Global mean surface air temperature and North Atlantic overturning in a suite of coupled GCM climate change experiments

Abstract. We present a seasonal climatology of tropopause altitude for 78° N 16° E derived from observations 2007–2010 by the SOUSY VHF radar on Svalbard. The spring minimum occurs one month later than that of surface air temperature and instead coincides with the maximum in ozone column density. This confirms similar studies based on radiosonde measurements in the arctic and demonstrates downward control by the stratosphere. If one is to exploit the potential of tropopause height as a metric for climate change at high latitude and elsewhere, it is imperative to observe and understand the processes which establish the tropopause – an understanding to which this study contributes.

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global mean surface air temperature

Encyclopedia of Environmental Change ◽

10.4135/9781446247501.n1729 ◽

2014 ◽

Keyword(s):

Air Temperature ◽

Surface Air Temperature ◽

Global Mean

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Contribution of SST change to multidecadal global and continental surface air temperature trends between 1910 and 2013

Climate Dynamics ◽

10.1007/s00382-019-05060-0 ◽

2019 ◽

Vol 54 (3-4) ◽

pp. 1295-1313

Author(s):

Yidan Xu ◽

Jianping Li ◽

Cheng Sun ◽

Xiaopei Lin ◽

Hailong Liu ◽

...

Keyword(s):

Air Temperature ◽

North Atlantic ◽

Surface Air Temperature ◽

Western Pacific ◽

Multidecadal Variability ◽

The North ◽

Temperature Trends ◽

Community Atmosphere Model ◽

Community Earth System Model ◽

Goddard Institute

AbstractThe global mean surface air temperature (GMST) shows multidecadal variability over the period of 1910–2013, with an increasing trend. This study quantifies the contribution of hemispheric surface air temperature (SAT) variations and individual ocean sea surface temperature (SST) changes to the GMST multidecadal variability for 1910–2013. At the hemispheric scale, both the Goddard Institute for Space Studies (GISS) observations and the Community Earth System Model (CESM) Community Atmosphere Model 5.3 (CAM5.3) simulation indicate that the Northern Hemisphere (NH) favors the GMST multidecadal trend during periods of accelerated warming (1910–1945, 1975–1998) and cooling (1940–1975, 2001–2013), whereas the Southern Hemisphere (SH) slows the intensity of both warming and cooling processes. The contribution of the NH SAT variation to the GMST multidecadal trend is higher than that of the SH. We conduct six experiments with different ocean SST forcing, and find that all the oceans make positive contributions to the GMST multidecadal trend during rapid warming periods. However, only the Indian, North Atlantic, and western Pacific oceans make positive contributions to the GMST multidecadal trend between 1940 and 1975, whereas only the tropical Pacific and the North Pacific SSTs contribute to the GMST multidecadal trend between 2001 and 2013. The North Atlantic and western Pacific oceans have important impacts on modulating the GMST multidecadal trend across the entire 20th century. Each ocean makes different contributions to the SAT multidecadal trend of different continents during different periods.

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“Borehole temperatures, climate change and pre-observational surface air temperature mean: Allowance for hydraulic conditions” by Louise Bodri and Vladimir Cermak

Global and Planetary Change ◽

10.1016/j.gloplacha.2005.02.006 ◽

2005 ◽

Vol 48 (4) ◽

pp. 313-314 ◽

Cited By ~ 3

Author(s):

Grant Ferguson

Keyword(s):

Climate Change ◽

Air Temperature ◽

Surface Air Temperature ◽

Hydraulic Conditions ◽

Borehole Temperatures

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Evaluation of CLDAS and GLDAS Datasets for Near-Surface Air Temperature over Major Land Areas of China

Sustainability ◽

10.3390/su12104311 ◽

2020 ◽

Vol 12 (10) ◽

pp. 4311

Author(s):

Shuai Han ◽

Buchun Liu ◽

Chunxiang Shi ◽

Yuan Liu ◽

Meijuan Qiu ◽

...

Keyword(s):

Climate Change ◽

Sustainable Development ◽

Data Assimilation ◽

Air Temperature ◽

Surface Air Temperature ◽

Near Surface ◽

Land Data Assimilation ◽

Land Data Assimilation System ◽

Data Assimilation System ◽

Assimilation System

As one of the most principal meteorological factors to affect global climate change and human sustainable development, temperature plays an important role in biogeochemical and hydrosphere cycle. To date, there are a wide range of temperature data sources and only a detailed understanding of the reliability of these datasets can help us carry out related research. In this study, the hourly and daily near-surface air temperature observations collected at national automatic weather stations (NAWS) in China were used to compare with the China Meteorological Administration (CMA) Land Data Assimilation System (CLDAS) and the Global Land Data Assimilation System (GLDAS), both of which were developed by using the advanced multi-source data fusion technology. Results are as follows. (1) The spatial and temporal variations of the near-surface air temperature agree well between CLDAS and GLDAS over major land of China, except that spatial details in high mountainous areas were not sufficiently displayed in GLDAS; (2) The near-surface air temperature of CLDAS were more significantly correlated with observations than that of GLDAS, but more caution is necessary when using the data in mountain areas as the accuracy of the datasets gradually decreases with increasing altitude; (3) CLDAS can better illustrate the distribution of areas of daily maximum above 35 °C and help to monitor high temperature weather. The main conclusion of this study is that CLDAS near-surface air temperature has a higher reliability in China, which is very important for the study of climate change and sustainable development in East Asia.

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A novel method for assessing climate change impacts in ecotron experiments

International Journal of Biometeorology ◽

10.1007/s00484-020-01951-8 ◽

2020 ◽

Vol 64 (10) ◽

pp. 1709-1727

Author(s):

Inne Vanderkelen ◽

Jakob Zscheischler ◽

Lukas Gudmundsson ◽

Klaus Keuler ◽

Francois Rineau ◽

...

Keyword(s):

Climate Change ◽

Regional Climate Model ◽

Air Temperature ◽

Climate Model ◽

Regional Climate ◽

Climate Forcing ◽

Future Climate Change ◽

Ecosystem Responses ◽

Model Projection ◽

Global Mean

Abstract Ecotron facilities allow accurate control of many environmental variables coupled with extensive monitoring of ecosystem processes. They therefore require multivariate perturbation of climate variables, close to what is observed in the field and projections for the future. Here, we present a new method for creating realistic climate forcing for manipulation experiments and apply it to the UHasselt Ecotron experiment. The new methodology uses data derived from the best available regional climate model projection and consists of generating climate forcing along a gradient representative of increasingly high global mean air temperature anomalies. We first identified the best-performing regional climate model simulation for the ecotron site from the Coordinated Regional Downscaling Experiment in the European domain (EURO-CORDEX) ensemble based on two criteria: (i) highest skill compared to observations from a nearby weather station and (ii) representativeness of the multi-model mean in future projections. The time window is subsequently selected from the model projection for each ecotron unit based on the global mean air temperature of the driving global climate model. The ecotron units are forced with 3-hourly output from the projections of the 5-year period in which the global mean air temperature crosses the predefined values. With the new approach, Ecotron facilities become able to assess ecosystem responses on changing climatic conditions, while accounting for the co-variation between climatic variables and their projection in variability, well representing possible compound events. The presented methodology can also be applied to other manipulation experiments, aiming at investigating ecosystem responses to realistic future climate change.

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An Integrated Procedure to Determine a Reference Station Network for Evaluating and Adjusting Urban Bias in Surface Air Temperature Data

Journal of Applied Meteorology and Climatology ◽

10.1175/jamc-d-14-0295.1 ◽

2015 ◽

Vol 54 (6) ◽

pp. 1248-1266 ◽

Cited By ~ 28

Author(s):

Guoyu Ren ◽

Jiao Li ◽

Yuyu Ren ◽

Ziying Chu ◽

Aiying Zhang ◽

...

Keyword(s):

Climate Change ◽

Air Temperature ◽

Historical Data ◽

Spatial Scales ◽

Mainland China ◽

Surface Air Temperature ◽

Reference Station ◽

Reference Network ◽

Station Network

AbstractTrends in surface air temperature (SAT) are a critical indicator for climate change at varied spatial scales. Because of urbanization effects, however, the current SAT records of many urban stations can hardly meet the demands of the studies. Evaluation and adjustment of the urbanization effects on the SAT trends are needed, which requires an objective selection of reference (rural) stations. Based on the station history information from all meteorological stations with long-term records in mainland China, an integrated procedure for determining the reference SAT stations has been developed and is applied in forming a network of reference SAT stations. Historical data from the network are used to assess the urbanization effects on the long-term SAT trends of the stations of the national Reference Climate Network and Basic Meteorological Network (RCN+BMN or national stations), which had been used most frequently in studies of regional climate change throughout the country. This paper describes in detail the integrated procedure and the assessment results of urbanization effects on the SAT trends of the national stations applying the data from the reference station network determined using the procedure. The results showed a highly significant urbanization effect of 0.074°C (10 yr)−1 and urbanization contribution of 24.9% for the national stations of mainland China during the time period 1961–2004, which compared well to results that were reported in previous studies by the authors using the predecessor of the present reference network and the reference stations selected but when applying other methods. The authors are thus confident that the SAT data from the updated China reference station network as reported in this paper best represented the baseline SAT trends nationwide and could be used for evaluating and adjusting the urban biases in the historical data series of the SAT from different observational networks.

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