Removing long-term errors from AVHRR-based brightness temperature (BT)

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.

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

10.1109/igarss47720.2021.9554579 ◽

2021 ◽

Author(s):

Xiaojun Li ◽

J.-P. Wigncron ◽

F. Frappart ◽

Lei Fan ◽

Gabrielle De Lannoy ◽

...

Keyword(s):

Brightness Temperature ◽

Temperature Record ◽

L Band

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An Uncertainty Quantified Fundamental Climate Data Record for Microwave Humidity Sounders

Remote Sensing ◽

10.3390/rs11050548 ◽

2019 ◽

Vol 11 (5) ◽

pp. 548 ◽

Cited By ~ 6

Author(s):

Imke Hans ◽

Martin Burgdorf ◽

Stefan Buehler ◽

Marc Prange ◽

Theresa Lang ◽

...

Keyword(s):

Brightness Temperature ◽

Uncertainty Propagation ◽

Uncertainty Budget ◽

Intermediate Step ◽

Climate Data ◽

Data Record ◽

Upper Tropospheric Humidity ◽

Uncertainty Information ◽

Climate Data Record

To date, there is no long-term, stable, and uncertainty-quantified dataset of upper tropospheric humidity (UTH) that can be used for climate research. As intermediate step towards the overall goal of constructing such a climate data record (CDR) of UTH, we produced a new fundamental climate data record (FCDR) on the level of brightness temperature for microwave humidity sounders that will serve as basis for the CDR of UTH. Based on metrological principles, we constructed and implemented the measurement equation and the uncertainty propagation in the processing chain for the microwave humidity sounders. We reprocessed the level 1b data to obtain newly calibrated uncertainty quantified level 1c data in brightness temperature. Three aspects set apart this FCDR from previous attempts: (1) the data come in a ready-to-use NetCDF format; (2) the dataset provides extensive uncertainty information taking into account the different correlation behaviour of the underlying errors; and (3) inter-satellite biases have been understood and reduced by an improved calibration. Providing a detailed uncertainty budget on these data, this new FCDR provides valuable information for a climate scientist and also for the construction of the CDR.

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Comparison of AIRS and IASI Radiances Using GOES Imagers as Transfer Radiometers toward Climate Data Records

Journal of Applied Meteorology and Climatology ◽

10.1175/2009jamc2218.1 ◽

2010 ◽

Vol 49 (3) ◽

pp. 478-492 ◽

Cited By ~ 40

Author(s):

Likun Wang ◽

Xiangqian Wu ◽

Mitch Goldberg ◽

Changyong Cao ◽

Yaping Li ◽

...

Keyword(s):

Brightness Temperature ◽

Climate Data ◽

Atmospheric Infrared Sounder ◽

Mean Values ◽

Tropical Regions ◽

Time Period ◽

Double Differences ◽

Cross Track ◽

Spectral Channels

Abstract The Atmospheric Infrared Sounder (AIRS) and the Infrared Atmospheric Sounding Interferometer (IASI), together with the future Cross-track Infrared Sounder, will provide long-term hyperspectral measurements of the earth and its atmosphere at ∼10 km spatial resolution. Quantifying the radiometric difference between AIRS and IASI is crucial for creating fundamental climate data records and establishing the space-based infrared calibration standard. Since AIRS and IASI have different local equator crossing times, a direct comparison of these two instruments over the tropical regions is not feasible. Using the Geostationary Operational Environmental Satellite (GOES) imagers as transfer radiometers, this study compares AIRS and IASI over warm scenes in the tropical regions for a time period of 16 months. The double differences between AIRS and IASI radiance biases relative to the GOES-11 and -12 imagers are used to quantify the radiance differences between AIRS and IASI within the GOES imager spectral channels. The results indicate that, at the 95% confidence level, the mean values of the IASI − AIRS brightness temperature differences for warm scenes are very small, that is, −0.0641 ± 0.0074 K, −0.0432 ± 0.0114 K, and −0.0095 ± 0.0151 K for the GOES-11 6.7-, 10.7-, and 12.0-μm channels, respectively, and −0.0490 ± 0.0100 K, −0.0419 ± 0.0224 K, and −0.0884 ± 0.0160 K for the GOES-12 6.5-, 10.7-, and 13.3-μm channels, respectively. The brightness temperature biases between AIRS and IASI within the GOES imager spectral range are less than 0.1 K although the AIRS measurements are slightly warmer than those of IASI.

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Radiometric consistency assessment of hyperspectral infrared sounders

Atmospheric Measurement Techniques Discussions ◽

10.5194/amtd-8-7161-2015 ◽

2015 ◽

Vol 8 (7) ◽

pp. 7161-7199 ◽

Cited By ~ 5

Author(s):

L. Wang ◽

Y. Han ◽

X. Jin ◽

Y. Chen ◽

D. A. Tremblay

Keyword(s):

Brightness Temperature ◽

Infrared Imaging ◽

Atmospheric Infrared Sounder ◽

Atmospheric Sounding ◽

Benchmark Datasets ◽

Spectral Scale ◽

One Year ◽

Cross Track ◽

Spectral Channels

Abstract. The radiometric and spectral consistency among the Atmospheric Infrared Sounder (AIRS), the Infrared Atmospheric Sounding Interferometer (IASI), and the Cross-track Infrared Sounder (CrIS) is fundamental for the creation of long-term infrared (IR) hyperspectral radiance benchmark datasets for both inter-calibration and climate-related studies. In this study, the CrIS radiance measurements on Suomi National Polar-orbiting Partnership (SNPP) satellite are directly compared with IASI on MetOp-A and -B at the finest spectral scale and with AIRS on Aqua in 25 selected spectral regions through one year of simultaneous nadir overpass (SNO) observations to evaluate radiometric consistency of these four hyperspectral IR sounders. The spectra from different sounders are paired together through strict spatial and temporal collocation. The uniform scenes are selected by examining the collocated Visible Infrared Imaging Radiometer Suite (VIIRS) pixels. Their brightness temperature (BT) differences are then calculated by converting the spectra onto common spectral grids. The results indicate that CrIS agrees well with IASI on MetOp-A and IASI on MetOp-B at the longwave IR (LWIR) and middle-wave IR (MWIR) bands with 0.1–0.2 K differences. There are no apparent scene-dependent patterns for BT differences between CrIS and IASI for individual spectral channels. CrIS and AIRS are compared at the 25 spectral regions for both Polar and Tropical SNOs. The combined global SNO datasets indicate that, the CrIS-AIRS BT differences are less than or around 0.1 K among 21 of 25 comparison spectral regions and they range from 0.15 to 0.21 K in the remaining 4 spectral regions. CrIS-AIRS BT differences in some comparison spectral regions show weak scene-dependent features.

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Long-Term and High-Resolution Global Time Series of Brightness Temperature from Copula-Based Fusion of SMAP Enhanced and SMOS Data

Remote Sensing ◽

10.3390/rs10111842 ◽

2018 ◽

Vol 10 (11) ◽

pp. 1842 ◽

Cited By ~ 7

Author(s):

Christof Lorenz ◽

Carsten Montzka ◽

Thomas Jagdhuber ◽

Patrick Laux ◽

Harald Kunstmann

Keyword(s):

Time Series ◽

Soil Moisture ◽

High Resolution ◽

Brightness Temperature ◽

Spatial Resolution ◽

Prediction Models ◽

Weather Prediction ◽

Brightness Temperatures ◽

Climate Analysis

Long and consistent soil moisture time series at adequate spatial resolution are key to foster the application of soil moisture observations and remotely-sensed products in climate and numerical weather prediction models. The two L-band soil moisture satellite missions SMAP (Soil Moisture Active Passive) and SMOS (Soil Moisture and Ocean Salinity) are able to provide soil moisture estimates on global scales and in kilometer accuracy. However, the SMOS data record has an appropriate length of 7.5 years since late 2009, but with a coarse resolution of ∼25 km only. In contrast, a spatially-enhanced SMAP product is available at a higher resolution of 9 km, but for a shorter time period (since March 2015 only). Being the fundamental observable from passive microwave sensors, reliable brightness temperatures (Tbs) are a mandatory precondition for satellite-based soil moisture products. We therefore develop, evaluate and apply a copula-based data fusion approach for combining SMAP Enhanced (SMAP_E) and SMOS brightness Temperature (Tb) data. The approach exploits both linear and non-linear dependencies between the two satellite-based Tb products and allows one to generate conditional SMAP_E-like random samples during the pre-SMAP period. Our resulting global Copula-combined SMOS-SMAP_E (CoSMOP) Tbs are statistically consistent with SMAP_E brightness temperatures, have a spatial resolution of 9 km and cover the period from 2010 to 2018. A comparison with Service Soil Climate Analysis Network (SCAN)-sites over the Contiguous United States (CONUS) domain shows that the approach successfully reduces the average RMSE of the original SMOS data by 15%. At certain locations, improvements of 40% and more can be observed. Moreover, the median NSE can be enhanced from zero to almost 0.5. Hence, CoSMOP, which will be made freely available to the public, provides a first step towards a global, long-term, high-resolution and multi-sensor brightness temperature product, and thereby, also soil moisture.

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