The impact of inter-annual variability of annual cycle on long-term persistence of surface air temperature in long historical records

AbstractThis study investigates the impact of sea ice and snow changes on surface air temperature (SAT) trends on the multidecadal time scale over the mid- and high-latitudes of Eurasia during boreal autumn, winter and spring based on a 30-member ensemble simulations of the Community Earth System Model (CESM). A dynamical adjustment method is used to remove the internal component of circulation-induced SAT trends. The leading mode of dynamically adjusted SAT trends is featured by same-sign anomalies extending from northern Europe to central Siberia and to the Russian Far East, respectively, during boreal spring and autumn, and confined to western Siberia during winter. The internally generated component of sea ice concentration trends over the Barents-Kara Seas contributes to the differences in the thermodynamic component of internal SAT trends across the ensemble over adjacent northern Siberia during all the three seasons. The sea ice effect is largest in autumn and smallest in winter. Eurasian snow changes contribute to the spread in dynamically adjusted SAT trends as well around the periphery of snow covered region by modulating surface heat flux changes. The snow effect is identified over northeast Europe-western Siberia in autumn, north of the Caspian Sea in winter, and over eastern Europe-northern Siberia in spring. The effects of sea ice and snow on the SAT trends are realized mainly by modulating upward shortwave and longwave radiation fluxes.

Nature-based cooling potential: a multi-type green infrastructure evaluation in Toronto, Ontario, Canada

International Journal of Biometeorology ◽

10.1007/s00484-021-02100-5 ◽

2021 ◽

Author(s):

Vidya Anderson ◽

William A. Gough

Keyword(s):

Urban Agriculture ◽

Air Temperature ◽

Green Infrastructure ◽

Urban Climate ◽

Surface Air Temperature ◽

Green Roofs ◽

Near Surface ◽

Green Walls ◽

The Impact ◽

Agriculture Systems

AbstractThe application of green infrastructure presents an opportunity to mitigate rising temperatures using a multi-faceted ecosystems-based approach. A controlled field study in Toronto, Ontario, Canada, evaluates the impact of nature-based solutions on near surface air temperature regulation focusing on different applications of green infrastructure. A field campaign was undertaken over the course of two summers to measure the impact of green roofs, green walls, urban vegetation and forestry systems, and urban agriculture systems on near surface air temperature. This study demonstrates that multiple types of green infrastructure applications are beneficial in regulating near surface air temperature and are not limited to specific treatments. Widespread usage of green infrastructure could be a viable strategy to cool cities and improve urban climate.

Seasonal Surface Air Temperature and Precipitation in the FSU Climate Model Coupled to the CLM2

Journal of Climate ◽

10.1175/jcli3470.1 ◽

2005 ◽

Vol 18 (16) ◽

pp. 3217-3228 ◽

Cited By ~ 16

Author(s):

D. W. Shin ◽

S. Cocke ◽

T. E. LaRow ◽

James J. O’Brien

Keyword(s):

Heat Flux ◽

Air Temperature ◽

Climate Model ◽

Initial Conditions ◽

Sensible Heat Flux ◽

Surface Air Temperature ◽

Community Land Model ◽

Temperature And Precipitation ◽

The Impact ◽

Convective Scheme

Abstract The current Florida State University (FSU) climate model is upgraded by coupling the National Center for Atmospheric Research (NCAR) Community Land Model Version 2 (CLM2) as its land component in order to make a better simulation of surface air temperature and precipitation on the seasonal time scale, which is important for crop model application. Climatological and seasonal simulations with the FSU climate model coupled to the CLM2 (hereafter FSUCLM) are compared to those of the control (the FSU model with the original simple land surface treatment). The current version of the FSU model is known to have a cold bias in the temperature field and a wet bias in precipitation. The implementation of FSUCLM has reduced or eliminated this bias due to reduced latent heat flux and increased sensible heat flux. The role of the land model in seasonal simulations is shown to be more important during summertime than wintertime. An additional experiment that assimilates atmospheric forcings produces improved land-model initial conditions, which in turn reduces the biases further. The impact of various deep convective parameterizations is examined as well to further assess model performance. The land scheme plays a more important role than the convective scheme in simulations of surface air temperature. However, each convective scheme shows its own advantage over different geophysical locations in precipitation simulations.

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.

Sensitivity of amplitude-phase characteristics of the surface air temperature annual cycle to variations in annual mean temperature

Izvestiya Atmospheric and Oceanic Physics ◽

10.1134/s0001433806030030 ◽

2006 ◽

Vol 42 (3) ◽

pp. 300-312 ◽

Cited By ~ 7

Author(s):

A. V. Eliseev ◽

I. I. Mokhov ◽

M. S. Guseva

Keyword(s):

Air Temperature ◽

Annual Cycle ◽

Surface Air Temperature ◽

Mean Temperature

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

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.

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

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.

Temperature Annual Cycle Variation and Response to Solar Radiation during 1960 to 2016 in China

10.5194/egusphere-egu2020-3777 ◽

2020 ◽

Author(s):

Runze Zhao ◽

Kaicun Wang ◽

Guocan Wu ◽

Chunlue Zhou

Keyword(s):

Solar Radiation ◽

Air Temperature ◽

Annual Cycle ◽

Surface Air Temperature ◽

Seasonal Temperature ◽

Surface Solar Radiation ◽

Seasonal Temperature Variation ◽

Phase Amplitude ◽

Original Time ◽

Effect Of Surface

The change of its annual cycle is extremely important due to global warming. A widely used method to analyze the changes of temperature annual cycle is based on the decomposition to phase, amplitude and baseline terms. Solar radiation as the leading energy source of temperature changes can directly influence temperature annual cycle. In this study, we investigate the phase, amplitude and baseline of temperature and solar radiation annual cycle after Fourier transform during 1960-2016 in China. The results show that annual cycle of maximum, minimum and mean surface air temperature are advancing in time (-0.08, -0.27 and -0.33 days per ten years), decreasing in range (-0.07, -0.25 and -0.18 degrees per ten years) and rising in baseline (0.20, 0.34 and 0.25 degrees per ten years). To further quantify the effect of surface solar radiation to temperature, we remove the effect from its original time series of maximum and mean temperature, based on a linear regression. The compare of raw and adjusted temperature shows that surface solar radiation advancing the time by 0.19 and 0.19 days per ten years, reduces the range by 0.14 and 0.13 degrees per ten years, and reduces the baseline by 0.08 and 0.04 degrees per ten years, for surface maximum and mean daily air temperature. The result can explain parts of seasonal temperature variation. Effect of surface solar radiation is most obvious Yunnan-Guizhou Plateau for maximum phase. The low phase value in this area is corrected and well-match with other same latitude area after adjusted.