Relationship Between Air Temperature and Soil and Plant Surface Temperatures

2021 ◽  
Vol 12 (6) ◽  
pp. 755-766
Author(s):  
Ki Cheol Eom
Keyword(s):  
Air Temperature ◽  
Plant Surface ◽  
Surface Temperatures

scholarly journals Quantifying the Congruence between Air and Land Surface Temperatures for Various Climatic and Elevation Zones of Western Himalaya

2019 ◽  
Vol 11 (24) ◽  
pp. 2889 ◽  
Author(s):  
Shaktiman Singh ◽  
Anshuman Bhardwaj ◽  
Atar Singh ◽  
Lydia Sam ◽  
Mayank Shekhar ◽  
...  
Keyword(s):  
Air Temperature ◽  
Land Surface ◽  
Extreme Environments ◽  
Western Himalaya ◽  
In Situ Monitoring ◽  
Lapse Rate ◽  
Similar Data ◽  
Surface Temperatures ◽  
Land Surface Temperatures

The surface and near-surface air temperature observations are primary data for glacio-hydro-climatological studies. The in situ air temperature (Ta) observations require intense logistic and financial investments, making it sparse and fragmented particularly in remote and extreme environments. The temperatures in Himalaya are controlled by a complex system driven by topography, seasons, and cryosphere which further makes it difficult to record or predict its spatial heterogeneity. In this regard, finding a way to fill the observational spatiotemporal gaps in data becomes more crucial. Here, we show the comparison of Ta recorded at 11 high altitude stations in Western Himalaya with their respective land surface temperatures (Ts) recorded by Moderate Resolution Imagining Spectroradiometer (MODIS) Aqua and Terra satellites in cloud-free conditions. We found remarkable seasonal and spatial trends in the Ta vs. Ts relationship: (i) Ts are strongly correlated with Ta (R2 = 0.77, root mean square difference (RMSD) = 5.9 °C, n = 11,101 at daily scale and R2 = 0.80, RMSD = 5.7 °C, n = 3552 at 8-day scale); (ii) in general, the RMSD is lower for the winter months in comparison to summer months for all the stations, (iii) the RMSD is directly proportional to the elevations; (iv) the RMSD is inversely proportional to the annual precipitation. Our results demonstrate the statistically strong and previously unreported Ta vs. Ts relationship and spatial and seasonal variations in its intensity at daily resolution for the Western Himalaya. We anticipate that our results will provide the scientists in Himalaya or similar data-deficient extreme environments with an option to use freely available remotely observed Ts products in their models to fill-up the spatiotemporal data gaps related to in situ monitoring at daily resolution. Substituting Ta by Ts as input in various geophysical models can even improve the model accuracy as using spatially continuous satellite derived Ts in place of discrete in situ Ta extrapolated to different elevations using a constant lapse rate can provide more realistic estimates.

Estimating mean air temperature using MODIS day and night land surface temperatures

2013 ◽  
Vol 118 (1-2) ◽  
pp. 81-92 ◽  
Author(s):  
Hao Sun ◽  
Yunhao Chen ◽  
Adu Gong ◽  
Xiang Zhao ◽  
Wenfeng Zhan ◽  
...  
Keyword(s):  
Air Temperature ◽  
Land Surface ◽  
Surface Temperatures ◽  
Land Surface Temperatures

scholarly journals Potential surface temperature and shallow groundwater temperature response to climate change: an example from a small forested catchment in east-central New Brunswick (Canada)

2013 ◽  
Vol 17 (7) ◽  
pp. 2701-2716 ◽  
Author(s):  
B. L. Kurylyk ◽  
C. P.-A. Bourque ◽  
K. T. B. MacQuarrie
Keyword(s):  
Climate Change ◽  
Transfer Function ◽  
Surface Temperature ◽  
New Brunswick ◽  
Snow Cover ◽  
Air Temperature ◽  
Groundwater Temperature ◽  
Forested Catchment ◽  
Surface Temperatures ◽  
Precipitation Regimes

Abstract. Global climate models project significant changes to air temperature and precipitation regimes in many regions of the Northern Hemisphere. These meteorological changes will have associated impacts to surface and shallow subsurface thermal regimes, which are of interest to practitioners and researchers in many disciplines of the natural sciences. For example, groundwater temperature is critical for providing and sustaining suitable thermal habitat for cold-water salmonids. To investigate the surface and subsurface thermal effects of atmospheric climate change, seven downscaled climate scenarios (2046–2065) for a small forested catchment in New Brunswick, Canada were employed to drive the surface energy and moisture flux model, ForHyM2. Results from these seven simulations indicate that climate change-induced increases in air temperature and changes in snow cover could increase summer surface temperatures (range −0.30 to +3.49 °C, mean +1.49 °C), but decrease winter surface temperatures (range −1.12 to +0.08 °C, mean −0.53 °C) compared to the reference period simulation. Thus, changes to the timing and duration of snow cover will likely decouple changes in mean annual air temperature (mean +2.11 °C) and mean annual ground surface temperature (mean +1.06 °C). Projected surface temperature data were then used to drive an empirical surface to groundwater temperature transfer function developed from measured surface and groundwater temperature. Results from the empirical transfer function suggest that changes in groundwater temperature will exhibit seasonality at shallow depths (1.5 m), but be seasonally constant and approximately equivalent to the change in the mean annual surface temperature at deeper depths (8.75 m). The simulated increases in future groundwater temperature suggest that the thermal sensitivity of baseflow-dominated streams to decadal climate change may be greater than previous studies have indicated.

Numerical Analysis of Passive Microclimatic-Modifying Effects of a Moist Void-Brick Wall

2012 ◽  
Vol 193-194 ◽  
pp. 1156-1164 ◽  
Author(s):  
Jiang He ◽  
Kai Qiong Liu
Keyword(s):  
Air Temperature ◽  
Simulation Method ◽  
Urban Environments ◽  
Water Evaporation ◽  
Brick Wall ◽  
3D Cad ◽  
Surface Temperatures ◽  
Thermal Improvement ◽  
Improvement Effect ◽  
Computational Fluid Dynamics Cfd

As a passive cooling strategy aimed at controlling increased surface temperatures and creating cooler urban environments, a passive evaporative cooling wall constructed of moist void bricks was developed. The wall is capable of absorbing water and allows wind penetration, thus reducing their surface temperatures by means of water evaporation. This paper presents a numerical simulation method to predict and evaluate microclimatic modifying effects (air temperature reduction, ventilation cooling and vapor generation) of the wall in urban locations where installation of the wall is under consideration. This simulation is performed by coupling computational fluid dynamics (CFD) with a 3D-CAD-based thermal simulation tool. Methodology of the coupled simulation was described in this paper. In order to demonstrate the applicability of the proposed simulation method, a case study was performed to predict and evaluate the thermal improvement effect of the wall on thermal comfort at a rest station where the wall was installed. Simulation results show that, in terms of air temperature, airflow, humidity and surface temperature distributions, this simulation method can provide quantitative predictions and evaluations of microclimatic modifying effects resulting from the application of the wall.

Spatiotemporally characterizing urban temperatures based on remote sensing and GIS analysis: a case study in the city of Saskatoon (SK, Canada)

2014 ◽  
Vol 7 (1) ◽  
Author(s):  
Li Shen ◽  
Xulin Guo ◽  
Kang Xiao
Keyword(s):  
Linear Regression ◽  
Air Temperature ◽  
Spatial Scales ◽  
Pearson Correlation ◽  
Multiple Linear Regression Model ◽  
Influential Factors ◽  
Urban Surface ◽  
Urban Green Spaces ◽  
Surface Temperatures ◽  
Cooling Effects

AbstractThe purpose of this study is to spatiotemporally explore the characteristics of urban temperatures based on multi-temporal satellite data and historical in situ measurements. As one of the most rapidly urbanized cities in Canada, Saskatoon (SK) was selected as our study area. Surface brightness retrieving, Pearson correlation, linear regression modeling, and buffer analysis were applied to different satellite datasets. The results indicate that both Landsat and MODIS data can yield pronounced estimations of daily air temperature with a significantly adjusted R2 of 0.803 and 0.518 at the spatial scales of 120m and 1000 m, respectively. MODIS monthly LST data is highly suitable for monitoring the trend of monthly urban air temperature throughout summer (June, July, and August) due to a high average R2 of 0.8 (P<0.05), especially for the warmest month (July). Our findings also reveal that both the Saskatchewan River and urban green spaces have statistically significant cooling effects on the surrounding urban surface temperatures within 500 m and 200 m, respectively. In addition, a multiple linear regression model with four influential factors as independent variables can be developed to estimate urban surface temperatures with a highest adjusted R2 of 0.649 and a lowest standard error of 0.076.

scholarly journals Near-surface thermal stratification during summer at Summit, Greenland, and its relation to MODIS-derived surface temperatures

2017 ◽  
Author(s):  
Alden C. Adolph ◽  
Mary R. Albert ◽  
Dorothy K. Hall
Keyword(s):  
Remote Sensing ◽  
Surface Temperature ◽  
Skin Temperature ◽  
Air Temperature ◽  
The Arctic ◽  
Cold Bias ◽  
Near Surface ◽  
Surface Temperatures ◽  
In Situ Ir

Abstract. As rapid warming of the Arctic occurs, it is imperative that climate indicators such as temperature be monitored over large areas to understand and predict the effects of climate changes. Temperatures are traditionally tracked using in situ 2 m air temperatures, but in remote locations where few ground-based measurements exist, such as on the Greenland Ice Sheet, temperatures over large areas are assessed using remote sensing techniques. Because of the presence of surface-based temperature inversions in ice-covered areas, differences between 2 m air temperature and the temperature of the actual snow surface (referred to as skin temperature) can be significant and are particularly relevant when considering validation and application of remote sensing temperature data. We present results from a field campaign extending from 8 June through 18 July 2015, near Summit Station in Greenland to study surface temperature using the following measurements: skin temperature measured by an infrared (IR) sensor, thermochrons, and thermocouples; 2 m air temperature measured by a NOAA meteorological station; and a MODerate-resolution Imaging Spectroradiometer (MODIS) surface temperature product. Our data indicate that 2 m air temperature is often significantly higher than snow skin temperature measured in-situ, and this finding may account for apparent biases in previous surface temperature studies of MODIS products that used 2 m air temperature for validation. This inversion is present during summer months when incoming solar radiation and wind speed are both low. As compared to our in-situ IR skin temperature measurements, after additional cloud masking, the MOD/MYD11 Collection 6 surface-temperature standard product has an RMSE of 1.0 °C, spanning a range of temperatures from −35 °C to −5 °C. For our study area and time series, MODIS surface temperature products agree with skin surface temperatures better than previous studies indicated, especially at temperatures below −20 °C where other studies found a significant cold bias. The apparent cold bias present in others’ comparison of 2 m air temperature and MODIS surface temperature is perhaps a result of the near-surface temperature inversion that our data demonstrate. Further investigation of how in-situ IR skin temperatures compare to MODIS surface temperature at lower temperatures (below −35 °C) is warranted to determine if this cold bias does indeed exist.

Sign in / Sign up

Export Citation Format

Share Document