Comparisons of emissivity observations from satellites and the ground at the CRCS Dunhuang Gobi site

Yong, Zhang; Li, Zhenglong; Li, Jun

doi:10.1002/2014jd022216

Cited by 8 publications

(3 citation statements)

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“…However, hourly emissivity spectra that define the diurnal variation would be very useful for improving longwave radiation calculations in numerical models (Jin and Liang 2006). The diurnal variation of surface emissivity was first revealed by Li et al (2012) using Spinning Enhanced Visible and InfraRed Imager (SEVIRI), and later was verified with ground-based measurements (Zhang et al 2014). Compared to GEO imager measurements that can only provide emissivity at limited broad bands, GeoHIS measurements offer the opportunity for deriving hourly hyperspectral IR emissivity spectra using a physically based retrieval method (Li et al 2007;.…”

Section: Future Perspectives On the Applications Of Geohismentioning

confidence: 92%

Applications of Geostationary Hyperspectral Infrared Sounder Observations: Progress, Challenges, and Future Perspectives

Menzel

Schmit

et al. 2022

Bulletin of the American Meteorological Society

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A hyperspectral infrared (IR) sounder from geostationary orbit provides nearly continuous measurements of atmospheric thermodynamic and dynamic information within a weather cube, specifically the atmospheric temperature, moisture, and wind information at different pressure levels that are critical for improving high impact weather (HIW) nowcasting and numerical weather prediction (NWP). Geostationary hyperspectral IR sounders (GeoHIS) have been onboard China’s Fengyun-4 series since 2016 and will be onboard Europe’s Meteosat Third Generation (MTG) series in the 2024 time frame; the U.S. and other countries are also planning to include GeoHIS instruments on their next generation of geostationary weather satellites. Although availability of on-orbit GeoHIS data are limited currently, studies have been conducted and progress has been made on developing the applications of high temporal resolution GeoHIS observations. These include but are not limited to deriving three-dimensional wind fields for nowcasting and NWP applications, trending atmospheric instability for warning in pre-convective environments, conducting impact studies with data from the experimental Geostationary Interferometric Infrared Sounder (GIIRS) onboard Fengyun-4A, preparing observing system simulation experiments (OSSEs), and monitoring diurnal variation of atmospheric composition. This paper provides an overview of the current applications of GeoHIS, discusses the data processing challenges, and provides perspectives on future development. The purpose is to provide direction on utilization of the current and assist preparation for the upcoming GeoHIS observations for nowcasting, NWP and other applications.

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Section: Future Perspectives On the Applications Of Geohismentioning

confidence: 92%

Applications of Geostationary Hyperspectral Infrared Sounder Observations: Progress, Challenges, and Future Perspectives

Menzel

Schmit

et al. 2022

Bulletin of the American Meteorological Society

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“…The direct method to estimate surface emissivity in the laboratory experiment involves the comparison of the radiant temperature between the measured samples and blackbody. However, direct measurement of surface emissivity in the field is practically difficult due to cost and instrumental system [ 31 , 46 , 47 , 48 , 49 , 50 ]. For known values of the T s (here by thermocouple) and T b (by IRT), the surface emissivity can be estimated using Equation (2) as

…”

Section: Methodsmentioning

confidence: 99%

Intercomparison of In Situ Sensors for Ground-Based Land Surface Temperature Measurements

Krishnan

Meyers

Hook

et al. 2020

Sensors

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Land surface temperature (LST) is a key variable in the determination of land surface energy exchange processes from local to global scales. Accurate ground measurements of LST are necessary for a number of applications including validation of satellite LST products or improvement of both climate and numerical weather prediction models. With the objective of assessing the quality of in situ measurements of LST and to evaluate the quantitative uncertainties in the ground-based LST measurements, intensive field experiments were conducted at NOAA’s Air Resources Laboratory (ARL)’s Atmospheric Turbulence and Diffusion Division (ATDD) in Oak Ridge, Tennessee, USA, from October 2015 to January 2016. The results of the comparison of LSTs retrieved by three narrow angle broadband infrared temperature sensors (IRT), hemispherical longwave radiation (LWR) measurements by pyrgeometers, forward looking infrared camera with direct LSTs by multiple thermocouples (TC), and near surface air temperature (AT) are presented here. The brightness temperature (BT) measurements by the IRTs agreed well with a bias of <0.23 °C, and root mean square error (RMSE) of <0.36 °C. The daytime LST(TC) and LST(IRT) showed better agreement (bias = 0.26 °C and RMSE = 0.67 °C) than with LST(LWR) (bias > 1.1 and RMSE > 1.46 °C). In contrast, the difference between nighttime LSTs by IRTs, TCs, and LWR were <0.47 °C, whereas nighttime AT explained >81% of the variance in LST(IRT) with a bias of 2.64 °C and RMSE of 3.6 °C. To evaluate the annual and seasonal differences in LST(IRT), LST(LWR) and AT, the analysis was extended to four grassland sites in the USA. For the annual dataset of LST, the bias between LST (IRT) and LST (LWR) was <0.7 °C, except at the semiarid grassland (1.5 °C), whereas the absolute bias between AT and LST at the four sites were <2 °C. The monthly difference between LST (IRT) and LST (LWR) (or AT) reached up to 2 °C (5 °C), whereas half-hourly differences between LSTs and AT were several degrees in magnitude depending on the site characteristics, time of the day and the season.

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“…LSE is important to obtain the LST 24,25 . LSE could be estimated by using physical modeling method 26 ; the MODIS LSE data 27,28 are also used widely and assimilated into the land surface models. The LST and soil moisture are the prognostic variables of the surface energy and water balance model.…”

Section: Introductionmentioning

confidence: 99%

Assimilating Satellite Land Surface States Data from Fengyun-4A

Meng

2019

Sci Rep

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Fengyun-4A is the new generation of Chinese geostationary meteorological satellites. Land surface albedo, land surface emissivity and land surface temperature are key states for land surface modelling. In this paper, the land surface albedo, land surface emissivity and land surface temperature data from Fengyun-4A were assimilated into the Integrated Urban land Model. The Fengyun-4A data are one of the data sources for the land data assimilation system which devoted to produce the high spatial and temporal resolution, multiple parameters near real-time land data sets. The Moderate-Resolution Imaging Spectroradiometer (MODIS) LSA and LSE data, the Institute of Atmospheric Physics, China Academy of Sciences (IAP) 325 m tower observation data and the observed 5 cm and 10 cm soil temperature data in more than 100 sites are used for validation. The results indicate the MODIS land surface albedo is much smaller than the Fengyun-4A and is superior to the Fengyun-4A for the Institute of Atmospheric Physics, China Academy of Sciences 325 m tower site. The Moderate-Resolution Imaging Spectroradiometer land surface emissivity is smaller than the Fengyun-4A in barren land surface and the differences is relatively small for other land use and land cover categories. In most regions of the research area, the Fengyun-4A land surface albedo and land surface emissivity are larger than those of the simulations. After the land surface albedo assimilation, in most regions the simulated net radiation was decreased. After the land surface emissivity assimilation, in most regions the simulated net radiation was increased. After the land surface temperature assimilation, the biases of the land surface temperature were decreased apparently; the biases of the daily average 5 cm and 10 cm soil temperature were decreased.

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Comparisons of emissivity observations from satellites and the ground at the CRCS Dunhuang Gobi site

Cited by 8 publications

References 65 publications

Applications of Geostationary Hyperspectral Infrared Sounder Observations: Progress, Challenges, and Future Perspectives

Applications of Geostationary Hyperspectral Infrared Sounder Observations: Progress, Challenges, and Future Perspectives

Intercomparison of In Situ Sensors for Ground-Based Land Surface Temperature Measurements

Assimilating Satellite Land Surface States Data from Fengyun-4A

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