Global Long-Term Brightness Temperature Record from L-Band SMOS and Smap Observations

Author(s):  
Xiaojun Li ◽  
J.-P. Wigncron ◽  
F. Frappart ◽  
Lei Fan ◽  
Gabrielle De Lannoy ◽  
...  
2020 ◽  
Vol 12 (12) ◽  
pp. 1915
Author(s):  
Joe K. Taylor ◽  
Henry E. Revercomb ◽  
Fred A. Best ◽  
David C. Tobin ◽  
P. Jonathan Gero

The Absolute Radiance Interferometer (ARI) is an infrared spectrometer designed to serve as an on-orbit radiometric reference with the ultra-high accuracy (better than 0.1 K 3‑σ or k = 3 brightness temperature at scene brightness temperature) needed to optimize measurement of the long-term changes of Earth’s atmosphere and surface. If flown in an orbit that frequently crosses sun-synchronous orbits, ARI could be used to inter-calibrate the international fleet of infrared (IR) hyperspectral sounders to similar measurement accuracy, thereby establishing an observing system capable of achieving sampling biases on high-information-content spectral radiance products that are also < 0.1 K 3‑σ. It has been shown that such a climate observing system with <0.1 K 2‑σ overall accuracy would make it possible to realize times to detect subtle trends of temperature and water vapor distributions that closely match those of an ideal system, given the limit set by the natural variability of the atmosphere. This paper presents the ARI sensor's overall design, the new technologies developed to allow on-orbit verification and test of its accuracy, and the laboratory results that demonstrate its capability. In addition, we describe the techniques and uncertainty estimates for transferring ARI accuracy to operational sounders, providing economical global coverage. Societal challenges posed by climate change suggest that a Pathfinder ARI should be deployed as soon as possible.


2018 ◽  
Vol 10 (9) ◽  
pp. 1451 ◽  
Author(s):  
Alexandre Roy ◽  
Marion Leduc-Leballeur ◽  
Ghislain Picard ◽  
Alain Royer ◽  
Peter Toose ◽  
...  

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.


2019 ◽  
Author(s):  
Maciej Miernecki ◽  
Lars Kaleschke ◽  
Nina Maaß ◽  
Stefan Hendricks ◽  
Sten Schmidl Søbjrg

Abstract. Sea ice thickness measurements with L-band radiometry is a technique which allows daily, weather-independent monitoring of the polar sea ice cover. The sea-ice thickness retrieval algorithms relay on the sensitivity of the L-band brightness temperature to sea-ice thickness. In this work, we investigate the decimetre-scale surface roughness as a factor influencing the L-band emissions from sea ice. We used an airborne laser scanner to construct a digital elevation model of the sea ice surface. We found that the probability density function of surface slopes is exponential for a range of degrees of roughness. Then we applied the geometrical optics, bounded with the MIcrowave L-band LAyered Sea ice emission model in the Monte Carlo simulation to simulate the effects of surface roughness. According to this simulations, the most affected by surface roughness is the vertical polarization around Brewster's angle, where the decrease in brightness temperature can reach 8 K. The vertical polarization for the same configuration exhibits a 4 K increase. The near-nadir angles are little affected, up to 2.6 K decrease for the most deformed ice. Overall the effects of large-scale surface roughness can be expressed as a superposition of two factors: the change in intensity and the polarization mixing. The first factor depends on surface permittivity, second shows little dependence on it. Comparison of the brightness temperature simulations with the radiometer data does not yield definite results.


2020 ◽  
Vol 12 (4) ◽  
pp. 650
Author(s):  
Pablo Sánchez-Gámez ◽  
Carolina Gabarro ◽  
Antonio Turiel ◽  
Marcos Portabella

The European Space Agency (ESA) Soil Moisture and Ocean Salinity (SMOS) and the National Aeronautics and Space Administration (NASA) Soil Moisture Active Passive (SMAP) missions are providing brightness temperature measurements at 1.4 GHz (L-band) for about 10 and 4 years respectively. One of the new areas of geophysical exploitation of L-band radiometry is on thin (i.e., less than 1 m) Sea Ice Thickness (SIT), for which theoretical and empirical retrieval methods have been proposed. However, a comprehensive validation of SIT products has been hindered by the lack of suitable ground truth. The in-situ SIT datasets most commonly used for validation are affected by one important limitation: They are available mainly during late winter and spring months, when sea ice is fully developed and the thickness probability density function is wider than for autumn ice and less representative at the satellite spatial resolution. Using Upward Looking Sonar (ULS) data from the Woods Hole Oceanographic Institution (WHOI), acquired all year round, permits overcoming the mentioned limitation, thus improving the characterization of the L-band brightness temperature response to changes in thin SIT. State-of-the-art satellite SIT products and the Cumulative Freezing Degree Days (CFDD) model are verified against the ULS ground truth. The results show that the L-band SIT can be meaningfully retrieved up to 0.6 m, although the signal starts to saturate at 0.3 m. In contrast, despite the simplicity of the CFDD model, its predicted SIT values correlate very well with the ULS in-situ data during the sea ice growth season. The comparison between the CFDD SIT and the current L-band SIT products shows that both the sea ice concentration and the season are fundamental factors influencing the quality of the thickness retrieval from L-band satellites.


2020 ◽  
Vol 12 (18) ◽  
pp. 3098
Author(s):  
Jongmin Park ◽  
Barton A. Forman ◽  
Rolf H. Reichle ◽  
Gabrielle De Lannoy ◽  
Saad B. Tarik

L-band brightness temperature (Tb) is one of the key remotely-sensed variables that provides information regarding surface soil moisture conditions. In order to harness the information in Tb observations, a radiative transfer model (RTM) is investigated for eventual inclusion into a data assimilation framework. In this study, Tb estimates from the RTM implemented in the NASA Goddard Earth Observing System (GEOS) were evaluated against the nearly four-year record of daily Tb observations collected by L-band radiometers onboard the Aquarius satellite. Statistics between the modeled and observed Tb were computed over North America as a function of soil hydraulic properties and vegetation types. Overall, statistics showed good agreement between the modeled and observed Tb with a relatively low, domain-average bias (0.79 K (ascending) and −2.79 K (descending)), root mean squared error (11.0 K (ascending) and 11.7 K (descending)), and unbiased root mean squared error (8.14 K (ascending) and 8.28 K (descending)). In terms of soil hydraulic parameters, large porosity and large wilting point both lead to high uncertainty in modeled Tb due to the large variability in dielectric constant and surface roughness used by the RTM. The performance of the RTM as a function of vegetation type suggests better agreement in regions with broadleaf deciduous and needleleaf forests while grassland regions exhibited the worst accuracy amongst the five different vegetation types.


2007 ◽  
Author(s):  
Mohammed Z. Rahman ◽  
Leonid Roytman ◽  
Felix Kogan

2010 ◽  
Vol 4 (4) ◽  
pp. 583-592 ◽  
Author(s):  
L. Kaleschke ◽  
N. Maaß ◽  
C. Haas ◽  
S. Hendricks ◽  
G. Heygster ◽  
...  

Abstract. In preparation for the European Space Agency's (ESA) Soil Moisture and Ocean Salinity (SMOS) mission, we investigated the potential of L-band (1.4 GHz) radiometry to measure sea-ice thickness. Sea-ice brightness temperature was measured at 1.4 GHz and ice thickness was measured along nearly coincident flight tracks during the SMOS Sea-Ice campaign in the Bay of Bothnia in March 2007. A research aircraft was equipped with the L-band Radiometer EMIRAD and coordinated with helicopter based electromagnetic induction (EM) ice thickness measurements. We developed a three layer (ocean-ice-atmosphere) dielectric slab model for the calculation of ice thickness from brightness temperature. The dielectric properties depend on the relative brine volume which is a function of the bulk ice salinity and temperature. The model calculations suggest a thickness sensitivity of up to 1.5 m for low-salinity (multi-year or brackish) sea-ice. For Arctic first year ice the modelled thickness sensitivity is less than half a meter. It reduces to a few centimeters for temperatures approaching the melting point. The campaign was conducted under unfavorable melting conditions and the spatial overlap between the L-band and EM-measurements was relatively small. Despite these disadvantageous conditions we demonstrate the possibility to measure the sea-ice thickness with the certain limitation up to 1.5 m. The ice thickness derived from SMOS measurements would be complementary to ESA's CryoSat-2 mission in terms of the error characteristics and the spatiotemporal coverage. The relative error for the SMOS ice thickness retrieval is expected to be not less than about 20%.


2016 ◽  
Vol 13 (9) ◽  
pp. 1295-1299 ◽  
Author(s):  
Qian Cui ◽  
Xiaolong Dong ◽  
Jiancheng Shi ◽  
Tianjie Zhao ◽  
Chuan Xiong

2013 ◽  
Vol 12 (3) ◽  
pp. vzj2012.0072 ◽  
Author(s):  
Xujun Han ◽  
Harrie-Jan Hendricks Franssen ◽  
Xin Li ◽  
Yanlin Zhang ◽  
Carsten Montzka ◽  
...  

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