Uncertainties and shortcomings of ground surface temperature histories derived from inversion of temperature logs

Analysing borehole temperature data in terms of ground surface history can add useful information to reconstructions of past climates. Therefore, a rigorous assessment of uncertainties and error sources is a necessary prerequisite for the meaningful interpretation of such ground surface temperature histories. This study analyses the most prominent sources of uncertainty. The diffusive nature of the process makes the inversion relatively robust against incomplete knowledge of the thermal diffusivity. Similarly the influence of heat production is small. It turns out that for investigations of the last 1000 to 100000 years the maximum depth of the temperature log is crucial. More than 3000 m are required for an optimal inversion. Reconstructions of the last one or two millennia require only modestly deep logs (>300 m) but suffer severely from noisy data.Comment: 28 pages, 18 figure, 3 table

Ground surface temperature and continental heat gain: uncertainties from underground

Temperature changes at the Earthʼs surface propagate and are recorded underground as perturbations to the equilibrium thermal regime associated with the heat flow from the Earthʼs interior. Borehole climatology is concerned with the analysis and interpretation of these downward propagating subsurface temperature anomalies in terms of surface climate. Proper determination of the steady-state geothermal regime is therefore crucial because it is the reference against which climate-induced subsurface temperature anomalies are estimated. Here, we examine the effects of data noise on the determination of the steady-state geothermal regime of the subsurface and the subsequent impact on estimates of ground surface temperature (GST) history and heat gain. We carry out a series of Monte Carlo experiments using 1000 Gaussian noise realizations and depth sections of 100 and 200 m as for steady-state estimates depth intervals, as well as a range of data sampling intervals from 10 m to 0.02 m. Results indicate that typical uncertainties for 50 year averages are on the order of ±0.02 K for the most recent 100 year period. These uncertainties grow with decreasing sampling intervals, reaching about ±0.1 K for a 10 m sampling interval under identical conditions and target period. Uncertainties increase for progressively older periods, reaching ±0.3 K at 500 years before present for a 10 m sampling interval. The uncertainties in reconstructed GST histories for the Northern Hemisphere for the most recent 50 year period can reach a maximum of ±0.5 K in some areas. We suggest that continuous logging should be the preferred approach when measuring geothermal data for climate reconstructions, and that for those using the International Heat Flow Commission database for borehole climatology, the steady-state thermal conditions should be estimated from boreholes as deep as possible and using a large fitting depth range (~100 m)

Impacts of the Last Glacial Cycle on ground surface temperature reconstructions over the last millennium

Borehole temperature profiles provide robust estimates of past ground surface temperature changes, in agreement with meteorological data. Nevertheless, past climatic changes such as the Last Glacial Cycle (LGC) generated thermal effects in the subsurface that affect estimates of recent climatic change from geothermal data. We use an ensemble of ice sheet simulations spanning the last 120 ka to assess the impact of the Laurentide Ice Sheet on recent ground surface temperature histories reconstructed from borehole temperature profiles over North America. When the thermal remnants of the LGC are removed, we find larger amounts of subsurface heat storage (2.8 times) and an increased warming of the ground surface over North America by 0.75 K, both relative to uncorrected borehole estimates

Reconstruction of remote climate change from borehole temperature measurement in the eastern part of Morocco

Data from temperature measurements in boreholes are indicators of the temperature variations associated with past climate change. This paper is a contribution to reconstruct the ground surface temperature history (GSTH) from geothermal data in the eastern part of Morocco. From a set of several temperature logs, measured in the study area, only two were found suitable for estimating the ground surface temperature history (GSTH). In order to reconstruct the surface temperature past changes the functional space inversion method (FSI) was used. The inversion reveals a recent warming in the last century with respective amplitude of 0.1 °C and 1 °C for the boreholes 2952 in Oujda and 1624 in Berkane. These results can be confirmed by the air temperature record of the meteorical station in Oujda despite the scarceness of data beyond 1959

Investigation of the Effect of Ground and Air Temperature on Very High Frequency Radio Signals

This paper presents the results of the investigation of the effect of ground surface temperature and air temperature on the Very High Frequency (VHF) radio wave propagation by experimental method. The experimental measured data obtained were analyzed by regression technique. The results based on the best trendline shown that as the ground surface temperature increases, the loss (Path Loss) in the VHF radio signal reduces with gradient coefficient of 21.8dB/0C. Also, the results shown that as the air temperature increases, the loss in the VHF radio signal reduces, however with very smaller gradient coefficient of 7.5dB/0C than the ground surface temperature. The observation of Path Loss against increase in temperature is based on the weather condition when relative humidity (RH) is low. However, when the RH is high and the temperature is also high, the observation is relatively different. This is evident from another results which shown that as the RH increases, there is little increase in  loss of the VHF radio signal, with gradient coefficient of about 2.32dB/0C. This can be due to the effects of refraction, diffraction and scattering of the radio wave by the presence of the water vapor in the air when RH is high. Significantly, the results have shown that the VHF radio wave propagates through the ground surface more than the space (air) during the period under consideration. Keywords: Ground surface, Air, Temperature, Path Loss, Very High Frequency radi

Thermal log analysis for recognition of ground surface temperature change and water movements

International audienceA joint analysis of surface air temperature series recorded at meteorological stations and temperature-depth profiles logged in near-by boreholes was performed to estimate conditions existing prior to the beginning of the instrumental record in central-northern Italy. The adopted method considers conductive and advective heat transport in a horizontally layered medium and provides simultaneous estimates of the pre-observational temperatures and the Darcy velocities. The reconstruction of the ground surface temperature history using an inversion method was performed for boreholes where hydrological disturbances to measured temperature logs were proved to be negligible. Both methods revealed generally coherent climatic changes in the whole investigated area. Climatic conditions were generally warm and comparable with the reference period 1960?1990. The absence of the Little Ice Age in the middle ages seems to be a generic feature of the climate in central-northern Italy. Climate change of the 19th century was generally insignificant with well balanced periods of cold and warmth. The investigated area became significantly colder only at the end of the 19th century. Cooling culminated around 1950 when it was replaced by rapid warming. Recent warming was not inferred only for one of the investigated holes. This discrepancy can be attributed to local environmental conditions

Impact of borehole depths on reconstructed estimates of ground surface temperature histories and energy storage

Estimates of ground surface temperature changes and continental energy storage from geothermal data have become well-accepted indicators of climatic changes. These estimates are independent contributions to the ensemble of paleoclimatic reconstructions and have been used for the validation of general circulation models, and as a component of the energy budget accounting of the global climate system. Recent global and hemispheric analyses of geothermal data were based on data available in the borehole paleoclimatology database, which contains subsurface temperature profiles from a minimum depth of 200 m to about 600 m. Because of the nature of heat conduction, different depth ranges contain the record of past and persistent changes in the energy balance between the lower atmosphere and the ground for different time periods. Here we examine the dependency of estimated ground surface temperature histories and the magnitude of the subsurface heat content on the depth of borehole temperature profiles. Our results show that uncertainties in the estimates of the long-term surface temperature are in the range of ±0.5K. We conclude that previous estimates of ground surface temperature change remain valid for the period since industrialization, but longer-term estimates are subject to considerable uncertainties. The subsurface heat content shows a larger range of variability arising from differences in depth of the borehole temperature profiles, as well as from differences in the time of data acquisition, spanning four decades. These results indicate that estimates of subsurface heat should be carried out with caution to decrease cumulative errors in any spatial analysis

Gap‐filling algorithm for ground surface temperature data measured in permafrost and periglacial environments

Ground surface temperatures (GST) are widely measured in mountain permafrost areas, but their time series data can be interrupted by gaps. Gaps complicate the calculation of aggregates and indices required for analysing temporal and spatial variability between loggers and sites. We present an algorithm to estimate daily mean GST and the resulting uncertainty. The algorithm is designed to automatically fill data gaps in a database of several tens to hundreds of time series, for example, the Swiss Permafrost Monitoring Network (PERMOS). Using numerous randomly generated artificial gaps, we validated the performance of the gap-filling routine in terms of (1) the bias resulting on annual means, (2) thawing and freezing degree-days, and (3) the accuracy of the uncertainty estimation. Although quantile mapping provided the most reliable gap-filling approach overall, linear interpolation between neighbouring values performed equally well for gap durations of up to 3–5 days. Finding the most similar regressors is crucial and also the main source of errors, particularly because of the large spatial and temporal variability of ground and snow properties in high-mountain terrains. Applying the gap-filling technique to the PERMOS GST data increased the total number of complete hydrological years available for analysis by 70 per cent (>450-filled gaps), likely without exceeding a maximal uncertainty of ± 0.25 °C in calculated annual mean value

Selection of borehole temperature depth profiles for regional climate reconstructions

International audienceBorehole temperature depth profiles are commonly used to infer time variations in the ground surface temperature on centennial time scales. We compare different procedures to obtain a regional ground surface temperature history (GSTH) from an ensemble of borehole temperature depth profiles. We address in particular the question of selecting profiles that are not contaminated by non climatic surface perturbations and we compare the joint inversion of all the profiles with the average of individual inversions. We show that the resolution and the stability of the inversion of selected profiles are much improved over those for a complete data set. When profiles have been selected, the average GSTH of individual inversions and the GSTH of the joint inversion are almost identical. This is not observed when the entire data set is inverted: the average of individual inversions is different from the joint inversion. We also show that the joint inversion of very noisy data sets does not improve the resolution but, on the contrary, causes strong instabilities in the inversion. When the profiles that are affected by noise can not be eliminated, averaging of the individual inversions yields the most stable result, but with very poor resolution