scholarly journals Spatiotemporal Variability of Heat Storage in Major U.S. Cities—A Satellite-Based Analysis

2020 ◽  
Vol 13 (1) ◽  
pp. 59
Author(s):  
Joshua Hrisko ◽  
Prathap Ramamurthy ◽  
David Melecio-Vázquez ◽  
Jorge E. Gonzalez
Keyword(s):  
New York ◽  
Energy Balance ◽  
Surface Energy ◽  
Surface Temperature ◽  
Land Surface ◽  
Surface Energy Balance ◽  
Heat Storage ◽  
Numerical Weather ◽  
Numerical Weather Model ◽  
Weather Model

Heat storage, ΔQs, is quantified for 10 major U.S. cities using a method called the thermal variability scheme (TVS), which incorporates urban thermal mass parameters and the variability of land surface temperatures. The remotely sensed land surface temperature (LST) is retrieved from the GOES-16 satellite and is used in conjunction with high spatial resolution land cover and imperviousness classes. New York City is first used as a testing ground to compare the satellite-derived heat storage model to two other methods: a surface energy balance (SEB) residual derived from numerical weather model fluxes, and a residual calculated from ground-based eddy covariance flux tower measurements. The satellite determination of ΔQs was found to fall between the residual method predicted by both the numerical weather model and the surface flux stations. The GOES-16 LST was then downscaled to 1-km using the WRF surface temperature output, which resulted in a higher spatial representation of storage heat in cities. The subsequent model was used to predict the total heat stored across 10 major urban areas across the contiguous United States for August 2019. The analysis presents a positive correlation between population density and heat storage, where higher density cities such as New York and Chicago have a higher capacity to store heat when compared to lower density cities such as Houston or Dallas. Application of the TVS ultimately has the potential to improve closure of the urban surface energy balance.

scholarly journals Impact of Increasing Urban Density on Local Climate: Spatial and Temporal Variations in the Surface Energy Balance in Melbourne, Australia

2007 ◽  
Vol 46 (4) ◽  
pp. 477-493 ◽  
Author(s):  
Andrew M. Coutts ◽  
Jason Beringer ◽  
Nigel J. Tapper
Keyword(s):  
Energy Balance ◽  
Surface Energy ◽  
Land Surface ◽  
Surface Energy Balance ◽  
Heat Storage ◽  
Surface Characteristics ◽  
Housing Density ◽  
Local Climate ◽  
Urban Sites ◽  
Land Surface Characteristics

Abstract Variations in urban surface characteristics are known to alter the local climate through modification of land surface processes that influence the surface energy balance and boundary layer and lead to distinct urban climates. In Melbourne, Australia, urban densities are planned to increase under a new strategic urban plan. Using the eddy covariance technique, this study aimed to determine the impact of increasing housing density on the surface energy balance and to investigate the relationship to Melbourne’s local climate. Across four sites of increasing housing density and varying land surface characteristics (three urban and one rural), it was found that the partitioning of available energy was similar at all three urban sites. Bowen ratios were consistently greater than 1 throughout the year at the urban sites (often as high as 5) and were higher than the rural site (less than 1) because of reduced evapotranspiration. The greatest difference among sites was seen in urban heat storage, which was influenced by urban canopy complexity, albedo, and thermal admittance. Resulting daily surface temperatures were therefore different among the urban sites, yet differences in above-canopy daytime air temperatures were small because of similar energy partitioning and efficient mixing. However, greater nocturnal temperatures were observed with increasing density as a result of variations in heat storage release that are in part due to urban canyon morphology. Knowledge of the surface energy balance is imperative for urban planning schemes because there is a possibility for manipulation of land surface characteristics for improved urban climates.

scholarly journals Regional evapotranspiration from an image-based implementation of the Surface Temperature Initiated Closure (STIC1.2) model and its validation across an aridity gradient in the conterminous US

2018 ◽  
Vol 22 (4) ◽  
pp. 2311-2341 ◽  
Author(s):  
Nishan Bhattarai ◽  
Kaniska Mallick ◽  
Nathaniel A. Brunsell ◽  
Ge Sun ◽  
Meha Jain
Keyword(s):  
Energy Balance ◽  
Surface Energy ◽  
Surface Temperature ◽  
Land Surface ◽  
Surface Energy Balance ◽  
Regional Scale ◽  
Absolute Error ◽  
Error Statistics ◽  
Aridity Gradient ◽  
Balance System

Abstract. Recent studies have highlighted the need for improved characterizations of aerodynamic conductance and temperature (gA and T0) in thermal remote-sensing-based surface energy balance (SEB) models to reduce uncertainties in regional-scale evapotranspiration (ET) mapping. By integrating radiometric surface temperature (TR) into the Penman–Monteith (PM) equation and finding analytical solutions of gA and T0, this need was recently addressed by the Surface Temperature Initiated Closure (STIC) model. However, previous implementations of STIC were confined to the ecosystem-scale using flux tower observations of infrared temperature. This study demonstrates the first regional-scale implementation of the most recent version of the STIC model (STIC1.2) that integrates the Moderate Resolution Imaging Spectroradiometer (MODIS) derived TR and ancillary land surface variables in conjunction with NLDAS (North American Land Data Assimilation System) atmospheric variables into a combined structure of the PM and Shuttleworth–Wallace (SW) framework for estimating ET at 1 km × 1 km spatial resolution. Evaluation of STIC1.2 at 13 core AmeriFlux sites covering a broad spectrum of climates and biomes across an aridity gradient in the conterminous US suggests that STIC1.2 can provide spatially explicit ET maps with reliable accuracies from dry to wet extremes. When observed ET from one wet, one dry, and one normal precipitation year from all sites were combined, STIC1.2 explained 66 % of the variability in observed 8-day cumulative ET with a root mean square error (RMSE) of 7.4 mm/8-day, mean absolute error (MAE) of 5 mm/8-day, and percent bias (PBIAS) of −4 %. These error statistics showed relatively better accuracies than a widely used but previous version of the SEB-based Surface Energy Balance System (SEBS) model, which utilized a simple NDVI-based parameterization of surface roughness (zOM), and the PM-based MOD16 ET. SEBS was found to overestimate (PBIAS = 28 %) and MOD16 was found to underestimate ET (PBIAS = −26 %). The performance of STIC1.2 was better in forest and grassland ecosystems as compared to cropland (20 % underestimation) and woody savanna (40 % overestimation). Model inter-comparison suggested that ET differences between the models are robustly correlated with gA and associated roughness length estimation uncertainties which are intrinsically connected to TR uncertainties, vapor pressure deficit (DA), and vegetation cover. A consistent performance of STIC1.2 in a broad range of hydrological and biome categories, as well as the capacity to capture spatio-temporal ET signatures across an aridity gradient, points to the potential for this simplified analytical model for near-real-time ET mapping from regional to continental scales.

scholarly journals Reconnoitering the effect of shallow groundwater on land surface temperature and surface energy balance using MODIS and SEBS

2012 ◽  
Vol 16 (7) ◽  
pp. 1833-1844 ◽  
Author(s):  
F. Alkhaier ◽  
Z. Su ◽  
G. N. Flerchinger
Keyword(s):  
Energy Balance ◽  
Surface Energy ◽  
Surface Temperature ◽  
Water Table ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Surface Energy Balance ◽  
Shallow Groundwater ◽  
Companion Paper ◽  
Daily Evaporation

Abstract. The possibility of observing shallow groundwater depth and areal extent using satellite measurements can support groundwater models and vast irrigation systems management. Moreover, these measurements can help to include the effect of shallow groundwater on surface energy balance within land surface models and climate studies, which broadens the methods that yield more reliable and informative results. To examine the capacity of MODIS in detecting the effect of shallow groundwater on land surface temperature and the surface energy balance in an area within Al-Balikh River basin in northern Syria, we studied the interrelationship between in-situ measured water table depths and land surface temperatures measured by MODIS. We, also, used the Surface Energy Balance System (SEBS) to calculate surface energy fluxes, evaporative fraction and daily evaporation, and inspected their relationships with water table depths. We found out that the daytime temperature increased while the nighttime temperature decreased when the depth of the water table increased. And, when the water table depth increased, net radiation, latent and ground heat fluxes, evaporative fraction and daily evaporation decreased, while sensible heat flux increased. This concords with the findings of a companion paper (Alkhaier et al., 2012). The observed clear relationships were the result of meeting both conditions that were concluded in the companion paper, i.e. high potential evaporation and big contrast in day-night temperature. Moreover, the prevailing conditions in this study area helped SEBS to yield accurate estimates. Under bare soil conditions and under the prevailing weather conditions, we conclude that MODIS is suitable for detecting the effect of shallow groundwater because it has proper imaging times and adequate sensor accuracy; nevertheless, its coarse spatial resolution is disadvantageous.

scholarly journals An All-Weather Land Surface Temperature Product Based on MSG/SEVIRI Observations

2019 ◽  
Vol 11 (24) ◽  
pp. 3044 ◽  
Author(s):  
João P. A. Martins ◽  
Isabel F. Trigo ◽  
Nicolas Ghilain ◽  
Carlos Jimenez ◽  
Frank-M. Göttsche ◽  
...  
Keyword(s):  
Energy Balance ◽  
Surface Energy ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Surface Energy Balance ◽  
New Product ◽  
Tropical Regions ◽  
Earth Observing System

A new all-weather land surface temperature (LST) product derived at the Satellite Application Facility on Land Surface Analysis (LSA-SAF) is presented. It is the first all-weather LST product based on visible and infrared observations combining clear-sky LST retrieved from the Spinning Enhanced Visible and Infrared Imager on Meteosat Second Generation (MSG/SEVIRI) infrared (IR) measurements with LST estimated with a land surface energy balance (EB) model to fill gaps caused by clouds. The EB model solves the surface energy balance mostly using products derived at LSA-SAF. The new product is compared with in situ observations made at 3 dedicated validation stations, and with a microwave (MW)-based LST product derived from Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) measurements. The validation against in-situ LST indicates an accuracy of the new product between -0.8 K and 1.1 K and a precision between 1.0 K and 1.4 K, generally showing a better performance than the MW product. The EB model shows some limitations concerning the representation of the LST diurnal cycle. Comparisons with MW LST generally show higher LST of the new product over desert areas, and lower LST over tropical regions. Several other imagers provide suitable measurements for implementing the proposed methodology, which offers the potential to obtain a global, nearly gap-free LST product.

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