Ground-based atmospheric measurements from CHRIS for satellite validation.

2020 ◽  
Author(s):  
El Kattar Marie-Thérèse ◽  
Auriol Frédérique ◽  
Herbin Hervé
Keyword(s):  
Greenhouse Gases ◽  
Spectral Resolution ◽  
Trace Gases ◽  
Space Missions ◽  
High Spectral Resolution ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Atmospheric Measurements ◽  
Gaseous Species ◽  
Infrared Measurements

<p>Ground-based high spectral resolution infrared measurements are considered to be the most efficient way to obtain accurate tropospheric abundances of different gaseous species and in particular greenhouse gases, such as CO<sub>2</sub> and CH<sub>4</sub>. Furthermore, this type of measurement is also commonly used to validate the satellite retrievals. Despite the outstanding capabilities of the spectrometers used by the TCCON and NDACC networks, they are inadequate for field campaigns; therefore, more compact and stable spectrometers have been developed. <strong>CHRIS</strong> (<strong>C</strong>ompact <strong>H</strong>igh <strong>S</strong>pectral <strong>R</strong>esolution <strong>I</strong>nfrared <strong>S</strong>pectrometer) is a new prototype based on the EM27-SUN from Bruker, with unique characteristics such as its high spectral resolution (0.135 cm<sup>-1</sup> non-apodized) with a spectral sampling every 0.065 cm<sup>-1</sup> to satisfy the Nyquist criterion. This optically stable instrument allows recording solar transmission light spectra in a wide spectral range (680 to 5200 cm<sup>-1</sup>) with a relatively high SNR (~780 in average).</p><p> </p><p>            This instrumental prototype is designed to perform measurements of greenhouse gases (CO<sub>2</sub>, CH<sub>4</sub> and H<sub>2</sub>O), trace gases (SO<sub>2</sub>, CO, HCl, NO<sub>x</sub>…) but also aerosols and clouds that have very typical spectral features in particular in the thermal infrared region. The main objective of this study is the accurate retrieval of tropospheric abundances of the greenhouse gases, CO<sub>2</sub> and CH<sub>4</sub>, in the TIR/SWIR regions, and study the synergy between them especially for the MAGIC campaign. CHRIS is a part of this ongoing campaign in an attempt to monitor the GHG and validate the actual space missions like IASI, OCO-2, GOSAT-2 and future space missions like Merlin, MicroCarb and IASI-NG.</p><p> </p><p>            Here, the spectral and radiometric characterization of this instrument is briefly explained. Furthermore, we present CHRIS’s capabilities to measure CO<sub>2</sub> and CH<sub>4</sub> vertical profiles through a complete information content analysis, a channel selection and an error budget estimation. The preliminary results of the retrieval of these gases using the radiative transfer model ARAHMIS developed at the LOA is also presented. CHRIS is also part of other campaigns such as ImagEtna and Shadow-2 to study the trace gases and aerosols respectively.</p>

scholarly journals Instrumental characteristics and Greenhouse gases measurement capabilities of the Compact High-spectral Resolution Infrared Spectrometer: CHRIS

2019 ◽  
Author(s):  
Marie-Thérèse El Kattar ◽  
Frédérique Auriol ◽  
Hervé Herbin
Keyword(s):  
Greenhouse Gases ◽  
Spectral Resolution ◽  
Complete Information ◽  
High Spectral Resolution ◽  
Gaseous Species ◽  
Future Space ◽  
Infrared Measurements ◽  
Thermal Region ◽  
Portable Spectrometers ◽  
Infrared Spectrometer

Abstract. Ground-based high spectral resolution infrared measurements are an efficient way to obtain accurate tropospheric abundances of different gaseous species and in particular GreenHouse Gases (GHG), such as CO2 and CH4. Many ground-based spectrometers are used in the NDACC and TCCON networks to validate the Level 2 satellite data, but their large dimensions and heavy mass makes them inadequate for field campaigns. To overcome these problems, the use of portable spectrometers was recently investigated. In this context, this paper deals with the CHRIS (Compact High-spectral Resolution Infrared Spectrometer) prototype with unique characteristics such as its high spectral resolution (0.135 cm-1 non-apodized) and its wide spectral range (680 to 5200 cm-1). Its main objective is the characterization of gases and aerosols in the infrared thermal region, that's why it requires high radiometric precision and accuracy, which is achieved by performing spectral and radiometric calibrations that will be presented in this paper. Also, CHRIS's capabilities to retrieve CO2 and CH4 vertical profiles are presented through a complete information content analysis, a channel selection and an error budget estimation in the attempt to join the ongoing campaigns, such as MAGIC, to monitor the GHG and validate the actual and future space missions.

scholarly journals A High-Spectral-Resolution Radiative Transfer Model for Simulating Multilayered Clouds and Aerosols in the Infrared Spectral Region

2015 ◽  
Vol 72 (2) ◽  
pp. 926-942 ◽  
Author(s):  
Chenxi Wang ◽  
Ping Yang ◽  
Xu Liu
Keyword(s):  
Radiative Transfer ◽  
Spectral Resolution ◽  
Present Model ◽  
Reference Model ◽  
Mineral Dust ◽  
High Spectral Resolution ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Multiple User ◽  
Infrared Measurements

Abstract A fast and flexible model is developed to simulate the transfer of thermal infrared radiation at wavenumbers from 700 to 1300 cm−1 with a spectral resolution of 0.1 cm−1 for scattering–absorbing atmospheres. In a single run and at multiple user-defined levels, the present model simulates radiances at different viewing angles and fluxes. Furthermore, the model takes into account complicated and realistic scenes in which ice cloud, water cloud, and mineral dust layers may coexist within an atmospheric column. The present model is compared to a rigorous reference model, the 32-stream Discrete Ordinate Radiative Transfer model (DISORT) code. For an atmosphere with three scattering layers (water, ice, and mineral dust), the root-mean-square error of the simulated brightness temperatures at the top of the atmosphere is approximately 0.05 K, and the relative flux errors at the boundary and internal levels are much smaller than 1%. Within the same computing environment, the fast model runs more than 10 000, 6000, and 4000 times faster than DISORT under single-layer, two-layer, and three-layer cloud–aerosol conditions, respectively. With its computational efficiency and accuracy, the present model may optimally facilitate the forward radiative transfer simulations involved in remote sensing implementations based on high-spectral-resolution and narrowband infrared measurements and in the data assimilation applications of the weather forecasting system. The selected 0.1-cm−1 spectral resolution is an obstacle to extending the present model to strongly absorptive bands (e.g., 600–700 cm−1). However, the present clear-sky module can be substituted by a more accurate model for specific applications involving spectral bands with strong absorption.

scholarly journals Instrumental characteristics and potential greenhouse gas measurement capabilities of the Compact High-Spectral-Resolution Infrared Spectrometer: CHRIS

2020 ◽  
Vol 13 (7) ◽  
pp. 3769-3786
Author(s):  
Marie-Thérèse El Kattar ◽  
Frédérique Auriol ◽  
Hervé Herbin
Keyword(s):  
Greenhouse Gases ◽  
Spectral Resolution ◽  
Complete Information ◽  
Atmospheric Composition ◽  
High Spectral Resolution ◽  
Gaseous Species ◽  
Infrared Measurements ◽  
Gas Measurement ◽  
Portable Spectrometers ◽  
Infrared Spectrometer

Abstract. Ground-based high-spectral-resolution infrared measurements are an efficient way to obtain accurate tropospheric abundances of different gaseous species, in particular greenhouse gases (GHGs) such as CO2 and CH4. Many ground-based spectrometers are used in the NDACC and TCCON networks to validate the Level 2 satellite data, but their large dimensions and heavy mass make them inadequate for field campaigns. To overcome these problems, the use of portable spectrometers was recently investigated. In this context, this paper deals with the CHRIS (Compact High-Spectral-Resolution Infrared Spectrometer) prototype with unique characteristics such as its high spectral resolution (0.135 cm−1 nonapodized) and its wide spectral range (680 to 5200 cm−1). Its main objective is the characterization of gases and aerosols in the thermal and shortwave infrared regions. That is why it requires high radiometric precision and accuracy, which are achieved by performing spectral and radiometric calibrations that are described in this paper. Furthermore, CHRIS's capabilities to retrieve vertical CO2 and CH4 profiles are presented through a complete information content analysis, a channel selection and an error budget estimation in the attempt to join ongoing campaigns such as MAGIC (Monitoring of Atmospheric composition and Greenhouse gases through multi-Instruments Campaigns) to monitor GHGs and validate the actual and future space missions such as IASI-NG and Microcarb.

Dependence of Simulation Biases at AHI Surface-Sensitive Channels on Land Surface Emissivity over China

2018 ◽  
Vol 35 (6) ◽  
pp. 1283-1298 ◽  
Author(s):  
X. Zhuge ◽  
X. Zou ◽  
F. Weng ◽  
M. Sun
Keyword(s):  
Brightness Temperature ◽  
Spectral Resolution ◽  
Land Surface ◽  
High Spectral Resolution ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Surface Emissivity ◽  
Bare Rock ◽  
Land Surface Emissivity ◽  
M Channels

AbstractThis study compares the simulation biases of Advanced Himawari Imager (AHI) brightness temperature to observations made at night over China through the use of three land surface emissivity (LSE) datasets. The University of Wisconsin–Madison High Spectral Resolution Emissivity dataset, the Combined Advanced Spaceborne Thermal Emission and Reflection Radiometer and Moderate Resolution Imaging Spectroradiometer Emissivity database over Land High Spectral Resolution Emissivity dataset, and the International Geosphere–Biosphere Programme (IGBP) infrared LSE module, as well as land skin temperature observations from the National Basic Meteorological Observing stations in China are used as inputs to the Community Radiative Transfer Model. The results suggest that the standard deviations of AHI observations minus background simulations (OMBs) are largely consistent for the three LSE datasets. Also, negative biases of the OMBs of brightness temperature uniformly occur for each of the three datasets. There are no significant differences in OMB biases estimated with the three LSE datasets over cropland and forest surface types for all five AHI surface-sensitive channels. Over the grassland surface type, significant differences (~0.8 K) are found at the 10.4-, 11.2-, and 12.4-μm channels if using the IGBP dataset. Over nonvegetated surface types (e.g., sandy land, gobi, and bare rock), the lack of a monthly variation in IGBP LSE introduces large negative biases for the 3.9- and 8.6-μm channels, which are greater than those from the two other LSE datasets. Thus, improvements in simulating AHI infrared surface-sensitive channels can be made when using spatially and temporally varying LSE estimates.

scholarly journals Retrieval of Ice Cloud Properties from AIRS and MODIS Observations Based on a Fast High-Spectral-Resolution Radiative Transfer Model

2013 ◽  
Vol 52 (3) ◽  
pp. 710-726 ◽  
Author(s):  
Chenxi Wang ◽  
Ping Yang ◽  
Steven Platnick ◽  
Andrew K. Heidinger ◽  
Bryan A. Baum ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Spectral Resolution ◽  
Spectral Response ◽  
Thermal Infrared ◽  
High Spectral Resolution ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Retrieval Method ◽  
Ice Cloud ◽  
Cloud Properties

AbstractA computationally efficient high-spectral-resolution cloudy-sky radiative transfer model (HRTM) in the thermal infrared region (700–1300 cm−1, 0.1 cm−1 spectral resolution) is advanced for simulating the upwelling radiance at the top of atmosphere and for retrieving cloud properties. A precomputed transmittance database is generated for simulating the absorption contributed by up to seven major atmospheric absorptive gases (H2O, CO2, O3, O2, CH4, CO, and N2O) by using a rigorous line-by-line radiative transfer model (LBLRTM). Both the line absorption of individual gases and continuum absorption are included in the database. A high-spectral-resolution ice particle bulk scattering properties database is employed to simulate the radiation transfer within a vertically nonisothermal ice cloud layer. Inherent to HRTM are sensor spectral response functions that couple with high-spectral-resolution measurements in the thermal infrared regions from instruments such as the Atmospheric Infrared Sounder (AIRS) and Infrared Atmospheric Sounding Interferometer. When compared with the LBLRTM and the discrete ordinates radiative transfer model (DISORT), the root-mean-square error of HRTM-simulated single-layer cloud brightness temperatures in the thermal infrared window region is generally smaller than 0.2 K. An ice cloud optical property retrieval scheme is developed using collocated AIRS and Moderate Resolution Imaging Spectroradiometer (MODIS) data. A retrieval method is proposed to take advantage of the high-spectral-resolution instrument. On the basis of the forward model and retrieval method, a case study is presented for the simultaneous retrieval of ice cloud optical thickness τ and effective particle size Deff that includes a cloud-top-altitude self-adjustment approach to improve consistency with simulations.

scholarly journals A synthetic data set of high-spectral resolution infrared spectra for the Arctic atmosphere

2016 ◽  
Author(s):  
C. J. Cox ◽  
P. M. Rowe ◽  
S. P. Neshyba ◽  
V. P. Walden
Keyword(s):  
Remote Sensing ◽  
Radiative Transfer ◽  
Infrared Spectra ◽  
Spectral Resolution ◽  
High Spectral Resolution ◽  
The Arctic ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Data Set ◽  
Atmospheric State

Abstract. Retrievals of cloud microphysical and macrophysical properties from ground-based and satellite-based infrared remote sensing instruments are critical for understanding clouds. However, retrieval uncertainties are difficult to quantify without a standard for comparison. This is particularly true over the polar regions where surface-based data for a cloud climatology are sparse, yet clouds represent a major source of uncertainty in weather and climate models. We describe a synthetic high-spectral resolution infrared data set that is designed to facilitate validation and development of cloud retrieval algorithms for surface- and satellite-based remote sensing instruments. Since the data set is calculated using pre-defined cloudy atmospheres, the properties of the cloud and atmospheric state are known a priori. The atmospheric state used for the simulations is drawn from radiosonde measurements made at the North Slope of Alaska (NSA) Atmospheric Radiation Measurement (ARM) site at Barrow, Alaska (71.325° N, 156.615° W), a location that is generally representative of the western Arctic. The cloud properties for each simulation are selected from statistical distributions derived from past field measurements. Upwelling (at 60 km) and downwelling (at the surface) infrared spectra are simulated for 222 cloudy cases from 50–3000 cm−1 (3.3 to 200 μm) at monochromatic (line-by-line) resolution at a spacing of ~ 0.01 cm−1 using the Line-by-line Radiative Transfer Model (LBLRTM) and the discrete-ordinate-method radiative transfer code (DISORT). These spectra are freely available for interested researchers from the ACADIS data repository (doi:10.5065/D61J97TT).

scholarly journals Measuring Stratospheric H2O with an Airborne Spectrometer

2014 ◽  
Vol 31 (7) ◽  
pp. 1502-1515 ◽  
Author(s):  
Maziar Bani Shahabadi ◽  
Yi Huang
Keyword(s):  
Water Vapor ◽  
Radiative Transfer ◽  
Spectral Resolution ◽  
High Sensitivity ◽  
Far Infrared ◽  
High Spectral Resolution ◽  
Radiative Transfer Model ◽  
Small Scale ◽  
Transfer Model ◽  
Infrared Spectral

Abstract This study examines the ability of an infrared spectral sensor flying at the tropopause level for retrieving stratospheric H2O. Synthetic downwelling radiance spectra simulated by the line-by-line radiative transfer model are used for this examination. The potential of high-sensitivity water vapor retrieval is demonstrated by an ideal sensor with low detector noise, high spectral resolution, and full infrared coverage. A suite of hypothetical sensors with varying specifications is then examined to determine the technological requirements for a satisfactory retrieval. This study finds that including far infrared in the sensor’s spectral coverage is essential for achieving accurate H2O retrieval with an accuracy of 0.4 ppmv (1-sigma). The uncertainties in other gas species such as CH4, N2O, O3, and CO2 do not significantly affect the H2O retrieval. Such a hyperspectral instrument may afford an advantageous tool, especially for detecting small-scale lower-stratospheric moistening events.

scholarly journals Denoising Algorithm for the FY-4A GIIRS Based on Principal Component Analysis

2019 ◽  
Vol 11 (22) ◽  
pp. 2710 ◽  
Author(s):  
Sihui Fan ◽  
Wei Han ◽  
Zhiqiu Gao ◽  
Ruoying Yin ◽  
Yu Zheng
Keyword(s):  
Principal Component Analysis ◽  
Spectral Resolution ◽  
Principal Component ◽  
Component Analysis ◽  
High Spectral Resolution ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Observation Data ◽  
Observation Error ◽  
Array Position

The Geostationary Interferometric Infrared Sounder (GIIRS) is the first high-spectral resolution advanced infrared (IR) sounder onboard the new-generation Chinese geostationary meteorological satellite FengYun-4A (FY-4A). The GIIRS has 1650 channels, and its spectrum ranges from 700 to 2250 cm−1 with an unapodized spectral resolution of 0.625 cm−1. It represents a significant breakthrough for measurements with high temporal, spatial and spectral resolutions worldwide. Many GIIRS channels have quite similar spectral signal characteristics that are highly correlated with each other in content and have a high degree of information redundancy. Therefore, this paper applies a principal component analysis (PCA)-based denoising algorithm (PDA) to study simulation data with different noise levels and observation data to reduce noise. The results show that the channel reconstruction using inter-channel spatial dependency and spectral similarity can reduce the noise in the observation brightness temperature (BT). A comparison of the BT observed by the GIIRS (O) with the BT simulated by the radiative transfer model (B) shows that a deviation occurs in the observation channel depending on the observation array. The results show that the array features of the reconstructed observation BT (rrO) depending on the observation array are weakened and the effect of the array position on the observations in the sub-center of the field of regard (FOR) are partially eliminated after the PDA procedure is applied. The high observation and simulation differences (O-B) in the sub-center of the FOR array notably reduced after the PDA procedure is implemented. The improvement of the high O-B is more distinct, and the low O-B becomes smoother. In each scan line, the standard deviation of the reconstructed background departures (rrO-B) is lower than that of the background departures (O-B). The observation error calculated by posterior estimation based on variational assimilation also verifies the efficiency of the PDA. The typhoon experiment also shows that among the 29 selected assimilation channels, the observation error of 65% of the channels was reduced as calculated by the triangle method.

Model Calculations and Interferometer Measurements of Ice-Cloud Characteristics

2000 ◽  
Vol 39 (5) ◽  
pp. 634-644 ◽  
Author(s):  
Sunggi Chung ◽  
Steven Ackerman ◽  
Paul F. van Delst ◽  
W. Paul Menzel
Keyword(s):  
Radiative Transfer ◽  
Spectral Resolution ◽  
Gas Absorption ◽  
High Spectral Resolution ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Model Calculations ◽  
Ice Cloud ◽  
Macrophysical Properties ◽  
Ice Water

Abstract This paper investigates the relationship between high–spectral resolution infrared (IR) radiances and the microphysical and macrophysical properties of cirrus clouds. Through use of radiosonde measurements of the atmospheric state at the Department of Energy’s Atmospheric Radiation Measurement Program site, high–spectral resolution IR radiances are calculated by combining trace gas absorption optical depths from a line-by-line radiative transfer model with the discrete ordinate radiative transfer (DISORT) method. The sensitivity of the high–spectral resolution IR radiances to particle size, ice-water path, cloud-top location, cloud thickness, and multilayered cloud conditions is estimated in a multitude of calculations. DISORT calculations and interferometer measurements of cirrus ice cloud between 700 and 1300 cm−1 are compared for three different situations. The measurements were made with the High–Spectral Resolution Interferometer Sounder mounted on a National Aeronautics and Space Administration ER-2 aircraft flying at 20-km altitude during the Subsonic Aircraft Contrail and Cloud Effects Special Study (SUCCESS).

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