Correcting for the influence of frozen lakes in satellite microwave radiometer observations through application of a microwave emission model

Abstract The Community Microwave Emission Model (CMEM) has been used to compute global L-band brightness temperatures at the top of the atmosphere. The input data comprise surface fields from the 40-yr ECMWF Re-Analysis (ERA-40), vegetation data from the ECOCLIMAP dataset, and the Food and Agriculture Organization’s (FAO) soil database. Modeled brightness temperatures have been compared against (historic) observations from the S-194 passive microwave radiometer onboard the Skylab space station. Different parameterizations for surface roughness and the vegetation optical depth have been used to calibrate the model. The best results have been obtained for rather simple approaches proposed by Wigneron et al. and Kirdyashev et al. The rms errors after calibration are 10.7 and 9.8 K for North and South America, respectively. Comparing the ERA-40 soil moisture product against the corresponding in situ observations suggests that the uncertainty in the modeled soil moisture is the predominant contributor to these rms errors. Although the bias between model and observed brightness temperatures are reduced after the calibration, systematic differences in the dynamic range remain. For NWP analysis applications, bias correction schemes should be applied prior to data assimilation. The calibrated model has been used to compute a 10-yr brightness temperature climatology based on ERA-40 data.

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Characterization of Errors in a Coupled Snow Hydrology–Microwave Emission Model

Journal of Hydrometeorology ◽

10.1175/2007jhm885.1 ◽

2008 ◽

Vol 9 (1) ◽

pp. 149-164 ◽

Cited By ~ 40

Author(s):

Konstantinos M. Andreadis ◽

Ding Liang ◽

Leung Tsang ◽

Dennis P. Lettenmaier ◽

Edward G. Josberger

Keyword(s):

Forest Cover ◽

Microwave Radiometer ◽

Coupled Model ◽

Microwave Remote Sensing ◽

Quantitative Information ◽

Microwave Emission ◽

Prediction Errors ◽

Emission Model ◽

Snow Hydrology ◽

Infiltration Capacity

Abstract Traditional approaches to the direct estimation of snow properties from passive microwave remote sensing have been plagued by limitations such as the tendency of estimates to saturate for moderately deep snowpacks and the effects of mixed land cover within remotely sensed pixels. An alternative approach is to assimilate satellite microwave emission observations directly, which requires embedding an accurate microwave emissions model into a hydrologic prediction scheme, as well as quantitative information of model and observation errors. In this study a coupled snow hydrology [Variable Infiltration Capacity (VIC)] and microwave emission [Dense Media Radiative Transfer (DMRT)] model are evaluated using multiscale brightness temperature (TB) measurements from the Cold Land Processes Experiment (CLPX). The ability of VIC to reproduce snowpack properties is shown with the use of snow pit measurements, while TB model predictions are evaluated through comparison with Ground-Based Microwave Radiometer (GBMR), aircraft [Polarimetric Scanning Radiometer (PSR)], and satellite [Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E)] TB measurements. Limitations of the model at the point scale were not as evident when comparing areal estimates. The coupled model was able to reproduce the TB spatial patterns observed by PSR in two of three sites. However, this was mostly due to the presence of relatively dense forest cover. An interesting result occurs when examining the spatial scaling behavior of the higher-resolution errors; the satellite-scale error is well approximated by the mode of the (spatial) histogram of errors at the smaller scale. In addition, TB prediction errors were almost invariant when aggregated to the satellite scale, while forest-cover fractions greater than 30% had a significant effect on TB predictions.

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Effects of Various parameters on Radiative Transfer Theory Based Microwave Emission Model

Journal of King Abdulaziz University-Meteorology Environment and Arid Land Agriculture Sciences ◽

10.4197/met.27-1.9 ◽

2017 ◽

Vol 27 (1) ◽

pp. 95-107

Author(s):

Mazen E. Assiri Mazen E. Assiri

Keyword(s):

Radiative Transfer ◽

Brightness Temperature ◽

Microwave Radiometer ◽

Microwave Emission ◽

Radiative Transfer Model ◽

Stem Volume ◽

Transfer Model ◽

Emission Model ◽

Radiative Transfer Theory ◽

Transfer Theory

This paper outlines research that is currently being carried out to model the interaction of electromagnetic radiation with earth and atmosphere. Among many others, passive microwave (PM) imagery represents a useful source of data for mapping Earth features. Since, signal of a microwave radiometer is composed of surface and atmospheric contributions, for proper interpretation of the data these effects should be quantified. This research presents analysis of radiative transfer model contributors, which include; the ground based parameters, forest area, water area, and meteorological parameters. The principal objective of this study is to analyze the degree to which brightness temperature can be affected by various earth and atmospheric features. A sensitivity analysis is performed to test the contributing effects of various parameters in radiative transfer theory based microwave emission model. The results of the study show that soil temperature and forest stem volume are the main contributing parameters in estimating brightness temperature values. The results further show that both the earthly located features and atmospheric parameters are important factors that must be taken into account in the development and application of radiative transfer theory based models

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MODELING X-BAND MICROWAVE RADIATION OF THE ARCTIC SEAS BASED ON SATELLITE OBSERVATIONS: TAKING INTO ACCOUNT A MEASUREMENT ANGLE

Meteorologiya i Gidrologiya ◽

10.52002/0130-2906-2021-4-69-77 ◽

2021 ◽

pp. 69-77

Author(s):

E. V. Zabolotskikh ◽

◽

B. Chapron ◽

◽

Keyword(s):

Wind Speed ◽

Microwave Radiation ◽

Microwave Radiometer ◽

Surface Wind ◽

Microwave Emission ◽

The Arctic ◽

Observation Angle ◽

Emission Model ◽

Arctic Seas ◽

X Band

The ocean X-band microwave emission model for modeling measurements of satellite radiometers over the cold Arctic seas at an observation angle of 65° is proposed. The model is based on the experimental geophysical model function (GMF) of microwave emission dependence on surface wind speed for an angle of 55°, that was developed from the AMSR2 (Advanced Microwave Scanning Radiometer 2) measurements and the two-scale theory of the ocean microwave radiation. The experimental GMF is derived from the comparison of AMSR2 measurements over the Arctic seas with surface wind speeds retrieved from these data. The model is limited by wind speed of 15 m/s and does not take into account the foam emission. The model allows discriminating between longwave and shortwave wind-induced microwave radiation and using the presented approach to proceed to the observation angle of the MTVZA-GYa (temperature and humidity atmospheric sounding unit) microwave radiometer on board the Meteor-M Russian polar orbiting satellites.

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Development of Microwave Emission Model for Frozen Soil with Considering the Volume Scattering Effect

IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium ◽

10.1109/igarss39084.2020.9323362 ◽

2020 ◽

Author(s):

Jian Wang ◽

Lingmei Jiang ◽

Xiaojing Liu ◽

Jianwei Yang

Keyword(s):

Frozen Soil ◽

Microwave Emission ◽

Emission Model ◽

Volume Scattering ◽

Scattering Effect

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Evaluation of the Effective Microstructure Parameter of the Microwave Emission Model of Layered Snowpack for Multiple-Layer Snow

Remote Sensing ◽

10.3390/rs13102012 ◽

2021 ◽

Vol 13 (10) ◽

pp. 2012

Author(s):

Yue Yu ◽

Jinmei Pan ◽

Jiancheng Shi

Keyword(s):

Process Model ◽

Mean Squared Error ◽

Weighted Average ◽

Single Layer ◽

Microwave Emission ◽

Emission Model ◽

Snow Layer ◽

Optimal Method ◽

Microstructure Parameter ◽

Multiple Layer

Natural snow, one of the most important components of the cryosphere, is fundamentally a layered medium. In forward simulation and retrieval, a single-layer effective microstructure parameter is widely used to represent the emission of multiple-layer snowpacks. However, in most cases, this parameter is fitted instead of calculated based on a physical theory. The uncertainty under different frequencies, polarizations, and snow conditions is uncertain. In this study, we explored different methods to reduce the layered snow properties to a set of single-layer values that can reproduce the same brightness temperature (TB) signal. A validated microwave emission model of layered snowpack (MEMLS) was used as the modelling tool. Multiple-layer snow TB from the snow’s surface was compared with the bulk TB of single-layer snow. The methods were tested using snow profile samples from the locally validated and global snow process model simulations, which follow the natural snow’s characteristics. The results showed that there are two factors that play critical roles in the stability of the bulk TB error, the single-layer effective microstructure parameter, and the reflectivity at the air–snow and snow–soil boundaries. It is important to use the same boundary reflectivity as the multiple-layer snow case calculated using the snow density at the topmost and bottommost layers instead of the average density. Afterwards, a mass-weighted average snow microstructure parameter can be used to calculate the volume scattering coefficient at 10.65 to 23.8 GHz. At 36.5 and 89 GHz, the effective microstructure parameter needs to be retrieved based on the product of the snow layer transmissivity. For thick snow, a cut-off threshold of 1/e is suggested to be used to include only the surface layers within the microwave penetration depth. The optimal method provides a root mean squared error of bulk TB of less than 5 K at 10.65 to 36.5 GHz and less than 10 K at 89 GHz for snow depths up to 130 cm.

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INFLUENCE OF REGULARITY OF SATELLITE MICROWAVE RADIOMETER MEASUREMENTS ON THE ACCURACY OF BRIGHTNESS TEMPERATURE REPRODUCTION IN AREAS OF THE TROPICAL CYCLONES

Meteorologiya i Gidrologiya ◽

10.52002/0130-2906-2021-4-78-85 ◽

2021 ◽

pp. 78-85

Author(s):

А. G. Grankov ◽

◽

А. А. Milshin ◽

Keyword(s):

Brightness Temperature ◽

Tropical Cyclones ◽

Microwave Radiometer ◽

Measurement Data ◽

Hurricane Wilma ◽

Brightness Temperatures ◽

Atmosphere System ◽

Ocean Atmosphere ◽

The Caribbean ◽

Satellite Microwave

An accuracy of reproduction of daily variations in the ocean–atmosphere system brightness temperature in the areas of development and movement of tropical hurricanes in the Caribbean Sea and Gulf of Mexico is analyzed. The analysis is based on the data of single and group satellite microwave radiometer measurements. The results are obtained using archival measurement data of SSM/I radiometers from the F11, F13, F14, and F15 DMSP satellites during the period of existence of tropical hurricanes Bret and Wilma. An example is given to demonstrate the use of daily brightness temperatures obtained from DMSP satellites for monitoring the development and propagation of hurricane Wilma.

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Analysis of Satellite Microwave Radiometer (SAMIR) data recorded from the Bhaskara-II satellite Comments on the paper by Rao et al. (1987)

International Journal of Remote Sensing ◽

10.1080/01431168908903963 ◽

1989 ◽

Vol 10 (7) ◽

pp. 1265-1267 ◽

Cited By ~ 1

Author(s):

P. N. PATHAK

Keyword(s):

Microwave Radiometer ◽

Satellite Microwave

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Modelling the L-Band Snow-Covered Surface Emission in a Winter Canadian Prairie Environment

Remote Sensing ◽

10.3390/rs10091451 ◽

2018 ◽

Vol 10 (9) ◽

pp. 1451 ◽

Cited By ~ 3

Author(s):

Alexandre Roy ◽

Marion Leduc-Leballeur ◽

Ghislain Picard ◽

Alain Royer ◽

Peter Toose ◽

...

Keyword(s):

Radiative Transfer ◽

Brightness Temperature ◽

Frozen Soil ◽

Microwave Emission ◽

Radiative Transfer Model ◽

Transfer Model ◽

Emission Model ◽

Canadian Prairie ◽

Seasonal Snow ◽

L Band

Detailed angular ground-based L-band brightness temperature (TB) measurements over snow covered frozen soil in a prairie environment were used to parameterize and evaluate an electromagnetic model, the Wave Approach for LOw-frequency MIcrowave emission in Snow (WALOMIS), for seasonal snow. WALOMIS, initially developed for Antarctic applications, was extended with a soil interface model. A Gaussian noise on snow layer thickness was implemented to account for natural variability and thus improve the TB simulations compared to observations. The model performance was compared with two radiative transfer models, the Dense Media Radiative Transfer-Multi Layer incoherent model (DMRT-ML) and a version of the Microwave Emission Model for Layered Snowpacks (MEMLS) adapted specifically for use at L-band in the original one-layer configuration (LS-MEMLS-1L). Angular radiometer measurements (30°, 40°, 50°, and 60°) were acquired at six snow pits. The root-mean-square error (RMSE) between simulated and measured TB at vertical and horizontal polarizations were similar for the three models, with overall RMSE between 7.2 and 10.5 K. However, WALOMIS and DMRT-ML were able to better reproduce the observed TB at higher incidence angles (50° and 60°) and at horizontal polarization. The similar results obtained between WALOMIS and DMRT-ML suggests that the interference phenomena are weak in the case of shallow seasonal snow despite the presence of visible layers with thicknesses smaller than the wavelength, and the radiative transfer model can thus be used to compute L-band brightness temperature.

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MEMLS3&a: Microwave Emission Model of Layered Snowpacks adapted to include backscattering

Geoscientific Model Development ◽

10.5194/gmd-8-2611-2015 ◽

2015 ◽

Vol 8 (8) ◽

pp. 2611-2626 ◽

Cited By ~ 18

Author(s):

M. Proksch ◽

C. Mätzler ◽

A. Wiesmann ◽

J. Lemmetyinen ◽

M. Schwank ◽

...

Keyword(s):

Microwave Remote Sensing ◽

Horizontal Layer ◽

Microwave Emission ◽

Emission Model ◽

Input Parameters ◽

Fitting Procedures ◽

Splitting Parameter ◽

Set Up ◽

Passive Measurements ◽

Active Microwave Remote Sensing

Abstract. The Microwave Emission Model of Layered Snowpacks (MEMLS) was originally developed for microwave emissions of snowpacks in the frequency range 5–100 GHz. It is based on six-flux theory to describe radiative transfer in snow including absorption, multiple volume scattering, radiation trapping due to internal reflection and a combination of coherent and incoherent superposition of reflections between horizontal layer interfaces. Here we introduce MEMLS3&a, an extension of MEMLS, which includes a backscatter model for active microwave remote sensing of snow. The reflectivity is decomposed into diffuse and specular components. Slight undulations of the snow surface are taken into account. The treatment of like- and cross-polarization is accomplished by an empirical splitting parameter q. MEMLS3&a (as well as MEMLS) is set up in a way that snow input parameters can be derived by objective measurement methods which avoid fitting procedures of the scattering efficiency of snow, required by several other models. For the validation of the model we have used a combination of active and passive measurements from the NoSREx (Nordic Snow Radar Experiment) campaign in Sodankylä, Finland. We find a reasonable agreement between the measurements and simulations, subject to uncertainties in hitherto unmeasured input parameters of the backscatter model. The model is written in Matlab and the code is publicly available for download through the following website: http://www.iapmw.unibe.ch/research/projects/snowtools/memls.html.

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