scholarly journals A non-iterative linear retrieval for infrared high-resolution limb sounders

2013 ◽  
Vol 6 (5) ◽  
pp. 1381-1396
Author(s):  
L. Millán ◽  
A. Dudhia
Keyword(s):  
High Resolution ◽  
Computing Time ◽  
Michelson Interferometer ◽  
High Spectral Resolution ◽  
Radiative Transfer Model ◽  
Spectral Signature ◽  
Transfer Model ◽  
Concentration Difference ◽  
Error Margin ◽  
Retrieval Scheme

Abstract. Currently, most of the high-spectral-resolution infrared limb sounders use subsets of the recorded spectra (microwindows) in their retrieval schemes to reduce the computing time of rerunning the radiative transfer model. A fast linear retrieval scheme is described which allows the whole spectral signature of the target molecule to be used. We determine that pressure and temperature retrievals can be treated linearly up to a 20% difference between the atmospheric state and the linearisation point for a 3% error margin and up to 10 K "difference" for a 3 K error margin near the stratopause and less than 0.5 K elsewhere. Assuming perfect pT knowledge, CH4 retrievals can be be treated linearly up to a 20% CH4 concentration "difference" for a 2% error margin. As an example, this technique is implemented for the Michelson Interferometer for Passive Atmospheric Sounding instrument, but it is applicable to any high-resolution limb sounder.

scholarly journals A non-iterative linear retrieval for infrared high resolution limb sounders

2013 ◽  
Vol 6 (1) ◽  
pp. 721-766
Author(s):  
L. Millán ◽  
A. Dudhia
Keyword(s):  
High Resolution ◽  
Computing Time ◽  
Michelson Interferometer ◽  
High Spectral Resolution ◽  
Radiative Transfer Model ◽  
Spectral Signature ◽  
Transfer Model ◽  
Gas Concentration ◽  
Atmospheric Sounding ◽  
Retrieval Scheme

Abstract. Currently most of the high spectral resolution infrared limb sounders use subsets of the recorded spectra (microwindows) in their retrieval schemes to reduce the computing time of rerunning the radiative transfer model. A fast linear retrieval scheme is described which allows the whole spectral signature of the target molecule to be used. We determine how close the linearisation point needs to be to the solution in order to fall in the linear regime and also suggest an adjustment to the forward model and Jacobians to propagate the change in pressure and temperature on the gas concentration retrievals. As an example, this technique is implemented for the Michelson Interferometer for Passive Atmospheric Sounding instrument, but it is applicable to any high resolution limb sounder.

scholarly journals MIPAS detection of cloud and aerosol particle occurrence in the UTLS with comparison to HIRDLS and CALIOP

2012 ◽  
Vol 5 (10) ◽  
pp. 2537-2553 ◽  
Author(s):  
H. Sembhi ◽  
J. Remedios ◽  
T. Trent ◽  
D. P. Moore ◽  
R. Spang ◽  
...  
Keyword(s):  
Aerosol Particle ◽  
Detection System ◽  
Michelson Interferometer ◽  
Detection Limits ◽  
Infrared Emission ◽  
High Spectral Resolution ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Polar Regions ◽  
Particle Injection

Abstract. Satellite infrared emission instruments require efficient systems that can separate and flag observations which are affected by clouds and aerosols. This paper investigates the identification of cloud and aerosols from infrared, limb sounding spectra that were recorded by the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS), a high spectral resolution Fourier transform spectrometer on the European Space Agency's (ESA) ENVISAT (Now inoperative since April 2012 due to loss of contact). Specifically, the performance of an existing cloud and aerosol particle detection method is simulated with a radiative transfer model in order to establish, for the first time, confident detection limits for particle presence in the atmosphere from MIPAS data. The newly established thresholds improve confidence in the ability to detect particle injection events, plume transport in the upper troposphere and lower stratosphere (UTLS) and better characterise cloud distributions utilising MIPAS spectra. The method also provides a fast front-end detection system for the MIPClouds processor; a processor designed for the retrieval of macro- and microphysical cloud properties from the MIPAS data. It is shown that across much of the stratosphere, the threshold for the standard cloud index in band A is 5.0 although threshold values of over 6.0 occur in restricted regimes. Polar regions show a surprising degree of uncertainty at altitudes above 20 km, potentially due to changing stratospheric trace gas concentrations in polar vortex conditions and poor signal-to-noise due to cold atmospheric temperatures. The optimised thresholds of this study can be used for much of the time, but time/composition-dependent thresholds are recommended for MIPAS data for the strongly perturbed polar stratosphere. In the UT, a threshold of 5.0 applies at 12 km and above but decreases rapidly at lower altitudes. The new thresholds are shown to allow much more sensitive detection of particle distributions in the UTLS, with extinction detection limits above 13 km often better than 10−4 km−1, with values approaching 10−5 km−1 in some cases. Comparisons of the new MIPAS results with cloud data from HIRDLS and CALIOP, outside of the poles, establish a good agreement in distributions (cloud and aerosol top heights and occurrence frequencies) with an offset between MIPAS and the other instruments of 0.5 km to 1 km between 12 km and 20 km, consistent with vertical oversampling of extended cloud layers within the MIPAS field of view. We conclude that infrared limb sounders provide a very consistent picture of particles in the UTLS, allowing detection limits which are consistent with the lidar observations. Investigations of MIPAS data for the Mount Kasatochi volcanic eruption on the Aleutian Islands and the Black Saturday fires in Australia are used to exemplify how useful MIPAS limb sounding data were for monitoring aerosol injections into the UTLS. It is shown that the new thresholds allowed such events to be much more effectively derived from MIPAS with detection limits for these case studies of 1 × 10−5 km−1 at a wavelength of 12 μm.

scholarly journals MIPAS detection of cloud and aerosol particle occurrence in the UTLS with comparison to HIRDLS and CALIOP

2012 ◽  
Vol 5 (1) ◽  
pp. 1795-1841 ◽  
Author(s):  
H. Sembhi ◽  
J. Remedios ◽  
T. Trent ◽  
D. P. Moore ◽  
R. Spang ◽  
...  
Keyword(s):  
Aerosol Particle ◽  
Detection System ◽  
Michelson Interferometer ◽  
Detection Limits ◽  
High Spectral Resolution ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Polar Regions ◽  
Particle Injection ◽  
Infra Red

Abstract. Satellite infra-red emission instruments require efficient systems that can separate and flag observations which are affected by clouds and aerosols. This paper investigates the identification of cloud and aerosols from infra-red, limb sounding spectra recorded by the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS), a high spectral resolution, Fourier transform spectrometer on ENVISAT. Specifically, the performance of an existing cloud and aerosol particle detection method is simulated, with a radiative transfer model, in order to establish for the first time limits to confident detection of particle effects in MIPAS data. The newly established thresholds improve confidence in the ability of MIPAS to detect particle injection events and plume transport in the UTLS as well as better characterised cloud distributions. The method also provides a fast front-end detection system for the MIPClouds processor, a processor designed for the retrieval of macro- and microphysical cloud properties from the MIPAS data. It is shown that across much of the stratosphere, the threshold for the standard cloud index in band A is 5 although values of greater than 6 occur in restricted regimes. Polar regions show a surprising degree of uncertainty at altitudes above 20 km due to potential high ClO formation and also poor signal-to-noise due to low atmosphere temperatures. The optimised thresholds of this study can be used for much of the time, but time/composition dependent thresholds are recommended for MIPAS data for the strongly perturbed polar stratosphere. In the UT, thresholds of 5 apply at 12 km and above but decrease rapidly at lower altitudes. The new thresholds are shown to allow much more sensitive detection of particle distributions in the upper troposphere and lower stratosphere (UTLS), with extinction detection limits above 13 km often better than 10−4 km−1, with values approaching 10−5 km−1 in some cases. Comparisons of the new MIPAS results with data from HIRDLS and CALIOP, outside of the poles, establishes good agreement in distributions (cloud occurrence frequencies and clouds and aerosol top heights) with an offset between MIPAS and the other instruments of 0.5 km between 12 and 20 km. We conclude that current infra-red limb sounders provide a very consistent picture of particles in the UTLS, allowing detection limits which are consistent with the lidar observations. Investigations of the MIPAS data for the Kasatochi volcanic eruption and the Black Saturday fires in Australia are used to exemplify the usefulness of MIPAS limb sounding data for monitoring aerosol injections into the UTLS, and into the stratosphere, in particular over monthly timescales. It is shown that the new thresholds allow such events to be much more effectively monitored from MIPAS with detection limits for these case studies of 1 × 10−5 km−1 at 12 μm.

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 High resolution and Monte Carlo additions to the SASKTRAN radiative transfer model

2015 ◽  
Vol 8 (3) ◽  
pp. 3357-3397 ◽  
Author(s):  
D. J. Zawada ◽  
S. R. Dueck ◽  
L. A. Rieger ◽  
A. E. Bourassa ◽  
N. D. Lloyd ◽  
...  
Keyword(s):  
Monte Carlo ◽  
High Resolution ◽  
Radiative Transfer ◽  
Spatial Resolution ◽  
High Spatial Resolution ◽  
Reference Model ◽  
Monte Carlo Model ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Systematic Bias

Abstract. The OSIRIS instrument on board the Odin spacecraft has been measuring limb scattered radiance since 2001. The vertical radiance profiles measured as the instrument nods are inverted, with the aid of the SASKTRAN radiative transfer model, to obtain vertical profiles of trace atmospheric constituents. Here we describe two newly developed modes of the SASKTRAN radiative transfer model: a high spatial resolution mode, and a Monte Carlo mode. The high spatial resolution mode is a successive orders model capable of modelling the multiply scattered radiance when the atmosphere is not spherically symmetric; the Monte Carlo mode is intended for use as a highly accurate reference model. It is shown that the two models agree in a wide variety of solar conditions to within 0.2%. As an example case for both models, Odin-OSIRIS scans were simulated with the Monte Carlo model and retrieved using the high resolution model. A systematic bias of up to 4% in retrieved ozone number density between scans where the instrument is scanning up or scanning down was identified. It was found that calculating the multiply scattered diffuse field at five discrete solar zenith angles is sufficient to eliminate the bias for typical Odin-OSIRIS geometries.

scholarly journals Understanding Satellite-Observed Mountain-Wave Signatures Using High-Resolution Numerical Model Data

2009 ◽  
Vol 24 (1) ◽  
pp. 76-86 ◽  
Author(s):  
W. F. Feltz ◽  
K. M. Bedka ◽  
J. A. Otkin ◽  
T. Greenwald ◽  
S. A. Ackerman
Keyword(s):  
Water Vapor ◽  
High Resolution ◽  
Weighting Function ◽  
Model Simulation ◽  
Wave Train ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Model Data ◽  
Mountain Wave ◽  
Mountain Waves

Abstract Prior work has shown that pilot reports of severe turbulence over Colorado often occur when complex interference or crossing wave patterns are present in satellite water vapor imagery downstream of the Rocky Mountains. To improve the understanding of these patterns, a high-resolution (1-km) Weather Research and Forecasting (WRF) model simulation was performed for an intense mountain-wave event that occurred on 6 March 2004. Synthetic satellite imagery was subsequently generated by passing the model-simulated data through a forward radiative transfer model. Comparison with concurrent Moderate Resolution Imaging Spectroradiometer (MODIS) water vapor imagery demonstrates that the synthetic satellite data realistically captured many of the observed mesoscale features, including a mountain-wave train extending far downstream of the Colorado Front Range, the deformation of this wave train by an approaching cold front, and the substantially warmer brightness temperatures in the lee of the major mountain ranges composing the Colorado Rockies. Inspection of the model data revealed that the mountain waves redistributed the water vapor within the lower and middle troposphere, with the maximum column-integrated water vapor content occurring one-quarter wavelength downstream of the maximum ascent within each mountain wave. Due to this phase shift, the strongest vertical motions occur halfway between the locally warm and cool brightness temperature couplets in the water vapor imagery. Interference patterns seen in the water vapor imagery appear to be associated with mesoscale variability in the ambient wind field at or near mountaintop due to flow interaction with the complex topography. It is also demonstrated that the synergistic use of multiple water vapor channels provides a more thorough depiction of the vertical extent of the mountain waves since the weighting function for each channel peaks at a different height in the atmosphere.

scholarly journals A weak spectral signature of water vapour in the atmosphere of HD 179949 b at high spectral resolution in the L band

2020 ◽  
Vol 494 (1) ◽  
pp. 108-119 ◽  
Author(s):  
Rebecca K Webb ◽  
Matteo Brogi ◽  
Siddharth Gandhi ◽  
Michael R Line ◽  
Jayne L Birkby ◽  
...  
Keyword(s):  
High Resolution ◽  
Radial Velocity ◽  
Semimajor Axis ◽  
Spectral Lines ◽  
Lapse Rate ◽  
High Spectral Resolution ◽  
High Resolution Spectroscopy ◽  
Spectral Signature ◽  
Orbital Inclination ◽  
L Band

ABSTRACT High-resolution spectroscopy ($R\, \geqslant \, 20\, 000$) is currently the only known method to constrain the orbital solution and atmospheric properties of non-transiting hot Jupiters. It does so by resolving the spectral features of the planet into a forest of spectral lines and directly observing its Doppler shift while orbiting the host star. In this study, we analyse VLT/CRIRES ($R=100\, 000$) L-band observations of the non-transiting giant planet HD 179949 b centred around 3.5 ${\mu {m}}$. We observe a weak (3.0σ, or S/N = 4.8) spectral signature of H2O in absorption contained within the radial velocity of the planet at superior-conjunction, with a mild dependence on the choice of line list used for the modelling. Combining this data with previous observations in the K band, we measure a detection significance of 8.4 σ for an atmosphere that is most consistent with a shallow lapse-rate, solar C/O ratio, and with CO and H2O being the only major sources of opacity in this wavelength range. As the two sets of data were taken 3 yr apart, this points to the absence of strong radial-velocity anomalies due, e.g. to variability in atmospheric circulation. We measure a projected orbital velocity for the planet of KP = (145.2 ± 2.0) km s−1 (1σ) and improve the error bars on this parameter by ∼70 per cent. However, we only marginally tighten constraints on orbital inclination ($66.2^{+3.7}_{-3.1}$ deg) and planet mass ($0.963^{+0.036}_{-0.031}$ Jupiter masses), due to the dominant uncertainties of stellar mass and semimajor axis. Follow ups of radial-velocity planets are thus crucial to fully enable their accurate characterization via high-resolution spectroscopy.

scholarly journals Using a Parameterization of a Radiative Transfer Model to Build High-Resolution Maps of Typical Clear-Sky UV Index in Catalonia, Spain

2005 ◽  
Vol 44 (6) ◽  
pp. 789-803 ◽  
Author(s):  
Jordi Badosa ◽  
Josep-Abel González ◽  
Josep Calbó ◽  
Michiel van Weele ◽  
Richard L. McKenzie
Keyword(s):  
High Resolution ◽  
Radiative Transfer ◽  
Zenith Angle ◽  
Solar Zenith Angle ◽  
Absolute Error ◽  
Single Scattering ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Uv Index ◽  
Wide Range

Abstract To perform a climatic analysis of the annual UV index (UVI) variations in Catalonia, Spain (northeast of the Iberian Peninsula), a new simple parameterization scheme is presented based on a multilayer radiative transfer model. The parameterization performs fast UVI calculations for a wide range of cloudless and snow-free situations and can be applied anywhere. The following parameters are considered: solar zenith angle, total ozone column, altitude, aerosol optical depth, and single-scattering albedo. A sensitivity analysis is presented to justify this choice with special attention to aerosol information. Comparisons with the base model show good agreement, most of all for the most common cases, giving an absolute error within ±0.2 in the UVI for a wide range of cases considered. Two tests are done to show the performance of the parameterization against UVI measurements. One uses data from a high-quality spectroradiometer from Lauder, New Zealand [45.04°S, 169.684°E, 370 m above mean sea level (MSL)], where there is a low presence of aerosols. The other uses data from a Robertson–Berger-type meter from Girona, Spain (41.97°N, 2.82°E, 100 m MSL), where there is more aerosol load and where it has been possible to study the effect of aerosol information on the model versus measurement comparison. The parameterization is applied to a climatic analysis of the annual UVI variation in Catalonia, showing the contributions of solar zenith angle, ozone, and aerosols. High-resolution seasonal maps of typical UV index values in Catalonia are presented.

Exploring continuous time series of vegetation hyperspectral reflectance and solar-induced fluorescence through radiative transfer model inversion

2020 ◽  
Author(s):  
Marco Celesti ◽  
Khelvi Biriukova ◽  
Petya K. E. Campbell ◽  
Ilaria Cesana ◽  
Sergio Cogliati ◽  
...  
Keyword(s):  
Time Series ◽  
Radiative Transfer ◽  
Near Infrared ◽  
Plant Traits ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Optimization Approach ◽  
Ancillary Data ◽  
Full Spectrum ◽  
Retrieval Scheme

<p>Remote sensing of solar-induced chlorophyll fluorescence (SIF) is of growing interest for the scientific community due to the inherent link of SIF with vegetation photosynthetic activity. An increasing number of in situ and airborne fluorescence spectrometers has been deployed worldwide to advance the understanding and usage of SIF for ecosystem studies. Particularly, a number of sites has been instrumented with the FloX (J&B Hyperspectral Devices, Germany), an automated instrument that houses two high resolution spectrometers covering the visible and near infrared spectral regions, one specifically optimized for fluorescence retrieval, the other for plant trait estimation.</p><p>In this contribution we explore the feasibility to consistently retrieve plant traits and SIF from canopy level FloX measurements through the numerical inversion of a light version of the SCOPE model. The optimization approach was specifically adapted to work with the high- frequency time series produced by the FloX. In this context, a strategy for optimal retrieval of plant traits at daily scale is discussed, together with the implementation of an emulator of the radiative transfer model in the retrieval scheme. The retrieval strategy was applied to site measurements across Europe and the US that span a variety of natural and agricultural ecosystems.</p><p>The full spectrum of canopy SIF, the fluorescence quantum efficiency, and main plant traits controlling light absorption and reabsorption were retrieved concurrently and evaluated over the growing season in comparison with site-specific ancillary data. Improvements and challenges of this method compared to other retrievals are discussed, together with the potential of applying a similar retrieval scheme to airborne datasets acquired with e.g. the HyPlant sensor, or the reconfigured “FLEX mode” data acquired with the recently launched Sentinel-3B during its commissioning phase.</p>

scholarly journals Clear-Sky Mask for the Advanced Clear-Sky Processor for Oceans

2010 ◽  
Vol 27 (10) ◽  
pp. 1609-1623 ◽  
Author(s):  
B. Petrenko ◽  
A. Ignatov ◽  
Y. Kihai ◽  
A. Heidinger
Keyword(s):  
High Resolution ◽  
Radiative Transfer ◽  
Weather Prediction ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Clear Sky ◽  
Brightness Temperatures ◽  
Spatial Uniformity ◽  
Uniformity Test ◽  
Cross Platform

Abstract The Advanced Clear Sky Processor for Oceans (ACSPO) generates clear-sky products, such as SST, clear-sky radiances, and aerosol, from Advanced Very High Resolution Radiometer (AVHRR)-like measurements. The ACSPO clear-sky mask (ACSM) identifies clear-sky pixels within the ACSPO products. This paper describes the ACSM structure and compares the performances of ACSM and its predecessor, Clouds from AVHRR Extended Algorithm (CLAVRx). ACSM essentially employs online clear-sky radiative transfer simulations enabled within ACSPO with the Community Radiative Transfer Model (CRTM) in conjunction with numerical weather prediction atmospheric [Global Forecast System (GFS)] and SST [Reynolds daily high-resolution blended SST (DSST)] fields. The baseline ACSM tests verify the accuracy of fitting observed brightness temperatures with CRTM, check retrieved SST for consistency with Reynolds SST, and identify ambient cloudiness at the boundaries of cloudy systems. Residual cloud effects are screened out with several tests, adopted from CLAVRx, and with the SST spatial uniformity test designed to minimize misclassification of sharp SST gradients as clouds. Cross-platform and temporal consistencies of retrieved SSTs are maintained by accounting for SST and brightness temperature biases, estimated within ACSPO online and independently from ACSM. The performance of ACSM is characterized in terms of statistics of deviations of retrieved SST from the DSST. ACSM increases the amount of “clear” pixels by 30% to 40% and improves statistics of retrieved SST compared with CLAVRx. ACSM is also shown to be capable of producing satisfactory statistics of SST anomalies if the reference SST field for the exact date of observations is unavailable at the time of processing.

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