Assessing Arctic Ground Surface Temperatures from Borehole Temperatures and Paleoclimatic Model Simulations

Author(s):  
Hugo Beltrami ◽  
Fracisco José Cuesta-Valero ◽  
Almudena García-García ◽  
Stephan Gruber ◽  
Fernando Jaume-Santero

<p>The surface temperature response to changes in our planet’s external forcing is larger at higher latitudes, a phenomenon known as polar amplification. The Arctic amplification has been particularly intense during the last century, with arctic-wide paleoclimatic reconstructions and state-of-the-art model simulations revealing a twofold arctic warming in comparison with the average global temperature increase. As a consequence, Arctic ground temperatures respond with rapid warming, but this response varies with snow cover and permafrost processes. Thus, changes in arctic ground temperatures are difficult to reconstruct from data, and to simulate in climate models.</p><p>Here, we reconstruct the ground surface temperature histories of 120 borehole temperature profiles above 60ºN for the last 400 years. Past surface temperature evolution from each profile was estimated using a Perturbed Parameter Inversion approach based on a singular value decomposition method. Long-term surface temperature climatologies (circa 1300 and 1700 CE) and quasi-steady state heat flow are also estimated from linear regression through the depth range 200 to 300 m of each borehole temperature profile. The retrieved temperatures are assessed against simulated ground surface temperatures from five Past Millennium and five Historical experiments from the Paleoclimate Modelling Intercomparison Project Phase III (PMIP3), and the fifth phase of the Coupled Model Intercomparison Project (CMIP5) archives, respectively.</p><p>Preliminary results from borehole estimates and PMIP3/CMIP5 simulations reveal that changes in recent Arctic ground temperatures vary spatially and are related to each site’s earlier thermal state of the surface. The magnitudes of ground warming from data and simulations differ with large discrepancies among models. As a consequence, a better understanding of freezing processes at and below the air-ground interface is necessary to interpret subsurface temperature records and global climate model simulations in the Arctic.</p>

2004 ◽  
Vol 41 (12) ◽  
pp. 1437-1451 ◽  
Author(s):  
K C Karunaratne ◽  
C R Burn

The association of site characteristics with the n-factor, a ratio of air to ground surface temperature, was investigated at five sites in the boreal forest near Mayo, Yukon Territory. Permafrost was in equilibrium with surface conditions at three sites, was degrading at another, and was absent from the fifth. Air and near-surface ground temperatures were recorded by data loggers between September 2000 and April 2002, and mean daily temperatures were accumulated to calculate n-factors for the freezing (nf) and thawing (nt) seasons. Air temperature did not vary between the sites, so inter-site differences in nf and nt were because of variations in surface temperature. Variations in nf between the sites over the two winters were primarily because of differences in snow depth, but at sites with similar snow cover, the surface temperatures were relatively high when the site was underlain by unfrozen ground. During summer, daily mean surface temperatures were initially less than air temperatures. However, once the thawing front had penetrated below the depth of diurnal temperature fluctuation, the air and ground surface temperatures converged. Since the rate of thaw penetration is governed by soil thermal diffusivity, nt varies directly with this property. These results indicate that subsurface conditions, particularly absolute temperature and ground thermal properties, exert considerable influence on n-factors, and, at the Mayo sites, the influence is greater than that of the vegetation.


2018 ◽  
Author(s):  
Duncan Ackerley ◽  
Robin Chadwick ◽  
Dietmar Dommenget ◽  
Paola Petrelli

Abstract. General circulation models (GCMs) are routinely run under Atmospheric Modelling Intercomparison Project (AMIP) conditions with prescribed sea surface temperatures (SSTs) and sea ice concentrations (SICs) from observations. These AMIP simulations are often used to evaluate the role of the land and/or atmosphere in causing the development of systematic errors in such GCMs. Extensions to the original AMIP experiment have also been developed to evaluate the response of the global climate to increased SSTs (prescribed) and carbon-dioxide (CO2) as part of the Cloud Feedback Model Intercomparison Project (CFMIP). None of these international modelling initiatives has undertaken a set of experiments where the land conditions are also prescribed, which is the focus of the work presented in this paper. Experiments are performed initially with freely varying land conditions (surface temperature and, soil temperature and mositure) under five different configurations (AMIP, AMIP with uniform 4 K added to SSTs, AMIP SST with quadrupled CO2, AMIP SST and quadrupled CO2 without the plant stomata response, and increasing the solar constant by 3.3 %). Then, the land surface temperatures from the free-land experiments are used to perform a set of “AMIP-prescribed land” (PL) simulations, which are evaluated against their free-land counterparts. The PL simulations agree well with the free-land experiments, which indicates that the land surface is prescribed in a way that is consistent with the original free-land configuration. Further experiments are also performed with different combinations of SSTs, CO2 concentrations, solar constant and land conditions. For example, SST and land conditions are used from the AMIP simulation with quadrupled CO2 in order to simulate the atmospheric response to increased CO2 concentrations without the surface temperature changing. The results of all these experiments have been made publicly available for further analysis. The main aims of this paper are to provide a description of the method used and an initial validation of these AMIP-prescribed land experiments.


2020 ◽  
Vol 16 (2) ◽  
pp. 453-474
Author(s):  
Camilo Melo-Aguilar ◽  
J. Fidel González-Rouco ◽  
Elena García-Bustamante ◽  
Norman Steinert ◽  
Johann H. Jungclaus ◽  
...  

Abstract. Borehole-based reconstruction is a well-established technique to recover information of the past climate variability based on two main hypotheses: (1) past ground surface temperature (GST) histories can be recovered from borehole temperature profiles (BTPs); (2) the past GST evolution is coupled to surface air temperature (SAT) changes, and thus, past SAT changes can be recovered from BTPs. Compared to some of the last millennium (LM) proxy-based reconstructions, previous studies based on the borehole technique indicate a larger temperature increase during the last few centuries. The nature of these differences has fostered the assessment of this reconstruction technique in search of potential causes of bias. Here, we expand previous works to explore potential methodological and physical biases using pseudo-proxy experiments with the Community Earth System Model Last Millennium Ensemble (CESM-LME). A heat-conduction forward model driven by simulated surface temperature is used to generate synthetic BTPs that are then inverted using singular value decomposition. This procedure is applied to the set of simulations that incorporates all of the LM external forcing factors as well as those that consider the concentration of the green house gases (GHGs) and the land use land cover (LULC) changes forcings separately. The results indicate that methodological issues may impact the representation of the simulated GST at different spatial scales, with the temporal logging of the BTPs as the main sampling issue that may lead to an underestimation of the simulated GST 20th-century trends. Our analysis also shows that in the surrogate reality of the CESM-LME the GST does not fully capture the SAT warming during the industrial period, and thus, there may be a further underestimation of the past SAT changes due to physical processes. Globally, this effect is mainly influenced by the GHG forcing, whereas regionally, LULC changes and other forcings factors also contribute. These findings suggest that despite the larger temperature increase suggested by the borehole estimations during the last few centuries of the LM relative to some other proxy reconstructions, both the methodological and physical biases would result in a underestimation of the 20th-century warming.


1991 ◽  
Vol 37 (126) ◽  
pp. 209-219 ◽  
Author(s):  
Alan E. Taylor

Abstract Changes in ground-surface temperature for the past few hundred years have been derived from deep temperature profiles at three wells in the northeastern Canadian Arctic Archipelago, and compared with the climatic history derived from the oxygen-isotope ratio 18O/16O measured in an ice core from the Agassiz Ice Cap, about 180-260 km to the east. Analysis of the ground-temperature profiles suggests that surface temperatures in the area decreased after the Little Climatic Optimum about 1000 years ago until the Little Ice Age (LIA). About 100 years ago, ground-surface temperatures appear to have increased by 2-5K to reach today’s values, while air temperatures increased by 2-3K, according to the isotope record. Part of the larger ground-surface temperature change may be due to other paleoenvironmental effects, such as an increase in snow cover coincident with the end of the LIA. The δ18O climatic record was successful in predicting the general features of the ground-temperature profiles observed at two of the sites, but not the third. There is contemporary evidence that surface temperatures at the latter site may be substantially modified by other environmental factors such as snow cover.


2019 ◽  
Vol 15 (3) ◽  
pp. 1099-1111 ◽  
Author(s):  
Francisco José Cuesta-Valero ◽  
Almudena García-García ◽  
Hugo Beltrami ◽  
Eduardo Zorita ◽  
Fernando Jaume-Santero

Abstract. Estimates of climate sensitivity from general circulation model (GCM) simulations still present a large spread despite the continued improvements in climate modeling since the 1970s. This variability is partially caused by the dependence of several long-term feedback mechanisms on the reference climate state. Indeed, state-of-the-art GCMs present a large spread of control climate states probably due to the lack of a suitable reference for constraining the climatology of preindustrial simulations. We assemble a new gridded database of long-term ground surface temperatures (LoST database) obtained from geothermal data over North America, and we explore its use as a potential reference for the evaluation of GCM preindustrial simulations. We compare the LoST database with observations from the Climate Research Unit (CRU) database, as well as with five past millennium transient climate simulations and five preindustrial control simulations from the third phase of the Paleoclimate Modelling Intercomparison Project (PMIP3) and the fifth phase of the Coupled Model Intercomparison Project (CMIP5). The database is consistent with meteorological observations as well as with both types of preindustrial simulations, which suggests that LoST temperatures can be employed as a reference to narrow down the spread of surface temperature climatologies on GCM preindustrial control and past millennium simulations.


2013 ◽  
Vol 6 (5) ◽  
pp. 1705-1714 ◽  
Author(s):  
J. Xu ◽  
L. Zhao ◽  

Abstract. On the basis of the fifth Coupled Model Intercomparison Project (CMIP5) and the climate model simulations covering 1979 through 2005, the temperature trends and their uncertainties have been examined to note the similarities or differences compared to the radiosonde observations, reanalyses and the third Coupled Model Intercomparison Project (CMIP3) simulations. The results show noticeable discrepancies for the estimated temperature trends in the four data groups (radiosonde, reanalysis, CMIP3 and CMIP5), although similarities can be observed. Compared to the CMIP3 model simulations, the simulations in some of the CMIP5 models were improved. The CMIP5 models displayed a negative temperature trend in the stratosphere closer to the strong negative trend seen in the observations. However, the positive tropospheric trend in the tropics is overestimated by the CMIP5 models relative to CMIP3 models. While some of the models produce temperature trend patterns more highly correlated with the observed patterns in CMIP5, the other models (such as CCSM4 and IPSL_CM5A-LR) exhibit the reverse tendency. The CMIP5 temperature trend uncertainty was significantly reduced in most areas, especially in the Arctic and Antarctic stratosphere, compared to the CMIP3 simulations. Similar to the CMIP3, the CMIP5 simulations overestimated the tropospheric warming in the tropics and Southern Hemisphere and underestimated the stratospheric cooling. The crossover point where tropospheric warming changes into stratospheric cooling occurred near 100 hPa in the tropics, which is higher than in the radiosonde and reanalysis data. The result is likely related to the overestimation of convective activity over the tropical areas in both the CMIP3 and CMIP5 models. Generally, for the temperature trend estimates associated with the numerical models including the reanalyses and global climate models, the uncertainty in the stratosphere is much larger than that in the troposphere, and the uncertainty in the Antarctic is the largest. In addition, note that the reanalyses show the largest uncertainty in the lower tropical stratosphere, and the CMIP3 simulations show the largest uncertainty in both the south and north polar regions.


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