperature increases of ca. 1degC/century develop, most of it happening during de 1970s.</p><p>The temporal variability of temperature anomalies in the Sierra de Guadarrama is highly correlated with the temperatures in the interior of the Iberian Peninsula. This relationship can be extended broadly over south-western Europe.</p>

THE INFLUENCE OF SEASONAL TEMPERATURE VARIABILITY ON SURVIVAL DURING BACKGROUND AND MASS EXTINCTIONS

2018 ◽  
Author(s):  
Matthew E. Clapham ◽  
◽  
Sarah E. Greene ◽  
Alexander Farnsworth ◽  
Dan J. Lunt ◽  
...  
Keyword(s):  
Temperature Variability ◽  
Seasonal Temperature ◽  
Mass Extinctions

An Assessment of Observed and Simulated Temperature Variability in Sierra de Guadarrama (Spain)

2021 ◽  
Author(s):  
Cristina Vegas Cañas ◽  
J. Fidel González Rouco ◽  
Jorge Navarro Montesinos ◽  
Elena García Bustamante ◽  
Etor E. Lucio Eceiza ◽  
...  
Keyword(s):  
Western Europe ◽  
Climate Model ◽  
Regional Climate ◽  
Monitoring Network ◽  
Horizontal Resolution ◽  
Temperature Variability ◽  
Added Value ◽  
Seasonal Temperature ◽  
Temperature Trends ◽  
Highly Correlated

<p>This work provides a first assessment of temperature variability from interannual to multidecadal timescales in Sierra de Guadarrama, located in central Spain, from observations and regional climate model (RCM) simulations. Observational data are provided by the Guadarrama Monitoring Network (GuMNet; www.ucm.es/gumnet) at higher altitudes, up to 2225 masl, and by the Spanish Meteorological Agency (AEMet) at lower sites. An experiment at high horizontal resolution of 1 km using the Weather Research and Forecasting (WRF) RCM, feeding from ERA Interim inputs, is used. Through model-data comparison, it is shown that the simulations are annually and seasonally highly representative of the observations, although there is a tendency in the model to underestimate observational temperatures, mostly at high altitudes. Results show that WRF provides an added value in relation to the reanalysis, with improved correlation and error metrics relative to observations.</p><p>The analysis of temperature trends shows a warming in the area during the last 20 years, very significant in autumn. When spanning the analysis to the whole observational period, back to the beginning of the 20th century at some sites, significant annual and seasonal temperature increases of 1℃/decade develop, most of them happening during de 1970s, although not as intense as during the last 20 years.</p><p>The temporal variability of temperature anomalies in the Sierra de Guadarrama is highly correlated with the temperatures in the interior of the Iberian Peninsula. This relationship can be extended broadly over south-western Europe.</p>

scholarly journals Comparison and assessment of large-scale surface temperature in climate model simulations

2019 ◽  
Vol 5 (1) ◽  
pp. 67-85
Author(s):  
Raquel Barata ◽  
Raquel Prado ◽  
Bruno Sansó
Keyword(s):  
Surface Temperature ◽  
Seasonal Changes ◽  
Large Scale ◽  
Climate Model ◽  
Internal Variability ◽  
Temperature Variability ◽  
Data Driven ◽  
Model Simulations ◽  
Climate Model Simulations

Abstract. We present a data-driven approach to assess and compare the behavior of large-scale spatial averages of surface temperature in climate model simulations and in observational products. We rely on univariate and multivariate dynamic linear model (DLM) techniques to estimate both long-term and seasonal changes in temperature. The residuals from the DLM analyses capture the internal variability of the climate system and exhibit complex temporal autocorrelation structure. To characterize this internal variability, we explore the structure of these residuals using univariate and multivariate autoregressive (AR) models. As a proof of concept that can easily be extended to other climate models, we apply our approach to one particular climate model (MIROC5). Our results illustrate model versus data differences in both long-term and seasonal changes in temperature. Despite differences in the underlying factors contributing to variability, the different types of simulation yield very similar spectral estimates of internal temperature variability. In general, we find that there is no evidence that the MIROC5 model systematically underestimates the amplitude of observed surface temperature variability on multi-decadal timescales – a finding that has considerable relevance regarding efforts to identify anthropogenic “fingerprints” in observational surface temperature data. Our methodology and results present a novel approach to obtaining data-driven estimates of climate variability for purposes of model evaluation.

Long-term predictability of winter teleconnection indices and their relationship to seasonal temperature extremes in Europe

2021 ◽  
Author(s):  
Nina Schuhen ◽  
Nathalie Schaller ◽  
Hannah C. Bloomfield ◽  
David J. Brayshaw ◽  
Jana Sillmann ◽  
...  
Keyword(s):  
Twentieth Century ◽  
Surface Temperature ◽  
North Atlantic Oscillation ◽  
North Atlantic ◽  
Decadal Variability ◽  
Environmental Research ◽  
Seasonal Temperature ◽  
East Atlantic ◽  
Teleconnection Patterns

<p>European winter weather is dominated by several low-frequency teleconnection patterns, the main ones being the North Atlantic Oscillation (NAO), East Atlantic, East Atlantic/Western Russia and Scandinavian patterns. Through predicting these patterns, skillful forecasts of weather parameters like surface temperature can be generated, which in turn are used in a variety of applications (e.g., predictions of energy demand). A previous study (Weisheimer et.al., 2017) found that the NAO was subject to decadal variability during the twentieth century, affecting its long-term predictability. During recent decades, predictions for the NAO index have shown considerable skill, but this is likely to change during future periods of reduced predictability.</p><p>We analyze the century-long ERA-20C reanalysis and ASF-20C seasonal hindcast datasets to find if the other main teleconnection patterns also experience fluctuations in predictability, with potential implications for future skill and development of seasonal forecasting models. By linking the teleconnections to extreme cold and heat wave indices (Russo et al., 2015), we highlight the impact of these large-scale patterns on seasonal surface temperature in Europe during two periods of interest in the middle and end of the century. Our study shows that even though the predictability of the teleconnection patterns themselves fluctuates on a decadal scale, the links to winter surface temperatures are not significantly affected. However, the ability of the seasonal hindcasts to reproduce these patterns is quite limited.</p><p> </p><p>References:</p><p>Russo, S., Sillmann, J., & Fischer, E. M. (2015). Top ten European heatwaves since 1950 and their occurrence in the coming decades. Environmental Research Letters, 10(12), 124003. doi: 10.1088/1748-9326/10/12/124003</p><p>Weisheimer, A., Schaller, N., O’Reilly, C., MacLeod, D. A., & Palmer, T. (2017). Atmospheric seasonal forecasts of the twentieth century:  multi-decadal variability in predictive skill of the winter North Atlantic Oscillation (NAO) and their potential value for extreme event attribution. Quarterly Journal of the Royal Meteorological Society, 143(703), 917-926. doi: 10.1002/qj.29</p>

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