scholarly journals Multiparameter Spatiotemporal Anomalies with Some of the Strong Earthquakes (M > 6:0) in 2018 around the World

2019 ◽  
Author(s):  
Azad Rasul
Keyword(s):  
Wind Speed ◽  
Surface Temperature ◽  
Air Temperature ◽  
Land Surface ◽  
Earthquake Forecasting ◽  
Specific Humidity ◽  
Negative Anomaly ◽  
Positive Anomaly ◽  
The World ◽  
Before And After

One of the most destructive natural disasters is the earthquake which brings enormous risks to humankind. The objective of the current study was to determine the Earthquake’s remote sensing multiparameter (i.e. land surface temperature (LST), air temperature, specific humidity, precipitation and wind speed) spatiotemporal anomaly of many earthquake samples occurred during 2018 around the world. In this research 11 earthquake (M > 6:0) studied (4 samples selected in a land with transparent sky situations, 3 samples in land within cloudy situations and 4 samples in marine earthquakes). The interquartile range (IQR) and mean ± 2σ methods utilized to improve the efficiency of anomalous differences. As a result, based on the IQR method, negative anomaly before the event detected during the daytime in Mexico and during the nighttime in Afghanistan. In addition, a negative outlier of brightness temperature (BT) detected in Alaska before, after and during the event. In contrast, based on IQR and mean ± 2σ positive anomaly detected in precipitation before and after the event in all investigated examples. According to mean ± 2σ, negative anomaly LST, specific humidity, sea surface temperature (SST_100) and wind detected in most examined earthquake samples. In contrast, positive SST_0 anomaly observed in Fiji and Honduras after the earthquake. Our results suggested in marine earthquakes, for earthquake forecasting we can merge a prior negative anomaly in the wind speed and SST_100. Regarding the in land cloudy sky earthquakes, merging anomaly parameters could be the negative prior anomaly in BT, skin temperature, in contrast, a positive anomaly in precipitation. In land transparent sky earthquake, usually negative prior anomalies in air temperature, specific humidity and LST.

scholarly journals Land Surface Temperature Anomalies Detection for the Strong Earthquakes in 2018

2020 ◽  
Vol 8 (2) ◽  
pp. 15-21
Author(s):  
Azad Rasul ◽  
Luqman W. Omar
Keyword(s):  
Surface Temperature ◽  
Natural Disaster ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Negative Anomaly ◽  
Positive Anomaly ◽  
Strong Earthquakes ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

Earthquake every year leads to human and material losses and unpredictability of it by now makes this natural disaster worsen. The objective of the current study was to determine the anomalies in land surface temperature (LST) in areas affected by earthquakes. In this research, three earthquakes (M >6) were studied. Moderate Resolution Imaging Spectroradiometer Aqua and Terra day and night LST data used from 2003 to 2018. The interquartile range (IQR) and mean ± 2σ methods utilized to select anomalies. As a result, based on the IQR method, no prior and after anomaly detected in selected cases and data. Based on mean ± 2σ, usually positive anomaly occurred during daytime. However, negative (or positive) anomaly occurred during the nighttime before the Mexico and Bolivia earthquakes. During 10 days after the earthquake, sometimes a negative anomaly detected.

scholarly journals Observing Local-Scale Variability of Near-Surface Temperature and Humidity Using a Wireless Sensor Network

2012 ◽  
Vol 51 (1) ◽  
pp. 30-41 ◽  
Author(s):  
Katharina Lengfeld ◽  
Felix Ament
Keyword(s):  
Wireless Sensor Network ◽  
Wind Speed ◽  
Surface Temperature ◽  
Sensor Network ◽  
Air Temperature ◽  
Surface Air Temperature ◽  
Specific Humidity ◽  
Wireless Sensor ◽  
Near Surface ◽  
Single Station

AbstractIn this paper the influence of surface type, wind speed, and other environmental conditions on near-surface air temperature, specific humidity, and surface temperature is studied. A wireless sensor network consisting of 13 low-cost meteorological stations was set up as a 2.3-km-long double transect in western Germany during the Fluxes and Patterns in the Soil–Vegetation–Atmosphere Scheme (FLUXPAT2009) campaign. This deployment covered various surface types, including a small river. It was found that the air temperature was mainly influenced by the distance to the river and that its variability is controlled by the wind speed. During the night, a pool of cold air formed in the valley close to the water. The specific humidity is also governed by proximity to the river, especially during the night and for low wind speeds. In contrast, the differences in surface temperature were caused by different land cover. These results can be confirmed by a cluster analysis. Setting up 13 stations in a relatively small area is not always feasible. In this study, an estimation of the error that is made by considering the effect of a reduced number of stations is given. Use of only a single station results in an error of 0.86 K in air temperature, 0.67 g kg−1 in specific humidity, and 1.4 K in surface 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 An updated evaluation of the global mean land surface air temperature and surface temperature trends based on CLSAT and CMST

2021 ◽  
Vol 56 (1-2) ◽  
pp. 635-650 ◽  
Author(s):  
Qingxiang Li ◽  
Wenbin Sun ◽  
Xiang Yun ◽  
Boyin Huang ◽  
Wenjie Dong ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Air Temperature ◽  
Land Surface ◽  
Surface Air Temperature ◽  
Temperature Trends ◽  
Global Mean

scholarly journals Characterizing Surface and Air Temperature in the Baltic Sea Coastal Area Using Remote Sensing Techniques and Gis

2016 ◽  
Vol 23 (1) ◽  
pp. 3-11 ◽  
Author(s):  
Andrzej Chybicki ◽  
Marcin Kulawiak ◽  
Zbigniew Łubniewski
Keyword(s):  
Surface Temperature ◽  
Coastal Zone ◽  
Air Temperature ◽  
Land Surface ◽  
Vegetation Indices ◽  
Indirect Comparison ◽  
Surface Characteristics ◽  
Comparison Method ◽  
Effective Emissivity ◽  
Water Vapour Content

Abstract Estimation of surface temperature using multispectral imagery retrieved from satellite sensors constitutes several problems in terms of accuracy, accessibility, quality and evaluation. In order to obtain accurate results, currently utilized methods rely on removing atmospheric fluctuations in separate spectral windows, applying atmospheric corrections or utilizing additional information related to atmosphere or surface characteristics like atmospheric water vapour content, surface effective emissivity correction or transmittance correction. Obtaining accurate results of estimation is particularly critical for regions with fairly non-uniform distribution of surface effective emissivity and surface characteristics such as coastal zone areas. The paper presents the relationship between retrieved land surface temperature, air temperature, sea surface temperature and vegetation indices (VI) calculated based on remote observations in the coastal zone area. An indirect comparison method between remotely estimated surface temperature and air temperature using LST/VI feature space characteristics in an operational Geographic Information System is also presented.

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 Correlation and Causation Analysis Between COVID-19 and Environmental Factors in China

2021 ◽  
Vol 3 ◽  
Author(s):  
Zuofang Zheng ◽  
Junxia Dou ◽  
Conglan Cheng ◽  
Hua Gao
Keyword(s):  
Wind Speed ◽  
Air Temperature ◽  
Regional Climate ◽  
Climate Impact ◽  
Control Measures ◽  
Specific Humidity ◽  
Human Society ◽  
Causality Test ◽  
Low Wind Speed ◽  
Causation Analysis

Coronavirus disease 2019 (COVID-19) is seriously threatening and altering human society. Although prevention and control measures play an important role in preventing the transmission of severe acute respiratory syndrome coronavirus, signals of climate impact can still be detected globally. In this paper, the data of 265 cities in China were analyzed. The results show that the correlations between COVID-19 and air quality index (AQI) and PM2.5 concentration were very weak and that the correlations between COVID-19 and meteorological factors were significantly different in different climate backgrounds. So, a fixed model is not enough to describe the correlations. Overall, high humidity, low wind speed, and relatively lower air temperature are conducive to the spread of COVID-19. The climate background suitable for the spread of COVID-19 in China is air temperature 0~15°C, specific humidity <3 g kg−1, and wind speed <3 m s−1. The Granger causality test shows that there is a causal relationship between daily average air temperature and the number of COVID-19 confirmed cases in some cities of China, and air temperature is indicative of the number of confirmed cases the next day. However, this phenomenon is not universal due to regional climate differences.

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>

Sign in / Sign up

Export Citation Format

Share Document