THE RELIABILITY OF THE SURFACE AIR TEMPERATURE AND GEOPOTENTIAL HEIGHT DATA AND THEIR LONG-TERM CHANGES IN THE 20CR PROJECT

The field of Н500 geopotential height over the central part of the second natural synoptic region in January during 1950–2019 is analysed to determine regime characteristics of the Okhotsk tropospheric cyclone and its role in the formation of air temperature anomalies over the eastern coast of Asia. A mechanism of occurrence of extreme surface air temperatures using this technique is presented. Extremely low air temperature in the area of the minimum and related deep through are formed during the years when the Н500 minimum is localized over the Sea of Okhotsk. A methodology for constructing ellipses approximating the Н500 level lines in a small neighborhood of the Н500 minimum is developed, the ellipse characteristics are calculated, and their relation to the tropospheric cyclone evolution is analysed. The characteristics of the ellipses constructed in the neighborhood of the geopotential height minimum outside the Sea of Okhotsk significantly differ from those of the ellipses over the Sea of Okhotsk. A high compression of the ellipses towards the major axis is reported when the Far Eastern through intensity is reduced. In this case, an outflow of warm oceanic air masses to the Sea of Okhotsk is observed. The location of the Н500 minimum and the characteristics of the ellipses located within the center circle may be used to explain reasons for dramatic changes in air temperature in the study region. Keywords: Оkhotsk tropospheric cyclone, Н500 minima centers, extreme surface air temperature, ellipse characteristics

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Quantifying heating biases in marine air temperature observations, ~1790 - present

10.5194/egusphere-egu21-2936 ◽

2021 ◽

Author(s):

Thomas Cropper ◽

Elizabeth Kent ◽

David Berry ◽

Richard Cornes ◽

Beatriz Recinos-Rivas

Keyword(s):

Air Temperature ◽

Diurnal Cycle ◽

Surface Air Temperature ◽

Night Time ◽

Data Set ◽

Near Surface ◽

Marine Surface ◽

Heating Model ◽

Marine Air

Accurate, long-term time series of near-surface air temperature (AT) are the fundamental datasets on which the magnitude of anthropogenic climate change is scientifically and societally addressed. Across the ocean, these (near-surface) climate records use Sea Surface Temperature (SST) instead of Marine Air Temperature (MAT) and blend the SST and AT over land to create datasets. MAT has often been overlooked as a data choice as daytime MAT observations from ships are known to contain warm biases due to the storage of accumulated solar energy. Two recent MAT datasets, CLASSnmat (1881 &#8211; 2019) and UAHNMAT (1900 &#8211; 2018), both use night-time MAT observations only. Daytime MAT observations in the International Comprehensive Ocean&#8211;Atmosphere Data Set (ICOADS) account for over half of the MAT observations in ICOADS, and this proportion increases further back in time (i.e. pre-1850s). If long-term MAT records over the ocean are to be extended, the use of daytime MAT is vital.&#160;To adjust for the daytime MAT heating bias, and apply it to ICOADS, we present the application of a physics-based model, which accounts for the accumulated energy storage throughout the day. As the &#8216;true&#8217; diurnal cycle of MAT over the ocean has not been, to-date, adequately quantified, our approach also removes the diurnal cycle from ICOADS observations and generates a night-time equivalent MAT for all observations. We fit this model to MAT observations from groups of ships in ICOADS that share similar heating biases and metadata characteristics. This enables us to use the empirically derived coefficients (representing the physical energy transfer terms of the heating model) obtained from the fit for use in removal of the heating bias and diurnal cycle from ship-based MAT observations throughout ICOADS which share similar characteristics (i.e. we can remove the diurnal cycle from a ship which only reports once daily at noon). This adjustment will create an MAT record of night-time-equivalent temperatures that will enable an extension of the marine surface AT record back into the 18th century.

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Unnatural trend of global land long‐term surface air temperature change

International Journal of Climatology ◽

10.1002/joc.6961 ◽

2020 ◽

Author(s):

Yu Wang ◽

Pengcheng Yan ◽

Fei Ji ◽

Shankai Tang ◽

Liu Yang ◽

...

Keyword(s):

Temperature Change ◽

Air Temperature ◽

Surface Air Temperature ◽

Global Land

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Influence of radiative forcing factors on ground–air temperature coupling during the last millennium: implications for borehole climatology

Climate of the Past ◽

10.5194/cp-14-1583-2018 ◽

2018 ◽

Vol 14 (11) ◽

pp. 1583-1606 ◽

Cited By ~ 7

Author(s):

Camilo Melo-Aguilar ◽

J. Fidel González-Rouco ◽

Elena García-Bustamante ◽

Jorge Navarro-Montesinos ◽

Norman Steinert

Keyword(s):

Air Temperature ◽

Land Surface ◽

Radiative Forcing ◽

Spatial Scales ◽

Ground Surface ◽

Surface Air Temperature ◽

Small Variation ◽

Last Millennium ◽

Reconstruction Methods

Abstract. Past climate variations may be uncovered via reconstruction methods that use proxy data as predictors. Among them, borehole reconstruction is a well-established technique to recover the long-term past surface air temperature (SAT) evolution. It is based on the assumption that SAT changes are strongly coupled to ground surface temperature (GST) changes and transferred to the subsurface by thermal conduction. We evaluate the SAT–GST coupling during the last millennium (LM) using simulations from the Community Earth System Model LM Ensemble (CESM-LME). The validity of such a premise is explored by analyzing the structure of the SAT–GST covariance during the LM and also by investigating the evolution of the long-term SAT–GST relationship. The multiple and single-forcing simulations in the CESM-LME are used to analyze the SAT–GST relationship within different regions and spatial scales and to derive the influence of the different forcing factors on producing feedback mechanisms that alter the energy balance at the surface. The results indicate that SAT–GST coupling is strong at global and above multi-decadal timescales in CESM-LME, although a relatively small variation in the long-term SAT–GST relationship is also represented. However, at a global scale such variation does not significantly impact the SAT–GST coupling, at local to regional scales this relationship experiences considerable long-term changes mostly after the end of the 19th century. Land use land cover changes are the main driver for locally and regionally decoupling SAT and GST, as they modify the land surface properties such as albedo, surface roughness and hydrology, which in turn modifies the energy fluxes at the surface. Snow cover feedbacks due to the influence of other external forcing are also important for corrupting the long-term SAT–GST coupling. Our findings suggest that such local and regional SAT–GST decoupling processes may represent a source of bias for SAT reconstructions from borehole measurement, since the thermal signature imprinted in the subsurface over the affected regions is not fully representative of the long-term SAT variations.

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The importance of surface air temperature fluctuations on long-term performance of vertical ground heat exchangers

Geomechanics for Energy and the Environment ◽

10.1016/j.gete.2016.02.003 ◽

2016 ◽

Vol 6 ◽

pp. 35-44 ◽

Cited By ~ 41

Author(s):

Asal Bidarmaghz ◽

Guillermo A. Narsilio ◽

Ian W. Johnston ◽

Stuart Colls

Keyword(s):

Air Temperature ◽

Heat Exchangers ◽

Surface Air Temperature ◽

Temperature Fluctuations ◽

Ground Heat Exchangers ◽

Vertical Ground ◽

Long Term Performance ◽

Term Performance

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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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