Using multi-timescale methods and satellite-derived land surface temperature for the interpolation of daily maximum air temperature in Oregon

2015 ◽  
Vol 35 (13) ◽  
pp. 3862-3878 ◽  
Author(s):  
Benoit Parmentier ◽  
Brian J. McGill ◽  
Adam M. Wilson ◽  
James Regetz ◽  
Walter Jetz ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Air Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Daily Maximum ◽  
Maximum Air Temperature

Spatial Hotspot Analysis of Bucharest’s Urban Heat Island (UHI) Using Modis Data

2018 ◽  
Vol 18 (1) ◽  
pp. 14-22 ◽  
Author(s):  
Georgiana Grigoraș ◽  
Bogdan Urițescu
Keyword(s):  
Surface Temperature ◽  
Air Temperature ◽  
Land Surface Temperature ◽  
Hot Spots ◽  
Land Surface ◽  
Hot Spot ◽  
Monitoring Network ◽  
Residential Areas ◽  
Hotspot Analysis ◽  
The City

Abstract The aim of the study is to find the relationship between the land surface temperature and air temperature and to determine the hot spots in the urban area of Bucharest, the capital of Romania. The analysis was based on images from both moderate-resolution imaging spectroradiometer (MODIS), located on both Terra and Aqua platforms, as well as on data recorded by the four automatic weather stations existing in the endowment of The National Air Quality Monitoring Network, from the summer of 2017. Correlation coefficients between land surface temperature and air temperature were higher at night (0.8-0.87) and slightly lower during the day (0.71-0.77). After the validation of satellite data with in-situ temperature measurements, the hot spots in the metropolitan area of Bucharest were identified using Getis-Ord spatial statistics analysis. It has been achieved that the “very hot” areas are grouped in the center of the city and along the main traffic streets and dense residential areas. During the day the "very hot spots” represent 33.2% of the city's surface, and during the night 31.6%. The area where the mentioned spots persist, falls into the "very hot spot" category both day and night, it represents 27.1% of the city’s surface and it is mainly represented by the city center.

scholarly journals Spring Frost Damage to Tea Plants Can Be Identified with Daily Minimum Air Temperatures Estimated by MODIS Land Surface Temperature Products

2021 ◽  
Vol 13 (6) ◽  
pp. 1177
Author(s):  
Peijuan Wang ◽  
Yuping Ma ◽  
Junxian Tang ◽  
Dingrong Wu ◽  
Hui Chen ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Air Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Frost Damage ◽  
Estimation Model ◽  
Spring Frost ◽  
Tea Plants ◽  
Elevation Model ◽  
Minimum Air Temperature

Tea (Camellia sinensis) is one of the most dominant economic plants in China and plays an important role in agricultural economic benefits. Spring tea is the most popular drink due to Chinese drinking habits. Although the global temperature is generally warming, spring frost damage (SFD) to tea plants still occurs from time to time, and severely restricts the production and quality of spring tea. Therefore, monitoring and evaluating the impact of SFD to tea plants in a timely and precise manner is a significant and urgent task for scientists and tea producers in China. The region designated as the Middle and Lower Reaches of the Yangtze River (MLRYR) in China is a major tea plantation area producing small tea leaves and low shrubs. This region was selected to study SFD to tea plants using meteorological observations and remotely sensed products. Comparative analysis between minimum air temperature (Tmin) and two MODIS nighttime land surface temperature (LST) products at six pixel-window scales was used to determine the best suitable product and spatial scale. Results showed that the LST nighttime product derived from MYD11A1 data at the 3 × 3 pixel window resolution was the best proxy for daily minimum air temperature. A Tmin estimation model was established using this dataset and digital elevation model (DEM) data, employing the standard lapse rate of air temperature with elevation. Model validation with 145,210 ground-based Tmin observations showed that the accuracy of estimated Tmin was acceptable with a relatively high coefficient of determination (R2 = 0.841), low root mean square error (RMSE = 2.15 °C) and mean absolute error (MAE = 1.66 °C), and reasonable normalized RMSE (NRMSE = 25.4%) and Nash–Sutcliffe model efficiency (EF = 0.12), with significantly improved consistency of LST and Tmin estimation. Based on the Tmin estimation model, three major cooling episodes recorded in the "Yearbook of Meteorological Disasters in China" in spring 2006 were accurately identified, and several highlighted regions in the first two cooling episodes were also precisely captured. This study confirmed that estimating Tmin based on MYD11A1 nighttime products and DEM is a useful method for monitoring and evaluating SFD to tea plants in the MLRYR. Furthermore, this method precisely identified the spatial characteristics and distribution of SFD and will therefore be helpful for taking effective preventative measures to mitigate the economic losses resulting from frost damage.

scholarly journals Near–surface air temperature and snow skin temperature comparison from CREST-SAFE station data with MODIS land surface temperature data

2015 ◽  
Vol 12 (8) ◽  
pp. 7665-7687 ◽  
Author(s):  
C. L. Pérez Díaz ◽  
T. Lakhankar ◽  
P. Romanov ◽  
J. Muñoz ◽  
R. Khanbilvardi ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Skin Temperature ◽  
Air Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Hydrological Cycle ◽  
Critical Role ◽  
Surface Air Temperature ◽  
Balance Model ◽  
Near Surface

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.

scholarly journals Role of vegetation in representing land surface temperature in the CHTESSEL (CY45R1) and SURFEX-ISBA (v8.1) land surface models: a case study over Iberia

2020 ◽  
Vol 13 (9) ◽  
pp. 3975-3993 ◽  
Author(s):  
Miguel Nogueira ◽  
Clément Albergel ◽  
Souhail Boussetta ◽  
Frederico Johannsen ◽  
Isabel F. Trigo ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Vegetation Cover ◽  
Land Surface ◽  
Added Value ◽  
Vegetation Coverage ◽  
Daily Maximum ◽  
Cold Bias ◽  
Weather Forecasts ◽  
Surface Models

Abstract. Earth observations were used to evaluate the representation of land surface temperature (LST) and vegetation coverage over Iberia in two state-of-the-art land surface models (LSMs) – the European Centre for Medium-Range Weather Forecasts (ECMWF) Carbon-Hydrology Tiled ECMWF Scheme for Surface Exchanges over Land (CHTESSEL) and the Météo-France Interaction between Soil Biosphere and Atmosphere model (ISBA) within the SURface EXternalisée modeling platform (SURFEX-ISBA) for the 2004–2015 period. The results showed that the daily maximum LST simulated by CHTESSEL over Iberia was affected by a large cold bias during summer months when compared against the Satellite Application Facility on Land Surface Analysis (LSA-SAF), reaching magnitudes larger than 10 ∘C over wide portions of central and southwestern Iberia. This error was shown to be tightly linked to a misrepresentation of the vegetation cover.  In contrast, SURFEX simulations did not display such a cold bias. We show that this was due to the better representation of vegetation cover in SURFEX, which uses an updated land cover dataset (ECOCLIMAP-II) and an interactive vegetation evolution, representing seasonality. The representation of vegetation over Iberia in CHTESSEL was improved by combining information from the European Space Agency Climate Change Initiative (ESA-CCI) land cover dataset with the Copernicus Global Land Service (CGLS) leaf area index (LAI) and fraction of vegetation coverage (FCOVER). The proposed improvement in vegetation also included a clumping approach that introduces seasonality to the vegetation cover. The results showed significant added value, removing the daily maximum LST summer cold bias completely, without reducing the accuracy of the simulated LST, regardless of season or time of the day. The striking performance differences between SURFEX and CHTESSEL were fundamental to guiding the developments in CHTESSEL highlighting the importance of using different models. This work has important implications: first, it takes advantage of LST, a key variable in surface–atmosphere energy and water exchanges, which is closely related to satellite top-of-atmosphere observations, to improve the model's representation of land surface processes. Second, CHTESSEL is the land surface model employed by ECMWF in the production of their weather forecasts and reanalysis; hence systematic errors in land surface variables and fluxes are then propagated into those products. Indeed, we showed that the summer daily maximum LST cold bias over Iberia in CHTESSEL is present in the widely used ECMWF fifth-generation reanalysis (ERA5). Finally, our results provided hints about the interaction between vegetation land–atmosphere exchanges, highlighting the relevance of the vegetation cover and respective seasonality in representing land surface temperature in both CHTESSEL and SURFEX. As a whole, this work demonstrated the added value of using multiple earth observation products for constraining and improving weather and climate simulations.

Recent Trends in Land Surface Temperature on the Tibetan Plateau

2006 ◽  
Vol 19 (12) ◽  
pp. 2995-3003 ◽  
Author(s):  
Yuichiro Oku ◽  
Hirohiko Ishikawa ◽  
Shigenori Haginoya ◽  
Yaoming Ma
Keyword(s):  
Tibetan Plateau ◽  
Surface Temperature ◽  
Air Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Precipitation Amount ◽  
Surface Air Temperature ◽  
The Tibetan Plateau ◽  
Near Surface ◽  
Diurnal Range

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.

Study on Urban Thermal Environment based on Diurnal Temperature Range

2020 ◽  
Author(s):  
Zheng Guo ◽  
Miaomiao Cheng
Keyword(s):  
Surface Temperature ◽  
Air Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Thermal Environment ◽  
Surface Air Temperature ◽  
Heat Island ◽  
Near Surface ◽  
Diurnal Range ◽  
Urban Thermal Environment

<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>

scholarly journals Estimation of Daily Air Temperature Based on MODIS Land Surface Temperature Products over the Corn Belt in the US

2015 ◽  
Vol 7 (1) ◽  
pp. 951-970 ◽  
Author(s):  
Linglin Zeng ◽  
Brian Wardlow ◽  
Tsegaye Tadesse ◽  
Jie Shan ◽  
Michael Hayes ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Air Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Corn Belt ◽  
Modis Land Surface Temperature ◽  
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