Estimating surface air temperatures, from Meteosat land surface temperatures, using an empirical solar zenith angle model

Cresswell, Mark; Morse, Andrew P.; Thomson, Madeleine C.; Connor, Stephen J.

doi:10.1080/014311699212885

Cited by 134 publications

(89 citation statements)

References 2 publications

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“…This method is based on the correlation between land surface temperature (T s ) and normalized difference vegetation index. The other is an empirical equation derived from statistical results for estimating air temperature (Cresswell et al, 1999). Stathopoulou et al (2006) and Vogt et al (1997) applied a simple linear regression to estimate daily mean (T a ) and maximum air temperature (T max ) based on NOAA-AVHRR T s and good agreements were obtained.…”

Section: Introductionmentioning

confidence: 99%

Daily mean air temperature estimation from MODIS land surface temperature products based on M5 model tree

Emamifar

Rahimikhoob

Noroozi

2013

Intl Journal of Climatology

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ABSTRACT:The use of satellite data to estimate air temperature (T a ) near the Earth's surface has become an effective way for a large area with high spatial and temporal resolution. In this study, M5 model tree was used to estimate T a in Khuzestan province (in the southwest of Iran) using satellite remotely sensed land surface temperature (T s ) data acquired by the MODerate Resolution Imaging Spectroradiometer (MODIS)-Terra sensor. The input variables for the M5 model tree were the daytime and nighttime MODIS T s , extraterrestrial solar radiation and Julian day. A total of 365 images of MOD11A1 T s product for the year 2007, covering the area of this study were collected from the Land Processes Distributed Active Archive Center (LP DAAC). The results of this study showed that mean daily T a can be estimated with acceptable levels of the statistical indicators from MODIS data and from the two geographic parameters using the M5 model. Root mean square error and R 2 for the comparison between observed and estimated T a for the tested data are 2.3 and 0.96 • C, respectively.KEY WORDS air temperature; M5 model tree; MODIS-Terra sensor; Iran

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Section: Introductionmentioning

confidence: 99%

Daily mean air temperature estimation from MODIS land surface temperature products based on M5 model tree

Emamifar

Rahimikhoob

Noroozi

2013

Intl Journal of Climatology

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“…11a). In this case, the temperatures obtained from the Meteosat-10 images are more than 5 K cooler relative to the IMS ground measurements and can be removed (Cresswell et al, 1999). Region B represents estimated GPS IWV values taken from stations in cloudy conditions but with a line of sight that does not intersect the clouds (Fig.…”

Section: Wv Estimation From Meteosat-10mentioning

confidence: 99%

“…This could lead to bias errors of up to 5 %, which corresponds to approximately 1 K in brightness temperature. Furthermore, the temperature values derived from Meteosat are an indication of reflected long-wave radiation rather than the true value of ambient air temperature, and they therefore also need to be adjusted (Cresswell et al, 1999). Nevertheless, the main advantage of using satellite data such as from Meteosat is the ability to obtain WV and surface temperature distribution on regional or global scale (Roca et al, 1997).…”

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confidence: 99%

“…The most common ones utilize radiosondes (Kley et al, 2000;Soden et al, 2004;Miloshevich et al, 2006), different techniques of GPS meteorology (Bevis et al, 1992(Bevis et al, , 1994Duan et al, 1996;Ware and Alber, 1997;Hagemann and Bengtsson, 2003;Vedel et al, 2004;Heise et al, 2009;Guerova et al, 2013;Hordyniec et al, 2015) or measurements from remote sensing satellites (Velden et al, 1997;Cresswell et al, 1999;Jiang et al, 2012). Radiosondes offer an essential component of the global observing system due to their extended lifetime and broad geographic coverage (Kley et al, 2000).…”

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confidence: 99%

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Combining Meteosat-10 satellite image data with GPS tropospheric path delays to estimate regional integrated water vapor (IWV) distribution

Leontiev

Reuveni

2017

Atmos. Meas. Tech.

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Abstract. Using GPS satellites signals, we can study different processes and coupling mechanisms that can help us understand the physical conditions in the lower atmosphere, which might lead or act as proxies for severe weather events such as extreme storms and flooding. GPS signals received by ground stations are multi-purpose and can also provide estimates of tropospheric zenith delays, which can be converted into accurate integrated water vapor (IWV) observations using collocated pressure and temperature measurements on the ground. Here, we present for the first time the use of Israel's dense regional GPS network for extracting tropospheric zenith path delays combined with near-realtime Meteosat-10 water vapor (WV) and surface temperature pixel intensity values (7.3 and 10.8 µm channels, respectively) in order to assess whether it is possible to obtain absolute IWV (kg m −2 ) distribution. The results show good agreement between the absolute values obtained from our triangulation strategy based solely on GPS zenith total delays (ZTD) and Meteosat-10 surface temperature data compared with available radiosonde IWV absolute values. The presented strategy can provide high temporal and special IWV resolution, which is needed as part of the accurate and comprehensive observation data integrated in modern data assimilation systems and is required for increasing the accuracy of regional numerical weather prediction systems forecast.

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“…obtained from weather station are used for ET estimation. Observation of these parameters over regional scale can be possible with high temporal resolution satellite remote sensing and proximal field based sensing systems (Prihodko and Gowrad 1997;Cresswell et al, 1999).…”

Section: Introductionmentioning

confidence: 99%

Time Series Analysis of Remote Sensing Observations for Citrus Crop Growth Stage and Evapotranspiration Estimation

Sawant¹,

Chakraborty²,

Suradhaniwar³

et al. 2016

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Satellite based earth observation (EO) platforms have proved capability to spatio-temporally monitor changes on the earth's surface. Long term satellite missions have provided huge repository of optical remote sensing datasets, and United States Geological Survey (USGS) Landsat program is one of the oldest sources of optical EO datasets. This historical and near real time EO archive is a rich source of information to understand the seasonal changes in the horticultural crops. Citrus (Mandarin / Nagpur Orange) is one of the major horticultural crops cultivated in central India. Erratic behaviour of rainfall and dependency on groundwater for irrigation has wide impact on the citrus crop yield. Also, wide variations are reported in temperature and relative humidity causing early fruit onset and increase in crop water requirement. Therefore, there is need to study the crop growth stages and crop evapotranspiration at spatio-temporal scale for managing the scarce resources. In this study, an attempt has been made to understand the citrus crop growth stages using Normalized Difference Time Series (NDVI) time series data obtained from Landsat archives (http://earthexplorer.usgs.gov/). Total 388 Landsat 4, 5, 7 and 8 scenes (from year 1990 to Aug. 2015) for Worldwide Reference System (WRS) 2, path 145 and row 45 were selected to understand seasonal variations in citrus crop growth. Considering Landsat 30 meter spatial resolution to obtain homogeneous pixels with crop cover orchards larger than 2 hectare area was selected. To consider change in wavelength bandwidth (radiometric resolution) with Landsat sensors (i.e. 4, 5, 7 and 8) NDVI has been selected to obtain continuous sensor independent time series. The obtained crop growth stage information has been used to estimate citrus basal crop coefficient information (Kcb). Satellite based Kcb estimates were used with proximal agrometeorological sensing system observed relevant weather parameters for crop ET estimation. The results show that time series EO based crop growth stage estimates provide better information about geographically separated citrus orchards. Attempts are being made to estimate regional variations in citrus crop water requirement for effective irrigation planning. In future high resolution Sentinel 2 observations from European Space Agency (ESA) will be used to fill the time gaps and to get better understanding about citrus crop canopy parameters.

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Estimating surface air temperatures, from Meteosat land surface temperatures, using an empirical solar zenith angle model

Cited by 134 publications

References 2 publications

Daily mean air temperature estimation from MODIS land surface temperature products based on M5 model tree

Daily mean air temperature estimation from MODIS land surface temperature products based on M5 model tree

Combining Meteosat-10 satellite image data with GPS tropospheric path delays to estimate regional integrated water vapor (IWV) distribution

Time Series Analysis of Remote Sensing Observations for Citrus Crop Growth Stage and Evapotranspiration Estimation

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