Constraining a physically based Soil-Vegetation-Atmosphere Transfer model with surface water content and thermal infrared brightness temperature measurements using a multiobjective approach

Abstract. The paper examines the stability of the relation between microwave emission from the soil and the average near-surface water content in the case of relatively smooth, bare soils, and then considers the extent to which microwave radiometry can be used to estimate the effective surface resistance to vapour transfer, which is also related to the near-surface water status. The analysis is based on the use of a model (MICRO-SWEAT) which couples a microwave radiative transfer model with a SVAT scheme that describes the exchanges of water vapour, energy and sensible heat at the land surface. Verification of MICRO-SWEAT showed good agreement (about 3K RMSE) between predicted L band (1.4 GHz) brightness temperature over soils with contrasting texture during a multi-day drydown, and those measured using a truck-mounted radiometer. There was good agreement between the measured and predicted relations between the average water content of the upper 2 cm of the soil profile and the brightness temperature normalised with respect to the radiometric surface temperature. Some of the scatter in this relationship was attributable to diurnal variation in the magnitude of near-surface gradients in temperature and water content, and could be accounted for by using the physically-based simulation model. The influence of soil texture on this relationship was well-simulated using MICRO-SWEAT. The paper concludes by demonstrating how MICRO-SWEAT can be used to establish a relationship between the normalised brightness temperature and the surface resistance for use in the prediction of evaporation using the Penman-Montheith equation.

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Feasibility study of cloud base height remote sensing by ground-based sky thermal infrared brightness temperature measurements

10.1117/12.619663 ◽

2005 ◽

Author(s):

Wenxing Zhang ◽

Daren Lu ◽

Youli Chang

Keyword(s):

Remote Sensing ◽

Brightness Temperature ◽

Feasibility Study ◽

Thermal Infrared ◽

Temperature Measurements ◽

Cloud Base ◽

Cloud Base Height ◽

Infrared Brightness

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A Physically Based Algorithm for Non-Blackbody Correction of Cloud-Top Temperature and Application to Convection Study

Journal of Applied Meteorology and Climatology ◽

10.1175/jamc-d-13-0331.1 ◽

2014 ◽

Vol 53 (7) ◽

pp. 1844-1857 ◽

Cited By ~ 7

Author(s):

Chunpeng Wang ◽

Zhengzhao Johnny Luo ◽

Xiuhong Chen ◽

Xiping Zeng ◽

Wei-Kuo Tao ◽

...

Keyword(s):

Brightness Temperature ◽

Weighting Function ◽

Convective Cloud ◽

Transfer Model ◽

Height Range ◽

Convective Clouds ◽

Physically Based ◽

Moderate Resolution Imaging Spectroradiometer ◽

The Difference ◽

Cloud Top Temperature

AbstractCloud-top temperature (CTT) is an important parameter for convective clouds and is usually different from the 11-μm brightness temperature due to non-blackbody effects. This paper presents an algorithm for estimating convective CTT by using simultaneous passive [Moderate Resolution Imaging Spectroradiometer (MODIS)] and active [CloudSat + Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO)] measurements of clouds to correct for the non-blackbody effect. To do this, a weighting function of the MODIS 11-μm band is explicitly calculated by feeding cloud hydrometer profiles from CloudSat and CALIPSO retrievals and temperature and humidity profiles based on ECMWF analyses into a radiation transfer model. Among 16 837 tropical deep convective clouds observed by CloudSat in 2008, the averaged effective emission level (EEL) of the 11-μm channel is located at optical depth ~0.72, with a standard deviation of 0.3. The distance between the EEL and cloud-top height determined by CloudSat is shown to be related to a parameter called cloud-top fuzziness (CTF), defined as the vertical separation between −30 and 10 dBZ of CloudSat radar reflectivity. On the basis of these findings a relationship is then developed between the CTF and the difference between MODIS 11-μm brightness temperature and physical CTT, the latter being the non-blackbody correction of CTT. Correction of the non-blackbody effect of CTT is applied to analyze convective cloud-top buoyancy. With this correction, about 70% of the convective cores observed by CloudSat in the height range of 6–10 km have positive buoyancy near cloud top, meaning clouds are still growing vertically, although their final fate cannot be determined by snapshot observations.

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Notice of Retraction: Research on the thermal infrared brightness temperature of the 2008 Ms7.3 earthquake in Yutian, Xinjiang of China

2010 Second IITA International Conference on Geoscience and Remote Sensing ◽

10.1109/iita-grs.2010.5603203 ◽

2010 ◽

Author(s):

Weidong Li ◽

Xinjian Shan

Keyword(s):

Brightness Temperature ◽

Thermal Infrared ◽

Xinjiang Of China ◽

Infrared Brightness

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Calibration of Special Sensor Microwave Imager/Sounder (SSMIS) upper air brightness temperature measurements using a comprehensive radiative transfer model

Radio Science ◽

10.1029/2005rs003329 ◽

2006 ◽

Vol 41 (4) ◽

pp. n/a-n/a ◽

Cited By ~ 10

Author(s):

Dana Xavier Kerola

Keyword(s):

Radiative Transfer ◽

Brightness Temperature ◽

Temperature Measurements ◽

Radiative Transfer Model ◽

Transfer Model ◽

Microwave Imager

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Kernel-driven model fitting of multi-angle thermal infrared brightness temperature and its application

JOURNAL OF INFRARED AND MILLIMETER WAVES ◽

10.3724/sp.j.1010.2011.00361 ◽

2012 ◽

Vol 30 (4) ◽

pp. 361-365 ◽

Cited By ~ 13

Author(s):

Jing-Jing PENG ◽

Qiang LIU ◽

Qin-Huo LIU ◽

Jia-Hong LI ◽

Hong-Zhang MA ◽

...

Keyword(s):

Brightness Temperature ◽

Model Fitting ◽

Thermal Infrared ◽

Infrared Brightness

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Validation of the Hurricane Imaging Radiometer Forward Radiative Transfer Model for a Convective Rain Event

Remote Sensing ◽

10.3390/rs11222650 ◽

2019 ◽

Vol 11 (22) ◽

pp. 2650

Author(s):

Abdusalam Alasgah ◽

Maria Jacob ◽

Linwood Jones ◽

Larry Schneider

Keyword(s):

Radiative Transfer ◽

Brightness Temperature ◽

Surface Wind ◽

Surface Wind Speed ◽

Temperature Measurements ◽

Radiative Transfer Model ◽

Squall Line ◽

Transfer Model ◽

Rain Event ◽

Brightness Temperatures

The airborne Hurricane Imaging Radiometer (HIRAD) was developed to remotely sense hurricane surface wind speed (WS) and rain rate (RR) from a high-altitude aircraft. The approach was to obtain simultaneous brightness temperature measurements over a wide frequency range to independently retrieve the WS and RR. In the absence of rain, the WS retrieval has been robust; however, for moderate to high rain rates, the joint WS/RR retrieval has not been successful. The objective of this paper was to resolve this issue by developing an improved forward radiative transfer model (RTM) for the HIRAD cross-track viewing geometry, with separated upwelling and specularly reflected downwelling atmospheric paths. Furthermore, this paper presents empirical results from an unplanned opportunity that occurred when HIRAD measured brightness temperatures over an intense tropical squall line, which was simultaneously observed by a ground based NEXRAD (Next Generation Weather Radar) radar. The independently derived NEXRAD RR created the simultaneous 3D rain field “surface truth”, which was used as an input to the RTM to generate HIRAD modeled brightness temperatures. This paper presents favorable results of comparisons of theoretical and the simultaneous, collocated HIRAD brightness temperature measurements that validate the accuracy of this new HIRAD RTM.

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