scholarly journals The QME AERI LBLRTM: A Closure Experiment for Downwelling High Spectral Resolution Infrared Radiance

2004 ◽  
Vol 61 (22) ◽  
pp. 2657-2675 ◽  
Author(s):  
D. D. Turner ◽  
D. C. Tobin ◽  
S. A. Clough ◽  
P. D. Brown ◽  
R. G. Ellingson ◽  
...  

Abstract Research funded by the U.S. Department of Energy's Atmospheric Radiation Measurement (ARM) program has led to significant improvements in longwave radiative transfer modeling over the last decade. These improvements, which have generally come in small incremental changes, were made primarily in the water vapor self- and foreign-broadened continuum and the water vapor absorption line parameters. These changes, when taken as a whole, result in up to a 6 W m−2 improvement in the modeled clear-sky downwelling longwave radiative flux at the surface and significantly better agreement with spectral observations. This paper provides an overview of the history of ARM with regard to clear-sky longwave radiative transfer, and analyzes remaining related uncertainties in the ARM state-of-the-art Line-by-Line Radiative Transfer Model (LBLRTM). A quality measurement experiment (QME) for the downwelling infrared radiance at the ARM Southern Great Plains site has been ongoing since 1994. This experiment has three objectives: 1) to validate and improve the absorption models and spectral line parameters used in line-by-line radiative transfer models, 2) to assess the ability to define the atmospheric state, and 3) to assess the quality of the radiance observations that serve as ground truth for the model. Analysis of data from 1994 to 1997 made significant contributions to optimizing the QME, but is limited by small but significant uncertainties and deficiencies in the atmospheric state and radiance observations. This paper concentrates on the analysis of QME data from 1998 to 2001, wherein the data have been carefully selected to address the uncertainties in the 1994–97 dataset. Analysis of this newer dataset suggests that the representation of self-broadened water vapor continuum absorption is 3%–8% too strong in the 750–1000 cm−1 region. The dataset also provides information on the accuracy of the self- and foreign-broadened continuum absorption in the 1100–1300 cm−1 region. After accounting for these changes, remaining differences in modeled and observed downwelling clear-sky fluxes are less than 1.5 W m−2 over a wide range of atmospheric states.

2016 ◽  
Author(s):  
C. J. Cox ◽  
P. M. Rowe ◽  
S. P. Neshyba ◽  
V. P. Walden

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).


2014 ◽  
Vol 31 (7) ◽  
pp. 1502-1515 ◽  
Author(s):  
Maziar Bani Shahabadi ◽  
Yi Huang

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.


2016 ◽  
Vol 8 (1) ◽  
pp. 199-211 ◽  
Author(s):  
Christopher J. Cox ◽  
Penny M. Rowe ◽  
Steven P. Neshyba ◽  
Von P. Walden

Abstract. Cloud microphysical and macrophysical properties are critical for understanding the role of clouds in climate. These properties are commonly retrieved from ground-based and satellite-based infrared remote sensing instruments. 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 260 cloudy cases from 50 to 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 NSF Arctic Data Center data repository (doi:10.5065/D61J97TT).


2009 ◽  
Vol 9 (19) ◽  
pp. 7397-7417 ◽  
Author(s):  
M. W. Shephard ◽  
S. A. Clough ◽  
V. H. Payne ◽  
W. L. Smith ◽  
S. Kireev ◽  
...  

Abstract. Presented here are comparisons between the Infrared Atmospheric Sounding instrument (IASI) and the "Line-By-Line Radiative Transfer Model" (LBLRTM). Spectral residuals from radiance closure studies during the IASI JAIVEx validation campaign provide insight into a number of spectroscopy issues relevant to remote sounding of temperature, water vapor and trace gases from IASI. In order to perform quality IASI trace gas retrievals, the temperature and water vapor fields must be retrieved as accurately as possible. In general, the residuals in the CO2 ν2 region are of the order of the IASI instrument noise. However, outstanding issues with the CO2 spectral regions remain. There is a large residual ~−1.7 K in the 667 cm−1 Q-branch, and residuals in the CO2 ν2 and N2O/CO2 ν3 spectral regions that sample the troposphere are inconsistent, with the N2O/CO2 ν3 region being too negative (warmer) by ~0.7 K. Residuals on this lower wavenumber side of the CO2 ν3 band will be improved by line parameter updates, while future efforts to reduce the residuals reaching ~−0.5 K on the higher wavenumber side of the CO2 ν3 band will focus on addressing limitations in the modeling of the CO2 line shape (line coupling and duration of collision) effects. Brightness temperature residuals from the radiance closure studies in the ν2 water vapor band have standard deviations of ~0.2–0.3 K with some large peak residuals reaching ±0.5–1.0 K. These are larger than the instrument noise indicating that systematic errors still remain. New H2O line intensities and positions have a significant impact on the retrieved water vapor, particularly in the upper troposphere where the water vapor retrievals are 10% drier when using line intensities compared with HITRAN 2004. In addition to O3, CH4, and CO, of the IASI instrument combined with an accurate forward model allows for the detection of minor species with weak atmospheric signatures in the nadir radiances, such as HNO3 and OCS.


2018 ◽  
Vol 10 (10) ◽  
pp. 1632 ◽  
Author(s):  
Bin Yang ◽  
Yuri Knyazikhin ◽  
Donghui Xie ◽  
Haimeng Zhao ◽  
Junqiang Zhang ◽  
...  

Interpreting remotely-sensed data requires realistic, but simple, models of radiative transfer that occurs within a vegetation canopy. In this paper, an improved version of the stochastic radiative transfer model (SRTM) is proposed by assuming that all photons that have not been specularly reflected enter the leaf interior. The contribution of leaf specular reflection is considered by modifying leaf scattering phase function using Fresnel reflectance. The canopy bidirectional reflectance factor (BRF) estimated from this model is evaluated through comparisons with field-measured maize BRF. The result shows that accounting for leaf specular reflection can provide better performance than that when leaf specular reflection is neglected over a wide range of view zenith angles. The improved version of the SRTM is further adopted to investigate the influence of leaf specular reflection on the canopy radiative regime, with emphases on vertical profiles of mean radiation flux density, canopy absorptance, BRF, and normalized difference vegetation index (NDVI). It is demonstrated that accounting for leaf specular reflection can increase leaf albedo, which consequently increases canopy mean upward/downward mean radiation flux density and canopy nadir BRF and decreases canopy absorptance and canopy nadir NDVI when leaf angles are spherically distributed. The influence is greater for downward/upward radiation flux densities and canopy nadir BRF than that for canopy absorptance and NDVI. The results provide knowledge of leaf specular reflection and canopy radiative regime, and are helpful for forward reflectance simulations and backward inversions. Moreover, polarization measurements are suggested for studies of leaf specular reflection, as leaf specular reflection is closely related to the canopy polarization.


2018 ◽  
Vol 75 (7) ◽  
pp. 2217-2233 ◽  
Author(s):  
Guanglin Tang ◽  
Ping Yang ◽  
George W. Kattawar ◽  
Xianglei Huang ◽  
Eli J. Mlawer ◽  
...  

Abstract Cloud longwave scattering is generally neglected in general circulation models (GCMs), but it plays a significant and highly uncertain role in the atmospheric energy budget as demonstrated in recent studies. To reduce the errors caused by neglecting cloud longwave scattering, two new radiance adjustment methods are developed that retain the computational efficiency of broadband radiative transfer simulations. In particular, two existing scaling methods and the two new adjustment methods are implemented in the Rapid Radiative Transfer Model (RRTM). The results are then compared with those based on the Discrete Ordinate Radiative Transfer model (DISORT) that explicitly accounts for multiple scattering by clouds. The two scaling methods are shown to improve the accuracy of radiative transfer simulations for optically thin clouds but not effectively for optically thick clouds. However, the adjustment methods reduce computational errors over a wide range, from optically thin to thick clouds. With the adjustment methods, the errors resulting from neglecting cloud longwave scattering are reduced to less than 2 W m−2 for the upward irradiance at the top of the atmosphere and less than 0.5 W m−2 for the surface downward irradiance. The adjustment schemes prove to be more accurate and efficient than a four-stream approximation that explicitly accounts for multiple scattering. The neglect of cloud longwave scattering results in an underestimate of the surface downward irradiance (cooling effect), but the errors are almost eliminated by the adjustment methods (warming effect).


2005 ◽  
Vol 44 (6) ◽  
pp. 789-803 ◽  
Author(s):  
Jordi Badosa ◽  
Josep-Abel González ◽  
Josep Calbó ◽  
Michiel van Weele ◽  
Richard L. McKenzie

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.


2012 ◽  
Vol 5 (2) ◽  
pp. 2221-2271
Author(s):  
P. Liebing ◽  
K. Bramstedt ◽  
S. Noël ◽  
V. Rozanov ◽  
H. Bovensmann ◽  
...  

Abstract. SCIAMACHY is a passive imaging spectrometer onboard ENVISAT, designed to obtain trace gas abundances from measured radiances and irradiances in the UV to SWIR range in nadir, limb and occultation viewing modes. Its grating spectrometer introduces a substantial sensitivity to the polarization of the incoming light with nonnegligible effects on the radiometric calibration. To be able to correct for the polarization sensitivity, SCIAMACHY utilizes broadband Polarization Measurement Devices (PMDs). While for the nadir viewing mode the measured atmospheric polarization has been validated against POLDER data (Tilstra and Stammes, 2007, 2010), a similar validation study regarding the limb viewing mode has not yet been performed. This paper aims at an assessment of the quality of the SCIAMACHY limb polarization data. Since limb polarization measurements by other air- or spaceborne instruments in the spectral range of SCIAMACHY are not available, a comparison with radiative transfer simulations by SCIATRAN V3.1(Rozanov et al., 2012) using a wide range of atmospheric parameters is performed. SCIATRAN is a vector radiative transfer model (VRTM) capable of performing calculations of the multiply scattered radiance in a~spherically symmetric atmosphere. The study shows that the limb polarization data exhibit a large systematic bias which is decreasing with wavelength. The most likely reason for this bias is an instrumental phase shift which changes the relative contributions of different Stokes vector components to the PMD signal as compared to on-ground calibration measurements. It is also shown that it is in principle feasible to recalibrate the polarization sensitivity using the in-flight data and the VRTM simulations, enabling also the monitoring of its degradation. Together with an optimization of the algorithm used to calculate the in-flight polarization data an improved polarization correction can increase the radiometric accuracy of SCIAMACHY limb radiance spectra substantially.


2013 ◽  
Vol 6 (6) ◽  
pp. 1503-1520 ◽  
Author(s):  
P. Liebing ◽  
K. Bramstedt ◽  
S. Noël ◽  
V. Rozanov ◽  
H. Bovensmann ◽  
...  

Abstract. SCIAMACHY is a passive imaging spectrometer onboard ENVISAT designed to obtain trace gas abundances from measured radiances and irradiances in the UV to SWIR range in nadir-, limb- and occultation-viewing modes. Its grating spectrometer introduces a substantial sensitivity to the polarization of the incoming light with nonnegligible effects on the radiometric calibration. To be able to correct for the polarization sensitivity, SCIAMACHY utilizes broadband Polarization Measurement Devices (PMDs). While for the nadir-viewing mode the measured atmospheric polarization has been validated against POLDER data (Tilstra and Stammes, 2007, 2010), a similar validation study regarding the limb-viewing mode has not yet been performed. This paper aims at an assessment of the quality of the SCIAMACHY limb polarization data. Since limb polarization measurements by other air/spaceborne instruments in the spectral range of SCIAMACHY are not available, a comparison with radiative transfer simulations by SCIATRAN V3.1 (Rozanov et al., 2013) using a wide range of atmospheric parameters is performed. SCIATRAN is a vector radiative transfer model (VRTM) capable of performing calculations of the multiply scattered radiance in a spherically symmetric atmosphere. The study shows that the limb polarization data exhibit a large time-dependent bias that decreases with wavelength. Possible reasons for this bias are a still unknown combination of insufficient accuracy or inconsistencies of the on-ground calibration data, scan mirror degradation and stress induced changes of the polarization response of components inside the optical bench of the instrument. It is shown that it should in principle be feasible to recalibrate the effective polarization sensitivity of the instrument using the in-flight data and VRTM simulations.


2010 ◽  
Vol 27 (10) ◽  
pp. 1609-1623 ◽  
Author(s):  
B. Petrenko ◽  
A. Ignatov ◽  
Y. Kihai ◽  
A. Heidinger

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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