scholarly journals Effects of Near-Surface Air Temperature on Sub-Surface Geothermal Gradient and Heat Flow in Bornu-Chad Basin, Nigeria

Author(s):  
Andrew A. Tyoh ◽  
Etim Daniel Uko ◽  
Olatunji S. Ayanninuola ◽  
Onengiyeofori A. Davies

A study of the effect of near-surface temperature on fields of subsurface geothermal gradient and heat flow has been carried out in the Bornu-Chad Basin, Nigeria, using corrected Bottom-Hole Temperatures (BHTc) lithologic-log data from 9 oil wells. The geothermal gradient using only BHTs ranges from 15.9oCkm-1 to 38.2oCkm-1 with an average of 26.9+/-3.5oCkm-1, while that computed with mean annual temperature and BHTs ranges from 28.2oCkm-1 to 51.5oCkm-1with an average of 37.5+/-2.5oCkm-1. The geothermal gradient using the mean annual temperature and BHTs in the Bornu-Chad is higher than using only BHTs by 7.0oCkm-1. Heatflow ranges from a minimum of 61 mWm-2 to a maximum of 114mWm-2 with an average of 68+/-5.89mWm-2. The isotherm maps exhibit an increasing SW-NE trend. An average heat flow of 68+/-5.9mWm-2 deduced from Bornu-Chad basin is normal for a continental passive margin with age of about 100My. Geothermal gradient results show a distinct and direct relationship with near-surface conditions. There are indications that surface heat flow is controlled by lithology, geothermal gradient and near-surface solar radiation conditions in the Bornu-Chad basin. Consequently, it is recommended that the mean surface temperature be used in geothermal gradients and heatflows estimations. The knowledge of geothermal properties is very important in the search for geothermal energy in the area of study.

2015 ◽  
Vol 12 (8) ◽  
pp. 7665-7687 ◽  
Author(s):  
C. L. Pérez Díaz ◽  
T. Lakhankar ◽  
P. Romanov ◽  
J. Muñoz ◽  
R. Khanbilvardi ◽  
...  

Abstract. Land Surface Temperature (LST) is a key variable (commonly studied to understand the hydrological cycle) that helps drive the energy balance and water exchange between the Earth's surface and its atmosphere. One observable constituent of much importance in the land surface water balance model is snow. Snow cover plays a critical role in the regional to global scale hydrological cycle because rain-on-snow with warm air temperatures accelerates rapid snow-melt, which is responsible for the majority of the spring floods. Accurate information on near-surface air temperature (T-air) and snow skin temperature (T-skin) helps us comprehend the energy and water balances in the Earth's hydrological cycle. T-skin is critical in estimating latent and sensible heat fluxes over snow covered areas because incoming and outgoing radiation fluxes from the snow mass and the air temperature above make it different from the average snowpack temperature. This study investigates the correlation between MODerate resolution Imaging Spectroradiometer (MODIS) LST data and observed T-air and T-skin data from NOAA-CREST-Snow Analysis and Field Experiment (CREST-SAFE) for the winters of 2013 and 2014. LST satellite validation is imperative because high-latitude regions are significantly affected by climate warming and there is a need to aid existing meteorological station networks with the spatially continuous measurements provided by satellites. Results indicate that near-surface air temperature correlates better than snow skin temperature with MODIS LST data. Additional findings show that there is a negative trend demonstrating that the air minus snow skin temperature difference is inversely proportional to cloud cover. To a lesser extent, it will be examined whether the surface properties at the site are representative for the LST properties within the instrument field of view.


2006 ◽  
Vol 19 (12) ◽  
pp. 2995-3003 ◽  
Author(s):  
Yuichiro Oku ◽  
Hirohiko Ishikawa ◽  
Shigenori Haginoya ◽  
Yaoming Ma

Abstract The diurnal, seasonal, and interannual variations in land surface temperature (LST) on the Tibetan Plateau from 1996 to 2002 are analyzed using the hourly LST dataset obtained by Japanese Geostationary Meteorological Satellite 5 (GMS-5) observations. Comparing LST retrieved from GMS-5 with independent precipitation amount data demonstrates the consistent and complementary relationship between them. The results indicate an increase in the LST over this period. The daily minimum has risen faster than the daily maximum, resulting in a narrowing of the diurnal range of LST. This is in agreement with the observed trends in both global and plateau near-surface air temperature. Since the near-surface air temperature is mainly controlled by LST, this result ensures a warming trend in near-surface air temperature.


2020 ◽  
Author(s):  
Zheng Guo ◽  
Miaomiao Cheng

<p>Diurnal temperature range (includes land surface temperature diurnal range and near surface air temperature diurnal range) is an important meteorological parameter, which is a very important factor in the field of the urban thermal environmental. Nowadays, the research of urban thermal environment mainly focused on surface heat island and canopy heat island.</p><p>Based on analysis of the current status of city thermal environment. Firstly, a method was proposed to obtain near surface air temperature diurnal range in this study, difference of land surface temperature between day and night were introduced into the improved temperature vegetation index feature space based on remote sensing data. Secondly, compared with the district administrative division, we analyzed the spatial and temporal distribution characteristics of the diurnal range of land surface temperature and near surface air temperature.</p><p>The conclusions of this study are as follows:</p><p>1 During 2003-2012s, the land surface temperature and near surface air temperature diurnal range of Beijing were fluctuating upward. The rising trend of the near surface air temperature diurnal range was more significant than land surface temperature diurnal range. In addition, the rise and decline of land surface temperature and near surface air temperature diurnal range in different districts were different. In the six city districts, the land surface temperature and near surface air temperature diurnal range in the six areas of the city were mainly downward. The decline trend of near surface air temperature diurnal range was more significant than land surface temperature diurnal range.</p><p>2 During 2003-2012s, the land surface temperature and near surface air temperature diurnal range of Beijing with similar characteristics in spatial distribution, with higher distribution land surface temperature and near surface air temperature diurnal range in urban area and with lower distribution of land surface temperature and near surface air temperature diurnal range in the Northwest Mountainous area and the area of Miyun reservoir.</p>


2000 ◽  
Vol 31 ◽  
pp. 287-294 ◽  
Author(s):  
Ketil Isaksen ◽  
Daniel Vonder Mühll ◽  
Hansueli Gubler ◽  
Thomas Kohl ◽  
Johan Ludvig Sollid

AbstractAnalyses of the geothermal gradient in permafrost areas constitute a key signal of the ground-surface temperature history. Permafrost temperatures in selected areas are particularly well suited to reconstructing past surface-temperature changes, mainly because there is no thermal disturbance due to circulating groundwater. One year of temperature data from an instrumented 102 m deep borehole in permafrost on Janssonhaugen, Svalbard, is presented. Ground thermal properties are calculated. The average value for the thermal conductivity is 1.85 ±0.05 W m–1 K–1 , and the average value for the thermal diffusivity is 1.1m2 s–1, which gives a phase speed for the annual wave of 5.65 × KT2 m d–1. The depth of zero annual amplitude is 18 m The permafrost thickness is estimated as approximately 220 m. Analysis of the temperatures reveals an increasing temperature gradient with depth. Using a heat-conduction inversion model, a palaeoclimatic reconstruction is presented, showing a warming of the surface temperature over the last 60–80 years. The temperature profile represents a regional signal on Svalbard, which shows an inflection associated with near-surface warming of 1.5 ± 0.5°C in the 20th century.


2018 ◽  
Author(s):  
Gabriel Gerard Rooney ◽  
Nicole van Lipzig ◽  
Wim Thiery

Abstract. We make use of a unique high-quality, long-term observational dataset on a tropical lake to assess the effect of rainfall on lake surface temperature. The lake in question is Lake Kivu, one of the African Great Lakes, and was selected for its remarkably uniform climate and availability of multi-year, over-lake meteorological observations. Rain may have a cooling effect on the lake surface by lowering the near-surface air temperature, by the direct rain heat flux into the lake, by mixing the lake surface layer through the flux of kinetic energy, and by convective mixing of the lake surface layer. The potential importance of the rainfall effect is discussed in terms of both heat flux and kinetic-energy flux. To estimate the rainfall effect on the mean diurnal cycle of lake surface temperature, the data are binned into categories of daily rainfall amount. They are further filtered based on comparable values of daily mean net radiation, which reduces the influence of radiative-flux differences. Our results indicate that days with heavy rainfall may experience a reduction in lake surface temperature of approximately 0.3 K by the end of the day compared to days with light-to-moderate rainfall. Overall this study highlights a new potential control on lake surface temperature, and suggests that further efforts are needed to quantify this effect in other regions and to include this process in atmospheric models.


2021 ◽  
Author(s):  
Kimberly Novick

<p>In addition to dramatic reductions to anthropogenic greenhouse gas emissions, most pathways for limiting global warming to less than 2 degrees C rely on managed alterations to the land surface designed to increase land carbon uptake and storage (so-called “natural climate solutions”, or NCS). Reforestation is the NCS with the largest estimated climate mitigation potential, and at least in energy-limited temperate climates, evidence is mounting that transitions from short-stature ecosystems (croplands, grasslands) to forests substantially reduce surface temperature. In this way, reforestation, at least in some places, may also represent a useful tool for local climate adaptation. However, existing work on the topic has tended to focus on how reforestation affects mean annual and seasonal surface temperature, with comparatively less attention paid to the biophysical impacts of reforestation when local cooling would be most beneficial (i.e. at mid-day, and especially droughts and heat waves). Moreover, while surface temperature is a critical driver of ecosystem processes, arguably the near-surface air temperature is the more relevant target for climate adaptation. The duality between reforestation impacts on surface and air temperature has historically been challenging to deconvolve, and thus we do not yet understand the extent to which forest surface cooling extends to the air. In this talk, new strategies are discussed for blending flux tower data and remote sensing observations to uncover the links between reforestation, surface energy balance, and near-surface air temperature dynamics, with a particular emphasis on how plant water use strategies mediate these relationships during summer days and periods of hydrologic stress.  </p>


2020 ◽  
Author(s):  
Seok-Woo Shin ◽  
Dong-Hyun Cha ◽  
Taehyung Kim ◽  
Gayoung Kim ◽  
Changyoung Park ◽  
...  

<p>Extreme temperature can have a devastating impact on the ecological environment (i.e., human health and crops) and the socioeconomic system. To adapt to and cope with the rapidly changing climate, it is essential to understand the present climate and to estimate the future change in terms of temperature. In this study, we evaluate the characteristics of near-surface air temperature (SAT) simulated by two regional climate models (i.e., MM5 and HadGEM3-RA) over East Asia, focusing on the mean and extreme values. To analyze extreme climate, we used the indices for daily maximum (Tmax) and minimum (Tmin) temperatures among the developed Expert Team on Climate Change Detection and Indices (ETCCDI) indices. In the results of the CORDEX-East Asia phase Ⅰ, the mean and extreme values of SAT for DJF (JJA) tend to be colder (warmer) than observation data over the East Asian region. In those of CORDEX-East Asia phase Ⅱ, the mean and extreme values of SAT for DJF and JJA have warmer than those of the CORDEX-East Asia phase Ⅰ except for those of HadGEM3-RA for DJF. Furthermore, the Extreme Temperature Range (ETR, maximum value of Tmax - minimum value of Tmin) of CORDEX-East Asia phase Ⅰ data, which are significantly different from those of observation data, are reduced in that of CORDEX-East Asia phase Ⅱ. Consequently, the high-resolution regional climate models play a role in the improvement of the cold bias having the relatively low-resolution ones. To understand the reasons for the improved and weak points of regional climate models, we investigated the atmospheric field (i.e., flow, air mass, precipitation, and radiation) influencing near-surface air temperature. Model performances for SAT over East Asia were influenced by the expansion of the western North Pacific subtropical high and the location of convective precipitation in JJA and by the contraction of the Siberian high, the spatial distribution of snowfall and associated upwelling longwave radiation in DJF.</p>


Sensors ◽  
2020 ◽  
Vol 20 (18) ◽  
pp. 5268
Author(s):  
Praveena Krishnan ◽  
Tilden P. Meyers ◽  
Simon J. Hook ◽  
Mark Heuer ◽  
David Senn ◽  
...  

Land surface temperature (LST) is a key variable in the determination of land surface energy exchange processes from local to global scales. Accurate ground measurements of LST are necessary for a number of applications including validation of satellite LST products or improvement of both climate and numerical weather prediction models. With the objective of assessing the quality of in situ measurements of LST and to evaluate the quantitative uncertainties in the ground-based LST measurements, intensive field experiments were conducted at NOAA’s Air Resources Laboratory (ARL)’s Atmospheric Turbulence and Diffusion Division (ATDD) in Oak Ridge, Tennessee, USA, from October 2015 to January 2016. The results of the comparison of LSTs retrieved by three narrow angle broadband infrared temperature sensors (IRT), hemispherical longwave radiation (LWR) measurements by pyrgeometers, forward looking infrared camera with direct LSTs by multiple thermocouples (TC), and near surface air temperature (AT) are presented here. The brightness temperature (BT) measurements by the IRTs agreed well with a bias of <0.23 °C, and root mean square error (RMSE) of <0.36 °C. The daytime LST(TC) and LST(IRT) showed better agreement (bias = 0.26 °C and RMSE = 0.67 °C) than with LST(LWR) (bias > 1.1 and RMSE > 1.46 °C). In contrast, the difference between nighttime LSTs by IRTs, TCs, and LWR were <0.47 °C, whereas nighttime AT explained >81% of the variance in LST(IRT) with a bias of 2.64 °C and RMSE of 3.6 °C. To evaluate the annual and seasonal differences in LST(IRT), LST(LWR) and AT, the analysis was extended to four grassland sites in the USA. For the annual dataset of LST, the bias between LST (IRT) and LST (LWR) was <0.7 °C, except at the semiarid grassland (1.5 °C), whereas the absolute bias between AT and LST at the four sites were <2 °C. The monthly difference between LST (IRT) and LST (LWR) (or AT) reached up to 2 °C (5 °C), whereas half-hourly differences between LSTs and AT were several degrees in magnitude depending on the site characteristics, time of the day and the season.


2007 ◽  
Vol 20 (21) ◽  
pp. 5455-5467 ◽  
Author(s):  
R. J. Stouffer ◽  
R. T. Wetherald

Abstract This study documents the temperature variance change in two different versions of a coupled ocean–atmosphere general circulation model forced with estimates of future increases of greenhouse gas (GHG) and aerosol concentrations. The variance changes are examined using an ensemble of 8 transient integrations for the older model version and 10 transient integrations for the newer one. Monthly and annual data are used to compute the mean and variance changes. Emphasis is placed upon computing and analyzing the variance changes for the middle of the twenty-first century and compared with those found in a control integration. The large-scale variance of lower-tropospheric temperature (including surface air temperature) generally decreases in high latitudes particularly during fall due to a delayed onset of sea ice as the climate warms. Sea ice acts to insolate the atmosphere from the much larger heat capacity of the ocean. Therefore, the near-surface temperature variance tends to be larger over the sea ice–covered regions, than the nearby ice-free regions. The near-surface temperature variance also decreases during the winter and spring due to a general reduction in the extent of sea ice during winter and spring. Changes in storminess were also examined and were found to have relatively little effect upon the reduction of temperature variance. Generally small changes of surface air temperature variance occurred in low and midlatitudes over both land and oceanic areas year-round. An exception to this was a general reduction of variance in the equatorial Pacific Ocean for the newer model. Small increases in the surface air temperature variance occur in mid- to high latitudes during the summer months, suggesting the possibility of more frequent and longer-lasting heat waves in response to increasing GHGs.


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