Trends in surface air temperature and temperature extremes in the Great Basin during the 20thcentury from ground-based observations

2013 ◽  
Vol 118 (9) ◽  
pp. 3579-3589 ◽  
Author(s):  
Guoping Tang ◽  
John A. Arnone
Keyword(s):  
Great Basin ◽  
Air Temperature ◽  
Surface Air Temperature ◽  
Temperature Extremes

The role of internal variability in climate change projections of North American surface air temperature and temperature extremes in CanESM2 large ensemble simulations

2020 ◽  
Author(s):  
Bin Yu ◽  
Guilong Li ◽  
Shangfeng Chen ◽  
Hai Lin
Keyword(s):  
Climate Change ◽  
Air Temperature ◽  
North American ◽  
Surface Air Temperature ◽  
Internal Variability ◽  
Temperature Extremes ◽  
Large Ensemble ◽  
Climate Simulations ◽  
Ensemble Mean

<p>Recent studies indicated that the internal climate variability plays an important role in various aspects of projected climate changes on regional and local scales. Here we present results of the spreads in projected trends of wintertime North American surface air temperature and extremes indices of warm and cold days over the next half-century, by analyzing a 50-member large ensemble of climate simulations conducted with CanESM2. CanESM2 simulations confirm the important role of internal variability in projected surface temperature trends as demonstrated in previous studies. Yet the spread in North American warming trends in CanESM2 is generally smaller than those obtained from CCSM3 and ECHAM5 large ensemble simulations. Despite this, large spreads in the climate means as well as climate change trends of North American temperature extremes are apparent in CanESM2, especially in the projected cold day trends. The ensemble mean of forced climate simulations reveals high risks of warm days over the western coast and north Canada, as well as a weakening belt of cold days extending from Alaska to the northeast US. The individual ensemble members differ from the ensemble mean mainly in magnitude of the warm day trends, but depart from the ensemble mean in conspicuous ways, including spatial pattern and magnitude, of the cold day trends. The signal-to-noise ratio pattern of the warm day trend resembles that of the surface air temperature trend; with stronger signals over north Canada, Alaska, and the southwestern US than the midsection of the continent. The projected cold day patterns reveal strong signals over the southwestern US, north Canada, and the northeastern US. In addition, the internally generated components of temperature and temperature extreme trends exhibit spatial coherences over North America, and are comparable to the externally forced trends. The large-scale atmospheric circulation-induced temperature variability influences these trends. Overall, our results suggest that climate change trends of North American temperature extremes are likely very uncertain and need to be applied with caution.</p>

Recent changes in daily precipitation and surface air temperature extremes in mainland Portugal, in the period 1941–2007

2013 ◽  
Vol 127 ◽  
pp. 195-209 ◽  
Author(s):  
M. Isabel P. de Lima ◽  
Fátima Espírito Santo ◽  
Alexandre M. Ramos ◽  
João L.M.P. de Lima
Keyword(s):  
Air Temperature ◽  
Daily Precipitation ◽  
Surface Air Temperature ◽  
Temperature Extremes ◽  
Mainland Portugal

scholarly journals Evaluation of CMIP5 and CMIP6 simulations of historical surface air temperature extremes using proper evaluation methods

2020 ◽  
Vol 15 (12) ◽  
pp. 124041
Author(s):  
Thordis L Thorarinsdottir ◽  
Jana Sillmann ◽  
Marion Haugen ◽  
Nadine Gissibl ◽  
Marit Sandstad
Keyword(s):  
Air Temperature ◽  
Surface Air Temperature ◽  
Evaluation Methods ◽  
Temperature Extremes

scholarly journals Estimation of Hourly near Surface Air Temperature Across Israel Using an Ensemble Model

2020 ◽  
Vol 12 (11) ◽  
pp. 1741
Author(s):  
Bin Zhou ◽  
Evyatar Erell ◽  
Ian Hough ◽  
Alexandra Shtein ◽  
Allan C. Just ◽  
...  
Keyword(s):  
Human Health ◽  
Temporal Resolution ◽  
Air Temperature ◽  
Surface Air Temperature ◽  
Temperature Extremes ◽  
Ensemble Model ◽  
Near Surface ◽  
Extreme Gradient Boosting ◽  
Spatio Temporal ◽  
Stage 1

Mapping of near-surface air temperature (Ta) at high spatio-temporal resolution is essential for unbiased assessment of human health exposure to temperature extremes, not least given the observed trend of urbanization and global climate change. Data constraints have led previous studies to focus merely on daily Ta metrics, rather than hourly ones, making them insufficient for intra-day assessment of health exposure. In this study, we present a three-stage machine learning-based ensemble model to estimate hourly Ta at a high spatial resolution of 1 × 1 km2, incorporating remotely sensed surface skin temperature (Ts) from geostationary satellites, reanalysis synoptic variables, and observations from weather stations, as well as auxiliary geospatial variables, which account for spatio-temporal variability of Ta. The Stage 1 model gap-fills hourly Ts at 4 × 4 km2 from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI), which are subsequently fed into the Stage 2 model to estimate hourly Ta at the same spatio-temporal resolution. The Stage 3 model downscales the residuals between estimated and measured Ta to a grid of 1 × 1 km2, taking into account additionally the monthly diurnal pattern of Ts derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) data. In each stage, the ensemble model synergizes estimates from the constituent base learners—random forest (RF) and extreme gradient boosting (XGBoost)—by applying a geographically weighted generalized additive model (GAM), which allows the weights of results from individual models to vary over space and time. Demonstrated for Israel for the period 2004–2017, the proposed ensemble model outperformed each of the two base learners. It also attained excellent five-fold cross-validated performance, with overall root mean square error (RMSE) of 0.8 and 0.9 °C, mean absolute error (MAE) of 0.6 and 0.7 °C, and R2 of 0.95 and 0.98 in Stage 1 and Stage 2, respectively. The Stage 3 model for downscaling Ta residuals to 1 km MODIS grids achieved overall RMSE of 0.3 °C, MAE of 0.5 °C, and R2 of 0.63. The generated hourly 1 × 1 km2 Ta thus serves as a foundation for monitoring and assessing human health exposure to temperature extremes at a larger geographical scale, helping to further minimize exposure misclassification in epidemiological studies.

scholarly journals Sinuosity of Atmospheric Circulation over Southeastern China and Its Relationship to Surface Air Temperature and High Temperature Extremes

Atmosphere ◽  
2021 ◽  
Vol 12 (9) ◽  
pp. 1139
Author(s):  
Yongdi Wang ◽  
Fei Wang ◽  
Xinyu Sun
Keyword(s):  
High Temperature ◽  
Atmospheric Circulation ◽  
Air Temperature ◽  
21St Century ◽  
Surface Air Temperature ◽  
Future Climate ◽  
Temperature Extremes ◽  
Southeastern China ◽  
Climate Conditions ◽  
High Temperature Extremes

Linking sinuosity, a fairly recently developed metric, with high temperature extremes (HTEs) can be both useful and insightful to better understand the physical mechanisms behind HTEs. However, it is not clear whether there exists a relationship between the sinuosity changes and HTE changes in present and future climate conditions over southeastern China. In this paper, the anomalous characteristics of the atmospheric circulation are quantified by sinuosity. Three sinuosity metrics are used in this study: individual sinuosity (SIN), aggregate sinuosity (ASIN), and comprehensive sinuosity (CSIN). Furthermore, we examine the relationship between sinuosity changes and HTE changes in present and future climate conditions. ASIN is strongly correlated with surface air temperature (SAT). We find that the influence of individual sinuosity (SIN) at different latitudes on the SAT of southeastern China is different. The SIN of low (middle) latitude isohypses has significant positive (negative) correlations with the SAT of southeastern China. The SIN of high-latitude isohypses is rather limited and can therefore be ignored. The projected relationship between the sinuosity changes and HTE changes in the late 21st century suggests similar results. The change in SAT is related to the changes in climate variables over southeastern China in the future, and these changes increase with the increase in Z500 or V850 and the decrease in U500. Moreover, the frequencies of large (small) comprehensive sinuosity (CSIN) values at low (mid) latitudes will increase. At the end of the 21st century, Z500 isohypses at different latitudes will have an obvious poleward shift. Our results indicate that measuring the aggregate waviness of the midtropospheric flow (via sinuosity) can provide insight regarding HTEs, and the climate model output can be used to examine the future likelihood of increased HTE.

A tripole pattern of summer surface air temperature anomalies over northern Eurasia and its precursory signals in the tropical Atlantic and northern Asian land

2021 ◽  
Vol 41 (6) ◽  
pp. 3688-3704
Author(s):  
Kejun He ◽  
Ge Liu ◽  
Renguang Wu ◽  
Jingxin Li ◽  
Huimei Wang ◽  
...  
Keyword(s):  
Air Temperature ◽  
Surface Air Temperature ◽  
Northern Eurasia ◽  
Tropical Atlantic ◽  
Temperature Anomalies ◽  
Air Temperature Anomalies
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