Development of a remote sensing algorithm to retrieve atmospheric aerosol properties using multiwavelength and multipixel information

NASA Astrophysics Data System (ADS)

Hashimoto, Makiko; Nakajima, Teruyuki

2017-06-01

We developed a satellite remote sensing algorithm to retrieve the aerosol optical properties using satellite-received radiances for multiple wavelengths and pixels. Our algorithm utilizes spatial inhomogeneity of surface reflectance to retrieve aerosol properties, and the main target is urban aerosols. This algorithm can simultaneously retrieve aerosol optical thicknesses (AOT) for fine- and coarse-mode aerosols, soot volume fraction in fine-mode aerosols (SF), and surface reflectance over heterogeneous surfaces such as urban areas that are difficult to obtain by conventional pixel-by-pixel methods. We applied this algorithm to radiances measured by the Greenhouse Gases Observing Satellite/Thermal and Near Infrared Sensor for Carbon Observations-Cloud and Aerosol Image (GOSAT/TANSO-CAI) at four wavelengths and were able to retrieve the aerosol parameters in several urban regions and other surface types. A comparison of the retrieved AOTs with those from the Aerosol Robotic Network (AERONET) indicated retrieval accuracy within ±0.077 on average. It was also found that the column-averaged SF and the aerosol single scattering albedo (SSA) underwent seasonal changes as consistent with the ground surface measurements of SSA and black carbon at Beijing, China.

Retrieving cloud, dust and ozone abundances in the Martian atmosphere using SPICAM/UV nadir spectra

NASA Astrophysics Data System (ADS)

Willame, Y.; Vandaele, A. C.; Depiesse, C.; Lefèvre, F.; Letocart, V.; Gillotay, D.; Montmessin, F.

2017-08-01

We present the retrieval algorithm developed to analyse nadir spectra from SPICAM/UV aboard Mars-Express. The purpose is to retrieve simultaneously several parameters of the Martian atmosphere and surface: the dust optical depth, the ozone total column, the cloud opacity and the surface albedo. The retrieval code couples the use of an existing complete radiative transfer code, an inversion method and a cloud detection algorithm. We describe the working principle of our algorithm and the parametrisation used to model the required absorption, scattering and reflection processes of the solar UV radiation that occur in the Martian atmosphere and at its surface. The retrieval method has been applied on 4 Martian years of SPICAM/UV data to obtain climatologies of the different quantities under investigation. An overview of the climatology is given for each species showing their seasonal and spatial distributions. The results show a good qualitative agreement with previous observations. Quantitative comparisons of the retrieved dust optical depths indicate generally larger values than previous studies. Possible shortcomings in the dust modelling (altitude profile) have been identified and may be part of the reason for this difference. The ozone results are found to be influenced by the presence of clouds. Preliminary quantitative comparisons show that our retrieved ozone columns are consistent with other results when no ice clouds are present, and are larger for the cases with clouds at high latitude. Sensitivity tests have also been performed showing that the use of other a priori assumptions such as the altitude distribution or some scattering properties can have an important impact on the retrieval.

New-Generation NASA Aura Ozone Monitoring Instrument (OMI) Volcanic SO2 Dataset: Algorithm Description, Initial Results, and Continuation with the Suomi-NPP Ozone Mapping and Profiler Suite (OMPS)

NASA Technical Reports Server (NTRS)

Li, Can; Krotkov, Nickolay A.; Carn, Simon; Zhang, Yan; Spurr, Robert J. D.; Joiner, Joanna

2017-01-01

Since the fall of 2004, the Ozone Monitoring Instrument (OMI) has been providing global monitoring of volcanic SO2 emissions, helping to understand their climate impacts and to mitigate aviation hazards. Here we introduce a new-generation OMI volcanic SO2 dataset based on a principal component analysis (PCA) retrieval technique. To reduce retrieval noise and artifacts as seen in the current operational linear fit (LF) algorithm, the new algorithm, OMSO2VOLCANO, uses characteristic features extracted directly from OMI radiances in the spectral fitting, thereby helping to minimize interferences from various geophysical processes (e.g., O3 absorption) and measurement details (e.g., wavelength shift). To solve the problem of low bias for large SO2 total columns in the LF product, the OMSO2VOLCANO algorithm employs a table lookup approach to estimate SO2 Jacobians (i.e., the instrument sensitivity to a perturbation in the SO2 column amount) and iteratively adjusts the spectral fitting window to exclude shorter wavelengths where the SO2 absorption signals are saturated. To first order, the effects of clouds and aerosols are accounted for using a simple Lambertian equivalent reflectivity approach. As with the LF algorithm, OMSO2VOLCANO provides total column retrievals based on a set of predefined SO2 profiles from the lower troposphere to the lower stratosphere, including a new profile peaked at 13 km for plumes in the upper troposphere. Examples given in this study indicate that the new dataset shows significant improvement over the LF product, with at least 50% reduction in retrieval noise over the remote Pacific. For large eruptions such as Kasatochi in 2008 (approximately 1700 kt total SO2/ and Sierra Negra in 2005 (greater than 1100DU maximum SO2), OMSO2VOLCANO generally agrees well with other algorithms that also utilize the full spectral content of satellite measurements, while the LF algorithm tends to underestimate SO2. We also demonstrate that, despite the coarser spatial and spectral resolution of the Suomi National Polar-orbiting Partnership (Suomi-NPP) Ozone Mapping and Profiler Suite (OMPS) instrument, application of the new PCA algorithm to OMPS data produces highly consistent retrievals between OMI and OMPS. The new PCA algorithm is therefore capable of continuing the volcanic SO2 data record well into the future using current and future hyperspectral UV satellite instruments.

Tropospheric NO2 retrieved from OMI, GOME(-2), and SCIAMACHY within the Quality Assurance For Essential Climate Variables (QA4ECV) project: retrieval improvement, harmonization, and quality assurance

NASA Astrophysics Data System (ADS)

Folkert Boersma, K.

2017-04-01

One of the prime targets of the EU-project Quality Assurance for Essential Climate Variables (QA4ECV, www.qa4ecv.eu) is the generation and subsequent quality assurance of harmonized, long-term data records of ECVs or precursors thereof. Here we report on a new harmonized and improved retrieval algorithm for NO2 columns and its application to spectra measured by the GOME, SCIAMACHY, OMI, and GOME-2(A) sensors over the period 1996-2016. Our community 'best practices' algorithm is based on the classical 3-step DOAS method. It benefits from a thorough comparison and iteration of spectral fitting and air mass factor calculation approaches between IUP Bremen, BIRA, Max Planck Institute for Chemistry, KNMI, WUR, and a number of external partners. For step 1 of the retrieval, we show that improved spectral calibration and the inclusion of liquid water and intensity-offset correction terms in the fitting procedure, lead to 10-30% smaller NO2 slant columns, in better agreement with independent measurements. Moreover, the QA4ECV NO2 slant columns show 15-35% lower uncertainties relative to earlier versions of the spectral fitting algorithm. For step 2, the stratospheric correction, the algorithm relies on the assimilation of NO2 slant columns over remote regions in the Tracer Model 5 (TM5-MP) chemistry transport model. The representation of stratospheric NOy in the model is improved by nudging towards ODIN HNO3:O3 ratios, leading to more realistic NO2 concentrations in the free-running mode, which is relevant at high latitudes near the terminator. The coupling to TM5-Mass Parallel also allows the calculation of air mass factors (AMFs, step 3) from a priori NO2 vertical profiles simulated at a spatial resolution of 1°×1°, so that hotspot gradients are better resolved in the a priori profile shapes. Other AMF improvements include the use of improved cloud information, and a correction for photon scattering in a spherical atmosphere. Preliminary comparisons indicate that the new QA4ECV tropospheric NO2 columns are ±10% lower than operational products, and provide more spatial detail on the horizontal distribution of NO2 in the troposphere. Our comparisons provide more insight in the origin and nature of the retrieval uncertainties. The final QAECV NO2 product therefore contains overall uncertainty estimates for every measurement, but also information on the contribution of uncertainties of each retrieval sub-step to the overall uncertainty budget. We conclude with a presentation of the data format and a verification of the QA4ECV NO2 columns using the traceable quality assurance methodologies developed in the QA4ECV-project, and via validation against independent measurements (using the online QA4ECV Atmospheric Validation Server tool).

Improved Determination of Surface and Atmospheric Temperatures Using Only Shortwave AIRS Channels: The AIRS Version 6 Retrieval Algorithm

NASA Technical Reports Server (NTRS)

Susskind, Joel; Blaisdell, John; Iredell, Lena

2010-01-01

AIRS was launched on EOS Aqua on May 4, 2002 together with ASMU-A and HSB to form a next generation polar orbiting infrared and microwave atmosphere sounding system (Pagano et al 2003). The theoretical approach used to analyze AIRS/AMSU/HSB data in the presence of clouds in the AIRS Science Team Version 3 at-launch algorithm, and that used in the Version 4 post-launch algorithm, have been published previously. Significant theoretical and practical improvements have been made in the analysis of AIRS/AMSU data since the Version 4 algorithm. Most of these have already been incorporated in the AIRS Science Team Version 5 algorithm (Susskind et al 2010), now being used operationally at the Goddard DISC. The AIRS Version 5 retrieval algorithm contains three significant improvements over Version 4. Improved physics in Version 5 allowed for use of AIRS clear column radiances (R(sub i)) in the entire 4.3 micron CO2 absorption band in the retrieval of temperature profiles T(p) during both day and night. Tropospheric sounding 15 micron CO2 observations were used primarily in the generation of clear column radiances (R(sub i)) for all channels. This new approach allowed for the generation of accurate Quality Controlled values of R(sub i) and T(p) under more stressing cloud conditions. Secondly, Version 5 contained a new methodology to provide accurate case-by-case error estimates for retrieved geophysical parameters and for channel-by-channel clear column radiances. Thresholds of these error estimates are used in a new approach for Quality Control. Finally, Version 5 contained for the first time an approach to provide AIRS soundings in partially cloudy conditions that does not require use of any microwave data. This new AIRS Only sounding methodology was developed as a backup to AIRS Version 5 should the AMSU-A instrument fail. Susskind et al 2010 shows that Version 5 AIRS Only sounding are only slightly degraded from the AIRS/AMSU soundings, even at large fractional cloud cover.

Operational trace gas column observations from GOME-2 on MetOp

NASA Astrophysics Data System (ADS)

Valks, Pieter; Hao, Nan; Pinardi, Gaia; Hedelt, Pascal; Liu, Song; Van Roozendael, Michel; De Smedt, Isabelle; Theys, Nicolas; Koukouli, MariLiza; Balis, Dimitris

2017-04-01

This contribution focuses on the operational GOME-2 trace gas column products developed in the framework of EUMETSAT's Satellite Application Facility on Atmospheric Composition Monitoring (AC-SAF). We present an overview of the retrieval algorithms for ozone, OClO, NO2, SO2 and formaldehyde, and we show examples of various applications such as air quality and climate monitoring, using observations from the GOME-2 instruments on MetOp-A and MetOp-B. Total ozone and the minor trace gas columns from GOME-2 are retrieved with the latest version 4.8 of the GOME Data Processor (GDP), which uses an optimized Differential Optical Absorption Spectroscopy (DOAS) algorithm, with air mass factor conversions based on the LIDORT model. Improved total and tropospheric NO2 columns are retrieved in the visible wavelength region between 425 and 497 nm. SO2 emissions from volcanic and anthropogenic sources can be measured by GOME-2 using the UV wavelength region around 320 nm. For formaldehyde, an optimal DOAS fitting window around 335 nm has been determined for GOME-2. The GOME-2 trace gas columns have reached the operational EUMETSAT product status, and are available to the users in near real time (within two hours after sensing by GOME-2). The use of trace gas observations from the GOME-2 instruments on MetOp-A and MetOp-B for air quality purposed will be illustrated, e.g. for South-East Asia and Europe. Furthermore, comparisons of the GOME-2 satellite observations with ground-based measurements will be shown. Finally, the use of GOME-2 trace-gas column data in the Copernicus Atmosphere Monitoring Service (CAMS) will be presented.

An Integrated Retrieval Framework for AMSR2: Implications for Light Precipitation and Sea Ice Edge Detectability

NASA Astrophysics Data System (ADS)

Duncan, D.; Kummerow, C. D.; Meier, W.

2016-12-01

Over the lifetime of AMSR-E, operational retrieval algorithms were developed and run for precipitation, ocean suite (SST, wind speed, cloud liquid water path, and column water vapor over ocean), sea ice, snow water equivalent, and soil moisture. With a separate algorithm for each group, the retrievals were never interactive or integrated in any way despite many co-sensitivities. AMSR2, the follow-on mission to AMSR-E, retrieves the same parameters at a slightly higher spatial resolution. We have combined the operational algorithms for AMSR2 in a way that facilitates sharing information between the retrievals. Difficulties that arose were mainly related to calibration, spatial resolution, coastlines, and order of processing. The integration of all algorithms for AMSR2 has numerous benefits, including better detection of light precipitation and sea ice, fewer screened out pixels, and better quality flags. Integrating the algorithms opens up avenues for investigating the limits of detectability for precipitation from a passive microwave radiometer and the impact of spatial resolution on sea ice edge detection; these are investigated using CloudSat and MODIS coincident observations from the A-Train constellation.

Report of the International Ozone Trends Panel 1988, volume 1

NASA Technical Reports Server (NTRS)

1989-01-01

Chapters on the following topics are presented: spacecraft instrument calibration and stability; information content of ozone retrieval algorithms; trends in total column ozone measurements; and trends in ozone profile measurement.

CO2 profile retrievals from TCCON spectra

NASA Astrophysics Data System (ADS)

Dohe, Susanne; Hase, Frank; Sepúlveda, Eliezer; García, Omaira; Wunch, Debra; Wennberg, Paul; Gómez-Peláez, Angel; Abshire, James B.; Wofsy, Steven C.; Schneider, Matthias; Blumenstock, Thomas

2014-05-01

The Total Carbon Column Observing Network (TCCON) is a global network of ground-based Fourier Transform Spectrometers recording direct solar spectra in the near-infrared spectral region. With stringent requirements on the instrumentation, data processing and calibration, accurate and precise column-averaged abundances of CO2, CH4, N2O, HF, CO, H2O, and HDO are retrieved being an essential contribution for the validation of satellite data (e.g. GOSAT, OCO-2) and carbon cycle research (Olsen and Randerson, 2004). However, the determined column-averaged dry air mole fraction (DMF) contains no information about the vertical CO2 profile, due to the use of a simple scaling retrieval within the common TCCON analysis, where the fitting algorithm GFIT (e.g. Yang et al., 2005) is used. In this presentation we will apply a different procedure for calculating trace gas abundances from the measured spectra, the fitting algorithm PROFFIT (Hase et. al., 2004) which has been shown to be in very good accordance with GFIT. PROFFIT additionally offers the ability to perform profile retrievals in which the pressure broadening effect of absorption lines is used to retrieve vertical gas profiles, being of great interest especially for the CO2 modelling community. A new analyzing procedure will be shown and retrieved vertical CO2 profiles of the TCCON sites Izaña (Tenerife, Canary Islands, Spain) and Lamont (Oklahoma, USA) will be presented and compared with simultaneously performed surface in-situ measurements and CO2 profiles from different aircraft campaigns. References: - Hase, F. et al., J.Q.S.R.T. 87, 25-52, 2004. - Olsen, S.C. and Randerson, J.T., J.G.Res., 109, D023012, 2004. - Yang, Z. et al., J.Q.S.R.T., 90, 309-321, 2005.

Lidar-Radiometer Inversion Code (LIRIC) for the Retrieval of Vertical Aerosol Properties from Combined Lidar Radiometer Data: Development and Distribution in EARLINET

NASA Technical Reports Server (NTRS)

Chaikovsky, A.; Dubovik, O.; Holben, Brent N.; Bril, A.; Goloub, P.; Tanre, D.; Pappalardo, G.; Wandinger, U.; Chaikovskaya, L.; Denisov, S.;

Orbiting Carbon Observatory-2 (OCO-2) cloud screening algorithms: validation against collocated MODIS and CALIOP data

NASA Astrophysics Data System (ADS)

Taylor, Thomas E.; O'Dell, Christopher W.; Frankenberg, Christian; Partain, Philip T.; Cronk, Heather Q.; Savtchenko, Andrey; Nelson, Robert R.; Rosenthal, Emily J.; Chang, Albert Y.; Fisher, Brenden; Osterman, Gregory B.; Pollock, Randy H.; Crisp, David; Eldering, Annmarie; Gunson, Michael R.

2016-03-01

The objective of the National Aeronautics and Space Administration's (NASA) Orbiting Carbon Observatory-2 (OCO-2) mission is to retrieve the column-averaged carbon dioxide (CO2) dry air mole fraction (XCO2) from satellite measurements of reflected sunlight in the near-infrared. These estimates can be biased by clouds and aerosols, i.e., contamination, within the instrument's field of view. Screening of the most contaminated soundings minimizes unnecessary calls to the computationally expensive Level 2 (L2) XCO2 retrieval algorithm. Hence, robust cloud screening methods have been an important focus of the OCO-2 algorithm development team. Two distinct, computationally inexpensive cloud screening algorithms have been developed for this application. The A-Band Preprocessor (ABP) retrieves the surface pressure using measurements in the 0.76 µm O2 A band, neglecting scattering by clouds and aerosols, which introduce photon path-length differences that can cause large deviations between the expected and retrieved surface pressure. The Iterative Maximum A Posteriori (IMAP) Differential Optical Absorption Spectroscopy (DOAS) Preprocessor (IDP) retrieves independent estimates of the CO2 and H2O column abundances using observations taken at 1.61 µm (weak CO2 band) and 2.06 µm (strong CO2 band), while neglecting atmospheric scattering. The CO2 and H2O column abundances retrieved in these two spectral regions differ significantly in the presence of cloud and scattering aerosols. The combination of these two algorithms, which are sensitive to different features in the spectra, provides the basis for cloud screening of the OCO-2 data set.To validate the OCO-2 cloud screening approach, collocated measurements from NASA's Moderate Resolution Imaging Spectrometer (MODIS), aboard the Aqua platform, were compared to results from the two OCO-2 cloud screening algorithms. With tuning of algorithmic threshold parameters that allows for processing of ≃ 20-25 % of all OCO-2 soundings, agreement between the OCO-2 and MODIS cloud screening methods is found to be ≃ 85 % over four 16-day orbit repeat cycles in both the winter (December) and spring (April-May) for OCO-2 nadir-land, glint-land and glint-water observations.No major, systematic, spatial or temporal dependencies were found, although slight differences in the seasonal data sets do exist and validation is more problematic with increasing solar zenith angle and when surfaces are covered in snow and ice and have complex topography. To further analyze the performance of the cloud screening algorithms, an initial comparison of OCO-2 observations was made to collocated measurements from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) aboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). These comparisons highlight the strength of the OCO-2 cloud screening algorithms in identifying high, thin clouds but suggest some difficulty in identifying some clouds near the surface, even when the optical thicknesses are greater than 1.

An advanced retrieval algorithm for greenhouse gases using polarization information measured by GOSAT TANSO-FTS SWIR I: Simulation study

NASA Astrophysics Data System (ADS)

Kikuchi, N.; Yoshida, Y.; Uchino, O.; Morino, I.; Yokota, T.

2016-11-01

We present an algorithm for retrieving column-averaged dry air mole fraction of carbon dioxide (XCO2) and methane (XCH4) from reflected spectra in the shortwave infrared (SWIR) measured by the TANSO-FTS (Thermal And Near infrared Sensor for carbon Observation Fourier Transform Spectrometer) sensor on board the Greenhouse gases Observing SATellite (GOSAT). The algorithm uses the two linear polarizations observed by TANSO-FTS to improve corrections to the interference effects of atmospheric aerosols, which degrade the accuracy in the retrieved greenhouse gas concentrations. To account for polarization by the land surface reflection in the forward model, we introduced a bidirectional reflection matrix model that has two parameters to be retrieved simultaneously with other state parameters. The accuracy in XCO2 and XCH4 values retrieved with the algorithm was evaluated by using simulated retrievals over both land and ocean, focusing on the capability of the algorithm to correct imperfect prior knowledge of aerosols. To do this, we first generated simulated TANSO-FTS spectra using a global distribution of aerosols computed by the aerosol transport model SPRINTARS. Then the simulated spectra were submitted to the algorithms as measurements both with and without polarization information, adopting a priori profiles of aerosols that differ from the true profiles. We found that the accuracy of XCO2 and XCH4, as well as profiles of aerosols, retrieved with polarization information was considerably improved over values retrieved without polarization information, for simulated observations over land with aerosol optical thickness greater than 0.1 at 1.6 μm.

Atmospheric Soundings from AIRS/AMSU in Partial Cloud Cover

NASA Technical Reports Server (NTRS)

Susskind, Joel; Atlas, Robert

2005-01-01

Simultaneous use of AIRS/AMSU-A observations allow for the determination of accurate atmospheric soundings under partial cloud cover conditions. The methodology involves the determination of the radiances AIRS would have seen if the AIRS fields of view were clear, called clear column radiances, and use of these radiances to infer the atmospheric and surface conditions giving rise to these clear column radiances. Susskind et al. demonstrate via simulation that accurate temperature soundings and clear column radiances can be derived from AIRS/AMSU-A observations in cases of up to 80% partial cloud cover, with only a small degradation in accuracy compared to that obtained in clear scenes. Susskind and Atlas show that these findings hold for real AIRS/AMSU-A soundings as well. For data assimilation purposes, this small degradation in accuracy is more than offset by a significant increase in spatial coverage (roughly 50% of global cases were accepted, compared to 3.6% of the global cases being diagnosed as clear), and assimilation of AIRS temperature soundings in partially cloudy conditions resulted in a larger improvement in forecast skill than when AIRS soundings were assimilated only under clear conditions. Alternatively, derived AIRS clear column radiances under partial cloud cover could also be used for data assimilation purposes. Further improvements in AIRS sounding methodology have been made since the results shown in Susskind and Atlas . A new version of the AIRS/AMSU-A retrieval algorithm, Version 4.0, was delivered to the Goddard DAAC in February 2005 for production of AIRS derived products, including clear column radiances. The major improvement in the Version 4.0 retrieval algorithm is with regard to a more flexible, parameter dependent, quality control. Results are shown of the accuracy and spatial distribution of temperature-moisture profiles and clear column radiances derived from AIRS/AMSU-A as a function of fractional cloud cover using the Version 4.0 algorithm. Use of the Version 4.0 AIRS temperature profiles increased the positive forecast impact arising from AIRS retrievals relative to what was shown in Susskind and Atlas .

Total ozone column retrieval from UV-MFRSR irradiance measurements: evaluation at Mauna Loa station

NASA Astrophysics Data System (ADS)

Zempila, Melina Maria; Fragkos, Konstantinos; Davis, John; Sun, Zhibin; Chen, Maosi; Gao, Wei

2017-09-01

The USDA UV-B Monitoring and Research Program (UVMRP) comprises of 36 climatological sites along with 4 long-duration research sites, in 27 states, one Canadian province, and the south island of New Zealand. Each station is equipped with an Ultraviolet multi-filter rotating shadowband radiometer (UV-MFRSR) which can provide response-weighted irradiances at 7 wavelengths (300, 305.5, 311.4, 317.6, 325.4, and 368 nm) with a nominal full width at half maximun of 2 nm. These UV irradiance data from the long term monitoring station at Mauna Loa, Hawaii, are used as input to a retrieval algorithm in order to derive high time frequency total ozone columns. The sensitivity of the algorithm to the different wavelength inputs is tested and the uncertainty of the retrievals is assessed based on error propagation methods. For the validation of the method, collocated hourly ozone data from the Dobson Network of the Global Monitoring Division (GMD) of the Earth System Radiation Laboratory (ESRL) under the jurisdiction of the US National Oceanic & Atmospheric Administration (NOAA) for the period 2010-2015 were used.

Regarding retrievals of methane in the atmosphere from IASI/Metop spectra and their comparison with ground-based FTIR measurements data

NASA Astrophysics Data System (ADS)

Khamatnurova, M. Yu.; Gribanov, K. G.; Zakharov, V. I.; Rokotyan, N. V.; Imasu, R.

2017-11-01

The algorithm for atmospheric methane distribution retrieval in atmosphere from IASI spectra has been developed. The feasibility of Levenberg-Marquardt method for atmospheric methane total column amount retrieval from the spectra measured by IASI/METOP modified for the case of lack of a priori covariance matrices for methane vertical profiles is studied in this paper. Method and algorithm were implemented into software package together with iterative estimation of a posteriori covariance matrices and averaging kernels for each individual retrieval. This allows retrieval quality selection using the properties of both types of matrices. Methane (XCH4) retrieval by Levenberg-Marquardt method from IASI/METOP spectra is presented in this work. NCEP/NCAR reanalysis data provided by ESRL (NOAA, Boulder, USA) were taken as initial guess. Surface temperature, air temperature and humidity vertical profiles are retrieved before methane vertical profile retrieval. The data retrieved from ground-based measurements at the Ural Atmospheric Station and data of L2/IASI standard product were used for the verification of the method and results of methane retrieval from IASI/METOP spectra.

Orbiting Carbon Observatory-2 (OCO-2) cloud screening algorithms; validation against collocated MODIS and CALIOP data

NASA Astrophysics Data System (ADS)

Taylor, T. E.; O'Dell, C. W.; Frankenberg, C.; Partain, P.; Cronk, H. Q.; Savtchenko, A.; Nelson, R. R.; Rosenthal, E. J.; Chang, A. Y.; Fisher, B.; Osterman, G.; Pollock, R. H.; Crisp, D.; Eldering, A.; Gunson, M. R.

2015-12-01

The objective of the National Aeronautics and Space Administration's (NASA) Orbiting Carbon Observatory-2 (OCO-2) mission is to retrieve the column-averaged carbon dioxide (CO2) dry air mole fraction (XCO2) from satellite measurements of reflected sunlight in the near-infrared. These estimates can be biased by clouds and aerosols within the instrument's field of view (FOV). Screening of the most contaminated soundings minimizes unnecessary calls to the computationally expensive Level 2 (L2) XCO2 retrieval algorithm. Hence, robust cloud screening methods have been an important focus of the OCO-2 algorithm development team. Two distinct, computationally inexpensive cloud screening algorithms have been developed for this application. The A-Band Preprocessor (ABP) retrieves the surface pressure using measurements in the 0.76 μm O2 A-band, neglecting scattering by clouds and aerosols, which introduce photon path-length (PPL) differences that can cause large deviations between the expected and retrieved surface pressure. The Iterative Maximum A-Posteriori (IMAP) Differential Optical Absorption Spectroscopy (DOAS) Preprocessor (IDP) retrieves independent estimates of the CO2 and H2O column abundances using observations taken at 1.61 μm (weak CO2 band) and 2.06 μm (strong CO2 band), while neglecting atmospheric scattering. The CO2 and H2O column abundances retrieved in these two spectral regions differ significantly in the presence of cloud and scattering aerosols. The combination of these two algorithms, which key off of different features in the spectra, provides the basis for cloud screening of the OCO-2 data set. To validate the OCO-2 cloud screening approach, collocated measurements from NASA's Moderate Resolution Imaging Spectrometer (MODIS), aboard the Aqua platform, were compared to results from the two OCO-2 cloud screening algorithms. With tuning to allow throughputs of ≃ 30 %, agreement between the OCO-2 and MODIS cloud screening methods is found to be ≃ 85 % over four 16-day orbit repeat cycles in both the winter (December) and spring (April-May) for OCO-2 nadir-land, glint-land and glint-water observations. No major, systematic, spatial or temporal dependencies were found, although slight differences in the seasonal data sets do exist and validation is more problematic with increasing solar zenith angle and when surfaces are covered in snow and ice and have complex topography. To further analyze the performance of the cloud screening algorithms, an initial comparison of OCO-2 observations was made to collocated measurements from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) aboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). These comparisons highlight the strength of the OCO-2 cloud screening algorithms in identifying high, thin clouds but suggest some difficulty in identifying some clouds near the surface, even when the optical thicknesses are greater than 1.

Retrieval of Ocean Surface Windspeed and Rainrate from the Hurricane Imaging Radiometer (HIRAD) Brightness Temperature Observations

NASA Technical Reports Server (NTRS)

Biswas, Sayak K.; Jones, Linwood; Roberts, Jason; Ruf, Christopher; Ulhorn, Eric; Miller, Timothy

2012-01-01

The Hurricane Imaging Radiometer (HIRAD) is a new airborne synthetic aperture passive microwave radiometer capable of wide swath imaging of the ocean surface wind speed under heavy precipitation e.g. in tropical cyclones. It uses interferometric signal processing to produce upwelling brightness temperature (Tb) images at its four operating frequencies 4, 5, 6 and 6.6 GHz [1,2]. HIRAD participated in NASA s Genesis and Rapid Intensification Processes (GRIP) mission during 2010 as its first science field campaign. It produced Tb images with 70 km swath width and 3 km resolution from a 20 km altitude. From this, ocean surface wind speed and column averaged atmospheric liquid water content can be retrieved across the swath. The column averaged liquid water then could be related to an average rain rate. The retrieval algorithm (and the HIRAD instrument itself) is a direct descendant of the nadir-only Stepped Frequency Microwave Radiometer that is used operationally by the NOAA Hurricane Research Division to monitor tropical cyclones [3,4]. However, due to HIRAD s slant viewing geometry (compared to nadir viewing SFMR) a major modification is required in the algorithm. Results based on the modified algorithm from the GRIP campaign will be presented in the paper.

Validation of YCAR algorithm over East Asia TCCON sites

NASA Astrophysics Data System (ADS)

Kim, W.; Kim, J.; Jung, Y.; Lee, H.; Goo, T. Y.; Cho, C. H.; Lee, S.

2016-12-01

In order to reduce the retrieval error of TANSO-FTS column averaged CO2 concentration (XCO2) induced by aerosol, we develop the Yonsei university CArbon Retrieval (YCAR) algorithm using aerosol information from TANSO-Cloud and Aerosol Imager (TANSO-CAI), providing simultaneous aerosol optical depth properties for the same geometry and optical path along with the FTS. Also we validate the retrieved results using ground-based TCCON measurement. Particularly this study first utilized the measurements at Anmyeondo, the only TCCON site located in South Korea, which can improve the quality of validation in East Asia. After the post screening process, YCAR algorithms have higher data availability by 33 - 85 % than other operational algorithms (NIES, ACOS, UoL). Although the YCAR algorithm has higher data availability, regression analysis with TCCON measurements are better or similar to other algorithms; Regression line of YCAR algorithm is close to linear identity function with RMSE of 2.05, bias of - 0.86 ppm. According to error analysis, retrieval error of YCAR algorithm is 1.394 - 1.478 ppm at East Asia. In addition, spatio-temporal sampling error of 0.324 - 0.358 ppm for each single sounding retrieval is also analyzed with Carbon Tracker - Asia data. These results of error analysis reveal the reliability and accuracy of latest version of our YCAR algorithm. Both XCO2 values retrieved using YCAR algorithm on TANSO-FTS and TCCON measurements show the consistent increasing trend about 2.3 - 2.6 ppm per year. Comparing to the increasing rate of global background CO2 amount measured in Mauna Loa, Hawaii (2 ppm per year), the increasing trend in East Asia shows about 30% higher trend due to the rapid increase of CO2 emission from the source region.

Land surface temperature measurements from EOS MODIS data

NASA Technical Reports Server (NTRS)

Wan, Zhengming

1994-01-01

A generalized split-window method for retrieving land-surface temperature (LST) from AVHRR and MODIS data has been developed. Accurate radiative transfer simulations show that the coefficients in the split-window algorithm for LST must depend on the viewing angle, if we are to achieve a LST accuracy of about 1 K for the whole scan swath range (+/-55.4 deg and +/-55 deg from nadir for AVHRR and MODIS, respectively) and for the ranges of surface temperature and atmospheric conditions over land, which are much wider than those over oceans. We obtain these coefficients from regression analysis of radiative transfer simulations, and we analyze sensitivity and error by using results from systematic radiative transfer simulations over wide ranges of surface temperatures and emissivities, and atmospheric water vapor abundance and temperatures. Simulations indicated that as atmospheric column water vapor increases and viewing angle is larger than 45 deg it is necessary to optimize the split-window method by separating the ranges of the atmospheric column water vapor and lower boundary temperature, and the surface temperature into tractable sub-ranges. The atmospheric lower boundary temperature and (vertical) column water vapor values retrieved from HIRS/2 or MODIS atmospheric sounding channels can be used to determine the range where the optimum coefficients of the split-window method are given. This new LST algorithm not only retrieves LST more accurately but also is less sensitive than viewing-angle independent LST algorithms to the uncertainty in the band emissivities of the land-surface in the split-window and to the instrument noise.

Improved OSIRIS NO2 retrieval algorithm: description and validation

NASA Astrophysics Data System (ADS)

Sioris, Christopher E.; Rieger, Landon A.; Lloyd, Nicholas D.; Bourassa, Adam E.; Roth, Chris Z.; Degenstein, Douglas A.; Camy-Peyret, Claude; Pfeilsticker, Klaus; Berthet, Gwenaël; Catoire, Valéry; Goutail, Florence; Pommereau, Jean-Pierre; McLinden, Chris A.

2017-03-01

A new retrieval algorithm for OSIRIS (Optical Spectrograph and Infrared Imager System) nitrogen dioxide (NO2) profiles is described and validated. The algorithm relies on spectral fitting to obtain slant column densities of NO2, followed by inversion using an algebraic reconstruction technique and the SaskTran spherical radiative transfer model (RTM) to obtain vertical profiles of local number density. The validation covers different latitudes (tropical to polar), years (2002-2012), all seasons (winter, spring, summer, and autumn), different concentrations of nitrogen dioxide (from denoxified polar vortex to polar summer), a range of solar zenith angles (68.6-90.5°), and altitudes between 10.5 and 39 km, thereby covering the full retrieval range of a typical OSIRIS NO2 profile. The use of a larger spectral fitting window than used in previous retrievals reduces retrieval uncertainties and the scatter in the retrieved profiles due to noisy radiances. Improvements are also demonstrated through the validation in terms of bias reduction at 15-17 km relative to the OSIRIS operational v3.0 algorithm. The diurnal variation of NO2 along the line of sight is included in a fully spherical multiple scattering RTM for the first time. Using this forward model with built-in photochemistry, the scatter of the differences relative to the correlative balloon NO2 profile data is reduced.

Algorithm theoretical baseline for formaldehyde retrievals from S5P TROPOMI and from the QA4ECV project

NASA Astrophysics Data System (ADS)

De Smedt, Isabelle; Theys, Nicolas; Yu, Huan; Danckaert, Thomas; Lerot, Christophe; Compernolle, Steven; Van Roozendael, Michel; Richter, Andreas; Hilboll, Andreas; Peters, Enno; Pedergnana, Mattia; Loyola, Diego; Beirle, Steffen; Wagner, Thomas; Eskes, Henk; van Geffen, Jos; Folkert Boersma, Klaas; Veefkind, Pepijn

2018-04-01

On board the Copernicus Sentinel-5 Precursor (S5P) platform, the TROPOspheric Monitoring Instrument (TROPOMI) is a double-channel, nadir-viewing grating spectrometer measuring solar back-scattered earthshine radiances in the ultraviolet, visible, near-infrared, and shortwave infrared with global daily coverage. In the ultraviolet range, its spectral resolution and radiometric performance are equivalent to those of its predecessor OMI, but its horizontal resolution at true nadir is improved by an order of magnitude. This paper introduces the formaldehyde (HCHO) tropospheric vertical column retrieval algorithm implemented in the S5P operational processor and comprehensively describes its various retrieval steps. Furthermore, algorithmic improvements developed in the framework of the EU FP7-project QA4ECV are described for future updates of the processor. Detailed error estimates are discussed in the light of Copernicus user requirements and needs for validation are highlighted. Finally, verification results based on the application of the algorithm to OMI measurements are presented, demonstrating the performances expected for TROPOMI.

OMI Total and Tropospheric Column Nitrogen Dioxide: Version 2 Status

NASA Technical Reports Server (NTRS)

Gleason, James

2007-01-01

The at-launch version of the OM1 NO2 total and tropospheric NO2 algorithm made a number of assumptions about instrument performance. Our knowledge of tropospheric NO2 has increased in the 3 years since the inital version was delivered. The results of the post-launch validation campaigns and improved atmospheric modelling has lead to changes in the NO2 retrieval algorithm. The algorithm changes and the impacts on the data products will be presented.

Ground-based FTIR retrievals of SF6 on Reunion Island

NASA Astrophysics Data System (ADS)

Zhou, Minqiang; Langerock, Bavo; Vigouroux, Corinne; Wang, Pucai; Hermans, Christian; Stiller, Gabriele; Walker, Kaley A.; Dutton, Geoff; Mahieu, Emmanuel; De Mazière, Martine

2018-02-01

SF6 total columns were successfully retrieved from FTIR (Fourier transform infrared) measurements (Saint Denis and Maïdo) on Reunion Island (21° S, 55° E) between 2004 and 2016 using the SFIT4 algorithm: the retrieval strategy and the error budget were presented. The FTIR SF6 retrieval has independent information in only one individual layer, covering the whole of the troposphere and the lower stratosphere. The trend in SF6 was analysed based on the FTIR-retrieved dry-air column-averaged mole fractions (XSF6) on Reunion Island, the in situ measurements at America Samoa (SMO) and the collocated satellite measurements (Michelson Interferometer for Passive Atmospheric Sounding, MIPAS, and Atmospheric Chemistry Experiment Fourier Transform Spectrometer, ACE-FTS) in the southern tropics. The SF6 annual growth rate from FTIR retrievals is 0.265 ± 0.013 pptv year-1 for 2004-2016, which is slightly weaker than that from the SMO in situ measurements (0.285 ± 0.002 pptv year-1) for the same time period. The SF6 trend in the troposphere from MIPAS and ACE-FTS observations is also close to the ones from the FTIR retrievals and the SMO in situ measurements.

Preliminary Martian Atmospheric Water Vapour Column Abundances with Mars Climate Sounder

NASA Astrophysics Data System (ADS)

Lolachi, Ramin; Irwin, P. G. J.; Teanby, N.; Calcutt, S.; Howett, C. J. A.; Bowles, N. E.; Taylor, F. W.; Schofield, J. T.; Kleinboehl, A.; McCleese, D. J.

2007-12-01

Mars Climate Sounder (MCS) is an infra-red radiometer on board NASA's Mars Reconnaissance Orbiter (MRO) launched in August 2005 and now orbiting Mars in a near circular polar orbit. MCS has nine spectral channels in the range 0.3-50 µm. Goals of MCS include global characterization of atmospheric temperature, dust and water profiles observing temporal and spatial variation. Using Oxford University's multivariate retrieval algorithm, NEMESIS, we present preliminary determinations of the water vapour column abundance in the Martian atmosphere during the period September-October 2006 (Ls range 111-129°, i.e. northern hemisphere summer). A combination of spectral channels inside and outside the water vapour rotation band (at 50 µm) are used to retrieve the column abundances mainly using nadir observations (as aerosol opacity is less important relative to water vapour opacity in nadir viewing geometry). We then compare these column abundances to earlier results from the Viking Orbiter Mars Atmospheric Water Detectors (MAWD) and the Thermal Emission Spectrometer (TES) on Mars Global Surveyor.

Tropospheric nitrogen dioxide column retrieval based on ground-based zenith-sky DOAS observations

NASA Astrophysics Data System (ADS)

Tack, F. M.; Hendrick, F.; Pinardi, G.; Fayt, C.; Van Roozendael, M.

2013-12-01

A retrieval approach has been developed to derive tropospheric NO2 vertical column amounts from ground-based zenith-sky measurements of scattered sunlight. Zenith radiance spectra are observed in the visible range by the BIRA-IASB Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) instrument and analyzed by the DOAS technique, based on a least-squares spectral fitting. In recent years, this technique has shown to be a well-suited remote sensing tool for monitoring atmospheric trace gases. The retrieval algorithm is developed and validated based on a two month dataset acquired from June to July 2009 in the framework of the Cabauw (51.97° N, 4.93° E) Intercomparison campaign for Nitrogen Dioxide measuring Instruments (CINDI). Once fully operational, the retrieval approach can be applied to observations from stations of the Network for the Detection of Atmospheric Composition Change (NDACC). The obtained tropospheric vertical column amounts are compared with the multi-axis retrieval from the BIRA-IASB MAX-DOAS instrument and the retrieval from a zenith-viewing only SAOZ instrument (Système d'Analyse par Observations Zénithales), owned by Laboratoire Atmosphères, Milieux, Observations Spatiales (LATMOS). First results show a good agreement for the whole time series with the multi-axis retrieval (R = 0.82; y = 0.88x + 0.30) as well as with the SAOZ retrieval (R = 0.85; y = 0.76x + 0.28 ). Main error sources arise from the uncertainties in the determination of tropospheric and stratospheric air mass factors, the stratospheric NO2 abundances and the residual amount in the reference spectrum. However zenith-sky measurements have been commonly used over the last decades for stratospheric monitoring, this study also illustrates the suitability for retrieval of tropospheric column amounts. As there are long time series of zenith-sky acquisitions available, the developed approach offers new perspectives with regard to the use of observations from the NDACC stations.

Facing the phase problem in Coherent Diffractive Imaging via Memetic Algorithms.

PubMed

Colombo, Alessandro; Galli, Davide Emilio; De Caro, Liberato; Scattarella, Francesco; Carlino, Elvio

2017-02-09

Coherent Diffractive Imaging is a lensless technique that allows imaging of matter at a spatial resolution not limited by lens aberrations. This technique exploits the measured diffraction pattern of a coherent beam scattered by periodic and non-periodic objects to retrieve spatial information. The diffracted intensity, for weak-scattering objects, is proportional to the modulus of the Fourier Transform of the object scattering function. Any phase information, needed to retrieve its scattering function, has to be retrieved by means of suitable algorithms. Here we present a new approach, based on a memetic algorithm, i.e. a hybrid genetic algorithm, to face the phase problem, which exploits the synergy of deterministic and stochastic optimization methods. The new approach has been tested on simulated data and applied to the phasing of transmission electron microscopy coherent electron diffraction data of a SrTiO 3 sample. We have been able to quantitatively retrieve the projected atomic potential, and also image the oxygen columns, which are not directly visible in the relevant high-resolution transmission electron microscopy images. Our approach proves to be a new powerful tool for the study of matter at atomic resolution and opens new perspectives in those applications in which effective phase retrieval is necessary.

Effects of daily, high spatial resolution a priori profiles of satellite-derived NOx emissions

NASA Astrophysics Data System (ADS)

Laughner, J.; Zare, A.; Cohen, R. C.

2016-12-01

The current generation of space-borne NO2 column observations provides a powerful method of constraining NOx emissions due to the spatial resolution and global coverage afforded by the Ozone Monitoring Instrument (OMI). The greater resolution available in next generation instruments such as TROPOMI and the capabilities of geosynchronous platforms TEMPO, Sentinel-4, and GEMS will provide even greater capabilities in this regard, but we must apply lessons learned from the current generation of retrieval algorithms to make the best use of these instruments. Here, we focus on the effect of the resolution of the a priori NO2 profiles used in the retrieval algorithms. We show that for an OMI retrieval, using daily high-resolution a priori profiles results in changes in the retrieved VCDs up to 40% when compared to a retrieval using monthly average profiles at the same resolution. Further, comparing a retrieval with daily high spatial resolution a priori profiles to a more standard one, we show that emissions derived increase by 100% when using the optimized retrieval.

Impact of spatial resolution on cirrus infrared satellite retrievals in the presence of cloud heterogeneity

NASA Astrophysics Data System (ADS)

Fauchez, T.; Platnick, S. E.; Meyer, K.; Zhang, Z.; Cornet, C.; Szczap, F.; Dubuisson, P.

2015-12-01

Cirrus clouds are an important part of the Earth radiation budget but an accurate assessment of their role remains highly uncertain. Cirrus optical properties such as Cloud Optical Thickness (COT) and ice crystal effective particle size are often retrieved with a combination of Visible/Near InfraRed (VNIR) and ShortWave-InfraRed (SWIR) reflectance channels. Alternatively, Thermal InfraRed (TIR) techniques, such as the Split Window Technique (SWT), have demonstrated better accuracy for thin cirrus effective radius retrievals with small effective radii. However, current global operational algorithms for both retrieval methods assume that cloudy pixels are horizontally homogeneous (Plane Parallel Approximation (PPA)) and independent (Independent Pixel Approximation (IPA)). The impact of these approximations on ice cloud retrievals needs to be understood and, as far as possible, corrected. Horizontal heterogeneity effects in the TIR spectrum are mainly dominated by the PPA bias that primarily depends on the COT subpixel heterogeneity; for solar reflectance channels, in addition to the PPA bias, the IPA can lead to significant retrieval errors due to a significant photon horizontal transport between cloudy columns, as well as brightening and shadowing effects that are more difficult to quantify. Furthermore TIR retrievals techniques have demonstrated better retrieval accuracy for thin cirrus having small effective radii over solar reflectance techniques. The TIR range is thus particularly relevant in order to characterize, as accurately as possible, thin cirrus clouds. Heterogeneity effects in the TIR are evaluated as a function of spatial resolution in order to estimate the optimal spatial resolution for TIR retrieval applications. These investigations are performed using a cirrus 3D cloud generator (3DCloud), a 3D radiative transfer code (3DMCPOL), and two retrieval algorithms, namely the operational MODIS retrieval algorithm (MOD06) and a research-level SWT algorithm.

Simultaneous polarimeter retrievals of microphysical aerosol and ocean color parameters from the "MAPP" algorithm with comparison to high-spectral-resolution lidar aerosol and ocean products.

PubMed

Stamnes, S; Hostetler, C; Ferrare, R; Burton, S; Liu, X; Hair, J; Hu, Y; Wasilewski, A; Martin, W; van Diedenhoven, B; Chowdhary, J; Cetinić, I; Berg, L K; Stamnes, K; Cairns, B

2018-04-01

We present an optimal-estimation-based retrieval framework, the microphysical aerosol properties from polarimetry (MAPP) algorithm, designed for simultaneous retrieval of aerosol microphysical properties and ocean color bio-optical parameters using multi-angular total and polarized radiances. Polarimetric measurements from the airborne NASA Research Scanning Polarimeter (RSP) were inverted by MAPP to produce atmosphere and ocean products. The RSP MAPP results are compared with co-incident lidar measurements made by the NASA High-Spectral-Resolution Lidar HSRL-1 and HSRL-2 instruments. Comparisons are made of the aerosol optical depth (AOD) at 355 and 532 nm, lidar column-averaged measurements of the aerosol lidar ratio and Ångstrøm exponent, and lidar ocean measurements of the particulate hemispherical backscatter coefficient and the diffuse attenuation coefficient. The measurements were collected during the 2012 Two-Column Aerosol Project (TCAP) campaign and the 2014 Ship-Aircraft Bio-Optical Research (SABOR) campaign. For the SABOR campaign, 73% RSP MAPP retrievals fall within ±0.04 AOD at 532 nm as measured by HSRL-1, with an R value of 0.933 and root-mean-square deviation of 0.0372. For the TCAP campaign, 53% of RSP MAPP retrievals are within 0.04 AOD as measured by HSRL-2, with an R value of 0.927 and root-mean-square deviation of 0.0673. Comparisons with HSRL-2 AOD at 355 nm during TCAP result in an R value of 0.959 and a root-mean-square deviation of 0.0694. The RSP retrievals using the MAPP optimal estimation framework represent a key milestone on the path to a combined lidar + polarimeter retrieval using both HSRL and RSP measurements.

Simultaneous polarimeter retrievals of microphysical aerosol and ocean color parameters from the “MAPP” algorithm with comparison to high-spectral-resolution lidar aerosol and ocean products

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stamnes, S.; Hostetler, C.; Ferrare, R.

We present an optimal estimation based retrieval framework, the Microphysical Aerosol Properties from Polarimetry (MAPP) algorithm, designed for simultaneous retrieval of aerosol microphysical properties and ocean color bio-optical parameters using multi-angular polarized radiances. Polarimetric measurements from the airborne NASA Research Scanning Polarimeter (RSP) were inverted by MAPP to produce atmosphere and ocean products. The RSP MAPP results are compared with co-incident lidar measurements made by the NASA High Spectral Resolution Lidar HSRL-1 and HSRL-2 instruments. Comparisons are made of the aerosol optical depth (AOD) at 355, 532, and 1064 nm, lidar column-averaged measurements of the aerosol lidar ratio and Ã…ngstrømmore » exponent, and lidar ocean measurements of the particulate hemispherical backscatter coefficient and the diffuse attenuation coefficient. The measurements were collected during the 2012 Two-Column Aerosol Project (TCAP) campaign and the 2014 Ship-Aircraft Bio- Optical Research (SABOR) campaign. For the SABOR campaign, 71% RSP MAPP retrievals fall within 0.04 AOD at 532 nm as measured by HSRL-1, with an R value of 0.925 and root-mean-square deviation of 0.04. For the TCAP campaign, 55% of RSP MAPP retrievals are within 0.04 AOD as measured by HSRL-2, with an R value of 0.925 and root-mean-square deviation of 0.07. Comparisons with HSRL-2 AOD at 355 nm during TCAP result in an R value of 0.96 and a root-mean-square deviation of also 0.07. The RSP retrievals using the MAPP optimal estimation framework represent a key milestone on the path to a combined lidar+polarimeter retrieval using both HSRL and RSP measurements.« less

Comparison of ozone retrievals from the Pandora spectrometer system and Dobson spectrophotometer in Boulder, Colorado

NASA Astrophysics Data System (ADS)

Herman, J.; Evans, R.; Cede, A.; Abuhassan, N.; Petropavlovskikh, I.; McConville, G.

2015-03-01

A comparison of retrieved total column ozone amounts TCO between the Pandora #34 spectrometer system and the Dobson #061 spectrophotometer from direct-sun observations was performed on the roof of the Boulder, Colorado NOAA building. This paper, part of an ongoing study, covers a one-year period starting on 17 December 2013. Both the standard Dobson and Pandora total column ozone TCO retrievals required a correction TCOcorr = TCO (1+C(T)) using the effective climatology derived ozone temperature T to remove a seasonal difference caused by using a fixed temperature in each retrieval algorithm. The respective corrections C(T) are CPandora = 0.00333(T-225) and CDobson = -0.0013 (T-226.7) per K. After the applied corrections removed the seasonal retrieval dependence on ozone temperature, TCO agreement between the instruments was within 1% for clear-sky conditions. For clear-sky observations, both co-located instruments tracked the day-to-day variation in total column ozone amounts with a correlation of r2 = 0.97 and an average offset of 1.1 ± 5.8 DU. In addition, the Pandora data showed 0.3% annual average agreement with satellite overpass data from AURA/OMI (Ozone Monitoring Instrument) and 1% annual average offset with Suomi-NPP/OMPS (Suomi National Polar-orbiting Partnership, the nadir viewing portion of the Ozone Mapper Profiler Suite).

Detecting Thin Cirrus in Multiangle Imaging Spectroradiometer Aerosol Retrievals

NASA Technical Reports Server (NTRS)

Pierce, Jeffrey R.; Kahn, Ralph A.; Davis, Matt R.; Comstock, Jennifer M.

2010-01-01

Thin cirrus clouds (optical depth (OD) < 03) are often undetected by standard cloud masking in satellite aerosol retrieval algorithms. However, the Mu]tiangle Imaging Spectroradiometer (MISR) aerosol retrieval has the potential to discriminate between the scattering phase functions of cirrus and aerosols, thus separating these components. Theoretical tests show that MISR is sensitive to cirrus OD within Max{0.05 1 20%l, similar to MISR's sensitivity to aerosol OD, and MISR can distinguish between small and large crystals, even at low latitudes, where the range of scattering angles observed by MISR is smallest. Including just two cirrus components in the aerosol retrieval algorithm would capture typical MISR sensitivity to the natural range of cinus properties; in situations where cirrus is present but the retrieval comparison space lacks these components, the retrieval tends to underestimate OD. Generally, MISR can also distinguish between cirrus and common aerosol types when the proper cirrus and aerosol optical models are included in the retrieval comparison space and total column OD is >-0.2. However, in some cases, especially at low latitudes, cirrus can be mistaken for some combinations of dust and large nonabsorbing spherical aerosols, raising a caution about retrievals in dusty marine regions when cirrus is present. Comparisons of MISR with lidar and Aerosol Robotic Network show good agreement in a majority of the cases, but situations where cirrus clouds have optical depths >0.15 and are horizontally inhomogeneous on spatial scales shorter than 50 km pose difficulties for cirrus retrieval using the MISR standard aerosol algorithm..

DNA Microarray Data Analysis: A Novel Biclustering Algorithm Approach

NASA Astrophysics Data System (ADS)

Tchagang, Alain B.; Tewfik, Ahmed H.

2006-12-01

Biclustering algorithms refer to a distinct class of clustering algorithms that perform simultaneous row-column clustering. Biclustering problems arise in DNA microarray data analysis, collaborative filtering, market research, information retrieval, text mining, electoral trends, exchange analysis, and so forth. When dealing with DNA microarray experimental data for example, the goal of biclustering algorithms is to find submatrices, that is, subgroups of genes and subgroups of conditions, where the genes exhibit highly correlated activities for every condition. In this study, we develop novel biclustering algorithms using basic linear algebra and arithmetic tools. The proposed biclustering algorithms can be used to search for all biclusters with constant values, biclusters with constant values on rows, biclusters with constant values on columns, and biclusters with coherent values from a set of data in a timely manner and without solving any optimization problem. We also show how one of the proposed biclustering algorithms can be adapted to identify biclusters with coherent evolution. The algorithms developed in this study discover all valid biclusters of each type, while almost all previous biclustering approaches will miss some.

The performance of Yonsei CArbon Retrieval (YCAR) algorithm with improved aerosol information using GOSAT measurements over East Asia

NASA Astrophysics Data System (ADS)

Jung, Y.; Kim, J.; Kim, W.; Boesch, H.; Yoshida, Y.; Cho, C.; Lee, H.; Goo, T. Y.

2016-12-01

The Greenhouse Gases Observing SATellite (GOSAT) is the first satellite dedicated to measure atmospheric CO2 concentrations from space that can able to improve our knowledge about carbon cycle. Several studies have performed to develop the CO2 retrieval algorithms using GOSAT measurements, but limitations in spatial coverage and uncertainties due to aerosols and thin cirrus clouds are still remained as a problem for monitoring CO2 concentration globally. In this study, we develop the Yonsei CArbon Retrieval (YCAR) algorithm based on optimal estimation method to retrieve the column-averaged dry-air mole fraction of carbon dioxide (XCO2) with optimized a priori CO2 profiles and aerosol models over East Asia. In previous studies, the aerosol optical properties (AOP) and the aerosol top height used to cause significant errors in retrieved XCO2 up to 2.5 ppm. Since this bias comes from a rough assumption of aerosol information in the forward model used in CO2 retrieval process, the YCAR algorithm improves the process to take into account AOPs as well as aerosol vertical distribution; total AOD and the fine mode fraction (FMF) are obtained from the ground-based measurements closely located, and other parameters are obtained from a priori information. Comparing to ground-based XCO2 measurements, the YCAR XCO2 product has a bias of 0.59±0.48 ppm and 2.16±0.87 ppm at Saga and Tsukuba sites, respectively, showing lower biases and higher correlations rather than the GOSAT standard products. These results reveal that considering better aerosol information can improve the accuracy of CO2 retrieval algorithm and provide more useful XCO2 information with reduced uncertainties.

An operational retrieval algorithm for determining aerosol optical properties in the ultraviolet

NASA Astrophysics Data System (ADS)

Taylor, Thomas E.; L'Ecuyer, Tristan S.; Slusser, James R.; Stephens, Graeme L.; Goering, Christian D.

2008-02-01

This paper describes a number of practical considerations concerning the optimization and operational implementation of an algorithm used to characterize the optical properties of aerosols across part of the ultraviolet (UV) spectrum. The algorithm estimates values of aerosol optical depth (AOD) and aerosol single scattering albedo (SSA) at seven wavelengths in the UV, as well as total column ozone (TOC) and wavelength-independent asymmetry factor (g) using direct and diffuse irradiances measured with a UV multifilter rotating shadowband radiometer (UV-MFRSR). A novel method for cloud screening the irradiance data set is introduced, as well as several improvements and optimizations to the retrieval scheme which yield a more realistic physical model for the inversion and increase the efficiency of the algorithm. Introduction of a wavelength-dependent retrieval error budget generated from rigorous forward model analysis as well as broadened covariances on the a priori values of AOD, SSA and g and tightened covariances of TOC allows sufficient retrieval sensitivity and resolution to obtain unique solutions of aerosol optical properties as demonstrated by synthetic retrievals. Analysis of a cloud screened data set (May 2003) from Panther Junction, Texas, demonstrates that the algorithm produces realistic values of the optical properties that compare favorably with pseudo-independent methods for AOD, TOC and calculated Ångstrom exponents. Retrieval errors of all parameters (except TOC) are shown to be negatively correlated to AOD, while the Shannon information content is positively correlated, indicating that retrieval skill improves with increasing atmospheric turbidity. When implemented operationally on more than thirty instruments in the Ultraviolet Monitoring and Research Program's (UVMRP) network, this retrieval algorithm will provide a comprehensive and internally consistent climatology of ground-based aerosol properties in the UV spectral range that can be used for both validation of satellite measurements as well as regional aerosol and ultraviolet transmission studies.

Consistent satellite XCO 2 retrievals from SCIAMACHY and GOSAT using the BESD algorithm

DOE PAGES

Heymann, J.; Reuter, M.; Hilker, M.; ...

2015-02-13

Consistent and accurate long-term data sets of global atmospheric concentrations of carbon dioxide (CO 2) are required for carbon cycle and climate related research. However, global data sets based on satellite observations may suffer from inconsistencies originating from the use of products derived from different satellites as needed to cover a long enough time period. One reason for inconsistencies can be the use of different retrieval algorithms. We address this potential issue by applying the same algorithm, the Bremen Optimal Estimation DOAS (BESD) algorithm, to different satellite instruments, SCIAMACHY on-board ENVISAT (March 2002–April 2012) and TANSO-FTS on-board GOSAT (launched inmore » January 2009), to retrieve XCO 2, the column-averaged dry-air mole fraction of CO 2. BESD has been initially developed for SCIAMACHY XCO 2 retrievals. Here, we present the first detailed assessment of the new GOSAT BESD XCO 2 product. GOSAT BESD XCO 2 is a product generated and delivered to the MACC project for assimilation into ECMWF's Integrated Forecasting System (IFS). We describe the modifications of the BESD algorithm needed in order to retrieve XCO 2 from GOSAT and present detailed comparisons with ground-based observations of XCO 2 from the Total Carbon Column Observing Network (TCCON). We discuss detailed comparison results between all three XCO 2 data sets (SCIAMACHY, GOSAT and TCCON). The comparison results demonstrate the good consistency between the SCIAMACHY and the GOSAT XCO 2. For example, we found a mean difference for daily averages of −0.60 ± 1.56 ppm (mean difference ± standard deviation) for GOSAT-SCIAMACHY (linear correlation coefficient r = 0.82), −0.34 ± 1.37 ppm ( r = 0.86) for GOSAT-TCCON and 0.10 ± 1.79 ppm ( r = 0.75) for SCIAMACHY-TCCON. The remaining differences between GOSAT and SCIAMACHY are likely due to non-perfect collocation (±2 h, 10° × 10° around TCCON sites), i.e., the observed air masses are not exactly identical, but likely also due to a still non-perfect BESD retrieval algorithm, which will be continuously improved in the future. Our overarching goal is to generate a satellite-derived XCO 2 data set appropriate for climate and carbon cycle research covering the longest possible time period. We therefore also plan to extend the existing SCIAMACHY and GOSAT data set discussed here by using also data from other missions (e.g., OCO-2, GOSAT-2, CarbonSat) in the future.« less

NO2 Total and Tropospheric Vertical Column Densities from OMI on EOS Aura: Update

NASA Technical Reports Server (NTRS)

Gleason, J.F.; Bucsela, E.J.; Celarier, E.A.; Veefkind, J.P.; Kim, S.W.; Frost, G.F.

2009-01-01

The Ozone Monitoring Instrument (OMI), which is on the EOS AURA satellite, retrieves vertical column densities (VCDs) of NO2, along with those of several other trace gases. The relatively high spatial resolution and daily global coverage of the instrument make it particularly well-suited to monitoring tropospheric pollution at scales on the order of 20 km. The OMI NO2 algorithm distinguishes polluted regions from background stratospheric NO2 using a separation algorithm that relies on the smoothly varying stratospheric NO2 and estimations of both stratospheric and tropospheric air mass factors (AMFs). Version 1 of OMI NO2 data has been released for public use. An overview of OMI NO2 data, some recent results and a description of the improvements for version 2 of the algorithm will be presented.

SO2 plume height retrieval from direct fitting of GOME-2 backscattered radiance measurements

NASA Astrophysics Data System (ADS)

van Gent, J.; Spurr, R.; Theys, N.; Lerot, C.; Brenot, H.; Van Roozendael, M.

2012-04-01

The use of satellite measurements for SO2 monitoring has become an important aspect in the support of aviation control. Satellite measurements are sometimes the only information available on SO2 concentrations from volcanic eruption events. The detection of SO2 can furthermore serve as a proxy for the presence of volcanic ash that poses a possible hazard to air traffic. In that respect, knowledge of both the total vertical column amount and the effective altitude of the volcanic SO2 plume is valuable information to air traffic control. The Belgian Institute for Space Aeronomy (BIRA-IASB) hosts the ESA-funded Support to Aviation Control Service (SACS). This system provides Volcanic Ash Advisory Centers (VAACs) worldwide with near real-time SO2 and volcanic ash data, derived from measurements from space. We present results from our algorithm for the simultaneous retrieval of total vertical columns of O3 and SO2 and effective SO2 plume height from GOME-2 backscattered radiance measurements. The algorithm is an extension to the GODFIT direct fitting algorithm, initially developed at BIRA-IASB for the derivation of improved total ozone columns from satellite data. The algorithm uses parameterized vertical SO2 profiles which allow for the derivation of the peak height of the SO2 plume, along with the trace gas total column amounts. To illustrate the applicability of the method, we present three case studies on recent volcanic eruptions: Merapi (2010), Grímsvotn (2011), and Nabro (2011). The derived SO2 plume altitude values are validated with the trajectory model FLEXPART and with aerosol altitude estimations from the CALIOP instrument on-board the NASA A-train CALIPSO platform. We find that the effective plume height can be obtained with a precision as fine as 1 km for moderate and strong volcanic events. Since this is valuable information for air traffic, we aim at incorporating the plume height information in the SACS system.

Accounting for the effects of surface BRDF on satellite cloud and trace-gas retrievals: a new approach based on geometry-dependent Lambertian equivalent reflectivity applied to OMI algorithms

NASA Astrophysics Data System (ADS)

Vasilkov, Alexander; Qin, Wenhan; Krotkov, Nickolay; Lamsal, Lok; Spurr, Robert; Haffner, David; Joiner, Joanna; Yang, Eun-Su; Marchenko, Sergey

2017-01-01

Most satellite nadir ultraviolet and visible cloud, aerosol, and trace-gas algorithms make use of climatological surface reflectivity databases. For example, cloud and NO2 retrievals for the Ozone Monitoring Instrument (OMI) use monthly gridded surface reflectivity climatologies that do not depend upon the observation geometry. In reality, reflection of incoming direct and diffuse solar light from land or ocean surfaces is sensitive to the sun-sensor geometry. This dependence is described by the bidirectional reflectance distribution function (BRDF). To account for the BRDF, we propose to use a new concept of geometry-dependent Lambertian equivalent reflectivity (LER). Implementation within the existing OMI cloud and NO2 retrieval infrastructure requires changes only to the input surface reflectivity database. The geometry-dependent LER is calculated using a vector radiative transfer model with high spatial resolution BRDF information from the Moderate Resolution Imaging Spectroradiometer (MODIS) over land and the Cox-Munk slope distribution over ocean with a contribution from water-leaving radiance. We compare the geometry-dependent and climatological LERs for two wavelengths, 354 and 466 nm, that are used in OMI cloud algorithms to derive cloud fractions. A detailed comparison of the cloud fractions and pressures derived with climatological and geometry-dependent LERs is carried out. Geometry-dependent LER and corresponding retrieved cloud products are then used as inputs to our OMI NO2 algorithm. We find that replacing the climatological OMI-based LERs with geometry-dependent LERs can increase NO2 vertical columns by up to 50 % in highly polluted areas; the differences include both BRDF effects and biases between the MODIS and OMI-based surface reflectance data sets. Only minor changes to NO2 columns (within 5 %) are found over unpolluted and overcast areas.

Accounting for the Effects of Surface BRDF on Satellite Cloud and Trace-Gas Retrievals: A New Approach Based on Geometry-Dependent Lambertian-Equivalent Reflectivity Applied to OMI Algorithms

NASA Technical Reports Server (NTRS)

Vasilkov, Alexander; Qin, Wenhan; Krotkov, Nickolay; Lamsal, Lok; Spurr, Robert; Haffner, David; Joiner, Joanna; Yang, Eun-Su; Marchenko, Sergey

2017-01-01

Most satellite nadir ultraviolet and visible cloud, aerosol, and trace-gas algorithms make use of climatological surface reflectivity databases. For example, cloud and NO2 retrievals for the Ozone Monitoring Instrument (OMI) use monthly gridded surface reflectivity climatologies that do not depend upon the observation geometry. In reality, reflection of incoming direct and diffuse solar light from land or ocean surfaces is sensitive to the sun-sensor geometry. This dependence is described by the bidirectional reflectance distribution function (BRDF). To account for the BRDF, we propose to use a new concept of geometry-dependent Lambertian equivalent reflectivity (LER). Implementation within the existing OMI cloud and NO2 retrieval infrastructure requires changes only to the input surface reflectivity database. The geometry-dependent LER is calculated using a vector radiative transfer model with high spatial resolution BRDF information from the Moderate Resolution Imaging Spectroradiometer (MODIS) over land and the Cox-Munk slope distribution over ocean with a contribution from water-leaving radiance. We compare the geometry-dependent and climatological LERs for two wavelengths, 354 and 466 nm, that are used in OMI cloud algorithms to derive cloud fractions. A detailed comparison of the cloud fractions and pressures derived with climatological and geometry-dependent LERs is carried out. Geometry-dependent LER and corresponding retrieved cloud products are then used as inputs to our OMI NO2 algorithm. We find that replacing the climatological OMI-based LERs with geometry-dependent LERs can increase NO2 vertical columns by up to 50% in highly polluted areas; the differences include both BRDF effects and biases between the MODIS and OMI-based surface reflectance data sets. Only minor changes to NO2 columns (within 5 %) are found over unpolluted and overcast areas.

The Greenhouse Gas Climate Change Initiative (GHG-CCI): comparative validation of GHG-CCI SCIAMACHY/ENVISAT and TANSO-FTS/GOSAT CO2 and CH4 retrieval algorithm products with measurements from the TCCON

NASA Astrophysics Data System (ADS)

Dils, B.; Buchwitz, M.; Reuter, M.; Schneising, O.; Boesch, H.; Parker, R.; Guerlet, S.; Aben, I.; Blumenstock, T.; Burrows, J. P.; Butz, A.; Deutscher, N. M.; Frankenberg, C.; Hase, F.; Hasekamp, O. P.; Heymann, J.; De Mazière, M.; Notholt, J.; Sussmann, R.; Warneke, T.; Griffith, D.; Sherlock, V.; Wunch, D.

2014-06-01

Column-averaged dry-air mole fractions of carbon dioxide and methane have been retrieved from spectra acquired by the TANSO-FTS (Thermal And Near-infrared Sensor for carbon Observations-Fourier Transform Spectrometer) and SCIAMACHY (Scanning Imaging Absorption Spectrometer for Atmospheric Cartography) instruments on board GOSAT (Greenhouse gases Observing SATellite) and ENVISAT (ENVIronmental SATellite), respectively, using a range of European retrieval algorithms. These retrievals have been compared with data from ground-based high-resolution Fourier transform spectrometers (FTSs) from the Total Carbon Column Observing Network (TCCON). The participating algorithms are the weighting function modified differential optical absorption spectroscopy (DOAS) algorithm (WFMD, University of Bremen), the Bremen optimal estimation DOAS algorithm (BESD, University of Bremen), the iterative maximum a posteriori DOAS (IMAP, Jet Propulsion Laboratory (JPL) and Netherlands Institute for Space Research algorithm (SRON)), the proxy and full-physics versions of SRON's RemoTeC algorithm (SRPR and SRFP, respectively) and the proxy and full-physics versions of the University of Leicester's adaptation of the OCO (Orbiting Carbon Observatory) algorithm (OCPR and OCFP, respectively). The goal of this algorithm inter-comparison was to identify strengths and weaknesses of the various so-called round- robin data sets generated with the various algorithms so as to determine which of the competing algorithms would proceed to the next round of the European Space Agency's (ESA) Greenhouse Gas Climate Change Initiative (GHG-CCI) project, which is the generation of the so-called Climate Research Data Package (CRDP), which is the first version of the Essential Climate Variable (ECV) "greenhouse gases" (GHGs). For XCO2, all algorithms reach the precision requirements for inverse modelling (< 8 ppm), with only WFMD having a lower precision (4.7 ppm) than the other algorithm products (2.4-2.5 ppm). When looking at the seasonal relative accuracy (SRA, variability of the bias in space and time), none of the algorithms have reached the demanding < 0.5 ppm threshold. For XCH4, the precision for both SCIAMACHY products (50.2 ppb for IMAP and 76.4 ppb for WFMD) fails to meet the < 34 ppb threshold for inverse modelling, but note that this work focusses on the period after the 2005 SCIAMACHY detector degradation. The GOSAT XCH4 precision ranges between 18.1 and 14.0 ppb. Looking at the SRA, all GOSAT algorithm products reach the < 10 ppm threshold (values ranging between 5.4 and 6.2 ppb). For SCIAMACHY, IMAP and WFMD have a SRA of 17.2 and 10.5 ppb, respectively.

Status of the NPP and J1 NOAA Unique Combined Atmospheric Processing System (NUCAPS): recent algorithm enhancements geared toward validation and near real time users applications.

NASA Astrophysics Data System (ADS)

Gambacorta, A.; Nalli, N. R.; Tan, C.; Iturbide-Sanchez, F.; Wilson, M.; Zhang, K.; Xiong, X.; Barnet, C. D.; Sun, B.; Zhou, L.; Wheeler, A.; Reale, A.; Goldberg, M.

2017-12-01

The NOAA Unique Combined Atmospheric Processing System (NUCAPS) is the NOAA operational algorithm to retrieve thermodynamic and composition variables from hyper spectral thermal sounders such as CrIS, IASI and AIRS. The combined use of microwave sounders, such as ATMS, AMSU and MHS, enables full atmospheric sounding of the atmospheric column under all-sky conditions. NUCAPS retrieval products are accessible in near real time (about 1.5 hour delay) through the NOAA Comprehensive Large Array-data Stewardship System (CLASS). Since February 2015, NUCAPS retrievals have been also accessible via Direct Broadcast, with unprecedented low latency of less than 0.5 hours. NUCAPS builds on a long-term, multi-agency investment on algorithm research and development. The uniqueness of this algorithm consists in a number of features that are key in providing highly accurate and stable atmospheric retrievals, suitable for real time weather and air quality applications. Firstly, maximizing the use of the information content present in hyper spectral thermal measurements forms the foundation of the NUCAPS retrieval algorithm. Secondly, NUCAPS is a modular, name-list driven design. It can process multiple hyper spectral infrared sounders (on Aqua, NPP, MetOp and JPSS series) by mean of the same exact retrieval software executable and underlying spectroscopy. Finally, a cloud-clearing algorithm and a synergetic use of microwave radiance measurements enable full vertical sounding of the atmosphere, under all-sky regimes. As we transition toward improved hyper spectral missions, assessing retrieval skill and consistency across multiple platforms becomes a priority for real time users applications. Focus of this presentation is a general introduction on the recent improvements in the delivery of the NUCAPS full spectral resolution upgrade and an overview of the lessons learned from the 2017 Hazardous Weather Test bed Spring Experiment. Test cases will be shown on the use of NPP and MetOp NUCAPS under pre-convective, capping inversion and dry layer intrusion events.

Error analysis of the greenhouse-gases monitor instrument short wave infrared XCO2 retrieval algorithm

NASA Astrophysics Data System (ADS)

Wu, Hao; Wang, Xianhua; Ye, Hanhan; Jiang, Yun; Duan, Fenghua

2018-01-01

We developed an algorithm (named GMI_XCO2) to retrieve the global column-averaged dry air mole fraction of atmospheric carbon dioxide (XCO2) for greenhouse-gases monitor instrument (GMI) and directional polarized camera (DPC) on the GF-5 satellite. This algorithm is designed to work in cloudless atmospheric conditions with aerosol optical thickness (AOT)<0.3. To quantify the uncertainty level of the retrieved XCO2 when the aerosols and cirrus clouds occurred in retrieving XCO2 with the GMI short wave infrared (SWIR) data, we analyzed the errors rate caused by the six types of aerosols and cirrus clouds. The results indicated that in AOT range of 0.05 to 0.3 (550 nm), the uncertainties of aerosols could lead to errors of -0.27% to 0.59%, -0.32% to 1.43%, -0.10% to 0.49%, -0.12% to 1.17%, -0.35% to 0.49%, and -0.02% to -0.24% for rural, dust, clean continental, maritime, urban, and soot aerosols, respectively. The retrieval results presented a large error due to cirrus clouds. In the cirrus optical thickness range of 0.05 to 0.8 (500 nm), the most underestimation is up to 26.25% when the surface albedo is 0.05. The most overestimation is 8.1% when the surface albedo is 0.65. The retrieval results of GMI simulation data demonstrated that the accuracy of our algorithm is within 4 ppm (˜1%) using the simultaneous measurement of aerosols and clouds from DPC. Moreover, the speed of our algorithm is faster than full-physics (FP) methods. We verified our algorithm with Greenhouse-gases Observing Satellite (GOSAT) data in Beijing area during 2016. The retrieval errors of most observations are within 4 ppm except for summer. Compared with the results of GOSAT, the correlation coefficient is 0.55 for the whole year data, increasing to 0.62 after excluding the summer data.

Investigating the Use of a Simplified Aerosol Parameterization in Space-Based XCO2 Retrievals from OCO-2

NASA Astrophysics Data System (ADS)

Nelson, R. R.; O'Dell, C.

2017-12-01

The primary goal of OCO-2 is to use hyperspectral measurements of reflected near-infrared sunlight to retrieve the column-averaged dry-air mole fraction of carbon dioxide (XCO2) with high accuracy. This is only possible for measurements of scenes nearly free of optically thick clouds and aerosols. As some cloud or aerosol contamination will always be present, the OCO-2 retrieval algorithm includes clouds and aerosols as retrieved properties in its state vector. Information content analyses demonstrate that there are only 2-6 pieces of information about aerosols in the OCO-2 radiances. However, the upcoming OCO-2 algorithm (B8) attempts to retrieve 9 aerosol parameters; this over-fitting can hinder convergence and produce multiple solutions. In this work, we develop a simplified cloud and aerosol parameterization that intelligently reduces the number of retrieved parameters to 5 by only retrieving information about two aerosol layers: a lower tropospheric layer and an upper tropospheric / stratospheric layer. We retrieve the optical depth of each layer and the height of the lower tropospheric layer. Each of these layers contains a mixture of fine and coarse mode aerosol. In comparisons between OCO-2 XCO2 estimates and validation sources including TCCON, this scheme performs about as well as the more complicated OCO-2 retrieval algorithm, but has the potential benefits of more interpretable aerosol results, faster convergence, less nonlinearity, and greater throughput. We also investigate the dependence of our results on the optical properties of the fine and coarse mode aerosol types, such as their effective radii and the environmental relative humidity.

Next Generation Aura-OMI SO2 Retrieval Algorithm: Introduction and Implementation Status

NASA Technical Reports Server (NTRS)

Li, Can; Joiner, Joanna; Krotkov, Nickolay A.; Bhartia, Pawan K.

2014-01-01

We introduce our next generation algorithm to retrieve SO2 using radiance measurements from the Aura Ozone Monitoring Instrument (OMI). We employ a principal component analysis technique to analyze OMI radiance spectral in 310.5-340 nm acquired over regions with no significant SO2. The resulting principal components (PCs) capture radiance variability caused by both physical processes (e.g., Rayleigh and Raman scattering, and ozone absorption) and measurement artifacts, enabling us to account for these various interferences in SO2 retrievals. By fitting these PCs along with SO2 Jacobians calculated with a radiative transfer model to OMI-measured radiance spectra, we directly estimate SO2 vertical column density in one step. As compared with the previous generation operational OMSO2 PBL (Planetary Boundary Layer) SO2 product, our new algorithm greatly reduces unphysical biases and decreases the noise by a factor of two, providing greater sensitivity to anthropogenic emissions. The new algorithm is fast, eliminates the need for instrument-specific radiance correction schemes, and can be easily adapted to other sensors. These attributes make it a promising technique for producing long-term, consistent SO2 records for air quality and climate research. We have operationally implemented this new algorithm on OMI SIPS for producing the new generation standard OMI SO2 products.

Nimbus-7 Scanning Multichannel Microwave Radiometer (SMMR) PARM tape user's guide

NASA Technical Reports Server (NTRS)

Han, D.; Gloersen, P.; Kim, S. T.; Fu, C. C.; Cebula, R. P.; Macmillan, D.

1992-01-01

The Scanning Multichannel Microwave Radiometer (SMMR) instrument, onboard the Nimbus-7 spacecraft, collected data from Oct. 1978 until Jun. 1986. The data were processed to physical parameter level products. Geophysical parameters retrieved include the following: sea-surface temperatures, sea-surface windspeed, total column water vapor, and sea-ice parameters. These products are stored on PARM-LO, PARM-SS, and PARM-30 tapes. The geophysical parameter retrieval algorithms and the quality of these products are described for the period between Nov. 1978 and Oct 1985. Additionally, data formats and data availability are included.

Effects of Surface BRDF on the OMI Cloud and NO2 Retrievals: A New Approach Based on Geometry-Dependent Lambertian Equivalent Reflectivity (GLER) Derived from MODIS

NASA Technical Reports Server (NTRS)

Vasilkov, Alexander; Qin, Wenhan; Krotkov, Nickolay; Lamsal, Lok; Spurr, Robert; Haffner, David; Joiner, Joanna; Yang, Eun-Su; Marchenko, Sergey

2017-01-01

The Ozone Monitoring Instrument (OMI) cloud and NO2 algorithms use a monthly gridded surface reflectivity climatology that does not depend upon the observation geometry. In reality, reflection of incoming direct and diffuse solar light from land or ocean surfaces is sensitive to the sun sensor geometry. This dependence is described by the bidirectional reflectance distribution function (BRDF). To account for the BRDF, we propose to use a new concept of geometry-dependent Lambertian equivalent reflectivity (GLER). Implementation within the existing OMI cloud and NO2 retrieval infrastructure requires changes only to the input surface reflectivity database. GLER is calculated using a vector radiative transfer model with high spatial resolution BRDF information from MODIS over land and the Cox Munk slope distribution over ocean with a contribution from water-leaving radiance. We compare GLER and climatological LER at 466 nm, which is used in the OMI O2-O2cloud algorithm to derive effective cloud fractions. A detailed comparison of the cloud fractions and pressures derived with climatological and GLERs is carried out. GLER and corresponding retrieved cloud products are then used as input to the OMI NO2 algorithm. We find that replacing the climatological OMI-based LERs with GLERs can increase NO2 vertical columns by up to 50 % in highly polluted areas; the differences include both BRDF effects and biases between the MODIS and OMI-based surface reflectance data sets. Only minor changes to NO2 columns (within 5 %) are found over unpolluted and overcast areas.

NASA GPM GV Science Implementation

NASA Technical Reports Server (NTRS)

Petersen, W. A.

2009-01-01

Pre-launch algorithm development & post-launch product evaluation: The GPM GV paradigm moves beyond traditional direct validation/comparison activities by incorporating improved algorithm physics & model applications (end-to-end validation) in the validation process. Three approaches: 1) National Network (surface): Operational networks to identify and resolve first order discrepancies (e.g., bias) between satellite and ground-based precipitation estimates. 2) Physical Process (vertical column): Cloud system and microphysical studies geared toward testing and refinement of physically-based retrieval algorithms. 3) Integrated (4-dimensional): Integration of satellite precipitation products into coupled prediction models to evaluate strengths/limitations of satellite precipitation producers.

Comparison of TOMS, SBW & SBUV/2 Version 8 Total Column Ozone Data with Data from Groundstations

NASA Technical Reports Server (NTRS)

Labow, G. J.; McPeters, R. D.; Bhartia, P. K.

2004-01-01

The Nimbus-7 and Earth Probe Total Ozone Mapping Spectrometer (TOMS) data as well as SBUV and SBUV/2 data have been reprocessed with a new retrieval algorithm (Version 8) and an updated calibration procedure. An overview will be presented systematically comparing ozone values to an ensemble of Brewer and Dobson spectrophotometers. The comparisons were made as a function of latitude, solar zenith angle, reflectivity and total ozone. Results show that the accuracy of the TOMS retrieval has been improved when aerosols are present in the atmosphere, when snow/ice and sea glint are present, and when ozone in the northern hemisphere is extremely low. TOMS overpass data are derived from the single TOMS best match measurement, almost always located within one degree of the ground station and usually made within an hour of local noon. The Version 8 Earth Probe TOMS ozone values have decreased by an average of about 1% due to a much better understanding of the calibration of the instrument. N-7 SBUV as well as the series of NOAA SBUV/2 column ozone values have also been processed with the Version 8 algorithm and have been compared to values from an ensemble of groundstations. Results show that the SBW column ozone values agree well with the groundstations and the datasets are useful for trend studies.

Data Retrieval Algorithm and Uncertainty Analysis for a Miniaturized, Laser Heterodyne Radiometer

NASA Astrophysics Data System (ADS)

Miller, J. H.; Melroy, H.; Wilson, E. L.; Clarke, G. B.

2013-12-01

In a collaboration between NASA Goddard Space Flight Center and George Washington University, a low-cost, surface instrument is being developed that can continuously monitor key carbon cycle gases in the atmospheric column: carbon dioxide (CO2) and methane (CH4). The instrument is based on a miniaturized, laser heterodyne radiometer (LHR) using near infrared (NIR) telecom lasers. Despite relatively weak absorption line strengths in this spectral region, spectrally-resolved atmospheric column absorptions for these two molecules fall in the range of 60-80% and thus sensitive and precise measurements of column concentrations are possible. Further, because the LHR technique has the potential for sub-Doppler spectral resolution, the possibility exists for interrogating line shapes to extract altitude profiles of the greenhouse gases. From late 2012 through 2013 the instrument was deployed for a variety of field measurements including at Park Falls, Wisconsin; Castle Airport near Atwater, California; and at the NOAA Mauna Loa Observatory in Hawaii. For each subsequent campaign, improvement in the figures of merit for the instrument (notably spectral sweep time and absorbance noise) has been observed. For the latter, the absorbance noise is approaching 0.002 optical density (OD) noise on a 1.8 OD signal. This presentation presents an overview of the measurement campaigns in the context of the data retrieval algorithm under development at GW for the calculation of column concentrations from them. For light transmission through the atmosphere, it is necessary to account for variation of pressure, temperature, composition, and refractive index through the atmosphere that are all functions of latitude, longitude, time of day, altitude, etc. In our initial work we began with coding developed under the LOWTRAN and MODTRAN programs by the AFOSR (and others). We also assumed temperature and pressure profiles from the 1976 US Standard Atmosphere and used the US Naval Observatory database for local zenith angle calculations to initialize path trajectory calculations. In our newest version of the retrieval algorithm, the Python programming language module PySolar is used for the path geometry calculations. For temperature, pressure, and humidity profiles with altitude we use the Modern-Era Retrospective Analysis for Research and Applications (MERRA) data that has been compiled every 6 hours. Spectral simulation is accomplished by integrating short-path segments along the trajectory using the SpecSyn spectral simulation suite developed at GW. Column concentrations are extracted by minimizing residuals between observed and modeled spectrum using the Nelder-Mead simplex algorithm as implemented in the SciPy Python module. We will also present an assessment of uncertainty in the reported concentrations from assumptions made in the meteorological data, LHR instrument and tracker noise, and radio frequency bandwidth and describe additional future goals in instrument development and deployment targets.

Retrieval of NO2 stratospheric profiles from ground-based zenith-sky uv-visible measurements at 60°N

NASA Astrophysics Data System (ADS)

Hendrick, F.; van Roozendael, M.; Lambert, J.-C.; Fayt, C.; Hermans, C.; de Mazière, M.

2003-04-01

Nitrogen dioxide (NO_2) plays an important role in controlling ozone abundances in the stratosphere, either directly through the NOx (NO+NO_2) catalytic cycle, either indirectly by reaction with the radical ClO to form the reservoir species ClONO_2. In this presentation, NO_2 stratospheric profiles are retrieved from ground-based UV-visible NO_2 slant column abundances measured since 1998 at the complementary NDSC station of Harestua (Norway, 60^oN). The retrieval algorithm is based on the Rodgers optimal estimation inversion method and a forward model consisting in the IASB-BIRA stacked box photochemical model PSCBOX coupled to the radiative transfer package UVspec/DISORT. This algorithm has been applied to a set of about 50 sunrises and sunsets for which spatially and temporally coincident NO_2 measurements made by the HALOE (Halogen Occultation Experiment) instrument on board the Upper Atmosphere Research Satellite (UARS) are available. The consistency between retrieved and HALOE profiles is discussed in term of the different seasonal conditions investigated which are spring with and without chlorine activation, summer, and fall.

Technology advancement for the ASCENDS mission using the ASCENDS CarbonHawk Experiment Simulator (ACES)

NASA Astrophysics Data System (ADS)

Obland, M. D.; Antill, C.; Browell, E. V.; Campbell, J. F.; CHEN, S.; Cleckner, C.; Dijoseph, M. S.; Harrison, F. W.; Ismail, S.; Lin, B.; Meadows, B. L.; Mills, C.; Nehrir, A. R.; Notari, A.; Prasad, N. S.; Kooi, S. A.; Vitullo, N.; Dobler, J. T.; Bender, J.; Blume, N.; Braun, M.; Horney, S.; McGregor, D.; Neal, M.; Shure, M.; Zaccheo, T.; Moore, B.; Crowell, S.; Rayner, P. J.; Welch, W.

2013-12-01

The ASCENDS CarbonHawk Experiment Simulator (ACES) is a NASA Langley Research Center project funded by NASA's Earth Science Technology Office that seeks to advance technologies critical to measuring atmospheric column carbon dioxide (CO2) mixing ratios in support of the NASA Active Sensing of CO2 Emissions over Nights, Days, and Seasons (ASCENDS) mission. The technologies being advanced are: (1) multiple transmitter and telescope-aperture operations, (2) high-efficiency CO2 laser transmitters, (3) a high bandwidth detector and transimpedance amplifier (TIA), and (4) advanced algorithms for cloud and aerosol discrimination. The instrument architecture is being developed for ACES to operate on a high-altitude aircraft, and it will be directly scalable to meet the ASCENDS mission requirements. The above technologies are critical for developing an airborne simulator and spaceborne instrument with lower platform consumption of size, mass, and power, and with improved performance. This design employs several laser transmitters and telescope-apertures to demonstrate column CO2 retrievals with alignment of multiple laser beams in the far-field. ACES will transmit five laser beams: three from commercial lasers operating near 1.57-microns, and two from the Exelis atmospheric oxygen (O2) fiber laser amplifier system operating near 1.26-microns. The Master Oscillator Power Amplifier at 1.57-microns measures CO2 column concentrations using an Integrated-Path Differential Absorption (IPDA) lidar approach. O2 column amounts needed for calculating the CO2 mixing ratio will be retrieved using the Exelis laser system with a similar IPDA approach. The three aperture telescope design was built to meet the constraints of the Global Hawk high-altitude unmanned aerial vehicle (UAV). This assembly integrates fiber-coupled transmit collimators for all of the laser transmitters and fiber-coupled optical signals from the three telescopes to the aft optics and detector package. The detector/TIA effort has improved the existing detector subsystem by: increasing its bandwidth to 5.4 MHz, exceeding the original goal of 5 MHz; reducing the overall mass from 18 lbs to <10 lbs; and increasing the duration of autonomous, service-free operation periods from 4 hrs to >24 hrs. The new detector subsystem will permit higher laser modulation rates, which provides greater flexibility for implementing thin-cloud discrimination algorithms as well as improving range resolution and error reduction, and will enable long-range flights on the Global Hawk. The cloud/aerosol discrimination work features development of new algorithms by Langley and Exelis for the avoidance of bias errors in the retrieval of column CO2 induced by the presence of thin clouds.

Intercomparison of daytime stratospheric NO2 satellite retrievals and model simulations

NASA Astrophysics Data System (ADS)

Belmonte Rivas, M.; Veefkind, P.; Boersma, F.; Levelt, P.; Eskes, H.; Gille, J.

2014-01-01

This paper evaluates the agreement between stratospheric NO2 retrievals from infrared limb sounders (MIPAS and HIRDLS) and solar UV/VIS backscatter sensors (OMI, SCIAMACHY limb and nadir) over the 2005-2007 period and across the seasons. The observational agreement is contrasted with the representation of NO2 profiles in 3-D chemical transport models such as the Whole Atmosphere Community Climate Model (SD-WACCM) and TM4. A conclusion central to this work is that the definition of a reference for stratospheric NO2 columns formed by consistent agreement among SCIAMACHY, MIPAS and HIRDLS limb records (all of which agree to within 0.25 × 1015 molecules cm-2 or better than 10%) allows us to draw attention to relative errors in other datasets, e.g.: (1) the WACCM model overestimates NO2 densities in the extratropical lower stratosphere, particularly over northern latitudes by up to 35% relative to limb observations, and (2) there are remarkable discrepancies between stratospheric NO2 column estimates from limb and nadir techniques, with a characteristic seasonal and latitude dependent pattern. We find that SCIAMACHY nadir and OMI stratospheric columns show overall biases of -0.6 × 1015 molecules cm-2 (-20%) and +0.6 × 10 15 molecules cm-2 (+20%) relative to limb observations. It is highlighted that biases in nadir stratospheric columns are not expected to affect tropospheric retrievals significantly, and that they can be attributed to errors in the total slant column density, either related to algorithmic or instrumental effects. In order to obtain accurate and long time series of stratospheric NO2, a critical evaluation of the currently used Differential Optical Absorption Spectroscopy (DOAS) approaches to nadir retrievals becomes essential, as well as their agreement to limb and ground-based observations, particularly now that limb techniques are giving way to nadir observations as the next generation of climate and air quality monitoring instruments pushes forth.

OMI Global Tropospheric Bromine Oxide (BrO) Column Densities: Algorithm, Retrieval and Initial Validation

NASA Astrophysics Data System (ADS)

Suleiman, R. M.; Chance, K.; Liu, X.; Kurosu, T. P.; Gonzalez Abad, G.

2014-12-01

We present and discuss a detailed description of the retrieval algorithms for the OMI BrO product. The BrO algorithms are based on direct fitting of radiances from 319.0-347.5 nm. Radiances are modeled from the solar irradiance, attenuated and adjusted by contributions from the target gas and interfering gases, rotational Raman scattering, undersampling, additive and multiplicative closure polynomials and a common mode spectrum. The version of the algorithm used for both BrO includes relevant changes with respect to the operational code, including the fit of the O2-O2 collisional complex, updates in the high resolution solar reference spectrum, updates in spectroscopy, an updated Air Mass Factor (AMF) calculation scheme, and the inclusion of scattering weights and vertical profiles in the level 2 products. Updates to the algorithms include accurate scattering weights and air mass factor calculations, scattering weights and profiles in outputs and available cross sections. We include retrieval parameter and window optimization to reduce the interference from O3, HCHO, O2-O2, SO2, improve fitting accuracy and uncertainty, reduce striping, and improve the long-term stability. We validate OMI BrO with ground-based measurements from Harestua and with chemical transport model simulations. We analyze the global distribution and seasonal variation of BrO and investigate BrO emissions from volcanoes and salt lakes.

Improved Soundings and Error Estimates using AIRS/AMSU Data

NASA Technical Reports Server (NTRS)

Susskind, Joel

2006-01-01

AIRS was launched on EOS Aqua on May 4, 2002, together with AMSU A and HSB, to form a next generation polar orbiting infrared and microwave atmospheric sounding system. The primary products of AIRS/AMSU are twice daily global fields of atmospheric temperature-humidity profiles, ozone profiles, sea/land surface skin temperature, and cloud related parameters including OLR. The sounding goals of AIRS are to produce 1 km tropospheric layer mean temperatures with an rms error of 1 K, and layer precipitable water with an rms error of 20 percent, in cases with up to 80 percent effective cloud cover. The basic theory used to analyze AIRS/AMSU/HSB data in the presence of clouds, called the at-launch algorithm, and a post-launch algorithm which differed only in the minor details from the at-launch algorithm, have been described previously. The post-launch algorithm, referred to as AIRS Version 4.0, has been used by the Goddard DAAC to analyze and distribute AIRS retrieval products. In this paper we show progress made toward the AIRS Version 5.0 algorithm which will be used by the Goddard DAAC starting late in 2006. A new methodology has been developed to provide accurate case by case error estimates for retrieved geophysical parameters and for the channel by channel cloud cleared radiances used to derive the geophysical parameters from the AIRS/AMSU observations. These error estimates are in turn used for quality control of the derived geophysical parameters and clear column radiances. Improvements made to the retrieval algorithm since Version 4.0 are described as well as results comparing Version 5.0 retrieval accuracy and spatial coverage with those obtained using Version 4.0.

Atmospheric infrared sounder

NASA Technical Reports Server (NTRS)

Rosenkranz, Philip, W.; Staelin, David, H.

1995-01-01

This report summarizes the activities of two Atmospheric Infrared Sounder (AIRS) team members during the first half of 1995. Changes to the microwave first-guess algorithm have separated processing of Advanced Microwave Sounding Unit A (AMSU-A) from AMSU-B data so that the different spatial resolutions of the two instruments may eventually be considered. Two-layer cloud simulation data was processed with this algorithm. The retrieved water vapor column densities and liquid water are compared. The information content of AIRS data was applied to AMSU temperature profile retrievals in clear and cloudy atmospheres. The significance of this study for AIRS/AMSU processing lies in the improvement attributable to spatial averaging and in the good results obtained with a very simple algorithm when all of the channels are used. Uncertainty about the availability of either a Microwave Humidity Sensor (MHS) or AMSU-B for EOS has motivated consideration of possible low-cost alternative designs for a microwave humidity sensor. One possible configuration would have two local oscillators (compared to three for MHS) at 118.75 and 183.31 GHz. Retrieval performances of the two instruments were compared in a memorandum titled 'Comparative Analysis of Alternative MHS Configurations', which is attached.

Carbon monoxide column retrieval for clear-sky and cloudy atmospheres: a full-mission data set from SCIAMACHY 2.3 µm reflectance measurements

NASA Astrophysics Data System (ADS)

Borsdorff, Tobias; aan de Brugh, Joost; Hu, Haili; Nédélec, Philippe; Aben, Ilse; Landgraf, Jochen

2017-05-01

We discuss the retrieval of carbon monoxide (CO) vertical column densities from clear-sky and cloud contaminated 2311-2338 nm reflectance spectra measured by the Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) from January 2003 until the end of the mission in April 2012. These data were processed with the Shortwave Infrared CO Retrieval algorithm (SICOR) that we developed for the operational data processing of the Tropospheric Monitoring Instrument (TROPOMI) that will be launched on ESA's Sentinel-5 Precursor (S5P) mission. This study complements previous work that was limited to clear-sky observations over land. Over the oceans, CO is estimated from cloudy-sky measurements only, which is an important addition to the SCIAMACHY clear-sky CO data set as shown by NDACC and TCCON measurements at coastal sites. For Ny-Ålesund, Lauder, Mauna Loa and Reunion, a validation of SCIAMACHY clear-sky retrievals is not meaningful because of the high retrieval noise and the few collocations at these sites. The situation improves significantly when considering cloudy-sky observations, where we find a low mean bias b = ±6. 0 ppb and a strong correlation between the validation and the SCIAMACHY results with a mean Pearson correlation coefficient r = 0. 7. Also for land observations, cloudy-sky CO retrievals present an interesting complement to the clear-sky data set. For example, at the cities Tehran and Beijing the agreement of SCIAMACHY clear-sky CO observations with MOZAIC/IAGOS airborne measurements is poor with a mean bias of b = 171. 2 ppb and 57.9 ppb because of local CO pollution, which cannot be captured by SCIAMACHY. For cloudy-sky retrievals, the validation improves significantly. Here the retrieved column is mainly sensitive to CO above the cloud and so not affected by the strong local surface emissions. Adjusting the MOZAIC/IAGOS measurements to the vertical sensitivity of the retrieval, the mean bias adds up to b = 52. 3 ppb and 5.0 ppb for Tehran and Beijing. At the less urbanised region around the airport Windhoek, local CO pollution is less prominent and so MOZAIC/IAGOS measurements agree well with SCIAMACHY clear-sky retrievals with a mean bias of b = 15. 5 ppb, but can be even further improved for cloudy SCIAMACHY observations with a mean bias of b = 0. 2 ppb. Overall the cloudy-sky CO retrievals from SCIAMACHY short-wave infrared measurements present a major extension of the clear-sky-only data set, which more than triples the amount of data and adds unique observations over the oceans. Moreover, the study represents the first application of the S5P algorithm for operational CO data processing on cloudy observations prior to the launch of the S5P mission.

Daytime O/N2 Retrieval Algorithm for the Ionospheric Connection Explorer (ICON)

NASA Astrophysics Data System (ADS)

Stephan, Andrew W.; Meier, R. R.; England, Scott L.; Mende, Stephen B.; Frey, Harald U.; Immel, Thomas J.

2018-02-01

The NASA Ionospheric Connection Explorer Far-Ultraviolet spectrometer, ICON FUV, will measure altitude profiles of the daytime far-ultraviolet (FUV) OI 135.6 nm and N2 Lyman-Birge-Hopfield (LBH) band emissions that are used to determine thermospheric density profiles and state parameters related to thermospheric composition; specifically the thermospheric column O/N2 ratio (symbolized as ΣO/N2). This paper describes the algorithm concept that has been adapted and updated from one previously applied with success to limb data from the Global Ultraviolet Imager (GUVI) on the NASA Thermosphere Ionosphere Mesosphere Energetics and Dynamics (TIMED) mission. We also describe the requirements that are imposed on the ICON FUV to measure ΣO/N2 over any 500-km sample in daytime with a precision of better than 8.7%. We present results from orbit-simulation testing that demonstrates that the ICON FUV and our thermospheric composition retrieval algorithm can meet these requirements and provide the measurements necessary to address ICON science objectives.

A Fast and Sensitive New Satellite SO2 Retrieval Algorithm based on Principal Component Analysis: Application to the Ozone Monitoring Instrument

NASA Technical Reports Server (NTRS)

Li, Can; Joiner, Joanna; Krotkov, A.; Bhartia, Pawan K.

2013-01-01

We describe a new algorithm to retrieve SO2 from satellite-measured hyperspectral radiances. We employ the principal component analysis technique in regions with no significant SO2 to capture radiance variability caused by both physical processes (e.g., Rayleigh and Raman scattering and ozone absorption) and measurement artifacts. We use the resulting principal components and SO2 Jacobians calculated with a radiative transfer model to directly estimate SO2 vertical column density in one step. Application to the Ozone Monitoring Instrument (OMI) radiance spectra in 310.5-340 nm demonstrates that this approach can greatly reduce biases in the operational OMI product and decrease the noise by a factor of 2, providing greater sensitivity to anthropogenic emissions. The new algorithm is fast, eliminates the need for instrument-specific radiance correction schemes, and can be easily adapted to other sensors. These attributes make it a promising technique for producing longterm, consistent SO2 records for air quality and climate research.

How Can TOLNet Help to Better Understand Tropospheric Ozone? A Satellite Perspective

NASA Technical Reports Server (NTRS)

Johnson, Matthew S.

2018-01-01

Potential sources of a priori ozone (O3) profiles for use in Tropospheric Emissions: Monitoring of Pollution (TEMPO) satellite tropospheric O3 retrievals are evaluated with observations from multiple Tropospheric Ozone Lidar Network (TOLNet) systems in North America. An O3 profile climatology (tropopause-based O3 climatology (TB-Clim), currently proposed for use in the TEMPO O3 retrieval algorithm) derived from ozonesonde observations and O3 profiles from three separate models (operational Goddard Earth Observing System (GEOS-5) Forward Processing (FP) product, reanalysis product from Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA2), and the GEOS-Chem chemical transport model (CTM)) were: 1) evaluated with TOLNet measurements on various temporal scales (seasonally, daily, hourly) and 2) implemented as a priori information in theoretical TEMPO tropospheric O3 retrievals in order to determine how each a priori impacts the accuracy of retrieved tropospheric (0-10 km) and lowermost tropospheric (LMT, 0-2 km) O3 columns. We found that all sources of a priori O3 profiles evaluated in this study generally reproduced the vertical structure of summer-averaged observations. However, larger differences between the a priori profiles and lidar observations were observed when evaluating inter-daily and diurnal variability of tropospheric O3. The TB-Clim O3 profile climatology was unable to replicate observed inter-daily and diurnal variability of O3 while model products, in particular GEOS-Chem simulations, displayed more skill in reproducing these features. Due to the ability of models, primarily the CTM used in this study, on average to capture the inter-daily and diurnal variability of tropospheric and LMT O3 columns, using a priori profiles from CTM simulations resulted in TEMPO retrievals with the best statistical comparison with lidar observations. Furthermore, important from an air quality perspective, when high LMT O3 values were observed, using CTM a priori profiles resulted in TEMPO LMT O3 retrievals with the least bias. The application of time-specific (non-climatological) hourly/daily model predictions as the a priori profile in TEMPO O3 retrievals will be best suited when applying this data to study air quality or event-based processes as the standard retrieval algorithm will still need to use a climatology product. Follow-on studies to this work are currently being conducted to investigate the application of different CTM-predicted O3 climatology products in the standard TEMPO retrieval algorithm. Finally, similar methods to those used in this study can be easily applied by TEMPO data users to recalculate tropospheric O3 profiles provided from the standard retrieval using a different source of a priori.

Development of a harmonised multi sensor retrieval scheme for HCHO within the Quality Assurance For Essential Climate Variables (QA4ECV) project

NASA Astrophysics Data System (ADS)

De Smedt, Isabelle; Richter, Andreas; Beirle, Steffen; Danckaert, Thomas; Van Roozendael, Michel; Yu, Huan; Bösch, Tim; Hilboll, Andreas; Peters, Enno; Doerner, Steffen; Wagner, Thomas; Wang, Yang; Lorente, Alba; Eskes, Henk; Van Geffen, Jos; Boersma, Folkert

2016-04-01

One of the main goals of the QA4ECV project is to define community best-practices for the generation of multi-decadal ECV data records from satellite instruments. QA4ECV will develop retrieval algorithms for the Land ECVs surface albedo, leaf area index (LAI), and fraction of active photosynthetic radiation (fAPAR), as well as for the Atmosphere ECV ozone and aerosol precursors nitrogen dioxide (NO2), formaldehyde (HCHO), and carbon monoxide (CO). Here we assess best practices and provide recommendations for the retrieval of HCHO. Best practices are established based on (1) a detailed intercomparison exercise between the QA4ECV partner's for each specific algorithm processing steps, (2) the feasibility of implementation, and (3) the requirement to generate consistent multi-sensor multi-decadal data records. We propose a fitting window covering the 328.5-346 nm spectral interval for the morning sensors (GOME, SCIAMACHY and GOME-2) and an extension to 328.5-359 nm for OMI and GOME-2, allowed by improved quality of the recorded spectra. A high level of consistency between group algorithms is found when the retrieval settings are carefully aligned. However, the retrieval of slant columns is highly sensitive to any change in the selected settings. The use of a mean background radiance as DOAS reference spectrum allows for a stabilization of the retrievals. A background correction based on the reference sector method is recommended for implementation in the QA4ECV HCHO algorithm as it further reduces retrieval uncertainties. HCHO AMFs using different radiative transfer codes show a good overall consistency when harmonized settings are used. As for NO2, it is proposed to use a priori HCHO profiles from the TM5 model. These are provided on a 1°x1° latitude-longitude grid.

Towards Improving Satellite Tropospheric NO2 Retrieval Products: Impacts of the spatial resolution and lighting NOx production from the a priori chemical transport model

NASA Astrophysics Data System (ADS)

Smeltzer, C. D.; Wang, Y.; Zhao, C.; Boersma, F.

2009-12-01

Polar orbiting satellite retrievals of tropospheric nitrogen dioxide (NO2) columns are important to a variety of scientific applications. These NO2 retrievals rely on a priori profiles from chemical transport models and radiative transfer models to derive the vertical columns (VCs) from slant columns measurements. In this work, we compare the retrieval results using a priori profiles from a global model (TM4) and a higher resolution regional model (REAM) at the OMI overpass hour of 1330 local time, implementing the Dutch OMI NO2 (DOMINO) retrieval. We also compare the retrieval results using a priori profiles from REAM model simulations with and without lightning NOx (NO + NO2) production. A priori model resolution and lightning NOx production are both found to have large impact on satellite retrievals by altering the satellite sensitivity to a particular observation by shifting the NO2 vertical distribution interpreted by the radiation model. The retrieved tropospheric NO2 VCs may increase by 25-100% in urban regions and be reduced by 50% in rural regions if the a priori profiles from REAM simulations are used during the retrievals instead of the profiles from TM4 simulations. The a priori profiles with lightning NOx may result in a 25-50% reduction of the retrieved tropospheric NO2 VCs compared to the a priori profiles without lightning. As first priority, a priori vertical NO2 profiles from a chemical transport model with a high resolution, which can better simulate urban-rural NO2 gradients in the boundary layer and make use of observation-based parameterizations of lightning NOx production, should be first implemented to obtain more accurate NO2 retrievals over the United States, where NOx source regions are spatially separated and lightning NOx production is significant. Then as consequence of a priori NO2 profile variabilities resulting from lightning and model resolution dynamics, geostationary satellite, daylight observations would further promote the next step towards producing a more complete NO2 data product provided sufficient resolution of the observations. Both the corrected retrieval algorithm and the proposed next generation geostationary satellite observations would thus improve emission inventories, better validate model simulations, and advantageously optimize regional specific ozone control strategies.

Improved Algorithms for Accurate Retrieval of UV - Visible Diffuse Attenuation Coefficients in Optically Complex, Inshore Waters

NASA Technical Reports Server (NTRS)

Cao, Fang; Fichot, Cedric G.; Hooker, Stanford B.; Miller, William L.

2014-01-01

Photochemical processes driven by high-energy ultraviolet radiation (UVR) in inshore, estuarine, and coastal waters play an important role in global bio geochemical cycles and biological systems. A key to modeling photochemical processes in these optically complex waters is an accurate description of the vertical distribution of UVR in the water column which can be obtained using the diffuse attenuation coefficients of down welling irradiance (Kd()). The Sea UV Sea UVc algorithms (Fichot et al., 2008) can accurately retrieve Kd ( 320, 340, 380,412, 443 and 490 nm) in oceanic and coastal waters using multispectral remote sensing reflectances (Rrs(), Sea WiFS bands). However, SeaUVSeaUVc algorithms are currently not optimized for use in optically complex, inshore waters, where they tend to severely underestimate Kd(). Here, a new training data set of optical properties collected in optically complex, inshore waters was used to re-parameterize the published SeaUVSeaUVc algorithms, resulting in improved Kd() retrievals for turbid, estuarine waters. Although the updated SeaUVSeaUVc algorithms perform best in optically complex waters, the published SeaUVSeaUVc models still perform well in most coastal and oceanic waters. Therefore, we propose a composite set of SeaUVSeaUVc algorithms, optimized for Kd() retrieval in almost all marine systems, ranging from oceanic to inshore waters. The composite algorithm set can retrieve Kd from ocean color with good accuracy across this wide range of water types (e.g., within 13 mean relative error for Kd(340)). A validation step using three independent, in situ data sets indicates that the composite SeaUVSeaUVc can generate accurate Kd values from 320 490 nm using satellite imagery on a global scale. Taking advantage of the inherent benefits of our statistical methods, we pooled the validation data with the training set, obtaining an optimized composite model for estimating Kd() in UV wavelengths for almost all marine waters. This optimized composite set of SeaUVSeaUVc algorithms will provide the optical community with improved ability to quantify the role of solar UV radiation in photochemical and photobiological processes in the ocean.

Smithsonian Astrophysical Observatory Ozone Mapping and Profiler Suite (SAO OMPS) formaldehyde retrieval

NASA Astrophysics Data System (ADS)

González Abad, Gonzalo; Vasilkov, Alexander; Seftor, Colin; Liu, Xiong; Chance, Kelly

2016-07-01

This paper presents our new formaldehyde (H2CO) retrievals, obtained from spectra recorded by the nadir instrument of the Ozone Mapping and Profiler Suite (OMPS) flown on board NASA's Suomi National Polar-orbiting Partnership (SUOMI-NPP) satellite. Our algorithm is similar to the one currently in place for the production of NASA's Ozone Monitoring Instrument (OMI) operational H2CO product. We are now able to produce a set of long-term data from two different instruments that share a similar concept and a similar retrieval approach. The ongoing overlap period between OMI and OMPS offers a perfect opportunity to study the consistency between both data sets. The different spatial and spectral resolution of the instruments is a source of discrepancy in the retrievals despite the similarity of the physic assumptions of the algorithm. We have concluded that the reduced spectral resolution of OMPS in comparison with OMI is not a significant obstacle in obtaining good-quality retrievals. Indeed, the improved signal-to-noise ratio of OMPS with respect to OMI helps to reduce the noise of the retrievals performed using OMPS spectra. However, the size of OMPS spatial pixels imposes a limitation in the capability to distinguish particular features of H2CO that are discernible with OMI. With root mean square (RMS) residuals ˜ 5 × 10-4 for individual pixels we estimate the detection limit to be about 7.5 × 1015 molecules cm-2. Total vertical column density (VCD) errors for individual pixels range between 40 % for pixels with high concentrations to 100 % or more for pixels with concentrations at or below the detection limit. We compare different OMI products (SAO OMI v3.0.2 and BIRA OMI v14) with our OMPS product using 1 year of data, between September 2012 and September 2013. The seasonality of the retrieved slant columns is captured similarly by all products but there are discrepancies in the values of the VCDs. The mean biases among the two OMI products and our OMPS product are 23 % between OMI SAO and OMPS SAO and 28 % between OMI BIRA and OMPS SAO for eight selected regions.

Multi-sensor cloud and aerosol retrieval simulator and remote sensing from model parameters - Part 2: Aerosols

NASA Astrophysics Data System (ADS)

Wind, Galina; da Silva, Arlindo M.; Norris, Peter M.; Platnick, Steven; Mattoo, Shana; Levy, Robert C.

2016-07-01

The Multi-sensor Cloud Retrieval Simulator (MCRS) produces a "simulated radiance" product from any high-resolution general circulation model with interactive aerosol as if a specific sensor such as the Moderate Resolution Imaging Spectroradiometer (MODIS) were viewing a combination of the atmospheric column and land-ocean surface at a specific location. Previously the MCRS code only included contributions from atmosphere and clouds in its radiance calculations and did not incorporate properties of aerosols. In this paper we added a new aerosol properties module to the MCRS code that allows users to insert a mixture of up to 15 different aerosol species in any of 36 vertical layers.This new MCRS code is now known as MCARS (Multi-sensor Cloud and Aerosol Retrieval Simulator). Inclusion of an aerosol module into MCARS not only allows for extensive, tightly controlled testing of various aspects of satellite operational cloud and aerosol properties retrieval algorithms, but also provides a platform for comparing cloud and aerosol models against satellite measurements. This kind of two-way platform can improve the efficacy of model parameterizations of measured satellite radiances, allowing the assessment of model skill consistently with the retrieval algorithm. The MCARS code provides dynamic controls for appearance of cloud and aerosol layers. Thereby detailed quantitative studies of the impacts of various atmospheric components can be controlled.In this paper we illustrate the operation of MCARS by deriving simulated radiances from various data field output by the Goddard Earth Observing System version 5 (GEOS-5) model. The model aerosol fields are prepared for translation to simulated radiance using the same model subgrid variability parameterizations as are used for cloud and atmospheric properties profiles, namely the ICA technique. After MCARS computes modeled sensor radiances equivalent to their observed counterparts, these radiances are presented as input to operational remote-sensing algorithms.Specifically, the MCARS-computed radiances are input into the processing chain used to produce the MODIS Data Collection 6 aerosol product (M{O/Y}D04). The M{O/Y}D04 product is of course normally produced from M{O/Y}D021KM MODIS Level-1B radiance product directly acquired by the MODIS instrument. MCARS matches the format and metadata of a M{O/Y}D021KM product. The resulting MCARS output can be directly provided to MODAPS (MODIS Adaptive Processing System) as input to various operational atmospheric retrieval algorithms. Thus the operational algorithms can be tested directly without needing to make any software changes to accommodate an alternative input source.We show direct application of this synthetic product in analysis of the performance of the MOD04 operational algorithm. We use biomass-burning case studies over Amazonia employed in a recent Working Group on Numerical Experimentation (WGNE)-sponsored study of aerosol impacts on numerical weather prediction (Freitas et al., 2015). We demonstrate that a known low bias in retrieved MODIS aerosol optical depth appears to be due to a disconnect between actual column relative humidity and the value assumed by the MODIS aerosol product.

Multi-Sensor Cloud and Aerosol Retrieval Simulator and Remote Sensing from Model Parameters . Part 2; Aerosols

NASA Technical Reports Server (NTRS)

Wind, Galina; Da Silva, Arlindo M.; Norris, Peter M.; Platnick, Steven; Mattoo, Shana; Levy, Robert C.

2016-01-01

The Multi-sensor Cloud Retrieval Simulator (MCRS) produces a simulated radiance product from any high-resolution general circulation model with interactive aerosol as if a specific sensor such as the Moderate Resolution Imaging Spectroradiometer (MODIS) were viewing a combination of the atmospheric column and land ocean surface at a specific location. Previously the MCRS code only included contributions from atmosphere and clouds in its radiance calculations and did not incorporate properties of aerosols. In this paper we added a new aerosol properties module to the MCRS code that allows users to insert a mixture of up to 15 different aerosol species in any of 36 vertical layers. This new MCRS code is now known as MCARS (Multi-sensor Cloud and Aerosol Retrieval Simulator). Inclusion of an aerosol module into MCARS not only allows for extensive, tightly controlled testing of various aspects of satellite operational cloud and aerosol properties retrieval algorithms, but also provides a platform for comparing cloud and aerosol models against satellite measurements. This kind of two-way platform can improve the efficacy of model parameterizations of measured satellite radiances, allowing the assessment of model skill consistently with the retrieval algorithm. The MCARS code provides dynamic controls for appearance of cloud and aerosol layers. Thereby detailed quantitative studies of the impacts of various atmospheric components can be controlled. In this paper we illustrate the operation of MCARS by deriving simulated radiances from various data field output by the Goddard Earth Observing System version 5 (GEOS-5) model. The model aerosol fields are prepared for translation to simulated radiance using the same model sub grid variability parameterizations as are used for cloud and atmospheric properties profiles, namely the ICA technique. After MCARS computes modeled sensor radiances equivalent to their observed counterparts, these radiances are presented as input to operational remote-sensing algorithms. Specifically, the MCARS-computed radiances are input into the processing chain used to produce the MODIS Data Collection 6 aerosol product (MOYD04). TheMOYD04 product is of course normally produced from MOYD021KM MODIS Level-1B radiance product directly acquired by the MODIS instrument. MCARS matches the format and metadata of a MOYD021KM product. The resulting MCARS output can be directly provided to MODAPS (MODIS Adaptive Processing System) as input to various operational atmospheric retrieval algorithms. Thus the operational algorithms can be tested directly without needing to make any software changes to accommodate an alternative input source. We show direct application of this synthetic product in analysis of the performance of the MOD04 operational algorithm. We use biomass-burning case studies over Amazonia employed in a recent Working Group on Numerical Experimentation (WGNE)-sponsored study of aerosol impacts on numerical weather prediction (Freitas et al., 2015). We demonstrate that a known low bias in retrieved MODIS aerosol optical depth appears to be due to a disconnect between actual column relative humidity and the value assumed by the MODIS aerosol product.

Comparison of tropospheric NO2 from in situ aircraft measurements with near-real-time and standard product data from OMI

NASA Astrophysics Data System (ADS)

Bucsela, E. J.; Perring, A. E.; Cohen, R. C.; Boersma, K. F.; Celarier, E. A.; Gleason, J. F.; Wenig, M. O.; Bertram, T. H.; Wooldridge, P. J.; Dirksen, R.; Veefkind, J. P.

2008-08-01

We present an analysis of in situ NO2 measurements from aircraft experiments between summer 2004 and spring 2006. The data are from the INTEX-A, PAVE, and INTEX-B campaigns and constitute the most comprehensive set of tropospheric NO2 profiles to date. Profile shapes from INTEX-A and PAVE are found to be qualitatively similar to annual mean profiles from the GEOS-Chem model. Using profiles from the INTEX-B campaign, we perform error-weighted linear regressions to compare the Ozone Monitoring Instrument (OMI) tropospheric NO2 columns from the near-real-time product (NRT) and standard product (SP) with the integrated in situ columns. Results indicate that the OMI SP algorithm yields NO2 amounts lower than the in situ columns by a factor of 0.86 (±0.2) and that NO2 amounts from the NRT algorithm are higher than the in situ data by a factor of 1.68 (±0.6). The correlation between the satellite and in situ data is good (r = 0.83) for both algorithms. Using averaging kernels, the influence of the algorithm's a priori profiles on the satellite retrieval is explored. Results imply that air mass factors from the a priori profiles are on average slightly larger (˜10%) than those from the measured profiles, but the differences are not significant.

Glyoxal Vertical Column Retrievals from the GOME-2/METOP-A European Spaceborne Sensor and Comparisons with the IMAGESv2 CT Model

NASA Astrophysics Data System (ADS)

Lerot, C.; Stavrakou, T.; de Smedt, I.; Muller, J. J.; van Roozendael, M.

2010-12-01

Glyoxal is mostly formed in our atmosphere as an intermediate product in the oxidation of non-methane volatile organic compounds (NMVOC). To a lesser extent, it is also directly emitted from biomass burning events and from fossil- and bio-fuel combustion processes. Several studies have estimated its atmospheric lifetime to 2-3 hours, which makes of glyoxal a good indicator for short-lived NMVOC emissions. Glyoxal is also known to be a precursor for secondary organic aerosols and could help to reduce the gap between observations and models for organic aerosol abundances. The three absorption bands of glyoxal in the visible region allow applying the DOAS (Differential Optical Absorption Spectroscopy) technique to retrieve its vertical column densities from the nadir backscattered light measurements performed by the GOME-2 satellite sensor. This instrument has been launched in October 2006 on board of the METOP-A platform and is characterized by a spatial resolution of 80 km x 40 km and by a large scan-width (1920 km) leading to a global coverage reached in 1.5 day. The GOME-2 glyoxal retrieval algorithm developed at BIRA-IASB accounts for the liquid water absorption and provides geophysically sound column measurements not only over lands but also over oceanic regions where spectral interferences between glyoxal and liquid water have been shown to be significant. The a-priori glyoxal vertical distribution required for the slant to vertical column conversion is provided by the global chemical transport model IMAGESv2. The highest glyoxal vertical column densities are mainly observed in continental tropical regions, while the mid-latitude columns strongly depend on the season with maximum values during warm months. An anthropogenic signature is also observed in highly populated regions of Asia. Comparisons with glyoxal columns simulated with IMAGESv2 in different regions of the world generally point to a missing glyoxal source in current models. As already reported from previous analysis with the SCIAMACHY instrument, significant glyoxal columns are also observed over tropical oceans, which remains unexplained so far.

Characterizing the Vertical Distribution of Aerosols using Ground-based Multiwavelength Lidar Data

NASA Astrophysics Data System (ADS)

Ferrare, R. A.; Thorsen, T. J.; Clayton, M.; Mueller, D.; Chemyakin, E.; Burton, S. P.; Goldsmith, J.; Holz, R.; Kuehn, R.; Eloranta, E. W.; Marais, W.; Newsom, R. K.; Liu, X.; Sawamura, P.; Holben, B. N.; Hostetler, C. A.

2016-12-01

Observations of aerosol optical and microphysical properties are critical for developing and evaluating aerosol transport model parameterizations and assessing global aerosol-radiation impacts on climate. During the Combined HSRL And Raman lidar Measurement Study (CHARMS), we investigated the synergistic use of ground-based Raman lidar and High Spectral Resolution Lidar (HSRL) measurements to retrieve aerosol properties aloft. Continuous (24/7) operation of these co-located lidars during the ten-week CHARMS mission (mid-July through September 2015) allowed the acquisition of a unique, multiwavelength ground-based lidar dataset for studying aerosol properties above the Southern Great Plains (SGP) site. The ARM Raman lidar measured profiles of aerosol backscatter, extinction and depolarization at 355 nm as well as profiles of water vapor mixing ratio and temperature. The University of Wisconsin HSRL simultaneously measured profiles of aerosol backscatter, extinction and depolarization at 532 nm and aerosol backscatter at 1064 nm. Recent advances in both lidar retrieval theory and algorithm development demonstrate that vertically-resolved retrievals using such multiwavelength lidar measurements of aerosol backscatter and extinction can help constrain both the aerosol optical (e.g. complex refractive index, scattering, etc.) and microphysical properties (e.g. effective radius, concentrations) as well as provide qualitative aerosol classification. Based on this work, the NASA Langley Research Center (LaRC) HSRL group developed automated algorithms for classifying and retrieving aerosol optical and microphysical properties, demonstrated these retrievals using data from the unique NASA/LaRC airborne multiwavelength HSRL-2 system, and validated the results using coincident airborne in situ data. We apply these algorithms to the CHARMS multiwavelength (Raman+HSRL) lidar dataset to retrieve aerosol properties above the SGP site. We present some profiles of aerosol effective radius and concentration retrieved from the CHARMS data and compare column-average aerosol properties derived from the multiwavelength lidar aerosol retrievals to corresponding values retrieved from AERONET measurements.

Six years of total ozone column measurements from SCIAMACHY nadir observations

NASA Astrophysics Data System (ADS)

Lerot, C.; van Roozendael, M.; van Geffen, J.; van Gent, J.; Fayt, C.; Spurr, R.; Lichtenberg, G.; von Bargen, A.

2009-04-01

Total O3 columns have been retrieved from six years of SCIAMACHY nadir UV radiance measurements using SDOAS, an adaptation of the GDOAS algorithm previously developed at BIRA-IASB for the GOME instrument. GDOAS and SDOAS have been implemented by the German Aerospace Center (DLR) in the version 4 of the GOME Data Processor (GDP) and in version 3 of the SCIAMACHY Ground Processor (SGP), respectively. The processors are being run at the DLR processing centre on behalf of the European Space Agency (ESA). We first focus on the description of the SDOAS algorithm with particular attention to the impact of uncertainties on the reference O3 absorption cross-sections. Second, the resulting SCIAMACHY total ozone data set is globally evaluated through large-scale comparisons with results from GOME and OMI as well as with ground-based correlative measurements. The various total ozone data sets are found to agree within 2% on average. However, a negative trend of 0.2-0.4%/year has been identified in the SCIAMACHY O3 columns; this probably originates from instrumental degradation effects that have not yet been fully characterized.

Six years of total ozone column measurements from SCIAMACHY nadir observations

NASA Astrophysics Data System (ADS)

Lerot, C.; van Roozendael, M.; van Geffen, J.; van Gent, J.; Fayt, C.; Spurr, R.; Lichtenberg, G.; von Bargen, A.

2008-11-01

Total O3 columns have been retrieved from six years of SCIAMACHY nadir UV radiance measurements using SDOAS, an adaptation of the GDOAS algorithm previously developed at BIRA-IASB for the GOME instrument. GDOAS and SDOAS have been implemented by the German Aerospace Center (DLR) in the version 4 of the GOME Data Processor (GDP) and in version 3 of the SCIAMACHY Ground Processor (SGP), respectively. The processors are being run at the DLR processing centre on behalf of the European Space Agency (ESA). We first focus on the description of the SDOAS algorithm with particular attention to the impact of uncertainties on the reference O3 absorption cross-sections. Second, the resulting SCIAMACHY total ozone data set is globally evaluated through large-scale comparisons with results from GOME and OMI as well as with ground-based correlative measurements. The various total ozone data sets are found to agree within 2% on average. However, a negative trend of 0.2-0.4%/year has been identified in the SCIAMACHY O3 columns; this probably originates from instrumental degradation effects that have not yet been fully characterized.

Kalman filters for assimilating near-surface observations in the Richards equation - Part 2: A dual filter approach for simultaneous retrieval of states and parameters

NASA Astrophysics Data System (ADS)

Medina, H.; Romano, N.; Chirico, G. B.

2012-12-01

We present a dual Kalman Filter (KF) approach for retrieving states and parameters controlling soil water dynamics in a homogenous soil column by using near-surface state observations. The dual Kalman filter couples a standard KF algorithm for retrieving the states and an unscented KF algorithm for retrieving the parameters. We examine the performance of the dual Kalman Filter applied to two alternative state-space formulations of the Richards equation, respectively differentiated by the type of variable employed for representing the states: either the soil water content (θ) or the soil matric pressure head (h). We use a synthetic time-series series of true states and noise corrupted observations and a synthetic time-series of meteorological forcing. The performance analyses account for the effect of the input parameters, the observation depth and the assimilation frequency as well as the relationship between the retrieved states and the assimilated variables. We show that the identifiability of the parameters is strongly conditioned by several factors, such as the initial guess of the unknown parameters, the wet or dry range of the retrieved states, the boundary conditions, as well as the form (h-based or θ-based) of the state-space formulation. State identifiability is instead efficient even with a relatively coarse time-resolution of the assimilated observation. The accuracy of the retrieved states exhibits limited sensitivity to the observation depth and the assimilation frequency.

2007-2017: 10 years of IASI CO retrievals

NASA Astrophysics Data System (ADS)

George, M.; Clerbaux, C.; Hadji-Lazaro, J.; Pierre-Francois, C.; Hurtmans, D.; Edwards, D. P.; Worden, H. M.; Deeter, M. N.; Mao, D.; August, T.; Crapeau, M.

2017-12-01

Carbon monoxide (CO) is an important trace gas for understanding air quality and atmospheric composition. It is a good tracer of pollution plumes and atmospheric dynamics. IASI CO concentrations are retrieved from the radiance data using the Fast Operational Retrievals on Layers for IASI (FORLI) algorithm, based on the Optimal Estimation theory. The operational production is performed at EUMETSAT and the products are distributed in NRT via EUMETCast under the AC SAF auspices. We present here an analysis of 10 years of global distributions of CO. Improvements of the last FORLI-CO version (v20151001) will be shown. Updates in the auxiliary parameters (temperature, cloud information) have an impact on the retrieved product. Comparison with MOPITT CO data (v7T, record starting in 2000) was performed, both for partial and total columns. Harmonizing IASI and MOPITT CO products is challenging: a method using corrective factors (developed in the framework of the QA4ECV project) will be presented.

Diurnal, seasonal and long-term variations of global formaldehyde columns inferred from combined OMI and GOME-2 observations

NASA Astrophysics Data System (ADS)

De Smedt, I.; Stavrakou, T.; Hendrick, F.; Danckaert, T.; Vlemmix, T.; Pinardi, G.; Theys, N.; Lerot, C.; Gielen, C.; Vigouroux, C.; Hermans, C.; Fayt, C.; Veefkind, P.; Müller, J.-F.; Van Roozendael, M.

2015-11-01

We present the new version (v14) of the BIRA-IASB algorithm for the retrieval of formaldehyde (H2CO) columns from spaceborne UV-visible sensors. Applied to OMI measurements from Aura and to GOME-2 measurements from MetOp-A and MetOp-B, this algorithm is used to produce global distributions of H2CO representative of mid-morning and early afternoon conditions. Its main features include (1) a new iterative DOAS scheme involving three fitting intervals to better account for the O2-O2 absorption, (2) the use of earthshine radiances averaged in the equatorial Pacific as reference spectra, and (3) a destriping correction and background normalisation resolved in the across-swath position. For the air mass factor calculation, a priori vertical profiles calculated by the IMAGES chemistry transport model at 09:30 and 13:30 LT are used. Although the resulting GOME-2 and OMI H2CO vertical columns are found to be highly correlated, some systematic differences are observed. Afternoon columns are generally larger than morning ones, especially in mid-latitude regions. In contrast, over tropical rainforests, morning H2CO columns significantly exceed those observed in the afternoon. These differences are discussed in terms of the H2CO column variation between mid-morning and early afternoon, using ground-based MAX-DOAS measurements available from seven stations in Europe, China and Africa. Validation results confirm the capacity of the combined satellite measurements to resolve diurnal variations in H2CO columns. Furthermore, vertical profiles derived from MAX-DOAS measurements in the Beijing area and in Bujumbura are used for a more detailed validation exercise. In both regions, we find an agreement better than 15 % when MAX-DOAS profiles are used as a priori for the satellite retrievals. Finally, regional trends in H2CO columns are estimated for the 2004-2014 period using SCIAMACHY and GOME-2 data for morning conditions, and OMI for early afternoon conditions. Consistent features are observed, such as an increase of the columns in India and central-eastern China, and a decrease in the eastern US and Europe. We find that the higher horizontal resolution of OMI combined with a better sampling and a more favourable illumination at midday allow for more significant trend estimates, especially over Europe and North America. Importantly, in some parts of the Amazonian forest, we observe with both time series a significant downward trend in H2CO columns, spatially correlated with areas affected by deforestation.

Diurnal, seasonal and long-term variations of global formaldehyde columns inferred from combined OMI and GOME-2 observations

NASA Astrophysics Data System (ADS)

De Smedt, I.; Stavrakou, T.; Hendrick, F.; Danckaert, T.; Vlemmix, T.; Pinardi, G.; Theys, N.; Lerot, C.; Gielen, C.; Vigouroux, C.; Hermans, C.; Fayt, C.; Veefkind, P.; Müller, J.-F.; Van Roozendael, M.

2015-04-01

We present the new version (v14) of the BIRA-IASB algorithm for the retrieval of formaldehyde (H2CO) columns from spaceborne UV-Visible sensors. Applied to OMI measurements from Aura and to GOME-2 measurements from MetOp-A and B, this algorithm is used to produce global distributions of H2CO representative of mid-morning and early afternoon conditions. Its main features include (1) a new iterative DOAS scheme involving three fitting intervals to better account for the O2-O2 absorption, (2) the use of earthshine radiances averaged in the equatorial Pacific as reference spectra, (3) a destriping correction and background normalisation resolved in the along-swath position. For the air mass factor calculation, a priori vertical profiles calculated by the IMAGES chemistry transport model at 9.30 a.m. and 13.30 p.m. are used. Although the resulting GOME-2 and OMI H2CO vertical columns are found to be highly correlated, some systematic differences are observed. Afternoon columns are generally larger than morning ones, especially in mid-latitude regions. In contrast, over tropical rainforests, morning H2CO columns significantly exceed those observed in the afternoon. These differences are discussed in terms of the H2CO column variation between mid-morning and early afternoon, using ground-based MAX-DOAS measurements available from seven stations in Europe, China and Africa. Validation results confirm the capacity of the combined satellite measurements to resolve diurnal variations in H2CO columns. Furthermore, vertical profiles derived from MAX-DOAS measurements in the Beijing area and in Bujumbura are used for a more detailed validation exercise. In both regions, we find an agreement better than 15% when MAX-DOAS profiles are used as a priori for the satellite retrievals. Finally regional trends in H2CO columns are estimated for the 2004-2014 period using SCIAMACHY and GOME-2 data for morning conditions, and OMI for early afternoon conditions. Consistent features are observed such as an increase of the columns in India and Central-East China, and a decrease in Eastern US and Europe. We find that the higher horizontal resolution of OMI combined to a better sampling and a more favourable illumination at mid-day allow for more significant trend estimates, especially over Europe and North America. Importantly, in some parts of the Amazonian forest, we observe with both time series a significant downward trend in H2CO columns, spatially correlated with areas affected by deforestation.

Intercomparison of daytime stratospheric NO2 satellite retrievals and model simulations

NASA Astrophysics Data System (ADS)

Belmonte Rivas, M.; Veefkind, P.; Boersma, F.; Levelt, P.; Eskes, H.; Gille, J.

2014-07-01

This paper evaluates the agreement between stratospheric NO2 retrievals from infrared limb sounders (Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) and High Resolution Dynamics Limb Sounder (HIRDLS)) and solar UV/VIS backscatter sensors (Ozone Monitoring Instrument (OMI), Scanning Imaging Absorption Spectrometer for Atmospheric Cartography (SCIAMACHY) limb and nadir) over the 2005-2007 period and across the seasons. The observational agreement is contrasted with the representation of NO2 profiles in 3-D chemical transport models such as the Whole Atmosphere Community Climate Model (WACCM) and TM4. A conclusion central to this work is that the definition of a reference for stratospheric NO2 columns formed by consistent agreement among SCIAMACHY, MIPAS and HIRDLS limb records (all of which agree to within 0.25 × 1015 molecules cm-2 or better than 10%) allows us to draw attention to relative errors in other data sets, e.g., (1) WACCM overestimates NO2 densities in the extratropical lower stratosphere, particularly in the springtime and over northern latitudes by up to 35% relative to limb observations, and (2) there are remarkable discrepancies between stratospheric NO2 column estimates from limb and nadir techniques, with a characteristic seasonally and latitudinally dependent pattern. We find that SCIAMACHY nadir and OMI stratospheric columns show overall biases of -0.5 × 1015 molecules cm-2 (-20%) and +0.6 × 1015 molecules cm-2 (+20%) relative to limb observations, respectively. It is argued that additive biases in nadir stratospheric columns are not expected to affect tropospheric retrievals significantly, and that they can be attributed to errors in the total slant column density, related either to algorithmic or instrumental effects. In order to obtain accurate and long-term time series of stratospheric NO2, an effort towards the harmonization of currently used differential optical absorption spectroscopy (DOAS) approaches to nadir retrievals becomes essential, as well as their agreement to limb and ground-based observations, particularly now that limb techniques are giving way to nadir observations as the next generation of climate and air quality monitoring instruments pushes forth.

An Improved Algorithm for Retrieving Surface Downwelling Longwave Radiation from Satellite Measurements

NASA Technical Reports Server (NTRS)

Zhou, Yaping; Kratz, David P.; Wilber, Anne C.; Gupta, Shashi K.; Cess, Robert D.

2007-01-01

Zhou and Cess [2001] developed an algorithm for retrieving surface downwelling longwave radiation (SDLW) based upon detailed studies using radiative transfer model calculations and surface radiometric measurements. Their algorithm linked clear sky SDLW with surface upwelling longwave flux and column precipitable water vapor. For cloudy sky cases, they used cloud liquid water path as an additional parameter to account for the effects of clouds. Despite the simplicity of their algorithm, it performed very well for most geographical regions except for those regions where the atmospheric conditions near the surface tend to be extremely cold and dry. Systematic errors were also found for scenes that were covered with ice clouds. An improved version of the algorithm prevents the large errors in the SDLW at low water vapor amounts by taking into account that under such conditions the SDLW and water vapor amount are nearly linear in their relationship. The new algorithm also utilizes cloud fraction and cloud liquid and ice water paths available from the Cloud and the Earth's Radiant Energy System (CERES) single scanner footprint (SSF) product to separately compute the clear and cloudy portions of the fluxes. The new algorithm has been validated against surface measurements at 29 stations around the globe for Terra and Aqua satellites. The results show significant improvement over the original version. The revised Zhou-Cess algorithm is also slightly better or comparable to more sophisticated algorithms currently implemented in the CERES processing and will be incorporated as one of the CERES empirical surface radiation algorithms.

Total column water vapor estimation over land using radiometer data from SAC-D/Aquarius

NASA Astrophysics Data System (ADS)

Epeloa, Javier; Meza, Amalia

2018-02-01

The aim of this study is retrieving atmospheric total column water vapor (CWV) over land surfaces using a microwave radiometer (MWR) onboard the Scientific Argentine Satellite (SAC-D/Aquarius). To research this goal, a statistical algorithm is used for the purpose of filtering the study region according to the climate type. A log-linear relationship between the brightness temperatures of the MWR and CWV obtained from Global Navigation Satellite System (GNSS) measurements was used. In this statistical algorithm, the retrieved CWV is derived from the Argentinian radiometer's brightness temperature which works at 23.8 GHz and 36.5 GHz, and taking into account CWVs observed from GNSS stations belonging to a region sharing the same climate type. We support this idea, having found a systematic effect when applying the algorithm; it was generated for one region using the previously mentioned criteria, however, it should be applied to additional regions, especially those with other climate types. The region we analyzed is in the Southeastern United States of America, where the climate type is Cfa (Köppen - Geiger classification); this climate type includes moist subtropical mid-latitude climates, with hot, muggy summers and frequent thunderstorms. However, MWR only contains measurements taken from over ocean surfaces; therefore the determination of water vapor over land is an important contribution to extend the use of the SAC-D/Aquarius radiometer measurements beyond the ocean surface. The CWVs computed by our algorithm are compared against radiosonde CWV observations and show a bias of about -0.6 mm, a root mean square (rms) of about 6 mm and a correlation of 0.89.

Space-based near-infrared CO2 measurements: Testing the Orbiting Carbon Observatory retrieval algorithm and validation concept using SCIAMACHY observations over Park Falls, Wisconsin

NASA Astrophysics Data System (ADS)

BöSch, H.; Toon, G. C.; Sen, B.; Washenfelder, R. A.; Wennberg, P. O.; Buchwitz, M.; de Beek, R.; Burrows, J. P.; Crisp, D.; Christi, M.; Connor, B. J.; Natraj, V.; Yung, Y. L.

2006-12-01

Space-based measurements of reflected sunlight in the near-infrared (NIR) region promise to yield accurate and precise observations of the global distribution of atmospheric CO2. The Orbiting Carbon Observatory (OCO) is a future NASA mission, which will use this technique to measure the column-averaged dry air mole fraction of CO2 ? with the precision and accuracy needed to quantify CO2 sources and sinks on regional scales (˜1000 × 1000 km2) and to characterize their variability on seasonal timescales. Here, we have used the OCO retrieval algorithm to retrieve ? and surface pressure from space-based Scanning Imaging Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY) measurements and from coincident ground-based Fourier transform spectrometer (FTS) measurements of the O2 A band at 0.76 μm and the 1.58 μm CO2 band for Park Falls, Wisconsin. Even after accounting for a systematic error in our representation of the O2 absorption cross sections, we still obtained a positive bias between SCIAMACHY and FTS ? retrievals of ˜3.5%. Additionally, the retrieved surface pressures from SCIAMACHY systematically underestimate measurements of a calibrated pressure sensor at the FTS site. These findings lead us to speculate about inadequacies in the forward model of our retrieval algorithm. By assuming a 1% intensity offset in the O2 A band region for the SCIAMACHY ? retrieval, we significantly improved the spectral fit and achieved better consistency between SCIAMACHY and FTS ? retrievals. We compared the seasonal cycle of ? at Park Falls from SCIAMACHY and FTS retrievals with calculations of the Model of Atmospheric Transport and Chemistry/Carnegie-Ames-Stanford Approach (MATCH/CASA) and found a good qualitative agreement but with MATCH/CASA underestimating the measured seasonal amplitude. Furthermore, since SCIAMACHY observations are similar in viewing geometry and spectral range to those of OCO, this study represents an important test of the OCO retrieval algorithm and validation concept using NIR spectra measured from space. Finally, we argue that significant improvements in precision and accuracy could be obtained from a dedicated CO2 instrument such as OCO, which has much higher spectral and spatial resolutions than SCIAMACHY. These measurements would then provide critical data for improving our understanding of the carbon cycle and carbon sources and sinks.

Comparison of Ozone Retrievals from the Pandora Spectrometer System and Dobson Spectrophotometer in Boulder, Colorado

NASA Technical Reports Server (NTRS)

Herman, J.; Evans, R.; Cede, A.; Abuhassan, N.; Petropavlovskikh, I.; McConville, G.

2015-01-01

A comparison of retrieved total column ozone (TCO) amounts between the Pandora #34 spectrometer system and the Dobson #061 spectrophotometer from direct-sun observations was performed on the roof of the Boulder, Colorado, NOAA building. This paper, part of an ongoing study, covers a 1-year period starting on 17 December 2013. Both the standard Dobson and Pandora TCO retrievals required a correction, TCO(sub corr) = TCO (1 + C(T)), using a monthly varying effective ozone temperature, T(sub E), derived from a temperature and ozone profile climatology. The correction is used to remove a seasonal difference caused by using a fixed temperature in each retrieval algorithm. The respective corrections C(T(sub E)) are C(sub Pandora) = 0.00333(T(sub E) - 225) and C(sub Dobson) = -0.0013(T(sub E) - 226.7) per degree K. After the applied corrections removed most of the seasonal retrieval dependence on ozone temperature, TCO agreement between the instruments was within 1% for clear-sky conditions. For clear-sky observations, both co-located instruments tracked the day-to-day variation in total column ozone amounts with a correlation of r(exp 2) = 0.97 and an average offset of 1.1 +/- 5.8 DU. In addition, the Pandora TCO data showed 0.3% annual average agreement with satellite overpass data from AURA/OMI (Ozone Monitoring Instrument) and 1% annual average offset with Suomi-NPP/OMPS (Suomi National Polar-orbiting Partnership, the nadir viewing portion of the Ozone Mapper Profiler Suite).

Comparison of ozone retrievals from the Pandora spectrometer system and Dobson spectrophotometer in Boulder, Colorado

NASA Astrophysics Data System (ADS)

Herman, J.; Evans, R.; Cede, A.; Abuhassan, N.; Petropavlovskikh, I.; McConville, G.

2015-08-01

A comparison of retrieved total column ozone (TCO) amounts between the Pandora #34 spectrometer system and the Dobson #061 spectrophotometer from direct-sun observations was performed on the roof of the Boulder, Colorado, NOAA building. This paper, part of an ongoing study, covers a 1-year period starting on 17 December 2013. Both the standard Dobson and Pandora TCO retrievals required a correction, TCOcorr = TCO (1 + C(T)), using a monthly varying effective ozone temperature, TE, derived from a temperature and ozone profile climatology. The correction is used to remove a seasonal difference caused by using a fixed temperature in each retrieval algorithm. The respective corrections C(TE) are CPandora = 0.00333(TE-225) and CDobson = -0.0013(TE-226.7) per degree K. After the applied corrections removed most of the seasonal retrieval dependence on ozone temperature, TCO agreement between the instruments was within 1 % for clear-sky conditions. For clear-sky observations, both co-located instruments tracked the day-to-day variation in total column ozone amounts with a correlation of r2 = 0.97 and an average offset of 1.1 ± 5.8 DU. In addition, the Pandora TCO data showed 0.3 % annual average agreement with satellite overpass data from AURA/OMI (Ozone Monitoring Instrument) and 1 % annual average offset with Suomi-NPP/OMPS (Suomi National Polar-orbiting Partnership, the nadir viewing portion of the Ozone Mapper Profiler Suite).

Comparison of MAX-DOAS profiling algorithms during CINDI-2 - Part 1: aerosols

NASA Astrophysics Data System (ADS)

Friess, Udo; Hendrick, Francois; Tirpitz, Jan-Lukas; Apituley, Arnoud; van Roozendael, Michel; Kreher, Karin; Richter, Andreas; Wagner, Thomas

2017-04-01

The second Cabauw Intercomparison campaign for Nitrogen Dioxide measuring Instruments (CINDI-2) took place at the Cabauw Experimental Site for Atmospheric Research (CESAR; Utrecht area, The Netherlands) from 25 August until 7 October 2016. CINDI-2 was aiming at assessing the consistency of MAX-DOAS slant column density measurements of tropospheric species (NO2, HCHO, O3, and O4) relevant for the validation of future ESA atmospheric Sentinel missions, through coordinated operation of a large number of DOAS and MAXDOAS instruments from all over the world. An important objective of the campaign was to study the relationship between remote-sensing column and profile measurements of the above species and collocated reference ancillary observations. For this purpose, the CINDI-2 Profiling Task Team (CPTT) was created, involving 22 groups performing aerosol and trace gas vertical profile inversion using dedicated MAX-DOAS profiling algorithms, as well as the teams responsible for ancillary profile and surface concentration measurements (NO2 analysers, NO2 sondes, NO2 and Raman LIDARs, CAPS, Long-Path DOAS, sun photometer, nephelometer, etc). The main purpose of the CPTT is to assess the consistency of the different profiling tools for retrieving aerosol extinction and trace gas vertical profiles through comparison exercises using commonly defined settings and to validate the retrievals with correlative observations. In this presentation, we give an overview of the MAX-DOAS vertical profile comparison results, focusing on the retrieval of aerosol extinction profiles, with the trace gas retrievals being presented in a companion abstract led by F. Hendrick. The performance of the different algorithms is investigated with respect to the variable visibility and cloud conditions encountered during the campaign. The consistency between optimal-estimation-based and parameterized profiling tools is also evaluated for these different conditions, together with the level of agreement with available ancillary aerosol observations, including sun photometer, nephelometer and LIDAR. This comparison study will be put in the perspective of the development of a centralized MAX-DOAS processing system within the framework of the ESA Fiducial Reference Measurements (FRM) project.

MARs Color Imager (MARCI) Daily Global Ozone Column Mapping from the Mars Reconnaissance Orbiter (MRO): A Survey of 2006-2010 Results

NASA Astrophysics Data System (ADS)

Clancy, R. T.; Wolff, M. J.; Malin, M. C.; Cantor, B. A.

2010-12-01

MARCI UV band imaging photometry within (260nm) and outside (320nm) the Hartley ozone band absorption supports daily global mapping of Mars ozone column abundances. Key retrieval issues include accurate UV radiometric calibrations, detailed specifications of surface and atmospheric background reflectance (surface albedo, atmospheric Raleigh and dust scattering/absorption), and simultaneous cloud retrievals. The implementation of accurate radiative transfer (RT) treatments of these processes has been accomplished (Wolff et al., 2010) such that daily global mapping retrievals for Mars ozone columns have been completed for the 2006-2010 period of MARCI global imaging. Ozone retrievals are most accurate for high column abundances associated with mid-to-high latitude regions during fall, winter, and spring seasons. We present a survey of these MARCI ozone column retrievals versus season, latitude, longitude, and year.

Fuzzy Classification of Ocean Color Satellite Data for Bio-optical Algorithm Constituent Retrievals

NASA Technical Reports Server (NTRS)

Campbell, Janet W.

1998-01-01

The ocean has been traditionally viewed as a 2 class system. Morel and Prieur (1977) classified ocean water according to the dominant absorbent particle suspended in the water column. Case 1 is described as having a high concentration of phytoplankton (and detritus) relative to other particles. Conversely, case 2 is described as having inorganic particles such as suspended sediments in high concentrations. Little work has gone into the problem of mixing bio-optical models for these different water types. An approach is put forth here to blend bio-optical algorithms based on a fuzzy classification scheme. This scheme involves two procedures. First, a clustering procedure identifies classes and builds class statistics from in-situ optical measurements. Next, a classification procedure assigns satellite pixels partial memberships to these classes based on their ocean color reflectance signature. These membership assignments can be used as the basis for a weighting retrievals from class-specific bio-optical algorithms. This technique is demonstrated with in-situ optical measurements and an image from the SeaWiFS ocean color satellite.

An Improved Algorithm for Retrieving Surface Downwelling Longwave Radiation from Satellite Measurements

NASA Technical Reports Server (NTRS)

Zhou, Yaping; Kratz, David P.; Wilber, Anne C.; Gupta, Shashi K.; Cess, Robert D.

2006-01-01

Retrieving surface longwave radiation from space has been a difficult task since the surface downwelling longwave radiation (SDLW) are integrations from radiation emitted by the entire atmosphere, while those emitted from the upper atmosphere are absorbed before reaching the surface. It is particularly problematic when thick clouds are present since thick clouds will virtually block all the longwave radiation from above, while satellites observe atmosphere emissions mostly from above the clouds. Zhou and Cess developed an algorithm for retrieving SDLW based upon detailed studies using radiative transfer model calculations and surface radiometric measurements. Their algorithm linked clear sky SDLW with surface upwelling longwave flux and column precipitable water vapor. For cloudy sky cases, they used cloud liquid water path as an additional parameter to account for the effects of clouds. Despite the simplicity of their algorithm, it performed very well for most geographical regions except for those regions where the atmospheric conditions near the surface tend to be extremely cold and dry. Systematic errors were also found for areas that were covered with ice clouds. An improved version of the algorithm was developed that prevents the large errors in the SDLW at low water vapor amounts. The new algorithm also utilizes cloud fraction and cloud liquid and ice water paths measured from the Cloud and the Earth's Radiant Energy System (CERES) satellites to separately compute the clear and cloudy portions of the fluxes. The new algorithm has been validated against surface measurements at 29 stations around the globe for the Terra and Aqua satellites. The results show significant improvement over the original version. The revised Zhou-Cess algorithm is also slightly better or comparable to more sophisticated algorithms currently implemented in the CERES processing. It will be incorporated in the CERES project as one of the empirical surface radiation algorithms.

Trace gas retrievals from Airborne Compact Atmospheric Mapper (ACAM) observations during the 2011 DISCOVER-AQ flight campaign

NASA Astrophysics Data System (ADS)

Liu, X.; Kowalewski, M. G.; Janz, S. J.; Bhartia, P. K.; Chance, K.; Krotkov, N. A.; Pickering, K. E.; Crawford, J. H.

2011-12-01

The DISCOVER-AQ (Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality) mission has just finished its first flight campaign in the Baltimore-Washington D.C. area in July 2011. The ACAM, flown on board the NASA UC-12 aircraft, includes two spectrographs covering the spectral region 304-900 nm and a high-definition video camera, and is expected to provide column measurements of several important air quality trace gases and aerosols for the DISCOVER-AQ mission. The quick look results for NO2 have been shown to very useful in capturing the strong spatiotemporal variability of NO2. Preliminary fitting of UV/Visible spectra has shown that ACAM measurements have adequate signal to noise ratio to measure the trace gases O2, NO2, HCHO, and maybe SO2 and CHOCHO, at individual pixel resolution, although a great deal of effort is needed to improve the instrument calibration and derive proper reference spectrum for retrieving absolute trace gas column densities. In this study, we present analysis of ACAM instrument calibration including slit function, wavelength registration, and radiometric calibration for both nadir-viewing and zenith-sky measurements. Based on this analysis, an irradiance reference spectrum at ACAM resolution will be derived from a high-resolution reference spectrum with additional correction to account for instrument calibration. Using the derived reference spectrum and/or the measured zenith sky measurements, we will perform non-linear least squares fitting to investigate the retrievals of slant column densities of these trace gases from ACAM measurements, and also use an optimal estimation based algorithm including full radiative transfer calculations to derive the vertical column densities of these trace gases. The initial results will be compared with available in-situ and ground-based measurements taken during the DISCOVER-AQ campaign.

Retrieval of the spectral diffuse attenuation coefficient Kd(λ) in open and coastal ocean waters using a neural network inversion

NASA Astrophysics Data System (ADS)

Jamet, C.; Loisel, H.; Dessailly, D.

2012-10-01

The diffuse attenuation coefficient, Kd(λ) is a fundamental radiometric parameter that is used to assess the light availability in the water column. A neural network approach is developed to assess Kd(λ) at any visible wavelengths from the remote sensing reflectances as measured by the SeaWiFS satellite sensor. The neural network (NN) inversion is trained using a combination of simulated and in-situ data sets covering a broad range ofKd(λ), between 0.0073 m-1 at 412 nm and 12.41 m-1at 510 nm. The performance of the retrieval is evaluated against two data sets, one consisting of mainly synthetic data while the other one contains in-situ data only and is compared to those obtained with previous published empirical (NASA, Morel and Maritorena (2001) and Zhang and Fell (2007)) and semi-analytical (Lee et al., 2005b) algorithms. On the in-situ data set from the COASTLOOC campaign, the retrieval accuracy of the present algorithm is quite similar to published algorithms for oligotrophic and mesotrophic ocean waters. But for Kd(490) > 0.25 m-1, the NN approach allows to retrieve Kd(490) with a much better accuracy than the four other methods. The results are consistent when compared with other SeaWiFS wavelengths. This new inversion is as suitable in the open ocean waters as in the turbid waters. The work here is straightforwardly applicable to the MERIS sensor and with few changes to the MODIS-AQUA sensor. The algorithm in matlab and C code is provided as auxiliary material.

Nitrogen Dioxide Observations from the Geostationary Trace Gas and Aerosol Sensor Optimization (GeoTaso) Airborne Instrument: Retrieval Algorithm and Measurements During DISCOVER-AQ Texas 2013

NASA Technical Reports Server (NTRS)

Nowlan, Caroline R.; Liu, Xiong; Leitch, James W.; Chance, Kelly; Abad, Gonzalo Gonzalez; Liu, Xiaojun; Zoogman, Peter; Cole, Joshua; Delker, Thomas; Good, William;

Aerosol retrieval experiments in the ESA Aerosol_cci project

NASA Astrophysics Data System (ADS)

Holzer-Popp, T.; de Leeuw, G.; Martynenko, D.; Klüser, L.; Bevan, S.; Davies, W.; Ducos, F.; Deuzé, J. L.; Graigner, R. G.; Heckel, A.; von Hoyningen-Hüne, W.; Kolmonen, P.; Litvinov, P.; North, P.; Poulsen, C. A.; Ramon, D.; Siddans, R.; Sogacheva, L.; Tanre, D.; Thomas, G. E.; Vountas, M.; Descloitres, J.; Griesfeller, J.; Kinne, S.; Schulz, M.; Pinnock, S.

2013-03-01

Within the ESA Climate Change Initiative (CCI) project Aerosol_cci (2010-2013) algorithms for the production of long-term total column aerosol optical depth (AOD) datasets from European Earth Observation sensors are developed. Starting with eight existing pre-cursor algorithms three analysis steps are conducted to improve and qualify the algorithms: (1) a series of experiments applied to one month of global data to understand several major sensitivities to assumptions needed due to the ill-posed nature of the underlying inversion problem, (2) a round robin exercise of "best" versions of each of these algorithms (defined using the step 1 outcome) applied to four months of global data to identify mature algorithms, and (3) a comprehensive validation exercise applied to one complete year of global data produced by the algorithms selected as mature based on the round robin exercise. The algorithms tested included four using AATSR, three using MERIS and one using PARASOL. This paper summarizes the first step. Three experiments were conducted to assess the potential impact of major assumptions in the various aerosol retrieval algorithms. In the first experiment a common set of four aerosol components was used to provide all algorithms with the same assumptions. The second experiment introduced an aerosol property climatology, derived from a combination of model and sun photometer observations, as a priori information in the retrievals on the occurrence of the common aerosol components and their mixing ratios. The third experiment assessed the impact of using a common nadir cloud mask for AATSR and MERIS algorithms in order to characterize the sensitivity to remaining cloud contamination in the retrievals against the baseline dataset versions. The impact of the algorithm changes was assessed for one month (September 2008) of data qualitatively by visible analysis of monthly mean AOD maps and quantitatively by comparing global daily gridded satellite data against daily average AERONET sun photometer observations for the different versions of each algorithm. The analysis allowed an assessment of sensitivities of all algorithms which helped define the best algorithm version for the subsequent round robin exercise; all algorithms (except for MERIS) showed some, in parts significant, improvement. In particular, using common aerosol components and partly also a priori aerosol type climatology is beneficial. On the other hand the use of an AATSR-based common cloud mask meant a clear improvement (though with significant reduction of coverage) for the MERIS standard product, but not for the algorithms using AATSR.

Overview of SCIAMACHY validation: 2002-2004

NASA Astrophysics Data System (ADS)

Piters, A. J. M.; Bramstedt, K.; Lambert, J.-C.; Kirchhoff, B.

2006-01-01

SCIAMACHY, on board Envisat, has been in operation now for almost three years. This UV/visible/NIR spectrometer measures the solar irradiance, the earthshine radiance scattered at nadir and from the limb, and the attenuation of solar radiation by the atmosphere during sunrise and sunset, from 240 to 2380 nm and at moderate spectral resolution. Vertical columns and profiles of a variety of atmospheric constituents are inferred from the SCIAMACHY radiometric measurements by dedicated retrieval algorithms. With the support of ESA and several international partners, a methodical SCIAMACHY validation programme has been developed jointly by Germany, the Netherlands and Belgium (the three instrument providing countries) to face complex requirements in terms of measured species, altitude range, spatial and temporal scales, geophysical states and intended scientific applications. This summary paper describes the approach adopted to address those requirements.

Since provisional releases of limited data sets in summer 2002, operational SCIAMACHY processors established at DLR on behalf of ESA were upgraded regularly and some data products - level-1b spectra, level-2 O3, NO2, BrO and clouds data - have improved significantly. Validation results summarised in this paper and also reported in this special issue conclude that for limited periods and geographical domains they can already be used for atmospheric research. Nevertheless, current processor versions still experience known limitations that hamper scientific usability in other periods and domains. Free from the constraints of operational processing, seven scientific institutes (BIRA-IASB, IFE/IUP-Bremen, IUP-Heidelberg, KNMI, MPI, SAO and SRON) have developed their own retrieval algorithms and generated SCIAMACHY data products, together addressing nearly all targeted constituents. Most of the UV-visible data products - O3, NO2, SO2, H2O total columns; BrO, OClO slant columns; O3, NO2, BrO profiles - already have acceptable, if not excellent, quality. Provisional near-infrared column products - CO, CH4, N2O and CO2 - have already demonstrated their potential for a variety of applications. Cloud and aerosol parameters are retrieved, suffering from calibration with the exception of cloud cover. In any case, scientific users are advised to read carefully validation reports before using the data. It is required and anticipated that SCIAMACHY validation will continue throughout instrument lifetime and beyond and will accompany regular processor upgrades.

Polarimetric Signatures of Initiating Convection During MC3E

NASA Technical Reports Server (NTRS)

Emory, Amber

2012-01-01

One of the goals of the Mid-latitude Continental Convective Clouds Experiment (MC3E) field campaign was to provide constraints for space-based rainfall retrieval algorithms over land. This study used datasets collected during the 2011 field campaign to combine radiometer and ground-based radar polarimetric retrievals in order to better understand hydrometeor type, habit and distribution for initiating continental convection. Cross-track and conically scanning nadir views from the Conical Scanning Millimeter-wave Imaging Radiometer (CoSMIR) were compared with ground-based polarimetric radar retrievals along the ER-2 flight track. Polarimetric signatures for both airborne radiometers and ground-based radars were well co-located with deep convection to relate radiometric signatures with low-level polarimetric radar data for hydrometeor identification and diameter estimation. For the time period of study, Z(sub DR) values indicated no presence of hail at the surface. However, the Z(sub DR) column extended well above the melting level into the mixed phase region, suggesting a possible source of frozen drop embryos for the future formation of hail. The results shown from this study contribute ground truth datasets for GPM PR algorithm development for convective events, which is an improvement upon previous stratiform precipitation centered framework.

Kalman filters for assimilating near-surface observations into the Richards equation - Part 1: Retrieving state profiles with linear and nonlinear numerical schemes

NASA Astrophysics Data System (ADS)

Chirico, G. B.; Medina, H.; Romano, N.

2014-07-01

This paper examines the potential of different algorithms, based on the Kalman filtering approach, for assimilating near-surface observations into a one-dimensional Richards equation governing soil water flow in soil. Our specific objectives are: (i) to compare the efficiency of different Kalman filter algorithms in retrieving matric pressure head profiles when they are implemented with different numerical schemes of the Richards equation; (ii) to evaluate the performance of these algorithms when nonlinearities arise from the nonlinearity of the observation equation, i.e. when surface soil water content observations are assimilated to retrieve matric pressure head values. The study is based on a synthetic simulation of an evaporation process from a homogeneous soil column. Our first objective is achieved by implementing a Standard Kalman Filter (SKF) algorithm with both an explicit finite difference scheme (EX) and a Crank-Nicolson (CN) linear finite difference scheme of the Richards equation. The Unscented (UKF) and Ensemble Kalman Filters (EnKF) are applied to handle the nonlinearity of a backward Euler finite difference scheme. To accomplish the second objective, an analogous framework is applied, with the exception of replacing SKF with the Extended Kalman Filter (EKF) in combination with a CN numerical scheme, so as to handle the nonlinearity of the observation equation. While the EX scheme is computationally too inefficient to be implemented in an operational assimilation scheme, the retrieval algorithm implemented with a CN scheme is found to be computationally more feasible and accurate than those implemented with the backward Euler scheme, at least for the examined one-dimensional problem. The UKF appears to be as feasible as the EnKF when one has to handle nonlinear numerical schemes or additional nonlinearities arising from the observation equation, at least for systems of small dimensionality as the one examined in this study.

Retrievals of atmospheric columnar carbon dioxide and methane from GOSAT observations with photon path-length probability density function (PPDF) method

NASA Astrophysics Data System (ADS)

Bril, A.; Oshchepkov, S.; Yokota, T.; Yoshida, Y.; Morino, I.; Uchino, O.; Belikov, D. A.; Maksyutov, S. S.

2014-12-01

We retrieved the column-averaged dry air mole fraction of atmospheric carbon dioxide (XCO2) and methane (XCH4) from the radiance spectra measured by Greenhouse gases Observing SATellite (GOSAT) for 48 months of the satellite operation from June 2009. Recent version of the Photon path-length Probability Density Function (PPDF)-based algorithm was used to estimate XCO2 and optical path modifications in terms of PPDF parameters. We also present results of numerical simulations for over-land observations and "sharp edge" tests for sun-glint mode to discuss the algorithm accuracy under conditions of strong optical path modification. For the methane abundance retrieved from 1.67-µm-absorption band we applied optical path correction based on PPDF parameters from 1.6-µm carbon dioxide (CO2) absorption band. Similarly to CO2-proxy technique, this correction assumes identical light path modifications in 1.67-µm and 1.6-µm bands. However, proxy approach needs pre-defined XCO2 values to compute XCH4, whilst the PPDF-based approach does not use prior assumptions on CO2 concentrations.Post-processing data correction for XCO2 and XCH4 over land observations was performed using regression matrix based on multivariate analysis of variance (MANOVA). The MANOVA statistics was applied to the GOSAT retrievals using reference collocated measurements of Total Carbon Column Observing Network (TCCON). The regression matrix was constructed using the parameters that were found to correlate with GOSAT-TCCON discrepancies: PPDF parameters α and ρ, that are mainly responsible for shortening and lengthening of the optical path due to atmospheric light scattering; solar and satellite zenith angles; surface pressure; surface albedo in three GOSAT short wave infrared (SWIR) bands. Application of the post-correction generally improves statistical characteristics of the GOSAT-TCCON correlation diagrams for individual stations as well as for aggregated data.In addition to the analysis of the observations over 12 TCCON stations we estimated temporal and spatial trends (interannual XCO2 and XCH4 variations, seasonal cycles, latitudinal gradients) and compared them with modeled results as well as with similar estimates from other GOSAT retrievals.

Global Precipitation Measurement (GPM) Ground Validation (GV) Science Implementation Plan

NASA Technical Reports Server (NTRS)

Petersen, Walter A.; Hou, Arthur Y.

2008-01-01

For pre-launch algorithm development and post-launch product evaluation Global Precipitation Measurement (GPM) Ground Validation (GV) goes beyond direct comparisons of surface rain rates between ground and satellite measurements to provide the means for improving retrieval algorithms and model applications.Three approaches to GPM GV include direct statistical validation (at the surface), precipitation physics validation (in a vertical columns), and integrated science validation (4-dimensional). These three approaches support five themes: core satellite error characterization; constellation satellites validation; development of physical models of snow, cloud water, and mixed phase; development of cloud-resolving model (CRM) and land-surface models to bridge observations and algorithms; and, development of coupled CRM-land surface modeling for basin-scale water budget studies and natural hazard prediction. This presentation describes the implementation of these approaches.

Aerosols correction of the OMI tropospheric NO2 retrievals over cloud-free scenes: Different methodologies based on the O2-O2 477 nm band

NASA Astrophysics Data System (ADS)

Chimot, Julien; Vlemmix, Tim; Veefkind, Pepijn; Levelt, Pieternel

2016-04-01

Numerous studies have drawn attention to the complexities related to the retrievals of tropospheric NO2 columns derived from satellite UltraViolet-Visible (UV-Vis) measurements in the presence of aerosols. Correction for aerosol effects will remain a challenge for the next generation of air quality satellite instruments such as TROPOMI on Sentinel-5 Precursor, Sentinel-4 and Sentinel-5. The Ozone Monitoring Instrument (OMI) instrument has provided daily global measurements of tropospheric NO2 for more than a decade. However, aerosols are not explicitly taken into account in the current operational OMI tropospheric NO2 retrieval chain (DOMINO v2 [Boersma et al., 2011]). Our study analyses 2 approaches for an operational aerosol correction, based on the use of the O2-O2 477 nm band. The 1st approach is the cloud-model based aerosol correction, also named "implicit aerosol correction", and already used in the operational chain. The OMI O2-O2 cloud retrieval algorithm, based on the Differential Optical Absorption Spectroscopy (DOAS) approach, is applied both to cloudy and to cloud-free scenes with aerosols present. Perturbation of the OMI cloud retrievals over scenes dominated by aerosols has been observed in recent studies led by [Castellanos et al., 2015; Lin et al., 2015; Lin et al., 2014]. We investigated the causes of these perturbations by: (1) confronting the OMI tropospheric NO2, clouds and MODIS AQUA aerosol products; (2) characterizing the key drivers of the aerosol net effects, compared to a signal from clouds, in the UV-Vis spectra. This study has focused on large industrialised areas like East-China, over cloud-free scenes. One of the key findings is the limitation due to the coarse sampling of the employed cloud Look-Up Table (LUT) to convert the results of the applied DOAS fit into effective cloud fraction and pressure. This leads to an underestimation of tropospheric NO2 amount in cases of particles located at elevated altitude. A higher sampling of the variation of O2-O2 SCD and continuum reflectance as a function of effective cloud parameters in case of low effective cloud fraction values is requested for applying an aerosol correction. The updates of the OMI O2-O2 cloud algorithm, based on the scheduled new OMI cloud LUT, will be presented in terms of impacts of the effective cloud retrievals and reduced biases of tropospheric NO2 columns over cloud-free scenes dominated by aerosols in China. A 2nd approach is investigated, assuming a more explicit aerosol correction. Previous analyses pointed out that the O2-O2 spectra contain information about aerosols: the continuum reflectance is primarily constrained by the Aerosol Optical thickness (AOT) while the O2-O2 Slant Column Density (SCD) mostly results from the combination of AOT and aerosols altitude. We have developed a first prototype algorithm allowing to retrieve information about AOT and aerosol altitude from the O2-O2 DOAS fit. We will discuss preliminary sensitivities and the potential accuracy of the associated explicit aerosol correction, without the use of effective cloud parameters.

Nadir Ozone Profile Retrieval from SCIAMACHY: application to the Antarctic Ozone Hole

NASA Astrophysics Data System (ADS)

Shah, Sweta; Piet, Stammes; Tuinder, Olaf N. E.; de Laat, Jos

2017-04-01

We present new nadir ozone profile retrievals using SCIAMACHY UV reflectance spectra for the mission period of the Envisat satellite. We have used the most recent Level-1 data version (v8 with degradation correction included) in the UV range (265-330 nm) and have used the OPERA optimal estimation algorithm (van Peet et al., AMT, 2014) developed in KNMI. We first show the comparison of the retrieved satellite profiles to co-located ozone sonde profiles in order to evaluate the accuracy of the retrieved ozone profile dataset. Based on these results, we have further processed the SCIAMCHY nadir dataset, specifically all the southern hemisphere pixels south of 45 degrees latitude for the months of August-November for the complete years 2003-2011. We show the monthly mean profiles, time-series of daily averages and minima of the retrieved stratospheric columns, and finally the ozone profile trend over the years 2003-2011. We also show the comparison of our results with the literature and hence the consistency of this new SCIAMACHY dataset.

Aerosol Retrievals from ARM SGP MFRSR Data

DOE Data Explorer

Alexandrov, Mikhail

2008-01-15

The Multi-Filter Rotating Shadowband Radiometer (MFRSR) makes precise simultaneous measurements of the solar direct normal and diffuse horizontal irradiances at six wavelengths (nominally 415, 500, 615, 673, 870, and 940 nm) at short intervals (20 sec for ARM instruments) throughout the day. Time series of spectral optical depth are derived from these measurements. Besides water vapor at 940 nm, the other gaseous absorbers within the MFRSR channels are NO2 (at 415, 500, and 615 nm) and ozone (at 500, 615, and 670 nm). Aerosols and Rayleigh scattering contribute atmospheric extinction in all MFRSR channels. Our recently updated MFRSR data analysis algorithm allows us to partition the spectral aerosol optical depth into fine and coarse modes and to retrieve the fine mode effective radius. In this approach we rely on climatological amounts of NO2 from SCIAMACHY satellite retrievals and use daily ozone columns from TOMS.

Space-Based Near-Infrared CO2 Measurements: Testing the Orbiting Carbon Observatory Retrieval Algorithm and Validation Concept Using SCIAMACHY Observations over Park Falls, Wisconsin

NASA Technical Reports Server (NTRS)

Bosch, H.; Toon, G. C.; Sen, B.; Washenfelder, R. A.; Wennberg, P. O.; Buchwitz, M.; deBeek, R.; Burrows, J. P.; Crisp, D.; Christi, M.;

Atmospheric moisture and cloud structure determined from SSM/I and global gridpoint analyses. [Special Sensor Microwave Imager

NASA Technical Reports Server (NTRS)

Robertson, Franklin R.; Huang, Huo-Jin

1989-01-01

Data from the Special Sensor Microwave Imager/I on the DMSP satellite are used to study atmospheric moisture and cloud structure. Column-integrated water vapor and total liquid water retrievals are obtained using an algorithm based on a radiative model for brightness temperature (Wentz, 1983). The results from analyzing microwave and IR measurements are combined with independent global gridpoint analyses to study the distribution and structure of atmospheric moisture over oceanic regions.

New Developments in the SCIAMACHY Level 2 Ground Processor Towards Version 7

NASA Astrophysics Data System (ADS)

Meringer, Markus; Noël, Stefan; Lichtenberg, Günter; Lerot, Christophe; Theys, Nicolas; Fehr, Thorsten; Dehn, Angelika; Liebing, Patricia; Gretschany, Sergei

2016-07-01

SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric ChartographY) aboard ESA's environmental satellite ENVISAT observed the Earth's atmosphere in limb, nadir, and solar/lunar occultation geometries covering the UV-Visible to NIR spectral range. It is a joint project of Germany, the Netherlands and Belgium and was launched in February 2002. SCIAMACHY doubled its originally planned in-orbit lifetime of five years before the communication to ENVISAT was severed in April 2012, and the mission entered its post-operational phase. In order to preserve the best quality of the outstanding data recorded by SCIAMACHY, data processors are still being updated. This presentation will highlight three new developments that are currently being incorporated into the forthcoming version 7 of ESA's operational level 2 processor: 1. Tropospheric BrO, a new retrieval based on the scientific algorithm of (Theys et al., 2011). This algorithm had originally been developed for the GOME-2 sensor and was later adapted for SCIAMACHY. The main principle of the new algorithm is to split BrO total columns, which are already an operational product, into stratospheric VCD_{strat} and tropospheric VCD_{trop} fractions. BrO VCD_{strat} is determined from a climatological approach, driven by SCIAMACHY O_3 and NO_2 observations. Tropospheric vertical column densities are then determined as difference VCD_{trop}=VCD_{total}-VCD_{strat}. 2. Improved cloud flagging using limb measurements (Liebing, 2015). Limb cloud flags are already part of the SCIAMACHY L2 product. They are currently calculated employing the scientific algorithm developed by (Eichmann et al., 2015). Clouds are categorized into four types: water, ice, polar stratospheric and noctilucent clouds. High atmospheric aerosol loadings, however, often lead to spurious cloud flags, when aerosols had been misidentified as clouds. The new algorithm will better discriminate between aerosol and clouds. It will also have a higher sensitivity w.r.t. thin clouds. 3. A new, future-proof file format for the level 2 product based on NetCDF. The data format will be aligned and harmonized with other missions, particularly GOME and Sentinels. The final concept for the new format is still under discussion within the SCIAMACHY Quality Working Group. References: K.-U. Eichmann et al.: Global cloud top height retrieval using SCIAMACHY limb spectra: model studies and first results, Atmos. Meas. Tech. Discuss., 8, 8295-8352, 2015. P. Liebing: New Limb Cloud Detection Algorithm Theoretical Basis Document, 2016. N. Theys et al.: Global observations of tropospheric BrO columns using GOME-2 satellite data, Atmos. Chem. Phys., 11, 1791-1811, 2011.

Version 2 of the IASI NH3 neural network retrieval algorithm: near-real-time and reanalysed datasets

NASA Astrophysics Data System (ADS)

Van Damme, Martin; Whitburn, Simon; Clarisse, Lieven; Clerbaux, Cathy; Hurtmans, Daniel; Coheur, Pierre-François

2017-12-01

Recently, Whitburn et al.(2016) presented a neural-network-based algorithm for retrieving atmospheric ammonia (NH3) columns from Infrared Atmospheric Sounding Interferometer (IASI) satellite observations. In the past year, several improvements have been introduced, and the resulting new baseline version, Artificial Neural Network for IASI (ANNI)-NH3-v2.1, is documented here. One of the main changes to the algorithm is that separate neural networks were trained for land and sea observations, resulting in a better training performance for both groups. By reducing and transforming the input parameter space, performance is now also better for observations associated with favourable sounding conditions (i.e. enhanced thermal contrasts). Other changes relate to the introduction of a bias correction over land and sea and the treatment of the satellite zenith angle. In addition to these algorithmic changes, new recommendations for post-filtering the data and for averaging data in time or space are formulated. We also introduce a second dataset (ANNI-NH3-v2.1R-I) which relies on ERA-Interim ECMWF meteorological input data, along with surface temperature retrieved from a dedicated network, rather than the operationally provided Eumetsat IASI Level 2 (L2) data used for the standard near-real-time version. The need for such a dataset emerged after a series of sharp discontinuities were identified in the NH3 time series, which could be traced back to incremental changes in the IASI L2 algorithms for temperature and clouds. The reanalysed dataset is coherent in time and can therefore be used to study trends. Furthermore, both datasets agree reasonably well in the mean on recent data, after the date when the IASI meteorological L2 version 6 became operational (30 September 2014).

Global observations of glyoxal columns from OMI/Aura and GOME-2/Metop-A sensors and comparison with multi-year simulations by the IMAGES model

NASA Astrophysics Data System (ADS)

Lerot, Christophe; Stavrakou, Trissevgeni; Hendrick, François; De Smedt, Isabelle; Müller, Jean-François; Volkamer, Rainer; Van Roozendael, Michel

2015-04-01

Volatile organic compounds (VOCs) originating from both natural and human activities play a key role in air quality. Information on their atmospheric concentrations can be derived using remote sensing techniques for a limited number of species, including formaldehyde (HCHO) and glyoxal (CHOCHO). The latter is mostly produced in the atmosphere as an intermediate product in the oxidation of other non-methane VOCs. It is also directly emitted from fire events and combustion processes. Owing to its short lifetime, elevated glyoxal concentrations are observed near emission sources. Measurements of atmospheric glyoxal concentrations therefore provide quantitative information on the different types of VOC emission and can help to better assess the quality of current inventories. In addition, glyoxal is also known to significantly contribute to the total budget of secondary organic aerosols. Global observations of glyoxal columns have been realized from different space-borne spectrometers using the well-known DOAS retrieval technique. In the past, we developed an algorithm to retrieve glyoxal columns from spectra measured by the GOME-2 instrument aboard METOP-A (Lerot et al., 2010). Specificities of this algorithm were an original two-step approach in the DOAS fit to minimize the impact of spectral interferences with the liquid water absorption as well as the use of a priori information from the Chemical Transport Model IMAGES in the air mass factor calculation. In this work, we present the adaptation of this algorithm to the OMI sensor on the AURA platform. The time series of glyoxal columns derived from OMI and GOME-2 are compared in different parts of the world and a high level of consistency is found. The OMI glyoxal data product is found to be very stable over the entire duration of the mission, in contrast to the GOME-2 product which is affected by instrumental degradation. We present validation results using several years of MAX-DOAS glyoxal measurements successively performed in Beijing and Xianghe, China, since 2008. Also, comparisons of the satellite data sets with simulations by the IMAGES chemistry transport model show generally good correlation. Sensitivity tests on the VOC emissions used in the model will also be discussed. Lerot, C., Stavrakou, T., De Smedt, I., Müller, J.-F., and Van Roozendael, M.: Glyoxal vertical columns from GOME-2 backscattered light measurements and comparisons with a global model, Atmos. Chem. Phys., 10, 12059-12072, doi:10.5194/acp-10-12059-2010, 2010.

A novel method to improve MODIS AOD retrievals in cloudy pixels using an analog ensemble approach

NASA Astrophysics Data System (ADS)

Kumar, R.; Raman, A.; Delle Monache, L.; Alessandrini, S.; Cheng, W. Y. Y.; Gaubert, B.; Arellano, A. F.

2016-12-01

Particulate matter (PM) concentrations are one of the fundamental indicators of air quality. Earth orbiting satellite platforms acquire column aerosol abundance that can in turn provide information about the PM concentrations. One of the serious limitations of column aerosol retrievals from low earth orbiting satellites is that these algorithms are based on clear sky assumptions. They do not retrieve AOD in cloudy pixels. After filtering cloudy pixels, these algorithms also arbitrarily remove brightest and darkest 25% of remaining pixels over ocean and brightest and darkest 50% pixels over land to filter any residual contamination from clouds. This becomes a critical issue especially in regions that experience monsoon, like Asia and North America. In case of North America, monsoon season experiences wide variety of extreme air quality events such as fires in California and dust storms in Arizona. Assessment of these episodic events warrants frequent monitoring of aerosol observations from remote sensing retrievals. In this study, we demonstrate a method to fill in cloudy pixels in Moderate Imaging Resolution Spectroradiometer (MODIS) AOD retrievals based on ensembles generated using an analog-based approach (AnEn). It provides a probabilistic distribution of AOD in cloudy pixels using historical records of model simulations of meteorological predictors such as AOD, relative humidity, and wind speed, and past observational records of MODIS AOD at a given target site. We use simulations from a coupled community weather forecasting model with chemistry (WRF-Chem) run at a resolution comparable to MODIS AOD. Analogs selected from summer months (June, July) of 2011-2013 from model and corresponding observations are used as a training dataset. Then, missing AOD retrievals in cloudy pixels in the last 31 days of the selected period are estimated. Here, we use AERONET stations as target sites to facilitate comparison against in-situ measurements. We use two approaches to evaluate the estimated AOD: 1) by comparing against reanalysis AOD, 2) by inverting AOD to PM10 concentrations and then comparing those with measured PM10. AnEn is an efficient approach to generate an ensemble as it involves only one model run and provides an estimate of uncertainty that complies with the physical and chemical state of the atmosphere.

Synthesizer: Expediting synthesis studies from context-free data with information retrieval techniques.

PubMed

Gandy, Lisa M; Gumm, Jordan; Fertig, Benjamin; Thessen, Anne; Kennish, Michael J; Chavan, Sameer; Marchionni, Luigi; Xia, Xiaoxin; Shankrit, Shambhavi; Fertig, Elana J

2017-01-01

Scientists have unprecedented access to a wide variety of high-quality datasets. These datasets, which are often independently curated, commonly use unstructured spreadsheets to store their data. Standardized annotations are essential to perform synthesis studies across investigators, but are often not used in practice. Therefore, accurately combining records in spreadsheets from differing studies requires tedious and error-prone human curation. These efforts result in a significant time and cost barrier to synthesis research. We propose an information retrieval inspired algorithm, Synthesize, that merges unstructured data automatically based on both column labels and values. Application of the Synthesize algorithm to cancer and ecological datasets had high accuracy (on the order of 85-100%). We further implement Synthesize in an open source web application, Synthesizer (https://github.com/lisagandy/synthesizer). The software accepts input as spreadsheets in comma separated value (CSV) format, visualizes the merged data, and outputs the results as a new spreadsheet. Synthesizer includes an easy to use graphical user interface, which enables the user to finish combining data and obtain perfect accuracy. Future work will allow detection of units to automatically merge continuous data and application of the algorithm to other data formats, including databases.

Synthesizer: Expediting synthesis studies from context-free data with information retrieval techniques

PubMed Central

Gumm, Jordan; Fertig, Benjamin; Thessen, Anne; Kennish, Michael J.; Chavan, Sameer; Marchionni, Luigi; Xia, Xiaoxin; Shankrit, Shambhavi; Fertig, Elana J.

2017-01-01

Scientists have unprecedented access to a wide variety of high-quality datasets. These datasets, which are often independently curated, commonly use unstructured spreadsheets to store their data. Standardized annotations are essential to perform synthesis studies across investigators, but are often not used in practice. Therefore, accurately combining records in spreadsheets from differing studies requires tedious and error-prone human curation. These efforts result in a significant time and cost barrier to synthesis research. We propose an information retrieval inspired algorithm, Synthesize, that merges unstructured data automatically based on both column labels and values. Application of the Synthesize algorithm to cancer and ecological datasets had high accuracy (on the order of 85–100%). We further implement Synthesize in an open source web application, Synthesizer (https://github.com/lisagandy/synthesizer). The software accepts input as spreadsheets in comma separated value (CSV) format, visualizes the merged data, and outputs the results as a new spreadsheet. Synthesizer includes an easy to use graphical user interface, which enables the user to finish combining data and obtain perfect accuracy. Future work will allow detection of units to automatically merge continuous data and application of the algorithm to other data formats, including databases. PMID:28437440

Data Fusion for Earth Science Remote Sensing

NASA Technical Reports Server (NTRS)

Braverman, Amy

2007-01-01

Beginning in 2004, NASA has supported the development of an international network of ground-based remote sensing installations for the measurement of greenhouse gas columns. This collaboration has been successful and is currently used in both carbon cycle investigations and in the efforts to validate the GOSAT space-based column observations of CO2 and CH4. With the support of a grant, this research group has established a network of ground-based column observations that provide an essential link between the satellite observations of CO2, CO, and CH4 and the extensive global in situ surface network. The Total Carbon Column Observing Network (TCCON) was established in 2004. At the time of this report seven sites, employing modern instrumentation, were operational or were expected to be shortly. TCCON is expected to expand. In addition to providing the most direct means of tying the in situ and remote sensing data sets together, TCCON provides a means of testing the retrieval algorithms of SCIAMACHY and GOSAT over the broadest variation in atmospheric state. TCCON provides a critically maintained and long timescale record for identification of temporal drift and spatial bias in the calibration of the space-based sensors. Finally, the global observations from TCCON are improving our understanding of how to use column observations to provide robust estimates of surface exchange of C02 and CH4 in advance of the launch of OCO and GOSAT. TCCON data are being used to better understand the impact of both regional fluxes and long-range transport on gradients in the C02 column. Such knowledge is essential for identifying the tools required to best use the space-based observations. The technical approach and methodology of retrieving greenhouse gas columns from near-IR solar spectra, data quality and process control are described. Additionally, the impact of and relevance to NASA of TCCON and satellite validation and carbon science are addressed.

A Retrieval of Tropical Latent Heating Using the 3D Structure of Precipitation Features

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ahmed, Fiaz; Schumacher, Courtney; Feng, Zhe

Traditionally, radar-based latent heating retrievals use rainfall to estimate the total column-integrated latent heating and then distribute that heating in the vertical using a model-based look-up table (LUT). In this study, we develop a new method that uses size characteristics of radar-observed precipitating echo (i.e., area and mean echo-top height) to estimate the vertical structure of latent heating. This technique (named the Convective-Stratiform Area [CSA] algorithm) builds on the fact that the shape and magnitude of latent heating profiles are dependent on the organization of convective systems and aims to avoid some of the pitfalls involved in retrieving accurate rainfallmore » amounts and microphysical information from radars and models. The CSA LUTs are based on a high-resolution Weather Research and Forecasting model (WRF) simulation whose domain spans much of the near-equatorial Indian Ocean. When applied to S-PolKa radar observations collected during the DYNAMO/CINDY2011/AMIE field campaign, the CSA retrieval compares well to heating profiles from a sounding-based budget analysis and improves upon a simple rain-based latent heating retrieval. The CSA LUTs also highlight the fact that convective latent heating increases in magnitude and height as cluster area and echo-top heights grow, with a notable congestus signature of cooling at mid levels. Stratiform latent heating is less dependent on echo-top height, but is strongly linked to area. Unrealistic latent heating profiles in the stratiform LUT, viz., a low-level heating spike, an elevated melting layer, and net column cooling were identified and corrected for. These issues highlight the need for improvement in model parameterizations, particularly in linking microphysical phase changes to larger mesoscale processes.« less

Comparison Between IASI/Metop-A and OMI/Aura Ozone Column Amounts with EUBREWNET Ground-Based Measurements

NASA Astrophysics Data System (ADS)

Lopez-Baeza, Ernesto

2016-07-01

This work addresses the comparison of {bf IASI (Infrared Atmospheric Sounding Interferometer)} on board Metop-A and {bf OMI (Ozone Monitoring Instrument)} on board Aura to several ground-based Brewer spectrophotometers belonging to the {bf European Brewer Network (EUBREWNET)} for the period September 2010 to December 2015. The focus of this study is to examine how well the satellite retrieval products capture the total ozone column amounts (TOC) at different latitudes and evaluate the different levels of Brewer spectrophotometer data. On this comparison Level 1, 1.5 and 2 Brewer data will be used to evaluate satellite data, where: 1) Level 1 Brewer data are the TOC calculated with the standard Brewer algorithm from the direct sun measurements; 2) Level 1.5 Brewer data are Level 1.0 observations filtered and corrected from instrumental issues: and 3) Level 2.0 Brewer data are 1.5 observations, but validated with a posteriori calibration. The IASI retrievals examined are operational IASI Level 2 products, version 5 from September 2010 to October 2014, and version 6 from October 2014 to December 2015, from {it EUMETSAT Data Centre}, while OMI retrievals are OMI-DOAS TOC products extracted from the {it NASA Goddard Earth Sciences Data and Information Services Center (GES DISC)}. The differences and their implications for the retrieved products will be discussed and, in order to evaluate the quality and sensitivity of each product, special attention will be put on analyzing the instrumental errors from these different measurement techniques. Furthermore, those parameters that could affect the comparison of the different datasets such as the different viewing geometry, the satellite data vertical sensitivity, cloudiness conditions, spectral region used for retrievals, and so on, will be analyzed in detail.

Comparison of OMI NO2 Observations and Their Seasonal and Weekly Cycles with Ground-Based Measurements in Helsinki

NASA Technical Reports Server (NTRS)

Ialongo, Iolanda; Herman, Jay; Krotkov, Nick; Lamsal, Lok; Boersma, Folkert; Hovila, Jari; Tamminen, Johanna

2016-01-01

We present the comparison of satellite-based OMI (Ozone Monitoring Instrument) NO2 products with ground-based observations in Helsinki. OMI NO2 total columns, available from standard product (SP) and DOMINO algorithm, are compared with the measurements performed by the Pandora spectrometer in Helsinki in 2012. The relative difference between Pandora 21 and OMI SP retrievals is 4 and 6 for clear sky and all sky conditions, respectively. DOMINO NO2 retrievals showed slightly lower total columns with median differences about 5 and 14 for clear sky and all sky conditions, respectively. Large differences often correspond to cloudy autumn-winter days with solar zenith angles above 65. Nevertheless, the differences remain within the retrieval uncertainties. Furthermore, the weekly and seasonal cycles from OMI, Pandora and NO2 surface concentrations are compared. Both satellite- and ground-based data show a similar weekly cycle, with lower NO2 levels during the weekend compared to the weekdays as result of reduced emissions from traffic and industrial activities. Also the seasonal cycle shows a similar behavior, even though the results are affected by the fact that most of the data are available during spring-summer because of cloud cover in other seasons. This is one of few works in which OMI NO2 retrievals are evaluated in an urban site at high latitudes (60N). Despite the city of Helsinki having relatively small pollution sources, OMI retrievals have proved to be able to describe air quality features and variability similar to surface observations. This adds confidence in using satellite observations for air quality monitoring also at high latitudes.

A full-mission data set of H2O and HDO columns from SCIAMACHY 2.3 µm reflectance measurements

NASA Astrophysics Data System (ADS)

Schneider, Andreas; Borsdorff, Tobias; aan de Brugh, Joost; Hu, Haili; Landgraf, Jochen

2018-06-01

A new data set of vertical column densities of the water vapour isotopologues H2O and HDO from the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) instrument for the whole of the mission period from January 2003 to April 2012 is presented. The data are retrieved from reflectance measurements in the spectral range 2339 to 2383 nm with the Shortwave Infrared CO Retrieval (SICOR) algorithm, ignoring atmospheric light scattering in the measurement simulation. The retrievals are validated with ground-based Fourier transform infrared measurements obtained within the Multi-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water (MUSICA) project. A good agreement for low-altitude stations is found with an average bias of -3.6×1021 for H2O and -1.0×1018 molec cm-2 for HDO. The a posteriori computed δD shows an average bias of -8 ‰, even though polar stations have a larger negative bias. The latter is due to the large amount of sensor noise in SCIAMACHY in combination with low albedo and high solar zenith angles. To demonstrate the benefit of accounting for light scattering in the retrieval, the quality of the data product fitting effective cloud parameters simultaneously with trace gas columns is evaluated in a dedicated case study for measurements round high-altitude stations. Due to a large altitude difference between the satellite ground pixel and the mountain station, clear-sky scenes yield a large bias, resulting in a δD bias of 125 ‰. When selecting scenes with optically thick clouds within 1000 m above or below the station altitude, the bias in a posteriori δD is reduced from 125 to 44 ‰. The insights from the present study will also benefit the analysis of the data from the new Sentinel-5 Precursor mission.

Water Column Correction for Coral Reef Studies by Remote Sensing

PubMed Central

Zoffoli, Maria Laura; Frouin, Robert; Kampel, Milton

2014-01-01

Human activity and natural climate trends constitute a major threat to coral reefs worldwide. Models predict a significant reduction in reef spatial extension together with a decline in biodiversity in the relatively near future. In this context, monitoring programs to detect changes in reef ecosystems are essential. In recent years, coral reef mapping using remote sensing data has benefited from instruments with better resolution and computational advances in storage and processing capabilities. However, the water column represents an additional complexity when extracting information from submerged substrates by remote sensing that demands a correction of its effect. In this article, the basic concepts of bottom substrate remote sensing and water column interference are presented. A compendium of methodologies developed to reduce water column effects in coral ecosystems studied by remote sensing that include their salient features, advantages and drawbacks is provided. Finally, algorithms to retrieve the bottom reflectance are applied to simulated data and actual remote sensing imagery and their performance is compared. The available methods are not able to completely eliminate the water column effect, but they can minimize its influence. Choosing the best method depends on the marine environment, available input data and desired outcome or scientific application. PMID:25215941

Water column correction for coral reef studies by remote sensing.

PubMed

Zoffoli, Maria Laura; Frouin, Robert; Kampel, Milton

2014-09-11

Human activity and natural climate trends constitute a major threat to coral reefs worldwide. Models predict a significant reduction in reef spatial extension together with a decline in biodiversity in the relatively near future. In this context, monitoring programs to detect changes in reef ecosystems are essential. In recent years, coral reef mapping using remote sensing data has benefited from instruments with better resolution and computational advances in storage and processing capabilities. However, the water column represents an additional complexity when extracting information from submerged substrates by remote sensing that demands a correction of its effect. In this article, the basic concepts of bottom substrate remote sensing and water column interference are presented. A compendium of methodologies developed to reduce water column effects in coral ecosystems studied by remote sensing that include their salient features, advantages and drawbacks is provided. Finally, algorithms to retrieve the bottom reflectance are applied to simulated data and actual remote sensing imagery and their performance is compared. The available methods are not able to completely eliminate the water column effect, but they can minimize its influence. Choosing the best method depends on the marine environment, available input data and desired outcome or scientific application.

Improvement and validation of trace gas retrieval from ACAM aircraft observation

NASA Astrophysics Data System (ADS)

Liu, C.; Liu, X.; Kowalewski, M. G.; Janz, S. J.; Gonzalez Abad, G.; Pickering, K. E.; Chance, K.; Lamsal, L. N.

2014-12-01

The ACAM (Airborne Compact Atmospheric Mapper) instrument, flown on board the NASA UC-12 aircraft during the DISCOVER-AQ (Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality) campaigns, was designed to provide remote sensing observations of tropospheric and boundary layer pollutants and help understand some of the most important pollutants that directly affect the health of the population. In this study, slant column densities (SCD) of trace gases (O3, NO2, HCHO) are retrieved from ACAM measurements during the Baltimore-Washington D.C. 2011 campaign by the Basic Optical Absorption Spectroscopy (BOAS) trace gas fitting algorithm using a nonlinear least-squares (NLLS) inversion technique, and then are converted to vertical column densities (VCDs) using the Air Mass Factors (AMF) calculated with the VLIDORT (Vector Linearized Discrete Ordinate Radiative Transfer) model and CMAQ (Community Multi-scale Air Quality) model simulations of trace gas profiles. For surface treatment in the AMF, we use high-resolution MODIS climatological BRDF product (Bidirectional Reflectance Distribution Function) at 470 nm for NO2, and use high-resolution surface albedo derived by combining MODIS and OMI albedo databases for HCHO and O3. We validate ACAM results with coincident ground-based PANDORA, aircraft (P3B) spiral and satellite (OMI) measurements and find out generally good agreement especially for NO2 and O3

Formaldehyde Distribution over North America: Implications for Satellite Retrievals of Formaldehyde Columns and Isoprene Emission

NASA Technical Reports Server (NTRS)

Millet, Dylan B.; Jacob, Daniel J.; Turquety, Solene; Hudman, Rynda C.; Wu, Shiliang; Anderson, Bruce E.; Fried, Alan; Walega, James; Heikes, Brian G.; Blake, Donald R.;

Comparison of MAX-DOAS profiling algorithms during CINDI-2 - Part 2: trace gases

NASA Astrophysics Data System (ADS)

Hendrick, Francois; Friess, Udo; Tirpitz, Lukas; Apituley, Arnoud; Van Roozendael, Michel; Kreher, Karin; Richter, Andreas; Wagner, Thomas

2017-04-01

The second Cabauw Intercomparison campaign for Nitrogen Dioxide measuring Instruments (CINDI-2) took place at the Cabauw Experimental Site for Atmospheric Research (CESAR; Utrecht area, The Netherlands) from 25 August until 7 October 2016. CINDI-2 was aiming at assessing the consistency of MAX-DOAS slant column density measurements of tropospheric species (NO2, HCHO, O3, and O4) relevant for the validation of future ESA atmospheric Sentinel missions, through coordinated operation of a large number of DOAS and MAXDOAS instruments from all over the world. An important objective of the campaign was to study the relationship between remote-sensing column and profile measurements of the above species and collocated reference ancillary observations. For this purpose, the CINDI-2 Profiling Task Team (CPTT) was created, involving 22 groups performing aerosol and trace gas vertical profile inversion using dedicated MAX-DOAS profiling algorithms, as well as the teams responsible for ancillary profile and surface concentration measurements (NO2 analysers, NO2 sondes, NO2 and Raman LIDARs, CAPS, Long-Path DOAS, sunphotometer, nephelometer, etc). The main purpose of the CPTT is to assess the consistency of the different profiling tools for retrieving aerosol extinction and trace gas vertical profiles through comparison exercises using commonly defined settings and to validate the retrievals with correlative observations. In this presentation, we give an overview of the MAX-DOAS vertical profile comparison results, focusing on NO2 and HCHO, the aerosol retrievals being presented in a companion abstract led by U. Frieß. The performance of the different algorithms is investigated with respect to the various sky and weather conditions and aerosol loadings encountered during the campaign. The consistency between optimal-estimation-based and parameterized profiling tools is also evaluated for these different conditions, together with the level of agreement with available NO2 and HCHO ancillary observations. This comparison study will be put in the perspective of the development of a centralized MAX-DOAS processing system within the framework of the ESA Fiducial Reference Measurements (FRM) project.

Methods for Retrievals of CO2 Mixing Ratios from JPL Laser Absorption Spectrometer Flights During a Summer 2011 Campaign

NASA Technical Reports Server (NTRS)

Menzies, Robert T.; Spiers, Gary D.; Jacob, Joseph C.

2013-01-01

The JPL airborne Laser Absorption Spectrometer instrument has been flown several times in the 2007-2011 time frame for the purpose of measuring CO2 mixing ratios in the lower atmosphere. This instrument employs CW laser transmitters and coherent detection receivers in the 2.05- micro m spectral region. The Integrated Path Differential Absorption (IPDA) method is used to retrieve weighted CO2 column mixing ratios. We present key features of the evolving LAS signal processing and data analysis algorithms and the calibration/validation methodology. Results from 2011 flights in various U.S. locations include observed mid-day CO2 drawdown in the Midwest and high spatial resolution plume detection during a leg downwind of the Four Corners power plant in New Mexico.

Evaluation of MODIS aerosol optical depth for semi­-arid environments in complex terrain

NASA Astrophysics Data System (ADS)

Holmes, H.; Loria Salazar, S. M.; Panorska, A. K.; Arnott, W. P.; Barnard, J.

2015-12-01

The use of satellite remote sensing to estimate spatially resolved ground level air pollutant concentrations is increasing due to advancements in remote sensing technology and the limited number of surface observations. Satellite retrievals provide global, spatiotemporal air quality information and are used to track plumes, estimate human exposures, model emissions, and determine sources (i.e., natural versus anthropogenic) in regulatory applications. Ground level PM2.5 concentrations can be estimated using columnar aerosol optical depth (AOD) from MODIS, where the satellite retrieval serves as a spatial surrogate to simulate surface PM2.5 gradients. The spatial statistical models and MODIS AOD retrieval algorithms have been evaluated for the dark, vegetated eastern US, while the semi-arid western US continues to be an understudied region with associated complexity due to heterogeneous emissions, smoke from wildfires, and complex terrain. The objective of this work is to evaluate the uncertainty of MODIS AOD retrievals by comparing with columnar AOD and surface PM2.5 measurements from AERONET and EPA networks. Data is analyzed from multiple stations in California and Nevada for three years where four major wildfires occurred. Results indicate that MODIS retrievals fail to estimate column-integrated aerosol pollution in the summer months. This is further investigated by quantifying the statistical relationships between MODIS AOD, AERONET AOD, and surface PM2.5 concentrations. Data analysis indicates that the distribution of MODIS AOD is significantly (p<0.05) different than AERONET AOD. Further, using the results of distributional and association analysis the impacts of MODIS AOD uncertainties on the spatial gradients are evaluated. Additionally, the relationships between these uncertainties and physical parameters in the retrieval algorithm (e.g., surface reflectance, Ångström Extinction Exponent) are discussed.

Regional trace gas monitoring simplified - A linear retrieval scheme for carbon monoxide from hyperspectral soundings

NASA Astrophysics Data System (ADS)

Smith, N.; Huang, A.; Weisz, E.; Annegarn, H. J.

2011-12-01

The Fast Linear Inversion Trace gas System (FLITS) is designed to retrieve tropospheric total column trace gas densities [molec.cm-2] from space-borne hyperspectral infrared soundings. The objective to develop a new retrieval scheme was motivated by the need for near real-time air quality monitoring at high spatial resolution. We present a case study of FLITS carbon monoxide (CO) retrievals from daytime (descending orbit) Infrared Atmospheric Sounding Interferometer (IASI) measurements that have a 0.5 cm-1 spectral resolution and 12 km footprint at nadir. The standard Level 2 IASI CO retrieval product (COL2) is available in near real-time but is spatially averaged over 2 x 2 pixels, or 50 x 50 km, and thus more suitable for global analysis. The study region is Southern Africa (south of the equator) for the period 28-31 August 2008. An atmospheric background estimate is obtained from a chemical transport model, emissivity from regional measurements and surface temperature (ST) from space-borne retrievals. The CO background error is set to 10%. FLITS retrieves CO by assuming a simple linear relationship between the IASI measurements and background estimate of the atmosphere and surface parameters. This differs from the COL2 algorithm that treats CO retrieval as a moderately non-linear problem. When compared to COL2, the FLITS retrievals display similar trends in distribution and transport of CO over time with the advantage of an improved spatial resolution (single-pixel). The value of the averaging kernel (A) is consistently above 0.5 and indicates that FLITS retrievals have a stable dependence on the measurement. This stability is achieved through careful channel selection in the strongest CO absorption lines (2050-2225 cm-1) and joint retrieval with skin temperature (IASI sensitivity to CO is highly correlated with ST), thus no spatial averaging is necessary. We conclude that the simplicity and stability of FLITS make it useful first as a research tool, i.e. the algorithm is easy to understand and computationally simple enough to run on most desktop computers, and second, as an operational tool that can calculate near real-time CO retrievals at instrument resolution for regional monitoring.

The OMPS Limb Profiler instrument

NASA Astrophysics Data System (ADS)

Rault, D. F.; Xu, P.

2011-12-01

The Ozone Mapping and Profiler Suite (OMPS) will continue the monitoring of the global distribution of the Earth's middle atmosphere ozone and aerosol. OMPS is composed of three instruments, namely the Total Column Mapper (heritage: TOMS, OMI), the Nadir Profiler (heritage: SBUV) and the Limb Profiler (heritage: SOLSE/LORE, OSIRIS, SCIAMACHY, SAGE III). The ultimate goal of the mission is to better understand and quantify the rate of stratospheric ozone recovery. OMPS is scheduled to be launched on the NPOESS Preparatory Project (NPP) platform in October 2011. The focus of the paper will be on the Limb Profiler (LP) instrument. The LP instrument will measure the Earth's limb radiance, from which ozone profile will be retrieved from the upper tropopause uo to 60km. End-to-end studies of the sensor and retrieval algorithm indicate the following expected performance for ozone: accuracy of 5% or better from the tropopause up to 50 km, precision of about 3-5% from 18 to 50 km, and vertical resolution of 1.5-2 km with vertical sampling of 1 km and along-track horizontal sampling of 1 deg latitude. The paper will describe the mission, discuss the retrieval algorithm, and summarize the expected performance. If available, the paper will also present early on-orbit data.

Information-rich spectral channels for simulated retrievals of partial column-averaged methane

NASA Astrophysics Data System (ADS)

Su, Zhan; Xi, Xi; Natraj, Vijay; Li, King-Fai; Shia, Run-Lie; Miller, Charles E.; Yung, Yuk L.

2016-01-01

Space-based remote sensing of the column-averaged methane dry air mole fraction (XCH4) has greatly increased our understanding of the spatiotemporal patterns in the global methane cycle. The potential to retrieve multiple pieces of vertical profile information would further improve the quantification of CH4 across space-time scales. We conduct information analysis for channel selection and evaluate the prospects of retrieving multiple pieces of information as well as total column CH4 from both ground-based and space-based near-infrared remote sensing spectra. We analyze the degrees of freedom of signal (DOF) in the CH4 absorption bands near 2.3 μm and 1.6 μm and select ˜1% of the channels that contain >95% of the information about the CH4 profile. The DOF is around 4 for fine ground-based spectra (resolution = 0.01 cm-1) and 3 for coarse space-based spectra (resolution = 0.20 cm-1) based on channel selection and a signal-to-noise ratio (SNR) of 300. The DOF varies from 2.2 to 3.2 when SNR is between 100 and 300, and spectral resolution is 0.20 cm-1. Simulated retrieval tests in clear-sky conditions using the selected channels reveal that the retrieved partial column-averaged CH4 values are not sensitive to the a priori profiles and can reflect local enhancements of CH4 in different partial air columns. Both the total and partial column-averaged retrieval errors in all tests are within 1% of the true state. These simulated tests highlight the possibility to retrieve up to three to four pieces of information about the vertical distribution of CH4 in reality.

Explicit and Observation-based Aerosol Treatment in Tropospheric NO2 Retrieval over China from the Ozone Monitoring Instrument

NASA Astrophysics Data System (ADS)

Liu, M.; Lin, J.; Boersma, F.; Pinardi, G.; Wang, Y.; Chimot, J.; Wagner, T.; Xie, P.; Eskes, H.; Van Roozendael, M.; Hendrick, F.

2017-12-01

Satellite retrieval of vertical column densities (VCDs) of tropospheric nitrogen dioxide (NO2) is influenced by aerosols substantially. Aerosols affect the retrieval of "effective cloud fraction (CF)" and "effective cloud top pressure (CP)" that are used in the subsequent NO2 retrieval to account for the presentence of clouds. And aerosol properties and vertical distributions directly affect the NO2 air mass factor (AMF) calculations. Our published POMINO algorithm uses a parallelized LIDORT-driven AMFv6 code to derive CF, CP and NO2 VCD. Daily information on aerosol optical properties are taken from GEOS-Chem simulations, with aerosol optical depth (AOD) further constrained by monthly MODIS AOD. However, the published algorithm does not include an observation-based constraint of aerosol vertical distribution. Here we construct a monthly climatological observation dataset of aerosol extinction profiles, based on Level-2 CALIOP data over 2007-2015, to further constrain aerosol vertical distributions. GEOS-Chem captures the temporal variations of CALIOP aerosol layer heights (ALH) but has an overall underestimate by about 0.3 km. It tends to overestimate the aerosol extinction by 10% below 2 km but with an underestimate by 30% above 2 km, leading to a low bias by 10-30% in the retrieved tropospheric NO2 VCD. After adjusting GEOS-Chem aerosol extinction profiles by the CALIOP monthly ALH climatology, the retrieved NO2 VCDs increase by 4-16% over China on a monthly basis in 2012. The improved NO2 VCDs are better correlated to independent MAX-DOAS observations at three sites than POMINO and DOMINO are - especially for the polluted cases, R2 reaches 0.76 for the adjusted POMINO, much higher than that for the published POMINO (0.68) and DOMINO (0.38). The newly retrieved CP increases by 60 hPa on average, because of a stronger aerosol screening effect. Compared to the CF used in DOMINO, which implicitly includes aerosol information, our improved CF is much lower and can reach a value of zero on actual cloud-free days. Overall, constraining aerosol vertical profiles greatly improves the retrievals of clouds and NO2 VCDs from satellite remote sensing. Our algorithm can be applied, with minimum modifications, to formaldehyde, sulfur dioxide and other species with similar retrieval methodologies.

Remotely operable compact instruments for measuring atmospheric CO2 and CH4 column densities at surface monitoring sites

NASA Astrophysics Data System (ADS)

Kobayashi, N.; Inoue, G.; Kawasaki, M.; Yoshioka, H.; Minomura, M.; Murata, I.; Nagahama, T.; Matsumi, Y.; Tanaka, T.; Morino, I.; Ibuki, T.

2010-08-01

Remotely operable compact instruments for measuring atmospheric CO2 and CH4 column densities were developed in two independent systems: one utilizing a grating-based desktop optical spectrum analyzer (OSA) with a resolution enough to resolve rotational lines of CO2 and CH4 in the regions of 1565-1585 and 1674-1682 nm, respectively; the other is an application of an optical fiber Fabry-Perot interferometer (FFPI) to obtain the CO2 column density. Direct sunlight was collimated via a small telescope installed on a portable sun tracker and then transmitted through an optical fiber into the OSA or the FFPI for optical analysis. The near infrared spectra of the OSA were retrieved by a least squares spectral fitting algorithm. The CO2 and CH4 column densities deduced were in excellent agreement with those measured by a Fourier transform spectrometer with high resolution. The rovibronic lines in the wavelength region of 1570-1575 nm were analyzed by the FFPI. The I0 and I values in the Beer-Lambert law equation to obtain CO2 column density were deduced by modulating temperature of the FFPI, which offered column CO2 with the statistical error less than 0.2% for six hours measurement.

Evaluating A Priori Ozone Profile Information Used in TEMPO Tropospheric Ozone Retrievals

NASA Technical Reports Server (NTRS)

Johnson, Matthew S.; Sullivan, John T.; Liu, Xiong; Newchurch, Mike; Kuang, Shi; McGee, Thomas J.; Langford, Andrew O'Neil; Senff, Christoph J.; Leblanc, Thierry; Berkoff, Timothy;

Evaluating a Priori Ozone Profile Information Used in TEMPO Tropospheric Ozone Retrievals

NASA Technical Reports Server (NTRS)

Johnson, Matthew S.; Sullivan, John; Liu, Xiong; Newchurch, Mike; Kuang, Shi; McGee, Thomas; Langford, Andrew; Senff, Chris; Leblanc, Thierry; Berkoff, Timothy;

Evaluating A Priori Ozone Profile Information Used in TEMPO Tropospheric Ozone Retrievals

NASA Astrophysics Data System (ADS)

Johnson, M. S.; Sullivan, J. T.; Liu, X.; Newchurch, M.; Kuang, S.; McGee, T. J.; Langford, A. O.; Senff, C. J.; Leblanc, T.; Berkoff, T.; Gronoff, G.; Chen, G.; Strawbridge, K. B.

2016-12-01

Ozone (O3) is a greenhouse gas and toxic pollutant which plays a major role in air quality. Typically, monitoring of surface air quality and O3 mixing ratios is primarily conducted using in situ measurement networks. This is partially due to high-quality information related to air quality being limited from space-borne platforms due to coarse spatial resolution, limited temporal frequency, and minimal sensitivity to lower tropospheric and surface-level O3. The Tropospheric Emissions: Monitoring of Pollution (TEMPO) satellite is designed to address these limitations of current space-based platforms and to improve our ability to monitor North American air quality. TEMPO will provide hourly data of total column and vertical profiles of O3 with high spatial resolution to be used as a near-real-time air quality product. TEMPO O3 retrievals will apply the Smithsonian Astrophysical Observatory profile algorithm developed based on work from GOME, GOME-2, and OMI. This algorithm uses a priori O3 profile information from a climatological data-base developed from long-term ozone-sonde measurements (tropopause-based (TB) O3 climatology). It has been shown that satellite O3 retrievals are sensitive to a priori O3 profiles and covariance matrices. During this work we investigate the climatological data to be used in TEMPO algorithms (TB O3) and simulated data from the NASA GMAO Goddard Earth Observing System (GEOS-5) Forward Processing (FP) near-real-time (NRT) model products. These two data products will be evaluated with ground-based lidar data from the Tropospheric Ozone Lidar Network (TOLNet) at various locations of the US. This study evaluates the TB climatology, GEOS-5 climatology, and 3-hourly GEOS-5 data compared to lower tropospheric observations to demonstrate the accuracy of a priori information to potentially be used in TEMPO O3 algorithms. Here we present our initial analysis and the theoretical impact on TEMPO retrievals in the lower troposphere.

Validation of the CrIS fast physical NH3 retrieval with ground-based FTIR

NASA Astrophysics Data System (ADS)

Dammers, Enrico; Shephard, Mark W.; Palm, Mathias; Cady-Pereira, Karen; Capps, Shannon; Lutsch, Erik; Strong, Kim; Hannigan, James W.; Ortega, Ivan; Toon, Geoffrey C.; Stremme, Wolfgang; Grutter, Michel; Jones, Nicholas; Smale, Dan; Siemons, Jacob; Hrpcek, Kevin; Tremblay, Denis; Schaap, Martijn; Notholt, Justus; Erisman, Jan Willem

2017-07-01

Presented here is the validation of the CrIS (Cross-track Infrared Sounder) fast physical NH3 retrieval (CFPR) column and profile measurements using ground-based Fourier transform infrared (FTIR) observations. We use the total columns and profiles from seven FTIR sites in the Network for the Detection of Atmospheric Composition Change (NDACC) to validate the satellite data products. The overall FTIR and CrIS total columns have a positive correlation of r = 0.77 (N = 218) with very little bias (a slope of 1.02). Binning the comparisons by total column amounts, for concentrations larger than 1.0 × 1016 molecules cm-2, i.e. ranging from moderate to polluted conditions, the relative difference is on average ˜ 0-5 % with a standard deviation of 25-50 %, which is comparable to the estimated retrieval uncertainties in both CrIS and the FTIR. For the smallest total column range (< 1.0 × 1016 molecules cm-2) where there are a large number of observations at or near the CrIS noise level (detection limit) the absolute differences between CrIS and the FTIR total columns show a slight positive column bias. The CrIS and FTIR profile comparison differences are mostly within the range of the single-level retrieved profile values from estimated retrieval uncertainties, showing average differences in the range of ˜ 20 to 40 %. The CrIS retrievals typically show good vertical sensitivity down into the boundary layer which typically peaks at ˜ 850 hPa (˜ 1.5 km). At this level the median absolute difference is 0.87 (std = ±0.08) ppb, corresponding to a median relative difference of 39 % (std = ±2 %). Most of the absolute and relative profile comparison differences are in the range of the estimated retrieval uncertainties. At the surface, where CrIS typically has lower sensitivity, it tends to overestimate in low-concentration conditions and underestimate in higher atmospheric concentration conditions.

Validation of GOME (ERS-2) NO2 vertical column data with ground-based measurements at Issyk-Kul (Kyrgyzstan)

NASA Astrophysics Data System (ADS)

Ionov, D.; Sinyakov, V.; Semenov, V.

Starting from 1995 the global monitoring of atmospheric nitrogen dioxide is carried out by the measurements of nadir-viewing GOME spectrometer aboard ERS-2 satellite. Continuous validation of that data by means of comparisons with well-controlled ground-based measurements is important to ensure the quality of GOME data products and improve related retrieval algorithms. At the station of Issyk-Kul (Kyrgyzstan) the ground-based spectroscopic observations of NO2 vertical column have been started since 1983. The station is located on the northern shore of Issyk-Kul lake, 1650 meters above the sea level (42.6 N, 77.0 E). The site is equipped with grating spectrometer for the twilight measurements of zenith-scattered solar radiation in the visible range, and applies the DOAS technique to retrieve NO2 vertical column. It is included in the list of NDSC stations as a complementary one. The present study is focused on validation of GOME NO2 vertical column data, based on 8-year comparison with correlative ground-based measurements at Issyk-Kul station in 1996-2003. Within the investigation, an agreement of both individual and monthly averaged GOME measurements with corresponding twilight ground-based observations is examined. Such agreement is analyzed with respect to different conditions (season, sun elevation), temporal/spatial criteria choice (actual overpass location, correction for diurnal variation) and data processing (GDP version 2.7, 3.0). In addition, NO2 vertical columns were integrated from simultaneous stratospheric profile measurements by NASA HALOE and SAGE-II/III satellite instruments and introduced to explain the differences with ground-based observations. In particular cases, NO2 vertical profiles retrieved from the twilight ground-based measurements at Issuk-Kul were also included into comparison. Overall, summertime GOME NO2 vertical columns were found to be systematicaly lower than ground-based data. This work was supported by International Association for the promotion of co-operation with scientists from the New Independent States of the former Soviet Union (INTAS-YSF-02-138), International Science and Technology Center (ISTC Kr-763), Russian Foundation for Basic Research (RFBR-03-05-64626), the joint foundation of Russian Ministry of Education and St.Petersburg Administration (PD02-1.5-96) and the President of Russia grant (MK-2686.2003.05).

Fast retrievals of tropospheric carbonyl sulfide with IASI

NASA Astrophysics Data System (ADS)

Vincent, R. Anthony; Dudhia, Anu

2017-02-01

Iterative retrievals of trace gases, such as carbonyl sulfide (OCS), from satellites can be exceedingly slow. The algorithm may even fail to keep pace with data acquisition such that analysis is limited to local events of special interest and short time spans. With this in mind, a linear retrieval scheme was developed to estimate total column amounts of OCS at a rate roughly 104 times faster than a typical iterative retrieval. This scheme incorporates two concepts not utilized in previously published linear estimates. First, all physical parameters affecting the signal are included in the state vector and accounted for jointly, rather than treated as effective noise. Second, the initialization point is determined from an ensemble of atmospheres based on comparing the model spectra to the observations, thus improving the linearity of the problem. All of the 2014 data from the Infrared Atmospheric Sounding Interferometer (IASI), instruments A and B, were analysed and showed spatial features of OCS total columns, including depletions over tropical rainforests, seasonal enhancements over the oceans, and distinct OCS features over land. Error due to assuming linearity was found to be on the order of 11 % globally for OCS. However, systematic errors from effects such as varying surface emissivity and extinction due to aerosols have yet to be robustly characterized. Comparisons to surface volume mixing ratio in situ samples taken by NOAA show seasonal correlations greater than 0.7 for five out of seven sites across the globe. Furthermore, this linear scheme was applied to OCS, but may also be used as a rapid estimator of any detectable trace gas using IASI or similar nadir-viewing instruments.

Mini MAX-DOAS Measurements of Air Pollutants over China

NASA Astrophysics Data System (ADS)

Staadt, Steffen; Hao, Nan; Trautmann, Thomas

2016-08-01

This study continues the work of Clémer et al., (2010) and is aimed to improve trace gas retrievals with mini MAX-DOAS measurements in Nanjing. Based on that work, aerosol extinction vertical profiles are retrieved using the bePRO inversion algorithm developed by the Royal Belgian Institute for Space Aeronomy (BIRA- IASB). Afterwards, the tropospheric trace gas vertical profiles and vertical column densities (VCDs) are retrieved by applying the optimal estimation method to the O4 MAX-DOAS measurements. The Profiles for N O2 , S O2 , glyoxal, formaldehyde and nitrous acid are obtained with different results and different settings for the DOAS measurement. The AODs show small positive correlation against the AERONET values. For NO2, the retrieval shows reasonable concentrations in winter as opposed to summer and has small positive correlations with GOME-2 data. The SO2 VCDs are not correlated with the GOME-2 data, due to high uncertainties from MAX-DOAS and satellite retrievals, while the vertical mixing ratios (VMR) show good agreement with in-situ data (SORPES) at Nanjing. Nitrous acid shows a maximum in winter and a minimum in summer, while glyoxal has its maximum in August and September.

Nitrogen dioxide observations from the Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) airborne instrument: Retrieval algorithm and measurements during DISCOVER-AQ Texas 2013

NASA Astrophysics Data System (ADS)

Nowlan, Caroline R.; Liu, Xiong; Leitch, James W.; Chance, Kelly; González Abad, Gonzalo; Liu, Cheng; Zoogman, Peter; Cole, Joshua; Delker, Thomas; Good, William; Murcray, Frank; Ruppert, Lyle; Soo, Daniel; Follette-Cook, Melanie B.; Janz, Scott J.; Kowalewski, Matthew G.; Loughner, Christopher P.; Pickering, Kenneth E.; Herman, Jay R.; Beaver, Melinda R.; Long, Russell W.; Szykman, James J.; Judd, Laura M.; Kelley, Paul; Luke, Winston T.; Ren, Xinrong; Al-Saadi, Jassim A.

2016-06-01

The Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) airborne instrument is a test bed for upcoming air quality satellite instruments that will measure backscattered ultraviolet, visible and near-infrared light from geostationary orbit. GeoTASO flew on the NASA Falcon aircraft in its first intensive field measurement campaign during the Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) Earth Venture Mission over Houston, Texas, in September 2013. Measurements of backscattered solar radiation between 420 and 465 nm collected on 4 days during the campaign are used to determine slant column amounts of NO2 at 250 m × 250 m spatial resolution with a fitting precision of 2.2 × 1015 moleculescm-2. These slant columns are converted to tropospheric NO2 vertical columns using a radiative transfer model and trace gas profiles from the Community Multiscale Air Quality (CMAQ) model. Total column NO2 from GeoTASO is well correlated with ground-based Pandora observations (r = 0.90 on the most polluted and cloud-free day of measurements and r = 0.74 overall), with GeoTASO NO2 slightly higher for the most polluted observations. Surface NO2 mixing ratios inferred from GeoTASO using the CMAQ model show good correlation with NO2 measured in situ at the surface during the campaign (r = 0.85). NO2 slant columns from GeoTASO also agree well with preliminary retrievals from the GEO-CAPE Airborne Simulator (GCAS) which flew on the NASA King Air B200 (r = 0.81, slope = 0.91). Enhanced NO2 is resolvable over areas of traffic NOx emissions and near individual petrochemical facilities.

Physical Validation of GPM Retrieval Algorithms Over Land: An Overview of the Mid-Latitude Continental Convective Clouds Experiment (MC3E)

NASA Technical Reports Server (NTRS)

Petersen, Walter A.; Jensen, Michael P.

2011-01-01

The joint NASA Global Precipitation Measurement (GPM) -- DOE Atmospheric Radiation Measurement (ARM) Midlatitude Continental Convective Clouds Experiment (MC3E) was conducted from April 22-June 6, 2011, centered on the DOE-ARM Southern Great Plains Central Facility site in northern Oklahoma. GPM field campaign objectives focused on the collection of airborne and ground-based measurements of warm-season continental precipitation processes to support refinement of GPM retrieval algorithm physics over land, and to improve the fidelity of coupled cloud resolving and land-surface satellite simulator models. DOE ARM objectives were synergistically focused on relating observations of cloud microphysics and the surrounding environment to feedbacks on convective system dynamics, an effort driven by the need to better represent those interactions in numerical modeling frameworks. More specific topics addressed by MC3E include ice processes and ice characteristics as coupled to precipitation at the surface and radiometer signals measured in space, the correlation properties of rainfall and drop size distributions and impacts on dual-frequency radar retrieval algorithms, the transition of cloud water to rain water (e.g., autoconversion processes) and the vertical distribution of cloud water in precipitating clouds, and vertical draft structure statistics in cumulus convection. The MC3E observational strategy relied on NASA ER-2 high-altitude airborne multi-frequency radar (HIWRAP Ka-Ku band) and radiometer (AMPR, CoSMIR; 10-183 GHz) sampling (a GPM "proxy") over an atmospheric column being simultaneously profiled in situ by the University of North Dakota Citation microphysics aircraft, an array of ground-based multi-frequency scanning polarimetric radars (DOE Ka-W, X and C-band; NASA D3R Ka-Ku and NPOL S-bands) and wind-profilers (S/UHF bands), supported by a dense network of over 20 disdrometers and rain gauges, all nested in the coverage of a six-station mesoscale rawinsonde network. As an exploratory effort to examine land-surface emissivity impacts on retrieval algorithms, and to demonstrate airborne soil moisture retrieval capabilities, the University of Tennessee Space Institute Piper aircraft carrying the MAPIR L-band radiometer was also flown during the latter half of the experiment in coordination with the ER-2. The observational strategy provided a means to sample the atmospheric column in a redundant framework that enables inter-calibration and constraint of measured and retrieved precipitation characteristics such as particle size distributions, or water contents- all within the umbrella of "proxy" satellite measurements (i.e., the ER-2). Complimenting the precipitation sampling framework, frequent and coincident launches of atmospheric soundings (e.g., 4-8/day) then provided a much larger mesoscale view of the thermodynamic and winds environment, a data set useful for initializing cloud models. The datasets collected represent a variety cloud and precipitation types including isolated cumulus clouds, severe thunderstorms, mesoscale convective systems, and widespread regions of light to moderate stratiform precipitation. We will present the MC3E experiment design, an overview of operations, and a summary of preliminary results.

A method to combine spaceborne radar and radiometric observations of precipitation

NASA Astrophysics Data System (ADS)

Munchak, Stephen Joseph

This dissertation describes the development and application of a combined radar-radiometer rainfall retrieval algorithm for the Tropical Rainfall Measuring Mission (TRMM) satellite. A retrieval framework based upon optimal estimation theory is proposed wherein three parameters describing the raindrop size distribution (DSD), ice particle size distribution (PSD), and cloud water path (cLWP) are retrieved for each radar profile. The retrieved rainfall rate is found to be strongly sensitive to the a priori constraints in DSD and cLWP; thus, these parameters are tuned to match polarimetric radar estimates of rainfall near Kwajalein, Republic of Marshall Islands. An independent validation against gauge-tuned radar rainfall estimates at Melbourne, FL shows agreement within 2% which exceeds previous algorithms' ability to match rainfall at these two sites. The algorithm is then applied to two years of TRMM data over oceans to determine the sources of DSD variability. Three correlated sets of variables representing storm dynamics, background environment, and cloud microphysics are found to account for approximately 50% of the variability in the absolute and reflectivity-normalized median drop size. Structures of radar reflectivity are also identified and related to drop size, with these relationships being confirmed by ground-based polarimetric radar data from the North American Monsoon Experiment (NAME). Regional patterns of DSD and the sources of variability identified herein are also shown to be consistent with previous work documenting regional DSD properties. In particular, mid-latitude regions and tropical regions near land tend to have larger drops for a given reflectivity, whereas the smallest drops are found in the eastern Pacific Intertropical Convergence Zone. Due to properties of the DSD and rain water/cloud water partitioning that change with column water vapor, it is shown that increases in water vapor in a global warming scenario could lead to slight (1%) underestimates of a rainfall trends by radar but larger overestimates (5%) by radiometer algorithms. Further analyses are performed to compare tropical oceanic mean rainfall rates between the combined algorithm and other sources. The combined algorithm is 15% higher than the version 6 of the 2A25 radar-only algorithm and 6.6% higher than the Global Precipitation Climatology Project (GPCP) estimate for the same time-space domain. Despite being higher than these two sources, the combined total is not inconsistent with estimates of the other components of the energy budget given their uncertainties.

Profiling the SO2 Plume from Volcan Turrialba: Ticosonde Balloon Measurements Compared with OMI and OMPS Retrievals

NASA Astrophysics Data System (ADS)

Selkirk, H. B.; Krotkov, N. A.; Li, C.; Morris, G.; Diaz, J. A.; Carn, S. A.; Voemel, H.; Nord, P. M.; Larson, K.

2014-12-01

The summit of Volcan Turrialba (elev. 3340 m) lies less than 50 km upstream in the prevailing easterlies from the Ticosonde balloon launch site at San Jose, Costa Rica, where ECC ozone sondes have been launched regularly since 2005. In 2006 we began to see telltale notches in the ozone profiles in the altitude range between 2 and 6 km. Given the proximity of Turrialba, it seemed likely that SO2 in the volcano's plume was interfering in the chemical reaction in the ECC ozone sonde used to detect ozone. In early 2010, fumarolic activity in the Turrialba crater increased strongly, and the profile notches in our soundings increased in frequency as well, consistent with this hypothesis. In February 2012 we tested a dual ECC sonde system, where an additional sonde is flown on the same payload using a selective SO2 filter. The difference of the measurements in the dual sonde is a direct measure of the amount of SO2 encountered. This first dual sonde passed through the plume, and the data indicated a tropospheric SO2 column of 1.4 DU, comparing favorably with a total column of 1.7 DU in the OMI 3-km linear fit (LF) product at the sonde profile location and at nearly the same time. We are now launching dual sondes on a regular basis with 18 launches in the first 12 months through July 2014; 11 of these have detectable SO2 signals. These soundings have great potential for validation of the Aura OMI and the Suomi-NPP OMPS retrievals of SO2. Here we present the sonde measurements and compare them with two satellite datasets: the Aura OMI Linear Fit (LF) product and the Suomi-NPP OMPS Principal Components Analysis (PCA) boundary layer product. The PCA algorithm reduces retrieval noise and artifacts by more accurately accounting for various interferences in SO2 retrievals such as O3 absorption and rotational Raman scattering. The comparisons with the in situ observations indicate a significant improvement of the PCA algorithm in capturing relatively weak volcanic SO2 signals.

Profiling the SO2 Plume from Volcan Turrialba: Ticosonde Balloon Measurements Compared with OMI and OMPS Retrievals

NASA Technical Reports Server (NTRS)

Selkirk, Henry; Krotkov, Nickolay; Li, Can; Morris, Gary (Inventor); Diaz, Jorge Andres; Carn, Simon; Vomel, Holger; Corrales, Ernesto; Nord, Paul; Larson, Kelsey

2014-01-01

The summit of Volcan Turrialba (elev. 3340 m) lies less than 50 km upstream in the prevailing easterlies from the Ticosonde balloon launch site at San Jose, Costa Rica, where ECC ozone sondes have been launched regularly since 2005. In 2006 we began to see telltale notches in the ozone profiles in the altitude range between 2 and 6 km. Given the proximity of Turrialba, it seemed likely that SO2 in the volcano's plume was interfering in the chemical reaction in the ECC ozone sonde used to detect ozone. In early 2010, fumarolic activity in the Turrialba crater increased strongly, and the profile notches in our soundings increased in frequency as well, consistent with this hypothesis. In February 2012 we tested a dual ECC sonde system, where an additional sonde is flown on the same payload using a selective SO2 filter. The difference of the measurements in the dual sonde is a direct measure of the amount of SO2 encountered. This first dual sonde passed through the plume, and the data indicated a tropospheric SO2 column of 1.4 DU, comparing favorably with a total column of 1.7 DU in the OMI 3-km linear fit (LF) product at the sonde profile location and at nearly the same time. We are now launching dual sondes on a regular basis with 18 launches in the first 12 months through July 2014; 11 of these have detectable SO2 signals. These soundings have great potential for validation of the Aura OMI and the Suomi-NPP OMPS retrievals of SO2. Here we present the sonde measurements and compare them with two satellite datasets: the Aura OMI Linear Fit (LF) product and the Suomi-NPP OMPS Principal Components Analysis (PCA) boundary layer product. The PCA algorithm reduces retrieval noise and artifacts by more accurately accounting for various interferences in SO2 retrievals such as O3 absorption and rotational Raman scattering. The comparisons with the in situ observations indicate a significant improvement of the PCA algorithm in capturing relatively weak volcanic SO2 signals.

Retrieval of tropospheric aerosol properties over land from visible and near-infrared spectral reflectance: Application over Maryland

NASA Astrophysics Data System (ADS)

Levy, Robert Carroll

Aerosols are major components of the Earth's global climate system, affecting the radiation budget and cloud processes of the atmosphere. When located near the surface, high concentrations lead to lowered visibility, increased health problems and generally reduced quality of life for the human population. Over the United States mid-Atlantic region, aerosol pollution is a problem mainly during the summer. Satellites, such as the MODerate Imaging Spectrometer (MODIS), from their vantage point above the atmosphere, provide unprecedented coverage of global and regional aerosols over land. During MODIS' eight-year operation, exhaustive data validation and analyses have shown how the algorithm should be improved. This dissertation describes the development of the 'second-generation' operational algorithm for retrieval of global tropospheric aerosol properties over dark land surfaces, from MODIS-observed spectral reflectance. New understanding about global aerosol properties, land surface reflectance characteristics, and radiative transfer properties were learned in the process. This new operational algorithm performs a simultaneous inversion of reflectance in two visible channels (0.47 and 0.66 mum) and one shortwave infrared channel (2.12 mum), thereby having increased sensitivity to coarse aerosol. Inversion of the three channels retrieves the aerosol optical depth (tau) at 0.55 mum, the percentage of non-dust (fine model) aerosol (eta) and the surface reflectance. This algorithm is applied globally, and retrieves tau that is highly correlated (y = 0.02 + 1.0x, R=0.9) with ground-based sunphotometer measurements. The new algorithm estimates the global, over-land, long-term averaged tau ˜ 0.21, a 25% reduction from previous MODIS estimates. This leads to reducing estimates of global, non-desert, over-land aerosol direct radiative effect (all aerosols) by 1.7 W·m-2 (0.5 W·m-2 over the entire globe), which significantly impacts assessment of aerosol direct radiative forcing (contribution from anthropogenic aerosols only). Over the U.S. mid-Atlantic region, validated retrievals of tau (an integrated column property) can help to estimate surface PM2.5 concentration, a monitored criteria air quality property. The 3-dimensional aerosol loading in the region is characterized using aircraft measurements and the Community Multi-scale Air Quality Model (CMAQ) model, leading to some convergence of observed quantities and modeled processes.

Lidar Ratios for Dust Aerosols Derived From Retrievals of CALIPSO Visible Extinction Profiles Constrained by Optical Depths from MODIS-Aqua and CALIPSO/CloudSat Ocean Surface Reflectance Measurements

NASA Technical Reports Server (NTRS)

Young, Stuart A.; Josset, Damien B.; Vaughan, Mark A.

2010-01-01

CALIPSO's (Cloud Aerosol Lidar Infrared Pathfinder Satellite Observations) analysis algorithms generally require the use of tabulated values of the lidar ratio in order to retrieve aerosol extinction and optical depth from measured profiles of attenuated backscatter. However, for any given time or location, the lidar ratio for a given aerosol type can differ from the tabulated value. To gain some insight as to the extent of the variability, we here calculate the lidar ratio for dust aerosols using aerosol optical depth constraints from two sources. Daytime measurements are constrained using Level 2, Collection 5, 550-nm aerosol optical depth measurements made over the ocean by the MODIS (Moderate Resolution Imaging Spectroradiometer) on board the Aqua satellite, which flies in formation with CALIPSO. We also retrieve lidar ratios from night-time profiles constrained by aerosol column optical depths obtained by analysis of CALIPSO and CloudSat backscatter signals from the ocean surface.

Observations over Hurricanes from the Ozone Monitoring Instrument

NASA Technical Reports Server (NTRS)

Joiner, J.; Vasilkov, A.; Yang, K.; Bhartia, P. K.

2006-01-01

There is an apparent inconsistency between the total column ozone derived from the total ozone mapping spectrometer (TOMS) and aircraft observations within the eye region of tropical cyclones. The higher spectral resolution, coverage, and sampling of the ozone monitoring instrument (OMI) on NASA s Aura satellite as compared with TOMS allows for improved ozone retrievals by including estimates of cloud pressure derived simultaneously using the effects of rotational Raman scattering. The retrieved cloud pressures from OM1 are more appropriate than the climatological cloud-top pressures based on infrared measurements used in the TOMS and initial OM1 algorithms. We find that total ozone within the eye of hurricane Katrina is significantly overestimated when we use climatological cloud pressures. Using OMI-retrieved cloud pressures, total ozone in the eye is similar to that in the surrounding area. The corrected total ozone is in better agreement with aircraft measurements that imply relatively small or negligible amounts of stratospheric intrusion into the eye region of tropical cyclones.

New Developments in the SCIAMACHY L2 Ground Processor

NASA Astrophysics Data System (ADS)

Gretschany, Sergei; Lichtenberg, Günter; Meringer, Markus; Theys, Nicolas; Lerot, Christophe; Liebing, Patricia; Noel, Stefan; Dehn, Angelika; Fehr, Thorsten

2016-04-01

SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric ChartographY) aboard ESA's environmental satellite ENVISAT observed the Earth's atmosphere in limb, nadir, and solar/lunar occultation geometries covering the UV-Visible to NIR spectral range. It is a joint project of Germany, the Netherlands and Belgium and was launched in February 2002. SCIAMACHY doubled its originally planned in-orbit lifetime of five years before the communication to ENVISAT was severed in April 2012, and the mission entered its post-operational phase. In order to preserve the best quality of the outstanding data recorded by SCIAMACHY, data processors are still being updated. This presentation will highlight three new developments that are currently being incorporated into the forthcoming Version 7 of ESA's operational Level 2 processor: 1. Tropospheric BrO, a new retrieval based on the scientific algorithm of (Theys et al., 2011). This algorithm had been originally developed for the GOME-2 sensor and later adapted for SCIAMACHY. The main principle of the new algorithm is to utilize BrO total columns (already an operational product) and split them into stratospheric VCDstrat and tropospheric VCDtrop fractions. BrO VCDstrat is determined from a climatological approach, driven by SCIAMACHY O3 and NO2 observations. VCDtrop is then determined simply as a difference: VCDtrop = VCDtotal - VCDstrat. 2. Improved cloud flagging using limb measurements (Liebing, 2015). Limb cloud flags are already part of the SCIAMACHY L2 product. They are currently calculated employing the scientific algorithm developed by (Eichmann et al., 2015). Clouds are categorized into four types: water, ice, polar stratospheric and noctilucent clouds. High atmospheric aerosol loadings, however, often lead to spurious cloud flags, when aerosols had been misidentified as clouds. The new algorithm will better discriminate between aerosol and clouds. It will also have a higher sensitivity w.r.t. thin clouds. 3. A new, future-proof file format for the level 2 product based on NetCDF. Although the final concept for the new format is still under discussion within the SCIAMACHY Quality Working Group, main features of the new format have already been clarified. The data format should be aligned and harmonized with other missions (esp. Sentinels and GOME-1). Splitting of the L2 products into profile and column products is also considered. Additionally, reading routines for the new formats will be developed and provided. References: K.-U. Eichmann et al., Global cloud top height retrieval using SCIAMACHY limb spectra: model studies and first results, Atmos. Meas. Tech. Discuss., 8, 8295-8352, 2015. P. Liebing, New Limb Cloud Detection Algorithm Theoretical Basis Document, 2015. N. Theys et al., Global observations of tropospheric BrO columns using GOME-2 satellite data, Atmos. Chem. Phys., 11, 1791-1811, 2011.

Aerosol retrieval experiments in the ESA Aerosol_cci project

NASA Astrophysics Data System (ADS)

Holzer-Popp, T.; de Leeuw, G.; Griesfeller, J.; Martynenko, D.; Klüser, L.; Bevan, S.; Davies, W.; Ducos, F.; Deuzé, J. L.; Graigner, R. G.; Heckel, A.; von Hoyningen-Hüne, W.; Kolmonen, P.; Litvinov, P.; North, P.; Poulsen, C. A.; Ramon, D.; Siddans, R.; Sogacheva, L.; Tanre, D.; Thomas, G. E.; Vountas, M.; Descloitres, J.; Griesfeller, J.; Kinne, S.; Schulz, M.; Pinnock, S.

2013-08-01

Within the ESA Climate Change Initiative (CCI) project Aerosol_cci (2010-2013), algorithms for the production of long-term total column aerosol optical depth (AOD) datasets from European Earth Observation sensors are developed. Starting with eight existing pre-cursor algorithms three analysis steps are conducted to improve and qualify the algorithms: (1) a series of experiments applied to one month of global data to understand several major sensitivities to assumptions needed due to the ill-posed nature of the underlying inversion problem, (2) a round robin exercise of "best" versions of each of these algorithms (defined using the step 1 outcome) applied to four months of global data to identify mature algorithms, and (3) a comprehensive validation exercise applied to one complete year of global data produced by the algorithms selected as mature based on the round robin exercise. The algorithms tested included four using AATSR, three using MERIS and one using PARASOL. This paper summarizes the first step. Three experiments were conducted to assess the potential impact of major assumptions in the various aerosol retrieval algorithms. In the first experiment a common set of four aerosol components was used to provide all algorithms with the same assumptions. The second experiment introduced an aerosol property climatology, derived from a combination of model and sun photometer observations, as a priori information in the retrievals on the occurrence of the common aerosol components. The third experiment assessed the impact of using a common nadir cloud mask for AATSR and MERIS algorithms in order to characterize the sensitivity to remaining cloud contamination in the retrievals against the baseline dataset versions. The impact of the algorithm changes was assessed for one month (September 2008) of data: qualitatively by inspection of monthly mean AOD maps and quantitatively by comparing daily gridded satellite data against daily averaged AERONET sun photometer observations for the different versions of each algorithm globally (land and coastal) and for three regions with different aerosol regimes. The analysis allowed for an assessment of sensitivities of all algorithms, which helped define the best algorithm versions for the subsequent round robin exercise; all algorithms (except for MERIS) showed some, in parts significant, improvement. In particular, using common aerosol components and partly also a priori aerosol-type climatology is beneficial. On the other hand the use of an AATSR-based common cloud mask meant a clear improvement (though with significant reduction of coverage) for the MERIS standard product, but not for the algorithms using AATSR. It is noted that all these observations are mostly consistent for all five analyses (global land, global coastal, three regional), which can be understood well, since the set of aerosol components defined in Sect. 3.1 was explicitly designed to cover different global aerosol regimes (with low and high absorption fine mode, sea salt and dust).

Regional uncertainty of GOSAT XCO2 retrievals in China: quantification and attribution

NASA Astrophysics Data System (ADS)

Bie, Nian; Lei, Liping; Zeng, ZhaoCheng; Cai, Bofeng; Yang, Shaoyuan; He, Zhonghua; Wu, Changjiang; Nassar, Ray

2018-03-01

The regional uncertainty of the column-averaged dry air mole fraction of CO2 (XCO2) retrieved using different algorithms from the Greenhouse gases Observing SATellite (GOSAT) and its attribution are still not well understood. This paper investigates the regional performance of XCO2 within a latitude band of 37-42° N segmented into 8 cells in a grid of 5° from west to east (80-120° E) in China, where typical land surface types and geographic conditions exist. The former includes desert, grassland and built-up areas mixed with cropland; and the latter includes anthropogenic emissions that change from small to large from west to east, including those from the megacity of Beijing. For these specific cells, we evaluate the regional uncertainty of GOSAT XCO2 retrievals by quantifying and attributing the consistency of XCO2 retrievals from four algorithms (ACOS, NIES, OCFP and SRFP) by intercomparison. These retrievals are then specifically compared with simulated XCO2 from the high-resolution nested model in East Asia of the Goddard Earth Observing System 3-D chemical transport model (GEOS-Chem). We also introduce the anthropogenic CO2 emissions data generated from the investigation of surface emitting point sources that was conducted by the Ministry of Environmental Protection of China to GEOS-Chem simulations of XCO2 over the Chinese mainland. The results indicate that (1) regionally, the four algorithms demonstrate smaller absolute biases of 0.7-1.1 ppm in eastern cells, which are covered by built-up areas mixed with cropland with intensive anthropogenic emissions, than those in the western desert cells (1.0-1.6 ppm) with a high-brightness surface from the pairwise comparison results of XCO2 retrievals. (2) Compared with XCO2 simulated by GEOS-Chem (GEOS-XCO2), the XCO2 values from ACOS and SRFP have better agreement, while values from OCFP are the least consistent with GEOS-XCO2. (3) Viewing attributions of XCO2 in the spatio-temporal pattern, ACOS and SRFP demonstrate similar patterns, while OCFP is largely different from the others. In conclusion, the discrepancy in the four algorithms is the smallest in eastern cells in the study area, where the megacity of Beijing is located and where there are strong anthropogenic CO2 emissions, which implies that XCO2 from satellite observations could be reliably applied in the assessment of atmospheric CO2 enhancements induced by anthropogenic CO2 emissions. The large inconsistency among the four algorithms presented in western deserts which displays a high albedo and dust aerosols, moreover, demonstrates that further improvement is still necessary in such regions, even though many algorithms have endeavored to minimize the effects of aerosols scattering and surface albedo.

Retrieval of atmospheric properties from hyper and multispectral imagery with the FLAASH atmospheric correction algorithm

NASA Astrophysics Data System (ADS)

Perkins, Timothy; Adler-Golden, Steven; Matthew, Michael; Berk, Alexander; Anderson, Gail; Gardner, James; Felde, Gerald

2005-10-01

Atmospheric Correction Algorithms (ACAs) are used in applications of remotely sensed Hyperspectral and Multispectral Imagery (HSI/MSI) to correct for atmospheric effects on measurements acquired by air and space-borne systems. The Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) algorithm is a forward-model based ACA created for HSI and MSI instruments which operate in the visible through shortwave infrared (Vis-SWIR) spectral regime. Designed as a general-purpose, physics-based code for inverting at-sensor radiance measurements into surface reflectance, FLAASH provides a collection of spectral analysis and atmospheric retrieval methods including: a per-pixel vertical water vapor column estimate, determination of aerosol optical depth, estimation of scattering for compensation of adjacency effects, detection/characterization of clouds, and smoothing of spectral structure resulting from an imperfect atmospheric correction. To further improve the accuracy of the atmospheric correction process, FLAASH will also detect and compensate for sensor-introduced artifacts such as optical smile and wavelength mis-calibration. FLAASH relies on the MODTRANTM radiative transfer (RT) code as the physical basis behind its mathematical formulation, and has been developed in parallel with upgrades to MODTRAN in order to take advantage of the latest improvements in speed and accuracy. For example, the rapid, high fidelity multiple scattering (MS) option available in MODTRAN4 can greatly improve the accuracy of atmospheric retrievals over the 2-stream approximation. In this paper, advanced features available in FLAASH are described, including the principles and methods used to derive atmospheric parameters from HSI and MSI data. Results are presented from processing of Hyperion, AVIRIS, and LANDSAT data.

Improving UK Air Quality Modelling Through Exploitation of Satellite Observations

NASA Astrophysics Data System (ADS)

Pope, Richard; Chipperfield, Martyn; Savage, Nick

2014-05-01

In this work the applicability of satellite observations to evaluate the operational UK Met Office Air Quality in the Unified Model (AQUM) have been investigated. The main focus involved the AQUM validation against satellite observations, investigation of satellite retrieval error types and of synoptic meteorological-atmospheric chemistry relationships simulated/seen by the AQUM/satellite. The AQUM is a short range forecast model of atmospheric chemistry and aerosols up to 5 days. It has been designed to predict potentially hazardous air pollution events, e.g. high concentrations of surface ozone. The AQUM has only been validated against UK atmospheric chemistry recording surface stations. Therefore, satellite observations of atmospheric chemistry have been used to further validate the model, taking advantage of better satellite spatial coverage. Observations of summer and winter 2006 tropospheric column NO2 from both OMI and SCIAMACHY show that the AQUM generally compares well with the observations. However, in northern England positive biases (AQUM - satellite) suggest that the AQUM overestimates column NO2; we present results of sensitivity experiments on UK emissions datasets suspected to be the cause. In winter, the AQUM over predicts background column NO2 when compared to both satellite instruments. We hypothesise that the cause is the AQUM winter night-time chemistry, where the NO2 sinks are not substantially defined. Satellite data are prone to errors/uncertainty such as random, systematic and smoothing errors. We have investigated these error types and developed an algorithm to calculate and reduce the random error component of DOAS NO2 retrievals, giving more robust seasonal satellite composites. The Lamb Weather Types (LWT), an objective method of classifying the daily synoptic weather over the UK, were used to create composite satellite maps of column NO2 under different synoptic conditions. Under cyclonic conditions, satellite observed UK column NO2 is reduced as the indicative south-westerly flow transports it away from the UK over the North Sea. However, under anticyclonic conditions, the satellite shows that the stable conditions enhance the build-up of column NO2 over source regions. The influence of wind direction on column NO2 can also be seen from space with transport leeward of the source regions.

Comparison of GOME tropospheric NO2 columns with NO2 profiles deduced from ground-based in situ measurements

NASA Astrophysics Data System (ADS)

Schaub, D.; Boersma, K. F.; Kaiser, J. W.; Weiss, A. K.; Folini, D.; Eskes, H. J.; Buchmann, B.

2006-08-01

Nitrogen dioxide (NO2) vertical tropospheric column densities (VTCs) retrieved from the Global Ozone Monitoring Experiment (GOME) are compared to coincident ground-based tropospheric NO2 columns. The ground-based columns are deduced from in situ measurements at different altitudes in the Alps for 1997 to June 2003, yielding a unique long-term comparison of GOME NO2 VTC data retrieved by a collaboration of KNMI (Royal Netherlands Meteorological Institute) and BIRA/IASB (Belgian Institute for Space Aeronomy) with independently derived tropospheric NO2 profiles. A first comparison relates the GOME retrieved tropospheric columns to the tropospheric columns obtained by integrating the ground-based NO2 measurements. For a second comparison, the tropospheric profiles constructed from the ground-based measurements are first multiplied with the averaging kernel (AK) of the GOME retrieval. The second approach makes the comparison independent from the a priori NO2 profile used in the GOME retrieval. This allows splitting the total difference between the column data sets into two contributions: one that is due to differences between the a priori and the ground-based NO2 profile shapes, and another that can be attributed to uncertainties in both the remaining retrieval parameters (such as, e.g., surface albedo or aerosol concentration) and the ground-based in situ NO2 profiles. For anticyclonic clear sky conditions the comparison indicates a good agreement between the columns (n=157, R=0.70/0.74 for the first/second comparison approach, respectively). The mean relative difference (with respect to the ground-based columns) is -7% with a standard deviation of 40% and GOME on average slightly underestimating the ground-based columns. Both data sets show a similar seasonal behaviour with a distinct maximum of spring NO2 VTCs. Further analysis indicates small GOME columns being systematically smaller than the ground-based ones. The influence of different shapes in the a priori and the ground-based NO2 profile is analysed by considering AK information. It is moderate and indicates similar shapes of the profiles for clear sky conditions. Only for large GOME columns, differences between the profile shapes explain the larger part of the relative difference. In contrast, the other error sources give rise to the larger relative differences found towards smaller columns. Further, for the clear sky cases, errors from different sources are found to compensate each other partially. The comparison for cloudy cases indicates a poorer agreement between the columns (n=60, R=0.61). The mean relative difference between the columns is 60% with a standard deviation of 118% and GOME on average overestimating the ground-based columns. The clear improvement after inclusion of AK information (n=60, R=0.87) suggests larger errors in the a priori NO2 profiles under cloudy conditions and demonstrates the importance of using accurate profile information for (partially) clouded scenes.

Utilization of O4 slant column density to derive aerosol layer height from a spaceborne UV-visible hyperspectral sensor: sensitivity and case study

NASA Astrophysics Data System (ADS)

Park, S. S.; Kim, J.; Lee, H.; Torres, O.; Lee, K.-M.; Lee, S. D.

2015-03-01

The sensitivities of oxygen-dimer (O4) slant column densities (SCDs) to changes in aerosol layer height are investigated using simulated radiances by a radiative transfer model, Linearized Discrete Ordinate Radiative Transfer (LIDORT), and Differential Optical Absorption Spectroscopy (DOAS) technique. The sensitivities of the O4 SCDs to aerosol types and optical properties are also evaluated and compared. Among the O4 absorption bands at 340, 360, 380, and 477 nm, the O4 absorption band at 477 nm is found to be the most suitable to retrieve the aerosol effective height. However, the O4 SCD at 477 nm is significantly influenced not only by the aerosol layer effective height but also by aerosol vertical profiles, optical properties including single scattering albedo (SSA), aerosol optical depth (AOD), and surface albedo. Overall, the error of the retrieved aerosol effective height is estimated to be 414 m (16.5%), 564 m (22.4%), and 1343 m (52.5%) for absorbing, dust, and non-absorbing aerosol, respectively, assuming knowledge on the aerosol vertical distribution type. Using radiance data from the Ozone Monitoring Instrument (OMI), a new algorithm is developed to derive the aerosol effective height over East Asia after the determination of the aerosol type and AOD from the MODerate resolution Imaging Spectroradiometer (MODIS). The retrieved aerosol effective heights are lower by approximately 300 m (27 %) compared to those obtained from the ground-based LIDAR measurements.

The Potential of Clear Sky Carbon Dioxide Satellite Retrievals

NASA Astrophysics Data System (ADS)

Nelson, R.; O'Dell, C.

2013-12-01

It has been shown that neglecting scattering and absorption by aerosols and thin clouds can lead to significant errors in retrievals of the column-averaged dry-air mole fraction of carbon dioxide (XCO2) from space-based measurements of near-infrared reflected sunlight. These clear sky retrievals, which assume no aerosol effects, are desirable because of their high computational efficiency relative to common full physics retrievals. Further, clear sky retrievals may be able to make higher quality measurements relative to the full physics approach because they may introduce fewer potential biases under certain circumstances. These biases can appear when we try to retrieve clouds and aerosols in the full physics methods when there are none actually present. Recent work has shown that intelligent pre-screening can remove soundings with large light-path modifications over ocean surfaces. In this work, we test the hypothesis that intelligent pre-screening of soundings may be successfully used over land surfaces as well as oceans, which would allow clear sky retrievals to be applicable over all surfaces. We also test the hypothesis that major light path modification effects associated with aerosols can be identified based on spectral tests at 0.76, 1.6, and 2 microns. This presentation summarizes our study of both simulated data and satellite observations from the GOSAT instrument in order to assess the effectiveness of using a clear sky retrieval algorithm coupled with intelligent pre-screening to accurately measure carbon dioxide from space-borne instruments.

Aerosol algorithm evaluation within aerosol-CCI

NASA Astrophysics Data System (ADS)

Kinne, Stefan; Schulz, Michael; Griesfeller, Jan

Properties of aerosol retrievals from space are difficult. Even data from dedicated satellite sensors face contaminations which limit the accuracy of aerosol retrieval products. Issues are the identification of complete cloud-free scenes, the need to assume aerosol compositional features in an underdetermined solution space and the requirement to characterize the background at high accuracy. Usually the development of aerosol is a slow process, requiring continuous feedback from evaluations. To demonstrate maturity, these evaluations need to cover different regions and seasons and many different aerosol properties, because aerosol composition is quite diverse and highly variable in space and time, as atmospheric aerosol lifetimes are only a few days. Three years ago the ESA Climate Change Initiative started to support aerosol retrieval efforts in order to develop aerosol retrieval products for the climate community from underutilized ESA satellite sensors. The initial focus was on retrievals of AOD (a measure for the atmospheric column amount) and of Angstrom (a proxy for aerosol size) from the ATSR and MERIS sensors on ENVISAT. The goal was to offer retrieval products that are comparable or better in accuracy than commonly used NASA products of MODIS or MISR. Fortunately, accurate reference data of ground based sun-/sky-photometry networks exist. Thus, retrieval assessments could and were conducted independently by different evaluation groups. Here, results of these evaluations for the year 2008 are summarized. The capability of these newly developed retrievals is analyzed and quantified in scores. These scores allowed a ranking of competing efforts and also allow skill comparisons of these new retrievals against existing and commonly used retrievals.

Ozone and Aerosol Retrieval from Backscattered Ultraviolet Radiation

NASA Technical Reports Server (NTRS)

Bhartia, Pawan K.

2012-01-01

In this presentation we will discuss the techniques to estimate total column ozone and aerosol absorption optical depth from the measurements of back scattered ultraviolet (buv) radiation. The total ozone algorithm has been used to create a unique record of the ozone layer, spanning more than 3 decades, from a series of instruments (BUV, SBUV, TOMS, SBUV/2) flown on NASA, NOAA, Japanese and Russian satellites. We will discuss how this algorithm can be considered a generalization of the well-known Dobson/Brewer technique that has been used to process data from ground-based instruments for many decades, and how it differs from the DOAS techniques that have been used to estimate vertical column densities of a host of trace gases from data collected by GOME and SCIAMACHY instruments. The buv aerosol algorithm is most suitable for the detection of UV absorbing aerosols (smoke, desert dust, volcanic ash) and is the only technique that can detect aerosols embedded in clouds. This algorithm has been used to create a quarter century record of aerosol absorption optical depth using the buv data collected by a series of TOMS instruments. We will also discuss how the data from the OMI instrument launched on July 15, 2004 will be combined with data from MODIS and CALIPSO lidar data to enhance the accuracy and information content of satellite-derived aerosol measurements. The OMI and MODIS instruments are currently flying on EOS Aura and EOS Aqua satellites respectively, part of a constellation of satellites called the "A-train".

First Directly Retrieved Global Distribution of Tropospheric Column Ozone from GOME: Comparison with the GEOS-CHEM Model

NASA Technical Reports Server (NTRS)

Liu, Xiong; Chance, Kelly; Sioris, Christopher E.; Kurosu, Thomas P.; Spurr, Robert J. D.; Martin, Randall V.; Fu, Tzung-May; Logan, Jennifer A.; Jacob, Daniel J.; Palmer, Paul I.;

Assessing systematic errors in GOSAT CO2 retrievals by comparing assimilated fields to independent CO2 data

NASA Astrophysics Data System (ADS)

Baker, D. F.; Oda, T.; O'Dell, C.; Wunch, D.; Jacobson, A. R.; Yoshida, Y.; Partners, T.

2012-12-01

Measurements of column CO2 concentration from space are now being taken at a spatial and temporal density that permits regional CO2 sources and sinks to be estimated. Systematic errors in the satellite retrievals must be minimized for these estimates to be useful, however. CO2 retrievals from the TANSO instrument aboard the GOSAT satellite are compared to similar column retrievals from the Total Carbon Column Observing Network (TCCON) as the primary method of validation; while this is a powerful approach, it can only be done for overflights of 10-20 locations and has not, for example, permitted validation of GOSAT data over the oceans or deserts. Here we present a complementary approach that uses a global atmospheric transport model and flux inversion method to compare different types of CO2 measurements (GOSAT, TCCON, surface in situ, and aircraft) at different locations, at the cost of added transport error. The measurements from any single type of data are used in a variational carbon data assimilation method to optimize surface CO2 fluxes (with a CarbonTracker prior), then the corresponding optimized CO2 concentration fields are compared to those data types not inverted, using the appropriate vertical weighting. With this approach, we find that GOSAT column CO2 retrievals from the ACOS project (version 2.9 and 2.10) contain systematic errors that make the modeled fit to the independent data worse. However, we find that the differences between the GOSAT data and our prior model are correlated with certain physical variables (aerosol amount, surface albedo, correction to total column mass) that are likely driving errors in the retrievals, independent of CO2 concentration. If we correct the GOSAT data using a fit to these variables, then we find the GOSAT data to improve the fit to independent CO2 data, which suggests that the useful information in the measurements outweighs the negative impact of the remaining systematic errors. With this assurance, we compare the flux estimates given by assimilating the ACOS GOSAT retrievals to similar ones given by NIES GOSAT column retrievals, bias-corrected in a similar manner. Finally, we have found systematic differences on the order of a half ppm between column CO2 integrals from 18 TCCON sites and those given by assimilating NOAA in situ data (both surface and aircraft profile) in this approach. We assess how these differences change in switching to a newer version of the TCCON retrieval software.

Field Results from Three Campaigns to Validate the Performance of the Miniaturized Laser Heterodyne Radiometer (Mini-LHR) for Measuring Carbon Dioxide and Methane in the Atmospheric Column

NASA Technical Reports Server (NTRS)

Miller, J. Houston; Clarke, Greg B.; Melroy, Hilary; Ott, Lesley; Steel, Emily Wilson

2014-01-01

In a collaboration between NASA GSFC and GWU, a low-cost, surface instrument is being developed that can continuously monitor key carbon cycle gases in the atmospheric column: carbon dioxide (CO2) and methane (CH4). The instrument is based on a miniaturized, laser heterodyne radiometer (LHR) using near infrared (NIR) telecom lasers. Despite relatively weak absorption line strengths in this spectral region, spectrallyresolved atmospheric column absorptions for these two molecules fall in the range of 60-80% and thus sensitive and precise measurements of column concentrations are possible. In the last year, the instrument was deployed for field measurements at Park Falls, Wisconsin; Castle Airport near Atwater, California; and at the NOAA Mauna Loa Observatory in Hawaii. For each subsequent campaign, improvement in the figures of merit for the instrument has been observed. In the latest work the absorbance noise is approaching 0.002 optical density (OD) noise on a 1.8 OD signal. An overview of the measurement campaigns and the data retrieval algorithm for the calculation of column concentrations will be presented. For light transmission through the atmosphere, it is necessary to account for variation of pressure, temperature, composition, and refractive index through the atmosphere that are all functions of latitude, longitude, time of day, altitude, etc. For temperature, pressure, and humidity profiles with altitude we use the Modern-Era Retrospective Analysis for Research and Applications (MERRA) data. Spectral simulation is accomplished by integrating short-path segments along the trajectory using the SpecSyn spectral simulation suite developed at GW. Column concentrations are extracted by minimizing residuals between observed and modeled spectrum using the Nelder-Mead simplex algorithm. We will also present an assessment of uncertainty in the reported concentrations from assumptions made in the meteorological data, LHR instrument and tracker noise, and radio frequency bandwidth and describe additional future goals in instrument development and deployment target

Highlights from the 11-Year Record of Tropospheric Ozone from OMI/MLS and Continuation of that Long Record Using OMPS Measurements

NASA Technical Reports Server (NTRS)

Ziemke, J. R.; Kramarova, N. A.; Bhartia, P. K.; Degenstein, D. A.; Deland, M. T.

2016-01-01

Since October 2004 the Ozone Monitoring Instrument (OMI) and Microwave Limb Sounder (MLS) onboard the Aura satellite have provided over 11 years of continuous tropospheric ozone measurements. These OMI/MLS measurements have been used in many studies to evaluate dynamical and photochemical effects caused by ENSO, the Madden-Julian Oscillation (MJO) and shorter timescales, as well as long-term trends and the effects of deep convection on tropospheric ozone. Given that the OMI and MLS instruments have now extended well beyond their expected lifetimes, our goal is to continue their long record of tropospheric ozone using recent Ozone Mapping Profiler Suite (OMPS) measurements. The OMPS onboard the Suomi National Polar-orbiting Partnership NPP satellite was launched on October 28, 2011 and is comprised of three instruments: the nadir mapper, the nadir profiler, and the limb profiler. Our study combines total column ozone from the OMPS nadir mapper with stratospheric column ozone from the OMPS limb profiler to measure tropospheric ozone residual. The time period for the OMPS measurements is March 2012 present. For the OMPS limb profiler retrievals, the OMPS v2 algorithm from Goddard is tested against the University of Saskatchewan (USask) Algorithm. The retrieved ozone profiles from each of these algorithms are evaluated with ozone profiles from both ozonesondes and the Aura Microwave Limb Sounder (MLS). Effects on derived OMPS tropospheric ozone caused by the 2015-2016 El Nino event are highlighted. This recent El Nino produced anomalies in tropospheric ozone throughout the tropical Pacific involving increases of approximately 10 DU over Indonesia and decreases approximately 5-10 DU in the eastern Pacific. These changes in ozone due to El Nino were predominantly dynamically-induced, caused by the eastward shift in sea-surface temperature and convection from the western to the eastern Pacific.

MGS TES observations of the water vapor above the seasonal and perennial ice caps during northern spring and summer

NASA Astrophysics Data System (ADS)

Pankine, Alexey A.; Tamppari, Leslie K.; Smith, Michael D.

2010-11-01

We report on new retrievals of water vapor column abundances from the Mars Global Surveyor (MGS) Thermal Emission Spectrometer (TES) data. The new retrievals are from the TES nadir data taken above the 'cold' surface areas in the North polar region ( Tsurf < 220 K, including seasonal frost and permanent ice cap) during spring and summer seasons, where retrievals were not performed initially. Retrievals are possible (with some modifications to the original algorithm) over cold surfaces overlaid by sufficiently warm atmosphere. The retrieved water vapor column abundances are compared to the column abundances observed by other spacecrafts in the Northern polar region during spring and summer and good agreement is found. We detect an annulus of water vapor growing above the edge of the retreating seasonal cap during spring. The formation of the vapor annulus is consistent with the previously proposed mechanism for water cycling in the polar region, according to which vapor released by frost sublimation during spring re-condenses on the retreating seasonal CO 2 cap. The source of the vapor in the vapor annulus, according to this model, is the water frost on the surface of the CO 2 at the retreating edge of the cap and the frost on the ground that is exposed by the retreating cap. Small contribution from regolith sources is possible too, but cannot be quantified based on the TES vapor data alone. Water vapor annulus exhibits interannual variability, which we attribute to variations in the atmospheric temperature. We propose that during spring and summer the water ice sublimation is retarded by high relative humidity of the local atmosphere, and that higher atmospheric temperatures lead to higher vapor column abundances by increasing the water holding capacity of the atmosphere. Since the atmospheric temperatures are strongly influenced by the atmospheric dust content, local dust storms may be controlling the release of vapor into the polar atmosphere. Water vapor abundances above the residual polar cap also exhibit noticeable interannual variability. In some years abundances above the cap are lower than the abundances outside of the cap, consistent with previous observations, while in the other years the abundances above the cap are higher or similar to abundances outside of the cap. We speculate that the differences may be due to weaker off-cap transport in the latter case, keeping more vapor closer to the source at the surface of the residual cap. Despite the large observed variability in water vapor column abundances in the Northern polar region during spring and summer, the latitudinal distribution of the vapor mass in the atmosphere is very similar during the summer season. If the variability in vapor abundances is caused by the variability of vapor sources across the residual cap then this would mean that they annually contribute relatively little vapor mass to significantly affect the vapor mass budget. Alternatively this may suggest that the vapor variability is caused by the variability of the polar atmospheric circulation. The new water vapor retrievals should be useful in tuning the Global Circulation Models of the martian water cycle.

MAMAP - a new spectrometer system for column-averaged methane and carbon dioxide observations from aircraft: retrieval algorithm and first inversions for point source emission rates

NASA Astrophysics Data System (ADS)

Krings, T.; Gerilowski, K.; Buchwitz, M.; Reuter, M.; Tretner, A.; Erzinger, J.; Heinze, D.; Burrows, J. P.; Bovensmann, H.

2011-04-01

MAMAP is an airborne passive remote sensing instrument designed for measuring columns of methane (CH4) and carbon dioxide (CO2). The MAMAP instrument consists of two optical grating spectrometers: One in the short wave infrared band (SWIR) at 1590-1690 nm to measure CO2 and CH4 absorptions and another one in the near infrared (NIR) at 757-768 nm to measure O2 absorptions for reference purposes. MAMAP can be operated in both nadir and zenith geometry during the flight. Mounted on an airplane MAMAP can effectively survey areas on regional to local scales with a ground pixel resolution of about 29 m × 33 m for a typical aircraft altitude of 1250 m and a velocity of 200 km h-1. The retrieval precision of the measured column relative to background is typically ≲ 1% (1σ). MAMAP can be used to close the gap between satellite data exhibiting global coverage but with a rather coarse resolution on the one hand and highly accurate in situ measurements with sparse coverage on the other hand. In July 2007 test flights were performed over two coal-fired powerplants operated by Vattenfall Europe Generation AG: Jänschwalde (27.4 Mt CO2 yr-1) and Schwarze Pumpe (11.9 Mt CO2 yr-1), about 100 km southeast of Berlin, Germany. By using two different inversion approaches, one based on an optimal estimation scheme to fit Gaussian plume models from multiple sources to the data, and another using a simple Gaussian integral method, the emission rates can be determined and compared with emissions as stated by Vattenfall Europe. An extensive error analysis for the retrieval's dry column results (XCO2 and XCH4) and for the two inversion methods has been performed. Both methods - the Gaussian plume model fit and the Gaussian integral method - are capable of delivering reliable estimates for strong point source emission rates, given appropriate flight patterns and detailed knowledge of wind conditions.

Retrievals of methane from IASI radiance spectra and comparisons with ground-based FTIR measurements

NASA Astrophysics Data System (ADS)

Kerzenmacher, T.; Kumps, N.; de Mazière, M.; Kruglanski, M.; Senten, C.; Vanhaelewyn, G.; Vandaele, A. C.; Vigouroux, C.

2009-04-01

The Infrared Atmospheric Sounding Interferometer (IASI), launched on 19 October 2006, is a Fourier transform spectrometer onboard METOP-1, observing the radiance of the Earth's surface and atmosphere in nadir mode. The spectral range covers the 645 to 2760 cm-1 region with a resolution of 0.35 to 0.5 cm-1. A line-by-line spectral simulation and inversion code, ASIMUT, has been developed for the retrieval of chemical species from infrared spectra. The code includes an analytical calculation of the Jacobians for use in the inversion part of the algorithm based on the Optimal Estimation Method. In 2007 we conducted a measurement campaign at St Denis, Île de la Réunion where we performed ground-based solar absorption observations with a infrared Fourier transform spectrometer. ASIMUT has been used to retrieve methane from the ground-based and collocated satellite measurements. For the latter we selected pixels that are situated over the sea. In this presentation we will show the retrieval strategies, the resulting methane column time series above St Denis and the comparisons of the satellite data with the ground-based data sets. Vertical profile information in these data sets will also be discussed.

Ozone Climatological Profiles for Version 8 TOMS and SBUV Retrievals

NASA Technical Reports Server (NTRS)

McPeters, R. D.; Logan, J. A.; Labow, G. J.

2003-01-01

A new altitude dependent ozone climatology has been produced for use with the latest Total Ozone Mapping Spectrometer (TOMS) and Solar Backscatter Ultraviolet (SBUV) retrieval algorithms. The climatology consists of monthly average profiles for ten degree latitude zones covering from 0 to 60 km. The climatology was formed by combining data from SAGE II (1988 to 2000) and MLS (1991-1999) with data from balloon sondes (1988-2002). Ozone below about 20 km is based on balloons sondes, while ozone above 30 km is based on satellite measurements. The profiles join smoothly between 20 and 30 km. The ozone climatology in the southern hemisphere and tropics has been greatly enhanced in recent years by the addition of balloon sonde stations under the SHADOZ (Southern Hemisphere Additional Ozonesondes) program. A major source of error in the TOMS and SBUV retrieval of total column ozone comes from their reduced sensitivity to ozone in the lower troposphere. An accurate climatology for the retrieval a priori is important for reducing this error on the average. The new climatology follows the seasonal behavior of tropospheric ozone and reflects its hemispheric asymmetry. Comparisons of TOMS version 8 ozone with ground stations show an improvement due in part to the new climatology.

Detection of carbon monoxide pollution from cities and wildfires on regional and urban scales: the benefit of CO column retrievals from SCIAMACHY 2.3 µm measurements under cloudy conditions

NASA Astrophysics Data System (ADS)

Borsdorff, Tobias; Andrasec, Josip; aan de Brugh, Joost; Hu, Haili; Aben, Ilse; Landgraf, Jochen

2018-05-01

In the perspective of the upcoming TROPOMI Sentinel-5 Precursor carbon monoxide data product, we discuss the benefit of using CO total column retrievals from cloud-contaminated SCIAMACHY 2.3 µm shortwave infrared spectra to detect atmospheric CO enhancements on regional and urban scales due to emissions from cities and wildfires. The study uses the operational Sentinel-5 Precursor algorithm SICOR, which infers the vertically integrated CO column together with effective cloud parameters. We investigate its capability to detect localized CO enhancements distinguishing between clear-sky observations and observations with low (< 1.5 km) and medium-high clouds (1.5-5 km). As an example, we analyse CO enhancements over the cities Paris, Los Angeles and Tehran as well as the wildfire events in Mexico-Guatemala 2005 and Alaska-Canada 2004. The CO average of the SCIAMACHY full-mission data set of clear-sky observations can detect weak CO enhancements of less than 10 ppb due to air pollution in these cities. For low-cloud conditions, the CO data product performs similarly well. For medium-high clouds, the observations show a reduced CO signal both over Tehran and Los Angeles, while for Paris no significant CO enhancement can be detected. This indicates that information about the vertical distribution of CO can be obtained from the SCIAMACHY measurements. Moreover, for the Mexico-Guatemala fires, the low-cloud CO data captures a strong outflow of CO over the Gulf of Mexico and the Pacific Ocean and so provides complementary information to clear-sky retrievals, which can only be obtained over land. For both burning events, enhanced CO values are even detectable with medium-high-cloud retrievals, confirming a distinct vertical extension of the pollution. The larger number of additional measurements, and hence the better spatial coverage, significantly improve the detection of wildfire pollution using both the clear-sky and cloudy CO retrievals. Due to the improved instrument performance of the TROPOMI instrument with respect to its precursor SCIAMACHY, the upcoming Sentinel-5 Precursor CO data product will allow improved detection of CO emissions and their vertical extension over cities and fires, making new research applications possible.

Impacts of Mass-dimension and Area-dimension relationships on retrieval ice particle effective radius from radar and lidar measurements

NASA Astrophysics Data System (ADS)

Ham, S. H.; Kato, S.; Rose, F. G.

2016-12-01

In the retrieval of ice clouds from Radar and Lidar Measurements, mass-Dimension (m-D) and Area-Dimension (A-D) relationships are often used to describe nonspherical ice particle shapes. This study analytically investigates how the assumption of m-D and A-D relationships affects retrieval of ice effective radius. We use gamma and lognormal particle distributions and integrate optical parameters over the size distribution. The effective radius is expressed as a function of radar reflectivity factor, visible extinction coefficient, and parameters describing m-D and A-D relationships. The analytic expressions are used for converting effective radius retrieved from one set of m-D and A-D relationships into that with another set of m-D and A-D, including plates, solid columns, bullets, and mixture of different habits. The conversion method can be used for consistent radiative transfer simulation with cloud retrieval algorithms. In addition, when we want to merge cloud effective radii retrieved from different m-D and A-D, the conversion method can be efficiently used to remove undesired biases caused by m-D and A-D assumptions. Furthermore, the sensitivity of the effective radius to m-D and A-D relationships can be quantified by taking the first derivative of the effective radius with respect to parameters expressing the m-D and A-D relationships.

A Comparison of Aerosol Measurements from OCO-2 and MODIS

NASA Astrophysics Data System (ADS)

Nelson, R. R.; O'Dell, C.

2016-12-01

The goal of OCO-2 is to use hyperspectral measurements of reflected near-infrared sunlight to retrieve carbon dioxide with high accuracy and precision. This is only possible, however, if the light-path modification effects caused by clouds and aerosols are properly quantified. Even tiny amounts of clouds or aerosols can induce sufficient light-path modifications to lead to large errors in the estimated CO2 column-mean (XCO2). Therefore, it is imperative to evaluate the accuracy of the OCO-2 retrieved aerosol parameters. In this study, we compare OCO-2 retrieved aerosol parameters to Aqua-MODIS observations co-located in time and space. We find that there are significant disagreements between the aerosol information derived from MODIS and the retrieved aerosol parameters from OCO-2. These results are unsurprising, as previous comparisons to AERONET have also been poor. However, the tight co-location between Aqua and OCO-2 in the Afternoon Constellation allows us to examine the potential synergistic use of OCO-2 and MODIS measurements to more accurately constrain aerosol properties, potentially leading to a more accurate CO2 measurement. Specifically, we used select MODIS aerosol properties as the a priori for the OCO-2 retrievals and present the results here. Future studies include investigating the possibility of ingesting the MODIS radiances directly into the OCO-2 retrieval algorithm to further improve OCO-2's aerosol scheme and the resulting measurements.

Retrieval Analysis of the CO2 1.6 μm Band in Solar Absorption Spectra Measured by a Ground-Based High-Resolution Fourier Transform Spectrometer at Tsukuba

NASA Astrophysics Data System (ADS)

Ohyama, H.; Morino, I.; Nagahama, T.; Suto, H.; Oguma, H.; Machida, T.; Sugimoto, N.; Nakane, H.; Nakagawa, K.

2006-12-01

The global measurements of greenhouse gases from space are being planned, such as GOSAT (Greenhouse gases Observing SATellite) and OCO (Orbiting Carbon Observatory). Satellite remote sensing needs validations with other measurement techniques, for example, in-situ or sampling measurement by aircraft or ground station, or remote sensing measurement by ground-based Fourier Transform Spectrometer (FTS). The ground-based FTS measurement can provide the column amounts of atmospheric composition by a retrieval analysis with relatively high precision. In 2001, we started a project to observe the atmospheric compositions in solar absorption spectra by a ground- based high-resolution FTS (Bruker IFS 120 HR) located at Tsukuba, Japan. Three years ago, optical components of the FTS were replaced for measuring greenhouse gases such as carbon dioxide (CO2) and methane (CH4) in the near-infrared region: a CaF2 beam splitter, an InSb detector, and a 1.4-2.4 μm optical filter. The measurements were carried out once a day for ~100 days per year. We also made simultaneous FTS and aircraft in-situ measurements on August 10, 2004 and March 30, 2005. The retrieval analysis was performed for the measured spectra in the CO2 1.6 μm band. We used SEASCRAPE PLUS (Sequential Evaluation Algorithm for Simultaneous and Concurrent Retrieval of Atmospheric Parameter Estimates PLUS, Remote Sensing Analysis Systems, Inc.) as a retrieval analysis program. The column amounts were compared with those derived from in-situ measurements complemented by model data; differences are less than 1%. We have derived the diurnal variations of CO2 on the same days as in-situ measurements, and they showed tendencies similar to the tower measurements at the Meteorological Research Institute in Tsukuba.

Orbiting Carbon Observatory-2 (OCO-2) Cloud Screening; Validation Against Collocated MODIS and Initial Comparison to CALIOP Data

NASA Technical Reports Server (NTRS)

Taylor, Thomas E.; O'Dell, Christopher W.; Frankenberg, Christian; Partain, Philip; Cronk, Heather W.; Savtchenko, Andrey; Nelson, Robert R.; Rosenthal, Emily J.; Chang, Albert; Crisp, David;

Assessment of Mixed-Layer Height Estimation from Single-wavelength Ceilometer Profiles.

PubMed

Knepp, Travis N; Szykman, James J; Long, Russell; Duvall, Rachelle M; Krug, Jonathan; Beaver, Melinda; Cavender, Kevin; Kronmiller, Keith; Wheeler, Michael; Delgado, Ruben; Hoff, Raymond; Berkoff, Timothy; Olson, Erik; Clark, Richard; Wolfe, Daniel; Van Gilst, David; Neil, Doreen

2017-01-01

Differing boundary/mixed-layer height measurement methods were assessed in moderately-polluted and clean environments, with a focus on the Vaisala CL51 ceilometer. This intercomparison was performed as part of ongoing measurements at the Chemistry And Physics of the Atmospheric Boundary Layer Experiment (CAPABLE) site in Hampton, Virginia and during the 2014 Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) field campaign that took place in and around Denver, Colorado. We analyzed CL51 data that were collected via two different methods (BLView software, which applied correction factors, and simple terminal emulation logging) to determine the impact of data collection methodology. Further, we evaluated the STRucture of the ATmosphere (STRAT) algorithm as an open-source alternative to BLView (note that the current work presents an evaluation of the BLView and STRAT algorithms and does not intend to act as a validation of either). Filtering criteria were defined according to the change in mixed-layer height (MLH) distributions for each instrument and algorithm and were applied throughout the analysis to remove high-frequency fluctuations from the MLH retrievals. Of primary interest was determining how the different data-collection methodologies and algorithms compare to each other and to radiosonde-derived boundary-layer heights when deployed as part of a larger instrument network. We determined that data-collection methodology is not as important as the processing algorithm and that much of the algorithm differences might be driven by impacts of local meteorology and precipitation events that pose algorithm difficulties. The results of this study show that a common processing algorithm is necessary for LIght Detection And Ranging (LIDAR)-based MLH intercomparisons, and ceilometer-network operation and that sonde-derived boundary layer heights are higher (10-15% at mid-day) than LIDAR-derived mixed-layer heights. We show that averaging the retrieved MLH to 1-hour resolution (an appropriate time scale for a priori data model initialization) significantly improved correlation between differing instruments and differing algorithms.

Evaluation of improved operational standard tropospheric NO2 retrievals from Ozone Monitoring Instrument using in situ and surface-based NO2 observations

NASA Astrophysics Data System (ADS)

Celarier, E. A.; Lamsal, L.; Krotkov, N. A.; Bucsela, E. J.; Herman, J. R.; Dickerson, R. R.; He, H.; Brent, L. C.; Retscher, C.; Swartz, W. H.; Gleason, J. F.

2011-12-01

Nitrogen oxides are key actors in air quality and climate change. Column observations of tropospheric NO2 from the nadir-veiwing satellite sensors have been widely used to understand sources and chemistry of NOx. We have implemented several improvements to the operational algorithm developed at NASA GSFC and retrieved tropospheric NO2. Here we evaluate the new product using in situ surface measurements at the SEARCH, AQS/EPA, and NAPS networks, in situ aircraft (DISCOVER-AQ and RAMMPP), and ground-based PANDORA and DOAS measurements. The agreement among these data is within the uncertainty of measurements. The new OMI tropospheric NO2 product available at high spatial resolution is valuable to evaluate chemical transport models, to examine spatial and temporal pattern of NOx emissions, to provide top-down constraints to surface NOx emissions, and to estimate NOx lifetimes.

Land Surface Temperature Measurements from EOD MODIS Data

NASA Technical Reports Server (NTRS)

Wan, Zheng-Ming

1998-01-01

We made more tests of the version 2.0 daily Level 2 and Level 3 Land-Surface Temperature (LST) code (PGE 16) jointly with the MODIS Science Data Support Team (SDST). After making minor changes a few times, the PGE16 code has been successfully integrated and tested by MODIS SDST, and recently has passed the inspection at the Goddard Distributed Active Archive Center (DAAC). We conducted a field campaign in the area of Mono Lake, California on March 10, 1998, in order to validate the MODIS LST algorithm in cold and dry conditions. Two MODIS Airborne Simulator (MAS) flights were completed during the field campaign, one before noon, and another around 10 pm PST. The weather condition for the daytime flight was perfect: clear sky, the column water vapor measured by radiosonde around 0.3 cm, and wind speed less than a half meter per second. The quality of MAS data is good for both day and night flights. We analyzed the noise equivalent temperature difference (NE(delta)T) and the calibration accuracy of the seven MAS thermal infrared (TIR) bands, that are used in the MODIS day/night LST algorithm, with daytime MAS data over four flat homogeneous study areas: two on Grant Lake (covered with ice and snow, respectively), one on Mono Lake, and another on the snow field site where we made field measurements. NE(delta)T ranges from 0.2 to 0.6 k for bands 42, 45, 46, and 48. It ranges from 0.8 to 1.1 K for bands 30-32. The day and night MAS data have been used to retrieve surface temperature and emissivities in these bands. A simple method to correct the effect of night thin cirrus has been incorporated into the day/night LST algorithm in dry atmospheric conditions. We compared the retrieved surface temperatures with those measured with TIR spectrometer, radiometers and thermistors in the snow test site, and the retrieved emissivity images with topographic map. The daytime LST values match well within 1 K. The night LST retrieved from MAS data is 3.3 K colder than those from field measurements most likely because of the effect of haze at night. The good agreement among the regional averaged surface temperatures obtained from LST values retrieved at different resolutions increased our confidence in the MODIS day/night LST algorithm.

Using Airborne High Spectral Resolution Lidar Data to Evaluate Combined Active Plus Passive Retrievals of Aerosol Extinction Profiles

NASA Technical Reports Server (NTRS)

Burton, S. P.; Ferrare, R. A.; Kittaka, C.; Hostetler, C. A.; Hair, J. W.; Obland, M. D.; Rogers, R. R.; Cook, A. L.; Haper, D. B.

2008-01-01

Aerosol extinction profiles are derived from backscatter data by constraining the retrieval with column aerosol optical thickness (AOT), for example from coincident MODIS observations and without reliance on a priori assumptions about aerosol type or optical properties. The backscatter data were acquired with the NASA Langley High Spectral Resolution Lidar (HSRL). The HSRL also simultaneously measures extinction independently, thereby providing an ideal data set for evaluating the constrained retrieval of extinction from backscatter. We will show constrained extinction retrievals using various sources of column AOT, and examine comparisons with the HSRL extinction measurements and with a similar retrieval using data from the CALIOP lidar on the CALIPSO satellite.

Determination of nocturnal aerosol properties from a combination of lunar photometer and lidar observations

NASA Astrophysics Data System (ADS)

Li, Donghui; Li, Zhengqiang; Lv, Yang; Zhang, Ying; Li, Kaitao; Xu, Hua

2015-10-01

Aerosol plays a key role in the assessment of global climate change and environmental health, while observation is one of important way to deepen the understanding of aerosol properties. In this study, the newly instrument - lunar photometer is used to measure moonlight and nocturnal column aerosol optical depth (AOD, τ) is retrieved. The AOD algorithm is test and verified with sun photometer both in high and low aerosol loading. Ångström exponent (α) and fine/coarse mode AOD (τf, τc) 1 is derived from spectral AOD. The column aerosol properties (τ, α, τf, τc) inferred from the lunar photometer is analyzed based on two month measurement in Beijing. Micro-pulse lidar has advantages in retrieval of aerosol vertical distribution, especially in night. However, the typical solution of lidar equation needs lidar ratio(ratio of aerosol backscatter and extinction coefficient) assumed in advance(Fernald method), or constrained by AOD2. Yet lidar ratio is varied with aerosol type and not easy to fixed, and AOD is used of daylight measurement, which is not authentic when aerosol loading is different from day and night. In this paper, the nocturnal AOD measurement from lunar photometer combined with mie scattering lidar observations to inverse aerosol extinction coefficient(σ) profile in Beijing is discussed.

Above-Cloud Precipitable Water Retrievals using the MODIS 0.94 micron Band with Applications for Multi-Layer Cloud Detection

NASA Technical Reports Server (NTRS)

Platnick, S.; Wind, G.

2004-01-01

In order to perform satellite retrievals of cloud properties, it is important to account for the effect of the above-cloud atmosphere on the observations. The solar bands used in the operational MODIS Terra and Aqua cloud optical and microphysical algorithms (visible, NIR, and SWIR spectral windows) are primarily affected by water vapor, and to a lesser extent by well-mixed gases. For water vapor, the above-cloud column amount, or precipitable water, provides adequate information for an atmospheric correction; details of the vertical vapor distribution are not typically necessary for the level of correction required. Cloud-top pressure has a secondary effect due to pressure broadening influences. For well- mixed gases, cloud-top pressure is also required for estimates of above-cloud abundances. We present a method for obtaining above-cloud precipitable water over dark Ocean surfaces using the MODIS 0.94 pm vapor absorption band. The retrieval includes an iterative procedure for establishing cloud-top temperature and pressure, and is useful for both single layer water and ice clouds. Knowledge of cloud thermodynamic phase is fundamental in retrieving cloud optical and microphysical properties. However, in cases of optically thin cirrus overlapping lower water clouds, the concept of a single unique phase is ill- defined and depends, at least, on the spectral region of interest. We will present a method for multi-layer and multi-phase cloud detection which uses above-cloud precipitable water retrievals along with several existing MODIS operational cloud products (cloud-top pressure derived from a C02 slicing algorithm, IR and SWIR phase retrievals). Results are catagorized by whether the radiative signature in the MODIS solar bands is primarily that of a water cloud with ice cloud contamination, or visa-versa. Examples in polar and mid-latitude regions will be shown.

Adjusted Levenberg-Marquardt method application to methene retrieval from IASI/METOP spectra

NASA Astrophysics Data System (ADS)

Khamatnurova, Marina; Gribanov, Konstantin

2016-04-01

Levenberg-Marquardt method [1] with iteratively adjusted parameter and simultaneous evaluation of averaging kernels together with technique of parameters selection are developed and applied to the retrieval of methane vertical profiles in the atmosphere from IASI/METOP spectra. Retrieved methane vertical profiles are then used for calculation of total atmospheric column amount. NCEP/NCAR reanalysis data provided by ESRL (NOAA, Boulder,USA) [2] are taken as initial guess for retrieval algorithm. Surface temperature, temperature and humidity vertical profiles are retrieved before methane vertical profile retrieval for each selected spectrum. Modified software package FIRE-ARMS [3] were used for numerical experiments. To adjust parameters and validate the method we used ECMWF MACC reanalysis data [4]. Methane columnar values retrieved from cloudless IASI spectra demonstrate good agreement with MACC columnar values. Comparison is performed for IASI spectra measured in May of 2012 over Western Siberia. Application of the method for current IASI/METOP measurements are discussed. 1.Ma C., Jiang L. Some Research on Levenberg-Marquardt Method for the Nonlinear Equations // Applied Mathematics and Computation. 2007. V.184. P. 1032-1040 2.http://www.esrl.noaa.gov/psdhttp://www.esrl.noaa.gov/psd 3.Gribanov K.G., Zakharov V.I., Tashkun S.A., Tyuterev Vl.G.. A New Software Tool for Radiative Transfer Calculations and its application to IMG/ADEOS data // JQSRT.2001.V.68.№ 4. P. 435-451. 4.http://www.ecmwf.int/http://www.ecmwf.int

Retrieval and Analysis of Stratospheric NO2 from GOME

NASA Technical Reports Server (NTRS)

Wenig, M.; Kuehl, S.; Beirle, S.; Wagner, T.; Jaehne, B.; Platt, U.

2003-01-01

In this paper we describe the retrieval of stratospheric NO2 from the GOME (Global Ozone Monitoring Experiment) spectrometer. For this retrieval the Differential Optical Absorption Spectroscopy (DOAS) is used and we describe the influence of the instrument s characteristics on this measurement technique. This analysis led to an improved version of the DOAS algorithm resulting in results with lower systematic errors. Subsequently these results were used to separate the tropospheric and stratospheric fraction of the measured NO;! in the atmosphere. This paper is focusing on the annual variations of the stratospheric distribution of nitrogen oxides. For this examination the satellite data from beginning of 1996 to the end of 2001 was used and has been visualized in a plot zonal means versus time of the year, a visualization which proved to be very useful for Ozone. Additionally the so called "Noxon Cliff", a drop of NO2 column densities Noxon measured in 1975-77 while traveling northwards towards the pole in Canada, is shown. Also its southern equivalent could be discovered in the GOME data.

NOx emission estimates during the 2014 Youth Olympic Games in Nanjing

NASA Astrophysics Data System (ADS)

Ding, J.; van der A, R. J.; Mijling, B.; Levelt, P. F.; Hao, N.

2015-08-01

The Nanjing Government applied temporary environmental regulations to guarantee good air quality during the Youth Olympic Games (YOG) in 2014. We study the effect of those regulations by applying the emission estimate algorithm DECSO (Daily Emission estimates Constrained by Satellite Observations) to measurements of the Ozone Monitoring Instrument (OMI). We improved DECSO by updating the chemical transport model CHIMERE from v2006 to v2013 and by adding an Observation minus Forecast (OmF) criterion to filter outlying satellite retrievals due to high aerosol concentrations. The comparison of model results with both ground and satellite observations indicates that CHIMERE v2013 is better performing than CHIMERE v2006. After filtering the satellite observations with high aerosol loads that were leading to large OmF values, unrealistic jumps in the emission estimates are removed. Despite the cloudy conditions during the YOG we could still see a decrease of tropospheric NO2 column concentrations of about 32 % in the OMI observations when compared to the average NO2 columns from 2005 to 2012. The results of the improved DECSO algorithm for NOx emissions show a reduction of at least 25 % during the YOG period and afterwards. This indicates that air quality regulations taken by the local government have an effect in reducing NOx emissions. The algorithm is also able to detect an emission reduction of 10 % during the Chinese Spring Festival. This study demonstrates the capacity of the DECSO algorithm to capture the change of NOx emissions on a monthly scale. We also show that the observed NO2 columns and the derived emissions show different patterns that provide complimentary information. For example, the Nanjing smog episode in December 2013 led to a strong increase in NO2 concentrations without an increase in NOx emissions. Furthermore, DECSO gives us important information on the non-trivial seasonal relation between NOx emissions and NO2 concentrations on a local scale.

Optimal estimation for global ground-level fine particulate matter concentrations

NASA Astrophysics Data System (ADS)

Donkelaar, Aaron; Martin, Randall V.; Spurr, Robert J. D.; Drury, Easan; Remer, Lorraine A.; Levy, Robert C.; Wang, Jun

2013-06-01

We develop an optimal estimation (OE) algorithm based on top-of-atmosphere reflectances observed by the MODIS satellite instrument to retrieve near-surface fine particulate matter (PM2.5). The GEOS-Chem chemical transport model is used to provide prior information for the Aerosol Optical Depth (AOD) retrieval and to relate total column AOD to PM2.5. We adjust the shape of the GEOS-Chem relative vertical extinction profiles by comparison with lidar retrievals from the CALIOP satellite instrument. Surface reflectance relationships used in the OE algorithm are indexed by land type. Error quantities needed for this OE algorithm are inferred by comparison with AOD observations taken by a worldwide network of sun photometers (AERONET) and extended globally based upon aerosol speciation and cross correlation for simulated values, and upon land type for observational values. Significant agreement in PM2.5 is found over North America for 2005 (slope = 0.89; r = 0.82; 1-σ error = 1 µg/m3 + 27%), with improved coverage and correlation relative to previous work for the same region and time period, although certain subregions, such as the San Joaquin Valley of California are better represented by previous estimates. Independently derived error estimates of the OE PM2.5 values at in situ locations over North America (of ±(2.5 µg/m3 + 31%) and Europe of ±(3.5 µg/m3 + 30%) are corroborated by comparison with in situ observations, although globally (error estimates of ±(3.0 µg/m3 + 35%), may be underestimated. Global population-weighted PM2.5 at 50% relative humidity is estimated as 27.8 µg/m3 at 0.1° × 0.1° resolution.

Impact of NO2 horizontal heterogeneity on tropospheric NO2 vertical columns retrieved from satellite, multi-axis differential optical absorption spectroscopy, and in situ measurements

NASA Astrophysics Data System (ADS)

Mendolia, D.; D'Souza, R. J. C.; Evans, G. J.; Brook, J.

2013-01-01

Tropospheric NO2 vertical column densities were retrieved for the first time in Toronto, Canada using three methods of differing spatial scales. Remotely-sensed NO2 vertical column densities, retrieved from multi-axis differential optical absorption spectroscopy and satellite remote sensing, were evaluated by comparison with in situ vertical column densities derived using a pair of chemiluminescence monitors situated 0.01 and 0.5 km above ground level. The chemiluminescence measurements were corrected for the influence of NOz, which reduced the NO2 concentrations at 0.01 and 0.5 km by 8 ± 1% and 12 ± 1%, respectively. The average absolute decrease in the chemiluminescence NO2 measurement as a result of this correction was less than 1 ppb. Good correlation was observed between the remotely sensed and in situ NO2 vertical column densities (Pearson R ranging from 0.68 to 0.79), but the in situ vertical column densities were 27% to 55% greater than the remotely-sensed columns. These results indicate that NO2 horizontal heterogeneity strongly impacted the magnitude of the remotely-sensed columns. The in situ columns reflected an urban environment with major traffic sources, while the remotely-sensed NO2 vertical column densities were representative of the region, which included spatial heterogeneity introduced by residential neighbourhoods and Lake Ontario. Despite the difference in absolute values, the reasonable correlation between the vertical column densities determined by three distinct methods increased confidence in the validity of the values provided by each of the methods.

Retrieval of Total Ozone Amounts from Zenith-Sky Intensities in the Ultraviolet Region

NASA Technical Reports Server (NTRS)

Bojkov, B. R.; Bhartia, P. K.; Hilsenrath, E.; Labow, G. J.

2004-01-01

A new method to determine the total ozone column from zenith-sky intensities in the ultraviolet region has been developed for the Shuttle Solar Backscatter Ultraviolet Spectrometer (SSBUV) operating at the NASA Goddard Space Flight Center. The total ozone column amounts are derived by comparing the ratio of measured intensities from three wavelengths with the equivalent ratios calculated by a radiative transfer model. The differences between the retrieved ozone column amounts and the collocated Brewer double monochromator are within 2% for the measurement period beginning in April 2001. The methodology, as well as the influences of the ozone profiles, aerosols, surface albedo, and the solar zenith angle on the retrieved total ozone amounts will be presented.

Using Satellite Remote Sensing and Modelling for Insights into N02 Air Pollution and NO2 Emissions

NASA Technical Reports Server (NTRS)

Lamsal, L. N.; Martin, R. V.; Krotkov, N. A.; Bucsela, E. J.; Celarier, E. A.; vanDonkelaar, A.; Parrish, D.

2012-01-01

Nitrogen oxides (NO(x)) are key actors in air quality and climate change. Satellite remote sensing of tropospheric NO2 has developed rapidly with enhanced spatial and temporal resolution since initial observations in 1995. We have developed an improved algorithm and retrieved tropospheric NO2 columns from Ozone Monitoring Instrument. Column observations of tropospheric NO2 from the nadir-viewing satellite sensors contain large contributions from the boundary layer due to strong enhancement of NO2 in the boundary layer. We infer ground-level NO2 concentrations from the OMI satellite instrument which demonstrate significant agreement with in-situ surface measurements. We examine how NO2 columns measured by satellite, ground-level NO2 derived from satellite, and NO(x) emissions obtained from bottom-up inventories relate to world's urban population. We perform inverse modeling analysis of NO2 measurements from OMI to estimate "top-down" surface NO(x) emissions, which are used to evaluate and improve "bottom-up" emission inventories. We use NO2 column observations from OMI and the relationship between NO2 columns and NO(x) emissions from a GEOS-Chem model simulation to estimate the annual change in bottom-up NO(x) emissions. The emission updates offer an improved estimate of NO(x) that are critical to our understanding of air quality, acid deposition, and climate change.

A novel image retrieval algorithm based on PHOG and LSH

NASA Astrophysics Data System (ADS)

Wu, Hongliang; Wu, Weimin; Peng, Jiajin; Zhang, Junyuan

2017-08-01

PHOG can describe the local shape of the image and its relationship between the spaces. The using of PHOG algorithm to extract image features in image recognition and retrieval and other aspects have achieved good results. In recent years, locality sensitive hashing (LSH) algorithm has been superior to large-scale data in solving near-nearest neighbor problems compared with traditional algorithms. This paper presents a novel image retrieval algorithm based on PHOG and LSH. First, we use PHOG to extract the feature vector of the image, then use L different LSH hash table to reduce the dimension of PHOG texture to index values and map to different bucket, and finally extract the corresponding value of the image in the bucket for second image retrieval using Manhattan distance. This algorithm can adapt to the massive image retrieval, which ensures the high accuracy of the image retrieval and reduces the time complexity of the retrieval. This algorithm is of great significance.

SO2 over Central China: Measurements, Numerical Simulations and the Tropospheric Sulfur Budget

NASA Technical Reports Server (NTRS)

He, Hao; Li, Can; Loughner, Christopher P.; Li, Zhangqing; Krotkov, Nickolay A.; Yang, Kai; Wang, Lei; Zheng, Youfei; Bao, Xiangdong; Zhao, Guoqiang;

Simultaneous retrieval of atmospheric CO2 and light path modification from space-based spectroscopic observations of greenhouse gases: methodology and application to GOSAT measurements over TCCON sites.

PubMed

Oshchepkov, Sergey; Bril, Andrey; Yokota, Tatsuya; Yoshida, Yukio; Blumenstock, Thomas; Deutscher, Nicholas M; Dohe, Susanne; Macatangay, Ronald; Morino, Isamu; Notholt, Justus; Rettinger, Markus; Petri, Christof; Schneider, Matthias; Sussman, Ralf; Uchino, Osamu; Velazco, Voltaire; Wunch, Debra; Belikov, Dmitry

2013-02-20

This paper presents an improved photon path length probability density function method that permits simultaneous retrievals of column-average greenhouse gas mole fractions and light path modifications through the atmosphere when processing high-resolution radiance spectra acquired from space. We primarily describe the methodology and retrieval setup and then apply them to the processing of spectra measured by the Greenhouse gases Observing SATellite (GOSAT). We have demonstrated substantial improvements of the data processing with simultaneous carbon dioxide and light path retrievals and reasonable agreement of the satellite-based retrievals against ground-based Fourier transform spectrometer measurements provided by the Total Carbon Column Observing Network (TCCON).

The Star Schema Benchmark and Augmented Fact Table Indexing

NASA Astrophysics Data System (ADS)

O'Neil, Patrick; O'Neil, Elizabeth; Chen, Xuedong; Revilak, Stephen

We provide a benchmark measuring star schema queries retrieving data from a fact table with Where clause column restrictions on dimension tables. Clustering is crucial to performance with modern disk technology, since retrievals with filter factors down to 0.0005 are now performed most efficiently by sequential table search rather than by indexed access. DB2’s Multi-Dimensional Clustering (MDC) provides methods to "dice" the fact table along a number of orthogonal "dimensions", but only when these dimensions are columns in the fact table. The diced cells cluster fact rows on several of these "dimensions" at once so queries restricting several such columns can access crucially localized data, with much faster query response. Unfortunately, columns of dimension tables of a star schema are not usually represented in the fact table. In this paper, we show a simple way to adjoin physical copies of dimension columns to the fact table, dicing data to effectively cluster query retrieval, and explain how such dicing can be achieved on database products other than DB2. We provide benchmark measurements to show successful use of this methodology on three commercial database products.

Ozone and Aerosol Retrieval from Backscattered Ultraviolet Radiation

NASA Technical Reports Server (NTRS)

Bhartia, Pawan K.

2004-01-01

In this presentation we will discuss the techniques to estimate total column ozone and aerosol absorption optical depth from the measurements of backscattered ultraviolet (buv) radiation. The total ozone algorithm has been used to create a unique record of the ozone layer, spanning more than 3 decades, from a series of instruments (BUV, SBUV, TOMS, SBUV/2) flown on NASA, NOAA, Japanese and Russian satellites. We will discuss how this algorithm can be considered a generalization of the well-known Dobson/Brewer technique that has been used to process data from ground-based instruments for many decades, and how it differs from the DOAS techniques that have been used to estimate vertical column densities of a host of trace gases from data collected by GOME and SCIAMACHY instruments. The BUV aerosol algorithm is most suitable for the detection of UV absorbing aerosols (smoke, desert dust, volcanic ash) and is the only technique that can detect aerosols embedded in clouds. This algorithm has been used to create a quarter century record of aerosol absorption optical depth using the BUV data collected by a series of TOMS instruments. We will also discuss how the data from the OM1 instrument launched on July 15,2004 will be combined with data from MODIS and CALIPSO lidar data to enhance the accuracy and information content of satellite-derived aerosol measurements. The OM1 and MODIS instruments are currently flying on EOS Aura and EOS Aqua satellites respectively, part of a constellation of satellites called the "A-train". The CALIPSO satellite is expected to join this constellation in mid 2005.

First comparison of formaldehyde integral contents in ABL retrieved during clear-sky and overcast conditions by ZDOAS technique

NASA Astrophysics Data System (ADS)

Ivanov, Victor; Borovski, Alexander; Postylyakov, Oleg

2017-10-01

Formaldehyde (HCHO) is involved in a lot of chemical reactions in the atmosphere. Taking into account that HCHO basically undergo by photolysis and reaction with hydroxyl radical within a few hours, short-lived VOCs and direct HCHO emissions can cause local HCHO enhancement over certain areas, and, hence, exceeding background level of HCHO can be examined as a local pollution of the atmosphere by VOCs or existence of a local HCHO source. Several retrieval algorithms applicable for DOAS measurements in cloudless were previously developed. In previous works we proposed a new algorithm applicable for the overcast conditions. The algorithm has the typical F-coefficient error of about 10% for winter season, about 5% for summer season, and varying from 15 to 45% for transition season if the atmospheric boundary layer is below the cloud base. In this paper we briefly present our results of the HCHO vertical column retrieval measured at Zvenigorod Scientific Station (ZSS) for overcast. ZSS (55°41'49''N, 36°46'29''E) is located in Moscow region in 38 km west from Moscow. Because Western winds prevail in this region, ZSS is a background station the most part of time. But in cases of Eastern wind, the air quality at ZSS is affected by Moscow megapolis, and polluted air masses formed above Moscow can reach station in a few hours. Due to the absence of alternative overcast data of HCHO, we compare our overcast data with the HCHO vertical content, which we obtained for clear sky. We investigate similarities and differences in their statistical behavior in different air mass. The average overcast HCHO data have similar to clear-sky HCHO positive temperature trends for all wind direction. We found that the average retrieved overcast HCHO contents are systematically greater than the clear-sky retrieval data. But the difference between data retrieved for the overcast and clear-sky conditions are different for Eastern and Western winds. This difference is about 0.5×1016 mol cm-2 for Western winds and about 1.2×1016 mol cm-2 for Eastern winds. We suppose that observed difference between the overcast and clear-sky formaldehyde data can be caused by dependence of chemical reactions leading to the HCHO destruction and the HCHO formation from Moscow anthropogenic predecessors on the cloudy conditions.

Precipitable Water Variability Using SSM/I and GOES VAS Pathfinder Data Sets

NASA Technical Reports Server (NTRS)

Lerner, Jeffrey A.; Jedlovec, Gary J.; Kidder, Stanley Q.

1996-01-01

Determining moisture variability for all weather scenes is critical to understanding the earth's hydrologic cycle and global climate changes. Remote sensing from geostationary satellites provides the necessary temporal and spatial resolutions necessary for global change studies. Due to antenna size constraints imposed with the use of microwave radiometers, geostationary satellites have carried instruments passively measuring radiation at infrared wavelengths or shorter. The shortfall of using infrared instruments in moisture studies lies in its inability to sense terrestrial radiation through clouds. Microwave emissions, on the other hand, are mostly unaffected by cloudy atmospheres. Land surface emissivity at microwave frequencies exhibit both high temporal and spatial variability thus confining moisture retrievals at microwave frequencies to over marine atmospheres (a near uniform cold background). This study intercompares the total column integrated water content Precipitable Water, (PW) as derived from both the Special Sensor Microwave Imager (SSM/I) and the Geostationary Operational Environmental Satellite (GOES) VISSR Atmospheric Sounder (VAS) pathfinder data sets. PW is a bulk parameter often used to quantify moisture variability and is important to understanding the earth's hydrologic cycle and climate system. This research has been spawned in an effort to combine two different algorithms which together can lead to a more comprehensive quantification of global water vapor. The approach taken here is to intercompare two independent PW retrieval algorithms and to validate the resultant retrievals against an existing data set, namely the European Center for Medium range Weather Forecasts (ECMWF) model analysis data.

Monitoring carbon dioxide from space: Retrieval algorithm and flux inversion based on GOSAT data and using CarbonTracker-China

NASA Astrophysics Data System (ADS)

Yang, Dongxu; Zhang, Huifang; Liu, Yi; Chen, Baozhang; Cai, Zhaonan; Lü, Daren

2017-08-01

Monitoring atmospheric carbon dioxide (CO2) from space-borne state-of-the-art hyperspectral instruments can provide a high precision global dataset to improve carbon flux estimation and reduce the uncertainty of climate projection. Here, we introduce a carbon flux inversion system for estimating carbon flux with satellite measurements under the support of "The Strategic Priority Research Program of the Chinese Academy of Sciences—Climate Change: Carbon Budget and Relevant Issues". The carbon flux inversion system is composed of two separate parts: the Institute of Atmospheric Physics Carbon Dioxide Retrieval Algorithm for Satellite Remote Sensing (IAPCAS), and CarbonTracker-China (CT-China), developed at the Chinese Academy of Sciences. The Greenhouse gases Observing SATellite (GOSAT) measurements are used in the carbon flux inversion experiment. To improve the quality of the IAPCAS-GOSAT retrieval, we have developed a post-screening and bias correction method, resulting in 25%-30% of the data remaining after quality control. Based on these data, the seasonal variation of XCO2 (column-averaged CO2 dry-air mole fraction) is studied, and a strong relation with vegetation cover and population is identified. Then, the IAPCAS-GOSAT XCO2 product is used in carbon flux estimation by CT-China. The net ecosystem CO2 exchange is -0.34 Pg C yr-1 (±0.08 Pg C yr-1), with a large error reduction of 84%, which is a significant improvement on the error reduction when compared with in situ-only inversion.

Creating Aerosol Types from CHemistry (CATCH): A New Algorithm to Extend the Link Between Remote Sensing and Models

NASA Astrophysics Data System (ADS)

Dawson, K. W.; Meskhidze, N.; Burton, S. P.; Johnson, M. S.; Kacenelenbogen, M. S.; Hostetler, C. A.; Hu, Y.

2017-11-01

Current remote sensing methods can identify aerosol types within an atmospheric column, presenting an opportunity to incrementally bridge the gap between remote sensing and models. Here a new algorithm was designed for Creating Aerosol Types from CHemistry (CATCH). CATCH-derived aerosol types—dusty mix, maritime, urban, smoke, and fresh smoke—are based on first-generation airborne High Spectral Resolution Lidar (HSRL-1) retrievals during the Ship-Aircraft Bio-Optical Research (SABOR) campaign, July/August 2014. CATCH is designed to derive aerosol types from model output of chemical composition. CATCH-derived aerosol types are determined by multivariate clustering of model-calculated variables that have been trained using retrievals of aerosol types from HSRL-1. CATCH-derived aerosol types (with the exception of smoke) compare well with HSRL-1 retrievals during SABOR with an average difference in aerosol optical depth (AOD) <0.03. Data analysis shows that episodic free tropospheric transport of smoke is underpredicted by the Goddard Earth Observing System- with Chemistry (GEOS-Chem) model. Spatial distributions of CATCH-derived aerosol types for the North American model domain during July/August 2014 show that aerosol type-specific AOD values occurred over representative locations: urban over areas with large population, maritime over oceans, smoke, and fresh smoke over typical biomass burning regions. This study demonstrates that model-generated information on aerosol chemical composition can be translated into aerosol types analogous to those retrieved from remote sensing methods. In the future, spaceborne HSRL-1 and CATCH can be used to gain insight into chemical composition of aerosol types, reducing uncertainties in estimates of aerosol radiative forcing.

Retrieving Volcanic SO2 from the 4-UV channels on DSCOVR/EPIC

NASA Astrophysics Data System (ADS)

Fisher, B. L.; Krotkov, N. A.; Carn, S. A.; Taylor, S.; Li, C.; Bhartia, P. K.; Huang, L. K.; Haffner, D. P.

2017-12-01

Since arriving at the L1 Lagrange point in June 2015, the Earth Polychromatic Imaging Camera (EPIC) on board the Deep Space Climate Observatory (DSCOVR) has been collecting continuous full disk images of the sunlit earth from a distance of 1.5 million km. EPIC is a 10-band spectroradiometer that that has a field of view (FoV) at the earth's surface of about 25 km, providing a unique opportunity to observe the initial appearance and evolution of SO2 plumes from volcanic eruptions at about 90 minute temporal resolution. Our algorithm uses the 317.5, 325, 340 and 388 nm UV channels on EPIC to retrieve volcanic SO2, total column ozone, Lambertian equivalent reflectivity and its spectral dependence. The MS_SO2 algorithm has been successfully applied to the data from legacy and current NASA missions (e.g., Nimbus7/TOMS, SNPP/OMPS, and Aura/OMI). The separation between ozone and SO2 is possible due differences in the cross sections at the two shortest UV channels. The images for each spectral channel are not perfectly aligned due to the earth's rotation, geo-rectification, cloud noise, exposure time and spacecraft jitter. These issues introduce additional noise, for a multi-channel inversion. In this presentation, we describe some modifications to the algorithm that attempt to account for these issues. By comparing the plume areas, mass tonnage and peak SO2 values from other low earth observing satellites, it is shown that the algorithm significantly improves the identification of the plume, while eliminating false positives.

Building the GPM-GV Column from the GPM Cold season Precipitation Experiment (Invited)

NASA Astrophysics Data System (ADS)

Nesbitt, S. W.; Duffy, G. A.; Gleicher, K.; McFarquhar, G. M.; Kulie, M.; Williams, C. R.; Petersen, W. A.; Munchak, S. J.; Tokay, A.; Skofronick Jackson, G.; Chandrasekar, C. V.; Kollias, P.; Hudak, D. R.; Tanelli, S.

2013-12-01

Within the context of the Drop Size Distribution Working Group (DSDWG) of the Global Precipitation Mission-Ground Validation (GPM-GV) program, a major science and satellite precipitation algorithm validation focus is on quantitatively determining the variability of microphysical properties of precipitation in the vertical column, as well as the radiative properties of those particles at GPM-relevant microwave frequencies. The GPM Cold season Precipitation Experiment, or GCPEx, was conducted to address both of these objectives in mid-latitude winter precipitation. Radar observations at C, X, Ku, Ka, and W band from ground based scanning radars, profiling radars, and aircraft, as well as an aircraft passive microwave imager from GCPEx, conducted in early 2012 near Barrie, Ontario, Canada, can be used to constrain the observed reflectivites and brightness temperatures in snow as well as construct radar dual frequency ratios (DFRs) that can be used to identify regimes of microwave radiative properties in observed hydrometeor columns. These data can be directly matched with aircraft and ground based in situ microphysical probes, such as 2-D and bulk aircraft probes and surface disdrometers, to place the microphysical and microwave scattering and emission properties of the snow in context throughout the column of hydrometeors. In this presentation, particle scattering regimes will be identified in GCPEx hydrometeor columns storm events using a clustering technique in a multi-frequency DFR-near Rayleigh radar reflectivity phase space using matched ground-based and aircraft-based radar and passive microwave data. These data will be interpreted using matched in situ disdrometer and aircraft probe microphysical data (particle size distributions, habit identification, fall speed, mass-diameter relationships) derived during the events analyzed. This database is geared towards evaluating scattering simulations and the choice of integral particle size distributions for snow precipitation retrieval algorithms for ground and spaceborne radars at relevant wavelengths. A comparison of results for different cases with varying synoptic forcing and microphysical evolution will be presented.

Overview of SCIAMACHY validation: 2002 2004

NASA Astrophysics Data System (ADS)

Piters, A. J. M.; Bramstedt, K.; Lambert, J.-C.; Kirchhoff, B.

2005-08-01

SCIAMACHY, on board Envisat, is now in operation for almost three years. This UV/visible/NIR spectrometer measures the solar irradiance, the earthshine radiance scattered at nadir and from the limb, and the attenuation of solar radiation by the atmosphere during sunrise and sunset, from 240 to 2380 nm and at moderate spectral resolution. Vertical columns and profiles of a variety of atmospheric constituents are inferred from the SCIAMACHY radiometric measurements by dedicated retrieval algorithms. With the support of ESA and several international partners, a methodical SCIAMACHY validation programme has been developed jointly by Germany, the Netherlands and Belgium (the three instrument providing countries) to face complex requirements in terms of measured species, altitude range, spatial and temporal scales, geophysical states and intended scientific applications. This summary paper describes the approach adopted to address those requirements. The actual validation of the operational SCIAMACHY processors established at DLR on behalf of ESA has been hampered by data distribution and processor problems. Since first data releases in summer 2002, operational processors were upgraded regularly and some data products - level-1b spectra, level-2 O3, NO2, BrO and clouds data - have improved significantly. Validation results summarised in this paper conclude that for limited periods and geographical domains they can already be used for atmospheric research. Nevertheless, remaining processor problems cause major errors preventing from scientific usability in other periods and domains. Untied to the constraints of operational processing, seven scientific institutes (BIRA-IASB, IFE, IUP-Heidelberg, KNMI, MPI, SAO and SRON) have developed their own retrieval algorithms and generated SCIAMACHY data products, together addressing nearly all targeted constituents. Most of the UV-visible data products (both columns and profiles) already have acceptable, if not excellent, quality. Several near-infrared column products are still in development but they have already demonstrated their potential for a variety of applications. In any case, scientific users are advised to read carefully validation reports before using the data. It is required and anticipated that SCIAMACHY validation will continue throughout instrument lifetime and beyond. The actual amount of work will obviously depend on funding considerations.

Eleven years of tropospheric NO2 measured by GOME, SCIAMACHY and OMI

NASA Astrophysics Data System (ADS)

Eskes, H.; Boersma, F.; Dirksen, R.; van der A, R.; Veefkind, P.; Levelt, P.; Brinksma, E.; van Roozendael, M.; de Smedt, I.; Gleason, J.

2006-12-01

Based on measurements of GOME on ESA ERS-2, SCIAMACHY on ESA-ENVISAT, and Ozone Monitoring Instrument (OMI) on the NASA EOS-Aura satellite there is now a unique 11-year dataset of global tropospheric nitrogen dioxide measurements from space. The retrieval approach consists of two steps. The first step is an application of the DOAS (Differential Optical Absorption Spectroscopy) approach which delivers the total absorption optical thickness along the light path (the slant column). For GOME and SCIAMACHY this is based on the DOAS implementation developed by BIRA/IASB. For OMI the DOAS implementation was developed in a collaboration between KNMI and NASA. The second retrieval step, developed at KNMI, estimates the tropospheric vertical column of NO2 based on the slant column, cloud fraction and cloud top height retrieval, stratospheric column estimates derived from a data assimilation approach and vertical profile estimates from space-time collocated profiles from the TM chemistry-transport model. The second step was applied with only minor modifications to all three instruments to generate a uniform 11-year data set. In our talk we will address the following topics: - A short summary of the retrieval approach and results - Comparisons with other retrievals - Comparisons with global and regional-scale models - OMI-SCIAMACHY and SCIAMACHY-GOME comparisons - Validation with independent measurements - Trend studies of NO2 for the past 11 years

Toward Quantitative Estimation of the Effect of Aerosol Particles in the Global Climate Model and Cloud Resolving Model

NASA Astrophysics Data System (ADS)

Eskes, H.; Boersma, F.; Dirksen, R.; van der A, R.; Veefkind, P.; Levelt, P.; Brinksma, E.; van Roozendael, M.; de Smedt, I.; Gleason, J.

2005-05-01

Based on measurements of GOME on ESA ERS-2, SCIAMACHY on ESA-ENVISAT, and Ozone Monitoring Instrument (OMI) on the NASA EOS-Aura satellite there is now a unique 11-year dataset of global tropospheric nitrogen dioxide measurements from space. The retrieval approach consists of two steps. The first step is an application of the DOAS (Differential Optical Absorption Spectroscopy) approach which delivers the total absorption optical thickness along the light path (the slant column). For GOME and SCIAMACHY this is based on the DOAS implementation developed by BIRA/IASB. For OMI the DOAS implementation was developed in a collaboration between KNMI and NASA. The second retrieval step, developed at KNMI, estimates the tropospheric vertical column of NO2 based on the slant column, cloud fraction and cloud top height retrieval, stratospheric column estimates derived from a data assimilation approach and vertical profile estimates from space-time collocated profiles from the TM chemistry-transport model. The second step was applied with only minor modifications to all three instruments to generate a uniform 11-year data set. In our talk we will address the following topics: - A short summary of the retrieval approach and results - Comparisons with other retrievals - Comparisons with global and regional-scale models - OMI-SCIAMACHY and SCIAMACHY-GOME comparisons - Validation with independent measurements - Trend studies of NO2 for the past 11 years

Bayesian aerosol retrieval algorithm for MODIS AOD retrieval over land

NASA Astrophysics Data System (ADS)

Lipponen, Antti; Mielonen, Tero; Pitkänen, Mikko R. A.; Levy, Robert C.; Sawyer, Virginia R.; Romakkaniemi, Sami; Kolehmainen, Ville; Arola, Antti

2018-03-01

We have developed a Bayesian aerosol retrieval (BAR) algorithm for the retrieval of aerosol optical depth (AOD) over land from the Moderate Resolution Imaging Spectroradiometer (MODIS). In the BAR algorithm, we simultaneously retrieve all dark land pixels in a granule, utilize spatial correlation models for the unknown aerosol parameters, use a statistical prior model for the surface reflectance, and take into account the uncertainties due to fixed aerosol models. The retrieved parameters are total AOD at 0.55 µm, fine-mode fraction (FMF), and surface reflectances at four different wavelengths (0.47, 0.55, 0.64, and 2.1 µm). The accuracy of the new algorithm is evaluated by comparing the AOD retrievals to Aerosol Robotic Network (AERONET) AOD. The results show that the BAR significantly improves the accuracy of AOD retrievals over the operational Dark Target (DT) algorithm. A reduction of about 29 % in the AOD root mean square error and decrease of about 80 % in the median bias of AOD were found globally when the BAR was used instead of the DT algorithm. Furthermore, the fraction of AOD retrievals inside the ±(0.05+15 %) expected error envelope increased from 55 to 76 %. In addition to retrieving the values of AOD, FMF, and surface reflectance, the BAR also gives pixel-level posterior uncertainty estimates for the retrieved parameters. The BAR algorithm always results in physical, non-negative AOD values, and the average computation time for a single granule was less than a minute on a modern personal computer.

The influence of aerosols and land-use type on NO2 satellite retrieval over China

NASA Astrophysics Data System (ADS)

Liu, Mengyao; Lin, Jintai; Boersma, Folkert; Eskes, Henk; Chimot, Julien

2017-04-01

Both aerosols and surface reflectance have a strong influence on the retrieval of NO2 tropospheric vertical column densities (VCDs), especially over China with its heavy aerosol loading and rapid changes in land-use type. However, satellite retrievals of NO2 VCDs usually do not explicitly account for aerosol optical effects and surface reflectance anisotropy (BRDF) that varies in space and time. We develop an improved algorithm to derive tropospheric AMFs and VCDs over China from the OMI instrument - POMINO and DOMINO. This method can also be applied to TropOMI NO2 retrievals in the future. With small pixels of TropOMI and higher probability of encountering clear-sky scenes, the influence of BRDF and aerosol interference becomes more important than for OMI. Daily aerosol information is taken from the GEOS-Chem chemistry transport model and the aerosol optical depth (AOD) is adjusted via MODIS AOD climatology. We take the MODIS MCD43C2 C5 product to account for BRDF effects. The relative altitude of NO2 and aerosols is critical factor influencing the NO2 retrieval. In order to evaluate the aerosol extinction profiles (AEP) of GEOS-Chem improve our algorithm, we compare the GEOS-Chem simulation with CALIOP and develop a CALIOP AEP climatology to regulate the model's AEP. This provides a new way to include aerosol information into the tracer gas retrieval for OMI and TropOMI. Preliminary results indicate that the model performs reasonably well in reproducing the AEP shape. However, it seems to overestimate aerosols under 2km and underestimate above. We find that relative humidity (RH) is an important factor influencing the AEP shape when comparing the model with observations. If we adjust the GEOS-Chem RH to CALIOP's RH, the correlations of their AEPs also improve. Besides, take advantage of our retrieval method, we executed sensitivity tests to analyze their influences on NO2 trend and spatiotemporal variations in retrieval. It' the first time to investigate influence from aerosols and surface reflectance in 10-year period (2005-2015) in the real retrieval. We find their influences are largely time and space dependent, but their effects on trend are small, leading relative 7% differences in different areas.

[Investigation on remote measurement of air pollution by a method of infrared passive scanning imaging].

PubMed

Jiao, Yang; Xu, Liang; Gao, Min-Guang; Feng, Ming-Chun; Jin, Ling; Tong, Jing-Jing; Li, Sheng

2012-07-01

Passive remote sensing by Fourier-transform infrared (FTIR) spectrometry allows detection of air pollution. However, for the localization of a leak and a complete assessment of the situation in the case of the release of a hazardous cloud, information about the position and the distribution of a cloud is essential. Therefore, an imaging passive remote sensing system comprising an interferometer, a data acquisition and processing software, scan system, a video system, and a personal computer has been developed. The remote sensing of SF6 was done. The column densities of all directions in which a target compound has been identified may be retrieved by a nonlinear least squares fitting algorithm and algorithm of radiation transfer, and a false color image is displayed. The results were visualized by a video image, overlaid by false color concentration distribution image. The system has a high selectivity, and allows visualization and quantification of pollutant clouds.

The Ozone Mapping and Profiler Suite (OMPS) Limb Profiler (LP) Version 1 aerosol extinction retrieval algorithm: theoretical basis

NASA Astrophysics Data System (ADS)

Loughman, Robert; Bhartia, Pawan K.; Chen, Zhong; Xu, Philippe; Nyaku, Ernest; Taha, Ghassan

2018-05-01

The theoretical basis of the Ozone Mapping and Profiler Suite (OMPS) Limb Profiler (LP) Version 1 aerosol extinction retrieval algorithm is presented. The algorithm uses an assumed bimodal lognormal aerosol size distribution to retrieve aerosol extinction profiles at 675 nm from OMPS LP radiance measurements. A first-guess aerosol extinction profile is updated by iteration using the Chahine nonlinear relaxation method, based on comparisons between the measured radiance profile at 675 nm and the radiance profile calculated by the Gauss-Seidel limb-scattering (GSLS) radiative transfer model for a spherical-shell atmosphere. This algorithm is discussed in the context of previous limb-scattering aerosol extinction retrieval algorithms, and the most significant error sources are enumerated. The retrieval algorithm is limited primarily by uncertainty about the aerosol phase function. Horizontal variations in aerosol extinction, which violate the spherical-shell atmosphere assumed in the version 1 algorithm, may also limit the quality of the retrieved aerosol extinction profiles significantly.

A retrieval algorithm of hydrometer profile for submillimeter-wave radiometer

NASA Astrophysics Data System (ADS)

Liu, Yuli; Buehler, Stefan; Liu, Heguang

2017-04-01

Vertical profiles of particle microphysics perform vital functions for the estimation of climatic feedback. This paper proposes a new algorithm to retrieve the profile of the parameters of the hydrometeor(i.e., ice, snow, rain, liquid cloud, graupel) based on passive submillimeter-wave measurements. These parameters include water content and particle size. The first part of the algorithm builds the database and retrieves the integrated quantities. Database is built up by Atmospheric Radiative Transfer Simulator(ARTS), which uses atmosphere data to simulate the corresponding brightness temperature. Neural network, trained by the precalculated database, is developed to retrieve the water path for each type of particles. The second part of the algorithm analyses the statistical relationship between water path and vertical parameters profiles. Based on the strong dependence existing between vertical layers in the profiles, Principal Component Analysis(PCA) technique is applied. The third part of the algorithm uses the forward model explicitly to retrieve the hydrometeor profiles. Cost function is calculated in each iteration, and Differential Evolution(DE) algorithm is used to adjust the parameter values during the evolutionary process. The performance of this algorithm is planning to be verified for both simulation database and measurement data, by retrieving profiles in comparison with the initial one. Results show that this algorithm has the ability to retrieve the hydrometeor profiles efficiently. The combination of ARTS and optimization algorithm can get much better results than the commonly used database approach. Meanwhile, the concept that ARTS can be used explicitly in the retrieval process shows great potential in providing solution to other retrieval problems.

Highlights of TOMS Version 9 Total Ozone Algorithm

NASA Technical Reports Server (NTRS)

Bhartia, Pawan; Haffner, David

2012-01-01

The fundamental basis of TOMS total ozone algorithm was developed some 45 years ago by Dave and Mateer. It was designed to estimate total ozone from satellite measurements of the backscattered UV radiances at few discrete wavelengths in the Huggins ozone absorption band (310-340 nm). Over the years, as the need for higher accuracy in measuring total ozone from space has increased, several improvements to the basic algorithms have been made. They include: better correction for the effects of aerosols and clouds, an improved method to account for the variation in shape of ozone profiles with season, latitude, and total ozone, and a multi-wavelength correction for remaining profile shape errors. These improvements have made it possible to retrieve total ozone with just 3 spectral channels of moderate spectral resolution (approx. 1 nm) with accuracy comparable to state-of-the-art spectral fitting algorithms like DOAS that require high spectral resolution measurements at large number of wavelengths. One of the deficiencies of the TOMS algorithm has been that it doesn't provide an error estimate. This is a particular problem in high latitudes when the profile shape errors become significant and vary with latitude, season, total ozone, and instrument viewing geometry. The primary objective of the TOMS V9 algorithm is to account for these effects in estimating the error bars. This is done by a straightforward implementation of the Rodgers optimum estimation method using a priori ozone profiles and their error covariances matrices constructed using Aura MLS and ozonesonde data. The algorithm produces a vertical ozone profile that contains 1-2.5 pieces of information (degrees of freedom of signal) depending upon solar zenith angle (SZA). The profile is integrated to obtain the total column. We provide information that shows the altitude range in which the profile is best determined by the measurements. One can use this information in data assimilation and analysis. A side benefit of this algorithm is that it is considerably simpler than the present algorithm that uses a database of 1512 profiles to retrieve total ozone. These profiles are tedious to construct and modify. Though conceptually similar to the SBUV V8 algorithm that was developed about a decade ago, the SBUV and TOMS V9 algorithms differ in detail. The TOMS algorithm uses 3 wavelengths to retrieve the profile while the SBUV algorithm uses 6-9 wavelengths, so TOMS provides less profile information. However both algorithms have comparable total ozone information and TOMS V9 can be easily adapted to use additional wavelengths from instruments like GOME, OMI and OMPS to provide better profile information at smaller SZAs. The other significant difference between the two algorithms is that while the SBUV algorithm has been optimized for deriving monthly zonal means by making an appropriate choice of the a priori error covariance matrix, the TOMS algorithm has been optimized for tracking short-term variability using month and latitude dependent covariance matrices.

Optimization of CO2 Surface Flux using GOSAT Total Column CO2: First Results for 2009-2010

NASA Astrophysics Data System (ADS)

Basu, S.; Houweling, S.

2011-12-01

Constraining surface flux estimates of CO2 using satellite measurements has been one of the long-standing goals of the atmospheric inverse modeling community. We present the first results of inverting GOSAT total column CO2 measurements for obtaining global monthly CO2 flux maps over one year (June 2009 to May 2010). We use the SRON RemoTeC retrieval of CO2 for our inversions. The SRON retrieval has been shown to have no bias when compared to TCCON total column measurements, and latitudinal gradients of the retrieved CO2 are consistent with gradients deduced from the surface flask network [Butz et al, 2011]. This makes this retrieval an ideal candidate for atmospheric inversions, which are highly sensitive to spurious gradients. Our inversion system is analogous to the CarbonTracker (CT) data assimilation system; it is initialized with the prior CO2 fluxes of CT, and uses the same atmospheric transport model, i.e., TM5. The two major differences are (a) we add GOSAT CO2 data to the inversion in addition to flask data, and (b) we use a 4DVAR optimization system instead of a Kalman filter. We compare inversions using (a) only GOSAT total column CO2 measurements, (b) only surface flask CO2 measurements, and (c) the joint data set of GOSAT and surface flask measurements. We validate GOSAT-only inversions against the NOAA surface flask network and joint inversions against CONTRAIL and other aircraft campaigns. We see that inverted fluxes from a GOSAT-only inversion are consistent with fluxes from a stations-only inversion, reaffirming the low biases in SRON retrievals. From the joint inversion, we estimate the amount of added constraints upon adding GOSAT total column measurements to existing surface layer measurements.

OMPS TC EDR Algorithm: Improvement and Verification

NASA Astrophysics Data System (ADS)

Novicki, M.; Sen, B.; Hao, X.; Qu, J. J.

2009-12-01

The Ozone Mapper and Profiler Suite (OMPS) is scheduled to be launched on the NPOESS Preparatory Project (NPP) platform in early 2011. The OMPS will continue monitoring ozone from space, using three instruments, namely the Total Column Mapper (heritage: TOMS), the Nadir Profiler (heritage: SBUV) and the Limb Profiler (heritage: SOLSE/LORE). The Total Column Mapper (TC) sensor images the Earth through a slit, nadir-cell horizontally spaced at 49.5 km cross-track with an along-track reporting interval of 50 km. The total field of view (FOV) cross track is 110 degrees to provide daily global coverage. The TC sensor, a grating spectrometer, provides 0.45 nm spectral sampling across the wavelength range of 300-380 nm. The calibration stability, which is essential to enable long-term ozone monitoring, is maintained by periodic observations of the Sun, using a diffuser to redirect the solar irradiance into the sensor. We describe the data analysis method being presently implemented to retrieve the total column ozone Earth Data Record (EDR) from the radiance data measured by the TC sensor. We discuss the software changes, the test data used to verify the functional performance and the test results.

Pulse retrieval algorithm for interferometric frequency-resolved optical gating based on differential evolution.

PubMed

Hyyti, Janne; Escoto, Esmerando; Steinmeyer, Günter

2017-10-01

A novel algorithm for the ultrashort laser pulse characterization method of interferometric frequency-resolved optical gating (iFROG) is presented. Based on a genetic method, namely, differential evolution, the algorithm can exploit all available information of an iFROG measurement to retrieve the complex electric field of a pulse. The retrieval is subjected to a series of numerical tests to prove the robustness of the algorithm against experimental artifacts and noise. These tests show that the integrated error-correction mechanisms of the iFROG method can be successfully used to remove the effect from timing errors and spectrally varying efficiency in the detection. Moreover, the accuracy and noise resilience of the new algorithm are shown to outperform retrieval based on the generalized projections algorithm, which is widely used as the standard method in FROG retrieval. The differential evolution algorithm is further validated with experimental data, measured with unamplified three-cycle pulses from a mode-locked Ti:sapphire laser. Additionally introducing group delay dispersion in the beam path, the retrieval results show excellent agreement with independent measurements with a commercial pulse measurement device based on spectral phase interferometry for direct electric-field retrieval. Further experimental tests with strongly attenuated pulses indicate resilience of differential-evolution-based retrieval against massive measurement noise.

Satellite remote sensing of aerosol and cloud properties over Eurasia

NASA Astrophysics Data System (ADS)

Sogacheva, Larisa; Kolmonen, Pekka; Saponaro, Giulia; Virtanen, Timo; Rodriguez, Edith; Sundström, Anu-Maija; Atlaskina, Ksenia; de Leeuw, Gerrit

2015-04-01

Satellite remote sensing provides the spatial distribution of aerosol and cloud properties over a wide area. In our studies large data sets are used for statistical studies on aerosol and cloud interaction in an area over Fennoscandia, the Baltic Sea and adjacent regions over the European mainland. This area spans several regimes with different influences on aerosol cloud interaction such as a the transition from relative clean air over Fennoscandia to more anthropogenically polluted air further south, and the influence maritime air over the Baltic and oceanic air advected from the North Atlantic. Anthropogenic pollution occurs in several parts of the study area, and in particular near densely populated areas and megacities, but also in industrialized areas and areas with dense traffic. The aerosol in such areas is quite different from that produced over the boreal forest and has different effects on air quality and climate. Studies have been made on the effects of aerosols on air quality and on the radiation balance in China. The aim of the study is to study the effect of these different regimes on aerosol-cloud interaction using a large aerosol and cloud data set retrieved with the (Advanced) Along Track Scanning Radiometer (A)ATSR Dual View algorithm (ADV) further developed at Finnish Meteorological Institute and aerosol and cloud data provided by MODIS. Retrieval algorithms for aerosol and clouds have been developed for the (A)ATSR, consisting of a series of instruments of which we use the second and third one: ATSR-2 which flew on the ERS-2 satellite (1995-2003) and AATSR which flew on the ENVISAT satellite (2002-2012) (both from the European Space Agency, ESA). The ADV algorithm provides aerosol data on a global scale with a default resolution of 10x10km2 (L2) and an aggregate product on 1x1 degree (L3). Optional, a 1x1 km2 retrieval products is available over smaller areas for specific studies. Since for the retrieval of AOD no prior knowledge is needed on surface properties, the surface reflectance can be independently retrieved using the AOD for atmospheric correction. For the retrieval of cloud properties, the SACURA algorithm has been implemented in the ADV/ASV aerosol retrieval suite. Cloud properties retrieved from AATSR data are cloud fraction, cloud optical thickness, cloud top height, cloud droplet effective radius, liquid water path. Aerosol and cloud properties are applied for different studies over the Eurasia area. Using the simultaneous retrieval of aerosol and cloud properties allows for study of the transition from the aerosol regime to the cloud regime, such as changes in effective radius or AOD (aerosol optical depth) to COT (cloud optical thickness). The column- integrated aerosol extinction, aerosol optical depth or AOD, which is primarily reported from satellite observations, can be used as a proxy for cloud condensation nuclei (CCN) and hence contains information on the ability of aerosol particles to form clouds. Hence, connecting this information with direct observations of cloud properties provides information on aerosol-cloud interactions.

Uncertainties in Cloud Phase and Optical Thickness Retrievals from the Earth Polychromatic Imaging Camera (EPIC)

NASA Technical Reports Server (NTRS)

Meyer, Kerry; Yang, Yuekui; Platnick, Steven

2016-01-01

This paper presents an investigation of the expected uncertainties of a single channel cloud optical thickness (COT) retrieval technique, as well as a simple cloud-temperature-threshold-based thermodynamic phase approach, in support of the Deep Space Climate Observatory (DSCOVR) mission. DSCOVR cloud products will be derived from Earth Polychromatic Imaging Camera (EPIC) observations in the ultraviolet and visible spectra. Since EPIC is not equipped with a spectral channel in the shortwave or mid-wave infrared that is sensitive to cloud effective radius (CER), COT will be inferred from a single visible channel with the assumption of appropriate CER values for liquid and ice phase clouds. One month of Aqua MODIS daytime granules from April 2005 is selected for investigating cloud phase sensitivity, and a subset of these granules that has similar EPIC sun-view geometry is selected for investigating COT uncertainties. EPIC COT retrievals are simulated with the same algorithm as the operational MODIS cloud products (MOD06), except using fixed phase-dependent CER values. Uncertainty estimates are derived by comparing the single channel COT retrievals with the baseline bi-spectral MODIS retrievals. Results show that a single channel COT retrieval is feasible for EPIC. For ice clouds, single channel retrieval errors are minimal (less than 2 percent) due to the particle- size insensitivity of the assumed ice crystal (i.e., severely roughened aggregate of hexagonal columns) scattering properties at visible wavelengths, while for liquid clouds the error is mostly limited to within 10 percent, although for thin clouds (COT less than 2) the error can be higher. Potential uncertainties in EPIC cloud masking and cloud temperature retrievals are not considered in this study.

Uncertainties in cloud phase and optical thickness retrievals from the Earth Polychromatic Imaging Camera (EPIC)

PubMed Central

Meyer, Kerry; Yang, Yuekui; Platnick, Steven

2018-01-01

This paper presents an investigation of the expected uncertainties of a single channel cloud optical thickness (COT) retrieval technique, as well as a simple cloud temperature threshold based thermodynamic phase approach, in support of the Deep Space Climate Observatory (DSCOVR) mission. DSCOVR cloud products will be derived from Earth Polychromatic Imaging Camera (EPIC) observations in the ultraviolet and visible spectra. Since EPIC is not equipped with a spectral channel in the shortwave or mid-wave infrared that is sensitive to cloud effective radius (CER), COT will be inferred from a single visible channel with the assumption of appropriate CER values for liquid and ice phase clouds. One month of Aqua MODIS daytime granules from April 2005 is selected for investigating cloud phase sensitivity, and a subset of these granules that has similar EPIC sun-view geometry is selected for investigating COT uncertainties. EPIC COT retrievals are simulated with the same algorithm as the operational MODIS cloud products (MOD06), except using fixed phase-dependent CER values. Uncertainty estimates are derived by comparing the single channel COT retrievals with the baseline bi-spectral MODIS retrievals. Results show that a single channel COT retrieval is feasible for EPIC. For ice clouds, single channel retrieval errors are minimal (< 2%) due to the particle size insensitivity of the assumed ice crystal (i.e., severely roughened aggregate of hexagonal columns) scattering properties at visible wavelengths, while for liquid clouds the error is mostly limited to within 10%, although for thin clouds (COT < 2) the error can be higher. Potential uncertainties in EPIC cloud masking and cloud temperature retrievals are not considered in this study. PMID:29619116

Uncertainties in cloud phase and optical thickness retrievals from the Earth Polychromatic Imaging Camera (EPIC).

PubMed

Meyer, Kerry; Yang, Yuekui; Platnick, Steven

2016-01-01

This paper presents an investigation of the expected uncertainties of a single channel cloud optical thickness (COT) retrieval technique, as well as a simple cloud temperature threshold based thermodynamic phase approach, in support of the Deep Space Climate Observatory (DSCOVR) mission. DSCOVR cloud products will be derived from Earth Polychromatic Imaging Camera (EPIC) observations in the ultraviolet and visible spectra. Since EPIC is not equipped with a spectral channel in the shortwave or mid-wave infrared that is sensitive to cloud effective radius (CER), COT will be inferred from a single visible channel with the assumption of appropriate CER values for liquid and ice phase clouds. One month of Aqua MODIS daytime granules from April 2005 is selected for investigating cloud phase sensitivity, and a subset of these granules that has similar EPIC sun-view geometry is selected for investigating COT uncertainties. EPIC COT retrievals are simulated with the same algorithm as the operational MODIS cloud products (MOD06), except using fixed phase-dependent CER values. Uncertainty estimates are derived by comparing the single channel COT retrievals with the baseline bi-spectral MODIS retrievals. Results show that a single channel COT retrieval is feasible for EPIC. For ice clouds, single channel retrieval errors are minimal (< 2%) due to the particle size insensitivity of the assumed ice crystal (i.e., severely roughened aggregate of hexagonal columns) scattering properties at visible wavelengths, while for liquid clouds the error is mostly limited to within 10%, although for thin clouds (COT < 2) the error can be higher. Potential uncertainties in EPIC cloud masking and cloud temperature retrievals are not considered in this study.

Uncertainties in cloud phase and optical thickness retrievals from the Earth Polychromatic Imaging Camera (EPIC)

NASA Astrophysics Data System (ADS)

Meyer, Kerry; Yang, Yuekui; Platnick, Steven

2016-04-01

This paper presents an investigation of the expected uncertainties of a single-channel cloud optical thickness (COT) retrieval technique, as well as a simple cloud-temperature-threshold-based thermodynamic phase approach, in support of the Deep Space Climate Observatory (DSCOVR) mission. DSCOVR cloud products will be derived from Earth Polychromatic Imaging Camera (EPIC) observations in the ultraviolet and visible spectra. Since EPIC is not equipped with a spectral channel in the shortwave or mid-wave infrared that is sensitive to cloud effective radius (CER), COT will be inferred from a single visible channel with the assumption of appropriate CER values for liquid and ice phase clouds. One month of Aqua MODerate-resolution Imaging Spectroradiometer (MODIS) daytime granules from April 2005 is selected for investigating cloud phase sensitivity, and a subset of these granules that has similar EPIC Sun-view geometry is selected for investigating COT uncertainties. EPIC COT retrievals are simulated with the same algorithm as the operational MODIS cloud products (MOD06), except using fixed phase-dependent CER values. Uncertainty estimates are derived by comparing the single-channel COT retrievals with the baseline bi-spectral MODIS retrievals. Results show that a single-channel COT retrieval is feasible for EPIC. For ice clouds, single-channel retrieval errors are minimal (< 2 %) due to the particle size insensitivity of the assumed ice crystal (i.e., severely roughened aggregate of hexagonal columns) scattering properties at visible wavelengths, while for liquid clouds the error is mostly limited to within 10 %, although for thin clouds (COT < 2) the error can be higher. Potential uncertainties in EPIC cloud masking and cloud temperature retrievals are not considered in this study.

Evaluation of the Multi-Angle Implementation of Atmospheric Correction (MAIAC) Aerosol Algorithm through Intercomparison with VIIRS Aerosol Products and AERONET

NASA Technical Reports Server (NTRS)

Superczynski, Stephen D.; Kondragunta, Shobha; Lyapustin, Alexei I.

2017-01-01

The Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm is under evaluation for use in conjunction with the Geostationary Coastal and Air Pollution Events (GEO-CAPE) mission. Column aerosol optical thickness (AOT) data from MAIAC are compared against corresponding data. from the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument over North America during 2013. Product coverage and retrieval strategy, along with regional variations in AOT through comparison of both matched and un-matched seasonally gridded data are reviewed. MAIAC shows extended coverage over parts of the continent when compared to VIIRS, owing to its pixel selection process and ability to retrieve aerosol information over brighter surfaces. To estimate data accuracy, both products are compared with AERONET Level 2 measurements to determine the amount of error present and discover if there is any dependency on viewing geometry and/or surface characteristics. Results suggest that MAIAC performs well over this region with a relatively small bias of -0.01; however there is a tendency for greater negative biases over bright surfaces and at larger scattering angles. Additional analysis over an expanded area and longer time period are likely needed to determine a comprehensive assessment of the products capability over the Western Hemisphere. and meet the levels of accuracy needed for aerosol monitoring.

Evaluation of the multi-angle implementation of atmospheric correction (MAIAC) aerosol algorithm through intercomparison with VIIRS aerosol products and AERONET

NASA Astrophysics Data System (ADS)

Superczynski, Stephen D.; Kondragunta, Shobha; Lyapustin, Alexei I.

2017-03-01

The multi-angle implementation of atmospheric correction (MAIAC) algorithm is under evaluation for use in conjunction with the Geostationary Coastal and Air Pollution Events mission. Column aerosol optical thickness (AOT) data from MAIAC are compared against corresponding data from the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument over North America during 2013. Product coverage and retrieval strategy, along with regional variations in AOT through comparison of both matched and unmatched seasonally gridded data, are reviewed. MAIAC shows extended coverage over parts of the continent when compared to VIIRS, owing to its pixel selection process and ability to retrieve aerosol information over brighter surfaces. To estimate data accuracy, both products are compared with Aerosol Robotic Network level 2 measurements to determine the amount of error present and discover if there is any dependency on viewing geometry and/or surface characteristics. Results suggest that MAIAC performs well over this region with a relatively small bias of -0.01; however, there is a tendency for greater negative biases over bright surfaces and at larger scattering angles. Additional analysis over an expanded area and longer time period are likely needed to determine a comprehensive assessment of the products' capability over the Western Hemisphere.

Evaluation of the Multi-Angle Implementation of Atmospheric Correction (MAIAC) Aerosol Algorithm through Intercomparison with VIIRS Aerosol Products and AERONET

PubMed Central

Superczynski, Stephen D.; Kondragunta, Shobha; Lyapustin, Alexei I.

2018-01-01

The Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm is under evaluation for use in conjunction with the Geostationary Coastal and Air Pollution Events (GEO-CAPE) mission. Column aerosol optical thickness (AOT) data from MAIAC are compared against corresponding data from the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument over North America during 2013. Product coverage and retrieval strategy, along with regional variations in AOT through comparison of both matched and un-matched seasonally gridded data are reviewed. MAIAC shows extended coverage over parts of the continent when compared to VIIRS, owing to its pixel selection process and ability to retrieve aerosol information over brighter surfaces. To estimate data accuracy, both products are compared with AERONET Level 2 measurements to determine the amount of error present and discover if there is any dependency on viewing geometry and/or surface characteristics. Results suggest that MAIAC performs well over this region with a relatively small bias of −0.01; however there is a tendency for greater negative biases over bright surfaces and at larger scattering angles. Additional analysis over an expanded area and longer time period are likely needed to determine a comprehensive assessment of the products capability over the Western Hemisphere. PMID:29796366

Evaluation of the Multi-Angle Implementation of Atmospheric Correction (MAIAC) Aerosol Algorithm through Intercomparison with VIIRS Aerosol Products and AERONET.

PubMed

Superczynski, Stephen D; Kondragunta, Shobha; Lyapustin, Alexei I

2017-03-16

The Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm is under evaluation for use in conjunction with the Geostationary Coastal and Air Pollution Events (GEO-CAPE) mission. Column aerosol optical thickness (AOT) data from MAIAC are compared against corresponding data from the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument over North America during 2013. Product coverage and retrieval strategy, along with regional variations in AOT through comparison of both matched and un-matched seasonally gridded data are reviewed. MAIAC shows extended coverage over parts of the continent when compared to VIIRS, owing to its pixel selection process and ability to retrieve aerosol information over brighter surfaces. To estimate data accuracy, both products are compared with AERONET Level 2 measurements to determine the amount of error present and discover if there is any dependency on viewing geometry and/or surface characteristics. Results suggest that MAIAC performs well over this region with a relatively small bias of -0.01; however there is a tendency for greater negative biases over bright surfaces and at larger scattering angles. Additional analysis over an expanded area and longer time period are likely needed to determine a comprehensive assessment of the products capability over the Western Hemisphere.

Investigating evaporation of melting ice particles within a bin melting layer model

NASA Astrophysics Data System (ADS)

Neumann, Andrea J.

Single column models have been used to help develop algorithms for remote sensing retrievals. Assumptions in the single-column models may affect the assumptions of the remote sensing retrievals. Studies of the melting layer that use single column models often assume environments that are near or at water saturation. This study investigates the effects of evaporation upon melting particles to determine whether the assumption of negligible mass loss still holds within subsaturated melting layers. A single column, melting layer model is modified to include the effects of sublimation and evaporation upon the particles. Other changes to the model include switching the order in which the model loops over particle sizes and model layers; including a particle sedimentation scheme; adding aggregation, accretion, and collision and coalescence processes; allowing environmental variables such as the water vapor diffusivity and the Schmidt number to vary with the changes in the environment; adding explicitly calculated particle temperature, changing the particle terminal velocity parameterization; and using a newly-derived effective density-dimensional relationship for use in particle mass calculations. Simulations of idealized melting layer environments show that significant mass loss due to evaporation during melting is possible within subsaturated environments. Short melting distances, accelerating particle fall speeds, and short melting times help constrain the amount of mass lost due to evaporation while melting is occurring, even in subsaturated profiles. Sublimation prior to melting can also be a significant source of mass loss. The trends shown on the particle scale also appear in the bulk distribution parameters such as rainfall rate and ice water content. Simulations incorporating observed melting layer environments show that significant mass loss due to evaporation during the melting process is possible under certain environmental conditions. A profile such as the first melting layer profile on 10 May 2011 from the Midlatitude Continental Convective Clouds Experiment (MC3E) that is neither too saturated nor too subsaturated is possible and shows considerable mass loss for all particle sizes. Most melting layer profiles sampled during MC3E were too saturated for more than a dozen or two of the smallest particle sizes to experience significant mass loss. The aggregation, accretion, and collision and coalescence processes also countered significant mass loss at the largest particles sizes because these particles are efficient at collecting smaller particles due to their relative large sweep-out area. From these results, it appears that the assumption of negligible mass loss due to evaporation while melting is occurring is not always valid. Studies that use large, low-density snowflakes and high RH environments can safely use the assumption of negligible mass loss. Studies that use small ice particles or low RH environments (RH less than about 80%) cannot use the assumption of negligible mass loss due to evaporation. Retrieval algorithms may be overestimating surface precipitation rates and intensities in subsaturated environments due to the assumptions of negligible mass loss while melting and near-saturated melting layer environments.

A microwave satellite water vapour column retrieval for polar winter conditions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Perro, Christopher; Lesins, Glen; Duck, Thomas J.

A new microwave satellite water vapour retrieval for the polar winter atmosphere is presented. The retrieval builds on the work of Miao et al. (2001) and Melsheimer and Heygster (2008), employing auxiliary information for atmospheric conditions and numerical optimization. It was tested using simulated and actual measurements from the Microwave Humidity Sounder (MHS) satellite instruments. Ground truth was provided by the G-band vapour radiometer (GVR) at Barrow, Alaska. For water vapour columns less than 6 kg m -2, comparisons between the retrieval and GVR result in a root mean square (RMS) deviation of 0.39 kg m -2 and a systematic bias of 0.08 kg m -2. These results aremore » compared with RMS deviations and biases at Barrow for the retrieval of Melsheimer and Heygster (2008), the AIRS and MIRS satellite data products, and the ERA-Interim, NCEP, JRA-55, and ASR reanalyses. When applied to MHS measurements, the new retrieval produces a smaller RMS deviation and bias than for the earlier retrieval and satellite data products. The RMS deviations for the new retrieval were comparable to those for the ERA-Interim, JRA-55, and ASR reanalyses; however, the MHS retrievals have much finer horizontal resolution (15 km at nadir) and reveal more structure. The new retrieval can be used to obtain pan-Arctic maps of water vapour columns of unprecedented quality. It may also be applied to measurements from the Special Sensor Microwave/Temperature 2 (SSM/T2), Advanced Microwave Sounding Unit B (AMSU-B), Special Sensor Microwave Imager/Sounder (SSMIS), Advanced Technology Microwave Sounder (ATMS), and Chinese MicroWave Humidity Sounder (MWHS) instruments.« less

High-Accuracy Measurements of Total Column Water Vapor From the Orbiting Carbon Observatory-2

NASA Technical Reports Server (NTRS)

Nelson, Robert R.; Crisp, David; Ott, Lesley E.; O'Dell, Christopher W.

2016-01-01

Accurate knowledge of the distribution of water vapor in Earth's atmosphere is of critical importance to both weather and climate studies. Here we report on measurements of total column water vapor (TCWV) from hyperspectral observations of near-infrared reflected sunlight over land and ocean surfaces from the Orbiting Carbon Observatory-2 (OCO-2). These measurements are an ancillary product of the retrieval algorithm used to measure atmospheric carbon dioxide concentrations, with information coming from three highly resolved spectral bands. Comparisons to high-accuracy validation data, including ground-based GPS and microwave radiometer data, demonstrate that OCO-2 TCWV measurements have maximum root-mean-square deviations of 0.9-1.3mm. Our results indicate that OCO-2 is the first space-based sensor to accurately and precisely measure the two most important greenhouse gases, water vapor and carbon dioxide, at high spatial resolution [1.3 x 2.3 km(exp. 2)] and that OCO-2 TCWV measurements may be useful in improving numerical weather predictions and reanalysis products.

Comparison of Tropical Ozone from SHADOZ with Remote Sensing Retrievals from Suomi-npp Ozone Mapping Profile Suite (OMPS)

NASA Technical Reports Server (NTRS)

Witte, Jacquelyn C.; Thompson, Anne M.; Ziemke, Jerald R.; Wargan, Krzysztof

2014-01-01

The Ozone Mapping Profile Suite (OMPS) was launched October 28, 2011 on-board the Suomi NPP satellite (http://npp.gsfc.nasa.gov). OMPS is the next generation total column ozone mapping instrument for monitoring the global distribution of stratospheric ozone. OMPS includes a limb profiler to measure the vertical structure of stratosphere ozone down to the mid-troposphere. This study uses tropical ozonesonde profile measurements from the Southern Hemisphere Additional Ozonesondes (SHADOZ, http://croc.gsfc.nasa.gov/shadoz) archive to evaluate total column ozone retrievals from OMPS and concurrent measurements from the Aura Ozone Monitoring Instrument (OMI), the predecessor of OMPS with a data record going back to 2004. We include ten SHADOZ stations that contain data overlapping the OMPS time period (2012-2013). This study capitalizes on the ozone profile measurements from SHADOZ to evaluate OMPS limb profile retrievals. Finally, we use SHADOZ sondes and OMPS retrievals to examine the agreement with the GEOS-5 Ozone Assimilation System (GOAS). The GOAS uses data from the OMI and the Microwave Limb Sounder (MLS) to constrain the total column and stratospheric profiles of ozone. The most recent version of the assimilation system is well constrained to the total column compared with SHADOZ ozonesonde data.

Utilization of O4 slant column density to derive aerosol layer height from a space-borne UV-visible hyperspectral sensor: sensitivity and case study

NASA Astrophysics Data System (ADS)

Park, Sang Seo; Kim, Jhoon; Lee, Hanlim; Torres, Omar; Lee, Kwang-Mog; Lee, Sang Deok

2016-02-01

The sensitivities of oxygen-dimer (O4) slant column densities (SCDs) to changes in aerosol layer height are investigated using the simulated radiances by a radiative transfer model, the linearized pseudo-spherical vector discrete ordinate radiative transfer (VLIDORT), and the differential optical absorption spectroscopy (DOAS) technique. The sensitivities of the O4 index (O4I), which is defined as dividing O4 SCD by 1040 molecules2 cm-5, to aerosol types and optical properties are also evaluated and compared. Among the O4 absorption bands at 340, 360, 380, and 477 nm, the O4 absorption band at 477 nm is found to be the most suitable to retrieve the aerosol effective height. However, the O4I at 477 nm is significantly influenced not only by the aerosol layer effective height but also by aerosol vertical profiles, optical properties including single scattering albedo (SSA), aerosol optical depth (AOD), particle size, and surface albedo. Overall, the error of the retrieved aerosol effective height is estimated to be 1276, 846, and 739 m for dust, non-absorbing, and absorbing aerosol, respectively, assuming knowledge on the aerosol vertical distribution shape. Using radiance data from the Ozone Monitoring Instrument (OMI), a new algorithm is developed to derive the aerosol effective height over East Asia after the determination of the aerosol type and AOD from the MODerate resolution Imaging Spectroradiometer (MODIS). About 80 % of retrieved aerosol effective heights are within the error range of 1 km compared to those obtained from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) measurements on thick aerosol layer cases.

Validation of GOSAT XCO2 and XCH4 retrieved by PPDF-S method and evaluation of sensitivity of aerosols to gas concentrations

NASA Astrophysics Data System (ADS)

Iwasaki, C.; Imasu, R.; Bril, A.; Yokota, T.; Yoshida, Y.; Morino, I.; Oshchepkov, S.; Rokotyan, N.; Zakharov, V.; Gribanov, K.

2017-12-01

Photon path length probability density function-Simultaneous (PPDF-S) method is one of effective algorithms for retrieving column-averaged concentrations of carbon dioxide (XCO2) and methane (XCH4) from Greenhouse gases Observing SATellite (GOSAT) spectra in Short Wavelength InfraRed (SWIR) [Oshchepkov et al., 2013]. In this study, we validated XCO2 and XCH4 retrieved by the PPDF-S method through comparison with the Total Carbon Column Observing Network (TCCON) data [Wunch et al., 2011] from 26 sites including additional site of the Ural Atmospheric Station at Kourovka [57.038°N and 59.545°E], Russia. Validation results using TCCON data show that bias and its standard deviation of PPDF-S data are respectively 0.48 and 2.10 ppm for XCO2, and -0.73 and 15.77 ppb for XCH4. The results for XCO2 are almost identical with those of Iwasaki et al. [2017] for which the validation data were limited at selected 11 sites. However, the bias of XCH4 shows opposite sign against that of Iwasaki et al. [2017]. Furthermore, the data at Kourouvka showed different features particularly for XCH4. In order to investigate the causes for the differences, we have carried out simulation studies mainly focusing on the effects of aerosols which modify the light path length of solar radiation [O'Brien and Rayner, 2002; Aben et al., 2007; Oshchepkov et al., 2008]. Based on the simulation studies using multiple radiation transfer code based on Discrete Ordinate Method (DOM), Polarization System for Transfer of Atmospheric Radiation3 (Pstar3) [Ota et al., 2010], sensitivity of aerosols to gas concentrations was examined.

Utilization of O4 Slant Column Density to Derive Aerosol Layer Height from a Space-Borne UV-Visible Hyperspectral Sensor: Sensitivity and Case Study

NASA Technical Reports Server (NTRS)

Park, Sang Seo; Kim, Jhoon; Lee, Hanlim; Torres, Omar; Lee, Kwang-Mog; Lee, Sang Deok

2016-01-01

The sensitivities of oxygen-dimer (O4) slant column densities (SCDs) to changes in aerosol layer height are investigated using the simulated radiances by a radiative transfer model, the linearized pseudo-spherical vector discrete ordinate radiative transfer (VLIDORT), and the differential optical absorption spectroscopy (DOAS) technique. The sensitivities of the O4 index (O4I), which is defined as dividing O4 SCD by 10(sup 40) molecules (sup 2) per centimeters(sup -5), to aerosol types and optical properties are also evaluated and compared. Among the O4 absorption bands at 340, 360, 380, and 477 nanometers, the O4 absorption band at 477 nanometers is found to be the most suitable to retrieve the aerosol effective height. However, the O4I at 477 nanometers is significantly influenced not only by the aerosol layer effective height but also by aerosol vertical profiles, optical properties including single scattering albedo (SSA), aerosol optical depth (AOD), particle size, and surface albedo. Overall, the error of the retrieved aerosol effective height is estimated to be 1276, 846, and 739 meters for dust, non-absorbing, and absorbing aerosol, respectively, assuming knowledge on the aerosol vertical distribution shape. Using radiance data from the Ozone Monitoring Instrument (OMI), a new algorithm is developed to derive the aerosol effective height over East Asia after the determination of the aerosol type and AOD from the MODerate resolution Imaging Spectroradiometer (MODIS). About 80 percent of retrieved aerosol effective heights are within the error range of 1 kilometer compared to those obtained from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) measurements on thick aerosol layer cases.

Utilization of O4 Slant Column Density to Derive Aerosol Layer Height from a Spaceborne UV-Visible Hyperspectral Sensor: Sensitivity and Case Study

NASA Technical Reports Server (NTRS)

Park, Sang Seo; Kim, Jhoon; Lee, Hanlim; Torres, Omar; Lee, Kwang-Mog; Lee, Sang Deok

2016-01-01

The sensitivities of oxygen-dimer (O4) slant column densities (SCDs) to changes in aerosol layer height are investigated using the simulated radiances by a radiative transfer model, the linearized pseudo-spherical vector discrete ordinate radiative transfer (VLIDORT), and the Differential Optical Absorption Spectroscopy (DOAS) technique. The sensitivities of the O4 index (O4I), which is defined as dividing O4 SCD by 10(exp 40) sq molecules cm(exp -5), to aerosol types and optical properties are also evaluated and compared. Among the O4 absorption bands at 340, 360, 380, and 477 nm, the O4 absorption band at 477 nm is found to be the most suitable to retrieve the aerosol effective height. However, the O4I at 477 nm is significantly influenced not only by the aerosol layer effective height but also by aerosol vertical profiles, optical properties including single scattering albedo (SSA), aerosol optical depth (AOD), particle size, and surface albedo. Overall, the error of the retrieved aerosol effective height is estimated to be 1276, 846, and 739 m for dust, non-absorbing, and absorbing aerosol, respectively, assuming knowledge on the aerosol vertical distribution shape. Using radiance data from the Ozone Monitoring Instrument (OMI), a new algorithm is developed to derive the aerosol effective height over East Asia after the determination of the aerosol type and AOD from the MODerate resolution Imaging Spectroradiometer (MODIS). About 80% of retrieved aerosol effective heights are within the error range of 1 km compared to those obtained from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) measurements on thick aerosol layer cases.

Assessment of Mixed-Layer Height Estimation from Single-wavelength Ceilometer Profiles

PubMed Central

Knepp, Travis N.; Szykman, James J.; Long, Russell; Duvall, Rachelle M.; Krug, Jonathan; Beaver, Melinda; Cavender, Kevin; Kronmiller, Keith; Wheeler, Michael; Delgado, Ruben; Hoff, Raymond; Berkoff, Timothy; Olson, Erik; Clark, Richard; Wolfe, Daniel; Van Gilst, David; Neil, Doreen

2018-01-01

Differing boundary/mixed-layer height measurement methods were assessed in moderately-polluted and clean environments, with a focus on the Vaisala CL51 ceilometer. This intercomparison was performed as part of ongoing measurements at the Chemistry And Physics of the Atmospheric Boundary Layer Experiment (CAPABLE) site in Hampton, Virginia and during the 2014 Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) field campaign that took place in and around Denver, Colorado. We analyzed CL51 data that were collected via two different methods (BLView software, which applied correction factors, and simple terminal emulation logging) to determine the impact of data collection methodology. Further, we evaluated the STRucture of the ATmosphere (STRAT) algorithm as an open-source alternative to BLView (note that the current work presents an evaluation of the BLView and STRAT algorithms and does not intend to act as a validation of either). Filtering criteria were defined according to the change in mixed-layer height (MLH) distributions for each instrument and algorithm and were applied throughout the analysis to remove high-frequency fluctuations from the MLH retrievals. Of primary interest was determining how the different data-collection methodologies and algorithms compare to each other and to radiosonde-derived boundary-layer heights when deployed as part of a larger instrument network. We determined that data-collection methodology is not as important as the processing algorithm and that much of the algorithm differences might be driven by impacts of local meteorology and precipitation events that pose algorithm difficulties. The results of this study show that a common processing algorithm is necessary for LIght Detection And Ranging (LIDAR)-based MLH intercomparisons, and ceilometer-network operation and that sonde-derived boundary layer heights are higher (10–15% at mid-day) than LIDAR-derived mixed-layer heights. We show that averaging the retrieved MLH to 1-hour resolution (an appropriate time scale for a priori data model initialization) significantly improved correlation between differing instruments and differing algorithms. PMID:29682087

Progress status of the GOSAT and GOSAT-2 SWIR L2 products

NASA Astrophysics Data System (ADS)

Yoshida, Y.; Oshio, H.; Kamei, A.; Morino, I.; Uchino, O.; Saito, M.; Noda, H.; Matsunaga, T.

2017-12-01

The Greenhouse gases Observing SATellite (GOSAT) has been operating for more than eight years, and the column-averaged dry air mole fractions of carbon dioxide, methane, and water vapor (XCO2, XCH4, and XH2O; hereafter called Xgas) have been retrieved globally from the Short-Wavelength InfraRed (SWIR) spectral data (0.76 μm, 1.6 μm, and 2.0 μm bands) observed with Thermal And Near-infrared Sensor for carbon Observation Fourier Transform Spectrometer (TANSO-FTS) onboard GOSAT. Xgas are simultaneously retrieved using a so-called full-physics retrieval method. The retrieval results are released as the FTS SWIR L2 product and available via GOSAT Data Archive Service (GDAS; https://data2.gosat.nies.go.jp/). During the TANSO-FTS operation, several issues were found, and some of them made small changes to the characteristics of the spectral data. Therefore, current SWIR L2 product has several minor versions as V02.xx to distinguish possible retrieval quality difference. To provide long-term uniform quality spectra, JAXA reprocessed whole spectral data as FTS L1B V201.202. We have been re-evaluating the characteristics of the new spectral data, and results will be reflected to the next major version up of the SWIR L2 products (V03). As a successor mission to the GOSAT, GOSAT-2 is planned to be launched in FY2018. According to the latest design of the TANSO-FTS-2 (FTS onboard the GOSAT-2), its SNR is higher than or almost equal to the TANSO-FTS, and its spectral range is expanded to cover the 2.3 μm carbon monoxide (CO) band. The SWIR L2 retrieval algorithm for GOSAT-2 is developing based on the latest retrieval algorithm for GOSAT. Our preliminary sensitivity test based on the designed specification shows that the SNR improvement in SWIR bands reduces the retrieval random error (precision) about 15% for XCO2 and 35% for XCH4 than those of GOSAT. In addition to the full-physics based XCO2, XCH4, XH2O, and XCO products, we are planning to provide the proxy-based XCH4 product as well as solar induced chlorophyll fluorescence (SIF) product.

Status of GeoTASO Trace Gas Data Analysis for the KORUS-AQ Campaign

NASA Astrophysics Data System (ADS)

Janz, S. J.; Nowlan, C. R.; Lamsal, L. N.; Kowalewski, M. G.; Judd, L. M.; Wang, J.

2017-12-01

The Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) instrument measures spectrally resolved backscattered solar radiation at high spatial resolution. The instrument completed 30 sorties on board the NASA LaRC UC-12 aircraft during the KORUS-AQ deployment in May-June of 2016. GeoTASO collects spatially resolved spectra with sufficient sensitivity to retrieve column amounts of the trace gas molecules NO2, SO2, H2CO, O3, and C2H2O2 as well as aerosol products. Typical product retrievals are done in 250 m2 bins with multiple overpasses of key ground sites, allowing for detailed spatio-temporal analysis. Flight patterns consisted of both contiguous overlapping grid patterns to simulate satellite observational strategies in support of future geostationary satellite algorithm development, and "race-track" sampling to perform calibration and validation with the in-situ DC-8 platform as well as ground based assets. We will summarize the status of the radiance data set as well as ongoing analysis from our co-Investigators.

Observations of Ultraviolet Emission from Mg+ in the Lower and Middle Thermosphere

NASA Astrophysics Data System (ADS)

Minschwaner, K.; Shukla, N.; Fortna, C.; Budzien, S.; Dymond, K.; McCoy, R.

2004-12-01

New observations of ionized magnesium dayglow are reported from the Ionospheric Spectroscopy and Atmospheric Chemistry (ISAAC) instrument on the ARGOS satellite. We focused on two periods, October 14-28 1999 and November 15-30 1999, when ISAAC obtained high quality limb spectra between 2600 and 3000 Å and from 85 to 350 km tangent altitude. In addition to the resonant scattering by Mg+ near 2800 Å, these limb spectra also contain signatures of fluorescent scattering by nitric oxide in the gamma bands, emission by molecular nitrogen in the Vergard-Kaplan bands, and atomic emission by oxygen in the 2972 Å line. A retrieval algorithm has been developed to measure the abundance of nitric oxide using the intensity of fluorescent scattering in the γ (1,5) band at 2670 Å. This technique then allows for separating the overlapping emission by nitric oxide in the γ (1,6) band from the Mg+ doublet at 2800 Å. Retrieved Mg+ column densities have been mapped as a function of altitude and geomagnetic latitude.

Algorithms and sensitivity analyses for Stratospheric Aerosol and Gas Experiment II water vapor retrieval

NASA Technical Reports Server (NTRS)

Chu, W. P.; Chiou, E. W.; Larsen, J. C.; Thomason, L. W.; Rind, D.; Buglia, J. J.; Oltmans, S.; Mccormick, M. P.; Mcmaster, L. M.

1993-01-01

The operational inversion algorithm used for the retrieval of the water-vapor vertical profiles from the Stratospheric Aerosol and Gas Experiment II (SAGE II) occultation data is presented. Unlike the algorithm used for the retrieval of aerosol, O3, and NO2, the water-vapor retrieval algorithm accounts for the nonlinear relationship between the concentration versus the broad-band absorption characteristics of water vapor. Problems related to the accuracy of the computational scheme, the accuracy of the removal of other interfering species, and the expected uncertainty of the retrieved profile are examined. Results are presented on the error analysis of the SAGE II water vapor retrieval, indicating that the SAGE II instrument produced good quality water vapor data.

Comparative Results of AIRS AMSU and CrIS/ATMS Retrievals Using a Scientifically Equivalent Retrieval Algorithm

NASA Technical Reports Server (NTRS)

Susskind, Joel; Kouvaris, Louis; Iredell, Lena

2016-01-01

The AIRS Science Team Version 6 retrieval algorithm is currently producing high quality level-3 Climate Data Records (CDRs) from AIRSAMSU which are critical for understanding climate processes. The AIRS Science Team is finalizing an improved Version-7 retrieval algorithm to reprocess all old and future AIRS data. AIRS CDRs should eventually cover the period September 2002 through at least 2020. CrISATMS is the only scheduled follow on to AIRSAMSU. The objective of this research is to prepare for generation of a long term CrISATMS level-3 data using a finalized retrieval algorithm that is scientifically equivalent to AIRSAMSU Version-7.

A Physical Model to Estimate Snowfall over Land using AMSU-B Observations

NASA Technical Reports Server (NTRS)

Kim, Min-Jeong; Weinman, J. A.; Olson, W. S.; Chang, D.-E.; Skofronick-Jackson, G.; Wang, J. R.

2008-01-01

In this study, we present an improved physical model to retrieve snowfall rate over land using brightness temperature observations from the National Oceanic and Atmospheric Administration's (NOAA) Advanced Microwave Sounder Unit-B (AMSU-B) at 89 GHz, 150 GHz, 183.3 +/- 1 GHz, 183.3 +/- 3 GHz, and 183.3 +/- 7 GHz. The retrieval model is applied to the New England blizzard of March 5, 2001 which deposited about 75 cm of snow over much of Vermont, New Hampshire, and northern New York. In this improved physical model, prior retrieval assumptions about snowflake shape, particle size distributions, environmental conditions, and optimization methodology have been updated. Here, single scattering parameters for snow particles are calculated with the Discrete-Dipole Approximation (DDA) method instead of assuming spherical shapes. Five different snow particle models (hexagonal columns, hexagonal plates, and three different kinds of aggregates) are considered. Snow particle size distributions are assumed to vary with air temperature and to follow aircraft measurements described by previous studies. Brightness temperatures at AMSU-B frequencies for the New England blizzard are calculated using these DDA calculated single scattering parameters and particle size distributions. The vertical profiles of pressure, temperature, relative humidity and hydrometeors are provided by MM5 model simulations. These profiles are treated as the a priori data base in the Bayesian retrieval algorithm. In algorithm applications to the blizzard data, calculated brightness temperatures associated with selected database profiles agree with AMSU-B observations to within about +/- 5 K at all five frequencies. Retrieved snowfall rates compare favorably with the near-concurrent National Weather Service (NWS) radar reflectivity measurements. The relationships between the NWS radar measured reflectivities Z(sub e) and retrieved snowfall rate R for a given snow particle model are derived by a histogram matching technique. All of these Z(sub e)-R relationships fall in the range of previously established Z(sub e)-R relationships for snowfall. This suggests that the current physical model developed in this study can reliably estimate the snowfall rate over land using the AMSU-B measured brightness temperatures.

Retrieval of volcanic SO2 from HIRS/2 using optimal estimation

NASA Astrophysics Data System (ADS)

Miles, Georgina M.; Siddans, Richard; Grainger, Roy G.; Prata, Alfred J.; Fisher, Bradford; Krotkov, Nickolay

2017-07-01

We present an optimal-estimation (OE) retrieval scheme for stratospheric sulfur dioxide from the High-Resolution Infrared Radiation Sounder 2 (HIRS/2) instruments on the NOAA and MetOp platforms, an infrared radiometer that has been operational since 1979. This algorithm is an improvement upon a previous method based on channel brightness temperature differences, which demonstrated the potential for monitoring volcanic SO2 using HIRS/2. The Prata method is fast but of limited accuracy. This algorithm uses an optimal-estimation retrieval approach yielding increased accuracy for only moderate computational cost. This is principally achieved by fitting the column water vapour and accounting for its interference in the retrieval of SO2. A cloud and aerosol model is used to evaluate the sensitivity of the scheme to the presence of ash and water/ice cloud. This identifies that cloud or ash above 6 km limits the accuracy of the water vapour fit, increasing the error in the SO2 estimate. Cloud top height is also retrieved. The scheme is applied to a case study event, the 1991 eruption of Cerro Hudson in Chile. The total erupted mass of SO2 is estimated to be 2300 kT ± 600 kT. This confirms it as one of the largest events since the 1991 eruption of Pinatubo, and of comparable scale to the Northern Hemisphere eruption of Kasatochi in 2008. This retrieval method yields a minimum mass per unit area detection limit of 3 DU, which is slightly less than that for the Total Ozone Mapping Spectrometer (TOMS), the only other instrument capable of monitoring SO2 from 1979 to 1996. We show an initial comparison to TOMS for part of this eruption, with broadly consistent results. Operating in the infrared (IR), HIRS has the advantage of being able to measure both during the day and at night, and there have frequently been multiple HIRS instruments operated simultaneously for better than daily sampling. If applied to all data from the series of past and future HIRS instruments, this method presents the opportunity to produce a comprehensive and consistent volcanic SO2 time series spanning over 40 years.

Applications of neural network methods to the processing of earth observation satellite data.

PubMed

Loyola, Diego G

2006-03-01

The new generation of earth observation satellites carries advanced sensors that will gather very precise data for studying the Earth system and global climate. This paper shows that neural network methods can be successfully used for solving forward and inverse remote sensing problems, providing both accurate and fast solutions. Two examples of multi-neural network systems for the determination of cloud properties and for the retrieval of total columns of ozone using satellite data are presented. The developed algorithms based on multi-neural network are currently being used for the operational processing of European atmospheric satellite sensors and will play a key role in related satellite missions planed for the near future.

The importance of using dynamical a-priori profiles for infrared O3 retrievals : the case of IASI.

NASA Astrophysics Data System (ADS)

Peiro, H.; Emili, E.; Le Flochmoen, E.; Barret, B.; Cariolle, D.

2016-12-01

Tropospheric ozone (O3) is a trace gas involved in the global greenhouse effect. To quantify its contribution to global warming, an accurate determination of O3 profiles is necessary. The instrument IASI (Infrared Atmospheric Sounding Interferometer), on board satellite MetOP-A, is the more sensitive sensor to tropospheric O3 with a high spatio-temporal coverage. Satellite retrievals are often based on the inversion of the measured radiance data with a variational approach. This requires an a priori profile and the correspondent error covariance matrix (COV) as ancillary input. Previous studies have shown some biases ( 20%) in IASI retrievals for tropospheric column in the Southern Hemisphere (SH). A possible source of errors is caused by the a priori profile. This study aims to i) build a dynamical a priori profile O3 with a Chemistry Transport Model (CTM), ii) integrate and to demonstrate the interest of this a priori profile in IASI retrievals.Global O3 profiles are retrieved from IASI radiances with the SOFRID (Software for a fast Retrieval of IASI Data) algorithm. It is based on the RTTOV (Radiative Transfer for TOVS) code and a 1D-Var retrieval scheme. Until now, a constant a priori profile was based on a combination of MOZAIC, WOUDC-SHADOZ and Aura/MLS data named here CLIM PR. The global CTM MOCAGE (Modèle de Chimie Atmosphérique à Grande Echelle) has been used with a linear O3 chemistry scheme to assimilate Microwave Limb Sounder (MLS) data. The model resolution of 2°x2°, with 60 sigma-hybrid vertical levels covering the stratosphere has been used. MLS level 2 products have been assimilated with a 4D-VAR variational algorithm to constrain stratospheric O3 and obtain high quality a priori profiles O3 above the tropopause. From this reanalysis, we built these profiles at a 6h frequency on a coarser resolution grid 10°x20° named MOCAGE+MLS PR.Statistical comparisons between retrievals and ozonesondes have shown better correlations and smaller biases for MOCAGE+MLS PR than CLIM PR. We found biases of 6% instead of 33% in SH showing that the a priori plays an important role within O3 infrared-retrievals. Improvements of IASI retrievals have been obtained in the free troposphere and low stratosphere, inserting dynamical a priori profiles from a CTM in SOFRID. Possible advancements would be to insert dynamical COV in SOFRID.

Resolving ice cloud optical thickness biases between CALIOP and MODIS using infrared retrievals

NASA Astrophysics Data System (ADS)

Holz, R. E.; Platnick, S.; Meyer, K.; Vaughan, M.; Heidinger, A.; Yang, P.; Wind, G.; Dutcher, S.; Ackerman, S.; Amarasinghe, N.; Nagle, F.; Wang, C.

2015-10-01

Despite its importance as one of the key radiative properties that determines the impact of upper tropospheric clouds on the radiation balance, ice cloud optical thickness (IOT) has proven to be one of the more challenging properties to retrieve from space-based remote sensing measurements. In particular, optically thin upper tropospheric ice clouds (cirrus) have been especially challenging due to their tenuous nature, extensive spatial scales, and complex particle shapes and light scattering characteristics. The lack of independent validation motivates the investigation presented in this paper, wherein systematic biases between MODIS Collection 5 (C5) and CALIOP Version 3 (V3) unconstrained retrievals of tenuous IOT (< 3) are examined using a month of collocated A-Train observations. An initial comparison revealed a factor of two bias between the MODIS and CALIOP IOT retrievals. This bias is investigated using an infrared (IR) radiative closure approach that compares both products with MODIS IR cirrus retrievals developed for this assessment. The analysis finds that both the MODIS C5 and the unconstrained CALIOP V3 retrievals are biased (high and low, respectively) relative to the IR IOT retrievals. Based on this finding, the MODIS and CALIOP algorithms are investigated with the goal of explaining and minimizing the biases relative to the IR. For MODIS we find that the assumed ice single scattering properties used for the C5 retrievals are not consistent with the mean IR COT distribution. The C5 ice scattering database results in the asymmetry parameter (g) varying as a function of effective radius with mean values that are too large. The MODIS retrievals have been brought into agreement with the IR by adopting a new ice scattering model for Collection 6 (C6) consisting of a modified gamma distribution comprised of a single habit (severely roughened aggregated columns); the C6 ice cloud optical property models have a constant g ~ 0.75 in the mid-visible spectrum, 5-15 % smaller than C5. For CALIOP, the assumed lidar ratio for unconstrained retrievals is fixed at 25 sr for the V3 data products. This value is found to be inconsistent with the constrained (predominantly nighttime) CALIOP retrievals. An experimental data set was produced using a modified lidar ratio of 32 sr for the unconstrained retrievals (an increase of 28 %), selected to provide consistency with the constrained V3 results. These modifications greatly improve the agreement with the IR and provide consistency between the MODIS and CALIOP products. Based on these results the recently released MODIS C6 optical products use the single habit distribution given above, while the upcoming CALIOP V4 unconstrained algorithm will use higher lidar ratios for unconstrained retrievals.

Resolving Ice Cloud Optical Thickness Biases Between CALIOP and MODIS Using Infrared Retrievals

NASA Technical Reports Server (NTRS)

Holz, R. E.; Platnick, S.; Meyer, K.; Vaughan, M.; Heidinger, A.; Yang, P.; Wind, G.; Dutcher, S.; Ackerman, S.; Amarasinghe, N.;

Resolving ice cloud optical thickness biases between CALIOP and MODIS using infrared retrievals

NASA Astrophysics Data System (ADS)

Holz, Robert E.; Platnick, Steven; Meyer, Kerry; Vaughan, Mark; Heidinger, Andrew; Yang, Ping; Wind, Gala; Dutcher, Steven; Ackerman, Steven; Amarasinghe, Nandana; Nagle, Fredrick; Wang, Chenxi

2016-04-01

Despite its importance as one of the key radiative properties that determines the impact of upper tropospheric clouds on the radiation balance, ice cloud optical thickness (IOT) has proven to be one of the more challenging properties to retrieve from space-based remote sensing measurements. In particular, optically thin upper tropospheric ice clouds (cirrus) have been especially challenging due to their tenuous nature, extensive spatial scales, and complex particle shapes and light-scattering characteristics. The lack of independent validation motivates the investigation presented in this paper, wherein systematic biases between MODIS Collection 5 (C5) and CALIOP Version 3 (V3) unconstrained retrievals of tenuous IOT (< 3) are examined using a month of collocated A-Train observations. An initial comparison revealed a factor of 2 bias between the MODIS and CALIOP IOT retrievals. This bias is investigated using an infrared (IR) radiative closure approach that compares both products with MODIS IR cirrus retrievals developed for this assessment. The analysis finds that both the MODIS C5 and the unconstrained CALIOP V3 retrievals are biased (high and low, respectively) relative to the IR IOT retrievals. Based on this finding, the MODIS and CALIOP algorithms are investigated with the goal of explaining and minimizing the biases relative to the IR. For MODIS we find that the assumed ice single-scattering properties used for the C5 retrievals are not consistent with the mean IR COT distribution. The C5 ice scattering database results in the asymmetry parameter (g) varying as a function of effective radius with mean values that are too large. The MODIS retrievals have been brought into agreement with the IR by adopting a new ice scattering model for Collection 6 (C6) consisting of a modified gamma distribution comprised of a single habit (severely roughened aggregated columns); the C6 ice cloud optical property models have a constant g ≈ 0.75 in the mid-visible spectrum, 5-15 % smaller than C5. For CALIOP, the assumed lidar ratio for unconstrained retrievals is fixed at 25 sr for the V3 data products. This value is found to be inconsistent with the constrained (predominantly nighttime) CALIOP retrievals. An experimental data set was produced using a modified lidar ratio of 32 sr for the unconstrained retrievals (an increase of 28 %), selected to provide consistency with the constrained V3 results. These modifications greatly improve the agreement with the IR and provide consistency between the MODIS and CALIOP products. Based on these results the recently released MODIS C6 optical products use the single-habit distribution given above, while the upcoming CALIOP V4 unconstrained algorithm will use higher lidar ratios for unconstrained retrievals.

Contribution of tropical wetland and biomass burning emissions to the methane growth rate: new insights from lower tropospheric partial column retrievals

NASA Astrophysics Data System (ADS)

Yin, Y.; Worden, J. R.; Bloom, A. A.; Frankenberg, C.

2017-12-01

Atmospheric CH4 concentration stabilized in the early 2000s and began to increase again since 2007. Recent literature has explored various explanations for possible causes of the growth rate change in CH4 with considerable contradictions among each other, suggesting this problem being ill-conditioned with currently available observations. Satellite observations of CH4 in the near infrared (NIR) with full column sensitivity began with SCIAMACHY (2003-2012) and extend to the present with GOSAT (2009-). Observations in the thermal infrared (TIR) such as from TES (2004-2011) and CrIS (2012-) provide data in the free troposphere. Combining the information pieces from TIR and NIR, we could resolve the lower tropospheric partial column of CH4 that is more sensitive to the surface methane fluxes. Here, using a newly developed lower tropospheric partial column retrieval and supplemented by MOPITT CO retrievals, we discuss the interannual variations of tropical CH4 emissions from wetland and biomass burning respectively, and further, we explore the relationship between those fluxes and climate variability.

Retrieval of Aerosol Microphysical Properties from AERONET Photo-Polarimetric Measurements. 2: A New Research Algorithm and Case Demonstration

NASA Technical Reports Server (NTRS)

Xu, Xiaoguang; Wang, Jun; Zeng, Jing; Spurr, Robert; Liu, Xiong; Dubovik, Oleg; Li, Li; Li, Zhengqiang; Mishchenko, Michael I.; Siniuk, Aliaksandr;

A novel Tikhonov-based approach for harmonized high-accuracy retrieval of methane columns and profiles from NDACC FTIR network measurements. Application to global validation of ENVISAT/SCIAMACHY biases

NASA Astrophysics Data System (ADS)

Sussmann, R.; Forster, F.; Borsdorff, T.; Buchwitz, M.; Duchatelet, P.; Frankenberg, C.; Hase, F.; Jones, N.; Petersen, K.; Taylor, J.

2009-04-01

The first goal of this paper is to present an original approach for retrieval of methane columns and profiles from ground-based mid-infrared solar FTIR routine measurements performed within the Network for the Detection of Atmospheric Composition Change (NDACC). It is based on an altitude constant Tikhonov first order (L1) regularization, applied to inversion of methane profiles given in units of percentage of the volume mixing ratios at each layer altitude. A mathematical presentation of this regularization matrix can be found in Sussmann and Borsdorff (2007, equations B3 and B4 therein). We show that this approach is ideally suited to achieve a harmonized retrieval for a set of different, globally distributed FTIR stations, since it is extraordinarily simple and robust. This is because it is directly related to the well tested classical retrieval approach of simple volume mixing ratio profile scaling (via one altitude constant scaling factor), but allows for some additional flexibility in the shape of the retrieved profiles. This helps to get the total columns better integrated, even in the presence of spectral perturbations (e.g., from clouds). The amount of flexibility of the retrieved profile shape (relative to the a priori profile) can easily be tuned empirically versus one figure of merit, like minimum diurnal variation of the retrieved columns, or targeting at minimum profile oscillations within the retrieved ensemble. Sensitivity studies will be presented showing the optimization procedure and an error characterization of the new retrieval. Based on this approach and in order to guarantee a station-to-station consistency of <1 % for satellite validation we performed a general harmonization effort for 13 selected globally distributed NDACC FTIR stations. Station-to-station biases are eliminated by using identical micro-windows, spectroscopic line lists, retrieval parameters, sources of ancillary data like pressure-temperature profiles, and water vapor data for deriving dry air columns. Furthermore, a geophysically consistent set of priori profiles for the retrievals at all stations was established. Global satellite measurements of column-averaged methane have recently shown a step forward in data quality via year 2003 and 2004 retrievals from two different processors, namely IMAP-DOAS ver. 49 and WFM-DOAS ver. 1.0 (Frankenberg et al., 2008; Buchwitz et al., 2008). Accuracy and precision have approached the order of 1 %, and can be considered for inverse modelling of sources and sinks. This means at the same time that the quality requirements for ground-based validation data have become higher. This has been addressed by our harmonization effort described above. Our network validation study utilizes the validation strategy developed during the first validation of ENVISAT/SCIAMACHY column-averaged methane by FTIR (Sussmann et al., 2005). The outcome of the new study is the accurate determination of the satellite-ground station biases as a function of latitude on global scale. Acknowledgments Funding by the EC-project HYMN (contract GOCE 037048) and the DLR project SATVAL-A (DLR 50EE 0702) is gratefully acknowledged. We thank for valuable contributions of T. Blumenstock (FZK/IMK-ASF), J.P. Burrows (Univ. Bremen), B. Dils (BIRA), J. Hannigan (NCAR), J. Klyft (Chalmers), E. Mahieu (Univ. Liege), M. De Mazière (BIRA), J. Mellqvist (Chalmers), J. Notholt (Univ. Bremen), M. Rettinger (FZK/IMK-IFU), O. Schneising (Univ. Bremen), K. Strong (Univ. Toronto), and C. Vigouroux (BIRA). References Frankenberg C., Bergamaschi. P., Butz, A., Houweling, S., Meirink, J.F., Notholt, J., Petersen, A.K., Schrijver, H., Warneke, T., Aben, I.: Tropical methane emissions: A revised view from SCIAMACHY onboard ENVISAT, Geophys. Res. Lett., 35, L15811, doi:10.1029/2008GL034300, 2008. Schneising, O., Buchwitz, M., Burrows, J. P., Bovensmann, H., Bergamaschi, P., and Peters, W., Three years of greenhouse gas column-averaged dry air mole fractions retrieved from satellite - Part 2: Methane, Atmos. Chem. Phys. Discuss., 8, 8273-8326, 2008. Sussmann, R. Stremme, W., Buchwitz, M., and de Beek, R.: Validation of ENVISAT/SCIAMACHY columnar methane by solar FTIR spectrometry at the Ground-Truthing Station Zugspitze, Atmos. Chem. Phys., 5, 2419-2429, 2005. Sussmann, R. and Borsdorff, T.: Technical note: Interference errors in infrared remote sounding of the atmosphere, Atmos. Chem. Phys., 7, 3537-3557, 2007.

Comparative Results of AIRS/AMSU and CrIS/ATMS Retrievals Using a Scientifically Equivalent Retrieval Algorithm

NASA Technical Reports Server (NTRS)

Susskind, Joel; Kouvaris, Louis; Iredell, Lena

2016-01-01

The AIRS Science Team Version-6 retrieval algorithm is currently producing high quality level-3 Climate Data Records (CDRs) from AIRS/AMSU which are critical for understanding climate processes. The AIRS Science Team is finalizing an improved Version-7 retrieval algorithm to reprocess all old and future AIRS data. AIRS CDRs should eventually cover the period September 2002 through at least 2020. CrIS/ATMS is the only scheduled follow on to AIRS/AMSU. The objective of this research is to prepare for generation of long term CrIS/ATMS CDRs using a retrieval algorithm that is scientifically equivalent to AIRS/AMSU Version-7.

Retrieving Liquid Water Path and Precipitable Water Vapor from the Atmospheric Radiation Measurement (ARM) Microwave Radiometers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Turner, David D.; Clough, Shepard A.; Liljegren, James C.

2007-11-01

Ground-based two-channel microwave radiometers have been used for over 15 years by the Atmospheric Radiation Measurement (ARM) program to provide observations of downwelling emitted radiance from which precipitable water vapor (PWV) and liquid water path (LWP) – twp geophysical parameters critical for many areas of atmospheric research – are retrieved. An algorithm that utilizes two advanced retrieval techniques, a computationally expensive physical-iterative approach and an efficient statistical method, has been developed to retrieve these parameters. An important component of this Microwave Retrieval (MWRRET) algorithm is the determination of small (< 1K) offsets that are subtracted from the observed brightness temperaturesmore » before the retrievals are performed. Accounting for these offsets removes systematic biases from the observations and/or the model spectroscopy necessary for the retrieval, significantly reducing the systematic biases in the retrieved LWP. The MWRRET algorithm provides significantly more accurate retrievals than the original ARM statistical retrieval which uses monthly retrieval coefficients. By combining the two retrieval methods with the application of brightness temperature offsets to reduce the spurious LWP bias in clear skies, the MWRRET algorithm provides significantly better retrievals of PWV and LWP from the ARM 2-channel microwave radiometers compared to the original ARM product.« less

Combined neural network/Phillips-Tikhonov approach to aerosol retrievals over land from the NASA Research Scanning Polarimeter

NASA Astrophysics Data System (ADS)

Di Noia, Antonio; Hasekamp, Otto P.; Wu, Lianghai; van Diedenhoven, Bastiaan; Cairns, Brian; Yorks, John E.

2017-11-01

In this paper, an algorithm for the retrieval of aerosol and land surface properties from airborne spectropolarimetric measurements - combining neural networks and an iterative scheme based on Phillips-Tikhonov regularization - is described. The algorithm - which is an extension of a scheme previously designed for ground-based retrievals - is applied to measurements from the Research Scanning Polarimeter (RSP) on board the NASA ER-2 aircraft. A neural network, trained on a large data set of synthetic measurements, is applied to perform aerosol retrievals from real RSP data, and the neural network retrievals are subsequently used as a first guess for the Phillips-Tikhonov retrieval. The resulting algorithm appears capable of accurately retrieving aerosol optical thickness, fine-mode effective radius and aerosol layer height from RSP data. Among the advantages of using a neural network as initial guess for an iterative algorithm are a decrease in processing time and an increase in the number of converging retrievals.

The Complexity of Bit Retrieval

DOE PAGES

Elser, Veit

2018-09-20

Bit retrieval is the problem of reconstructing a periodic binary sequence from its periodic autocorrelation, with applications in cryptography and x-ray crystallography. After defining the problem, with and without noise, we describe and compare various algorithms for solving it. A geometrical constraint satisfaction algorithm, relaxed-reflect-reflect, is currently the best algorithm for noisy bit retrieval.

The Complexity of Bit Retrieval

DOE Office of Scientific and Technical Information (OSTI.GOV)

Elser, Veit

Bit retrieval is the problem of reconstructing a periodic binary sequence from its periodic autocorrelation, with applications in cryptography and x-ray crystallography. After defining the problem, with and without noise, we describe and compare various algorithms for solving it. A geometrical constraint satisfaction algorithm, relaxed-reflect-reflect, is currently the best algorithm for noisy bit retrieval.

On averaging aspect ratios and distortion parameters over ice crystal population ensembles for estimating effective scattering asymmetry parameters

PubMed Central

van Diedenhoven, Bastiaan; Ackerman, Andrew S.; Fridlind, Ann M.; Cairns, Brian

2017-01-01

The use of ensemble-average values of aspect ratio and distortion parameter of hexagonal ice prisms for the estimation of ensemble-average scattering asymmetry parameters is evaluated. Using crystal aspect ratios greater than unity generally leads to ensemble-average values of aspect ratio that are inconsistent with the ensemble-average asymmetry parameters. When a definition of aspect ratio is used that limits the aspect ratio to below unity (α≤1) for both hexagonal plates and columns, the effective asymmetry parameters calculated using ensemble-average aspect ratios are generally consistent with ensemble-average asymmetry parameters, especially if aspect ratios are geometrically averaged. Ensemble-average distortion parameters generally also yield effective asymmetry parameters that are largely consistent with ensemble-average asymmetry parameters. In the case of mixtures of plates and columns, it is recommended to geometrically average the α≤1 aspect ratios and to subsequently calculate the effective asymmetry parameter using a column or plate geometry when the contribution by columns to a given mixture’s total projected area is greater or lower than 50%, respectively. In addition, we show that ensemble-average aspect ratios, distortion parameters and asymmetry parameters can generally be retrieved accurately from simulated multi-directional polarization measurements based on mixtures of varying columns and plates. However, such retrievals tend to be somewhat biased toward yielding column-like aspect ratios. Furthermore, generally large retrieval errors can occur for mixtures with approximately equal contributions of columns and plates and for ensembles with strong contributions of thin plates. PMID:28983127

Optimization of the GSFC TROPOZ DIAL retrieval using synthetic lidar returns and ozonesondes - Part 1: Algorithm validation

NASA Astrophysics Data System (ADS)

Sullivan, J. T.; McGee, T. J.; Leblanc, T.; Sumnicht, G. K.; Twigg, L. W.

2015-10-01

The main purpose of the NASA Goddard Space Flight Center TROPospheric OZone DIfferential Absorption Lidar (GSFC TROPOZ DIAL) is to measure the vertical distribution of tropospheric ozone for science investigations. Because of the important health and climate impacts of tropospheric ozone, it is imperative to quantify background photochemical ozone concentrations and ozone layers aloft, especially during air quality episodes. For these reasons, this paper addresses the necessary procedures to validate the TROPOZ retrieval algorithm and confirm that it is properly representing ozone concentrations. This paper is focused on ensuring the TROPOZ algorithm is properly quantifying ozone concentrations, and a following paper will focus on a systematic uncertainty analysis. This methodology begins by simulating synthetic lidar returns from actual TROPOZ lidar return signals in combination with a known ozone profile. From these synthetic signals, it is possible to explicitly determine retrieval algorithm biases from the known profile. This was then systematically performed to identify any areas that need refinement for a new operational version of the TROPOZ retrieval algorithm. One immediate outcome of this exercise was that a bin registration error in the correction for detector saturation within the original retrieval was discovered and was subsequently corrected for. Another noticeable outcome was that the vertical smoothing in the retrieval algorithm was upgraded from a constant vertical resolution to a variable vertical resolution to yield a statistical uncertainty of <10 %. This new and optimized vertical-resolution scheme retains the ability to resolve fluctuations in the known ozone profile, but it now allows near-field signals to be more appropriately smoothed. With these revisions to the previous TROPOZ retrieval, the optimized TROPOZ retrieval algorithm (TROPOZopt) has been effective in retrieving nearly 200 m lower to the surface. Also, as compared to the previous version of the retrieval, the TROPOZopt had an overall mean improvement of 3.5 %, and large improvements (upwards of 10-15 % as compared to the previous algorithm) were apparent between 4.5 and 9 km. Finally, to ensure the TROPOZopt retrieval algorithm is robust enough to handle actual lidar return signals, a comparison is shown between four nearby ozonesonde measurements. The ozonesondes are mostly within the TROPOZopt retrieval uncertainty bars, which implies that this exercise was quite successful.

An enhanced VIIRS aerosol optical thickness (AOT) retrieval algorithm over land using a global surface reflectance ratio database

NASA Astrophysics Data System (ADS)

Zhang, Hai; Kondragunta, Shobha; Laszlo, Istvan; Liu, Hongqing; Remer, Lorraine A.; Huang, Jingfeng; Superczynski, Stephen; Ciren, Pubu

2016-09-01

The Visible/Infrared Imager Radiometer Suite (VIIRS) on board the Suomi National Polar-orbiting Partnership (S-NPP) satellite has been retrieving aerosol optical thickness (AOT), operationally and globally, over ocean and land since shortly after S-NPP launch in 2011. However, the current operational VIIRS AOT retrieval algorithm over land has two limitations in its assumptions for land surfaces: (1) it only retrieves AOT over the dark surfaces and (2) it assumes that the global surface reflectance ratios between VIIRS bands are constants. In this work, we develop a surface reflectance ratio database over land with a spatial resolution 0.1° × 0.1° using 2 years of VIIRS top of atmosphere reflectances. We enhance the current operational VIIRS AOT retrieval algorithm by applying the surface reflectance ratio database in the algorithm. The enhanced algorithm is able to retrieve AOT over both dark and bright surfaces. Over bright surfaces, the VIIRS AOT retrievals from the enhanced algorithm have a correlation of 0.79, mean bias of -0.008, and standard deviation (STD) of error of 0.139 when compared against the ground-based observations at the global AERONET (Aerosol Robotic Network) sites. Over dark surfaces, the VIIRS AOT retrievals using the surface reflectance ratio database improve the root-mean-square error from 0.150 to 0.123. The use of the surface reflectance ratio database also increases the data coverage of more than 20% over dark surfaces. The AOT retrievals over bright surfaces are comparable to MODIS Deep Blue AOT retrievals.

System engineering approach to GPM retrieval algorithms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rose, C. R.; Chandrasekar, V.

2004-01-01

System engineering principles and methods are very useful in large-scale complex systems for developing the engineering requirements from end-user needs. Integrating research into system engineering is a challenging task. The proposed Global Precipitation Mission (GPM) satellite will use a dual-wavelength precipitation radar to measure and map global precipitation with unprecedented accuracy, resolution and areal coverage. The satellite vehicle, precipitation radars, retrieval algorithms, and ground validation (GV) functions are all critical subsystems of the overall GPM system and each contributes to the success of the mission. Errors in the radar measurements and models can adversely affect the retrieved output values. Groundmore » validation (GV) systems are intended to provide timely feedback to the satellite and retrieval algorithms based on measured data. These GV sites will consist of radars and DSD measurement systems and also have intrinsic constraints. One of the retrieval algorithms being studied for use with GPM is the dual-wavelength DSD algorithm that does not use the surface reference technique (SRT). The underlying microphysics of precipitation structures and drop-size distributions (DSDs) dictate the types of models and retrieval algorithms that can be used to estimate precipitation. Many types of dual-wavelength algorithms have been studied. Meneghini (2002) analyzed the performance of single-pass dual-wavelength surface-reference-technique (SRT) based algorithms. Mardiana (2003) demonstrated that a dual-wavelength retrieval algorithm could be successfully used without the use of the SRT. It uses an iterative approach based on measured reflectivities at both wavelengths and complex microphysical models to estimate both No and Do at each range bin. More recently, Liao (2004) proposed a solution to the Do ambiguity problem in rain within the dual-wavelength algorithm and showed a possible melting layer model based on stratified spheres. With the No and Do calculated at each bin, the rain rate can then be calculated based on a suitable rain-rate model. This paper develops a system engineering interface to the retrieval algorithms while remaining cognizant of system engineering issues so that it can be used to bridge the divide between algorithm physics an d overall mission requirements. Additionally, in line with the systems approach, a methodology is developed such that the measurement requirements pass through the retrieval model and other subsystems and manifest themselves as measurement and other system constraints. A systems model has been developed for the retrieval algorithm that can be evaluated through system-analysis tools such as MATLAB/Simulink.« less

HCHO and NO2 MAXDOAS retrieval strategies harmonization: Recent results from the EU FP7 project QA4ECV

NASA Astrophysics Data System (ADS)

Pinardi, Gaia; Peters, Enno; Hendrick, François; Gielen, Clio; Van Roozendael, Michel; Richter, Andreas; Piters, Ankie; Wagner, Thomas; Wang, Yang; Drosoglou, Theano; Bais, Alkis; Wang, Shanshan; Saiz-Lopez, Alfonso

2016-04-01

During the last decade, it has been extensively demonstrated that MAXDOAS is a useful and reliable technique to retrieve integrated column amounts of tropospheric trace gases and aerosols, as well as information on their vertical distributions. Since it is based on optical remote-sensing in the UV-visible region like nadir backscatter space-borne sensors, MAXDOAS is also increasingly recognized as a reference technique for validating satellite nadir observations of air quality species like NO2 and HCHO. However, building up an harmonized network of MAXDOAS spectrometers requires significant efforts in terms of common retrieval strategies and best-practices definitions. Within the EU FP7 project QA4ECV (Quality Assurance for Essential Climate Variables; see http://www.qa4ecv.eu/), harmonization activities have been initiated focusing on the two main steps of the MAXDOAS retrieval, i.e. the DOAS spectral fit providing the so-called differential slant column densities (DSCDs) and the conversion of the retrieved DSCDs to vertical profiles and/or vertical column densities (VCDs). Regarding the first step, the DOAS settings for HCHO and NO2 are optimized through an intercomparison exercise of slant column retrievals involving 15 groups of the MAXDOAS community including the QA4ECV partners, and based on the radiance spectra acquired during the MAD-CAT campaign held in Mainz (Germany) in June-July 2013 (see http://joseba.mpch-mainz.mpg.de/mad_cat.htm). The harmonization of the second step is done through the application of an AMF (aim mass factor) look-up table (LUT) approach on the optimized NO2 and HCHO DSCDs. The AMF LUTs depend on entry parameters like SZA, elevation and relative azimuth angles, wavelength, boundary layer height, AOD, and surface albedo. The advantages and drawbacks of the LUT approach are illustrated at several stations through comparison of the derived VCDs with those retrieved using the more sophisticated Optimal-Estimation-based profiling method. Recommendations for both MAXDOAS retrieval steps will be given in conclusion.

Airborne Measurements of CO2 Column Concentration and Range Using a Pulsed Direct-Detection IPDA Lidar

NASA Technical Reports Server (NTRS)

Abshire, James B.; Ramanathan, Anand; Riris, Haris; Mao, Jianping; Allan, Graham R.; Hasselbrack, William E.; Weaver, Clark J.; Browell, Edward V.

2013-01-01

We have previously demonstrated a pulsed direct detection IPDA lidar to measure range and the column concentration of atmospheric CO2. The lidar measures the atmospheric backscatter profiles and samples the shape of the 1,572.33 nm CO2 absorption line. We participated in the ASCENDS science flights on the NASA DC-8 aircraft during August 2011 and report here lidar measurements made on four flights over a variety of surface and cloud conditions near the US. These included over a stratus cloud deck over the Pacific Ocean, to a dry lake bed surrounded by mountains in Nevada, to a desert area with a coal-fired power plant, and from the Rocky Mountains to Iowa, with segments with both cumulus and cirrus clouds. Most flights were to altitudes >12 km and had 5-6 altitude steps. Analyses show the retrievals of lidar range, CO2 column absorption, and CO2 mixing ratio worked well when measuring over topography with rapidly changing height and reflectivity, through thin clouds, between cumulus clouds, and to stratus cloud tops. The retrievals shows the decrease in column CO2 due to growing vegetation when flying over Iowa cropland as well as a sudden increase in CO2 concentration near a coal-fired power plant. For regions where the CO2 concentration was relatively constant, the measured CO2 absorption lineshape (averaged for 50 s) matched the predicted shapes to better than 1% RMS error. For 10 s averaging, the scatter in the retrievals was typically 2-3 ppm and was limited by the received signal photon count. Retrievals were made using atmospheric parameters from both an atmospheric model and from in situ temperature and pressure from the aircraft. The retrievals had no free parameters and did not use empirical adjustments, and >70% of the measurements passed screening and were used in analysis. The differences between the lidar-measured retrievals and in situ measured average CO2 column concentrations were <1.4 ppm for flight measurement altitudes >6 km.

The operational cloud retrieval algorithms from TROPOMI on board Sentinel-5 Precursor

NASA Astrophysics Data System (ADS)

Loyola, Diego G.; Gimeno García, Sebastián; Lutz, Ronny; Argyrouli, Athina; Romahn, Fabian; Spurr, Robert J. D.; Pedergnana, Mattia; Doicu, Adrian; Molina García, Víctor; Schüssler, Olena

2018-01-01

This paper presents the operational cloud retrieval algorithms for the TROPOspheric Monitoring Instrument (TROPOMI) on board the European Space Agency Sentinel-5 Precursor (S5P) mission scheduled for launch in 2017. Two algorithms working in tandem are used for retrieving cloud properties: OCRA (Optical Cloud Recognition Algorithm) and ROCINN (Retrieval of Cloud Information using Neural Networks). OCRA retrieves the cloud fraction using TROPOMI measurements in the ultraviolet (UV) and visible (VIS) spectral regions, and ROCINN retrieves the cloud top height (pressure) and optical thickness (albedo) using TROPOMI measurements in and around the oxygen A-band in the near infrared (NIR). Cloud parameters from TROPOMI/S5P will be used not only for enhancing the accuracy of trace gas retrievals but also for extending the satellite data record of cloud information derived from oxygen A-band measurements, a record initiated with the Global Ozone Monitoring Experiment (GOME) on board the second European Remote-Sensing Satellite (ERS-2) over 20 years ago. The OCRA and ROCINN algorithms are integrated in the S5P operational processor UPAS (Universal Processor for UV/VIS/NIR Atmospheric Spectrometers), and we present here UPAS cloud results using the Ozone Monitoring Instrument (OMI) and GOME-2 measurements. In addition, we examine anticipated challenges for the TROPOMI/S5P cloud retrieval algorithms, and we discuss the future validation needs for OCRA and ROCINN.

NILU-UV multi-filter radiometer total ozone columns: Comparison with satellite observations over Thessaloniki, Greece.

PubMed

Zempila, Melina Maria; Taylor, Michael; Koukouli, Maria Elissavet; Lerot, Christophe; Fragkos, Konstantinos; Fountoulakis, Ilias; Bais, Alkiviadis; Balis, Dimitrios; van Roozendael, Michel

2017-07-15

This study aims to construct and validate a neural network (NN) model for the production of high frequency (~1min) ground-based estimates of total ozone column (TOC) at a mid-latitude UV and ozone monitoring station in the Laboratory of Atmospheric Physics of the Aristotle University of Thessaloniki (LAP/AUTh) for the years 2005-2014. In the first stage of model development, ~30,000 records of coincident solar UV spectral irradiance measurements from a Norsk Institutt for Luftforskning (NILU)-UV multi-filter radiometer and TOC measurements from a co-located Brewer spectroradiometer are used to train a NN to learn the nonlinear functional relation between the irradiances and TOC. The model is then subjected to sensitivity analysis and validation. Close agreement is obtained (R 2 =0.94, RMSE=8.21 DU and bias=-0.15 DU relative to the Brewer) for the training data in the correlation of NN estimates on Brewer derived TOC with 95% of the coincident data differing by less than 13 DU. In the second stage of development, a long time series (≥1 million records) of high frequency (~1min) NILU-UV ground-based measurements are presented as inputs to the NN model to generate high frequency TOC estimates. The advantage of the NN model is that it is not site dependent and is applicable to any NILU input data lying within the range of the training data. GOME/ERS-2, SCIAMACHY/Envisat, OMI/Aura and GOME2/MetOp-A TOC records are then used to perform a precise cross-validation analysis and comparison with the NILU TOC estimates over Thessaloniki. All 4 satellite TOC dataset are retrieved using the GOME Direct Fitting algorithm, version 3 (GODFIT_v3), for reasons of consistency. The NILU TOC estimates within ±30min of the overpass times agree well with the satellite TOC retrievals with coefficient of determination in the range 0.88≤R 2 ≤0.90 for all sky conditions and 0.95≤R 2 ≤0.96 for clear sky conditions. The mean fractional differences are found to be -0.67%±2.15%, -1.44%±2.25%, -2.09%±2.06% and -0.85%±2.19% for GOME, SCIAMACHY, OMI and GOME2 respectively for the clear sky cases. The near constant standard deviation (~±2.2%) across the array of sensors testifies directly to the stability of both the GODFIT_v3 algorithm and the NN model for providing coherent and robust TOC records. Furthermore, the high Pearson product moment correlation coefficients (0.94

Estimates of Lightning NOx Production Based on OMI NO2 Observations Over the Gulf of Mexico

NASA Technical Reports Server (NTRS)

Pickering, Kenneth E.; Bucsela, Eric; Allen, Dale; Ring, Allison; Holzworth, Robert; Krotkov, Nickolay

2016-01-01

We evaluate nitrogen oxide (NO(sub x) NO + NO2) production from lightning over the Gulf of Mexico region using data from the Ozone Monitoring Instrument (OMI) aboard NASAs Aura satellite along with detection efficiency-adjusted lightning data from the World Wide Lightning Location Network (WWLLN). A special algorithm was developed to retrieve the lightning NOx [(LNO(sub x)] signal from OMI. The algorithm in its general form takes the total slant column NO2 from OMI and removes the stratospheric contribution and tropospheric background and includes an air mass factor appropriate for the profile of lightning NO(sub x) to convert the slant column LNO2 to a vertical column of LNO(sub x). WWLLN flashes are totaled over a period of 3 h prior to OMI overpass, which is the time an air parcel is expected to remain in a 1 deg. x 1 deg. grid box. The analysis is conducted for grid cells containing flash counts greater than a threshold value of 3000 flashes that yields an expected LNO(sub x) signal greater than the background. Pixels with cloud radiance fraction greater than a criterion value (0.9) indicative of highly reflective clouds are used. Results for the summer seasons during 2007-2011 yield mean LNO(sub x) production of approximately 80 +/- 45 mol per flash over the region for the two analysis methods after accounting for biases and uncertainties in the estimation method. These results are consistent with literature estimates and more robust than many prior estimates due to the large number of storms considered but are sensitive to several substantial sources of uncertainty.

Gradient descent algorithm applied to wavefront retrieval from through-focus images by an extreme ultraviolet microscope with partially coherent source

DOE PAGES

Yamazoe, Kenji; Mochi, Iacopo; Goldberg, Kenneth A.

2014-12-01

The wavefront retrieval by gradient descent algorithm that is typically applied to coherent or incoherent imaging is extended to retrieve a wavefront from a series of through-focus images by partially coherent illumination. For accurate retrieval, we modeled partial coherence as well as object transmittance into the gradient descent algorithm. However, this modeling increases the computation time due to the complexity of partially coherent imaging simulation that is repeatedly used in the optimization loop. To accelerate the computation, we incorporate not only the Fourier transform but also an eigenfunction decomposition of the image. As a demonstration, the extended algorithm is appliedmore » to retrieve a field-dependent wavefront of a microscope operated at extreme ultraviolet wavelength (13.4 nm). The retrieved wavefront qualitatively matches the expected characteristics of the lens design.« less

Gradient descent algorithm applied to wavefront retrieval from through-focus images by an extreme ultraviolet microscope with partially coherent source

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yamazoe, Kenji; Mochi, Iacopo; Goldberg, Kenneth A.

The wavefront retrieval by gradient descent algorithm that is typically applied to coherent or incoherent imaging is extended to retrieve a wavefront from a series of through-focus images by partially coherent illumination. For accurate retrieval, we modeled partial coherence as well as object transmittance into the gradient descent algorithm. However, this modeling increases the computation time due to the complexity of partially coherent imaging simulation that is repeatedly used in the optimization loop. To accelerate the computation, we incorporate not only the Fourier transform but also an eigenfunction decomposition of the image. As a demonstration, the extended algorithm is appliedmore » to retrieve a field-dependent wavefront of a microscope operated at extreme ultraviolet wavelength (13.4 nm). The retrieved wavefront qualitatively matches the expected characteristics of the lens design.« less

An Uncertainty Quantification Framework for Remote Sensing Retrievals

NASA Astrophysics Data System (ADS)

Braverman, A. J.; Hobbs, J.

2017-12-01

Remote sensing data sets produced by NASA and other space agencies are the result of complex algorithms that infer geophysical state from observed radiances using retrieval algorithms. The processing must keep up with the downlinked data flow, and this necessitates computational compromises that affect the accuracies of retrieved estimates. The algorithms are also limited by imperfect knowledge of physics and of ancillary inputs that are required. All of this contributes to uncertainties that are generally not rigorously quantified by stepping outside the assumptions that underlie the retrieval methodology. In this talk we discuss a practical framework for uncertainty quantification that can be applied to a variety of remote sensing retrieval algorithms. Ours is a statistical approach that uses Monte Carlo simulation to approximate the sampling distribution of the retrieved estimates. We will discuss the strengths and weaknesses of this approach, and provide a case-study example from the Orbiting Carbon Observatory 2 mission.

A multimedia retrieval framework based on semi-supervised ranking and relevance feedback.

PubMed

Yang, Yi; Nie, Feiping; Xu, Dong; Luo, Jiebo; Zhuang, Yueting; Pan, Yunhe

2012-04-01

We present a new framework for multimedia content analysis and retrieval which consists of two independent algorithms. First, we propose a new semi-supervised algorithm called ranking with Local Regression and Global Alignment (LRGA) to learn a robust Laplacian matrix for data ranking. In LRGA, for each data point, a local linear regression model is used to predict the ranking scores of its neighboring points. A unified objective function is then proposed to globally align the local models from all the data points so that an optimal ranking score can be assigned to each data point. Second, we propose a semi-supervised long-term Relevance Feedback (RF) algorithm to refine the multimedia data representation. The proposed long-term RF algorithm utilizes both the multimedia data distribution in multimedia feature space and the history RF information provided by users. A trace ratio optimization problem is then formulated and solved by an efficient algorithm. The algorithms have been applied to several content-based multimedia retrieval applications, including cross-media retrieval, image retrieval, and 3D motion/pose data retrieval. Comprehensive experiments on four data sets have demonstrated its advantages in precision, robustness, scalability, and computational efficiency.

Validation of Copernicus Height-resolved Ozone data Products from Sentinel-5P TROPOMI using global sonde and lidar networks (CHEOPS-5P)

NASA Astrophysics Data System (ADS)

Keppens, Arno; Lambert, Jean-Christopher; Hubert, Daan; Verhoelst, Tijl; Granville, José; Ancellet, Gérard; Balis, Dimitris; Delcloo, Andy; Duflot, Valentin; Godin-Beekmann, Sophie; Koukouli, Marilisa; Leblanc, Thierry; Stavrakou, Trissevgeni; Steinbrecht, Wolfgang; Stübi, Réné; Thompson, Anne

2017-04-01

Monitoring of and research on air quality, stratospheric ozone and climate change require global and long-term observation of the vertical distribution of atmospheric ozone, at ever-improving resolution and accuracy. Global tropospheric and stratospheric ozone profile measurement capabilities from space have therefore improved substantially over the last decades. Being a part of the space segment of the Copernicus Atmosphere and Climate Services that is currently under implementation, the upcoming Sentinel-5 Precursor (S5P) mission with its imaging spectrometer TROPOMI (Tropospheric Monitoring Instrument) is dedicated to the measurement of nadir atmospheric radiance and solar irradiance in the UV-VIS-NIR-SWIR spectral range. Ozone profile and tropospheric ozone column data will be retrieved from these measurements by use of several complementary retrieval methods. The geophysical validation of the enhanced height-resolved ozone data products, as well as support to the continuous evolution of the associated retrieval algorithms, is a key objective of the CHEOPS-5P project, a contributor to the ESA-led S5P Validation Team (S5PVT). This work describes the principles and implementation of the CHEOPS-5P quality assessment (QA) and validation system. The QA/validation methodology relies on the analysis of S5P retrieval diagnostics and on comparisons of S5P data with reference ozone profile measurements. The latter are collected from ozonesonde, stratospheric lidar and tropospheric lidar stations performing network operation in the context of WMO's Global Atmosphere Watch, including the NDACC global and SHADOZ tropical networks. After adaptation of the Multi-TASTE versatile satellite validation environment currently operational in the context of ESA's CCI, EUMETSAT O3M-SAF, and CEOS and SPARC initiatives, a list of S5P data Quality Indicators (QI) will be derived from complementary investigations: (1) data content and information content studies of the S5P data retrievals; (2) traceable preparation of the S5P data and correlative measurements in view of data comparisons (co-location studies, unit and representation conversions, handling of smoothing and sampling issues, independent estimate of tropopause altitude, (sub-)column integration...), with associated error propagation; (3) data comparisons leading to statistical estimates of the systematic bias and random difference between S5P and reference network data as a function of latitude, their cycles, their long-term evolution, and their dependences on influence quantities (e.g., clouds, solar zenith angle, and slant column density); (4) and finally the assessment of compliance with user requirements as formulated, e.g., by Copernicus Atmosphere and Climate services and by GCOS.

Validation of 10-year SAO OMI Ozone Profile (PROFOZ) product using ozonesonde observations

NASA Astrophysics Data System (ADS)

Huang, Guanyu; Liu, Xiong; Chance, Kelly; Yang, Kai; Bhartia, Pawan K.; Cai, Zhaonan; Allaart, Marc; Ancellet, Gérard; Calpini, Bertrand; Coetzee, Gerrie J. R.; Cuevas-Agulló, Emilio; Cupeiro, Manuel; De Backer, Hugo; Dubey, Manvendra K.; Fuelberg, Henry E.; Fujiwara, Masatomo; Godin-Beekmann, Sophie; Hall, Tristan J.; Johnson, Bryan; Joseph, Everette; Kivi, Rigel; Kois, Bogumil; Komala, Ninong; König-Langlo, Gert; Laneve, Giovanni; Leblanc, Thierry; Marchand, Marion; Minschwaner, Kenneth R.; Morris, Gary; Newchurch, Michael J.; Ogino, Shin-Ya; Ohkawara, Nozomu; Piters, Ankie J. M.; Posny, Françoise; Querel, Richard; Scheele, Rinus; Schmidlin, Frank J.; Schnell, Russell C.; Schrems, Otto; Selkirk, Henry; Shiotani, Masato; Skrivánková, Pavla; Stübi, René; Taha, Ghassan; Tarasick, David W.; Thompson, Anne M.; Thouret, Valérie; Tully, Matthew B.; Van Malderen, Roeland; Vömel, Holger; von der Gathen, Peter; Witte, Jacquelyn C.; Yela, Margarita

2017-07-01

We validate the Ozone Monitoring Instrument (OMI) Ozone Profile (PROFOZ) product from October 2004 through December 2014 retrieved by the Smithsonian Astrophysical Observatory (SAO) algorithm against ozonesonde observations. We also evaluate the effects of OMI row anomaly (RA) on the retrieval by dividing the dataset into before and after the occurrence of serious OMI RA, i.e., pre-RA (2004-2008) and post-RA (2009-2014). The retrieval shows good agreement with ozonesondes in the tropics and midlatitudes and for pressure < ˜ 50 hPa in the high latitudes. It demonstrates clear improvement over the a priori down to the lower troposphere in the tropics and down to an average of ˜ 550 (300) hPa at middle (high) latitudes. In the tropics and midlatitudes, the profile mean biases (MBs) are less than 6 %, and the standard deviations (SDs) range from 5 to 10 % for pressure < ˜ 50 hPa to less than 18 % (27 %) in the tropics (midlatitudes) for pressure > ˜ 50 hPa after applying OMI averaging kernels to ozonesonde data. The MBs of the stratospheric ozone column (SOC, the ozone column from the tropopause pressure to the ozonesonde burst pressure) are within 2 % with SDs of < 5 % and the MBs of the tropospheric ozone column (TOC) are within 6 % with SDs of 15 %. In the high latitudes, the profile MBs are within 10 % with SDs of 5-15 % for pressure < ˜ 50 hPa but increase to 30 % with SDs as great as 40 % for pressure > ˜ 50 hPa. The SOC MBs increase up to 3 % with SDs as great as 6 % and the TOC SDs increase up to 30 %. The comparison generally degrades at larger solar zenith angles (SZA) due to weaker signals and additional sources of error, leading to worse performance at high latitudes and during the midlatitude winter. Agreement also degrades with increasing cloudiness for pressure > ˜ 100 hPa and varies with cross-track position, especially with large MBs and SDs at extreme off-nadir positions. In the tropics and midlatitudes, the post-RA comparison is considerably worse with larger SDs reaching 2 % in the stratosphere and 8 % in the troposphere and up to 6 % in TOC. There are systematic differences that vary with latitude compared to the pre-RA comparison. The retrieval comparison demonstrates good long-term stability during the pre-RA period but exhibits a statistically significant trend of 0.14-0.7 % year-1 for pressure < ˜ 80 hPa, 0.7 DU year-1 in SOC, and -0. 33 DU year-1 in TOC during the post-RA period. The spatiotemporal variation of retrieval performance suggests the need to improve OMI's radiometric calibration especially during the post-RA period to maintain the long-term stability and reduce the latitude/season/SZA and cross-track dependency of retrieval quality.

Intercomparison of 4 Years of Global Formaldehyde Observations from the GOME-2 and OMI Sensors

NASA Astrophysics Data System (ADS)

De Smedt, Isabelle; Van Roozendael, Michel; Stravrakou, Trissevgeni; Muller, Jean-Francois; Chance, Kelly; Kurosu, Thomas

2012-11-01

Formaldehyde (H2CO) tropospheric columns have been retrieved since 2007 from backscattered UV radiance measurements performed by the GOME-2 instrument on the EUMETSAT METOP-A platform. This data set extends the successful time-series of global H2CO observations established with GOME/ ERS-2 (1996-2003), SCIAMACHY/ ENVISAT (2003-2012), and OMI on the NASA AURA platform (2005-now). In this work, we perform an intercomparison of the H2CO tropospheric columns retrieved from GOME-2 and OMI between 2007 and 2010, respectively at BIRA-IASB and at Harvard SAO. We first compare the global formaldehyde data products that are provided by each retrieval group. We then investigate each step of the retrieval procedure: the slant column fitting, the reference sector correction and the air mass factor calculation. New air mass factors are computed for OMI using external parameters consistent with those used for GOME-2. By doing so, the impacts of the different a priori profiles and aerosol corrections are quantified. The remaining differences are evaluated in view of the expected diurnal variations of the formaldehyde concentrations, based on ground-based measurements performed in the Beijing area.

Properties of the water column and bottom derived from Airborne Visible Infrared Imaging Spectrometer (AVIRIS) data

NASA Astrophysics Data System (ADS)

Lee, Zhongping; Carder, Kendall L.; Chen, Robert F.; Peacock, Thomas G.

2001-06-01

Using Airborne Visible Infrared Imaging Spectrometer (AVIRIS) data as an example, we show in this study that the properties of the water column and bottom of a large, shallow area can be adequately retrieved using a model-driven optimization technique. The simultaneously derived properties include bottom depth, bottom albedo, and water absorption and backscattering coefficients, which in turn could be used to derive concentrations of chlorophyll, dissolved organic matter, and suspended sediments in the water column. The derived bottom depths were compared with a bathymetry chart and a boat survey and were found to agree very well. Also, the derived bottom albedo image shows clear spatial patterns, with end-members consistent with sand and seagrass. The image of absorption and backscattering coefficients indicates that the water is quite horizontally mixed. Without bottom corrections, chlorophyll a retrievals were ˜50 mg m-3, while the retrievals after bottom corrections were tenfold less, approximating real values. These results suggest that the model and approach used work very well for the retrieval of subsurface properties of shallow-water environments even for rather turbid environments like Tampa Bay, Florida.

Characterization of Asian Dust Properties Near Source Region During ACE-Asia

NASA Technical Reports Server (NTRS)

Tsay, Si-Chee; Hsu, N. Christina; King, Michael D.; Kaufman, Yoram J.; Herman, Jay R.

2004-01-01

Asian dust typically originates in desert areas far from polluted urban regions. During transport, dust layers can interact with anthropogenic sulfate and soot aerosols from heavily polluted urban areas. Added to the complex effects of clouds and natural marine aerosols, dust particles reaching the marine environment can have drastically different properties than those from the source. Thus, understanding the unique temporal and spatial variations of Asian aerosols is of special importance in regional-to-global climate issues such as radiative forcing, the hydrological cycle, and primary biological productivity in the mid-Pacific Ocean. During ACE-Asia campaign, we have acquired ground- based (temporal) and satellite (spatial) measurements to infer aerosol physical/optical/radiative properties, column precipitable water amount, and surface reflectivity over this region. The inclusion of flux measurements permits the determination of aerosol radiative flux in addition to measurements of loading and optical depth. At the time of the Terra/MODIS, SeaWiFS, TOMS and other satellite overpasses, these ground-based observations can provide valuable data to compare with satellite retrievals over land. In this paper, we will demonstrate new capability of the Deep Blue algorithm to track the evolution of the Asian dust storm from sources to sinks. Although there are large areas often covered by clouds in the dust season in East Asia, this algorithm is able to distinguish heavy dust from clouds over the entire regions. Examination of the retrieved daily maps of dust plumes over East Asia clearly identifies the sources contributing to the dust loading in the atmosphe. We have compared the satellite retrieved aerosol optical thickness to the ground-based measurements and obtained a reasonable agreement between these two. Our results also indicate that there is a large difference in the retrieved value of spectral single scattering albedo of windblown dust between different sources in East Asia.

Technology Advancement for Active Remote Sensing of Carbon Dioxide from Space Using the ASCENDS CarbonHawk Experiment Simulator: First Results

NASA Technical Reports Server (NTRS)

Obland, Michael D.; Nehrir, Amin R.; Lin, Bing; Harrison, F. Wallace; Kooi, Susan; Choi, Yonghoon; Plant, James; Yang, Melissa; Antill, Charles; Campbell, Joel;

Ozone column density determination from direct irradiance measurements in the ultraviolet performed by a four-channel precision filter radiometer.

PubMed

Ingold, T; Mätzler, C; Wehrli, C; Heimo, A; Kämpfer, N; Philipona, R

2001-04-20

Ultraviolet light was measured at four channels (305, 311, 318, and 332 nm) with a precision filter radiometer (UV-PFR) at Arosa, Switzerland (46.78 degrees , 9.68 degrees , 1850 m above sea level), within the instrument trial phase of a cooperative venture of the Swiss Meteorological Institute (MeteoSwiss) and the Physikalisch-Meteorologisches Observatorium Davos/World Radiation Center. We retrieved ozone-column density data from these direct relative irradiance measurements by adapting the Dobson standard method for all possible single-difference wavelength pairs and one double-difference pair (305/311 and 305/318) under conditions of cloud-free sky and of thin clouds (cloud optical depth <2.5 at 500 nm). All UV-PFR retrievals exhibited excellent agreement with those of collocated Dobson and Brewer spectrophotometers for data obtained during two months in 1999. Combining the results of the error analysis and the findings of the validation, we propose to retrieve ozone-column density by using the 305/311 single difference pair and the double-difference pair. Furthermore, combining both retrievals by building the ratio of ozone-column density yields information that is relevant to data quality control. Estimates of the 305/311 pair agree with measurements by the Dobson and Brewer instruments within 1% for both the mean and the standard deviation of the differences. For the double pair these values are in a range up to 1.6%. However, this pair is less sensitive to model errors. The retrieval performance is also consistent with satellite-based data from the Earth Probe Total Ozone Mapping Spectrometer (EP-TOMS) and the Global Ozone Monitoring Experiment instrument (GOME).

Ozone Column Density Determination From Direct Irradiance Measurements in the Ultraviolet Performed by a Four-Channel Precision Filter Radiometer

NASA Astrophysics Data System (ADS)

Ingold, Thomas; Mätzler, Christian; Wehrli, Christoph; Heimo, Alain; Kämpfer, Niklaus; Philipona, Rolf

2001-04-01

Ultraviolet light was measured at four channels (305, 311, 318, and 332 nm) with a precision filter radiometer (UV-PFR) at Arosa, Switzerland (46.78 , 9.68 , 1850 m above sea level), within the instrument trial phase of a cooperative venture of the Swiss Meteorological Institute (MeteoSwiss) and the Physikalisch-Meteorologisches Observatorium Davos /World Radiation Center. We retrieved ozone-column density data from these direct relative irradiance measurements by adapting the Dobson standard method for all possible single-difference wavelength pairs and one double-difference pair (305 /311 and 305 /318) under conditions of cloud-free sky and of thin clouds (cloud optical depth <2.5 at 500 nm). All UV-PFR retrievals exhibited excellent agreement with those of collocated Dobson and Brewer spectrophotometers for data obtained during two months in 1999. Combining the results of the error analysis and the findings of the validation, we propose to retrieve ozone-column density by using the 305 /311 single difference pair and the double-difference pair. Furthermore, combining both retrievals by building the ratio of ozone-column density yields information that is relevant to data quality control. Estimates of the 305 /311 pair agree with measurements by the Dobson and Brewer instruments within 1% for both the mean and the standard deviation of the differences. For the double pair these values are in a range up to 1.6%. However, this pair is less sensitive to model errors. The retrieval performance is also consistent with satellite-based data from the Earth Probe Total Ozone Mapping Spectrometer (EP-TOMS) and the Global Ozone Monitoring Experiment instrument (GOME).

DOAS-based total column ozone retrieval from Phaethon system

NASA Astrophysics Data System (ADS)

Gkertsi, F.; Bais, A. F.; Kouremeti, N.; Drosoglou, Th; Fountoulakis, I.; Fragkos, K.

2018-05-01

This study introduces the measurement of the total ozone column using Differential Optical Absorption Spectroscopy (DOAS) analysis of direct-sun spectra recorded by the Phaethon system. This methodology is based on the analysis of spectra relative to a reference spectrum that has been recorded by the same instrument. The slant column density of ozone associated with the reference spectrum is derived by Langley extrapolation. Total ozone data derived by Phaethon over two years in Thessaloniki are compared with those of a collocated, well-maintained and calibrated, Brewer spectrophotometer. When the retrieval of total ozone is based on the absorption cross sections of (Paur and Bass, 1984) at 228 K, Phaethon shows an average overestimation of 1.85 ± 1.86%. Taking into account the effect of the day-to-day variability of stratospheric temperature on total ozone derived by both systems, the bias is reduced to 0.94 ± 1.26%. The sensitivity of the total ozone retrieval to changes in temperature is larger for Phaethon than for Brewer.

Analysis of DIAL/HSRL aerosol backscatter and extinction profiles during the SEAC4RS campaign with an aerosol assimilation system

NASA Astrophysics Data System (ADS)

Weaver, C. J.; da Silva, A. M., Jr.; Colarco, P. R.; Randles, C. A.

2015-12-01

We retrieve aerosol concentrations and optical information from vertical profiles of airborne 532 nm extinction and 532 and 1064 nm backscatter measurements made during the SEAC4RS summer 2013 campaign. The observations are from the High Spectral Resolution Lidar (HSRL) Airborne Differential Absorption Lidar (DIAL) on board the NASA DC-8. Instead of retrieving information about aerosol microphysical properties such as indexes of refraction, we seek information more directly applicable to an aerosol transport model - in our case the Goddard Chemistry Aerosol Radiation and Transport (GOCART) module used in the GEOS-5 Earth modeling system. A joint atmosphere/aerosol mini-reanalysis was performed for the SEAC4RS period using GEOS-5. The meteorological reanalysis followed the MERRA-2 atmospheric reanalysis protocol, and aerosol information from MODIS, MISR, and AERONET provided a constraint on the simulated aerosol optical depth (i.e., total column loading of aerosols). We focus on the simulated concentrations of 10 relevant aerosol species simulated by the GOCART module: dust, sulfate, and organic and black carbon. Our first retrieval algorithm starts with the SEAC4RS mini-reanalysis and adjusts the concentration of each GOCART aerosol species so that differences between the observed and simulated backscatter and extinction measurements are minimized. In this case, too often we are unable to simulate the observations by simple adjustment of the aerosol concentrations. A second retrieval approach adjusts both the aerosol concentrations and the optical parameters (i.e., assigned mass extinction efficiency) associated with each GOCART species. We present results from DC-8 flights over smoke from forest fires over the western US using both retrieval approaches. Finally, we compare our retrieved quantities with in-situ observations of aerosol absorption, scattering, and mass concentrations at flight altitude.

Using the full IASI spectrum for the physical retrieval of temperature, H2O, HDO, O3, minor and trace gases

NASA Astrophysics Data System (ADS)

Serio, C.; Blasi, M. G.; Liuzzi, G.; Masiello, G.; Venafra, S.

2017-02-01

IASI (Infrared Atmospheric Sounder Interferometer) is flying on the European MetOp series of weather satellites. Besides acquiring temperature and humidity data, IASI also observes the infrared emission of the main minor and trace atmospheric components with high precision. The retrieval of these gases would be highly beneficial to the efforts of scientists monitoring Earths climate. IASI retrieval capability and algorithms have been mostly driven by Numerical Weather Prediction centers, whose limited resources for data transmission and computing is hampering the full exploitation of IASI information content. The quest for real or nearly real time processing has affected the precision of the estimation of minor and trace gases, which are normally retrieved on a very coarse spatial grid. The paper presents the very first retrieval of the complete suite of IASI target parameters by exploiting all its 8461 channels. The analysis has been exemplified for sea surface and the target parameters will include sea surface temperature, temperature profile, water vapour and HDO profiles, ozone profile, total column amount of CO, CO2, CH4, N2O, SO2, HNO3, NH3, OCS and CF4. Concerning CO2, CH4 and N2O, it will be shown that their colum amount can be obtained for each single IASI IFOV (Instantaneous Field of View) with a precision better than 1-2%, which opens the possibility to analyze, e.g., the formation of regional patterns of greenhouse gases. To assess the quality of the retrieval, a case study has been set up which considers two years of IASI soundings over the Hawaii, Manua Loa validation station.

A New Inversion-Based Algorithm for Retrieval of Over-Water Rain Rate from SSM/I Multichannel Imagery

NASA Technical Reports Server (NTRS)

Petty, Grant W.; Stettner, David R.

1994-01-01

This paper discusses certain aspects of a new inversion based algorithm for the retrieval of rain rate over the open ocean from the special sensor microwave/imager (SSM/I) multichannel imagery. This algorithm takes a more detailed physical approach to the retrieval problem than previously discussed algorithms that perform explicit forward radiative transfer calculations based on detailed model hydrometer profiles and attempt to match the observations to the predicted brightness temperature.

The Next-generation Berkeley High Resolution NO2 (BEHR NO2) Retrieval: Design and Preliminary Emissions Constraints

NASA Astrophysics Data System (ADS)

Laughner, J.; Cohen, R. C.

2017-12-01

Recent work has identified a number of assumptions made in NO2 retrievals that lead to biases in the retrieved NO2 column density. These include the treatment of the surface as an isotropic reflector, the absence of lightning NO2 in high resolution a priori profiles, and the use of monthly averaged a priori profiles. We present a new release of the Berkeley High Resolution (BEHR) OMI NO2 retrieval based on the new NASA Standard Product (version 3) that addresses these assumptions by: accounting for surface anisotropy by using a BRDF albedo product, using an updated method of regridding NO2 data, and revised NO2 a priori profiles that better account for lightning NO2 and daily variation in the profile shape. We quantify the effect these changes have on the retrieved NO2 column densities and the resultant impact these updates have on constraints of urban NOx emissions for select cities throughout the United States.

OMI observations of bromine monoxide emissions from salt lakes

NASA Astrophysics Data System (ADS)

Suleiman, R. M.; Chance, K.; Liu, X.; Gonzalez Abad, G.; Kurosu, T. P.

2015-12-01

In this study, we analyze bromine monoxide (BrO) data from the Ozone Monitoring Instrument (OMI) over various salt lakes. We used OMI data from 2005 to 2014 to investigate BrO signatures from salt lakes. The salt lakes regions we cover include Dead Sea; Salt Lake City, US; Salar de Uyuni, Bolivia; and Namtso, Tibet. Elevated signatures of BrO was found in July and August BrO monthly averages over the Dead Sea. Similar results were found in the BrO monthly averages for August 2006 for the Bolivian Salt Flats. We present a detailed description of the retrieval algorithm for the OMI operational bromine monoxide (BrO) product. The algorithm is based on direct fitting of radiances from 319.0-347.5 nm, within the UV-2 channel of OMI. Radiances are modeled from the solar irradiance, attenuated by contributions from the target gas and interfering gases, rotational Raman scattering, additive and multiplicative closure polynomials and a common mode spectrum. The common mode spectra (one per cross-track position, computed on-line) are the average of several hundred fitting residuals. They include any instrument effects that are unrelated to molecular scattering and absorption cross sections. The BrO retrieval uses albedo- and wavelength-dependent air mass factors (AMFs), which have been pre-computed using climatological BrO profiles. The wavelength-dependent AMF is applied pre-fit to the BrO cross-sections so that vertical column densities are retrieved directly. We validate OMI BrO with ground-based measurements from three stations (Harestua, Lauder, and Barrow) and with chemical transport model simulations. We analyze the global distribution and seasonal variation of BrO and investigate BrO emissions from volcanoes and salt lakes.

Measurements of Nitrogen Dioxide Total Column Amounts using a Brewer Double Spectrophotometer in Direct Sun Mode

NASA Technical Reports Server (NTRS)

Cede, Alexander; Herman, Jay; Richter, Andreas; Krotkov, Nickolay; Burrows, John

2006-01-01

NO2 column amounts were measured for the past 2 years at Goddard Space Flight Center, Greenbelt, Maryland, using a Brewer spectrometer in direct Sun mode. A new bootstrap method to calibrate the instrument is introduced and described. This technique selects the cleanest days from the database to obtain the solar reference spectrum. The main advantage for direct Sun measurements is that the conversion uncertainty from slant column to vertical column is negligible compared to the standard scattered light observations where it is typically on the order of 100% (2sigma) at polluted sites. The total 2sigma errors of the direct Sun retrieved column amounts decrease with solar zenith angle and are estimated at 0.2 to 0.6 Dobson units (DU, 1 DU approx. equal to 2.7 10(exp 16) molecules cm(exp -2)), which is more accurate than scattered light measurements for high NO2 amounts. Measured NO2 column amounts, ranging from 0 to 3 DU with a mean of 0.7 DU, show a pronounced daily course and a strong variability from day to day. The NO2 concentration typically increases from sunrise to noon. In the afternoon it decreases in summer and stays constant in winter. As expected from the anthropogenic nature of its source, NO2 amounts on weekends are significantly reduced. The measurements were compared to satellite retrievals from Scanning Image Absorption Spectrometer for Atmospheric Chartography (SCIAMACHY). Satellite data give the same average NO2 column and show a seasonal cycle that is similar to the ground data in the afternoon. We show that NO2 must be considered when retrieving aerosol absorption properties, especially for situations with low aerosol optical depth.

A Comparison of TOMS Version 8 Total Column Ozone Data with Data from Groundstations

NASA Technical Reports Server (NTRS)

Labow, G. J.; McPeters, R. D.; Bhartia, P. K.

2004-01-01

The Nimbus-7 and Earth Probe Total Ozone Mapping Spectrometer (TOMS) data have been reprocessed with a new retrieval algorithm, (Version 8) and an updated calibration procedure. These data have been systematically compared to total ozone data from Brewer and Dobson spectrophotometers for 73 individual ground stations. The comparisons were made as a function of latitude, solar zenith angle, reflectivity and total ozone. Results show that the accuracy of the TOMS retrieval'is much improved when aerosols are present in the atmosphere, when snow/ice and sea glint are present, and when ozone in the northern hemisphere is extremely low. TOMS overpass data are derived from the single TOMS best match measurement, almost always located within one degree of the ground station and usually made within an hour of local noon. The version 8 Earth Probe TOMS ozone values have decreased by an average of about 1% due to a much better understanding of the calibration of the instrument. The remaining differences between TOMS and ground stations suggest that there are still small errors in the TOMS retrievals. But if TOMS is used as a transfer standard to compare ground stations, the large station-to-station differences suggest the possibility of significant instrument errors at some ground stations.

Atmospheric parameterization schemes for satellite cloud property retrieval during FIRE IFO 2

NASA Technical Reports Server (NTRS)

Titlow, James; Baum, Bryan A.

1993-01-01

Satellite cloud retrieval algorithms generally require atmospheric temperature and humidity profiles to determine such cloud properties as pressure and height. For instance, the CO2 slicing technique called the ratio method requires the calculation of theoretical upwelling radiances both at the surface and a prescribed number (40) of atmospheric levels. This technique has been applied to data from, for example, the High Resolution Infrared Radiometer Sounder (HIRS/2, henceforth HIRS) flown aboard the NOAA series of polar orbiting satellites and the High Resolution Interferometer Sounder (HIS). In this particular study, four NOAA-11 HIRS channels in the 15-micron region are used. The ratio method may be applied to various channel combinations to estimate cloud top heights using channels in the 15-mu m region. Presently, the multispectral, multiresolution (MSMR) scheme uses 4 HIRS channel combination estimates for mid- to high-level cloud pressure retrieval and Advanced Very High Resolution Radiometer (AVHRR) data for low-level (is greater than 700 mb) cloud level retrieval. In order to determine theoretical upwelling radiances, atmospheric temperature and water vapor profiles must be provided as well as profiles of other radiatively important gas absorber constituents such as CO2, O3, and CH4. The assumed temperature and humidity profiles have a large effect on transmittance and radiance profiles, which in turn are used with HIRS data to calculate cloud pressure, and thus cloud height and temperature. For large spatial scale satellite data analysis, atmospheric parameterization schemes for cloud retrieval algorithms are usually based on a gridded product such as that provided by the European Center for Medium Range Weather Forecasting (ECMWF) or the National Meteorological Center (NMC). These global, gridded products prescribe temperature and humidity profiles for a limited number of pressure levels (up to 14) in a vertical atmospheric column. The FIRE IFO 2 experiment provides an opportunity to investigate current atmospheric profile parameterization schemes, compare satellite cloud height results using both gridded products (ECMWF) and high vertical resolution sonde data from the National Weather Service (NWS) and Cross Chain Loran Atmospheric Sounding System (CLASS), and suggest modifications in atmospheric parameterization schemes based on these results.

Case Studies of Water Vapor and Surface Liquid Water from AVIRIS Data Measured Over Denver, CO and Death Valley, CA

NASA Technical Reports Server (NTRS)

Gao, B.-C.; Kierein-Young, K. S.; Goetz, A. F. H.; Westwater, E. R.; Stankov, B. B.; Birkenheuer, D.

1991-01-01

High spatial resolution column atmospheric water vapor amounts and equivalent liquid water thicknesses of surface targets are retrieved from spectral data collected by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). The retrievals are made using a nonlinear least squares curve fitting technique. Two case studies from AVIRIS data acquired over Denver-Platteville area, Colorado and over Death Valley, California are presented. The column water vapor values derived from AVIRIS data over the Denver-Platteville area are compared with those obtained from radiosondes, ground level upward-looking microwave radiometers, and geostationary satellite measurements. The column water vapor image shows spatial variation patterns related to the passage of a weather front system. The column water vapor amounts derived from AVIRIS data over Death Valley decrease with increasing surface elevation. The derived liquid water image clearly shows surface drainage patterns.

XCO2 retrieval error over deserts near critical surface albedo

NASA Astrophysics Data System (ADS)

Zhang, Qiong; Shia, Run-Lie; Sander, Stanley P.; Yung, Yuk L.

2016-02-01

Large retrieval errors in column-weighted CO2 mixing ratio (XCO2) over deserts are evident in the Orbiting Carbon Observatory 2 version 7 L2 products. We argue that these errors are caused by the surface albedo being close to a critical surface albedo (αc). Over a surface with albedo close to αc, increasing the aerosol optical depth (AOD) does not change the continuum radiance. The spectral signature caused by changing the AOD is identical to that caused by changing the absorbing gas column. The degeneracy in the retrievals of AOD and XCO2 results in a loss of degrees of freedom and information content. We employ a two-stream-exact single scattering radiative transfer model to study the physical mechanism of XCO2 retrieval error over a surface with albedo close to αc. Based on retrieval tests over surfaces with different albedos, we conclude that over a surface with albedo close to αc, the XCO2 retrieval suffers from a significant loss of accuracy. We recommend a bias correction approach that has significantly improved the XCO2 retrieval from the California Laboratory for Atmospheric Remote Sensing data in the presence of aerosol loading.

Fast perceptual image hash based on cascade algorithm

NASA Astrophysics Data System (ADS)

Ruchay, Alexey; Kober, Vitaly; Yavtushenko, Evgeniya

2017-09-01

In this paper, we propose a perceptual image hash algorithm based on cascade algorithm, which can be applied in image authentication, retrieval, and indexing. Image perceptual hash uses for image retrieval in sense of human perception against distortions caused by compression, noise, common signal processing and geometrical modifications. The main disadvantage of perceptual hash is high time expenses. In the proposed cascade algorithm of image retrieval initializes with short hashes, and then a full hash is applied to the processed results. Computer simulation results show that the proposed hash algorithm yields a good performance in terms of robustness, discriminability, and time expenses.

Advancements for Active Remote Sensing of Carbon Dioxide from Space using the ASCENDS CarbonHawk Experiment Simulator: First Results

NASA Astrophysics Data System (ADS)

Obland, M. D.; Nehrir, A. R.; Lin, B.; Harrison, F. W.; Kooi, S. A.; Choi, Y.; Plant, J.; Yang, M. M.; Antill, C.; Campbell, J. F.; Ismail, S.; Browell, E. V.; Meadows, B.; Dobler, J. T.; Zaccheo, T. S.; Moore, B., III; Crowell, S.

2014-12-01

The ASCENDS CarbonHawk Experiment Simulator (ACES) is an Intensity-Modulated Continuous-Wave lidar system recently developed at NASA Langley Research Center that seeks to advance technologies and techniques critical to measuring atmospheric column carbon dioxide (CO2) mixing ratios in support of the NASA Active Sensing of CO2 Emissions over Nights, Days, and Seasons (ASCENDS) mission. These advancements include: (1) increasing the power-aperture product to approach ASCENDS mission requirements by implementing multi-aperture telescopes and multiple co-aligned laser transmitters; (2) incorporating high-efficiency, high-power Erbium-Doped Fiber Amplifiers (EDFAs); (3) developing and incorporating a high-bandwidth, low-noise HgCdTe detector and transimpedence amplifier (TIA) subsystem capable of long-duration operation on Global Hawk aircraft, and (4) advancing algorithms for cloud and aerosol discrimination. The ACES instrument architecture is being developed for operation on high-altitude aircraft and will be directly scalable to meet the ASCENDS mission requirements. ACES simultaneously transmits five laser beams: three from commercial EDFAs operating near 1571 nm, and two from the Exelis oxygen (O2) Raman fiber laser amplifier system operating near 1260 nm. The Integrated-Path Differential Absorption (IPDA) lidar approach is used at both wavelengths to independently measure the CO2 and O2 column number densities and retrieve the average column CO2 mixing ratio. The outgoing laser beams are aligned to the field of view of ACES' three fiber-coupled 17.8-cm diameter athermal telescopes. The backscattered light collected by the three telescopes is sent to the detector/TIA subsystem, which has a bandwidth of 4.7 MHz and operates service-free using a tactical dewar and cryocooler. Two key laser modulation approaches are being tested to significantly mitigate the effects of thin clouds on the retrieved CO2 column amounts. Full instrument development concluded in the spring of 2014. After ground range tests of the instrument, ACES successfully completed six test flights on the Langley Hu-25 aircraft in July, 2014, and recorded data at multiple altitudes over land and ocean surfaces with and without intervening clouds. Preliminary results from these flights will be presented in this paper.

Retrieving Atmospheric Profiles Data in the Presence of Clouds from Hyperspectral Remote Sensing Data

NASA Technical Reports Server (NTRS)

Liu, Xu; Larar, Allen M.; Zhou, Daniel K.; Kizer, Susan H.; Wu, Wan; Barnet, Christopher; Divakarla, Murty; Guo, Guang; Blackwell, Bill; Smith, William L.;

Cloud Retrieval Intercomparisons Between SEVIRI, MODIS and VIIRS with CHIMAERA PGE06 Data Collection 6 Products

NASA Technical Reports Server (NTRS)

Wind, Galina; Riedi, Jerome; Platnick, Steven; Heidinger, Andrew

2014-01-01

The Cross-platform HIgh resolution Multi-instrument AtmosphEric Retrieval Algorithms (CHIMAERA) system allows us to perform MODIS-like cloud top, optical and microphysical properties retrievals on any sensor that possesses a minimum set of common spectral channels. The CHIMAERA system uses a shared-core architecture that takes retrieval method out of the equation when intercomparisons are made. Here we show an example of such retrieval and a comparison of simultaneous retrievals done using SEVIRI, MODIS and VIIRS sensors. All sensor retrievals are performed using CLAVR-x (or CLAVR-x based) cloud top properties algorithm. SEVIRI uses the SAF_NWC cloud mask. MODIS and VIIRS use the IFF-based cloud mask that is a shared algorithm between MODIS and VIIRS. The MODIS and VIIRS retrievals are performed using a VIIRS branch of CHIMAERA that limits available MODIS channel set. Even though in that mode certain MODIS products such as multilayer cloud map are not available, the cloud retrieval remains fully equivalent to operational Data Collection 6.

Deriving mesoscale temperature and moisture fields from satellite radiance measurements over the United States

NASA Technical Reports Server (NTRS)

Hillger, D. W.; Vonder Haar, T. H.

1977-01-01

The ability to provide mesoscale temperature and moisture fields from operational satellite infrared sounding radiances over the United States is explored. High-resolution sounding information for mesoscale analysis and forecasting is shown to be obtainable in mostly clear areas. An iterative retrieval algorithm applied to NOAA-VTPR radiances uses a mean radiosonde sounding as a best initial-guess profile. Temperature soundings are then retrieved at a horizontal resolution of about 70 km, as is an indication of the precipitable water content of the vertical sounding columns. Derived temperature values may be biased in general by the initial-guess sounding or in certain areas by the cloud correction technique, but the resulting relative temperature changes across the field when not contaminated by clouds will be useful for mesoscale forecasting and models. The derived moisture, affected only by high clouds, proves to be reliable to within 0.5 cm of precipitable water and contains valuable horizontal information. Present-day applications from polar-orbiting satellites as well as possibilities from upcoming temperature and moisture sounders on geostationary satellites are noted.

First Observations of SO2 from the Satellite Suomi NPP OMPS: Widespread Air Pollution Events Over China

NASA Technical Reports Server (NTRS)

Yang, Kai; Dickerson, Russell R.; Carn, Simon A.; Ge, Cui; Wang, Jun

2013-01-01

Severe smog episodes over China in January 2013 received worldwide attention. This air pollution was distinguished by heavy loadings of fine particulate matter and SO2. To characterize these episodes, we employed the Ozone Mapping and Profiler Suite, Nadir Mapper (OMPS NM), an ultraviolet (UV) spectrometer flying on the Suomi National Polar-orbiting Partnership (SNPP) spacecraft since October 2011. We developed an advanced algorithm to quantify SO2 in the lower troposphere and achieved high-quality retrievals from OMPS NM, which are characterized by high precision, approx. 0.2 Dobson Units (DU; 1 DU = 2.69 x 10(exp 16) molecules/sq cm) for instantaneous field of view SO2 data and low biases (within +/-0.2 DU). Here we report SO2 retrievals and UV aerosol index data for these pollution events. The SO2 columns and the areas covered by high pollutant concentrations are quantified; the results reveal for the first time the full extent (an area of approx. 10(exp 6) sq km containing up to 60 kt of SO2) of these episodes.

Tropospheric Ozone during the TRACE-P Mission: Comparison between TOMS Satellite Retrievals and Aircraft Lidar Data, March 2001

NASA Technical Reports Server (NTRS)

Frolov, A. D.; Thompson, A. M.; Hudson, R. D.; Browell, E. V.; Oltmans, S. J.; Witte, J. C.; Bhartia, P. K. (Technical Monitor)

2002-01-01

Over the past several years, we have developed two new tropospheric ozone retrievals from the TOMS (Total Ozone Mapping Spectrometer) satellite instrument that are of sufficient resolution to follow pollution episodes. The modified-residual technique uses v. 7 TOMS total ozone and is applicable to tropical regimes in which the wave-one pattern in total ozone is observed. The TOMS-direct method ('TDOT' = TOMS Direct Ozone in the Troposphere) represents a new algorithm that uses TOMS radiances directly to extract tropospheric ozone in regions of constant stratospheric ozone. It is not geographically restricted, using meteorological regimes as the basis for classifying TOMS radiances and for selecting appropriate comparison data. TDOT is useful where tropospheric ozone displays high mixing ratios and variability characteristic of pollution. Some of these episodes were observed downwind of Asian biomass burning during the TRACE-P (Transport and Atmospheric Chemical Evolution-Pacific) field experiment in March 2001. This paper features comparisons among TDOT tropospheric ozone column depth, integrated uv-DIAL measurements made from NASA's DC-8, and ozonesonde data.

Assessment of Chlorophyll-a Algorithms Considering Different Trophic Statuses and Optimal Bands.

PubMed

Salem, Salem Ibrahim; Higa, Hiroto; Kim, Hyungjun; Kobayashi, Hiroshi; Oki, Kazuo; Oki, Taikan

2017-07-31

Numerous algorithms have been proposed to retrieve chlorophyll- a concentrations in Case 2 waters; however, the retrieval accuracy is far from satisfactory. In this research, seven algorithms are assessed with different band combinations of multispectral and hyperspectral bands using linear (LN), quadratic polynomial (QP) and power (PW) regression approaches, resulting in altogether 43 algorithmic combinations. These algorithms are evaluated by using simulated and measured datasets to understand the strengths and limitations of these algorithms. Two simulated datasets comprising 500,000 reflectance spectra each, both based on wide ranges of inherent optical properties (IOPs), are generated for the calibration and validation stages. Results reveal that the regression approach (i.e., LN, QP, and PW) has more influence on the simulated dataset than on the measured one. The algorithms that incorporated linear regression provide the highest retrieval accuracy for the simulated dataset. Results from simulated datasets reveal that the 3-band (3b) algorithm that incorporate 665-nm and 680-nm bands and band tuning selection approach outperformed other algorithms with root mean square error (RMSE) of 15.87 mg·m -3 , 16.25 mg·m -3 , and 19.05 mg·m -3 , respectively. The spatial distribution of the best performing algorithms, for various combinations of chlorophyll- a (Chla) and non-algal particles (NAP) concentrations, show that the 3b_tuning_QP and 3b_680_QP outperform other algorithms in terms of minimum RMSE frequency of 33.19% and 60.52%, respectively. However, the two algorithms failed to accurately retrieve Chla for many combinations of Chla and NAP, particularly for low Chla and NAP concentrations. In addition, the spatial distribution emphasizes that no single algorithm can provide outstanding accuracy for Chla retrieval and that multi-algorithms should be included to reduce the error. Comparing the results of the measured and simulated datasets reveal that the algorithms that incorporate the 665-nm band outperform other algorithms for measured dataset (RMSE = 36.84 mg·m -3 ), while algorithms that incorporate the band tuning approach provide the highest retrieval accuracy for the simulated dataset (RMSE = 25.05 mg·m -3 ).

Assessment of Chlorophyll-a Algorithms Considering Different Trophic Statuses and Optimal Bands

PubMed Central

Higa, Hiroto; Kobayashi, Hiroshi; Oki, Kazuo

2017-01-01

Numerous algorithms have been proposed to retrieve chlorophyll-a concentrations in Case 2 waters; however, the retrieval accuracy is far from satisfactory. In this research, seven algorithms are assessed with different band combinations of multispectral and hyperspectral bands using linear (LN), quadratic polynomial (QP) and power (PW) regression approaches, resulting in altogether 43 algorithmic combinations. These algorithms are evaluated by using simulated and measured datasets to understand the strengths and limitations of these algorithms. Two simulated datasets comprising 500,000 reflectance spectra each, both based on wide ranges of inherent optical properties (IOPs), are generated for the calibration and validation stages. Results reveal that the regression approach (i.e., LN, QP, and PW) has more influence on the simulated dataset than on the measured one. The algorithms that incorporated linear regression provide the highest retrieval accuracy for the simulated dataset. Results from simulated datasets reveal that the 3-band (3b) algorithm that incorporate 665-nm and 680-nm bands and band tuning selection approach outperformed other algorithms with root mean square error (RMSE) of 15.87 mg·m−3, 16.25 mg·m−3, and 19.05 mg·m−3, respectively. The spatial distribution of the best performing algorithms, for various combinations of chlorophyll-a (Chla) and non-algal particles (NAP) concentrations, show that the 3b_tuning_QP and 3b_680_QP outperform other algorithms in terms of minimum RMSE frequency of 33.19% and 60.52%, respectively. However, the two algorithms failed to accurately retrieve Chla for many combinations of Chla and NAP, particularly for low Chla and NAP concentrations. In addition, the spatial distribution emphasizes that no single algorithm can provide outstanding accuracy for Chla retrieval and that multi-algorithms should be included to reduce the error. Comparing the results of the measured and simulated datasets reveal that the algorithms that incorporate the 665-nm band outperform other algorithms for measured dataset (RMSE = 36.84 mg·m−3), while algorithms that incorporate the band tuning approach provide the highest retrieval accuracy for the simulated dataset (RMSE = 25.05 mg·m−3). PMID:28758984

Development of a generalized algorithm of satellite remote sensing using multi-wavelength and multi-pixel information (MWP method) for aerosol properties by satellite-borne imager

NASA Astrophysics Data System (ADS)

Hashimoto, M.; Nakajima, T.; Morimoto, S.; Takenaka, H.

2014-12-01

We have developed a new satellite remote sensing algorithm to retrieve the aerosol optical characteristics using multi-wavelength and multi-pixel information of satellite imagers (MWP method). In this algorithm, the inversion method is a combination of maximum a posteriori (MAP) method (Rodgers, 2000) and the Phillips-Twomey method (Phillips, 1962; Twomey, 1963) as a smoothing constraint for the state vector. Furthermore, with the progress of computing technique, this method has being combined with the direct radiation transfer calculation numerically solved by each iteration step of the non-linear inverse problem, without using LUT (Look Up Table) with several constraints.Retrieved parameters in our algorithm are aerosol optical properties, such as aerosol optical thickness (AOT) of fine and coarse mode particles, a volume soot fraction in fine mode particles, and ground surface albedo of each observed wavelength. We simultaneously retrieve all the parameters that characterize pixels in each of horizontal sub-domains consisting the target area. Then we successively apply the retrieval method to all the sub-domains in the target area.We conducted numerical tests for the retrieval of aerosol properties and ground surface albedo for GOSAT/CAI imager data to test the algorithm for the land area. The result of the experiment showed that AOTs of fine mode and coarse mode, soot fraction and ground surface albedo are successfully retrieved within expected accuracy. We discuss the accuracy of the algorithm for various land surface types. Then, we applied this algorithm to GOSAT/CAI imager data, and we compared retrieved and surface-observed AOTs at the CAI pixel closest to an AERONET (Aerosol Robotic Network) or SKYNET site in each region. Comparison at several sites in urban area indicated that AOTs retrieved by our method are in agreement with surface-observed AOT within ±0.066.Our future work is to extend the algorithm for analysis of AGEOS-II/GLI and GCOM/C-SGLI data.

An Examination of the Spatial Distribution of Carbon Dioxide and Systematic Errors

NASA Technical Reports Server (NTRS)

Coffey, Brennan; Gunson, Mike; Frankenberg, Christian; Osterman, Greg

2011-01-01

The industrial period and modern age is characterized by combustion of coal, oil, and natural gas for primary energy and transportation leading to rising levels of atmospheric of CO2. This increase, which is being carefully measured, has ramifications throughout the biological world. Through remote sensing, it is possible to measure how many molecules of CO2 lie in a defined column of air. However, other gases and particles are present in the atmosphere, such as aerosols and water, which make such measurements more complicated1. Understanding the detailed geometry and path length of the observation is vital to computing the concentration of CO2. Comparing these satellite readings with ground-truth data (TCCON) the systematic errors arising from these sources can be assessed. Once the error is understood, it can be scaled for in the retrieval algorithms to create a set of data, which is closer to the TCCON measurements1. Using this process, the algorithms are being developed to reduce bias, within.1% worldwide of the true value. At this stage, the accuracy is within 1%, but through correcting small errors contained in the algorithms, such as accounting for the scattering of sunlight, the desired accuracy can be achieved.

Importance of A Priori Vertical Ozone Profiles for TEMPO Air Quality Retrievals

NASA Astrophysics Data System (ADS)

Johnson, M. S.; Sullivan, J. T.; Liu, X.; Zoogman, P.; Newchurch, M.; Kuang, S.; McGee, T. J.; Leblanc, T.

2017-12-01

Ozone (O3) is a toxic pollutant which plays a major role in air quality. Typically, monitoring of surface air quality and O3 mixing ratios is conducted using in situ measurement networks. This is partially due to high-quality information related to air quality being limited from space-borne platforms due to coarse spatial resolution, limited temporal frequency, and minimal sensitivity to lower tropospheric and surface-level O3. The Tropospheric Emissions: Monitoring of Pollution (TEMPO) satellite is designed to address the limitations of current space-based platforms and to improve our ability to monitor North American air quality. TEMPO will provide hourly data of total column and vertical profiles of O3 with high spatial resolution to be used as a near-real-time air quality product. TEMPO O3 retrievals will apply the Smithsonian Astrophysical Observatory profile algorithm developed based on work from GOME, GOME-2, and OMI. This algorithm is suggested to use a priori O3 profile information from a climatological data-base developed from long-term ozone-sonde measurements (tropopause-based (TB-Clim) O3 climatology). This study evaluates the TB-Clim dataset and model simulated O3 profiles, which could potentially serve as a priori O3 profile information in TEMPO retrievals, from near-real-time data assimilation model products (NASA GMAO's operational GEOS-5 FP model and reanalysis data from MERRA2) and a full chemical transport model (CTM), GEOS-Chem. In this study, vertical profile products are evaluated with surface (0-2 km) and tropospheric (0-10 km) TOLNet observations and the theoretical impact of individual a priori profile sources on the accuracy of TEMPO O3 retrievals in the troposphere and at the surface are presented. Results indicate that while the TB-Clim climatological dataset can replicate seasonally-averaged tropospheric O3 profiles, model-simulated profiles from a full CTM resulted in more accurate tropospheric and surface-level O3 retrievals from TEMPO when compared to hourly and daily-averaged TOLNet observations. Furthermore, it is shown that when large surface O3 mixing ratios are observed, TEMPO retrieval values at the surface are most accurate when applying CTM a priori profile information compared to all other data products.

Performance Verification of GOSAT-2 FTS-2 Simulator and Sensitivity Analysis for Greenhouse Gases Retrieval

NASA Astrophysics Data System (ADS)

Kamei, A.; Yoshida, Y.; Dupuy, E.; Hiraki, K.; Matsunaga, T.

2015-12-01

The GOSAT-2, which is scheduled for launch in early 2018, is the successor mission to the Greenhouse gases Observing Satellite (GOSAT). The FTS-2 onboard the GOSAT-2 is a Fourier transform spectrometer, which has three bands in the near to short-wavelength infrared (SWIR) region and two bands in the thermal infrared (TIR) region to observe infrared light reflected and emitted from the Earth's surface and atmosphere with high-resolution spectra. Column amounts and vertical profiles of major greenhouse gases such as carbon dioxide (CO2) and methane (CH4) are retrieved from acquired radiance spectra. In addition, the FTS-2 has several improvements from the FTS onboard the GOSAT: 1) added spectral coverage in the SWIR region for carbon monoxide (CO) retrieval, 2) increased signal-to-noise ratio (SNR) for all bands, 3) extended range of along-track pointing angles for sunglint observations, 4) intelligent pointing to avoid cloud contamination. Since 2012, we have been developing a software tool, which is called the GOSAT-2 FTS-2 simulator, to simulate spectral radiance data that will be acquired by the GOSAT-2 FTS-2. The objective of it is to analyze/optimize data with respect to the sensor specification, the parameters for Level 1 processing, and the improvement of Level 2 retrieval algorithms. It consists of six components: 1) overall control, 2) sensor carrying platform, 3) spectral radiance calculation, 4) Fourier transform module, 5) Level 1B (L1B) processing, and 6) L1B data output. More realistic and faster simulations have been made possible by the improvement of details about sensor characteristics, the sophistication of data processing and algorithms, the addition of various observation modes, the use of surface and atmospheric ancillary data, and the speed-up and parallelization of radiative transfer code. This simulator is confirmed to be working properly from the reproduction of GOSAT FTS L1B data depends on the ancillary data. We will summarize the performance verification of the GOSAT-2 FTS-2 simulator and describe the future prospects for Level 2 retrieval. Besides, we will present the various sensitivity analyses relating to the engineering parameters and the atmospheric conditions on Level 1 processing for greenhouse gases retrieval.

A Semianalytical Ocean Color Inversion Algorithm with Explicit Water Column Depth and Substrate Reflectance Parameterization

NASA Technical Reports Server (NTRS)

Mckinna, Lachlan I. W.; Werdell, P. Jeremy; Fearns, Peter R. C.; Weeks, Scarla J.; Reichstetter, Martina; Franz, Bryan A.; Shea, Donald M.; Feldman, Gene C.

2015-01-01

A semianalytical ocean color inversion algorithm was developed for improving retrievals of inherent optical properties (IOPs) in optically shallow waters. In clear, geometrically shallow waters, light reflected off the seafloor can contribute to the water-leaving radiance signal. This can have a confounding effect on ocean color algorithms developed for optically deep waters, leading to an overestimation of IOPs. The algorithm described here, the Shallow Water Inversion Model (SWIM), uses pre-existing knowledge of bathymetry and benthic substrate brightness to account for optically shallow effects. SWIM was incorporated into the NASA Ocean Biology Processing Group's L2GEN code and tested in waters of the Great Barrier Reef, Australia, using the Moderate Resolution Imaging Spectroradiometer (MODIS) Aqua time series (2002-2013). SWIM-derived values of the total non-water absorption coefficient at 443 nm, at(443), the particulate backscattering coefficient at 443 nm, bbp(443), and the diffuse attenuation coefficient at 488 nm, Kd(488), were compared with values derived using the Generalized Inherent Optical Properties algorithm (GIOP) and the Quasi-Analytical Algorithm (QAA). The results indicated that in clear, optically shallow waters SWIM-derived values of at(443), bbp(443), and Kd(443) were realistically lower than values derived using GIOP and QAA, in agreement with radiative transfer modeling. This signified that the benthic reflectance correction was performing as expected. However, in more optically complex waters, SWIM had difficulty converging to a solution, a likely consequence of internal IOP parameterizations. Whilst a comprehensive study of the SWIM algorithm's behavior was conducted, further work is needed to validate the algorithm using in situ data.

FPGA implementation of sparse matrix algorithm for information retrieval

NASA Astrophysics Data System (ADS)

Bojanic, Slobodan; Jevtic, Ruzica; Nieto-Taladriz, Octavio

2005-06-01

Information text data retrieval requires a tremendous amount of processing time because of the size of the data and the complexity of information retrieval algorithms. In this paper the solution to this problem is proposed via hardware supported information retrieval algorithms. Reconfigurable computing may adopt frequent hardware modifications through its tailorable hardware and exploits parallelism for a given application through reconfigurable and flexible hardware units. The degree of the parallelism can be tuned for data. In this work we implemented standard BLAS (basic linear algebra subprogram) sparse matrix algorithm named Compressed Sparse Row (CSR) that is showed to be more efficient in terms of storage space requirement and query-processing timing over the other sparse matrix algorithms for information retrieval application. Although inverted index algorithm is treated as the de facto standard for information retrieval for years, an alternative approach to store the index of text collection in a sparse matrix structure gains more attention. This approach performs query processing using sparse matrix-vector multiplication and due to parallelization achieves a substantial efficiency over the sequential inverted index. The parallel implementations of information retrieval kernel are presented in this work targeting the Virtex II Field Programmable Gate Arrays (FPGAs) board from Xilinx. A recent development in scientific applications is the use of FPGA to achieve high performance results. Computational results are compared to implementations on other platforms. The design achieves a high level of parallelism for the overall function while retaining highly optimised hardware within processing unit.

Development, Comparisons and Evaluation of Aerosol Retrieval Algorithms

NASA Astrophysics Data System (ADS)

de Leeuw, G.; Holzer-Popp, T.; Aerosol-cci Team

2011-12-01

The Climate Change Initiative (cci) of the European Space Agency (ESA) has brought together a team of European Aerosol retrieval groups working on the development and improvement of aerosol retrieval algorithms. The goal of this cooperation is the development of methods to provide the best possible information on climate and climate change based on satellite observations. To achieve this, algorithms are characterized in detail as regards the retrieval approaches, the aerosol models used in each algorithm, cloud detection and surface treatment. A round-robin intercomparison of results from the various participating algorithms serves to identify the best modules or combinations of modules for each sensor. Annual global datasets including their uncertainties will then be produced and validated. The project builds on 9 existing algorithms to produce spectral aerosol optical depth (AOD and Ångström exponent) as well as other aerosol information; two instruments are included to provide the absorbing aerosol index (AAI) and stratospheric aerosol information. The algorithms included are: - 3 for ATSR (ORAC developed by RAL / Oxford university, ADV developed by FMI and the SU algorithm developed by Swansea University ) - 2 for MERIS (BAER by Bremen university and the ESA standard handled by HYGEOS) - 1 for POLDER over ocean (LOA) - 1 for synergetic retrieval (SYNAER by DLR ) - 1 for OMI retreival of the absorbing aerosol index with averaging kernel information (KNMI) - 1 for GOMOS stratospheric extinction profile retrieval (BIRA) The first seven algorithms aim at the retrieval of the AOD. However, each of the algorithms used differ in their approach, even for algorithms working with the same instrument such as ATSR or MERIS. To analyse the strengths and weaknesses of each algorithm several tests are made. The starting point for comparison and measurement of improvements is a retrieval run for 1 month, September 2008. The data from the same month are subsequently used for several runs with a prescribed set of aerosol models and an a priori data set derived from the median of AEROCOM model runs. The aerosol models and a priori data can be used in several ways, i.e. fully prescribed or with some freedom to choose a combination of aerosol models, based on the a priori or not. Another test gives insight in the effect of the cloud masks used, i.e. retrievals using the same cloud mask (the AATSR APOLLO cloud mask for collocated instruments) are compared with runs using the standard cloud masks. Tests to determine the influence of surface treatment are planned as well. The results of all these tests are evaluated by an independent team which compares the retrieval results with ground-based remote sensing (in particular AERONET) and in-situ data, and by a scoring method. Results are compared with other satellites such as MODIS and MISR. Blind tests using synthetic data are part of the algorithm characterization. The presentation will summarize results of the ongoing phase 1 inter-comparison and evaluation work within the Aerosol_cci project.

V2.1.4 L2AS Detailed Release Description September 27, 2001

Atmospheric Science Data Center

2013-03-14

... 27, 2001 Algorithm Changes Change method of selecting radiance pixels to use in aerosol retrieval over ... het. surface retrieval algorithm over areas of 100% dark water. Modify algorithm for selecting a default aerosol model to use in ...

Temporal and spatial distribution of metallic species in the upper atmosphere

NASA Astrophysics Data System (ADS)

Correira, John Thomas

2009-06-01

Every day the Earth is bombarded by approximately 100 tons of meteoric material. Much of this material is completely ablated on atmospheric entry, resulting in a layer of atomic metals in the upper atmosphere between 70 km - 150 km. These neutral atoms are ionized by solar radiation and charge exchange. Metal ions have a long lifetime against recombination loss, allowing them to be redistributed globally by electromagnetic forces, especially when lifted to altitudes >150 km. UV radiances from the Global Ozone Monitoring Experiment (GOME) spectrometer are used to determine long-term dayside variations of the total vertical column density below 795 km of the meteoric metal species Mg and Mg + in the upper atmosphere. A retrieval algorithm developed to determine magnesium column densities was applied to all available data from the years 1996-2001. Long term results show middle latitude dayside Mg + peaks in vertical content during the summer, while neutral Mg demonstrates a much more subtle maximum in summer. Atmospheric metal concentrations do not correlate strongly solar activity. An analysis of spatial variations shows geospatial distributions are patchy, with local regions of increased column density. To study short term variations and the role of meteor showers a time dependent mass flux rate is calculated using published estimates of meteor stream mass densities and activity profiles. An average daily mass flux rate is also calculated and used as a baseline against which shower mass flux rates are compared. These theoretical mass flux rates are then compared with GOME derived metal column densities. There appears to be little correlation between modeled meteor shower mass flux rates and changes in the observed neutral magnesium and Mg + metal column densities.

Comparison of AOD, AAOD and column single scattering albedo from AERONET retrievals and in situ profiling measurements

NASA Astrophysics Data System (ADS)

Andrews, Elisabeth; Ogren, John A.; Kinne, Stefan; Samset, Bjorn

2017-05-01

Here we present new results comparing aerosol optical depth (AOD), aerosol absorption optical depth (AAOD) and column single scattering albedo (SSA) obtained from in situ vertical profile measurements with AERONET ground-based remote sensing from two rural, continental sites in the US. The profiles are closely matched in time (within ±3 h) and space (within 15 km) with the AERONET retrievals. We have used Level 1.5 inversion retrievals when there was a valid Level 2 almucantar retrieval in order to be able to compare AAOD and column SSA below AERONET's recommended loading constraint (AOD > 0.4 at 440 nm). While there is reasonable agreement for the AOD comparisons, the direct comparisons of in situ-derived to AERONET-retrieved AAOD (or SSA) reveal that AERONET retrievals yield higher aerosol absorption than obtained from the in situ profiles for the low aerosol optical depth conditions prevalent at the two study sites. However, it should be noted that the majority of SSA comparisons for AOD440 > 0.2 are, nonetheless, within the reported SSA uncertainty bounds. The observation that, relative to in situ measurements, AERONET inversions exhibit increased absorption potential at low AOD values is generally consistent with other published AERONET-in situ comparisons across a range of locations, atmospheric conditions and AOD values. This systematic difference in the comparisons suggests a bias in one or both of the methods, but we cannot assess whether the AERONET retrievals are biased towards high absorption or the in situ measurements are biased low. Based on the discrepancy between the AERONET and in situ values, we conclude that scaling modeled black carbon concentrations upwards to match AERONET retrievals of AAOD should be approached with caution as it may lead to aerosol absorption overestimates in regions of low AOD. Both AERONET retrievals and in situ measurements suggest there is a systematic relationship between SSA and aerosol amount (AOD or aerosol light scattering) - specifically that SSA decreases at lower aerosol loading. This implies that the fairly common assumption that AERONET SSA values retrieved at high-AOD conditions can be used to obtain AAOD at low-AOD conditions may not be valid.

The 2010 Eyja eruption evolution by using IR satellite sensors measurements: retrieval comparison and insights into explosive volcanic processes

NASA Astrophysics Data System (ADS)

Piscini, A.; Corradini, S.; Merucci, L.; Scollo, S.

2010-12-01

The 2010 April-May Eyja eruption caused an unprecedented disruption to economic, political and cultural activities in Europe and across the world. Because of the harming effects of fine ash particles on aircrafts, many European airports were in fact closed causing millions of passengers to be stranded, and with a worldwide airline industry loss estimated of about 2.5 billion Euros. Both security and economical issues require robust and affordable volcanic cloud retrievals that may be really improved through the intercomparison among different remote sensing instruments. In this work the Thermal InfraRed (TIR) measurements of different polar and geostationary satellites instruments as the Moderate Resolution Imaging Spectroradiometer (MODIS), the Advanced Very High Resolution Radiometer (AVHRR) and the Spin Enhanced Visible and Infrared Imager (SEVIRI), have been used to retrieve the volcanic ash and SO2 in the entire eruption period over Iceland. The ash retrievals (mass, AOD and effective radius) have been carried out by means of the split window BTD technique using the channels centered around 11 and 12 micron. The least square fit procedure is used for the SO2 retrieval by using the 7.3 and 8.7 micron channels. The simulated TOA radiance Look-Up Table (LUT) needed for both the ash and SO2 column abundance retrievals have been computed using the MODTRAN 4 Radiative Transfer Model. Further, the volcanic plume column altitude and ash density have been computed and compared, when available, with ground observations. The results coming from the retrieval of different IR sensors show a good agreement over the entire eruption period. The column height, the volcanic ash and the SO2 emission trend confirm the indentified different phases occurred during the Eyja eruption. We remark that the retrieved volcanic plume evolution can give important insights into eruptive dynamics during long-lived explosive activity.

An enhanced TIMESAT algorithm for estimating vegetation phenology metrics from MODIS data

USGS Publications Warehouse

Tan, B.; Morisette, J.T.; Wolfe, R.E.; Gao, F.; Ederer, G.A.; Nightingale, J.; Pedelty, J.A.

2011-01-01

An enhanced TIMESAT algorithm was developed for retrieving vegetation phenology metrics from 250 m and 500 m spatial resolution Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indexes (VI) over North America. MODIS VI data were pre-processed using snow-cover and land surface temperature data, and temporally smoothed with the enhanced TIMESAT algorithm. An objective third derivative test was applied to define key phenology dates and retrieve a set of phenology metrics. This algorithm has been applied to two MODIS VIs: Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI). In this paper, we describe the algorithm and use EVI as an example to compare three sets of TIMESAT algorithm/MODIS VI combinations: a) original TIMESAT algorithm with original MODIS VI, b) original TIMESAT algorithm with pre-processed MODIS VI, and c) enhanced TIMESAT and pre-processed MODIS VI. All retrievals were compared with ground phenology observations, some made available through the National Phenology Network. Our results show that for MODIS data in middle to high latitude regions, snow and land surface temperature information is critical in retrieving phenology metrics from satellite observations. The results also show that the enhanced TIMESAT algorithm can better accommodate growing season start and end dates that vary significantly from year to year. The TIMESAT algorithm improvements contribute to more spatial coverage and more accurate retrievals of the phenology metrics. Among three sets of TIMESAT/MODIS VI combinations, the start of the growing season metric predicted by the enhanced TIMESAT algorithm using pre-processed MODIS VIs has the best associations with ground observed vegetation greenup dates. ?? 2010 IEEE.

An Enhanced TIMESAT Algorithm for Estimating Vegetation Phenology Metrics from MODIS Data

NASA Technical Reports Server (NTRS)

Tan, Bin; Morisette, Jeffrey T.; Wolfe, Robert E.; Gao, Feng; Ederer, Gregory A.; Nightingale, Joanne; Pedelty, Jeffrey A.

2012-01-01

An enhanced TIMESAT algorithm was developed for retrieving vegetation phenology metrics from 250 m and 500 m spatial resolution Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation indexes (VI) over North America. MODIS VI data were pre-processed using snow-cover and land surface temperature data, and temporally smoothed with the enhanced TIMESAT algorithm. An objective third derivative test was applied to define key phenology dates and retrieve a set of phenology metrics. This algorithm has been applied to two MODIS VIs: Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI). In this paper, we describe the algorithm and use EVI as an example to compare three sets of TIMESAT algorithm/MODIS VI combinations: a) original TIMESAT algorithm with original MODIS VI, b) original TIMESAT algorithm with pre-processed MODIS VI, and c) enhanced TIMESAT and pre-processed MODIS VI. All retrievals were compared with ground phenology observations, some made available through the National Phenology Network. Our results show that for MODIS data in middle to high latitude regions, snow and land surface temperature information is critical in retrieving phenology metrics from satellite observations. The results also show that the enhanced TIMESAT algorithm can better accommodate growing season start and end dates that vary significantly from year to year. The TIMESAT algorithm improvements contribute to more spatial coverage and more accurate retrievals of the phenology metrics. Among three sets of TIMESAT/MODIS VI combinations, the start of the growing season metric predicted by the enhanced TIMESAT algorithm using pre-processed MODIS VIs has the best associations with ground observed vegetation greenup dates.

A Parallel Relational Database Management System Approach to Relevance Feedback in Information Retrieval.

ERIC Educational Resources Information Center

Lundquist, Carol; Frieder, Ophir; Holmes, David O.; Grossman, David

1999-01-01

Describes a scalable, parallel, relational database-drive information retrieval engine. To support portability across a wide range of execution environments, all algorithms adhere to the SQL-92 standard. By incorporating relevance feedback algorithms, accuracy is enhanced over prior database-driven information retrieval efforts. Presents…

Initial Verification of GEOS-4 Aerosols Using CALIPSO and MODIS: Scene Classification

NASA Technical Reports Server (NTRS)

Welton, Ellsworth J.; Colarco, Peter R.; Hlavka, Dennis; Levy, Robert C.; Vaughan, Mark A.; daSilva, Arlindo

2007-01-01

A-train sensors such as MODIS and MISR provide column aerosol properties, and in the process a means of estimating aerosol type (e.g. smoke vs. dust). Correct classification of aerosol type is important because retrievals are often dependent upon selection of the right aerosol model. In addition, aerosol scene classification helps place the retrieved products in context for comparisons and analysis with aerosol transport models. The recent addition of CALIPSO to the A-train now provides a means of classifying aerosol distribution with altitude. CALIPSO level 1 products include profiles of attenuated backscatter at 532 and 1064 nm, and depolarization at 532 nm. Backscatter intensity, wavelength ratio, and depolarization provide information on the vertical profile of aerosol concentration, size, and shape. Thus similar estimates of aerosol type using MODIS or MISR are possible with CALIPSO, and the combination of data from all sensors provides a means of 3D aerosol scene classification. The NASA Goddard Earth Observing System general circulation model and data assimilation system (GEOS-4) provides global 3D aerosol mass for sulfate, sea salt, dust, and black and organic carbon. A GEOS-4 aerosol scene classification algorithm has been developed to provide estimates of aerosol mixtures along the flight track for NASA's Geoscience Laser Altimeter System (GLAS) satellite lidar. GLAS launched in 2003 and did not have the benefit of depolarization measurements or other sensors from the A-train. Aerosol typing from GLAS data alone was not possible, and the GEOS-4 aerosol classifier has been used to identify aerosol type and improve the retrieval of GLAS products. Here we compare 3D aerosol scene classification using CALIPSO and MODIS with the GEOS-4 aerosol classifier. Dust, smoke, and pollution examples will be discussed in the context of providing an initial verification of the 3D GEOS-4 aerosol products. Prior model verification has only been attempted with surface mass comparisons and column optical depth from AERONET and MODIS.

GOSAT CO2 retrieval results using TANSO-CAI aerosol information over East Asia

NASA Astrophysics Data System (ADS)

KIM, M.; Kim, W.; Jung, Y.; Lee, S.; Kim, J.; Lee, H.; Boesch, H.; Goo, T. Y.

2015-12-01

In the satellite remote sensing of CO2, incorrect aerosol information could induce large errors as previous studies suggested. Many factors, such as, aerosol type, wavelength dependency of AOD, aerosol polarization effect and etc. have been main error sources. Due to these aerosol effects, large number of data retrieved are screened out in quality control, or retrieval errors tend to increase if not screened out, especially in East Asia where aerosol concentrations are fairly high. To reduce these aerosol induced errors, a CO2 retrieval algorithm using the simultaneous TANSO-CAI aerosol information is developed. This algorithm adopts AOD and aerosol type information as a priori information from the CAI aerosol retrieval algorithm. The CO2 retrieval algorithm based on optimal estimation method and VLIDORT, a vector discrete ordinate radiative transfer model. The CO2 algorithm, developed with various state vectors to find accurate CO2 concentration, shows reasonable results when compared with other dataset. This study concentrates on the validation of retrieved results with the ground-based TCCON measurements in East Asia and the comparison with the previous retrieval from ACOS, NIES, and UoL. Although, the retrieved CO2 concentration is lower than previous results by ppm's, it shows similar trend and high correlation with previous results. Retrieved data and TCCON measurements data are compared at three stations of Tsukuba, Saga, Anmyeondo in East Asia, with the collocation criteria of ±2°in latitude/longitude and ±1 hours of GOSAT passing time. Compared results also show similar trend with good correlation. Based on the TCCON comparison results, bias correction equation is calculated and applied to the East Asia data.

Fast emission estimates in China and South Africa constrained by satellite observations

NASA Astrophysics Data System (ADS)

Mijling, Bas; van der A, Ronald

2013-04-01

Emission inventories of air pollutants are crucial information for policy makers and form important input data for air quality models. Unfortunately, bottom-up emission inventories, compiled from large quantities of statistical data, are easily outdated for emerging economies such as China and South Africa, where rapid economic growth change emissions accordingly. Alternatively, top-down emission estimates from satellite observations of air constituents have important advantages of being spatial consistent, having high temporal resolution, and enabling emission updates shortly after the satellite data become available. However, constraining emissions from observations of concentrations is computationally challenging. Within the GlobEmission project (part of the Data User Element programme of ESA) a new algorithm has been developed, specifically designed for fast daily emission estimates of short-lived atmospheric species on a mesoscopic scale (0.25 × 0.25 degree) from satellite observations of column concentrations. The algorithm needs only one forward model run from a chemical transport model to calculate the sensitivity of concentration to emission, using trajectory analysis to account for transport away from the source. By using a Kalman filter in the inverse step, optimal use of the a priori knowledge and the newly observed data is made. We apply the algorithm for NOx emission estimates in East China and South Africa, using the CHIMERE chemical transport model together with tropospheric NO2 column retrievals of the OMI and GOME-2 satellite instruments. The observations are used to construct a monthly emission time series, which reveal important emission trends such as the emission reduction measures during the Beijing Olympic Games, and the impact and recovery from the global economic crisis. The algorithm is also able to detect emerging sources (e.g. new power plants) and improve emission information for areas where proxy data are not or badly known (e.g. shipping emissions). The new emission inventories result in a better agreement between observations and simulations of air pollutant concentrations, facilitating improved air quality forecasts.

Comparative Analysis of Aerosol Retrievals from MODIS, OMI and MISR Over Sahara Region

NASA Technical Reports Server (NTRS)

Lyapustin, A.; Wang, Y.; Hsu, C.; Terres, O.; Leptoukh, G.; Kalashnikova, O.; Korkin, S.

2011-01-01

MODIS is a wide field-of-view sensor providing daily global observations of the Earth. Currently, global MODIS aerosol retrievals over land are performed with the main Dark Target algorithm complimented with the Deep Blue (DB) Algorithm over bright deserts. The Dark Target algorithm relies on surface parameterization which relates reflectance in MODIS visible bands with the 2.1 micrometer region, whereas the Deep Blue algorithm uses an ancillary angular distribution model of surface reflectance developed from the time series of clear-sky MODIS observations. Recently, a new Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm has been developed for MODIS. MAIAC uses a time series and an image based processing to perform simultaneous retrievals of aerosol properties and surface bidirectional reflectance. It is a generic algorithm which works over both dark vegetative surfaces and bright deserts and performs retrievals at 1 km resolution. In this work, we will provide a comparative analysis of DB, MAIAC, MISR and OMI aerosol products over bright deserts of northern Africa.

[The progress in retrieving land surface temperature based on thermal infrared and microwave remote sensing technologies].

PubMed

Zhang, Jia-Hua; Li, Xin; Yao, Feng-Mei; Li, Xian-Hua

2009-08-01

Land surface temperature (LST) is an important parameter in the study on the exchange of substance and energy between land surface and air for the land surface physics process at regional and global scales. Many applications of satellites remotely sensed data must provide exact and quantificational LST, such as drought, high temperature, forest fire, earthquake, hydrology and the vegetation monitor, and the models of global circulation and regional climate also need LST as input parameter. Therefore, the retrieval of LST using remote sensing technology becomes one of the key tasks in quantificational remote sensing study. Normally, in the spectrum bands, the thermal infrared (TIR, 3-15 microm) and microwave bands (1 mm-1 m) are important for retrieval of the LST. In the present paper, firstly, several methods for estimating the LST on the basis of thermal infrared (TIR) remote sensing were synthetically reviewed, i. e., the LST measured with an ground-base infrared thermometer, the LST retrieval from mono-window algorithm (MWA), single-channel algorithm (SCA), split-window techniques (SWT) and multi-channels algorithm(MCA), single-channel & multi-angle algorithm and multi-channels algorithm & multi-angle algorithm, and retrieval method of land surface component temperature using thermal infrared remotely sensed satellite observation. Secondly, the study status of land surface emissivity (epsilon) was presented. Thirdly, in order to retrieve LST for all weather conditions, microwave remotely sensed data, instead of thermal infrared data, have been developed recently, and the LST retrieval method from passive microwave remotely sensed data was also introduced. Finally, the main merits and shortcomings of different kinds of LST retrieval methods were discussed, respectively.

Satellite aerosol retrieval using dark target algorithm by coupling BRDF effect over AERONET site

NASA Astrophysics Data System (ADS)

Yang, Leiku; Xue, Yong; Guang, Jie; Li, Chi

2012-11-01

For most satellite aerosol retrieval algorithms even for multi-angle instrument, the simple forward model (FM) based on Lambertian surface assumption is employed to simulate top of the atmosphere (TOA) spectral reflectance, which does not fully consider the surface bi-directional reflectance functions (BRDF) effect. The approximating forward model largely simplifies the radiative transfer model, reduces the size of the look-up tables, and creates faster algorithm. At the same time, it creates systematic biases in the aerosol optical depth (AOD) retrieval. AOD product from the Moderate Resolution Imaging Spectro-radiometer (MODIS) data based on the dark target algorithm is considered as one of accurate satellite aerosol products at present. Though it performs well at a global scale, uncertainties are still found on regional in a lot of studies. The Lambertian surface assumpiton employed in the retrieving algorithm may be one of the uncertain factors. In this study, we first use radiative transfer simulations over dark target to assess the uncertainty to what extent is introduced from the Lambertian surface assumption. The result shows that the uncertainties of AOD retrieval could reach up to ±0.3. Then the Lambertian FM (L_FM) and the BRDF FM (BRDF_FM) are respectively employed in AOD retrieval using dark target algorithm from MODARNSS (MODIS/Terra and MODIS/Aqua Atmosphere Aeronet Subsetting Product) data over Beijing AERONET site. The validation shows that accuracy in AOD retrieval has been improved by employing the BRDF_FM accounting for the surface BRDF effect, the regression slope of scatter plots with retrieved AOD against AEROENET AOD increases from 0.7163 (for L_FM) to 0.7776 (for BRDF_FM) and the intercept decreases from 0.0778 (for L_FM) to 0.0627 (for BRDF_FM).

Large Scale Ice Water Path and 3-D Ice Water Content

DOE Data Explorer

Liu, Guosheng

2008-01-15

Cloud ice water concentration is one of the most important, yet poorly observed, cloud properties. Developing physical parameterizations used in general circulation models through single-column modeling is one of the key foci of the ARM program. In addition to the vertical profiles of temperature, water vapor and condensed water at the model grids, large-scale horizontal advective tendencies of these variables are also required as forcing terms in the single-column models. Observed horizontal advection of condensed water has not been available because the radar/lidar/radiometer observations at the ARM site are single-point measurement, therefore, do not provide horizontal distribution of condensed water. The intention of this product is to provide large-scale distribution of cloud ice water by merging available surface and satellite measurements. The satellite cloud ice water algorithm uses ARM ground-based measurements as baseline, produces datasets for 3-D cloud ice water distributions in a 10 deg x 10 deg area near ARM site. The approach of the study is to expand a (surface) point measurement to an (satellite) areal measurement. That is, this study takes the advantage of the high quality cloud measurements at the point of ARM site. We use the cloud characteristics derived from the point measurement to guide/constrain satellite retrieval, then use the satellite algorithm to derive the cloud ice water distributions within an area, i.e., 10 deg x 10 deg centered at ARM site.

Ensembles of satellite aerosol retrievals based on three AATSR algorithms within aerosol_cci

NASA Astrophysics Data System (ADS)

Kosmale, Miriam; Popp, Thomas

2016-04-01

Ensemble techniques are widely used in the modelling community, combining different modelling results in order to reduce uncertainties. This approach could be also adapted to satellite measurements. Aerosol_cci is an ESA funded project, where most of the European aerosol retrieval groups work together. The different algorithms are homogenized as far as it makes sense, but remain essentially different. Datasets are compared with ground based measurements and between each other. Three AATSR algorithms (Swansea university aerosol retrieval, ADV aerosol retrieval by FMI and Oxford aerosol retrieval ORAC) provide within this project 17 year global aerosol records. Each of these algorithms provides also uncertainty information on pixel level. Within the presented work, an ensembles of the three AATSR algorithms is performed. The advantage over each single algorithm is the higher spatial coverage due to more measurement pixels per gridbox. A validation to ground based AERONET measurements shows still a good correlation of the ensemble, compared to the single algorithms. Annual mean maps show the global aerosol distribution, based on a combination of the three aerosol algorithms. In addition, pixel level uncertainties of each algorithm are used for weighting the contributions, in order to reduce the uncertainty of the ensemble. Results of different versions of the ensembles for aerosol optical depth will be presented and discussed. The results are validated against ground based AERONET measurements. A higher spatial coverage on daily basis allows better results in annual mean maps. The benefit of using pixel level uncertainties is analysed.

Validation of Smithsonian Astrophysical Observatory's OMI Water Vapor Product

NASA Astrophysics Data System (ADS)

Wang, H.; Gonzalez Abad, G.; Liu, X.; Chance, K.

2015-12-01

We perform a comprehensive validation of SAO's OMI water vapor product. The SAO OMI water vapor slant column is retrieved using the 430 - 480 nm wavelength range. In addition to water vapor, the retrieval considers O3, NO2, liquid water, O4, C2H2O2, the Ring effect, water ring, 3rd order polynomial, common mode and under-sampling. The slant column is converted to vertical column using AMF. AMF is calculated using GEOS-Chem water vapor profile shape, OMCLDO2 cloud information and OMLER surface albedo information. We validate our product using NCAR's GPS network data over the world and RSS's gridded microwave data over the ocean. We also compare our product with the total precipitable water derived from the AERONET ground-based sun photometer data, the GlobVapour gridded product, and other datasets. We investigate the influence of sub-grid scale variability and filtering criteria on the comparison. We study the influence of clouds, aerosols and a priori profiles on the retrieval. We also assess the long-term performance and stability of our product and seek ways to improve it.

Evaluation of chlorophyll-a retrieval algorithms based on MERIS bands for optically varying eutrophic inland lakes.

PubMed

Lyu, Heng; Li, Xiaojun; Wang, Yannan; Jin, Qi; Cao, Kai; Wang, Qiao; Li, Yunmei

2015-10-15

Fourteen field campaigns were conducted in five inland lakes during different seasons between 2006 and 2013, and a total of 398 water samples with varying optical characteristics were collected. The characteristics were analyzed based on remote sensing reflectance, and an automatic cluster two-step method was applied for water classification. The inland waters could be clustered into three types, which we labeled water types I, II and III. From water types I to III, the effect of the phytoplankton on the optical characteristics gradually decreased. Four chlorophyll-a retrieval algorithms for Case II water, a two-band, three-band, four-band and SCI (Synthetic Chlorophyll Index) algorithm were evaluated for three water types based on the MERIS bands. Different MERIS bands were used for the three water types in each of the four algorithms. The four algorithms had different levels of retrieval accuracy for each water type, and no single algorithm could be successfully applied to all water types. For water types I and III, the three-band algorithm performed the best, while the four-band algorithm had the highest retrieval accuracy for water type II. However, the three-band algorithm is preferable to the two-band algorithm for turbid eutrophic inland waters. The SCI algorithm is recommended for highly turbid water with a higher concentration of total suspended solids. Our research indicates that the chlorophyll-a concentration retrieval by remote sensing for optically contrasted inland water requires a specific algorithm that is based on the optical characteristics of inland water bodies to obtain higher estimation accuracy. Copyright © 2015 Elsevier B.V. All rights reserved.

Retrieval of tropospheric carbon monoxide for the MOPITT experiment

NASA Astrophysics Data System (ADS)

Pan, Liwen; Gille, John C.; Edwards, David P.; Bailey, Paul L.; Rodgers, Clive D.

1998-12-01

A retrieval method for deriving the tropospheric carbon monoxide (CO) profile and column amount under clear sky conditions has been developed for the Measurements of Pollution In The Troposphere (MOPITT) instrument, scheduled for launch in 1998 onboard the EOS-AM1 satellite. This paper presents a description of the method along with analyses of retrieval information content. These analyses characterize the forward measurement sensitivity, the contribution of a priori information, and the retrieval vertical resolution. Ensembles of tropospheric CO profiles were compiled both from aircraft in situ measurements and from chemical model results and were used in retrieval experiments to characterize the method and to study the sensitivity to different parameters. Linear error analyses were carried out in parallel with the ensemble experiments. Results of these experiments and analyses indicate that MOPITT CO column measurements will have better than 10% precision, and CO profile measurement will have approximately three pieces of independent information that will resolve 3-5 tropospheric layers to approximately 10% precision. These analyses are important for understanding MOPITT data, both for application of data in tropospheric chemistry studies and for comparison with in situ measurements.

Ice surface temperature retrieval from AVHRR, ATSR, and passive microwave satellite data: Algorithm development and application

NASA Technical Reports Server (NTRS)

Key, Jeff; Maslanik, James; Steffen, Konrad

1995-01-01

During the second phase project year we have made progress in the development and refinement of surface temperature retrieval algorithms and in product generation. More specifically, we have accomplished the following: (1) acquired a new advanced very high resolution radiometer (AVHRR) data set for the Beaufort Sea area spanning an entire year; (2) acquired additional along-track scanning radiometer(ATSR) data for the Arctic and Antarctic now totalling over eight months; (3) refined our AVHRR Arctic and Antarctic ice surface temperature (IST) retrieval algorithm, including work specific to Greenland; (4) developed ATSR retrieval algorithms for the Arctic and Antarctic, including work specific to Greenland; (5) developed cloud masking procedures for both AVHRR and ATSR; (6) generated a two-week bi-polar global area coverage (GAC) set of composite images from which IST is being estimated; (7) investigated the effects of clouds and the atmosphere on passive microwave 'surface' temperature retrieval algorithms; and (8) generated surface temperatures for the Beaufort Sea data set, both from AVHRR and special sensor microwave imager (SSM/I).

Collaborative Study of Analysis of High Resolution Infrared Atmospheric Spectra Between NASA Langley Research Center and the University of Denver

NASA Technical Reports Server (NTRS)

Goldman, Aaron

1999-01-01

The Langley-D.U. collaboration on the analysis of high resolution infrared atmospheric spectra covered a number of important studies of trace gases identification and quantification from field spectra, and spectral line parameters analysis. The collaborative work included: Quantification and monitoring of trace gases from ground-based spectra available from various locations and seasons and from balloon flights. Studies toward identification and quantification of isotopic species, mostly oxygen and Sulfur isotopes. Search for new species on the available spectra. Update of spectroscopic line parameters, by combining laboratory and atmospheric spectra with theoretical spectroscopy methods. Study of trends of atmosphere trace constituents. Algorithms developments, retrievals intercomparisons and automatization of the analysis of NDSC spectra, for both column amounts and vertical profiles.

Evaluation of Cloud and Aerosol Screening of Early Orbiting Carbon Observatory-2 (OCO-2) Observations with Collocated MODIS Cloud Mask

NASA Astrophysics Data System (ADS)

Nelson, R. R.; Taylor, T.; O'Dell, C.; Cronk, H. Q.; Partain, P.; Frankenberg, C.; Eldering, A.; Crisp, D.; Gunson, M. R.; Chang, A.; Fisher, B.; Osterman, G. B.; Pollock, H. R.; Savtchenko, A.; Rosenthal, E. J.

2015-12-01

Effective cloud and aerosol screening is critically important to the Orbiting Carbon Observatory-2 (OCO-2), which can accurately determine column averaged dry air mole fraction of carbon dioxide (XCO2) only when scenes are sufficiently clear of scattering material. It is crucial to avoid sampling biases, in order to maintain a globally unbiased XCO2 record for inversion modeling to determine sources and sinks of carbon dioxide. This work presents analysis from the current operational B7 data set, which is identifying as clear approximately 20% of the order one million daily soundings. Of those soundings that are passed to the L2 retrieval algorithm, we find that almost 80% are yielding XCO2 estimates that converge. Two primary preprocessor algorithms are used to cloud screen the OCO-2 soundings. The A-Band Preprocessor (ABP) uses measurements in the Oxygen-A band near 0.76 microns (mm) to determine scenes with large photon path length modifications due to scattering by aerosol and clouds. The Iterative Maximum A-Posteriori (IMAP) Differential Optical Absorption Spectroscopy (DOAS) algorithm (IDP) computes ratios of retrieved CO2 (and H2O) in the 1.6mm (weak CO2) and 2.0mm (strong CO2) spectral bands to determine scenes with spectral differences, indicating contamination by scattering materials. We demonstrate that applying these two algorithms in tandem provides robust cloud screening of the OCO-2 data set. We compare the OCO-2 cloud screening results to collocated Moderate Resolution Imaging Spectroradiometer (MODIS) cloud mask data and show that agreement between the two sensors is approximately 85-90%. A detailed statistical analysis is performed on a winter and spring 16-day repeat cycle for the nadir-land, glint-land and glint-water viewing geometries. No strong seasonal, spatial or footprint dependencies are found, although the agreement tends to be worse at high solar zenith angles and for snow and ice covered surfaces.

Phase retrieval using regularization method in intensity correlation imaging

NASA Astrophysics Data System (ADS)

Li, Xiyu; Gao, Xin; Tang, Jia; Lu, Changming; Wang, Jianli; Wang, Bin

2014-11-01

Intensity correlation imaging(ICI) method can obtain high resolution image with ground-based low precision mirrors, in the imaging process, phase retrieval algorithm should be used to reconstituted the object's image. But the algorithm now used(such as hybrid input-output algorithm) is sensitive to noise and easy to stagnate. However the signal-to-noise ratio of intensity interferometry is low especially in imaging astronomical objects. In this paper, we build the mathematical model of phase retrieval and simplified it into a constrained optimization problem of a multi-dimensional function. New error function was designed by noise distribution and prior information using regularization method. The simulation results show that the regularization method can improve the performance of phase retrieval algorithm and get better image especially in low SNR condition

An Alternative Retrieval Algorithm for the Ozone Mapping and Profiler Suite Limb Profiler

DTIC Science & Technology

2012-05-01

behavior of aerosol extinction from the upper troposphere through the stratosphere is critical for retrieving ozone in this region. Aerosol scattering is......include area code) b. ABSTRACT c. THIS PAGE 18. NUMBER OF PAGES 17. LIMITATION OF ABSTRACT An Alternative Retrieval Algorithm for the Ozone Mapping and

CO2 variability from in situ and vertical column measurements in Mexico City

NASA Astrophysics Data System (ADS)

Baylon, J. L.; Grutter, M.; Stremme, W.; Bezanilla, A.; Plaza, E.

2014-12-01

UNAM started a program to measure, among many other atmospheric parameters, greenhouse gas concentrations at six stations in the Mexican territory as part of the "Red Universitaria de Observatorios Atmosfericos", RUOA (www.ruoa.unam.mx). In this work we present recent time series of CO2 measured at the station located in the university campus in Mexico City, and compare them to total vertical columns of this gas measured at the same location. In situ measurements are continuously carried out with a cavity ring-down spectrometer (Picarro Inc., G2401) since July 2014 and the columns are retrieved from solar absorption measurements taken with a Fourier transform infrared spectrometer (Bruker, Vertex 80) when conditions allow. The retrieval method is described and results of the comparison of both techniques and a detailed analysis of the variability of this important greenhouse gas is presented. Simultaneous surface and column CO2 data are useful to constrain models and estimate emissions.

Abundances of Jupiter's Trace Hydrocarbons from Voyager and Cassini. Data Tables: Cassini CIRS Observations Planetary and Space Science, Forthcoming 2010

NASA Technical Reports Server (NTRS)

Nixon, C. A.; Achterberg, R. K.; Romani, P. N.; Allen, M.; Zhang, X.; Teanby, N. A.; Irwin, P. G. J.; Flasar, F. M.

2010-01-01

The following six tables give the retrieved temperatures and volume mixing ratios of C2H2 and C2H6 and the formal errors on these results from the retrieval, as described in the manuscript. These are in the form of two-dimensional tables, specified on a latitudinal and vertical grid. The first column is the pressure in bar, and the second column gives the altitude in kilometers calculated from hydrostatic equilibrium, and applies to the equatorial profile only. The top row of the table specifies the planetographic latitude.

Abundances of Jupiter's Trace Hydrocarbons from Voyager and Cassini. Data Tables: Voyager IRIS Observations Planetary and Space Science, Forthcoming 2010

NASA Technical Reports Server (NTRS)

Nixon, C. A.; Achterberg, R. K.; Romani, P. N.; Allen, M.; Zhang, X.; Irwin, P. G. J.; Flasar, F. M.

2010-01-01

The following six tables give the retrieved temperatures and volume mixing ratios of C2H2 and C2H6 and the formal errors on these results from the retrieval, as described in the manuscript. These are in the form of two-dimensional tables, specified on a latitudinal and vertical grid. The first column is the pressure in bar, and the second column gives the altitude in kilometers calculated from hydrostatic equilibrium, and applies to the equatorial profile only. The top row of the table specifies the planetographic latitude.

Visualizing and improving the robustness of phase retrieval algorithms

DOE PAGES

Tripathi, Ashish; Leyffer, Sven; Munson, Todd; ...

2015-06-01

Coherent x-ray diffractive imaging is a novel imaging technique that utilizes phase retrieval and nonlinear optimization methods to image matter at nanometer scales. We explore how the convergence properties of a popular phase retrieval algorithm, Fienup's HIO, behave by introducing a reduced dimensionality problem allowing us to visualize and quantify convergence to local minima and the globally optimal solution. We then introduce generalizations of HIO that improve upon the original algorithm's ability to converge to the globally optimal solution.

Visualizing and improving the robustness of phase retrieval algorithms

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tripathi, Ashish; Leyffer, Sven; Munson, Todd

Coherent x-ray diffractive imaging is a novel imaging technique that utilizes phase retrieval and nonlinear optimization methods to image matter at nanometer scales. We explore how the convergence properties of a popular phase retrieval algorithm, Fienup's HIO, behave by introducing a reduced dimensionality problem allowing us to visualize and quantify convergence to local minima and the globally optimal solution. We then introduce generalizations of HIO that improve upon the original algorithm's ability to converge to the globally optimal solution.

Vertical profiles of aerosol optical properties and the solar heating rate estimated by combining sky radiometer and lidar measurements

NASA Astrophysics Data System (ADS)

Kudo, Rei; Nishizawa, Tomoaki; Aoyagi, Toshinori

2016-07-01

The SKYLIDAR algorithm was developed to estimate vertical profiles of aerosol optical properties from sky radiometer (SKYNET) and lidar (AD-Net) measurements. The solar heating rate was also estimated from the SKYLIDAR retrievals. The algorithm consists of two retrieval steps: (1) columnar properties are retrieved from the sky radiometer measurements and the vertically mean depolarization ratio obtained from the lidar measurements and (2) vertical profiles are retrieved from the lidar measurements and the results of the first step. The derived parameters are the vertical profiles of the size distribution, refractive index (real and imaginary parts), extinction coefficient, single-scattering albedo, and asymmetry factor. Sensitivity tests were conducted by applying the SKYLIDAR algorithm to the simulated sky radiometer and lidar data for vertical profiles of three different aerosols, continental average, transported dust, and pollution aerosols. The vertical profiles of the size distribution, extinction coefficient, and asymmetry factor were well estimated in all cases. The vertical profiles of the refractive index and single-scattering albedo of transported dust, but not those of transported pollution aerosol, were well estimated. To demonstrate the performance and validity of the SKYLIDAR algorithm, we applied the SKYLIDAR algorithm to the actual measurements at Tsukuba, Japan. The detailed vertical structures of the aerosol optical properties and solar heating rate of transported dust and smoke were investigated. Examination of the relationship between the solar heating rate and the aerosol optical properties showed that the vertical profile of the asymmetry factor played an important role in creating vertical variation in the solar heating rate. We then compared the columnar optical properties retrieved with the SKYLIDAR algorithm to those produced with the more established scheme SKYRAD.PACK, and the surface solar irradiance calculated from the SKYLIDAR retrievals was compared with pyranometer measurement. The results showed good agreements: the columnar values of the SKYLIDAR retrievals agreed with reliable SKYRAD.PACK retrievals, and the SKYLIDAR retrievals were sufficiently accurate to evaluate the surface solar irradiance.

A method to account for the temperature sensitivity of TCCON total column measurements

NASA Astrophysics Data System (ADS)

Niebling, Sabrina G.; Wunch, Debra; Toon, Geoffrey C.; Wennberg, Paul O.; Feist, Dietrich G.

2014-05-01

The Total Carbon Column Observing Network (TCCON) consists of ground-based Fourier Transform Spectrometer (FTS) systems all around the world. It achieves better than 0.25% precision and accuracy for total column measurements of CO2 [Wunch et al. (2011)]. In recent years, the TCCON data processing and retrieval software (GGG) has been improved to achieve better and better results (e. g. ghost correction, improved a priori profiles, more accurate spectroscopy). However, a small error is also introduced by the insufficent knowledge of the true temperature profile in the atmosphere above the individual instruments. This knowledge is crucial to retrieve highly precise gas concentrations. In the current version of the retrieval software, we use six-hourly NCEP reanalysis data to produce one temperature profile at local noon for each measurement day. For sites in the mid latitudes which can have a large diurnal variation of the temperature in the lowermost kilometers of the atmosphere, this approach can lead to small errors in the final gas concentration of the total column. Here, we present and describe a method to account for the temperature sensitivity of the total column measurements. We exploit the fact that H2O is most abundant in the lowermost kilometers of the atmosphere where the largest diurnal temperature variations occur. We use single H2O absorption lines with different temperature sensitivities to gain information about the temperature variations over the course of the day. This information is used to apply a posteriori correction of the retrieved gas concentration of total column. In addition, we show that the a posteriori temperature correction is effective by applying it to data from Lamont, Oklahoma, USA (36,6°N and 97,5°W). We chose this site because regular radiosonde launches with a time resolution of six hours provide detailed information of the real temperature in the atmosphere and allow us to test the effectiveness of our correction. References: Wunch, D., Toon, G. C., Blavier, J.-F. L., Washenfelder, R. A., Notholt, J., Connor, B. J., Griffith, D. W. T., Sherlock, V., and Wennberg, P. O.: The Total Carbon Column Observing Network, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 369, 2087-2112, 2011.

Information Retrieval and Graph Analysis Approaches for Book Recommendation.

PubMed

Benkoussas, Chahinez; Bellot, Patrice

2015-01-01

A combination of multiple information retrieval approaches is proposed for the purpose of book recommendation. In this paper, book recommendation is based on complex user's query. We used different theoretical retrieval models: probabilistic as InL2 (Divergence from Randomness model) and language model and tested their interpolated combination. Graph analysis algorithms such as PageRank have been successful in Web environments. We consider the application of this algorithm in a new retrieval approach to related document network comprised of social links. We called Directed Graph of Documents (DGD) a network constructed with documents and social information provided from each one of them. Specifically, this work tackles the problem of book recommendation in the context of INEX (Initiative for the Evaluation of XML retrieval) Social Book Search track. A series of reranking experiments demonstrate that combining retrieval models yields significant improvements in terms of standard ranked retrieval metrics. These results extend the applicability of link analysis algorithms to different environments.

Information Retrieval and Graph Analysis Approaches for Book Recommendation

PubMed Central

Benkoussas, Chahinez; Bellot, Patrice

2015-01-01

A combination of multiple information retrieval approaches is proposed for the purpose of book recommendation. In this paper, book recommendation is based on complex user's query. We used different theoretical retrieval models: probabilistic as InL2 (Divergence from Randomness model) and language model and tested their interpolated combination. Graph analysis algorithms such as PageRank have been successful in Web environments. We consider the application of this algorithm in a new retrieval approach to related document network comprised of social links. We called Directed Graph of Documents (DGD) a network constructed with documents and social information provided from each one of them. Specifically, this work tackles the problem of book recommendation in the context of INEX (Initiative for the Evaluation of XML retrieval) Social Book Search track. A series of reranking experiments demonstrate that combining retrieval models yields significant improvements in terms of standard ranked retrieval metrics. These results extend the applicability of link analysis algorithms to different environments. PMID:26504899

The GRAPE aerosol retrieval algorithm

NASA Astrophysics Data System (ADS)

Thomas, G. E.; Poulsen, C. A.; Sayer, A. M.; Marsh, S. H.; Dean, S. M.; Carboni, E.; Siddans, R.; Grainger, R. G.; Lawrence, B. N.

2009-11-01

The aerosol component of the Oxford-Rutherford Aerosol and Cloud (ORAC) combined cloud and aerosol retrieval scheme is described and the theoretical performance of the algorithm is analysed. ORAC is an optimal estimation retrieval scheme for deriving cloud and aerosol properties from measurements made by imaging satellite radiometers and, when applied to cloud free radiances, provides estimates of aerosol optical depth at a wavelength of 550 nm, aerosol effective radius and surface reflectance at 550 nm. The aerosol retrieval component of ORAC has several incarnations - this paper addresses the version which operates in conjunction with the cloud retrieval component of ORAC (described by Watts et al., 1998), as applied in producing the Global Retrieval of ATSR Cloud Parameters and Evaluation (GRAPE) data-set. The algorithm is described in detail and its performance examined. This includes a discussion of errors resulting from the formulation of the forward model, sensitivity of the retrieval to the measurements and a priori constraints, and errors resulting from assumptions made about the atmospheric/surface state.

The GRAPE aerosol retrieval algorithm

NASA Astrophysics Data System (ADS)

Thomas, G. E.; Poulsen, C. A.; Sayer, A. M.; Marsh, S. H.; Dean, S. M.; Carboni, E.; Siddans, R.; Grainger, R. G.; Lawrence, B. N.

2009-04-01

The aerosol component of the Oxford-Rutherford Aerosol and Cloud (ORAC) combined cloud and aerosol retrieval scheme is described and the theoretical performance of the algorithm is analysed. ORAC is an optimal estimation retrieval scheme for deriving cloud and aerosol properties from measurements made by imaging satellite radiometers and, when applied to cloud free radiances, provides estimates of aerosol optical depth at a wavelength of 550 nm, aerosol effective radius and surface reflectance at 550 nm. The aerosol retrieval component of ORAC has several incarnations - this paper addresses the version which operates in conjunction with the cloud retrieval component of ORAC (described by Watts et al., 1998), as applied in producing the Global Retrieval of ATSR Cloud Parameters and Evaluation (GRAPE) data-set. The algorithm is described in detail and its performance examined. This includes a discussion of errors resulting from the formulation of the forward model, sensitivity of the retrieval to the measurements and a priori constraints, and errors resulting from assumptions made about the atmospheric/surface state.

A 1DVAR-based snowfall rate retrieval algorithm for passive microwave radiometers

NASA Astrophysics Data System (ADS)

Meng, Huan; Dong, Jun; Ferraro, Ralph; Yan, Banghua; Zhao, Limin; Kongoli, Cezar; Wang, Nai-Yu; Zavodsky, Bradley

2017-06-01

Snowfall rate retrieval from spaceborne passive microwave (PMW) radiometers has gained momentum in recent years. PMW can be so utilized because of its ability to sense in-cloud precipitation. A physically based, overland snowfall rate (SFR) algorithm has been developed using measurements from the Advanced Microwave Sounding Unit-A/Microwave Humidity Sounder sensor pair and the Advanced Technology Microwave Sounder. Currently, these instruments are aboard five polar-orbiting satellites, namely, NOAA-18, NOAA-19, Metop-A, Metop-B, and Suomi-NPP. The SFR algorithm relies on a separate snowfall detection algorithm that is composed of a satellite-based statistical model and a set of numerical weather prediction model-based filters. There are four components in the SFR algorithm itself: cloud properties retrieval, computation of ice particle terminal velocity, ice water content adjustment, and the determination of snowfall rate. The retrieval of cloud properties is the foundation of the algorithm and is accomplished using a one-dimensional variational (1DVAR) model. An existing model is adopted to derive ice particle terminal velocity. Since no measurement of cloud ice distribution is available when SFR is retrieved in near real time, such distribution is implicitly assumed by deriving an empirical function that adjusts retrieved SFR toward radar snowfall estimates. Finally, SFR is determined numerically from a complex integral. The algorithm has been validated against both radar and ground observations of snowfall events from the contiguous United States with satisfactory results. Currently, the SFR product is operationally generated at the National Oceanic and Atmospheric Administration and can be obtained from that organization.

Information content of ozone retrieval algorithms

NASA Technical Reports Server (NTRS)

Rodgers, C.; Bhartia, P. K.; Chu, W. P.; Curran, R.; Deluisi, J.; Gille, J. C.; Hudson, R.; Mateer, C.; Rusch, D.; Thomas, R. J.

1989-01-01

The algorithms are characterized that were used for production processing by the major suppliers of ozone data to show quantitatively: how the retrieved profile is related to the actual profile (This characterizes the altitude range and vertical resolution of the data); the nature of systematic errors in the retrieved profiles, including their vertical structure and relation to uncertain instrumental parameters; how trends in the real ozone are reflected in trends in the retrieved ozone profile; and how trends in other quantities (both instrumental and atmospheric) might appear as trends in the ozone profile. No serious deficiencies were found in the algorithms used in generating the major available ozone data sets. As the measurements are all indirect in someway, and the retrieved profiles have different characteristics, data from different instruments are not directly comparable.

Optimal Aerosol Parameterization for Remote Sensing Retrievals

NASA Technical Reports Server (NTRS)

Newchurch, Michael J.

2004-01-01

We have developed a new algorithm for the retrieval of aerosol and gases from SAGE It1 solar transmission measurements. This algorithm improves upon the NASA operational algorithm in several key aspects, including solving the problem non-linearly and incorporating a new methodology for separating the contribution of aerosols and gases. In order to extract aerosol information we have built a huge database of aerosol models for both stratospheric and tropospheric aerosols, and polar stratospheric cloud particles. This set of models allows us to calculate a vast range of possible extinction spectra for aerosols. and from these, derive a set of eigenvectors which then provide the basis set used in our inversion algorithm. Our aerosol algorithm and retrievals are described in several articles (listed in References Section) published under this grant. In particular they allow us to analyze the spectral properties of aerosols and PSCs and ultimately derive their microphysical properties. We have found some considerable differences between our spectra and the ones derived from the SAGE III operational algorithm. These are interesting as they provide an independent check on the validity of published aerosol data and, in particular, on their associated uncertainties. In order to understand these differences, we are assembling independent aerosol data from other sources with which to make comparisons. We have carried out extensive comparisons of our ozone retrievals with both SAGE III and independent lidar, ozonesonde, and satellite measurements (Polyakov et al., 2004). These show very good agreement throughout the stratosphere and help to quantify differences which can be attributed to natural variation in ozone versus that produced by algorithmic differences. In the mid - upper stratosphere, agreement with independent data was generally within 5 - 20%. but in the lower stratosphere the differences were considerably larger. We believe that a large proportion of this discrepancy in the lower stratosphere is attributable to natural variation, and is also seen in comparisons between lidar and ozonesonde measurements. NO2 profiles obtained with our algorithm were compared to those obtained through the SAGE III operational algorithm and exhibited differences of 20 - 40%. Our retrieved profiles agree with the HALOE NO2 measurements significantly better than those of the operational retrieval. In other work (described below), we are extending our aerosol retrievals into the infrared regime and plan to perform retrievals from combined uv-visible-infrared spectra. This work will allow us to use the spectra to derive the size and composition of aerosols, and we plan to employ our algorithms in the analysis of PSC spectra. We are presently also developing a limb-scattering algorithm to retrieve aerosol data from limb measurements of solar scattered radiation.

Application of stochastic particle swarm optimization algorithm to determine the graded refractive index distribution in participating media

NASA Astrophysics Data System (ADS)

Wei, Lin-Yang; Qi, Hong; Ren, Ya-Tao; Ruan, Li-Ming

2016-11-01

Inverse estimation of the refractive index distribution in one-dimensional participating media with graded refractive index (GRI) is investigated. The forward radiative transfer problem is solved by the Chebyshev collocation spectral method. The stochastic particle swarm optimization (SPSO) algorithm is employed to retrieve three kinds of GRI distribution, i.e. the linear, sinusoidal and quadratic GRI distribution. The retrieval accuracy of GRI distribution with different wall emissivity, optical thickness, absorption coefficients and scattering coefficients are discussed thoroughly. To improve the retrieval accuracy of quadratic GRI distribution, a double-layer model is proposed to supply more measurement information. The influence of measurement errors upon the precision of estimated results is also investigated. Considering the GRI distribution is unknown beforehand in practice, a quadratic function is employed to retrieve the linear GRI by SPSO algorithm. All the results show that the SPSO algorithm is applicable to retrieve different GRI distributions in participating media accurately even with noisy data.

Dreaming of Atmospheres

NASA Astrophysics Data System (ADS)

Waldmann, I. P.

2016-04-01

Here, we introduce the RobERt (Robotic Exoplanet Recognition) algorithm for the classification of exoplanetary emission spectra. Spectral retrieval of exoplanetary atmospheres frequently requires the preselection of molecular/atomic opacities to be defined by the user. In the era of open-source, automated, and self-sufficient retrieval algorithms, manual input should be avoided. User dependent input could, in worst-case scenarios, lead to incomplete models and biases in the retrieval. The RobERt algorithm is based on deep-belief neural (DBN) networks trained to accurately recognize molecular signatures for a wide range of planets, atmospheric thermal profiles, and compositions. Reconstructions of the learned features, also referred to as the “dreams” of the network, indicate good convergence and an accurate representation of molecular features in the DBN. Using these deep neural networks, we work toward retrieval algorithms that themselves understand the nature of the observed spectra, are able to learn from current and past data, and make sensible qualitative preselections of atmospheric opacities to be used for the quantitative stage of the retrieval process.

Remote Sensing of Cloud Properties using Ground-based Measurements of Zenith Radiance

NASA Technical Reports Server (NTRS)

Chiu, J. Christine; Marshak, Alexander; Knyazikhin, Yuri; Wiscombe, Warren J.; Barker, Howard W.; Barnard, James C.; Luo, Yi

2006-01-01

An extensive verification of cloud property retrievals has been conducted for two algorithms using zenith radiances measured by the Atmospheric Radiation Measurement (ARM) Program ground-based passive two-channel (673 and 870 nm) Narrow Field-Of-View Radiometer. The underlying principle of these algorithms is that clouds have nearly identical optical properties at these wavelengths, but corresponding spectral surface reflectances (for vegetated surfaces) differ significantly. The first algorithm, the RED vs. NIR, works for a fully three-dimensional cloud situation. It retrieves not only cloud optical depth, but also an effective radiative cloud fraction. Importantly, due to one-second time resolution of radiance measurements, we are able, for the first time, to capture detailed changes in cloud structure at the natural time scale of cloud evolution. The cloud optical depths tau retrieved by this algorithm are comparable to those inferred from both downward fluxes in overcast situations and microwave brightness temperatures for broken clouds. Moreover, it can retrieve tau for thin patchy clouds, where flux and microwave observations fail to detect them. The second algorithm, referred to as COUPLED, couples zenith radiances with simultaneous fluxes to infer 2. In general, the COUPLED and RED vs. NIR algorithms retrieve consistent values of tau. However, the COUPLED algorithm is more sensitive to the accuracies of measured radiance, flux, and surface reflectance than the RED vs. NIR algorithm. This is especially true for thick overcast clouds where it may substantially overestimate z.

A new retrieval algorithm for tropospheric temperature, humidity and pressure profiling based on GNSS radio occultation data

NASA Astrophysics Data System (ADS)

Kirchengast, Gottfried; Li, Ying; Scherllin-Pirscher, Barbara; Schwärz, Marc; Schwarz, Jakob; Nielsen, Johannes K.

2017-04-01

The GNSS radio occultation (RO) technique is an important remote sensing technique for obtaining thermodynamic profiles of temperature, humidity, and pressure in the Earth's troposphere. However, due to refraction effects of both dry ambient air and water vapor in the troposphere, retrieval of accurate thermodynamic profiles at these lower altitudes is challenging and requires suitable background information in addition to the RO refractivity information. Here we introduce a new moist air retrieval algorithm aiming to improve the quality and robustness of retrieving temperature, humidity and pressure profiles in moist air tropospheric conditions. The new algorithm consists of four steps: (1) use of prescribed specific humidity and its uncertainty to retrieve temperature and its associated uncertainty; (2) use of prescribed temperature and its uncertainty to retrieve specific humidity and its associated uncertainty; (3) use of the previous results to estimate final temperature and specific humidity profiles through optimal estimation; (4) determination of air pressure and density profiles from the results obtained before. The new algorithm does not require elaborated matrix inversions which are otherwise widely used in 1D-Var retrieval algorithms, and it allows a transparent uncertainty propagation, whereby the uncertainties of prescribed variables are dynamically estimated accounting for their spatial and temporal variations. Estimated random uncertainties are calculated by constructing error covariance matrices from co-located ECMWF short-range forecast and corresponding analysis profiles. Systematic uncertainties are estimated by empirical modeling. The influence of regarding or disregarding vertical error correlations is quantified. The new scheme is implemented with static input uncertainty profiles in WEGC's current OPSv5.6 processing system and with full scope in WEGC's next-generation system, the Reference Occultation Processing System (rOPS). Results from both WEGC systems, current OPSv5.6 and next-generation rOPS, are shown and discussed, based on both insights from individual profiles and statistical ensembles, and compared to moist air retrieval results from the UCAR Boulder and ROM-SAF Copenhagen centers. The results show that the new algorithmic scheme improves the temperature, humidity and pressure retrieval performance, in particular also the robustness including for integrated uncertainty estimation for large-scale applications, over the previous algorithms. The new rOPS-implemented algorithm will therefore be used in the first large-scale reprocessing towards a tropospheric climate data record 2001-2016 by the rOPS, including its integrated uncertainty propagation.

Assessing Surface BRDF-related Biases Using Target Mode Retrievals from the Orbiting Carbon Observatory-2 (OCO-2)

NASA Astrophysics Data System (ADS)

Natraj, V.; McDuffie, J. L.; O'Dell, C.; Eldering, A.; Fu, D.; Wunch, D.; Wennberg, P. O.

2015-12-01

The Orbiting Carbon Observatory-2 (OCO-2) is NASA's first dedicated Earth remote sensing satellite to study atmospheric carbon dioxide from space, and was launched successfully on July 2, 2014. In the target mode of observation, the Observatory will lock its view onto a specific surface location, and will scan back and forth over that target while flying overhead. A target track pass can last for up to 9 minutes. Over that time period, the Observatory can acquire as many as 12,960 samples at local zenith angles that vary between 0° and 85°. Here, we analyze target track measurements over several of the OCO-2 validation sites where ground-based solar-looking Fourier Transform Spectrometers are located. Preliminary analysis of target mode retrievals using the operational algorithm show biases that appear to be due to not accounting for bidirectional surface reflection (BRDF) effects, i.e., the non-isotropic nature of surface reflection. To address this issue, we implement a realistic BRDF model. The column averaged CO2 dry air mole fraction (XCO2) results using this new model show much less variation with scattering angle (or airmass). Further, the retrieved aerosol optical depth (AOD) is in much better agreement with coincident AERONET values. We also use information content analysis to evaluate the degrees of freedom with respect to BRDF parameters, and investigate cross-correlations between the parameters.

Does the Acquisition of Spatial Skill Involve a Shift from Algorithm to Memory Retrieval?

ERIC Educational Resources Information Center

Frank, David J.; Macnamara, Brooke N.

2017-01-01

Performance on verbal and mathematical tasks is enhanced when participants shift from using algorithms to retrieving information directly from memory (Siegler, 1988a). However, it is unknown whether a shift to retrieval is involved in dynamic spatial skill acquisition. For example, do athletes mentally extrapolate the trajectory of the ball, or do…

Assessment of Uncertainty in Cloud Radiative Effects and Heating Rates through Retrieval Algorithm Differences: Analysis using 3-years of ARM data at Darwin, Australia

DOE Office of Scientific and Technical Information (OSTI.GOV)

Comstock, Jennifer M.; Protat, Alain; McFarlane, Sally A.

2013-05-22

Ground-based radar and lidar observations obtained at the Department of Energy’s Atmospheric Radiation Measurement Program’s Tropical Western Pacific site located in Darwin, Australia are used to retrieve ice cloud properties in anvil and cirrus clouds. Cloud microphysical properties derived from four different retrieval algorithms (two radar-lidar and two radar only algorithms) are compared by examining mean profiles and probability density functions of effective radius (Re), ice water content (IWC), extinction, ice number concentration, ice crystal fall speed, and vertical air velocity. Retrieval algorithm uncertainty is quantified using radiative flux closure exercises. The effect of uncertainty in retrieved quantities on themore » cloud radiative effect and radiative heating rates are presented. Our analysis shows that IWC compares well among algorithms, but Re shows significant discrepancies, which is attributed primarily to assumptions of particle shape. Uncertainty in Re and IWC translates into sometimes-large differences in cloud radiative effect (CRE) though the majority of cases have a CRE difference of roughly 10 W m-2 on average. These differences, which we believe are primarily driven by the uncertainty in Re, can cause up to 2 K/day difference in the radiative heating rates between algorithms.« less

Comparison of snow depth retrieval algorithm in Northeastern China based on AMSR2 and FY3B-MWRI data

NASA Astrophysics Data System (ADS)

Fan, Xintong; Gu, Lingjia; Ren, Ruizhi; Zhou, Tingting

2017-09-01

Snow accumulation has a very important influence on the natural environment and human activities. Meanwhile, improving the estimation accuracy of passive microwave snow depth (SD) retrieval is a hotspot currently. Northeastern China is a typical snow study area including many different land cover types, such as forest, grassland and farmland. Especially, there is relatively stable snow accumulation in January every year. The brightness temperatures which are observed by the Advanced Microwave Scanning Radiometer 2 (AMSR2) on GCOM-W1 and FengYun3B Microwave Radiation Imager (FY3B-MWRI) in the same period in 2013 are selected as the study data in the research. The results of snow depth retrieval using AMSR2 standard algorithm and Jiang's FY operational algorithm are compared in the research. Moreover, to validate the accuracy of the two algorithms, the retrieval results are compared with the SD data observed at the national meteorological stations in Northeastern China. Furthermore, the retrieval SD is also compared with AMSR2 and FY standard SD products, respectively. The root mean square errors (RMSE) results using AMSR2 standard algorithms and FY operational algorithm are close in the forest surface, which are 6.33cm and 6.28cm, respectively. However, The FY operational algorithm shows a better result than the AMSR2 standard algorithms in the grassland and farmland surface. The RMSE results using FY operational algorithm in the grassland and farmland surface are 2.44cm and 6.13cm, respectively.

4SM: A Novel Self-Calibrated Algebraic Ratio Method for Satellite-Derived Bathymetry and Water Column Correction

PubMed Central

Morel, Yann G.; Favoretto, Fabio

2017-01-01

All empirical water column correction methods have consistently been reported to require existing depth sounding data for the purpose of calibrating a simple depth retrieval model; they yield poor results over very bright or very dark bottoms. In contrast, we set out to (i) use only the relative radiance data in the image along with published data, and several new assumptions; (ii) in order to specify and operate the simplified radiative transfer equation (RTE); (iii) for the purpose of retrieving both the satellite derived bathymetry (SDB) and the water column corrected spectral reflectance over shallow seabeds. Sea truth regressions show that SDB depths retrieved by the method only need tide correction. Therefore it shall be demonstrated that, under such new assumptions, there is no need for (i) formal atmospheric correction; (ii) conversion of relative radiance into calibrated reflectance; or (iii) existing depth sounding data, to specify the simplified RTE and produce both SDB and spectral water column corrected radiance ready for bottom typing. Moreover, the use of the panchromatic band for that purpose is introduced. Altogether, we named this process the Self-Calibrated Supervised Spectral Shallow-sea Modeler (4SM). This approach requires a trained practitioner, though, to produce its results within hours of downloading the raw image. The ideal raw image should be a “near-nadir” view, exhibit homogeneous atmosphere and water column, include some coverage of optically deep waters and bare land, and lend itself to quality removal of haze, atmospheric adjacency effect, and sun/sky glint. PMID:28754028

4SM: A Novel Self-Calibrated Algebraic Ratio Method for Satellite-Derived Bathymetry and Water Column Correction.

PubMed

Morel, Yann G; Favoretto, Fabio

2017-07-21

All empirical water column correction methods have consistently been reported to require existing depth sounding data for the purpose of calibrating a simple depth retrieval model; they yield poor results over very bright or very dark bottoms. In contrast, we set out to (i) use only the relative radiance data in the image along with published data, and several new assumptions; (ii) in order to specify and operate the simplified radiative transfer equation (RTE); (iii) for the purpose of retrieving both the satellite derived bathymetry (SDB) and the water column corrected spectral reflectance over shallow seabeds. Sea truth regressions show that SDB depths retrieved by the method only need tide correction. Therefore it shall be demonstrated that, under such new assumptions, there is no need for (i) formal atmospheric correction; (ii) conversion of relative radiance into calibrated reflectance; or (iii) existing depth sounding data, to specify the simplified RTE and produce both SDB and spectral water column corrected radiance ready for bottom typing. Moreover, the use of the panchromatic band for that purpose is introduced. Altogether, we named this process the Self-Calibrated Supervised Spectral Shallow-sea Modeler (4SM). This approach requires a trained practitioner, though, to produce its results within hours of downloading the raw image. The ideal raw image should be a "near-nadir" view, exhibit homogeneous atmosphere and water column, include some coverage of optically deep waters and bare land, and lend itself to quality removal of haze, atmospheric adjacency effect, and sun/sky glint.

Optimization of the GSFC TROPOZ DIAL retrieval using synthetic lidar returns and ozonesondes - Part 1: Algorithm validation

NASA Astrophysics Data System (ADS)

Sullivan, J. T.; McGee, T. J.; Leblanc, T.; Sumnicht, G. K.; Twigg, L. W.

2015-04-01

The main purpose of the NASA Goddard Space Flight Center TROPospheric OZone DIfferential Absorption Lidar (GSFC TROPOZ DIAL) is to measure the vertical distribution of tropospheric ozone for science investigations. Because of the important health and climate impacts of tropospheric ozone, it is imperative to quantify background photochemical and aloft ozone concentrations, especially during air quality episodes. To better characterize tropospheric ozone, the Tropospheric Ozone Lidar Network (TOLNet) has recently been developed, which currently consists of five different ozone DIAL instruments, including the TROPOZ. This paper addresses the necessary procedures to validate the TROPOZ retrieval algorithm and develops a primary standard for retrieval consistency and optimization within TOLNet. This paper is focused on ensuring the TROPOZ and future TOLNet algorithms are properly quantifying ozone concentrations and the following paper will focus on defining a systematic uncertainty analysis standard for all TOLNet instruments. Although this paper is used to optimize the TROPOZ retrieval, the methodology presented may be extended and applied to most other DIAL instruments, even if the atmospheric product of interest is not tropospheric ozone (e.g. temperature or water vapor). The analysis begins by computing synthetic lidar returns from actual TROPOZ lidar return signals in combination with a known ozone profile. From these synthetic signals, it is possible to explicitly determine retrieval algorithm biases from the known profile, thereby identifying any areas that may need refinement for a new operational version of the TROPOZ retrieval algorithm. A new vertical resolution scheme is presented, which was upgraded from a constant vertical resolution to a variable vertical resolution, in order to yield a statistical uncertainty of <10%. The optimized vertical resolution scheme retains the ability to resolve fluctuations in the known ozone profile and now allows near field signals to be more appropriately smoothed. With these revisions, the optimized TROPOZ retrieval algorithm (TROPOZopt) has been effective in retrieving nearly 200 m lower to the surface. Also, as compared to the previous version of the retrieval, the TROPOZopt has reduced the mean profile bias by 3.5% and large reductions in bias (near 15 %) were apparent above 4.5 km. Finally, to ensure the TROPOZopt retrieval algorithm is robust enough to handle actual lidar return signals, a comparison is shown between four nearby ozonesonde measurements. The ozonesondes agree well with the retrieval and are mostly within the TROPOZopt retrieval uncertainty bars (which implies that this exercise was quite successful). A final mean percent difference plot is shown between the TROPOZopt and ozonesondes, which indicates that the new operational retrieval is mostly within 10% of the ozonesonde measurement and no systematic biases are present. The authors believe that this analysis has significantly added to the confidence in the TROPOZ instrument and provides a standard for current and future TOLNet algorithms.

Dreaming of Atmospheres

NASA Astrophysics Data System (ADS)

Waldmann, Ingo

2016-10-01

Radiative transfer retrievals have become the standard in modelling of exoplanetary transmission and emission spectra. Analysing currently available observations of exoplanetary atmospheres often invoke large and correlated parameter spaces that can be difficult to map or constrain.To address these issues, we have developed the Tau-REx (tau-retrieval of exoplanets) retrieval and the RobERt spectral recognition algorithms. Tau-REx is a bayesian atmospheric retrieval framework using Nested Sampling and cluster computing to fully map these large correlated parameter spaces. Nonetheless, data volumes can become prohibitively large and we must often select a subset of potential molecular/atomic absorbers in an atmosphere.In the era of open-source, automated and self-sufficient retrieval algorithms, such manual input should be avoided. User dependent input could, in worst case scenarios, lead to incomplete models and biases in the retrieval. The RobERt algorithm is build to address these issues. RobERt is a deep belief neural (DBN) networks trained to accurately recognise molecular signatures for a wide range of planets, atmospheric thermal profiles and compositions. Using these deep neural networks, we work towards retrieval algorithms that themselves understand the nature of the observed spectra, are able to learn from current and past data and make sensible qualitative preselections of atmospheric opacities to be used for the quantitative stage of the retrieval process.In this talk I will discuss how neural networks and Bayesian Nested Sampling can be used to solve highly degenerate spectral retrieval problems and what 'dreaming' neural networks can tell us about atmospheric characteristics.

On the use of harmonized HCHO and NO2 MAXDOAS measurements for the validation of GOME-2 and OMI satellite sensors

NASA Astrophysics Data System (ADS)

Pinardi, Gaia; Hendrick, François; Gielen, Clio; Van Roozendael, Michel; De Smedt, Isabelle; Lambert, Jean-Christopher; Granville, José; Compernolle, Steven; Richter, Andreas; Peters, Enno; Piters, Ankie; Wagner, Thomas; Wang, Yang; Drosoglou, Theano; Bais, Alkis; Wang, Shanshan; Saiz-Lopez, Alfonso

2017-04-01

During the last decade, the MAXDOAS technique has been increasingly recognized as a source of Fiducial Reference Measurements (FRM) suitable for the validation of satellite nadir observations of species relevant for climate and air quality like NO2 and HCHO. As part of the EU FP7 QA4ECV (Quality Assurance for Essential Climate Variables; see http://www.qa4ecv.eu/) project, efforts have been recently made to harmonize a network of a dozen of MAXDOAS spectrometers in view of their use to assess the quality of satellite climate data records generated within the same project. Harmonization tasks have addressed both retrieval steps involved in MAXDOAS retrievals, i.e. the DOAS spectral fit providing the differential slant column densities (DSCDs) and the conversion of the retrieved DSCDs into vertical profiles and/or vertical column densities (VCDs). In this work, we illustrate the successive harmonization steps and present the resulting QA4ECV MAXDOAS database v2. The approach adopted for the conversion of slant to vertical columns is based on a simplified look-up-table approach. The strength and limitation of this approach are discussed using reference data retrieved using an optimal estimation scheme. The QA4ECV MAXDOAS database is then used to validate satellite data sets of NO2 and HCHO columns derived from the Aura/OMI and MetOp/GOME-2 sensors. The methodology of comparison, which is also a subject of the QA4ECV project, is reviewed with respect to co-location criteria, impact of vertical and horizontal smoothing and representativeness of validation sites. We conclude by assessing the current strengths and limitations of the existing MAXDOAS datasets for NO2 and HCHO satellite validation.

Comparison of soil moisture retrieval algorithms based on the synergy between SMAP and SMOS-IC

NASA Astrophysics Data System (ADS)

Ebrahimi-Khusfi, Mohsen; Alavipanah, Seyed Kazem; Hamzeh, Saeid; Amiraslani, Farshad; Neysani Samany, Najmeh; Wigneron, Jean-Pierre

2018-05-01

This study was carried out to evaluate possible improvements of the soil moisture (SM) retrievals from the SMAP observations, based on the synergy between SMAP and SMOS. We assessed the impacts of the vegetation and soil roughness parameters on SM retrievals from SMAP observations. To do so, the effects of three key input parameters including the vegetation optical depth (VOD), effective scattering albedo (ω) and soil roughness (HR) parameters were assessed with the emphasis on the synergy with the VOD product derived from SMOS-IC, a new and simpler version of the SMOS algorithm, over two years of data (April 2015 to April 2017). First, a comprehensive comparison of seven SM retrieval algorithms was made to find the best one for SM retrievals from the SMAP observations. All results were evaluated against in situ measurements over 548 stations from the International Soil Moisture Network (ISMN) in terms of four statistical metrics: correlation coefficient (R), root mean square error (RMSE), bias and unbiased RMSE (UbRMSE). The comparison of seven SM retrieval algorithms showed that the dual channel algorithm based on the additional use of the SMOS-IC VOD product (selected algorithm) led to the best results of SM retrievals over 378, 399, 330 and 271 stations (out of a total of 548 stations) in terms of R, RMSE, UbRMSE and both R & UbRMSE, respectively. Moreover, comparing the measured and retrieved SM values showed that this synergy approach led to an increase in median R value from 0.6 to 0.65 and a decrease in median UbRMSE from 0.09 m3/m3 to 0.06 m3/m3. Second, using the algorithm selected in a first step and defined above, the ω and HR parameters were calibrated over 218 rather homogenous ISMN stations. 72 combinations of various values of ω and HR were used for the calibration over different land cover classes. In this calibration process, the optimal values of ω and HR were found for the different land cover classes. The obtained results indicated that the impact of the VOD parameter on SM retrievals is more considerable than the effects of HR and ω. Overall, the inclusion of the VOD parameter in the SMAP SM retrieval algorithm was found to be a very interesting approach and showed the large potential benefit of the synergy between SMAP and SMOS.

Cloud retrievals from satellite data using optimal estimation: evaluation and application to ATSR

NASA Astrophysics Data System (ADS)

Poulsen, C. A.; Siddans, R.; Thomas, G. E.; Sayer, A. M.; Grainger, R. G.; Campmany, E.; Dean, S. M.; Arnold, C.; Watts, P. D.

2012-08-01

Clouds play an important role in balancing the Earth's radiation budget. Hence, it is vital that cloud climatologies are produced that quantify cloud macro and micro physical parameters and the associated uncertainty. In this paper, we present an algorithm ORAC (Oxford-RAL retrieval of Aerosol and Cloud) which is based on fitting a physically consistent cloud model to satellite observations simultaneously from the visible to the mid-infrared, thereby ensuring that the resulting cloud properties provide both a good representation of the short-wave and long-wave radiative effects of the observed cloud. The advantages of the optimal estimation method are that it enables rigorous error propagation and the inclusion of all measurements and any a priori information and associated errors in a rigorous mathematical framework. The algorithm provides a measure of the consistency between retrieval representation of cloud and satellite radiances. The cloud parameters retrieved are the cloud top pressure, cloud optical depth, cloud effective radius, cloud fraction and cloud phase. The algorithm can be applied to most visible/infrared satellite instruments. In this paper, we demonstrate the applicability to the Along-Track Scanning Radiometers ATSR-2 and AATSR. Examples of applying the algorithm to ATSR-2 flight data are presented and the sensitivity of the retrievals assessed, in particular the algorithm is evaluated for a number of simulated single-layer and multi-layer conditions. The algorithm was found to perform well for single-layer cloud except when the cloud was very thin; i.e., less than 1 optical depths. For the multi-layer cloud, the algorithm was robust except when the upper ice cloud layer is less than five optical depths. In these cases the retrieved cloud top pressure and cloud effective radius become a weighted average of the 2 layers. The sum of optical depth of multi-layer cloud is retrieved well until the cloud becomes thick, greater than 50 optical depths, where the cloud begins to saturate. The cost proved a good indicator of multi-layer scenarios. Both the retrieval cost and the error need to be considered together in order to evaluate the quality of the retrieval. This algorithm in the configuration described here has been applied to both ATSR-2 and AATSR visible and infrared measurements in the context of the GRAPE (Global Retrieval and cloud Product Evaluation) project to produce a 14 yr consistent record for climate research.

Calibration and Image Reconstruction for the Hurricane Imaging Radiometer (HIRAD)

NASA Technical Reports Server (NTRS)

Ruf, Christopher; Roberts, J. Brent; Biswas, Sayak; James, Mark W.; Miller, Timothy

2012-01-01

The Hurricane Imaging Radiometer (HIRAD) is a new airborne passive microwave synthetic aperture radiometer designed to provide wide swath images of ocean surface wind speed under heavy precipitation and, in particular, in tropical cyclones. It operates at 4, 5, 6 and 6.6 GHz and uses interferometric signal processing to synthesize a pushbroom imager in software from a low profile planar antenna with no mechanical scanning. HIRAD participated in NASA s Genesis and Rapid Intensification Processes (GRIP) mission during Fall 2010 as its first science field campaign. HIRAD produced images of upwelling brightness temperature over a aprox 70 km swath width with approx 3 km spatial resolution. From this, ocean surface wind speed and column averaged atmospheric liquid water content can be retrieved across the swath. The calibration and image reconstruction algorithms that were used to verify HIRAD functional performance during and immediately after GRIP were only preliminary and used a number of simplifying assumptions and approximations about the instrument design and performance. The development and performance of a more detailed and complete set of algorithms are reported here.

Phase Retrieval Using a Genetic Algorithm on the Systematic Image-Based Optical Alignment Testbed

NASA Technical Reports Server (NTRS)

Taylor, Jaime R.

2003-01-01

NASA s Marshall Space Flight Center s Systematic Image-Based Optical Alignment (SIBOA) Testbed was developed to test phase retrieval algorithms and hardware techniques. Individuals working with the facility developed the idea of implementing phase retrieval by breaking the determination of the tip/tilt of each mirror apart from the piston motion (or translation) of each mirror. Presented in this report is an algorithm that determines the optimal phase correction associated only with the piston motion of the mirrors. A description of the Phase Retrieval problem is first presented. The Systematic Image-Based Optical Alignment (SIBOA) Testbeb is then described. A Discrete Fourier Transform (DFT) is necessary to transfer the incoming wavefront (or estimate of phase error) into the spatial frequency domain to compare it with the image. A method for reducing the DFT to seven scalar/matrix multiplications is presented. A genetic algorithm is then used to search for the phase error. The results of this new algorithm on a test problem are presented.

Efficient Retrieval of Massive Ocean Remote Sensing Images via a Cloud-Based Mean-Shift Algorithm.

PubMed

Yang, Mengzhao; Song, Wei; Mei, Haibin

2017-07-23

The rapid development of remote sensing (RS) technology has resulted in the proliferation of high-resolution images. There are challenges involved in not only storing large volumes of RS images but also in rapidly retrieving the images for ocean disaster analysis such as for storm surges and typhoon warnings. In this paper, we present an efficient retrieval of massive ocean RS images via a Cloud-based mean-shift algorithm. Distributed construction method via the pyramid model is proposed based on the maximum hierarchical layer algorithm and used to realize efficient storage structure of RS images on the Cloud platform. We achieve high-performance processing of massive RS images in the Hadoop system. Based on the pyramid Hadoop distributed file system (HDFS) storage method, an improved mean-shift algorithm for RS image retrieval is presented by fusion with the canopy algorithm via Hadoop MapReduce programming. The results show that the new method can achieve better performance for data storage than HDFS alone and WebGIS-based HDFS. Speedup and scaleup are very close to linear changes with an increase of RS images, which proves that image retrieval using our method is efficient.

Efficient Retrieval of Massive Ocean Remote Sensing Images via a Cloud-Based Mean-Shift Algorithm

PubMed Central

Song, Wei; Mei, Haibin

2017-01-01

The rapid development of remote sensing (RS) technology has resulted in the proliferation of high-resolution images. There are challenges involved in not only storing large volumes of RS images but also in rapidly retrieving the images for ocean disaster analysis such as for storm surges and typhoon warnings. In this paper, we present an efficient retrieval of massive ocean RS images via a Cloud-based mean-shift algorithm. Distributed construction method via the pyramid model is proposed based on the maximum hierarchical layer algorithm and used to realize efficient storage structure of RS images on the Cloud platform. We achieve high-performance processing of massive RS images in the Hadoop system. Based on the pyramid Hadoop distributed file system (HDFS) storage method, an improved mean-shift algorithm for RS image retrieval is presented by fusion with the canopy algorithm via Hadoop MapReduce programming. The results show that the new method can achieve better performance for data storage than HDFS alone and WebGIS-based HDFS. Speedup and scaleup are very close to linear changes with an increase of RS images, which proves that image retrieval using our method is efficient. PMID:28737699

EPA True NO2 ground site measurements ?? multiple sites, TCEQ ground site measurements of meteorological and air pollution parameters ?? multiple sites ,GeoTASO NO2 Vertical Column

EPA Pesticide Factsheets

EPA True NO2 ground site measurements ?? multiple sites - http://www-air.larc.nasa.gov/cgi-bin/ArcView/discover-aq.tx-2013; TCEQ ground site measurements of meteorological and air pollution parameters ?? multiple sites - http://www-air.larc.nasa.gov/cgi-bin/ArcView/discover-aq.tx-2013; GeoTASO NO2 Vertical Column - http://www-air.larc.nasa.gov/cgi-bin/ArcView/discover-aq.tx-2013?FALCON=1This dataset is associated with the following publication:Nowlan, C., X. Lu, J. Leitch, K. Chance, G. González Abad, C. Lu, P. Zoogman, J. Cole, T. Delker, W. Good, F. Murcray, L. Ruppert, D. Soo, M. Follette-Cook, S. Janz, M. Kowalewski, C. Loughner, K. Pickering, J. Herman, M. Beaver, R. Long, J. Szykman, L. Judd, P. Kelley, W. Luke, X. Ren, and J. Al-Saadi. Nitrogen dioxide observations from the Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) airborne instrument: Retrieval algorithm and measurements during DISCOVER-AQ Texas 2013. Atmospheric Measurement Techniques. Copernicus Publications, Katlenburg-Lindau, GERMANY, 9(6): 2647-2668, (2016).

Transfer and distortion of atmospheric information in the satellite temperature retrieval problem

NASA Technical Reports Server (NTRS)

Thompson, O. E.

1981-01-01

A systematic approach to investigating the transfer of basic ambient temperature information and its distortion by satellite systems and subsequent analysis algorithms is discussed. The retrieval analysis cycle is derived, the variance spectrum of information is examined as it takes different forms in that process, and the quality and quantity of information existing at each stop is compared with the initial ambient temperature information. Temperature retrieval algorithms can smooth, add, or further distort information, depending on how stable the algorithm is, and how heavily influenced by a priori data.

Experiments at SRT Using the NOAA CrIS/ATMS Proxy Data Set

NASA Technical Reports Server (NTRS)

Susskind, Joel; Kouvaris, Louis; Iredell, Lena

2011-01-01

The objectives of the talk are: (1) Assess the performance of NGAS Version-1.5.03.00 CrIS/ATMS retrieval algorithm as delivered by LaRC, modified to include the MW and IR tuning coefficients and new CrIS noise model (a) Percent acceptance (b) RMS and mean differences of T(p) vs. ECMWF truth as a function of % yield (2) Compare performance of NGAS retrieval algorithm with an AIRS Science Team Version-6 like retrieval algorithm modified at Sounder Research Team (SRT) for CrIS/ATMS

The Validation of Cloud Retrieval Algorithms Using Synthetic Datasets

NASA Astrophysics Data System (ADS)

Kokhanovsky, Alexander; Fischer, Jurgen; Linstrot, Rasmus; Meirink, Jan Fokke; Poulsen, Caroline; Preusker, Rene; Siddans, Richard; Thomas, Gareth; Arnold, Chris; Grainger, Roy; Lilli, Luca; Rozanov, Vladimir

2012-11-01

We have performed the inter-comparison study of cloud property retrievals using algorithms initially developed for AATSR (ORAC, RAL-Oxford University), AVHRR and SEVIRI (CPP, KNMI), SCIAMACHY/GOME (SACURA, University of Bremen), and MERIS (ANNA, Free University of Berlin). The accuracy of retrievals of cloud optical thickness (COT), effective radius (ER) of droplets, and cloud top height (CTH) is discussed.

Solar Occultation Retrieval Algorithm Development

NASA Technical Reports Server (NTRS)

Lumpe, Jerry D.

2004-01-01

This effort addresses the comparison and validation of currently operational solar occultation retrieval algorithms, and the development of generalized algorithms for future application to multiple platforms. initial development of generalized forward model algorithms capable of simulating transmission data from of the POAM II/III and SAGE II/III instruments. Work in the 2" quarter will focus on: completion of forward model algorithms, including accurate spectral characteristics for all instruments, and comparison of simulated transmission data with actual level 1 instrument data for specific occultation events.

Derivation of Tropospheric Ozone Climatology and Trends from TOMS Data

NASA Technical Reports Server (NTRS)

Newchurch, Michael J.; McPeters, Rich; Logan, Jennifer; Kim, Jae-Hwan

2002-01-01

This research addresses the following three objectives: (1) Derive tropospheric ozone columns from the TOMS instruments by computing the difference between total-ozone columns over cloudy areas and over clear areas in the tropics; (2) Compute secular trends in Nimbus-7 derived tropospheric Ozone column amounts and associated potential trends in the decadal-scale tropical cloud climatology; (3) Explain the occurrence of anomalously high ozone retrievals over high ice clouds.

Enhanced Deep Blue Aerosol Retrieval Algorithm: The Second Generation

NASA Technical Reports Server (NTRS)

Hsu, N. C.; Jeong, M.-J.; Bettenhausen, C.; Sayer, A. M.; Hansell, R.; Seftor, C. S.; Huang, J.; Tsay, S.-C.

2013-01-01

The aerosol products retrieved using the MODIS collection 5.1 Deep Blue algorithm have provided useful information about aerosol properties over bright-reflecting land surfaces, such as desert, semi-arid, and urban regions. However, many components of the C5.1 retrieval algorithm needed to be improved; for example, the use of a static surface database to estimate surface reflectances. This is particularly important over regions of mixed vegetated and non- vegetated surfaces, which may undergo strong seasonal changes in land cover. In order to address this issue, we develop a hybrid approach, which takes advantage of the combination of pre-calculated surface reflectance database and normalized difference vegetation index in determining the surface reflectance for aerosol retrievals. As a result, the spatial coverage of aerosol data generated by the enhanced Deep Blue algorithm has been extended from the arid and semi-arid regions to the entire land areas.

A circular median filter approach for resolving directional ambiguities in wind fields retrieved from spaceborne scatterometer data

NASA Technical Reports Server (NTRS)

Schultz, Howard

1990-01-01

The retrieval algorithm for spaceborne scatterometry proposed by Schultz (1985) is extended. A circular median filter (CMF) method is presented, which operates on wind directions independently of wind speed, removing any implicit wind speed dependence. A cell weighting scheme is included in the algorithm, permitting greater weights to be assigned to more reliable data. The mathematical properties of the ambiguous solutions to the wind retrieval problem are reviewed. The CMF algorithm is tested on twelve simulated data sets. The effects of spatially correlated likelihood assignment errors on the performance of the CMF algorithm are examined. Also, consideration is given to a wind field smoothing technique that uses a CMF.

Nimbus-7 Total Ozone Mapping Spectrometer (TOMS) Data Products User's Guide

NASA Technical Reports Server (NTRS)

McPeters, Richard D.; Bhartia, P. K.; Krueger, Arlin J.; Herman, Jay R.; Schlesinger, Barry M.; Wellemeyer, Charles G.; Seftor, Colin J.; Jaross, Glen; Taylor, Steven L.; Swissler, Tom;

Nimbus-7 Total Ozone Mapping Spectrometer (TOMS) data products user's guide

NASA Technical Reports Server (NTRS)

Mcpeters, Richard D.; Krueger, Arlin J.; Bhartia, P. K.; Herman, Jay R.; Oaks, Arnold; Ahmad, Ziuddin; Cebula, Richard P.; Schlesinger, Barry M.; Swissler, Tom; Taylor, Steven L.

1993-01-01

Two tape products from the Total Ozone Mapping Spectrometer (TOMS) aboard the Nimbus-7 have been archived at the National Space Science Data Center. The instrument measures backscattered Earth radiance and incoming solar irradiance; their ratio -- the albedo -- is used in ozone retrievals. In-flight measurements are used to monitor changes in the instrument sensitivity. The algorithm to retrieve total column ozone compares the observed ratios of albedos at pairs of wavelengths with pair ratios calculated for different ozone values, solar zenith angles, and optical paths. The initial error in the absolute scale for TOMS total ozone is 3 percent, the one standard-deviation random error is 2 percent, and the drift is +/- 1.5 percent over 14.5 years. The High Density TOMS (HDTOMS) tape contains the measured albedos, the derived total ozone amount, reflectivity, and cloud-height information for each scan position. It also contains an index of SO2 contamination for each position. The Gridded TOMS (GRIDTOMS) tape contains daily total ozone and reflectivity in roughly equal area grids (110 km in latitude by about 100-150 km in longitude). Detailed descriptions of the tape structure and record formats are provided.

Generating Global Leaf Area Index from Landsat: Algorithm Formulation and Demonstration

NASA Technical Reports Server (NTRS)

Ganguly, Sangram; Nemani, Ramakrishna R.; Zhang, Gong; Hashimoto, Hirofumi; Milesi, Cristina; Michaelis, Andrew; Wang, Weile; Votava, Petr; Samanta, Arindam; Melton, Forrest;

Observations of tropospheric trace gases from GOSAT thermal infrared spectra

NASA Astrophysics Data System (ADS)

Ohyama, Hirofumi; Shiomi, Kei; Kawakami, Shuji; Nakajima, Masakatsu; Maki, Takashi; Deushi, Makoto

2013-04-01

Thermal And Near infrared Sensor for carbon Observation-Fourier Transform Spectrometer (TANSO-FTS), which is one of the sensors onboard the Greenhouse gases Observing SATellite (GOSAT), measures the sunlight backscattered by the Earth's surface and atmosphere as well as the thermal radiance emitted from the Earth. Atmospheric trace gases such as ozone (O3), water vapor (H2O and HDO), methanol (CH3OH) and ammonia (NH3) are derived from the thermal infrared spectral radiance recorded with the TANSO-FTS by an optimal estimation retrieval approach. TANSO-FTS total ozone columns are compared with Dobson spectrophotometer and Ozone Monitoring Instrument (OMI) data. The TANSO-FTS total ozone retrievals exhibit a positive bias of 3-4% with a root-mean-square difference of 2-6% compared to the Dobson and OMI measurements. We compare TANSO-FTS tropospheric ozone columns to those from ozonesonde data as well as from a three-dimensional chemical-climate model (MRI-CCM2). The TANSO-FTS data have high correlations with the ozonesonde data. The seasonal trends of the retrieved tropospheric ozone are consistent with those of the ozonesonde data. The spatial distribution of the tropospheric ozone from the TANSO-FTS and MRI-CCM2 shows good agreement, especially in the high-level tropospheric ozone regions. We also retrieve tropospheric H2O and HDO profiles simultaneously, accounting for the cross correlations between the water isotopes. The joint retrieval results in precise estimation of the isotope ratio by partial cancellation of systematic errors common to both H2O and HDO. The retrieved profiles and columns are compared with radiosonde, GPS, and ground-based high-resolution FTS data. The temporal and spatial variations of the precipitable water and the isotope ratio are consistent with those of the validation data. Finally, air pollutants such as CH3OH and NH3 are retrieved using the retrieved ozone and water vapor. We present the latitudinal and seasonal variations of CH3OH related to plant growth and biomass burning, and the high-level NH3 in the hot spot areas.

Biclustering sparse binary genomic data.

PubMed

van Uitert, Miranda; Meuleman, Wouter; Wessels, Lodewyk

2008-12-01

Genomic datasets often consist of large, binary, sparse data matrices. In such a dataset, one is often interested in finding contiguous blocks that (mostly) contain ones. This is a biclustering problem, and while many algorithms have been proposed to deal with gene expression data, only two algorithms have been proposed that specifically deal with binary matrices. None of the gene expression biclustering algorithms can handle the large number of zeros in sparse binary matrices. The two proposed binary algorithms failed to produce meaningful results. In this article, we present a new algorithm that is able to extract biclusters from sparse, binary datasets. A powerful feature is that biclusters with different numbers of rows and columns can be detected, varying from many rows to few columns and few rows to many columns. It allows the user to guide the search towards biclusters of specific dimensions. When applying our algorithm to an input matrix derived from TRANSFAC, we find transcription factors with distinctly dissimilar binding motifs, but a clear set of common targets that are significantly enriched for GO categories.

Estimation of atmospheric columnar organic matter (OM) mass concentration from remote sensing measurements of aerosol spectral refractive indices

NASA Astrophysics Data System (ADS)

Zhang, Ying; Li, Zhengqiang; Sun, Yele; Lv, Yang; Xie, Yisong

2018-04-01

Aerosols have adverse effects on human health and air quality, changing Earth's energy balance and lead to climate change. The components of aerosol are important because of the different spectral characteristics. Based on the low hygroscopic and high scattering properties of organic matter (OM) in fine modal atmospheric aerosols, we develop an inversion algorithm using remote sensing to obtain aerosol components including black carbon (BC), organic matter (OM), ammonium nitrate-like (AN), dust-like (DU) components and aerosol water content (AW). In the algorithm, the microphysical characteristics (i.e. volume distribution and complex refractive index) of particulates are preliminarily separated to fine and coarse modes, and then aerosol components are retrieved using bimodal parameters. We execute the algorithm using remote sensing measurements of sun-sky radiometer at AERONET site (Beijing RADI) in a period from October of 2014 to January of 2015. The results show a reasonable distribution of aerosol components and a good fit for spectral feature calculations. The mean OM mass concentration in atmospheric column is account for 14.93% of the total and 56.34% of dry and fine-mode aerosol, being a fairly good correlation (R = 0.56) with the in situ observations near the surface layer.

Computing row and column counts for sparse QR and LU factorization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gilbert, John R.; Li, Xiaoye S.; Ng, Esmond G.

2001-01-01

We present algorithms to determine the number of nonzeros in each row and column of the factors of a sparse matrix, for both the QR factorization and the LU factorization with partial pivoting. The algorithms use only the nonzero structure of the input matrix, and run in time nearly linear in the number of nonzeros in that matrix. They may be used to set up data structures or schedule parallel operations in advance of the numerical factorization. The row and column counts we compute are upper bounds on the actual counts. If the input matrix is strong Hall and theremore » is no coincidental numerical cancellation, the counts are exact for QR factorization and are the tightest bounds possible for LU factorization. These algorithms are based on our earlier work on computing row and column counts for sparse Cholesky factorization, plus an efficient method to compute the column elimination tree of a sparse matrix without explicitly forming the product of the matrix and its transpose.« less

North Alabama Lightning Mapping Array (LMA): VHF Source Retrieval Algorithm and Error Analyses

NASA Technical Reports Server (NTRS)

Koshak, W. J.; Solakiewicz, R. J.; Blakeslee, R. J.; Goodman, S. J.; Christian, H. J.; Hall, J.; Bailey, J.; Krider, E. P.; Bateman, M. G.; Boccippio, D.

2003-01-01

Two approaches are used to characterize how accurately the North Alabama Lightning Mapping Array (LMA) is able to locate lightning VHF sources in space and in time. The first method uses a Monte Carlo computer simulation to estimate source retrieval errors. The simulation applies a VHF source retrieval algorithm that was recently developed at the NASA Marshall Space Flight Center (MSFC) and that is similar, but not identical to, the standard New Mexico Tech retrieval algorithm. The second method uses a purely theoretical technique (i.e., chi-squared Curvature Matrix Theory) to estimate retrieval errors. Both methods assume that the LMA system has an overall rms timing error of 50 ns, but all other possible errors (e.g., multiple sources per retrieval attempt) are neglected. The detailed spatial distributions of retrieval errors are provided. Given that the two methods are completely independent of one another, it is shown that they provide remarkably similar results. However, for many source locations, the Curvature Matrix Theory produces larger altitude error estimates than the (more realistic) Monte Carlo simulation.

Aerosol Retrievals over the Ocean using Channel 1 and 2 AVHRR Data: A Sensitivity Analysis and Preliminary Results

NASA Technical Reports Server (NTRS)

Mishchenko, Michael I.; Geogdzhayev, Igor V.; Cairns, Brian; Rossow, William B.; Lacis, Andrew A.

1999-01-01

This paper outlines the methodology of interpreting channel 1 and 2 AVHRR radiance data over the oceans and describes a detailed analysis of the sensitivity of monthly averages of retrieved aerosol parameters to the assumptions made in different retrieval algorithms. The analysis is based on using real AVHRR data and exploiting accurate numerical techniques for computing single and multiple scattering and spectral absorption of light in the vertically inhomogeneous atmosphere-ocean system. We show that two-channel algorithms can be expected to provide significantly more accurate and less biased retrievals of the aerosol optical thickness than one-channel algorithms and that imperfect cloud screening and calibration uncertainties are by far the largest sources of errors in the retrieved aerosol parameters. Both underestimating and overestimating aerosol absorption as well as the potentially strong variability of the real part of the aerosol refractive index may lead to regional and/or seasonal biases in optical thickness retrievals. The Angstrom exponent appears to be the most invariant aerosol size characteristic and should be retrieved along with optical thickness as the second aerosol parameter.

Millimeter-wave Imaging Radiometer (MIR) data processing and development of water vapor retrieval algorithms

NASA Technical Reports Server (NTRS)

Chang, L. Aron

1995-01-01

This document describes the progress of the task of the Millimeter-wave Imaging Radiometer (MIR) data processing and the development of water vapor retrieval algorithms, for the second six-month performing period. Aircraft MIR data from two 1995 field experiments were collected and processed with a revised data processing software. Two revised versions of water vapor retrieval algorithm were developed, one for the execution of retrieval on a supercomputer platform, and one for using pressure as the vertical coordinate. Two implementations of incorporating products from other sensors into the water vapor retrieval system, one from the Special Sensor Microwave Imager (SSM/I), the other from the High-resolution Interferometer Sounder (HIS). Water vapor retrievals were performed for both airborne MIR data and spaceborne SSM/T-2 data, during field experiments of TOGA/COARE, CAMEX-1, and CAMEX-2. The climatology of water vapor during TOGA/COARE was examined by SSM/T-2 soundings and conventional rawinsonde.

Ten Years of Cloud Optical and Microphysical Retrievals from MODIS

NASA Technical Reports Server (NTRS)

Platnick, Steven; King, Michael D.; Wind, Galina; Hubanks, Paul; Arnold, G. Thomas; Amarasinghe, Nandana

2010-01-01

The MODIS cloud optical properties algorithm (MOD06/MYD06 for Terra and Aqua MODIS, respectively) has undergone extensive improvements and enhancements since the launch of Terra. These changes have included: improvements in the cloud thermodynamic phase algorithm; substantial changes in the ice cloud light scattering look up tables (LUTs); a clear-sky restoral algorithm for flagging heavy aerosol and sunglint; greatly improved spectral surface albedo maps, including the spectral albedo of snow by ecosystem; inclusion of pixel-level uncertainty estimates for cloud optical thickness, effective radius, and water path derived for three error sources that includes the sensitivity of the retrievals to solar and viewing geometries. To improve overall retrieval quality, we have also implemented cloud edge removal and partly cloudy detection (using MOD35 cloud mask 250m tests), added a supplementary cloud optical thickness and effective radius algorithm over snow and sea ice surfaces and over the ocean, which enables comparison with the "standard" 2.1 11m effective radius retrieval, and added a multi-layer cloud detection algorithm. We will discuss the status of the MOD06 algorithm and show examples of pixellevel (Level-2) cloud retrievals for selected data granules, as well as gridded (Level-3) statistics, notably monthly means and histograms (lD and 2D, with the latter giving correlations between cloud optical thickness and effective radius, and other cloud product pairs).

Modified retrieval algorithm for three types of precipitation distribution using x-band synthetic aperture radar

NASA Astrophysics Data System (ADS)

Xie, Yanan; Zhou, Mingliang; Pan, Dengke

2017-10-01

The forward-scattering model is introduced to describe the response of normalized radar cross section (NRCS) of precipitation with synthetic aperture radar (SAR). Since the distribution of near-surface rainfall is related to the rate of near-surface rainfall and horizontal distribution factor, a retrieval algorithm called modified regression empirical and model-oriented statistical (M-M) based on the volterra integration theory is proposed. Compared with the model-oriented statistical and volterra integration (MOSVI) algorithm, the biggest difference is that the M-M algorithm is based on the modified regression empirical algorithm rather than the linear regression formula to retrieve the value of near-surface rainfall rate. Half of the empirical parameters are reduced in the weighted integral work and a smaller average relative error is received while the rainfall rate is less than 100 mm/h. Therefore, the algorithm proposed in this paper can obtain high-precision rainfall information.

Information retrieval algorithms: A survey

DOE Office of Scientific and Technical Information (OSTI.GOV)

Raghavan, P.

We give an overview of some algorithmic problems arising in the representation of text/image/multimedia objects in a form amenable to automated searching, and in conducting these searches efficiently. These operations are central to information retrieval and digital library systems.

A New, More Physically Based Algorithm, for Retrieving Aerosol Properties over Land from MODIS

NASA Technical Reports Server (NTRS)

Levy, Robert C.; Kaufman, Yoram J.; Remer, Lorraine A.; Mattoo, Shana

2004-01-01

The MOD Imaging Spectrometer (MODIS) has been successfully retrieving aerosol properties, beginning in early 2000 from Terra and from mid 2002 from Aqua. Over land, the retrieval algorithm makes use of three MODIS channels, in the blue, red and infrared wavelengths. As part of the validation exercises, retrieved spectral aerosol optical thickness (AOT) has been compared via scatterplots against spectral AOT measured by the global Aerosol Robotic NETwork (AERONET). On one hand, global and long term validation looks promising, with two-thirds (average plus and minus one standard deviation) of all points falling between published expected error bars. On the other hand, regression of these points shows a positive y-offset and a slope less than 1.0. For individual regions, such as along the U.S. East Coast, the offset and slope are even worse. Here, we introduce an overhaul of the algorithm for retrieving aerosol properties over land. Some well-known weaknesses in the current aerosol retrieval from MODIS include: a) rigid assumptions about the underlying surface reflectance, b) limited aerosol models to choose from, c) simplified (scalar) radiative transfer (RT) calculations used to simulate satellite observations, and d) assumption that aerosol is transparent in the infrared channel. The new algorithm attempts to address all four problems: a) The new algorithm will include surface type information, instead of fixed ratios of the reflectance in the visible channels to the mid-IR reflectance. b) It will include updated aerosol optical properties to reflect the growing aerosol retrieved from eight-plus years of AERONE". operation. c) The effects of polarization will be including using vector RT calculations. d) Most importantly, the new algorithm does not assume that aerosol is transparent in the infrared channel. It will be an inversion of reflectance observed in the three channels (blue, red, and infrared), rather than iterative single channel retrievals. Thus, this new formulation of the MODIS aerosol retrieval over land includes more physically based surface, aerosol and radiative transfer with fewer potentially erroneous assumptions.

Significant Advances in the AIRS Science Team Version-6 Retrieval Algorithm

NASA Technical Reports Server (NTRS)

Susskind, Joel; Blaisdell, John; Iredell, Lena; Molnar, Gyula

2012-01-01

AIRS/AMSU is the state of the art infrared and microwave atmospheric sounding system flying aboard EOS Aqua. The Goddard DISC has analyzed AIRS/AMSU observations, covering the period September 2002 until the present, using the AIRS Science Team Version-S retrieval algorithm. These products have been used by many researchers to make significant advances in both climate and weather applications. The AIRS Science Team Version-6 Retrieval, which will become operation in mid-20l2, contains many significant theoretical and practical improvements compared to Version-5 which should further enhance the utility of AIRS products for both climate and weather applications. In particular, major changes have been made with regard to the algOrithms used to 1) derive surface skin temperature and surface spectral emissivity; 2) generate the initial state used to start the retrieval procedure; 3) compute Outgoing Longwave Radiation; and 4) determine Quality Control. This paper will describe these advances found in the AIRS Version-6 retrieval algorithm and demonstrate the improvement of AIRS Version-6 products compared to those obtained using Version-5,

DREAMING OF ATMOSPHERES

DOE Office of Scientific and Technical Information (OSTI.GOV)

Waldmann, I. P., E-mail: ingo@star.ucl.ac.uk

Here, we introduce the RobERt (Robotic Exoplanet Recognition) algorithm for the classification of exoplanetary emission spectra. Spectral retrieval of exoplanetary atmospheres frequently requires the preselection of molecular/atomic opacities to be defined by the user. In the era of open-source, automated, and self-sufficient retrieval algorithms, manual input should be avoided. User dependent input could, in worst-case scenarios, lead to incomplete models and biases in the retrieval. The RobERt algorithm is based on deep-belief neural (DBN) networks trained to accurately recognize molecular signatures for a wide range of planets, atmospheric thermal profiles, and compositions. Reconstructions of the learned features, also referred to as themore » “dreams” of the network, indicate good convergence and an accurate representation of molecular features in the DBN. Using these deep neural networks, we work toward retrieval algorithms that themselves understand the nature of the observed spectra, are able to learn from current and past data, and make sensible qualitative preselections of atmospheric opacities to be used for the quantitative stage of the retrieval process.« less

Minimizing the semantic gap in biomedical content-based image retrieval

NASA Astrophysics Data System (ADS)

Guan, Haiying; Antani, Sameer; Long, L. Rodney; Thoma, George R.

2010-03-01

A major challenge in biomedical Content-Based Image Retrieval (CBIR) is to achieve meaningful mappings that minimize the semantic gap between the high-level biomedical semantic concepts and the low-level visual features in images. This paper presents a comprehensive learning-based scheme toward meeting this challenge and improving retrieval quality. The article presents two algorithms: a learning-based feature selection and fusion algorithm and the Ranking Support Vector Machine (Ranking SVM) algorithm. The feature selection algorithm aims to select 'good' features and fuse them using different similarity measurements to provide a better representation of the high-level concepts with the low-level image features. Ranking SVM is applied to learn the retrieval rank function and associate the selected low-level features with query concepts, given the ground-truth ranking of the training samples. The proposed scheme addresses four major issues in CBIR to improve the retrieval accuracy: image feature extraction, selection and fusion, similarity measurements, the association of the low-level features with high-level concepts, and the generation of the rank function to support high-level semantic image retrieval. It models the relationship between semantic concepts and image features, and enables retrieval at the semantic level. We apply it to the problem of vertebra shape retrieval from a digitized spine x-ray image set collected by the second National Health and Nutrition Examination Survey (NHANES II). The experimental results show an improvement of up to 41.92% in the mean average precision (MAP) over conventional image similarity computation methods.

Laser pulse bidirectional reflectance from CALIPSO mission

NASA Astrophysics Data System (ADS)

Lu, Xiaomei; Hu, Yongxiang; Yang, Yuekui; Vaughan, Mark; Liu, Zhaoyan; Rodier, Sharon; Hunt, William; Powell, Kathy; Lucker, Patricia; Trepte, Charles

2018-06-01

This paper presents an innovative retrieval method that translates the CALIOP land surface laser pulse returns into the surface bidirectional reflectance. To better analyze the surface returns, the CALIOP receiver impulse response and the downlinked samples' distribution at 30 m vertical resolution are discussed. The saturated laser pulse magnitudes from snow and ice surfaces are recovered based on information extracted from the tail end of the surface signal. The retrieved snow surface bidirectional reflectance is compared with reflectance from both CALIOP cloud-covered regions and MODIS BRDF-albedo model parameters. In addition to the surface bidirectional reflectance, the column top-of-atmosphere bidirectional reflectances are calculated from the CALIOP lidar background data and compared with the bidirectional reflectances derived from WFC radiance measurements. The retrieved CALIOP surface bidirectional reflectance and column top-of-atmosphere bidirectional reflectance results provide unique information to complement existing MODIS standard data products and are expected to have valuable applications for modelers.

Importance of a Priori Vertical Ozone Profiles for TEMPO Air Quality Retrievals

NASA Technical Reports Server (NTRS)

Johnson, Matthew S.; Sullivan, John; Liu, Xiong; Zoogman, Peter; Newchurch, Mike; Kuang, Shi; McGee, Thomas; Leblanc, Thierry

2017-01-01

Ozone (O3) is a toxic pollutant which plays a major role in air quality. Typically, monitoring of surface air quality and O3 mixing ratios is conducted using in situ measurement networks. This is partially due to high-quality information related to air quality being limited from space-borne platforms due to coarse spatial resolution, limited temporal frequency, and minimal sensitivity to lower tropospheric and surface-level O3. The Tropospheric Emissions: Monitoring of Pollution (TEMPO) satellite is designed to address the limitations of current space-based platforms and to improve our ability to monitor North American air quality. TEMPO will provide hourly data of total column and vertical profiles of O3 with high spatial resolution to be used as a near-real-time air quality product. TEMPO O3 retrievals will apply the Smithsonian Astrophysical Observatory profile algorithm developed based on work from GOME (Global Ozone Monitoring Experiment), GOME-2, and OMI (Ozone Monitoring Instrument). This algorithm is suggested to use a priori O3 profile information from a climatological data-base developed from long-term ozone-sonde measurements (tropopause-based (TB-Clim) O3 climatology). This study evaluates the TB-Clim dataset and model simulated O3 profiles, which could potentially serve as a priori O3 profile information in TEMPO retrievals, from near-real-time data assimilation model products (NASA GMAO's (Global Modeling and Assimilation Office) operational GEOS-5 (Goddard Earth Observing System, Version 5) FP (Forecast Products) model and reanalysis data from MERRA2 (Modern-Era Retrospective analysis for Research and Applications, Version 2)) and a full chemical transport model (CTM), GEOS-Chem. In this study, vertical profile products are evaluated with surface (0-2 kilometers) and tropospheric (0-10 kilometers) TOLNet (Tropospheric Ozone Lidar Network) observations and the theoretical impact of individual a priori profile sources on the accuracy of TEMPO O3 retrievals in the troposphere and at the surface are presented. Results indicate that while the TB-Clim climatological dataset can replicate seasonally-averaged tropospheric O3 profiles, model-simulated profiles from a full CTM resulted in more accurate tropospheric and surface-level O3 retrievals from TEMPO when compared to hourly and daily-averaged TOLNet observations. Furthermore, it is shown that when large surface O3 mixing ratios are observed, TEMPO retrieval values at the surface are most accurate when applying CTM a priori profile information compared to all other data products.

An integrated content and metadata based retrieval system for art.

PubMed

Lewis, Paul H; Martinez, Kirk; Abas, Fazly Salleh; Fauzi, Mohammad Faizal Ahmad; Chan, Stephen C Y; Addis, Matthew J; Boniface, Mike J; Grimwood, Paul; Stevenson, Alison; Lahanier, Christian; Stevenson, James

2004-03-01

A new approach to image retrieval is presented in the domain of museum and gallery image collections. Specialist algorithms, developed to address specific retrieval tasks, are combined with more conventional content and metadata retrieval approaches, and implemented within a distributed architecture to provide cross-collection searching and navigation in a seamless way. External systems can access the different collections using interoperability protocols and open standards, which were extended to accommodate content based as well as text based retrieval paradigms. After a brief overview of the complete system, we describe the novel design and evaluation of some of the specialist image analysis algorithms including a method for image retrieval based on sub-image queries, retrievals based on very low quality images and retrieval using canvas crack patterns. We show how effective retrieval results can be achieved by real end-users consisting of major museums and galleries, accessing the distributed but integrated digital collections.

Optically secured information retrieval using two authenticated phase-only masks.

PubMed

Wang, Xiaogang; Chen, Wen; Mei, Shengtao; Chen, Xudong

2015-10-23

We propose an algorithm for jointly designing two phase-only masks (POMs) that allow for the encryption and noise-free retrieval of triple images. The images required for optical retrieval are first stored in quick-response (QR) codes for noise-free retrieval and flexible readout. Two sparse POMs are respectively calculated from two different images used as references for authentication based on modified Gerchberg-Saxton algorithm (GSA) and pixel extraction, and are then used as support constraints in a modified double-phase retrieval algorithm (MPRA), together with the above-mentioned QR codes. No visible information about the target images or the reference images can be obtained from each of these authenticated POMs. This approach allows users to authenticate the two POMs used for image reconstruction without visual observation of the reference images. It also allows user to friendly access and readout with mobile devices.

Optically secured information retrieval using two authenticated phase-only masks

PubMed Central

Wang, Xiaogang; Chen, Wen; Mei, Shengtao; Chen, Xudong

2015-01-01

We propose an algorithm for jointly designing two phase-only masks (POMs) that allow for the encryption and noise-free retrieval of triple images. The images required for optical retrieval are first stored in quick-response (QR) codes for noise-free retrieval and flexible readout. Two sparse POMs are respectively calculated from two different images used as references for authentication based on modified Gerchberg-Saxton algorithm (GSA) and pixel extraction, and are then used as support constraints in a modified double-phase retrieval algorithm (MPRA), together with the above-mentioned QR codes. No visible information about the target images or the reference images can be obtained from each of these authenticated POMs. This approach allows users to authenticate the two POMs used for image reconstruction without visual observation of the reference images. It also allows user to friendly access and readout with mobile devices. PMID:26494213

Optically secured information retrieval using two authenticated phase-only masks

NASA Astrophysics Data System (ADS)

Wang, Xiaogang; Chen, Wen; Mei, Shengtao; Chen, Xudong

2015-10-01

We propose an algorithm for jointly designing two phase-only masks (POMs) that allow for the encryption and noise-free retrieval of triple images. The images required for optical retrieval are first stored in quick-response (QR) codes for noise-free retrieval and flexible readout. Two sparse POMs are respectively calculated from two different images used as references for authentication based on modified Gerchberg-Saxton algorithm (GSA) and pixel extraction, and are then used as support constraints in a modified double-phase retrieval algorithm (MPRA), together with the above-mentioned QR codes. No visible information about the target images or the reference images can be obtained from each of these authenticated POMs. This approach allows users to authenticate the two POMs used for image reconstruction without visual observation of the reference images. It also allows user to friendly access and readout with mobile devices.

Assessment of errors and biases in retrievals of X CO2, X CH4, X CO, and X N2O from a 0.5 cm –1 resolution solar-viewing spectrometer

DOE PAGES

Hedelius, Jacob K.; Viatte, Camille; Wunch, Debra; ...

2016-08-03

Bruker™ EM27/SUN instruments are commercial mobile solar-viewing near-IR spectrometers. They show promise for expanding the global density of atmospheric column measurements of greenhouse gases and are being marketed for such applications. They have been shown to measure the same variations of atmospheric gases within a day as the high-resolution spectrometers of the Total Carbon Column Observing Network (TCCON). However, there is little known about the long-term precision and uncertainty budgets of EM27/SUN measurements. In this study, which includes a comparison of 186 measurement days spanning 11 months, we note that atmospheric variations of X gas within a single day aremore » well captured by these low-resolution instruments, but over several months, the measurements drift noticeably. We present comparisons between EM27/SUN instruments and the TCCON using GGG as the retrieval algorithm. In addition, we perform several tests to evaluate the robustness of the performance and determine the largest sources of errors from these spectrometers. We include comparisons of X CO2, X CH4, X CO, and X N2O. Specifically we note EM27/SUN biases for January 2015 of 0.03, 0.75, –0.12, and 2.43 % for X CO2, X CH4, X CO, and X N2O respectively, with 1 σ running precisions of 0.08 and 0.06 % for X CO2 and X CH4 from measurements in Pasadena. We also identify significant error caused by nonlinear sensitivity when using an extended spectral range detector used to measure CO and N 2O.« less

Multi-year assimilation of IASI and MLS ozone retrievals: variability of tropospheric ozone over the tropics in response to ENSO

NASA Astrophysics Data System (ADS)

Peiro, Hélène; Emili, Emanuele; Cariolle, Daniel; Barret, Brice; Le Flochmoën, Eric

2018-05-01

The Infrared Atmospheric Sounder Instrument (IASI) allows global coverage with very high spatial resolution and its measurements are promising for long-term ozone monitoring. In this study, Microwave Limb Sounder (MLS) O3 profiles and IASI O3 partial columns (1013.25-345 hPa) are assimilated in a chemistry transport model to produce 6-hourly analyses of tropospheric ozone for 6 years (2008-2013). We have compared and evaluated the IASI-MLS analysis and the MLS analysis to assess the added value of IASI measurements. The global chemical transport model MOCAGE (MOdèle de Chimie Atmosphérique à Grande Echelle) has been used with a linear ozone chemistry scheme and meteorological forcing fields from ERA-Interim (ECMWF global reanalysis) with a horizontal resolution of 2° × 2° and 60 vertical levels. The MLS and IASI O3 retrievals have been assimilated with a 4-D variational algorithm to constrain stratospheric and tropospheric ozone respectively. The ozone analyses are validated against ozone soundings and tropospheric column ozone (TCO) from the OMI-MLS residual method. In addition, an Ozone ENSO Index (OEI) is computed from the analysis to validate the TCO variability during the ENSO events. We show that the assimilation of IASI reproduces the variability of tropospheric ozone well during the period under study. The variability deduced from the IASI-MLS analysis and the OMI-MLS measurements are similar for the period of study. The IASI-MLS analysis can reproduce the extreme oscillation of tropospheric ozone caused by ENSO events over the tropical Pacific Ocean, although a correction is required to reduce a constant bias present in the IASI-MLS analysis.

Retrieval of Atmospheric Water Vapor Profiles from the Special Sensor Microwave TEMPERATURE-2

NASA Astrophysics Data System (ADS)

Al-Khalaf, Abdulrahman Khal

1995-01-01

Radiometric measurements from the Special Sensor Microwave/Temperature-2 (SSM/T-2) instrument are used to retrieve atmospheric water vapor profiles over ocean, land, coast, and ice/snow backgrounds. These measurements are used to retrieve vertical distribution of integrated water vapor (IWV) and total integrated water vapor (TIWV) using a physical algorithm. The algorithm infers the presence of cloud at a given height from super-saturation of the retrieved humidity at that height then the algorithm estimate the cloud liquid water content. Retrievals of IWV over five different layers are validated against available ground truth such as global radiosondes and ECMWF analyses. Over ocean, the retrieved total integrated water vapor (TIWV) and IWV close to the surface compare quite well, with those from radiosonde observations and the European Center for Medium Range Weather Forecasts (ECMWF) analyses. However, comparisons to radiosonde results are better than (ECMWF) analyses. TIWV root mean square (RMS) difference was 5.95 mm and TWV RMS difference for the lowest layer (SFC-850 mb) was 2.8 mm for radiosonde comparisons. Water vapor retrieval over land is less accurate than over ocean due to the low contrast between the surface and the atmosphere near the surface; therefore, land retrievals are more reliable at layers above 700 mb. However, TIWV and IWV at all layers compare appropriately with ground truth. Over coastal areas the agreement between retrieved water vapor profiles and ground truth is quite good for both TIWV and IWV for the five layers. The natural variability and large variations in the surface emissivity over ice and snow fields leads toward poor results. Clouds degrade retrievals over land and coast, improve the retrievals a little over ocean, and improve dramatically over snow/ice. Examples of retrieved relative humidity profiles were shown to illustrate the algorithm performance for the actual profile retrieval. The overall features of the retrieved profiles compared well with those from radiosonde data and ECMWF analyses. However, due to the limited number of channels, the retrieved profiles generally do not reproduce the fine details when a rapid change in relative humidity versus height was observed.

A modern robust approach to remotely estimate chlorophyll in coastal and inland zones

NASA Astrophysics Data System (ADS)

Shanmugam, Palanisamy; He, Xianqiang; Singh, Rakesh Kumar; Varunan, Theenathayalan

2018-05-01

The chlorophyll concentration of a water body is an important proxy for representing the phytoplankton biomass. Its estimation from multi or hyper-spectral remote sensing data in natural waters is generally achieved by using (i) the waveband ratioing in two or more bands in the blue-green or (ii) by using a combination of the radiance peak position and magnitude in the red-near-infrared (NIR) spectrum. The blue-green ratio algorithms have been extensively used with satellite ocean color data to investigate chlorophyll distributions in open ocean and clear waters and the application of red-NIR algorithms is often restricted to turbid productive water bodies. These issues present the greatest obstacles to our ability to formulate a modern robust method suitable for quantitative assessments of the chlorophyll concentration in a diverse range of water types. The present study is focused to investigate the normalized water-leaving radiance spectra in the visible and NIR region and propose a robust algorithm (Generalized ABI, GABI algorithm) for chlorophyll concentration retrieval based on Algal Bloom index (ABI) which separates phytoplankton signals from other constituents in the water column. The GABI algorithm is validated using independent in-situ data from various regional to global waters and its performance is further evaluated by comparison with the blue-green waveband ratios and red-NIR algorithms. The results revealed that GABI yields significantly more accurate chlorophyll concentrations (with uncertainties less than 13.5%) and remains more stable in different waters types when compared with the blue-green waveband ratios and red-NIR algorithms. The performance of GABI is further demonstrated using HICO images from nearshore turbid productive waters and MERIS and MODIS-Aqua images from coastal and offshore waters of the Arabian Sea, Bay of Bengal and East China Sea.

Assessment of the Broadleaf Crops Leaf Area Index Product from the Terra MODIS Instrument

NASA Technical Reports Server (NTRS)

Tan, Bin; Hu, Jiannan; Huang, Dong; Yang, Wenze; Zhang, Ping; Shabanov, Nikolay V.; Knyazikhin, Yuri; Nemani, Ramakrishna R.; Myneni, Ranga B.

2005-01-01

The first significant processing of Terra MODIS data, called Collection 3, covered the period from November 2000 to December 2002. The Collection 3 leaf area index (LAI) and fraction vegetation absorbed photosynthetically active radiation (FPAR) products for broadleaf crops exhibited three anomalies (a) high LAI values during the peak growing season, (b) differences in LAI seasonality between the radiative transfer-based main algorithm and the vegetation index based back-up algorithm, and (c) too few retrievals from the main algorithm during the summer period when the crops are at full flush. The cause of these anomalies is a mismatch between reflectances modeled by the algorithm and MODIS measurements. Therefore, the Look-Up-Tables accompanying the algorithm were revised and implemented in Collection 4 processing. The main algorithm with the revised Look-Up-Tables generated retrievals for over 80% of the pixels with valid data. Retrievals from the back-up algorithm, although few, should be used with caution as they are generated from surface reflectances with high uncertainties.

Trends in formaldehyde columns over the Amazon rainforest, as observed from space with SCIAMACHY, OMI and GOME-2 spectrometers.

NASA Astrophysics Data System (ADS)

De Smedt, Isabelle; Stavrakou, Trissevgeni; Lerot, Christophe; Yu, Huan; François, Hendrick; Gielen, Clio; Pinardi, Gaia; Muller, Jean-François; Van Roozendael, Michel

2015-04-01

Atmospheric formaldehyde (H2CO) is a central carbonyl compound of tropospheric chemistry. It is produced by the oxidation of a large variety of volatile organic compounds (VOCs), from biogenic, pyrogenic or anthropogenic emission sources. Tropical vegetation, in particular the Amazon forest that represents over half of the planet's remaining rainforests, emit a wide range of highly reactive biogenic volatile organic compounds (BVOCs). Those play a critical role in atmospheric chemistry and climate, by changing the oxidation capacity of the atmosphere and thus the lifetimes of other key trace gases such as CO and CH4, and by producing organic aerosols. Satellite observations of H2CO, bringing information at the global scale and over decades, are essential to trace and understand the nature and the spatio-temporal evolution of VOC emissions. We have been developing algorithms to retrieve formaldehyde columns from satellite nadir UV spectral measurements, and we have processed the full level-1 datasets of GOME/ERS-2, SCIAMACHY/ENVISAT, GOME-2/METOPA&B and OMI/AURA (De Smedt et al., 2008; 2012; 2015). Resulting H2CO products are openly distributed via the TEMIS website (http://h2co.aeronomie.be). In this work, we use the morning and afternoon H2CO columns between 2004 and 2014, respectively composed by the SCIAMACHY and GOME2 A&B datasets, and from the OMI observations, to study the diurnal, seasonal and long-term variations of H2CO over the Amazon rainforest. The highest H2CO columns worldwide are observed, with morning columns markedly higher than early afternoon. Very large variations between the dry and the wet seasons occur each year. Importantly, in some areas of the forest, mainly in the Rondonia Brazilian State, we observe a net decrease of the H2CO columns. We find very high correlation coefficients between the satellite H2CO columns and the reported deforestation fires that have significantly decreased in Rondonia since 2004 [INPE].

Retrieving handwriting by combining word spotting and manifold ranking

NASA Astrophysics Data System (ADS)

Peña Saldarriaga, Sebastián; Morin, Emmanuel; Viard-Gaudin, Christian

2012-01-01

Online handwritten data, produced with Tablet PCs or digital pens, consists in a sequence of points (x, y). As the amount of data available in this form increases, algorithms for retrieval of online data are needed. Word spotting is a common approach used for the retrieval of handwriting. However, from an information retrieval (IR) perspective, word spotting is a primitive keyword based matching and retrieval strategy. We propose a framework for handwriting retrieval where an arbitrary word spotting method is used, and then a manifold ranking algorithm is applied on the initial retrieval scores. Experimental results on a database of more than 2,000 handwritten newswires show that our method can improve the performances of a state-of-the-art word spotting system by more than 10%.

The Error Structure of the SMAP Single and Dual Channel Soil Moisture Retrievals

NASA Astrophysics Data System (ADS)

Dong, Jianzhi; Crow, Wade T.; Bindlish, Rajat

2018-01-01

Knowledge of the temporal error structure for remotely sensed surface soil moisture retrievals can improve our ability to exploit them for hydrologic and climate studies. This study employs a triple collocation analysis to investigate both the total variance and temporal autocorrelation of errors in Soil Moisture Active and Passive (SMAP) products generated from two separate soil moisture retrieval algorithms, the vertically polarized brightness temperature-based single-channel algorithm (SCA-V, the current baseline SMAP algorithm) and the dual-channel algorithm (DCA). A key assumption made in SCA-V is that real-time vegetation opacity can be accurately captured using only a climatology for vegetation opacity. Results demonstrate that while SCA-V generally outperforms DCA, SCA-V can produce larger total errors when this assumption is significantly violated by interannual variability in vegetation health and biomass. Furthermore, larger autocorrelated errors in SCA-V retrievals are found in areas with relatively large vegetation opacity deviations from climatological expectations. This implies that a significant portion of the autocorrelated error in SCA-V is attributable to the violation of its vegetation opacity climatology assumption and suggests that utilizing a real (as opposed to climatological) vegetation opacity time series in the SCA-V algorithm would reduce the magnitude of autocorrelated soil moisture retrieval errors.

Assessment of the improvements in accuracy of aerosol characterization resulted from additions of polarimetric measurements to intensity-only observations using GRASP algorithm (Invited)

NASA Astrophysics Data System (ADS)

Dubovik, O.; Litvinov, P.; Lapyonok, T.; Herman, M.; Fedorenko, A.; Lopatin, A.; Goloub, P.; Ducos, F.; Aspetsberger, M.; Planer, W.; Federspiel, C.

2013-12-01

During last few years we were developing GRASP (Generalized Retrieval of Aerosol and Surface Properties) algorithm designed for the enhanced characterization of aerosol properties from spectral, multi-angular polarimetric remote sensing observations. The concept of GRASP essentially relies on the accumulated positive research heritage from previous remote sensing aerosol retrieval developments, in particular those from the AERONET and POLDER retrieval activities. The details of the algorithm are described by Dubovik et al. (Atmos. Meas. Tech., 4, 975-1018, 2011). The GRASP retrieves properties of both aerosol and land surface reflectance in cloud-free environments. It is based on highly advanced statistically optimized fitting and deduces nearly 50 unknowns for each observed site. The algorithm derives a similar set of aerosol parameters as AERONET including detailed particle size distribution, the spectrally dependent the complex index of refraction and the fraction of non-spherical particles. The algorithm uses detailed aerosol and surface models and fully accounts for all multiple interactions of scattered solar light with aerosol, gases and the underlying surface. All calculations are done on-line without using traditional look-up tables. In addition, the algorithm uses the new multi-pixel retrieval concept - a simultaneous fitting of a large group of pixels with additional constraints limiting the time variability of surface properties and spatial variability of aerosol properties. This principle is expected to result in higher consistency and accuracy of aerosol products compare to conventional approaches especially over bright surfaces where information content of satellite observations in respect to aerosol properties is limited. The GRASP is a highly versatile algorithm that allows input from both satellite and ground-based measurements. It also has essential flexibility in measurement processing. For example, if observation data set includes spectral measurements of both total intensity and polarization, the algorithm can be easily set to use either total intensity or polarization, as well as both of them in the same retrieval. Using this feature of the algorithm design we have studied the relative importance of total intensity and polarization measurements for retrieving different parameters of aerosol. In this presentation, we present the quantitative assessment of the improvements in aerosol retrievals associated with additions of polarimetric measurements to the intensity-only observations. The study has been performed using satellite measurements by POLDER/PARASOL polarimeter and ground-based measurements by new generation AERONET sun/sky-radiometers implementing measurements of polarization at each spectral channel.

Using Airborne High Spectral Resolution Lidar Data to Evaluate Combined Active Plus Passive Retrievals of Aerosol Extinction Profiles

NASA Technical Reports Server (NTRS)

Burton, S. P.; Ferrare, R. A.; Hostetler, C. A.; Hair, J. W.; Kittaka, C.; Vaughn, M. A.; Remer, L. A.

2010-01-01

We derive aerosol extinction profiles from airborne and space-based lidar backscatter signals by constraining the retrieval with column aerosol optical thickness (AOT), with no need to rely on assumptions about aerosol type or lidar ratio. The backscatter data were acquired by the NASA Langley Research Center airborne High Spectral Resolution Lidar (HSRL) and by the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument on the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite. The HSRL also simultaneously measures aerosol extinction coefficients independently using the high spectral resolution lidar technique, thereby providing an ideal data set for evaluating the retrieval. We retrieve aerosol extinction profiles from both HSRL and CALIOP attenuated backscatter data constrained with HSRL, Moderate-Resolution Imaging Spectroradiometer (MODIS), and Multiangle Imaging Spectroradiometer column AOT. The resulting profiles are compared with the aerosol extinction measured by HSRL. Retrievals are limited to cases where the column aerosol thickness is greater than 0.2 over land and 0.15 over water. In the case of large AOT, the results using the Aqua MODIS constraint over water are poorer than Aqua MODIS over land or Terra MODIS. The poorer results relate to an apparent bias in Aqua MODIS AOT over water observed in August 2007. This apparent bias is still under investigation. Finally, aerosol extinction coefficients are derived from CALIPSO backscatter data using AOT from Aqua MODIS for 28 profiles over land and 9 over water. They agree with coincident measurements by the airborne HSRL to within +/-0.016/km +/- 20% for at least two-thirds of land points and within +/-0.028/km +/- 20% for at least two-thirds of ocean points.

Impact of high-resolution a priori profiles on satellite-based formaldehyde retrievals

NASA Astrophysics Data System (ADS)

Kim, Si-Wan; Natraj, Vijay; Lee, Seoyoung; Kwon, Hyeong-Ahn; Park, Rokjin; de Gouw, Joost; Frost, Gregory; Kim, Jhoon; Stutz, Jochen; Trainer, Michael; Tsai, Catalina; Warneke, Carsten

2018-06-01

Formaldehyde (HCHO) is either directly emitted from sources or produced during the oxidation of volatile organic compounds (VOCs) in the troposphere. It is possible to infer atmospheric HCHO concentrations using space-based observations, which may be useful for studying emissions and tropospheric chemistry at urban to global scales depending on the quality of the retrievals. In the near future, an unprecedented volume of satellite-based HCHO measurement data will be available from both geostationary and polar-orbiting platforms. Therefore, it is essential to develop retrieval methods appropriate for the next-generation satellites that measure at higher spatial and temporal resolution than the current ones. In this study, we examine the importance of fine spatial and temporal resolution a priori profile information on the retrieval by conducting approximately 45 000 radiative transfer (RT) model calculations in the Los Angeles Basin (LA Basin) megacity. Our analyses suggest that an air mass factor (AMF, a factor converting observed slant columns to vertical columns) based on fine spatial and temporal resolution a priori profiles can better capture the spatial distributions of the enhanced HCHO plumes in an urban area than the nearly constant AMFs used for current operational products by increasing the columns by ˜ 50 % in the domain average and up to 100 % at a finer scale. For this urban area, the AMF values are inversely proportional to the magnitude of the HCHO mixing ratios in the boundary layer. Using our optimized model HCHO results in the Los Angeles Basin that mimic the HCHO retrievals from future geostationary satellites, we illustrate the effectiveness of HCHO data from geostationary measurements for understanding and predicting tropospheric ozone and its precursors.

Review of TRMM/GPM Rainfall Algorithm Validation

NASA Technical Reports Server (NTRS)

Smith, Eric A.

2004-01-01

A review is presented concerning current progress on evaluation and validation of standard Tropical Rainfall Measuring Mission (TRMM) precipitation retrieval algorithms and the prospects for implementing an improved validation research program for the next generation Global Precipitation Measurement (GPM) Mission. All standard TRMM algorithms are physical in design, and are thus based on fundamental principles of microwave radiative transfer and its interaction with semi-detailed cloud microphysical constituents. They are evaluated for consistency and degree of equivalence with one another, as well as intercompared to radar-retrieved rainfall at TRMM's four main ground validation sites. Similarities and differences are interpreted in the context of the radiative and microphysical assumptions underpinning the algorithms. Results indicate that the current accuracies of the TRMM Version 6 algorithms are approximately 15% at zonal-averaged / monthly scales with precisions of approximately 25% for full resolution / instantaneous rain rate estimates (i.e., level 2 retrievals). Strengths and weaknesses of the TRMM validation approach are summarized. Because the dew of convergence of level 2 TRMM algorithms is being used as a guide for setting validation requirements for the GPM mission, it is important that the GPM algorithm validation program be improved to ensure concomitant improvement in the standard GPM retrieval algorithms. An overview of the GPM Mission's validation plan is provided including a description of a new type of physical validation model using an analytic 3-dimensional radiative transfer model.

Algorithm For Solution Of Subset-Regression Problems

NASA Technical Reports Server (NTRS)

Verhaegen, Michel

1991-01-01

Reliable and flexible algorithm for solution of subset-regression problem performs QR decomposition with new column-pivoting strategy, enables selection of subset directly from originally defined regression parameters. This feature, in combination with number of extensions, makes algorithm very flexible for use in analysis of subset-regression problems in which parameters have physical meanings. Also extended to enable joint processing of columns contaminated by noise with those free of noise, without using scaling techniques.

Use of Multiangle Satellite Observations to Retrieve Aerosol Properties and Ocean Color

NASA Technical Reports Server (NTRS)

Martonchik, John V.; Diner, David; Khan, Ralph

2005-01-01

A new technique is described for retrieving aerosol over ocean water and the associated ocean color using multiangle satellite observations. Unlike current satellite aerosol retrieval algorithms which only utilize observations at red wavelengths and longer, with the assumption that these wavelengths have a negligible ocean (water-leaving radiance), this new algorithm uses all available spectral bands and simultaneously retrieves both aerosol properties and the spectral ocean color. We show some results of case studies using MISR data, performed over different water conditions (coastal water, blooms, and open water).

Subsurface classification of objects under turbid waters by means of regularization techniques applied to real hyperspectral data

NASA Astrophysics Data System (ADS)

Carpena, Emmanuel; Jiménez, Luis O.; Arzuaga, Emmanuel; Fonseca, Sujeily; Reyes, Ernesto; Figueroa, Juan

2017-05-01

Improved benthic habitat mapping is needed to monitor coral reefs around the world and to assist coastal zones management programs. A fundamental challenge to remotely sensed mapping of coastal shallow waters is due to the significant disparity in the optical properties of the water column caused by the interaction between the coast and the sea. The objects to be classified have weak signals that interact with turbid waters that include sediments. In real scenarios, the absorption and backscattering coefficients are unknown with different sources of variability (river discharges and coastal interactions). Under normal circumstances, another unknown variable is the depth of shallow waters. This paper presents the development of algorithms for retrieving information and its application to the classification and mapping of objects under coastal shallow waters with different unknown concentrations of sediments. A mathematical model that simplifies the radiative transfer equation was used to quantify the interaction between the object of interest, the medium and the sensor. The retrieval of information requires the development of mathematical models and processing tools in the area of inversion, image reconstruction and classification of hyperspectral data. The algorithms developed were applied to one set of real hyperspectral imagery taken in a tank filled with water and TiO2 that emulates turbid coastal shallow waters. Tikhonov method of regularization was used in the inversion process to estimate the bottom albedo of the water tank using a priori information in the form of stored spectral signatures, previously measured, of objects of interest.

DISCOVER-AQ: An Overview and Initial Comparisons of NO2 with OMI Observations

NASA Technical Reports Server (NTRS)

Pickering, Kenneth; Crawford, James; Krotkov, Nickolay; Bucsela, Eric; Lamsal, Lok; Celarier, Edward; Herman, Jay; Janz, Scott; Cohen, Ron; Weinheimer, Andrew

2011-01-01

The first deployment of the Earth Venture -1 DISCOVER-AQ (Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality) project was conducted during July 2011 in the Baltimore-Washington region. Two aircraft (a P-3B for in-situ sampling and a King Air for remote sensing) were used along with an extensive array of surface-based in-situ and remote sensing instrumentation. Fourteen flight days were accomplished by both aircraft and over 250 profiles of trace gases and aerosols were performed by the P-3B over surface air quality monitoring stations, which were specially outfitted with sunphotometers and Pandora UV/Vis spectrometers. The King Air flew with the High Spectral Resolution Lidar for aerosols and the ACAM UV/Vis spectrometer for trace gases. This suite of observations allows linkage of surface air quality with the vertical distributions of gases and aerosols, with remotely-sensed column amounts observed from the surface and from the King Air, and with satellite observations from Aura (OMI and TES), GOME-2, MODIS and GOES. The DISCOVER-AQ data will allow determination of under what conditions satellite retrievals are indicative of surface air quality, and they will be useful in planning new satellites. In addition to an overview of the project, a preliminary comparison of tropospheric column NO2 densities from the integration of in-situ P-3B observations, from the Pandoras and ACAM, and from the new Goddard OMI NO2 algorithm will be presented.

QTLTableMiner++: semantic mining of QTL tables in scientific articles.

PubMed

Singh, Gurnoor; Kuzniar, Arnold; van Mulligen, Erik M; Gavai, Anand; Bachem, Christian W; Visser, Richard G F; Finkers, Richard

2018-05-25

A quantitative trait locus (QTL) is a genomic region that correlates with a phenotype. Most of the experimental information about QTL mapping studies is described in tables of scientific publications. Traditional text mining techniques aim to extract information from unstructured text rather than from tables. We present QTLTableMiner ++ (QTM), a table mining tool that extracts and semantically annotates QTL information buried in (heterogeneous) tables of plant science literature. QTM is a command line tool written in the Java programming language. This tool takes scientific articles from the Europe PMC repository as input, extracts QTL tables using keyword matching and ontology-based concept identification. The tables are further normalized using rules derived from table properties such as captions, column headers and table footers. Furthermore, table columns are classified into three categories namely column descriptors, properties and values based on column headers and data types of cell entries. Abbreviations found in the tables are expanded using the Schwartz and Hearst algorithm. Finally, the content of QTL tables is semantically enriched with domain-specific ontologies (e.g. Crop Ontology, Plant Ontology and Trait Ontology) using the Apache Solr search platform and the results are stored in a relational database and a text file. The performance of the QTM tool was assessed by precision and recall based on the information retrieved from two manually annotated corpora of open access articles, i.e. QTL mapping studies in tomato (Solanum lycopersicum) and in potato (S. tuberosum). In summary, QTM detected QTL statements in tomato with 74.53% precision and 92.56% recall and in potato with 82.82% precision and 98.94% recall. QTM is a unique tool that aids in providing QTL information in machine-readable and semantically interoperable formats.

StatSTEM: An efficient approach for accurate and precise model-based quantification of atomic resolution electron microscopy images.

PubMed

De Backer, A; van den Bos, K H W; Van den Broek, W; Sijbers, J; Van Aert, S

2016-12-01

An efficient model-based estimation algorithm is introduced to quantify the atomic column positions and intensities from atomic resolution (scanning) transmission electron microscopy ((S)TEM) images. This algorithm uses the least squares estimator on image segments containing individual columns fully accounting for overlap between neighbouring columns, enabling the analysis of a large field of view. For this algorithm, the accuracy and precision with which measurements for the atomic column positions and scattering cross-sections from annular dark field (ADF) STEM images can be estimated, has been investigated. The highest attainable precision is reached even for low dose images. Furthermore, the advantages of the model-based approach taking into account overlap between neighbouring columns are highlighted. This is done for the estimation of the distance between two neighbouring columns as a function of their distance and for the estimation of the scattering cross-section which is compared to the integrated intensity from a Voronoi cell. To provide end-users this well-established quantification method, a user friendly program, StatSTEM, is developed which is freely available under a GNU public license. Copyright © 2016 Elsevier B.V. All rights reserved.

Combining approaches to on-line handwriting information retrieval

NASA Astrophysics Data System (ADS)

Peña Saldarriaga, Sebastián; Viard-Gaudin, Christian; Morin, Emmanuel

2010-01-01

In this work, we propose to combine two quite different approaches for retrieving handwritten documents. Our hypothesis is that different retrieval algorithms should retrieve different sets of documents for the same query. Therefore, significant improvements in retrieval performances can be expected. The first approach is based on information retrieval techniques carried out on the noisy texts obtained through handwriting recognition, while the second approach is recognition-free using a word spotting algorithm. Results shows that for texts having a word error rate (WER) lower than 23%, the performances obtained with the combined system are close to the performances obtained on clean digital texts. In addition, for poorly recognized texts (WER > 52%), an improvement of nearly 17% can be observed with respect to the best available baseline method.

Temperature Crosstalk Sensitivity of the Kummerow Rainfall Algorithm

NASA Technical Reports Server (NTRS)

Spencer, Roy W.; Petrenko, Boris

1999-01-01

Even though the signal source for passive microwave retrievals is thermal emission, retrievals of non-temperature geophysical parameters typically do not explicitly take into account the effects of temperature change on the retrievals. For global change research, changes in geophysical parameters (e.g. water vapor, rainfall, etc.) are referenced to the accompanying changes in temperature. If the retrieval of a certain parameter has a cross-talk response from temperature change alone, the retrievals might not be very useful for climate research. We investigated the sensitivity of the Kummerow rainfall retrieval algorithm to changes in air temperature. It was found that there was little net change in total rainfall with air temperature change. However, there were non-negligible changes within individual rain rate categories.

Beam-column joint shear prediction using hybridized deep learning neural network with genetic algorithm

NASA Astrophysics Data System (ADS)

Mundher Yaseen, Zaher; Abdulmohsin Afan, Haitham; Tran, Minh-Tung

2018-04-01

Scientifically evidenced that beam-column joints are a critical point in the reinforced concrete (RC) structure under the fluctuation loads effects. In this novel hybrid data-intelligence model developed to predict the joint shear behavior of exterior beam-column structure frame. The hybrid data-intelligence model is called genetic algorithm integrated with deep learning neural network model (GA-DLNN). The genetic algorithm is used as prior modelling phase for the input approximation whereas the DLNN predictive model is used for the prediction phase. To demonstrate this structural problem, experimental data is collected from the literature that defined the dimensional and specimens’ properties. The attained findings evidenced the efficitveness of the hybrid GA-DLNN in modelling beam-column joint shear problem. In addition, the accurate prediction achived with less input variables owing to the feasibility of the evolutionary phase.

Flash-Type Discrimination

NASA Technical Reports Server (NTRS)

Koshak, William J.

2010-01-01

This viewgraph presentation describes the significant progress made in the flash-type discrimination algorithm development. The contents include: 1) Highlights of Progress for GLM-R3 Flash-Type discrimination Algorithm Development; 2) Maximum Group Area (MGA) Data; 3) Retrieval Errors from Simulations; and 4) Preliminary Global-scale Retrieval.

Observing atmospheric formaldehyde (HCHO) from space: validation and intercomparison of six retrievals from four satellites (OMI, GOME2A, GOME2B, OMPS) with SEAC4RS aircraft observations over the Southeast US

PubMed Central

Zhu, Lei; Jacob, Daniel J.; Kim, Patrick S.; Fisher, Jenny A.; Yu, Karen; Travis, Katherine R.; Mickley, Loretta J.; Yantosca, Robert M.; Sulprizio, Melissa P.; De Smedt, Isabelle; Abad, Gonzalo Gonzalez; Chance, Kelly; Li, Can; Ferrare, Richard; Fried, Alan; Hair, Johnathan W.; Hanisco, Thomas F.; Richter, Dirk; Scarino, Amy Jo; Walega, James; Weibring, Petter; Wolfe, Glenn M.

2018-01-01

Formaldehyde (HCHO) column data from satellites are widely used as a proxy for emissions of volatile organic compounds (VOCs) but validation of the data has been extremely limited. Here we use highly accurate HCHO aircraft observations from the NASA SEAC4RS campaign over the Southeast US in August–September 2013 to validate and intercompare six retrievals of HCHO columns from four different satellite instruments (OMI, GOME2A, GOME2B and OMPS) and three different research groups. The GEOS-Chem chemical transport model is used as a common intercomparison platform. All retrievals feature a HCHO maximum over Arkansas and Louisiana, consistent with the aircraft observations and reflecting high emissions of biogenic isoprene. The retrievals are also interconsistent in their spatial variability over the Southeast US (r=0.4–0.8 on a 0.5°×0.5° grid) and in their day-to-day variability (r=0.5–0.8). However, all retrievals are biased low in the mean by 20–51%, which would lead to corresponding bias in estimates of isoprene emissions from the satellite data. The smallest bias is for OMI-BIRA, which has high corrected slant columns relative to the other retrievals and low scattering weights in its air mass factor (AMF) calculation. OMI-BIRA has systematic error in its assumed vertical HCHO shape profiles for the AMF calculation and correcting this would eliminate its bias relative to the SEAC4RS data. Our results support the use of satellite HCHO data as a quantitative proxy for isoprene emission after correction of the low mean bias. There is no evident pattern in the bias, suggesting that a uniform correction factor may be applied to the data until better understanding is achieved. PMID:29619044

Analyzing the impact of sensor characteristics on retrieval methods of solar-induced fluorescence

NASA Astrophysics Data System (ADS)

Ding, Wenjuan; Zhao, Feng; Yang, Lizi

2017-02-01

In this study, we evaluated the influence of retrieval algorithms and sensor characteristics, such as spectral resolution (SR) and signal to noise ratio (SNR), on the retrieval accuracy of fluorescence signal (Fs). Here Fs was retrieved by four commonly used retrieval methods, namely the original Fraunhofer Line Discriminator method (FLD), the 3 bands FLD (3FLD), the improved FLD (iFLD) and the spectral fitting method (SFM). Fs was retrieved in the oxygen A band centered at around 761nm (O2-A). We analyzed the impact of sensor characteristics on four retrieval methods based on simulated data which were generated by the model SCOPE (Soil Canopy Observation, Photochemistry and Energy fluxes), and obtained consistent conclusions when compared with experimental data. Results presented in this study indicate that both retrieval algorithms and sensor characteristics affect the retrieval accuracy of Fs. When applied to the actual measurement, we should choose the instrument with higher performance and adopt appropriate retrieval method according to measuring instruments and conditions.

Feasibility of retrieving dust properties and total column water vapor from solar spectra measured using a lander camera on Mars

NASA Astrophysics Data System (ADS)

Manago, Naohiro; Noguchi, Katsuyuki; Hashimoto, George L.; Senshu, Hiroki; Otobe, Naohito; Suzuki, Makoto; Kuze, Hiroaki

2017-12-01

Dust and water vapor are important constituents in the Martian atmosphere, exerting significant influence on the heat balance of the atmosphere and surface. We have developed a method to retrieve optical and physical properties of Martian dust from spectral intensities of direct and scattered solar radiation to be measured using a multi-wavelength environmental camera onboard a Mars lander. Martian dust is assumed to be composed of silicate-like substrate and hematite-like inclusion, having spheroidal shape with a monomodal gamma size distribution. Error analysis based on simulated data reveals that appropriate combinations of three bands centered at 450, 550, and 675 nm wavelengths and 4 scattering angles of 3°, 10°, 50°, and 120° lead to good retrieval of four dust parameters, namely, aerosol optical depth, effective radius and variance of size distribution, and volume mixing ratio of hematite. Retrieval error increases when some of the observational parameters such as color ratio or aureole are omitted from the retrieval. Also, the capability of retrieving total column water vapor is examined through observations of direct and scattered solar radiation intensities at 925, 935, and 972 nm. The simulation and error analysis presented here will be useful for designing an environmental camera that can elucidate the dust and water vapor properties in a future Mars lander mission.

The potential of LIRIC to validate the vertical profiles of the aerosol mass concentration estimated by an air quality model

NASA Astrophysics Data System (ADS)

Siomos, Nikolaos; Filoglou, Maria; Poupkou, Anastasia; Liora, Natalia; Dimopoulos, Spyros; Melas, Dimitris; Chaikovsky, Anatoli; Balis, Dimitris

2015-04-01

Vertical profiles of the aerosol mass concentration derived by a retrieval algorithm that uses combined sunphotometer and LIDAR data (LIRIC) were used in order to validate the mass concentration profiles estimated by the air quality model CAMx. LIDAR and CIMEL measurements of the Laboratory of Atmospheric Physics of the Aristotle University of Thessaloniki were used for this validation.The aerosol mass concentration profiles of the fine and coarse mode derived by CAMx were compared with the respective profiles derived by the retrieval algorithm. For the coarse mode particles, forecasts of the Saharan dust transportation model BSC-DREAM8bV2 were also taken into account. Each of the retrieval algorithm's profiles were matched to the models' profile with the best agreement within a time window of four hours before and after the central measurement. OPAC, a software than can provide optical properties of aerosol mixtures, was also employed in order to calculate the angstrom exponent and the lidar ratio values for 355nm and 532nm for each of the model's profiles aiming in a comparison with the angstrom exponent and the lidar ratio values derived by the retrieval algorithm for each measurement. The comparisons between the fine mode aerosol concentration profiles resulted in a good agreement between CAMx and the retrieval algorithm, with the vertical mean bias error never exceeding 7 μgr/m3. Concerning the aerosol coarse mode concentration profiles both CAMx and BSC-DREAM8bV2 values are severely underestimated, although, in cases of Saharan dust transportation events there is an agreement between the profiles of BSC-DREAM8bV2 model and the retrieval algorithm.

NO2 column changes induced by volcanic eruptions

NASA Technical Reports Server (NTRS)

Johnston, Paul V.; Keys, J. Gordon; Mckenzie, Richard L.

1994-01-01

Nitrogen dioxide slant column amounts measured by ground-based remote sensing from Lauder, New Zealand (45 deg S) and Campbell Island (53 deg S) during the second half of 1991 and early 1992 show anomalously low values that are attributed to the effects of volcanic eruptions. It is believed that the eruptions of Mount Pinatubo in the Philippines in June 1991 and possibly Mount Hudson in Chile in August 1991 are responsible for the stratospheric changes, which first became apparent in July 1991. The effects in the spring of 1991 are manifested as a reduction in the retrieved NO2 column amounts from normal levels by 35 to 45 percent, and an accompanying increase in the overnight decay of NO2. The existence of an accurate long-term record of column NO2 from the Lauder site enables us to quantify departures from the normal seasonal behavior with some confidence. Simultaneous retrievals of column ozone agree well with Dobson measurements, confirming that only part of the NO2 changes can be attributed to a modification of the scattering geometry by volcanic aerosols. Other reasons for the observed behavior are explored, including the effects of stratospheric temperature increases resulting from the aerosol loading and the possible involvement of heterogeneous chemical processes.

Marine Boundary Layer Cloud Property Retrievals from High-Resolution ASTER Observations: Case Studies and Comparison with Terra MODIS

NASA Technical Reports Server (NTRS)

Werner, Frank; Wind, Galina; Zhang, Zhibo; Platnick, Steven; Di Girolamo, Larry; Zhao, Guangyu; Amarasinghe, Nandana; Meyer, Kerry

2016-01-01

A research-level retrieval algorithm for cloud optical and microphysical properties is developed for the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) aboard the Terra satellite. It is based on the operational MODIS algorithm. This paper documents the technical details of this algorithm and evaluates the retrievals for selected marine boundary layer cloud scenes through comparisons with the operational MODIS Data Collection 6 (C6) cloud product. The newly developed, ASTERspecific cloud masking algorithm is evaluated through comparison with an independent algorithm reported in Zhao and Di Girolamo (2006). To validate and evaluate the cloud optical thickness (tau) and cloud effective radius (r(sub eff)) from ASTER, the high-spatial-resolution ASTER observations are first aggregated to the same 1000m resolution as MODIS. Subsequently, tau(sub aA) and r(sub eff, aA) retrieved from the aggregated ASTER radiances are compared with the collocated MODIS retrievals. For overcast pixels, the two data sets agree very well with Pearson's product-moment correlation coefficients of R greater than 0.970. However, for partially cloudy pixels there are significant differences between r(sub eff, aA) and the MODIS results which can exceed 10 micrometers. Moreover, it is shown that the numerous delicate cloud structures in the example marine boundary layer scenes, resolved by the high-resolution ASTER retrievals, are smoothed by the MODIS observations. The overall good agreement between the research-level ASTER results and the operational MODIS C6 products proves the feasibility of MODIS-like retrievals from ASTER reflectance measurements and provides the basis for future studies concerning the scale dependency of satellite observations and three-dimensional radiative effects.

Marine boundary layer cloud property retrievals from high-resolution ASTER observations: case studies and comparison with Terra MODIS

NASA Astrophysics Data System (ADS)

Werner, Frank; Wind, Galina; Zhang, Zhibo; Platnick, Steven; Di Girolamo, Larry; Zhao, Guangyu; Amarasinghe, Nandana; Meyer, Kerry

2016-12-01

A research-level retrieval algorithm for cloud optical and microphysical properties is developed for the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) aboard the Terra satellite. It is based on the operational MODIS algorithm. This paper documents the technical details of this algorithm and evaluates the retrievals for selected marine boundary layer cloud scenes through comparisons with the operational MODIS Data Collection 6 (C6) cloud product. The newly developed, ASTER-specific cloud masking algorithm is evaluated through comparison with an independent algorithm reported in [Zhao and Di Girolamo(2006)]. To validate and evaluate the cloud optical thickness (τ) and cloud effective radius (reff) from ASTER, the high-spatial-resolution ASTER observations are first aggregated to the same 1000 m resolution as MODIS. Subsequently, τaA and reff, aA retrieved from the aggregated ASTER radiances are compared with the collocated MODIS retrievals. For overcast pixels, the two data sets agree very well with Pearson's product-moment correlation coefficients of R > 0.970. However, for partially cloudy pixels there are significant differences between reff, aA and the MODIS results which can exceed 10 µm. Moreover, it is shown that the numerous delicate cloud structures in the example marine boundary layer scenes, resolved by the high-resolution ASTER retrievals, are smoothed by the MODIS observations. The overall good agreement between the research-level ASTER results and the operational MODIS C6 products proves the feasibility of MODIS-like retrievals from ASTER reflectance measurements and provides the basis for future studies concerning the scale dependency of satellite observations and three-dimensional radiative effects.

Recent Theoretical Advances in Analysis of AIRS/AMSU Sounding Data

NASA Technical Reports Server (NTRS)

Susskind, Joel

2007-01-01

AIRS was launched on EOS Aqua on May 4,2002, together with AMSU-A and HSB, to form a next generation polar orbiting infrared and microwave atmospheric sounding system. This paper describes the AIRS Science Team Version 5.0 retrieval algorithm. Starting in early 2007, the Goddard DAAC will use this algorithm to analyze near real time AIRS/AMSU observations. These products are then made available to the scientific community for research purposes. The products include twice daily measurements of the Earth's three dimensional global temperature, water vapor, and ozone distribution as well as cloud cover. In addition, accurate twice daily measurements of the earth's land and ocean temperatures are derived and reported. Scientists use this important set of observations for two major applications. They provide important information for climate studies of global and regional variability and trends of different aspects of the earth's atmosphere. They also provide information for researchers to improve the skill of weather forecasting. A very important new product of the AIRS Version 5 algorithm is accurate case-by-case error estimates of the retrieved products. This heightens their utility for use in both weather and climate applications. These error estimates are also used directly for quality control of the retrieved products. Version 5 also allows for accurate quality controlled AIRS only retrievals, called "Version 5 AO retrievals" which can be used as a backup methodology if AMSU fails. Examples of the accuracy of error estimates and quality controlled retrieval products of the AIRS/AMSU Version 5 and Version 5 AO algorithms are given, and shown to be significantly better than the previously used Version 4 algorithm. Assimilation of Version 5 retrievals are also shown to significantly improve forecast skill, especially when the case-by-case error estimates are utilized in the data assimilation process.

Using Induction to Refine Information Retrieval Strategies

NASA Technical Reports Server (NTRS)

Baudin, Catherine; Pell, Barney; Kedar, Smadar

1994-01-01

Conceptual information retrieval systems use structured document indices, domain knowledge and a set of heuristic retrieval strategies to match user queries with a set of indices describing the document's content. Such retrieval strategies increase the set of relevant documents retrieved (increase recall), but at the expense of returning additional irrelevant documents (decrease precision). Usually in conceptual information retrieval systems this tradeoff is managed by hand and with difficulty. This paper discusses ways of managing this tradeoff by the application of standard induction algorithms to refine the retrieval strategies in an engineering design domain. We gathered examples of query/retrieval pairs during the system's operation using feedback from a user on the retrieved information. We then fed these examples to the induction algorithm and generated decision trees that refine the existing set of retrieval strategies. We found that (1) induction improved the precision on a set of queries generated by another user, without a significant loss in recall, and (2) in an interactive mode, the decision trees pointed out flaws in the retrieval and indexing knowledge and suggested ways to refine the retrieval strategies.

A segmentation algorithm based on image projection for complex text layout

NASA Astrophysics Data System (ADS)

Zhu, Wangsheng; Chen, Qin; Wei, Chuanyi; Li, Ziyang

2017-10-01

Segmentation algorithm is an important part of layout analysis, considering the efficiency advantage of the top-down approach and the particularity of the object, a breakdown of projection layout segmentation algorithm. Firstly, the algorithm will algorithm first partitions the text image, and divided into several columns, then for each column scanning projection, the text image is divided into several sub regions through multiple projection. The experimental results show that, this method inherits the projection itself and rapid calculation speed, but also can avoid the effect of arc image information page segmentation, and also can accurate segmentation of the text image layout is complex.

Retrieval of volcanic ash height from satellite-based infrared measurements

NASA Astrophysics Data System (ADS)

Zhu, Lin; Li, Jun; Zhao, Yingying; Gong, He; Li, Wenjie

2017-05-01

A new algorithm for retrieving volcanic ash cloud height from satellite-based measurements is presented. This algorithm, which was developed in preparation for China's next-generation meteorological satellite (FY-4), is based on volcanic ash microphysical property simulation and statistical optimal estimation theory. The MSG satellite's main payload, a 12-channel Spinning Enhanced Visible and Infrared Imager, was used as proxy data to test this new algorithm. A series of eruptions of Iceland's Eyjafjallajökull volcano during April to May 2010 and the Puyehue-Cordón Caulle volcanic complex eruption in the Chilean Andes on 16 June 2011 were selected as two typical cases for evaluating the algorithm under various meteorological backgrounds. Independent volcanic ash simulation training samples and satellite-based Cloud-Aerosol Lidar with Orthogonal Polarization data were used as validation data. It is demonstrated that the statistically based volcanic ash height algorithm is able to rapidly retrieve volcanic ash heights, globally. The retrieved ash heights show comparable accuracy with both independent training data and the lidar measurements, which is consistent with previous studies. However, under complicated background, with multilayers in vertical scale, underlying stratus clouds tend to have detrimental effects on the final retrieval accuracy. This is an unresolved problem, like many other previously published methods using passive satellite sensors. Compared with previous studies, the FY-4 ash height algorithm is independent of simultaneous atmospheric profiles, providing a flexible way to estimate volcanic ash height using passive satellite infrared measurements.

Aquarius Salinity Retrieval Algorithm: Final Pre-Launch Version

NASA Technical Reports Server (NTRS)

Wentz, Frank J.; Le Vine, David M.

2011-01-01

This document provides the theoretical basis for the Aquarius salinity retrieval algorithm. The inputs to the algorithm are the Aquarius antenna temperature (T(sub A)) measurements along with a number of NCEP operational products and pre-computed tables of space radiation coming from the galaxy and sun. The output is sea-surface salinity and many intermediate variables required for the salinity calculation. This revision of the Algorithm Theoretical Basis Document (ATBD) is intended to be the final pre-launch version.

The SAPHIRE server: a new algorithm and implementation.

PubMed Central

Hersh, W.; Leone, T. J.

1995-01-01

SAPHIRE is an experimental information retrieval system implemented to test new approaches to automated indexing and retrieval of medical documents. Due to limitations in its original concept-matching algorithm, a modified algorithm has been implemented which allows greater flexibility in partial matching and different word order within concepts. With the concomitant growth in client-server applications and the Internet in general, the new algorithm has been implemented as a server that can be accessed via other applications on the Internet. PMID:8563413

Tomographic retrievals of ozone with the OMPS Limb Profiler: algorithm description and preliminary results

NASA Astrophysics Data System (ADS)

Zawada, Daniel J.; Rieger, Landon A.; Bourassa, Adam E.; Degenstein, Douglas A.

2018-04-01

Measurements of limb-scattered sunlight from the Ozone Mapping and Profiler Suite Limb Profiler (OMPS-LP) can be used to obtain vertical profiles of ozone in the stratosphere. In this paper we describe a two-dimensional, or tomographic, retrieval algorithm for OMPS-LP where variations are retrieved simultaneously in altitude and the along-orbital-track dimension. The algorithm has been applied to measurements from the center slit for the full OMPS-LP mission to create the publicly available University of Saskatchewan (USask) OMPS-LP 2D v1.0.2 dataset. Tropical ozone anomalies are compared with measurements from the Microwave Limb Sounder (MLS), where differences are less than 5 % of the mean ozone value for the majority of the stratosphere. Examples of near-coincident measurements with MLS are also shown, and agreement at the 5 % level is observed for the majority of the stratosphere. Both simulated retrievals and coincident comparisons with MLS are shown at the edge of the polar vortex, comparing the results to a traditional one-dimensional retrieval. The one-dimensional retrieval is shown to consistently overestimate the amount of ozone in areas of large horizontal gradients relative to both MLS and the two-dimensional retrieval.

Multiple Query Evaluation Based on an Enhanced Genetic Algorithm.

ERIC Educational Resources Information Center

Tamine, Lynda; Chrisment, Claude; Boughanem, Mohand

2003-01-01

Explains the use of genetic algorithms to combine results from multiple query evaluations to improve relevance in information retrieval. Discusses niching techniques, relevance feedback techniques, and evolution heuristics, and compares retrieval results obtained by both genetic multiple query evaluation and classical single query evaluation…

MERIS Retrieval of Water Quality Components in the Turbid Albemarle-Pamlico Sound Estuary, USA

EPA Science Inventory

Two remote-sensing optical algorithms for the retrieval of the water quality components (WQCs) in the Albemarle-Pamlico Estuarine System (APES) have been developed and validated for chlorophyll a (Chl) concentration. Both algorithms are semiempirical because they incorporate some...

Processing and evaluation of riverine waveforms acquired by an experimental bathymetric LiDAR

NASA Astrophysics Data System (ADS)

Kinzel, P. J.; Legleiter, C. J.; Nelson, J. M.

2010-12-01

Accurate mapping of fluvial environments with airborne bathymetric LiDAR is challenged not only by environmental characteristics but also the development and application of software routines to post-process the recorded laser waveforms. During a bathymetric LiDAR survey, the transmission of the green-wavelength laser pulses through the water column is influenced by a number of factors including turbidity, the presence of organic material, and the reflectivity of the streambed. For backscattered laser pulses returned from the river bottom and digitized by the LiDAR detector, post-processing software is needed to interpret and identify distinct inflections in the reflected waveform. Relevant features of this energy signal include the air-water interface, volume reflection from the water column itself, and, ideally, a strong return from the bottom. We discuss our efforts to acquire, analyze, and interpret riverine surveys using the USGS Experimental Advanced Airborne Research LiDAR (EAARL) in a variety of fluvial environments. Initial processing of data collected in the Trinity River, California, using the EAARL Airborne Lidar Processing Software (ALPS) highlighted the difficulty of retrieving a distinct bottom signal in deep pools. Examination of laser waveforms from these pools indicated that weak bottom reflections were often neglected by a trailing edge algorithm used by ALPS to process shallow riverine waveforms. For the Trinity waveforms, this algorithm had a tendency to identify earlier inflections as the bottom, resulting in a shallow bias. Similarly, an EAARL survey along the upper Colorado River, Colorado, also revealed the inadequacy of the trailing edge algorithm for detecting weak bottom reflections. We developed an alternative waveform processing routine by exporting digitized laser waveforms from ALPS, computing the local extrema, and fitting Gaussian curves to the convolved backscatter. Our field data indicate that these techniques improved the definition of pool areas dominated by weak bottom reflections. These processing techniques are also being tested for EAARL surveys collected along the Platte and Klamath Rivers where environmental conditions have resulted in suppressed or convolved bottom reflections.

Image encryption using fingerprint as key based on phase retrieval algorithm and public key cryptography

NASA Astrophysics Data System (ADS)

Zhao, Tieyu; Ran, Qiwen; Yuan, Lin; Chi, Yingying; Ma, Jing

2015-09-01

In this paper, a novel image encryption system with fingerprint used as a secret key is proposed based on the phase retrieval algorithm and RSA public key algorithm. In the system, the encryption keys include the fingerprint and the public key of RSA algorithm, while the decryption keys are the fingerprint and the private key of RSA algorithm. If the users share the fingerprint, then the system will meet the basic agreement of asymmetric cryptography. The system is also applicable for the information authentication. The fingerprint as secret key is used in both the encryption and decryption processes so that the receiver can identify the authenticity of the ciphertext by using the fingerprint in decryption process. Finally, the simulation results show the validity of the encryption scheme and the high robustness against attacks based on the phase retrieval technique.

Description and Sensitivity Analysis of the SOLSE/LORE-2 and SAGE III Limb Scattering Ozone Retrieval Algorithms

NASA Technical Reports Server (NTRS)

Loughman, R.; Flittner, D.; Herman, B.; Bhartia, P.; Hilsenrath, E.; McPeters, R.; Rault, D.

2002-01-01

The SOLSE (Shuttle Ozone Limb Sounding Experiment) and LORE (Limb Ozone Retrieval Experiment) instruments are scheduled for reflight on Space Shuttle flight STS-107 in July 2002. In addition, the SAGE III (Stratospheric Aerosol and Gas Experiment) instrument will begin to make limb scattering measurements during Spring 2002. The optimal estimation technique is used to analyze visible and ultraviolet limb scattered radiances and produce a retrieved ozone profile. The algorithm used to analyze data from the initial flight of the SOLSE/LORE instruments (on Space Shuttle flight STS-87 in November 1997) forms the basis of the current algorithms, with expansion to take advantage of the increased multispectral information provided by SOLSE/LORE-2 and SAGE III. We also present detailed sensitivity analysis for these ozone retrieval algorithms. The primary source of ozone retrieval error is tangent height misregistration (i.e., instrument pointing error), which is relevant throughout the altitude range of interest, and can produce retrieval errors on the order of 10-20 percent due to a tangent height registration error of 0.5 km at the tangent point. Other significant sources of error are sensitivity to stratospheric aerosol and sensitivity to error in the a priori ozone estimate (given assumed instrument signal-to-noise = 200). These can produce errors up to 10 percent for the ozone retrieval at altitudes less than 20 km, but produce little error above that level.

Assessment of Mars Atmospheric Temperature Retrievals from the Thermal Emission Spectrometer Radiances

NASA Technical Reports Server (NTRS)

Hoffman, Matthew J.; Eluszkiewicz, Janusz; Weisenstein, Deborah; Uymin, Gennady; Moncet, Jean-Luc

2012-01-01

Motivated by the needs of Mars data assimilation. particularly quantification of measurement errors and generation of averaging kernels. we have evaluated atmospheric temperature retrievals from Mars Global Surveyor (MGS) Thermal Emission Spectrometer (TES) radiances. Multiple sets of retrievals have been considered in this study; (1) retrievals available from the Planetary Data System (PDS), (2) retrievals based on variants of the retrieval algorithm used to generate the PDS retrievals, and (3) retrievals produced using the Mars 1-Dimensional Retrieval (M1R) algorithm based on the Optimal Spectral Sampling (OSS ) forward model. The retrieved temperature profiles are compared to the MGS Radio Science (RS) temperature profiles. For the samples tested, the M1R temperature profiles can be made to agree within 2 K with the RS temperature profiles, but only after tuning the prior and error statistics. Use of a global prior that does not take into account the seasonal dependence leads errors of up 6 K. In polar samples. errors relative to the RS temperature profiles are even larger. In these samples, the PDS temperature profiles also exhibit a poor fit with RS temperatures. This fit is worse than reported in previous studies, indicating that the lack of fit is due to a bias correction to TES radiances implemented after 2004. To explain the differences between the PDS and Ml R temperatures, the algorithms are compared directly, with the OSS forward model inserted into the PDS algorithm. Factors such as the filtering parameter, the use of linear versus nonlinear constrained inversion, and the choice of the forward model, are found to contribute heavily to the differences in the temperature profiles retrieved in the polar regions, resulting in uncertainties of up to 6 K. Even outside the poles, changes in the a priori statistics result in different profile shapes which all fit the radiances within the specified error. The importance of the a priori statistics prevents reliable global retrievals based a single a priori and strongly implies that a robust science analysis must instead rely on retrievals employing localized a priori information, for example from an ensemble based data assimilation system such as the Local Ensemble Transform Kalman Filter (LETKF).

Development and application of a probability distribution retrieval scheme to the remote sensing of clouds and precipitation

NASA Astrophysics Data System (ADS)

McKague, Darren Shawn

2001-12-01

The statistical properties of clouds and precipitation on a global scale are important to our understanding of climate. Inversion methods exist to retrieve the needed cloud and precipitation properties from satellite data pixel-by-pixel that can then be summarized over large data sets to obtain the desired statistics. These methods can be quite computationally expensive, and typically don't provide errors on the statistics. A new method is developed to directly retrieve probability distributions of parameters from the distribution of measured radiances. The method also provides estimates of the errors on the retrieved distributions. The method can retrieve joint distributions of parameters that allows for the study of the connection between parameters. A forward radiative transfer model creates a mapping from retrieval parameter space to radiance space. A Monte Carlo procedure uses the mapping to transform probability density from the observed radiance histogram to a two- dimensional retrieval property probability distribution function (PDF). An estimate of the uncertainty in the retrieved PDF is calculated from random realizations of the radiance to retrieval parameter PDF transformation given the uncertainty of the observed radiances, the radiance PDF, the forward radiative transfer, the finite number of prior state vectors, and the non-unique mapping to retrieval parameter space. The retrieval method is also applied to the remote sensing of precipitation from SSM/I microwave data. A method of stochastically generating hydrometeor fields based on the fields from a numerical cloud model is used to create the precipitation parameter radiance space transformation. The impact of vertical and horizontal variability within the hydrometeor fields has a significant impact on algorithm performance. Beamfilling factors are computed from the simulated hydrometeor fields. The beamfilling factors vary quite a bit depending upon the horizontal structure of the rain. The algorithm is applied to SSM/I images from the eastern tropical Pacific and is compared to PDFs of rain rate computed using pixel-by-pixel retrievals from Wilheit and from Liu and Curry. Differences exist between the three methods, but good general agreement is seen between the PDF retrieval algorithm and the algorithm of Liu and Curry. (Abstract shortened by UMI.)

Operational use of the AIRS Total Column Ozone Retrievals along with the RGB Airmass Product as Part of the GOES-R Proving Ground

NASA Technical Reports Server (NTRS)

Folmer, M.; Zavodsky, Bradley; Molthan, Andrew

2012-01-01

The Red, Green, Blue (RGB) Air Mass product has been demonstrated in the GOES ]R Proving Ground as a possible decision aid. Forecasters have been trained on the usefulness of identifying stratospheric intrusions and potential vorticity (PV) anomalies that can lead to explosive cyclogenesis, genesis of mesoscale convective systems (MCSs), or the transition of tropical cyclones to extratropical cyclones. It has also been demonstrated to distinguish different air mass types from warm, low ozone air masses to cool, high ozone air masses and the various interactions with the PV anomalies. To assist the forecasters in understanding the stratospheric contribution to high impact weather systems, the Atmospheric Infrared Sounder (AIRS) Total Column Ozone Retrievals have been made available as an operational tool. These AIRS retrievals provide additional information on the amount of ozone that is associated with the red coloring seen in the RGB Air Mass product. This paper discusses how the AIRS retrievals can be used to quantify the red coloring in RGB Air Mass product. These retrievals can be used to diagnose the depth of the stratospheric intrusions associated with different types of weather systems and provide the forecasters decision aid tools that can improve the quality of forecast products.

Ice surface temperature retrieval from AVHRR, ATSR, and passive microwave satellite data: Algorithm development and application

NASA Technical Reports Server (NTRS)

Key, Jeff; Maslanik, James; Steffen, Konrad

1994-01-01

During the first half of our second project year we have accomplished the following: (1) acquired a new AVHRR data set for the Beaufort Sea area spanning an entire year; (2) acquired additional ATSR data for the Arctic and Antarctic now totaling over seven months; (3) refined our AVHRR Arctic and Antarctic ice surface temperature (IST) retrieval algorithm, including work specific to Greenland; (4) developed ATSR retrieval algorithms for the Arctic and Antarctic, including work specific to Greenland; (5) investigated the effects of clouds and the atmosphere on passive microwave 'surface' temperature retrieval algorithms; (6) generated surface temperatures for the Beaufort Sea data set, both from AVHRR and SSM/I; and (7) continued work on compositing GAC data for coverage of the entire Arctic and Antarctic. During the second half of the year we will continue along these same lines, and will undertake a detailed validation study of the AVHRR and ATSR retrievals using LEADEX and the Beaufort Sea year-long data. Cloud masking methods used for the AVHRR will be modified for use with the ATSR. Methods of blending in situ and satellite-derived surface temperature data sets will be investigated.

Retrieve Optically Thick Ice Cloud Microphysical Properties by Using Airborne Dual-Wavelength Radar Measurements

NASA Technical Reports Server (NTRS)

Wang, Zhien; Heymsfield, Gerald M.; Li, Lihua; Heymsfield, Andrew J.

2005-01-01

An algorithm to retrieve optically thick ice cloud microphysical property profiles is developed by using the GSFC 9.6 GHz ER-2 Doppler Radar (EDOP) and the 94 GHz Cloud Radar System (CRS) measurements aboard the high-altitude ER-2 aircraft. In situ size distribution and total water content data from the CRYSTAL-FACE field campaign are used for the algorithm development. To reduce uncertainty in calculated radar reflectivity factors (Ze) at these wavelengths, coincident radar measurements and size distribution data are used to guide the selection of mass-length relationships and to deal with the density and non-spherical effects of ice crystals on the Ze calculations. The algorithm is able to retrieve microphysical property profiles of optically thick ice clouds, such as, deep convective and anvil clouds, which are very challenging for single frequency radar and lidar. Examples of retrieved microphysical properties for a deep convective clouds are presented, which show that EDOP and CRS measurements provide rich information to study cloud structure and evolution. Good agreement between IWPs derived from an independent submillimeter-wave radiometer, CoSSIR, and dual-wavelength radar measurements indicates accuracy of the IWC retrieved from the two-frequency radar algorithm.

Improved Methodology for Surface and Atmospheric Soundings, Error Estimates, and Quality Control Procedures: the AIRS Science Team Version-6 Retrieval Algorithm

NASA Technical Reports Server (NTRS)

Susskind, Joel; Blaisdell, John; Iredell, Lena

2014-01-01

The AIRS Science Team Version-6 AIRS/AMSU retrieval algorithm is now operational at the Goddard DISC. AIRS Version-6 level-2 products are generated near real-time at the Goddard DISC and all level-2 and level-3 products are available starting from September 2002. This paper describes some of the significant improvements in retrieval methodology contained in the Version-6 retrieval algorithm compared to that previously used in Version-5. In particular, the AIRS Science Team made major improvements with regard to the algorithms used to 1) derive surface skin temperature and surface spectral emissivity; 2) generate the initial state used to start the cloud clearing and retrieval procedures; and 3) derive error estimates and use them for Quality Control. Significant improvements have also been made in the generation of cloud parameters. In addition to the basic AIRS/AMSU mode, Version-6 also operates in an AIRS Only (AO) mode which produces results almost as good as those of the full AIRS/AMSU mode. This paper also demonstrates the improvements of some AIRS Version-6 and Version-6 AO products compared to those obtained using Version-5.

Observations of the vertical distributions of summertime atmospheric pollutants and the corresponding ozone production in Shanghai, China

NASA Astrophysics Data System (ADS)

Xing, Chengzhi; Liu, Cheng; Wang, Shanshan; Chan, Ka Lok; Gao, Yang; Huang, Xin; Su, Wenjing; Zhang, Chengxin; Dong, Yunsheng; Fan, Guangqiang; Zhang, Tianshu; Chen, Zhenyi; Hu, Qihou; Su, Hang; Xie, Zhouqing; Liu, Jianguo

2017-12-01

Ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) and lidar measurements were performed in Shanghai, China, during May 2016 to investigate the vertical distribution of summertime atmospheric pollutants. In this study, vertical profiles of aerosol extinction coefficient, nitrogen dioxide (NO2) and formaldehyde (HCHO) concentrations were retrieved from MAX-DOAS measurements using the Heidelberg Profile (HEIPRO) algorithm, while vertical distribution of ozone (O3) was obtained from an ozone lidar. Sensitivity study of the MAX-DOAS aerosol profile retrieval shows that the a priori aerosol profile shape has significant influences on the aerosol profile retrieval. Aerosol profiles retrieved from MAX-DOAS measurements with Gaussian a priori profile demonstrate the best agreements with simultaneous lidar measurements and vehicle-based tethered-balloon observations among all a priori aerosol profiles. Tropospheric NO2 vertical column densities (VCDs) measured with MAX-DOAS show a good agreement with OMI satellite observations with a Pearson correlation coefficient (R) of 0.95. In addition, measurements of the O3 vertical distribution indicate that the ozone productions do not only occur at surface level but also at higher altitudes (about 1.1 km). Planetary boundary layer (PBL) height and horizontal and vertical wind field information were integrated to discuss the ozone formation at upper altitudes. The results reveal that enhanced ozone concentrations at ground level and upper altitudes are not directly related to horizontal and vertical transportation. Similar patterns of O3 and HCHO vertical distributions were observed during this campaign, which implies that the ozone productions near the surface and at higher altitudes are mainly influenced by the abundance of volatile organic compounds (VOCs) in the lower troposphere.

A New Technique for Retrieval of Tropospheric and Stratospheric Ozone Profiles using Sky Radiance Measurements at Multiple View Angles: Application to a Brewer Spectrometer

NASA Technical Reports Server (NTRS)

Tzortziou, Maria; Krotkov, Nickolay A.; Cede, Alexander; Herman, Jay R.; Vasilkov, Alexander

2008-01-01

This paper describes and applies a new technique for retrieving diurnal variability in tropospheric ozone vertical distribution using ground-based measurements of ultraviolet sky radiances. The measured radiances are obtained by a polarization-insensitive modified Brewer double spectrometer located at Goddard Space Flight Center, in Greenbelt, Maryland, USA. Results demonstrate that the Brewer angular (0-72deg viewing zenith angle) and spectral (303-320 nm) measurements of sky radiance in the solar principal plane provide sufficient information to derive tropospheric ozone diurnal variability. In addition, the Brewer measurements provide stratospheric ozone vertical distributions at least twice per day near sunrise and sunset. Frequent measurements of total column ozone amounts from direct-sun observations are used as constraints in the retrieval. The vertical ozone profile resolution is shown in terms of averaging kernels to yield at least four points in the troposphere-low stratosphere, including good information in Umkehr layer 0 (0-5 km). The focus of this paper is on the derivation of stratospheric and tropospheric ozone profiles using both simulated and measured radiances. We briefly discuss the necessary modifications of the Brewer spectrometer that were used to eliminate instrumental polarization sensitivity so that accurate sky radiances can be obtained in the presence of strong Rayleigh scattering and aerosols. The results demonstrate that including a site-specific and time-dependent aerosol correction, based on Brewer direct-sun observations of aerosol optical thickness, is critical to minimize the sky radiance residuals as a function of observing angle in the optimal estimation inversion algorithm and improve the accuracy of the retrieved ozone profile.

Theory of the amplitude-phase retrieval in any linear-transform system and its applications

NASA Astrophysics Data System (ADS)

Yang, Guozhen; Gu, Ben-Yuan; Dong, Bi-Zhen

1992-12-01

This paper is a summary of the theory of the amplitude-phase retrieval problem in any linear transform system and its applications based on our previous works in the past decade. We describe the general statement on the amplitude-phase retrieval problem in an imaging system and derive a set of equations governing the amplitude-phase distribution in terms of the rigorous mathematical derivation. We then show that, by using these equations and an iterative algorithm, a variety of amplitude-phase problems can be successfully handled. We carry out the systematic investigations and comprehensive numerical calculations to demonstrate the utilization of this new algorithm in various transform systems. For instance, we have achieved the phase retrieval from two intensity measurements in an imaging system with diffraction loss (non-unitary transform), both theoretically and experimentally, and the recovery of model real image from its Hartley-transform modulus only in one and two dimensional cases. We discuss the achievement of the phase retrieval problem from a single intensity only based on the sampling theorem and our algorithm. We also apply this algorithm to provide an optimal design of the phase-adjusted plate for a phase-adjustment focusing laser accelerator and a design approach of single phase-only element for implementing optical interconnect. In order to closely simulate the really measured data, we examine the reconstruction of image from its spectral modulus corrupted by a random noise in detail. The results show that the convergent solution can always be obtained and the quality of the recovered image is satisfactory. We also indicated the relationship and distinction between our algorithm and the original Gerchberg- Saxton algorithm. From these studies, we conclude that our algorithm shows great capability to deal with the comprehensive phase-retrieval problems in the imaging system and the inverse problem in solid state physics. It may open a new way to solve important inverse source problems extensively appearing in physics.

Phase-Retrieval Uncertainty Estimation and Algorithm Comparison for the JWST-ISIM Test Campaign

NASA Technical Reports Server (NTRS)

Aronstein, David L.; Smith, J. Scott

2016-01-01

Phase retrieval, the process of determining the exitpupil wavefront of an optical instrument from image-plane intensity measurements, is the baseline methodology for characterizing the wavefront for the suite of science instruments (SIs) in the Integrated Science Instrument Module (ISIM) for the James Webb Space Telescope (JWST). JWST is a large, infrared space telescope with a 6.5-meter diameter primary mirror. JWST is currently NASA's flagship mission and will be the premier space observatory of the next decade. ISIM contains four optical benches with nine unique instruments, including redundancies. ISIM was characterized at the Goddard Space Flight Center (GSFC) in Greenbelt, MD in a series of cryogenic vacuum tests using a telescope simulator. During these tests, phase-retrieval algorithms were used to characterize the instruments. The objective of this paper is to describe the Monte-Carlo simulations that were used to establish uncertainties (i.e., error bars) for the wavefronts of the various instruments in ISIM. Multiple retrieval algorithms were used in the analysis of ISIM phase-retrieval focus-sweep data, including an iterativetransform algorithm and a nonlinear optimization algorithm. These algorithms emphasize the recovery of numerous optical parameters, including low-order wavefront composition described by Zernike polynomial terms and high-order wavefront described by a point-by-point map, location of instrument best focus, focal ratio, exit-pupil amplitude, the morphology of any extended object, and optical jitter. The secondary objective of this paper is to report on the relative accuracies of these algorithms for the ISIM instrument tests, and a comparison of their computational complexity and their performance on central and graphical processing unit clusters. From a phase-retrieval perspective, the ISIM test campaign includes a variety of source illumination bandwidths, various image-plane sampling criteria above and below the Nyquist- Shannon critical sampling value, various extended object sizes, and several other impactful effects.

A cloud and radiation model-based algorithm for rainfall retrieval from SSM/I multispectral microwave measurements

NASA Technical Reports Server (NTRS)

Xiang, Xuwu; Smith, Eric A.; Tripoli, Gregory J.

1992-01-01

A hybrid statistical-physical retrieval scheme is explored which combines a statistical approach with an approach based on the development of cloud-radiation models designed to simulate precipitating atmospheres. The algorithm employs the detailed microphysical information from a cloud model as input to a radiative transfer model which generates a cloud-radiation model database. Statistical procedures are then invoked to objectively generate an initial guess composite profile data set from the database. The retrieval algorithm has been tested for a tropical typhoon case using Special Sensor Microwave/Imager (SSM/I) data and has shown satisfactory results.

Fast Emission Estimates in China Constrained by Satellite Observations (Invited)

NASA Astrophysics Data System (ADS)

Mijling, B.; van der A, R.

2013-12-01

Emission inventories of air pollutants are crucial information for policy makers and form important input data for air quality models. Unfortunately, bottom-up emission inventories, compiled from large quantities of statistical data, are easily outdated for an emerging economy such as China, where rapid economic growth changes emissions accordingly. Alternatively, top-down emission estimates from satellite observations of air constituents have important advantages of being spatial consistent, having high temporal resolution, and enabling emission updates shortly after the satellite data become available. Constraining emissions from concentration measurements is, however, computationally challenging. Within the GlobEmission project of the European Space Agency (ESA) a new algorithm has been developed, specifically designed for fast daily emission estimates of short-lived atmospheric species on a mesoscopic scale (0.25 × 0.25 degree) from satellite observations of column concentrations. The algorithm needs only one forward model run from a chemical transport model to calculate the sensitivity of concentration to emission, using trajectory analysis to account for transport away from the source. By using a Kalman filter in the inverse step, optimal use of the a priori knowledge and the newly observed data is made. We apply the algorithm for NOx emission estimates in East China, using the CHIMERE model together with tropospheric NO2 column retrievals of the OMI and GOME-2 satellite instruments. The observations are used to construct a monthly emission time series, which reveal important emission trends such as the emission reduction measures during the Beijing Olympic Games, and the impact and recovery from the global economic crisis. The algorithm is also able to detect emerging sources (e.g. new power plants) and improve emission information for areas where proxy data are not or badly known (e.g. shipping emissions). The new emission estimates result in a better agreement between observations and simulations of air pollutant concentrations, facilitating improved air quality forecasts. The EU project MarcoPolo will combine these emission estimates from space with statistical information on e.g. land use, population density and traffic to construct a new up-to-date emission inventory for China.

Three-dimensional Distribution of Greenhouse Gas Concentrations over Megacities Observed by GOSAT

NASA Astrophysics Data System (ADS)

Kikuchi, N.; Kuze, A.; Kataoka, F.; Shiomi, K.; Hashimoto, M.; Suto, H.; Knuteson, R. O.; Iraci, L. T.; Yates, E. L.; Gore, W.; Tanaka, T.

2017-12-01

Since the launch in January 2009, TANSO-FTS onboard GOSAT continues to observe the global distribution of carbon dioxide (CO2) and methane (CH4) concentrations. The regular grid observation is the standard observation mode, because a reduction of the uncertainty in the surface fluxes of CO2 and CH4in a subcontinental scale is one of the prime objectives of GOSAT. To meet an increasing demand for monitoring the anthropogenic emission of the greenhouses gases from large cities, GOSAT has carried out extensive target mode observations over several megacities since 2016. Although the footprint of TANSO-FTS is relatively large, the flexible pointing mechanism enables us to cover a city and the surrounding area at the same time. Another advantage of GOSAT TANSO-FTS is that it measures both SWIR and TIR spectra at the same footprint. By adding TIR windows to the existing SWIR retrieval algorithm, we can get the degrees of freedom larger than 2 for CO2 concentrations. This means that we can retrieve not only the column averaged concentration of CO2 (XCO2), but also the two-layer structure of CO2 concentrations, independent of the a priori constraint. In this study, we present three-dimensional distributions of CO2 and CH4 retrieved from GOSAT observations over several megacities including New York City. Fig. 1 shows the seasonal variation of XCO2 over New York City in 2016 covered by 16 footprints of GOSAT observations. A three-dimensional representation of CO2 concentrations is shown in Fig. 2 observed on September 15, 2016. In this example, CO2 concentrations were lower in the lower atmosphere in most of GOSAT footprints, indicating that CO2 was depleted in the lower atmosphere as expected for the summer season. In the winter season, the CO2 concentrations were enhanced in the lower atmosphere as shown in Fig. 3. This example indicates that GOSAT can detect variations in both the column and the vertical structure of CO2 over megacities. Similar analyses are underway for other megacities and will be shown in the presentation.

Validating the accuracy of SO2 gas retrievals in the thermal infrared (8-14 μm)

NASA Astrophysics Data System (ADS)

Gabrieli, Andrea; Porter, John N.; Wright, Robert; Lucey, Paul G.

2017-11-01

Quantifying sulfur dioxide (SO2) in volcanic plumes is important for eruption predictions and public health. Ground-based remote sensing of spectral radiance of plumes contains information on the path-concentration of SO2. However, reliable inversion algorithms are needed to convert plume spectral radiance measurements into SO2 path-concentrations. Various techniques have been used for this purpose. Recent approaches have employed thermal infrared (TIR) imaging between 8 μm and 14 μm to provide two-dimensional mapping of plume SO2 path-concentration, using what might be described as "dual-view" techniques. In this case, the radiance (or its surrogate brightness temperature) is computed for portions of the image that correspond to the plume and compared with spectral radiance obtained for adjacent regions of the image that do not (i.e., "clear sky"). In this way, the contribution that the plume makes to the measured radiance can be isolated from the background atmospheric contribution, this residual signal being converted to an estimate of gas path-concentration via radiative transfer modeling. These dual-view approaches suffer from several issues, mainly the assumption of clear sky background conditions. At this time, the various inversion algorithms remain poorly validated. This paper makes two contributions. Firstly, it validates the aforementioned dual-view approaches, using hyperspectral TIR imaging data. Secondly, it introduces a new method to derive SO2 path-concentrations, which allows for single point SO2 path-concentration retrievals, suitable for hyperspectral imaging with clear or cloudy background conditions. The SO2 amenable lookup table algorithm (SO2-ALTA) uses the MODTRAN5 radiative transfer model to compute radiance for a variety (millions) of plume and atmospheric conditions. Rather than searching this lookup table to find the best fit for each measured spectrum, the lookup table was used to train a partial least square regression (PLSR) model. The coefficients of this model are used to invert measured radiance spectra to path-concentration on a pixel-by-pixel basis. In order to validate the algorithms, TIR hyperspectral measurements were carried out by measuring sky radiance when looking through gas cells filled with known amounts of SO2. SO2-ALTA was also tested on retrieving SO2 path-concentrations from the Kīlauea volcano, Hawai'i. For cloud-free conditions, all three techniques worked well. In cases where background clouds were present, then only SO2-ALTA was found to provide good results, but only under low atmospheric water vapor column amounts.

Retrieval of Dry Snow Parameters from Radiometric Data Using a Dense Medium Model and Genetic Algorithms

NASA Technical Reports Server (NTRS)

Tedesco, Marco; Kim, Edward J.

2005-01-01

In this paper, GA-based techniques are used to invert the equations of an electromagnetic model based on Dense Medium Radiative Transfer Theory (DMRT) under the Quasi Crystalline Approximation with Coherent Potential to retrieve snow depth, mean grain size and fractional volume from microwave brightness temperatures. The technique is initially tested on both noisy and not-noisy simulated data. During this phase, different configurations of genetic algorithm parameters are considered to quantify how their change can affect the algorithm performance. A configuration of GA parameters is then selected and the algorithm is applied to experimental data acquired during the NASA Cold Land Process Experiment. Snow parameters retrieved with the GA-DMRT technique are then compared with snow parameters measured on field.

Kalman filters for assimilating near-surface observations into the Richards equation - Part 2: A dual filter approach for simultaneous retrieval of states and parameters

NASA Astrophysics Data System (ADS)

Medina, H.; Romano, N.; Chirico, G. B.

2014-07-01

This study presents a dual Kalman filter (DSUKF - dual standard-unscented Kalman filter) for retrieving states and parameters controlling the soil water dynamics in a homogeneous soil column, by assimilating near-surface state observations. The DSUKF couples a standard Kalman filter for retrieving the states of a linear solver of the Richards equation, and an unscented Kalman filter for retrieving the parameters of the soil hydraulic functions, which are defined according to the van Genuchten-Mualem closed-form model. The accuracy and the computational expense of the DSUKF are compared with those of the dual ensemble Kalman filter (DEnKF) implemented with a nonlinear solver of the Richards equation. Both the DSUKF and the DEnKF are applied with two alternative state-space formulations of the Richards equation, respectively differentiated by the type of variable employed for representing the states: either the soil water content (θ) or the soil water matric pressure head (h). The comparison analyses are conducted with reference to synthetic time series of the true states, noise corrupted observations, and synthetic time series of the meteorological forcing. The performance of the retrieval algorithms are examined accounting for the effects exerted on the output by the input parameters, the observation depth and assimilation frequency, as well as by the relationship between retrieved states and assimilated variables. The uncertainty of the states retrieved with DSUKF is considerably reduced, for any initial wrong parameterization, with similar accuracy but less computational effort than the DEnKF, when this is implemented with ensembles of 25 members. For ensemble sizes of the same order of those involved in the DSUKF, the DEnKF fails to provide reliable posterior estimates of states and parameters. The retrieval performance of the soil hydraulic parameters is strongly affected by several factors, such as the initial guess of the unknown parameters, the wet or dry range of the retrieved states, the boundary conditions, as well as the form (h-based or θ-based) of the state-space formulation. Several analyses are reported to show that the identifiability of the saturated hydraulic conductivity is hindered by the strong correlation with other parameters of the soil hydraulic functions defined according to the van Genuchten-Mualem closed-form model.

Analysis of Leaf Area Index and Fraction of PAR Absorbed by Vegetation Products from the Terra MODIS Sensor: 2000-2005

NASA Technical Reports Server (NTRS)

Yang, Wenze; Huang, Dong; Tan, Bin; Stroeve, Julienne C.; Shabanov, Nikolay V.; Knyazikhin, Yuri; Nemani, Ramakrishna R.; Myneni, Ranga B.

2006-01-01

The analysis of two years of Collection 3 and five years of Collection 4 Terra Moderate Resolution Imaging Spectroradiometer (MODIS) Leaf Area Index (LAI) and Fraction of Photosynthetically Active Radiation (FPAR) data sets is presented in this article with the goal of understanding product quality with respect to version (Collection 3 versus 4), algorithm (main versus backup), snow (snow-free versus snow on the ground), and cloud (cloud-free versus cloudy) conditions. Retrievals from the main radiative transfer algorithm increased from 55% in Collection 3 to 67% in Collection 4 due to algorithm refinements and improved inputs. Anomalously high LAI/FPAR values observed in Collection 3 product in some vegetation types were corrected in Collection 4. The problem of reflectance saturation and too few main algorithm retrievals in broadleaf forests persisted in Collection 4. The spurious seasonality in needleleaf LAI/FPAR fields was traced to fewer reliable input data and retrievals during the boreal winter period. About 97% of the snow covered pixels were processed by the backup Normalized Difference Vegetation Index-based algorithm. Similarly, a majority of retrievals under cloudy conditions were obtained from the backup algorithm. For these reasons, the users are advised to consult the quality flags accompanying the LAI and FPAR product.

The Order-Restricted Association Model: Two Estimation Algorithms and Issues in Testing

ERIC Educational Resources Information Center

Galindo-Garre, Francisca; Vermunt, Jeroen K.

2004-01-01

This paper presents a row-column (RC) association model in which the estimated row and column scores are forced to be in agreement with a priori specified ordering. Two efficient algorithms for finding the order-restricted maximum likelihood (ML) estimates are proposed and their reliability under different degrees of association is investigated by…

Advances in Pulsed Lidar Measurements of CO2 Column Concentrations from Aircraft and for Space

NASA Astrophysics Data System (ADS)

Abshire, J. B.; Ramanathan, A. K.; Allan, G. R.; Hasselbrack, W. E.; Riris, H.; Numata, K.; Mao, J.; Sun, X.

2016-12-01

We have demonstrated an improved pulsed, multiple-wavelength integrated path differential absorption lidar for measuring the tropospheric CO2 concentrations. The lidar measures the range resolved shape of the 1572.33 nm CO2 absorption line to scattering surfaces, including the ground and the tops of clouds. Airborne measurements have used both 30 and 15 fixed wavelength samples distributed across the line. Analysis estimates the lidar range and pulse energies at each wavelength 10 times per second. The retrievals solve for the CO2 absorption line shape and the column average CO2 concentrations by using radiative transfer calculations, the aircraft altitude and range to the scattering surface, and the atmospheric conditions. We compare these to CO2 concentrations from in-situ sensors. In recent campaigns the lidar used a step-locked laser diode source, and a new HgCdTe APD detector in the receiver. During August and September 2014 the ASCENDS campaign flew over the California Central Valley, a coastal redwood forest, desert areas, and above growing crops in Iowa. Analyses show the retrievals of lidar range and CO2 column absorption, and mixing ratio worked well when measuring over variable topography and through thin clouds and aerosols. The retrievals clearly show the decrease in CO2 concentration over growing cropland. Airborne lidar measurements of horizontal gradients of CO2 concentrations across Nevada, Colorado and Nebraska showed good agreement with those from a model of CO2 flux and transport (PCTM). In several flights the agreement of the lidar with the column average concentration was < 1ppm, with standard deviation of 0.9 ppm. Two additional flights were made in February 2016 using a larger laser spot size and an optimized receiver. These improved the sensitivity x3, and the retrievals show 0.7 ppm precision over the desert in 1 second averaging time. A summary of these results will be presented, along with on-going developments for a space version.

Assessment of the Quality of the Version 1.07 Temperature-Versus-Pressure Profiles of the Middle Atmosphere from TIMED/SABER

NASA Technical Reports Server (NTRS)

Remsberg, E. E.; Marshall, B. T.; Garcia-Comas, M.; Krueger, D.; Lingenfelser, G. S.; Martin-Torres, J.; Mlynczak, M. G.; Russell, J. M., III; Smith, A. K.; Zhao, Y.;

Remote Sensing of Cloud, Aerosol, and Water Vapor Properties from MODIS

NASA Technical Reports Server (NTRS)

King, Michael D.

2001-01-01

MODIS is an earth-viewing cross-track scanning spectroradiometer launched on the Terra satellite in December 1999. MODIS scans a swath width sufficient to provide nearly complete global coverage every two days from a polar-orbiting, sun-synchronous, platform at an altitude of 705 km, and provides images in 36 spectral bands from 0.415 to 14.235 microns with spatial resolutions of 250 m (2 bands), 500 m (5 bands) and 1000 m (29 bands). These bands have been carefully selected to enable advanced studies of land, ocean, and atmospheric processes. In this presentation I will review the comprehensive set of remote sensing algorithms that have been developed for the remote sensing of atmospheric properties using MODIS data, placing primary emphasis on the principal atmospheric applications of: (1) developing a cloud mask for distinguishing clear sky from clouds, (2) retrieving global cloud radiative and microphysical properties, including cloud top pressure and temperature, effective emissivity, cloud optical thickness, thermodynamic phase, and effective radius, (3) monitoring tropospheric aerosol optical thickness over the land and ocean and aerosol size distribution over the ocean, (4) determining atmospheric profiles of moisture and temperature, and (5) estimating column water amount. The physical principles behind the determination of each of these atmospheric products will be described, together with an example of their application using MODIS observations. All products are archived into two categories: pixel-level retrievals (referred to as Level-2 products) and global gridded products at a latitude and longitude resolution of 1 deg (Level-3 products). An overview of the MODIS atmosphere algorithms and products, status, validation activities, and early level-2 and -3 results will be presented. Finally, I will present some highlights from the land and ocean algorithms developed for processing global MODIS observations, including: (1) surface reflectance, (2) vegetation indices, leaf area index, and FPAR, (3) albedo and nadir BRDF-adjusted reflectance, (4) normalized water-leaving radiance, (5) chlorophyll-a concentration, and (6) sea surface temperature.

A radiative transfer model for sea surface temperature retrieval for the along-track scanning radiometer

NASA Astrophysics Data System (ADS)

ZáVody, A. M.; Mutlow, C. T.; Llewellyn-Jones, D. T.

1995-01-01

The measurements made by the along-track scanning radiometer are now converted routinely into sea surface temperature (SST). The details of the atmospheric model which had been used for deriving the SST algorithms are given, together with tables of the coefficients in the algorithms for the different SST products. The accuracy of the retrieval under normal conditions and the effect of errors in the model on the retrieved SST are briefly discussed.

Remote Sensing of Cloud Top Height from SEVIRI: Analysis of Eleven Current Retrieval Algorithms

NASA Technical Reports Server (NTRS)

Hamann, U.; Walther, A.; Baum, B.; Bennartz, R.; Bugliaro, L.; Derrien, M.; Francis, P. N.; Heidinger, A.; Joro, S.; Kniffka, A.;

Collaborative Study for Analysis of High Resolution Infrared Atmospheric Spectra Between NASA Langley Research Center and the University of Denver

NASA Technical Reports Server (NTRS)

Goldman, A.

2002-01-01

The Langley-D.U. collaboration on the analysis of high resolultion infrared atmospheric spectra covered a number of important studies of trace gases identification and quantification from field spectra, and spectral line parameters analysis. The collaborative work included: 1) Quantification and monitoring of trace gases from ground-based spectra available from various locations and seasons and from balloon flights; 2) Identification and preliminary quantification of several isotopic species, including oxygen and Sulfur isotopes; 3) Search for new species on the available spectra, including the use of selective coadding of ground-based spectra for high signal to noise; 4) Update of spectroscopic line parameters, by combining laboratory and atmospheric spectra with theoretical spectroscopy methods; 5) Study of trends and correlations of atmosphere trace constituents; and 6) Algorithms developments, retrievals intercomparisons and automatization of the analysis of NDSC spectra, for both column amounts and vertical profiles.

The Time Series Technique for Aerosol Retrievals over Land from MODIS: Algorithm MAIAC

NASA Technical Reports Server (NTRS)

Lyapustin, Alexei; Wang, Yujie

2008-01-01

Atmospheric aerosols interact with sun light by scattering and absorbing radiation. By changing irradiance of the Earth surface, modifying cloud fractional cover and microphysical properties and a number of other mechanisms, they affect the energy balance, hydrological cycle, and planetary climate [IPCC, 2007]. In many world regions there is a growing impact of aerosols on air quality and human health. The Earth Observing System [NASA, 1999] initiated high quality global Earth observations and operational aerosol retrievals over land. With the wide swath (2300 km) of MODIS instrument, the MODIS Dark Target algorithm [Kaufman et al., 1997; Remer et al., 2005; Levy et al., 2007] currently complemented with the Deep Blue method [Hsu et al., 2004] provides daily global view of planetary atmospheric aerosol. The MISR algorithm [Martonchik et al., 1998; Diner et al., 2005] makes high quality aerosol retrievals in 300 km swaths covering the globe in 8 days. With MODIS aerosol program being very successful, there are still several unresolved issues in the retrieval algorithms. The current processing is pixel-based and relies on a single-orbit data. Such an approach produces a single measurement for every pixel characterized by two main unknowns, aerosol optical thickness (AOT) and surface reflectance (SR). This lack of information constitutes a fundamental problem of the remote sensing which cannot be resolved without a priori information. For example, MODIS Dark Target algorithm makes spectral assumptions about surface reflectance, whereas the Deep Blue method uses ancillary global database of surface reflectance composed from minimal monthly measurements with Rayleigh correction. Both algorithms use Lambertian surface model. The surface-related assumptions in the aerosol retrievals may affect subsequent atmospheric correction in unintended way. For example, the Dark Target algorithm uses an empirical relationship to predict SR in the Blue (B3) and Red (B1) bands from the 2.1 m channel (B7) for the purpose of aerosol retrieval. Obviously, the subsequent atmospheric correction will produce the same SR in the red and blue bands as predicted, i.e. an empirical function of 2.1. In other words, the spectral, spatial and temporal variability of surface reflectance in the Blue and Red bands appears borrowed from band B7. This may have certain implications for the vegetation and global carbon analysis because the chlorophyll-sensing bands B1, B3 are effectively substituted in terms of variability by band B7, which is sensitive to the plant liquid water. This chapter describes a new recently developed generic aerosol-surface retrieval algorithm for MODIS. The Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm simultaneously retrieves AOT and surface bi-directional reflection factor (BRF) using the time series of MODIS measurements.

Seasonal in situ observations of glyoxal and methylglyoxal over the temperate oceans of the Southern Hemisphere

NASA Astrophysics Data System (ADS)

Lawson, S. J.; Selleck, P. W.; Galbally, I. E.; Keywood, M. D.; Harvey, M. J.; Lerot, C.; Helmig, D.; Ristovski, Z.

2014-08-01

Dicarbonyls glyoxal and methylglyoxal have been measured with 2,4-dinitrophenylhydrazine (2,4-DNPH) cartridges and high performance liquid chromatography (HPLC), optimised for dicarbonyl detection, in clean marine air over the temperate Southern Hemisphere (SH) oceans. Measurements of a range of dicarbonyl precursors (volatile organic compounds, VOCs) were made in parallel. These are the first in situ measurements of glyoxal and methylglyoxal over the remote temperate oceans. Six 24 h samples were collected in late summer (February-March) over the Chatham Rise in the South West Pacific Ocean during the Surface Ocean Aerosol Production (SOAP) voyage in 2012, while 34 24 h samples were collected at Cape Grim Baseline Air Pollution Station in late winter (August-September) 2011. Average glyoxal mixing ratios in clean marine air were 7 ppt at Cape Grim, and 24 ppt over Chatham Rise. Average methylglyoxal mixing ratios in clean marine air were 28 ppt at Cape Grim and 12 ppt over Chatham Rise. The mixing ratios of glyoxal at Cape Grim are the lowest observed over the remote oceans, while mixing ratios over Chatham Rise are in good agreement with other temperate and tropical observations, including concurrent MAX-DOAS observations. Methylglyoxal mixing ratios at both sites are comparable to the only other marine methylglyoxal observations available over the tropical Northern Hemisphere (NH) ocean. Ratios of glyoxal : methylglyoxal > 1 over Chatham Rise but < 1 at Cape Grim, suggesting different formation and/or loss processes or rates dominate at each site. Dicarbonyl precursor VOCs, including isoprene and monoterpenes, are used to calculate an upper estimate yield of glyoxal and methylglyoxal in the remote marine boundary layer and explain at most 1-3 ppt of dicarbonyls observed, corresponding to 11 and 17% of the observed glyoxal and 28 and 10% of the methylglyoxal at Chatham Rise and Cape Grim, respectively, highlighting a significant but as yet unknown production mechanism. Glyoxal surface observations from both sites were converted to vertical columns and compared to average vertical column densities (VCDs) from GOME-2 satellite retrievals. Both satellite columns and in situ observations are higher in summer than winter, however satellite vertical column densities exceeded the surface observations by more than 1.5 × 1014 molecules cm-2 at both sites. This discrepancy may be due to the incorrect assumption that all glyoxal observed by satellite is within the boundary layer, or may be due to challenges retrieving low VCDs of glyoxal over the oceans due to interferences by liquid water absorption, or use of an inappropriate normalisation reference value in the retrieval algorithm. This study provides much needed data to verify the presence of these short lived gases over the remote ocean and provide further evidence of an as yet unidentified source of both glyoxal and also methylglyoxal over the remote oceans.

Seasonal in situ observations of glyoxal and methylglyoxal over the temperate oceans of the Southern Hemisphere

NASA Astrophysics Data System (ADS)

Lawson, S. J.; Selleck, P. W.; Galbally, I. E.; Keywood, M. D.; Harvey, M. J.; Lerot, C.; Helmig, D.; Ristovski, Z.

2015-01-01

The dicarbonyls glyoxal and methylglyoxal have been measured with 2,4-dinitrophenylhydrazine (2,4-DNPH) cartridges and high-performance liquid chromatography (HPLC), optimised for dicarbonyl detection, in clean marine air over the temperate Southern Hemisphere (SH) oceans. Measurements of a range of dicarbonyl precursors (volatile organic compounds, VOCs) were made in parallel. These are the first in situ measurements of glyoxal and methylglyoxal over the remote temperate oceans. Six 24 h samples were collected in summer (February-March) over the Chatham Rise in the south-west Pacific Ocean during the Surface Ocean Aerosol Production (SOAP) voyage in 2012, while 34 24 h samples were collected at Cape Grim Baseline Air Pollution Station in the late winter (August-September) of 2011. Average glyoxal mixing ratios in clean marine air were 7 ppt at Cape Grim and 23 ppt over Chatham Rise. Average methylglyoxal mixing ratios in clean marine air were 28 ppt at Cape Grim and 10 ppt over Chatham Rise. The mixing ratios of glyoxal at Cape Grim are the lowest observed over the remote oceans, while mixing ratios over Chatham Rise are in good agreement with other temperate and tropical observations, including concurrent Multi-Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) observations. Methylglyoxal mixing ratios at both sites are comparable to the only other marine methylglyoxal observations available over the tropical Northern Hemisphere (NH) ocean. Ratios of glyoxal : methylglyoxal > 1 over Chatham Rise but < 1 at Cape Grim suggest that a different formation and/or loss processes or rates dominate at each site. Dicarbonyl precursor VOCs, including isoprene and monoterpenes, are used to calculate an upper-estimate yield of glyoxal and methylglyoxal in the remote marine boundary layer and explain at most 1-3 ppt of dicarbonyls observed, corresponding to 10% and 17% of the observed glyoxal and 29 and 10% of the methylglyoxal at Chatham Rise and Cape Grim, respectively, highlighting a significant but as yet unknown production mechanism. Surface-level glyoxal observations from both sites were converted to vertical columns and compared to average vertical column densities (VCDs) from GOME-2 satellite retrievals. Both satellite columns and in situ observations are higher in summer than winter; however, satellite vertical column densities exceeded the surface observations by more than 1.5 × 1014 molecules cm-2 at both sites. This discrepancy may be due to the incorrect assumption that all glyoxal observed by satellite is within the boundary layer, or it may be due to challenges retrieving low VCDs of glyoxal over the oceans due to interferences by liquid water absorption or the use of an inappropriate normalisation reference value in the retrieval algorithm. This study provides much-needed data to verify the presence of these short-lived gases over the remote ocean and provide further evidence of an as yet unidentified source of both glyoxal and also methylglyoxal over the remote oceans.

Evaluation of the OMI Cloud Pressures Derived from Rotational Raman Scattering by Comparisons with other Satellite Data and Radiative Transfer Simulations

NASA Technical Reports Server (NTRS)

Vasilkov, Alexander; Joiner, Joanna; Spurr, Robert; Bhartia, Pawan K.; Levelt, Pieternel; Stephens, Graeme

2009-01-01

In this paper we examine differences between cloud pressures retrieved from the Ozone Monitoring Instrument (OMI) using the ultraviolet rotational Raman scattering (RRS) algorithm and those from the thermal infrared (IR) Aqua/MODIS. Several cloud data sets are currently being used in OMI trace gas retrieval algorithms including climatologies based on IR measurements and simultaneous cloud parameters derived from OMI. From a validation perspective, it is important to understand the OMI retrieved cloud parameters and how they differ with those derived from the IR. To this end, we perform radiative transfer calculations to simulate the effects of different geophysical conditions on the OMI RRS cloud pressure retrievals. We also quantify errors related to the use of the Mixed Lambert-Equivalent Reflectivity (MLER) concept as currently implemented of the OMI algorithms. Using properties from the Cloudsat radar and MODIS, we show that radiative transfer calculations support the following: (1) The MLER model is adequate for single-layer optically thick, geometrically thin clouds, but can produce significant errors in estimated cloud pressure for optically thin clouds. (2) In a two-layer cloud, the RRS algorithm may retrieve a cloud pressure that is either between the two cloud decks or even beneath the top of the lower cloud deck because of scattering between the cloud layers; the retrieved pressure depends upon the viewing geometry and the optical depth of the upper cloud deck. (3) Absorbing aerosol in and above a cloud can produce significant errors in the retrieved cloud pressure. (4) The retrieved RRS effective pressure for a deep convective cloud will be significantly higher than the physical cloud top pressure derived with thermal IR.

A Simple and Universal Aerosol Retrieval Algorithm for Landsat Series Images Over Complex Surfaces

NASA Astrophysics Data System (ADS)

Wei, Jing; Huang, Bo; Sun, Lin; Zhang, Zhaoyang; Wang, Lunche; Bilal, Muhammad

2017-12-01

Operational aerosol optical depth (AOD) products are available at coarse spatial resolutions from several to tens of kilometers. These resolutions limit the application of these products for monitoring atmospheric pollutants at the city level. Therefore, a simple, universal, and high-resolution (30 m) Landsat aerosol retrieval algorithm over complex urban surfaces is developed. The surface reflectance is estimated from a combination of top of atmosphere reflectance at short-wave infrared (2.22 μm) and Landsat 4-7 surface reflectance climate data records over densely vegetated areas and bright areas. The aerosol type is determined using the historical aerosol optical properties derived from the local urban Aerosol Robotic Network (AERONET) site (Beijing). AERONET ground-based sun photometer AOD measurements from five sites located in urban and rural areas are obtained to validate the AOD retrievals. Terra MODerate resolution Imaging Spectrometer Collection (C) 6 AOD products (MOD04) including the dark target (DT), the deep blue (DB), and the combined DT and DB (DT&DB) retrievals at 10 km spatial resolution are obtained for comparison purposes. Validation results show that the Landsat AOD retrievals at a 30 m resolution are well correlated with the AERONET AOD measurements (R2 = 0.932) and that approximately 77.46% of the retrievals fall within the expected error with a low mean absolute error of 0.090 and a root-mean-square error of 0.126. Comparison results show that Landsat AOD retrievals are overall better and less biased than MOD04 AOD products, indicating that the new algorithm is robust and performs well in AOD retrieval over complex surfaces. The new algorithm can provide continuous and detailed spatial distributions of AOD during both low and high aerosol loadings.

Improve observation-based ground-level ozone spatial distribution by compositing satellite and surface observations: A simulation experiment

NASA Astrophysics Data System (ADS)

Zhang, Yuzhong; Wang, Yuhang; Crawford, James; Cheng, Ye; Li, Jianfeng

2018-05-01

Obtaining the full spatial coverage of daily surface ozone fields is challenging because of the sparsity of the surface monitoring network and the difficulty in direct satellite retrievals of surface ozone. We propose an indirect satellite retrieval framework to utilize the information from satellite-measured column densities of tropospheric NO2 and CH2O, which are sensitive to the lower troposphere, to derive surface ozone fields. The method is applicable to upcoming geostationary satellites with high-quality NO2 and CH2O measurements. To prove the concept, we conduct a simulation experiment using a 3-D chemical transport model for July 2011 over the eastern US. The results show that a second order regression using both NO2 and CH2O column densities can be an effective predictor for daily maximum 8-h average ozone. Furthermore, this indirect retrieval approach is shown to be complementary to spatial interpolation of surface observations, especially in regions where the surface sites are sparse. Combining column observations of NO2 and CH2O with surface site measurements leads to an improved representation of surface ozone over simple kriging, increasing the R2 value from 0.53 to 0.64 at a surface site distance of 252 km. The improvements are even more significant with larger surface site distances. The simulation experiment suggests that the indirect satellite retrieval technique can potentially be a useful tool to derive the full spatial coverage of daily surface ozone fields if satellite observation uncertainty is moderate.

Comparison of a single-view and a double-view aerosol optical depth retrieval algorithm

NASA Astrophysics Data System (ADS)

Henderson, Bradley G.; Chylek, Petr

2003-11-01

We compare the results of a single-view and a double-view aerosol optical depth (AOD) retrieval algorithm applied to image pairs acquired over NASA Stennis Space Center, Mississippi. The image data were acquired by the Department of Energy's (DOE) Multispectral Thermal Imager (MTI), a pushbroom satellite imager with 15 bands from the visible to the thermal infrared. MTI has the ability to acquire imagery in pairs in which the first image is a near-nadir view and the second image is off-nadir with a zenith angle of approximately 60°. A total of 15 image pairs were used in the analysis. For a given image pair, AOD retrieval is performed twice---once using a single-view algorithm applied to the near-nadir image, then again using a double-view algorithm. Errors for both retrievals are computed by comparing the results to AERONET AOD measurements obtained at the same time and place. The single-view algorithm showed an RMS error about the mean of 0.076 in AOD units, whereas the double-view algorithm showed a modest improvement with an RMS error of 0.06. The single-view errors show a positive bias which is presumed to be a result of the empirical relationship used to determine ground reflectance in the visible. A plot of AOD error of the double-view algorithm versus time shows a noticeable trend which is interpreted to be a calibration drift. When this trend is removed, the RMS error of the double-view algorithm drops to 0.030. The single-view algorithm qualitatively appears to perform better during the spring and summer whereas the double-view algorithm seems to be less sensitive to season.

SEOM's Sentinel-3/OLCI' project CAWA: advanced GRASP aerosol retrieval

NASA Astrophysics Data System (ADS)

Dubovik, Oleg; litvinov, Pavel; Huang, Xin; Aspetsberger, Michael; Fuertes, David; Brockmann, Carsten; Fischer, Jürgen; Bojkov, Bojan

2016-04-01

The CAWA "Advanced Clouds, Aerosols and WAter vapour products for Sentinel-3/OLCI" ESA-SEOM project aims on the development of advanced atmospheric retrieval algorithms for the Sentinel-3/OLCI mission, and is prepared using Envisat/MERIS and Aqua/MODIS datasets. This presentation discusses mainly CAWA aerosol product developments and results. CAWA aerosol retrieval uses recently developed GRASP algorithm (Generalized Retrieval of Aerosol and Surface Properties) algorithm described by Dubovik et al. (2014). GRASP derives extended set of atmospheric parameters using multi-pixel concept - a simultaneous fitting of a large group of pixels under additional a priori constraints limiting the time variability of surface properties and spatial variability of aerosol properties. Over land GRASP simultaneously retrieves properties of both aerosol and underlying surface even over bright surfaces. GRAPS doesn't use traditional look-up-tables and performs retrieval as search in continuous space of solution. All radiative transfer calculations are performed as part of the retrieval. The results of comprehensive sensitivity tests, as well as results obtained from real Envisat/MERIS data will be presented. The tests analyze various aspects of aerosol and surface reflectance retrieval accuracy. In addition, the possibilities of retrieval improvement by means of implementing synergetic inversion of a combination of OLCI data with observations by SLSTR are explored. Both the results of numerical tests, as well as the results of processing several years of Envisat/MERIS data illustrate demonstrate reliable retrieval of AOD (Aerosol Optical Depth) and surface BRDF. Observed retrieval issues and advancements will be discussed. For example, for some situations we illustrate possibilities of retrieving aerosol absorption - property that hardly accessible from satellite observations with no multi-angular and polarimetric capabilities.

Phase retrieval via incremental truncated amplitude flow algorithm

NASA Astrophysics Data System (ADS)

Zhang, Quanbing; Wang, Zhifa; Wang, Linjie; Cheng, Shichao

2017-10-01

This paper considers the phase retrieval problem of recovering the unknown signal from the given quadratic measurements. A phase retrieval algorithm based on Incremental Truncated Amplitude Flow (ITAF) which combines the ITWF algorithm and the TAF algorithm is proposed. The proposed ITAF algorithm enhances the initialization by performing both of the truncation methods used in ITWF and TAF respectively, and improves the performance in the gradient stage by applying the incremental method proposed in ITWF to the loop stage of TAF. Moreover, the original sampling vector and measurements are preprocessed before initialization according to the variance of the sensing matrix. Simulation experiments verified the feasibility and validity of the proposed ITAF algorithm. The experimental results show that it can obtain higher success rate and faster convergence speed compared with other algorithms. Especially, for the noiseless random Gaussian signals, ITAF can recover any real-valued signal accurately from the magnitude measurements whose number is about 2.5 times of the signal length, which is close to the theoretic limit (about 2 times of the signal length). And it usually converges to the optimal solution within 20 iterations which is much less than the state-of-the-art algorithms.

Atmospheric Precorrected Differential Absorption technique to retrieve columnar water vapor

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schlaepfer, D.; Itten, K.I.; Borel, C.C.

1998-09-01

Differential absorption techniques are suitable to retrieve the total column water vapor contents from imaging spectroscopy data. A technique called Atmospheric Precorrected Differential Absorption (APDA) is derived directly from simplified radiative transfer equations. It combines a partial atmospheric correction with a differential absorption technique. The atmospheric path radiance term is iteratively corrected during the retrieval of water vapor. This improves the results especially over low background albedos. The error of the method for various ground reflectance spectra is below 7% for most of the spectra. The channel combinations for two test cases are then defined, using a quantitative procedure, whichmore » is based on MODTRAN simulations and the image itself. An error analysis indicates that the influence of aerosols and channel calibration is minimal. The APDA technique is then applied to two AVIRIS images acquired in 1991 and 1995. The accuracy of the measured water vapor columns is within a range of {+-}5% compared to ground truth radiosonde data.« less

3D Radiative Aspects of the Increased Aerosol Optical Depth Near Clouds

NASA Technical Reports Server (NTRS)

Marshak, Alexander; Wen, Guoyong; Remer, Lorraine; Cahalan, Robert; Coakley, Jim

2007-01-01

To characterize aerosol-cloud interactions it is important to correctly retrieve aerosol optical depth in the vicinity of clouds. It is well reported in the literature that aerosol optical depth increases with cloud cover. Part of the increase comes from real physics as humidification; another part, however, comes from 3D cloud effects in the remote sensing retrievals. In many cases it is hard to say whether the retrieved increased values of aerosol optical depth are remote sensing artifacts or real. In the presentation, we will discuss how the 3D cloud affects can be mitigated. We will demonstrate a simple model that can assess the enhanced illumination of cloud-free columns in the vicinity of clouds. This model is based on the assumption that the enhancement in the cloud-free column radiance comes from the enhanced Rayleigh scattering due to presence of surrounding clouds. A stochastic cloud model of broken cloudiness is used to simulate the upward flux.

Complex amplitude reconstruction by iterative amplitude-phase retrieval algorithm with reference

NASA Astrophysics Data System (ADS)

Shen, Cheng; Guo, Cheng; Tan, Jiubin; Liu, Shutian; Liu, Zhengjun

2018-06-01

Multi-image iterative phase retrieval methods have been successfully applied in plenty of research fields due to their simple but efficient implementation. However, there is a mismatch between the measurement of the first long imaging distance and the sequential interval. In this paper, an amplitude-phase retrieval algorithm with reference is put forward without additional measurements or priori knowledge. It gets rid of measuring the first imaging distance. With a designed update formula, it significantly raises the convergence speed and the reconstruction fidelity, especially in phase retrieval. Its superiority over the original amplitude-phase retrieval (APR) method is validated by numerical analysis and experiments. Furthermore, it provides a conceptual design of a compact holographic image sensor, which can achieve numerical refocusing easily.

Evaluation of Aerosol Pollution Determination From MODIS Satellite Retrievals for Semi-Arid Reno, NV, USA with In-Situ Measurements

NASA Astrophysics Data System (ADS)

Loria-Salazar, S. Marcela

The aim of the present work is to carry out a detailed analysis of ground and columnar aerosol properties obtained by in-situ Photoacoustic and Integrated Nephelometer (PIN), Cimel CE-318 sunphotometer and MODIS instrument onboard Aqua and Terra satellites, for semi-arid Reno, Nevada, USA in the local summer months of 2012. Satellite determination of local aerosol pollution is desirable because of the potential for broad spatial and temporal coverage. However, retrieval of quantitative measures of air pollution such as Aerosol Optical Depth (AOD) from satellite measurements is challenging because of the underlying surface albedo being heterogeneous in space and time. Therefore, comparisons of satellite retrievals with measurements from ground-based sun photometers are crucial for validation, testing, and further development of instruments and retrieval algorithms. Ground-based sunphotometry and in-situ ground observations show that seasonal weather changes and fire plumes have great influence on the atmosphere aerosol optics. The Apparent Optical Height (AOH) follows the shape of the development of the Convective Boundary Layer (CBL) when fire conditions were not present. However, significant fine particle optical depth was inferred beyond the CBL thereby complicating the use of remote sensing measurements for near-ground aerosol pollution measurements. A meteorological analysis was performed to help diagnose the nature of the aerosols above Reno. The calculation of a Zephyr index and back trajectory analysis demonstrated that a local circulation often induces aerosol transport from Northern CA over the Sierra Nevada Mountains that doubles the Aerosol Optical Depth (AOD) at 500 nm. Sunphotometer measurements were used as a `ground truth' for satellite retrievals to evaluate the current state of the science retrievals in this challenging location. Satellite retrieved for AOD showed the presence of wild fires in Northern CA during August. AOD retrieved using the "dark-target algorithm" may be unrealistically high over the Great Basin. Low correlation was found between AERONET AOD and dark-target algorithm AOD retrievals from Aqua and Terra during June and July. During fire conditions the dark-target algorithm AOD values correlated better with AERONET measurements in August. Use of the Deep-blue algorithm for MODIS data to retrieve AOD did not provide enough points to compare with AERONET in June and July. In August, AOD from deep-blue and AERONET retrievals exhibited low correlation. AEE from MODIS products and AERONET exhibited low correlation during every month. Apparently satellite AOD retrievals need much improvement for areas like semi-arid Reno.

Phase retrieval based wavefront sensing experimental implementation and wavefront sensing accuracy calibration

NASA Astrophysics Data System (ADS)

Mao, Heng; Wang, Xiao; Zhao, Dazun

2009-05-01

As a wavefront sensing (WFS) tool, Baseline algorithm, which is classified as the iterative-transform algorithm of phase retrieval, estimates the phase distribution at pupil from some known PSFs at defocus planes. By using multiple phase diversities and appropriate phase unwrapping methods, this algorithm can accomplish reliable unique solution and high dynamic phase measurement. In the paper, a Baseline algorithm based wavefront sensing experiment with modification of phase unwrapping has been implemented, and corresponding Graphical User Interfaces (GUI) software has also been given. The adaptability and repeatability of Baseline algorithm have been validated in experiments. Moreover, referring to the ZYGO interferometric results, the WFS accuracy of this algorithm has been exactly calibrated.

A New 1DVAR Retrieval for AMSR2 and GMI: Validation and Sensitivites

NASA Astrophysics Data System (ADS)

Duncan, D.; Kummerow, C. D.

2015-12-01

A new non-raining retrieval has been developed for microwave imagers and applied to the GMI and AMSR2 sensors. With the Community Radiative Transfer Model (CRTM) as the forward model for the physical retrieval, a 1-dimensional variational method finds the atmospheric state which minimizes the difference between observed and simulated brightness temperatures. A key innovation of the algorithm development is a method to calculate the sensor error covariance matrix that is specific to the forward model employed and includes off-diagonal elements, allowing the algorithm to handle various forward models and sensors with little cross-talk. The water vapor profile is resolved by way of empirical orthogonal functions (EOFs) and then summed to get total precipitable water (TPW). Validation of retrieved 10m wind speed, TPW, and sea surface temperature (SST) is performed via comparison with buoys and radiosondes as well as global models and other remotely sensed products. In addition to the validation, sensitivity experiments investigate the impact of ancillary data on the under-constrained retrieval, a concern for climate data records that strive to be independent of model biases. The introduction of model analysis data is found to aid the algorithm most at high frequency channels and affect TPW retrievals, whereas wind and cloud water retrievals show little effect from ingesting further ancillary data.

A Bayesian approach to microwave precipitation profile retrieval

NASA Technical Reports Server (NTRS)

Evans, K. Franklin; Turk, Joseph; Wong, Takmeng; Stephens, Graeme L.

1995-01-01

A multichannel passive microwave precipitation retrieval algorithm is developed. Bayes theorem is used to combine statistical information from numerical cloud models with forward radiative transfer modeling. A multivariate lognormal prior probability distribution contains the covariance information about hydrometeor distribution that resolves the nonuniqueness inherent in the inversion process. Hydrometeor profiles are retrieved by maximizing the posterior probability density for each vector of observations. The hydrometeor profile retrieval method is tested with data from the Advanced Microwave Precipitation Radiometer (10, 19, 37, and 85 GHz) of convection over ocean and land in Florida. The CP-2 multiparameter radar data are used to verify the retrieved profiles. The results show that the method can retrieve approximate hydrometeor profiles, with larger errors over land than water. There is considerably greater accuracy in the retrieval of integrated hydrometeor contents than of profiles. Many of the retrieval errors are traced to problems with the cloud model microphysical information, and future improvements to the algorithm are suggested.

Evaluation of Skin Temperatures Retrieved from GOES-8

NASA Technical Reports Server (NTRS)

Suggs, Ronnie, J.; Jedlovec, G. J.; Lapenta, W. M.; Haines, S. L.

2000-01-01

Skin temperatures derived from geostationary satellites have the potential of providing the temporal and spatial resolution needed for model assimilation. To adequately assess the potential improvements in numerical model forecasts that can be made by assimilating satellite data, an estimate of the accuracy of the skin temperature product is necessary. A particular skin temperature algorithm, the Physical Split Window Technique, that uses the longwave infrared channels of the GOES Imager has shown promise in recent model assimilation studies to provide land surface temperatures with reasonable accuracy. A comparison of retrieved GOES-8 skin temperatures from this algorithm with in situ measurements is presented. Various retrieval algorithm issues are addressed including surface emissivity

Remote sensing of cirrus cloud vertical size profile using MODIS data

NASA Astrophysics Data System (ADS)

Wang, Xingjuan; Liou, K. N.; Ou, Steve S. C.; Mace, G. G.; Deng, M.

2009-05-01

This paper describes an algorithm for inferring cirrus cloud top and cloud base effective particle sizes and cloud optical thickness from the Moderate Resolution Imaging Spectroradiometer (MODIS) 0.645, 1.64 and 2.13, and 3.75 μm band reflectances/radiances. This approach uses a successive minimization method based on a look-up library of precomputed reflectances/radiances from an adding-doubling radiative transfer program, subject to corrections for Rayleigh scattering at the 0.645 μm band, above-cloud water vapor absorption, and 3.75 μm thermal emission. The algorithmic accuracy and limitation of the retrieval method were investigated by synthetic retrievals subject to the instrument noise and the perturbation of input parameters. The retrieval algorithm was applied to three MODIS cirrus scenes over the Atmospheric Radiation Measurement Program's southern Great Plain site, north central China, and northeast Asia. The reliability of retrieved cloud optical thicknesses and mean effective particle sizes was evaluated by comparison with MODIS cloud products and qualitatively good correlations were obtained for all three cases, indicating that the performance of the vertical sizing algorithm is comparable with the MODIS retrieval program. Retrieved cloud top and cloud base ice crystal effective sizes were also compared with those derived from the collocated ground-based millimeter wavelength cloud radar for the first case and from the Cloud Profiling Radar onboard CloudSat for the other two cases. Differences between retrieved and radar-derived cloud properties are discussed in light of assumptions made in the collocation process and limitations in radar remote sensing characteristics.

Performance analysis of algorithms for retrieval of magnetic resonance images for interactive teleradiology

NASA Astrophysics Data System (ADS)

Atkins, M. Stella; Hwang, Robert; Tang, Simon

2001-05-01

We have implemented a prototype system consisting of a Java- based image viewer and a web server extension component for transmitting Magnetic Resonance Images (MRI) to an image viewer, to test the performance of different image retrieval techniques. We used full-resolution images, and images compressed/decompressed using the Set Partitioning in Hierarchical Trees (SPIHT) image compression algorithm. We examined the SPIHT decompression algorithm using both non- progressive and progressive transmission, focusing on the running times of the algorithm, client memory usage and garbage collection. We also compared the Java implementation with a native C++ implementation of the non- progressive SPIHT decompression variant. Our performance measurements showed that for uncompressed image retrieval using a 10Mbps Ethernet, a film of 16 MR images can be retrieved and displayed almost within interactive times. The native C++ code implementation of the client-side decoder is twice as fast as the Java decoder. If the network bandwidth is low, the high communication time for retrieving uncompressed images may be reduced by use of SPIHT-compressed images, although the image quality is then degraded. To provide diagnostic quality images, we also investigated the retrieval of up to 3 images on a MR film at full-resolution, using progressive SPIHT decompression. The Java-based implementation of progressive decompression performed badly, mainly due to the memory requirements for maintaining the image states, and the high cost of execution of the Java garbage collector. Hence, in systems where the bandwidth is high, such as found in a hospital intranet, SPIHT image compression does not provide advantages for image retrieval performance.

Accuracy Assessment of Aqua-MODIS Aerosol Optical Depth Over Coastal Regions: Importance of Quality Flag and Sea Surface Wind Speed

NASA Technical Reports Server (NTRS)

Anderson, J. C.; Wang, J.; Zeng, J.; Petrenko, M.; Leptoukh, G. G.; Ichoku, C.

2012-01-01

Coastal regions around the globe are a major source for anthropogenic aerosols in the atmosphere, but the underlying surface characteristics are not favorable for the Moderate Resolution Imaging Spectroradiometer (MODIS) algorithms designed for retrieval of aerosols over dark land or open-ocean surfaces. Using data collected from 62 coastal stations worldwide from the Aerosol Robotic Network (AERONET) from approximately 2002-2010, accuracy assessments are made for coastal aerosol optical depth (AOD) retrieved from MODIS aboard Aqua satellite. It is found that coastal AODs (at 550 nm) characterized respectively by the MODIS Dark Land (hereafter Land) surface algorithm, the Open-Ocean (hereafter Ocean) algorithm, and AERONET all exhibit a log-normal distribution. After filtering by quality flags, the MODIS AODs respectively retrieved from the Land and Ocean algorithms are highly correlated with AERONET (with R(sup 2) is approximately equal to 0.8), but only the Land algorithm AODs fall within the expected error envelope greater than 66% of the time. Furthermore, the MODIS AODs from the Land algorithm, Ocean algorithm, and combined Land and Ocean product show statistically significant discrepancies from their respective counterparts from AERONET in terms of mean, probability density function, and cumulative density function, which suggest a need for future improvement in retrieval algorithms. Without filtering with quality flag, the MODIS Land and Ocean AOD dataset can be degraded by 30-50% in terms of mean bias. Overall, the MODIS Ocean algorithm overestimates the AERONET coastal AOD by 0.021 for AOD less than 0.25 and underestimates it by 0.029 for AOD greater than 0.25. This dichotomy is shown to be related to the ocean surface wind speed and cloud contamination effects on the satellite aerosol retrieval. The Modern Era Retrospective-Analysis for Research and Applications (MERRA) reveals that wind speeds over the global coastal region 25 (with a mean and median value of 2.94 meters per second and 2.66 meters per second, respectively) are often slower than 6 meters per second assumed in the MODIS Ocean algorithm. As a result of high correlation (R(sup 2) greater than 0.98) between the bias in binned MODIS AOD and the corresponding binned wind speed over the coastal sea surface, an empirical scheme for correcting the bias of AOD retrieved from the MODIS Ocean algorithm is formulated and is shown to be effective over the majority of the coastal AERONET stations, and hence can be used in future analysis of AOD trend and MODIS AOD data assimilation.

Phase retrieval by coherent modulation imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Fucai; Chen, Bo; Morrison, Graeme R.

Phase retrieval is a long-standing problem in imaging when only the intensity of the wavefield can be recorded. Coherent diffraction imaging (CDI) is a lensless technique that uses iterative algorithms to recover amplitude and phase contrast images from diffraction intensity data. For general samples, phase retrieval from a single diffraction pattern has been an algorithmic and experimental challenge. Here we report a method of phase retrieval that uses a known modulation of the sample exit-wave. This coherent modulation imaging (CMI) method removes inherent ambiguities of CDI and uses a reliable, rapidly converging iterative algorithm involving three planes. It works formore » extended samples, does not require tight support for convergence, and relaxes dynamic range requirements on the detector. CMI provides a robust method for imaging in materials and biological science, while its single-shot capability will benefit the investigation of dynamical processes with pulsed sources, such as X-ray free electron laser.« less

Phase retrieval by coherent modulation imaging

DOE PAGES

Zhang, Fucai; Chen, Bo; Morrison, Graeme R.; ...

2016-11-18

Phase retrieval is a long-standing problem in imaging when only the intensity of the wavefield can be recorded. Coherent diffraction imaging (CDI) is a lensless technique that uses iterative algorithms to recover amplitude and phase contrast images from diffraction intensity data. For general samples, phase retrieval from a single diffraction pattern has been an algorithmic and experimental challenge. Here we report a method of phase retrieval that uses a known modulation of the sample exit-wave. This coherent modulation imaging (CMI) method removes inherent ambiguities of CDI and uses a reliable, rapidly converging iterative algorithm involving three planes. It works formore » extended samples, does not require tight support for convergence, and relaxes dynamic range requirements on the detector. CMI provides a robust method for imaging in materials and biological science, while its single-shot capability will benefit the investigation of dynamical processes with pulsed sources, such as X-ray free electron laser.« less

Columnar aerosol properties over oceans by combining surface and aircraft measurements: sensitivity analysis.

PubMed

Zhang, T; Gordon, H R

1997-04-20

We report a sensitivity analysis for the algorithm presented by Gordon and Zhang [Appl. Opt. 34, 5552 (1995)] for inverting the radiance exiting the top and bottom of the atmosphere to yield the aerosol-scattering phase function [P(?)] and single-scattering albedo (omega(0)). The study of the algorithm's sensitivity to radiometric calibration errors, mean-zero instrument noise, sea-surface roughness, the curvature of the Earth's atmosphere, the polarization of the light field, and incorrect assumptions regarding the vertical structure of the atmosphere, indicates that the retrieved omega(0) has excellent stability even for very large values (~2) of the aerosol optical thickness; however, the error in the retrieved P(?) strongly depends on the measurement error and on the assumptions made in the retrieval algorithm. The retrieved phase functions in the blue are usually poor compared with those in the near infrared.

Phase retrieval by coherent modulation imaging.

PubMed

Zhang, Fucai; Chen, Bo; Morrison, Graeme R; Vila-Comamala, Joan; Guizar-Sicairos, Manuel; Robinson, Ian K

2016-11-18

Phase retrieval is a long-standing problem in imaging when only the intensity of the wavefield can be recorded. Coherent diffraction imaging is a lensless technique that uses iterative algorithms to recover amplitude and phase contrast images from diffraction intensity data. For general samples, phase retrieval from a single-diffraction pattern has been an algorithmic and experimental challenge. Here we report a method of phase retrieval that uses a known modulation of the sample exit wave. This coherent modulation imaging method removes inherent ambiguities of coherent diffraction imaging and uses a reliable, rapidly converging iterative algorithm involving three planes. It works for extended samples, does not require tight support for convergence and relaxes dynamic range requirements on the detector. Coherent modulation imaging provides a robust method for imaging in materials and biological science, while its single-shot capability will benefit the investigation of dynamical processes with pulsed sources, such as X-ray free-electron lasers.

DOLPHIn—Dictionary Learning for Phase Retrieval

NASA Astrophysics Data System (ADS)

Tillmann, Andreas M.; Eldar, Yonina C.; Mairal, Julien

2016-12-01

We propose a new algorithm to learn a dictionary for reconstructing and sparsely encoding signals from measurements without phase. Specifically, we consider the task of estimating a two-dimensional image from squared-magnitude measurements of a complex-valued linear transformation of the original image. Several recent phase retrieval algorithms exploit underlying sparsity of the unknown signal in order to improve recovery performance. In this work, we consider such a sparse signal prior in the context of phase retrieval, when the sparsifying dictionary is not known in advance. Our algorithm jointly reconstructs the unknown signal - possibly corrupted by noise - and learns a dictionary such that each patch of the estimated image can be sparsely represented. Numerical experiments demonstrate that our approach can obtain significantly better reconstructions for phase retrieval problems with noise than methods that cannot exploit such "hidden" sparsity. Moreover, on the theoretical side, we provide a convergence result for our method.

MWRRET Value-Added Product: The Retrieval of Liquid Water Path and Precipitable Water Vapor from Microwave Radiometer (MWR) Data Sets (Revision 2)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gaustad, KL; Turner, DD; McFarlane, SA

2011-07-25

This report provides a short description of the Atmospheric Radiation Measurement (ARM) Climate Research Facility microwave radiometer (MWR) Retrieval (MWRRET) value-added product (VAP) algorithm. This algorithm utilizes a complementary physical retrieval method and applies brightness temperature offsets to reduce spurious liquid water path (LWP) bias in clear skies resulting in significantly improved precipitable water vapor (PWV) and LWP retrievals. We present a general overview of the technique, input parameters, output products, and describe data quality checks. A more complete discussion of the theory and results is given in Turner et al. (2007b).

An introduction to the theory of ptychographic phase retrieval methods

NASA Astrophysics Data System (ADS)

Konijnenberg, Sander

2017-12-01

An overview of several ptychographic phase retrieval methods and the theory behind them is presented. By looking into the theory behind more basic single-intensity pattern phase retrieval methods, a theoretical framework is provided for analyzing ptychographic algorithms. Extensions of ptychographic algorithms that deal with issues such as partial coherence, thick samples, or uncertainties of the probe or probe positions are also discussed. This introduction is intended for scientists and students without prior experience in the field of phase retrieval or ptychography to quickly get introduced to the theory, so that they can put the more specialized literature in context more easily.

Retrieval of aerosol optical properties using MERIS observations: Algorithm and some first results.

PubMed

Mei, Linlu; Rozanov, Vladimir; Vountas, Marco; Burrows, John P; Levy, Robert C; Lotz, Wolfhardt

2017-08-01

The MEdium Resolution Imaging Spectrometer (MERIS) instrument on board ESA Envisat made measurements from 2002 to 2012. Although MERIS was limited in spectral coverage, accurate Aerosol Optical Thickness (AOT) from MERIS data are retrieved by using appropriate additional information. We introduce a new AOT retrieval algorithm for MERIS over land surfaces, referred to as eXtensible Bremen AErosol Retrieval (XBAER). XBAER is similar to the "dark-target" (DT) retrieval algorithm used for Moderate-resolution Imaging Spectroradiometer (MODIS), in that it uses a lookup table (LUT) to match to satellite-observed reflectance and derive the AOT. Instead of a global parameterization of surface spectral reflectance, XBAER uses a set of spectral coefficients to prescribe surface properties. In this manner, XBAER is not limited to dark surfaces (vegetation) and retrieves AOT over bright surface (desert, semiarid, and urban areas). Preliminary validation of the MERIS-derived AOT and the ground-based Aerosol Robotic Network (AERONET) measurements yield good agreement, the resulting regression equation is y = (0.92 × ± 0.07) + (0.05 ± 0.01) and Pearson correlation coefficient of R = 0.78. Global monthly means of AOT have been compared from XBAER, MODIS and other satellite-derived datasets.

a New Algorithm for the Aod Inversion from Noaa/avhrr Data

NASA Astrophysics Data System (ADS)

Sun, L.; Li, R.; Yu, H.

2018-04-01

The advanced very high resolution radiometer (AVHRR) data from the National Oceanic and Atmospheric Administration satellite is one of the earliest data applied in aerosol research. The dense dark vegetation (DDV) algorithm is a popular method for the present land aerosol retrieval. One of the most crucial steps in the DDV algorithm with AVHRR data is estimating the land surface reflectance (LSR). However, LSR cannot be easily estimated because of the lack of a 2.13 μm band. In this article, the moderate resolution imaging spectroradiometer (MODIS) vegetation index product (MYD13) is introduced to support the estimation of AVHRR LSR. The relationship between MODIS NDVI and the AVHRR LSR of the visible band is analysed to retrieve aerosol optical depth (AOD) from AVHRR data. Retrieval experiments are carried out in mid-eastern America. The AOD data from AErosol RObotic NETwork (AERONET) measurements are used to evaluate the aerosol retrieval from AVHRR data, the results indicate that about 74 % of the retrieved AOD are within the expected error range of ±(0.05 + 0.2), and a cross comparison of the AOD retrieval results with the MODIS aerosol product (MYD04) shows that the AOD datasets have a similar spatial distribution.

The role of cloud contamination, aerosol layer height and aerosol model in the assessment of the OMI near-UV retrievals over the ocean

NASA Astrophysics Data System (ADS)

Gassó, Santiago; Torres, Omar

2016-07-01

Retrievals of aerosol optical depth (AOD) at 388 nm over the ocean from the Ozone Monitoring Instrument (OMI) two-channel near-UV algorithm (OMAERUV) have been compared with independent AOD measurements. The analysis was carried out over the open ocean (OMI and MODerate-resolution Imaging Spectrometer (MODIS) AOD comparisons) and over coastal and island sites (OMI and AERONET, the AErosol RObotic NETwork). Additionally, a research version of the retrieval algorithm (using MODIS and CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) information as constraints) was utilized to evaluate the sensitivity of the retrieval to different assumed aerosol properties. Overall, the comparison resulted in differences (OMI minus independent measurements) within the expected levels of uncertainty for the OMI AOD retrievals (0.1 for AOD < 0.3, 30 % for AOD > 0.3). Using examples from case studies with outliers, the reasons that led to the observed differences were examined with specific purpose to determine whether they are related to instrument limitations (i.e., pixel size, calibration) or algorithm assumptions (such as aerosol shape, aerosol height). The analysis confirms that OMAERUV does an adequate job at rejecting cloudy scenes within the instrument's capabilities. There is a residual cloud contamination in OMI pixels with quality flag 0 (the best conditions for aerosol retrieval according to the algorithm), resulting in a bias towards high AODs in OMAERUV. This bias is more pronounced at low concentrations of absorbing aerosols (AOD 388 nm ˜ < 0.5). For higher aerosol loadings, the bias remains within OMI's AOD uncertainties. In pixels where OMAERUV assigned a dust aerosol model, a fraction of them (< 20 %) had retrieved AODs significantly lower than AERONET and MODIS AODs. In a case study, a detailed examination of the aerosol height from CALIOP and the AODs from MODIS, along with sensitivity tests, was carried out by varying the different assumed parameters in the retrieval (imaginary index of refraction, size distribution, aerosol height, particle shape). It was found that the spherical shape assumption for dust in the current retrieval is the main cause of the underestimate. In addition, it is demonstrated in an example how an incorrect assumption of the aerosol height can lead to an underestimate. Nevertheless, this is not as significant as the effect of particle shape. These findings will be incorporated in a future version of the retrieval algorithm.

The Re-Analysis of Ozone Profile Data from a 41-Year Series of SBUV Instruments

NASA Technical Reports Server (NTRS)

Kramarova, Natalya; Frith, Stacey; Bhartia, Pawan K.; McPeters, Richard; Labow, Gordon; Taylor, Steven; Fisher, Bradford

2012-01-01

In this study we present the validation of ozone profiles from a number of Solar Back Scattered Ultra Violet (SBUV) and SBUV/2 instruments that were recently reprocessed using an updated (Version 8.6) algorithm. The SBUV dataset provides the longest available record of global ozone profiles, spanning a 41-year period from 1970 to 2011 (except a 5-year gap in the 1970s) and includes ozone profile records obtained from the Nimbus-4 BUV and Nimbus-7 SBUV instruments, and a series of SBUV(/2) instruments launched on NOAA operational satellites (NOAA 09, 11, 14, 16, 17, 18, 19). Although modifications in instrument design were made in the evolution from the BUV instrument to the modern SBUV(/2) model, the basic principles of the measurement technique and retrieval algorithm remain the same. The long term SBUV data record allows us to create a consistent, calibrated dataset of ozone profiles that can be used for climate studies and trend analyses. In particular, we focus on estimating the various sources of error in the SBUV profile ozone retrievals using independent observations and analysis of the algorithm itself. For the first time we include in the metadata a quantitative estimate of the smoothing error, defined as the error due to profile variability that the SBUV observing system cannot inherently measure. The magnitude of the smoothing error varies with altitude, latitude, season and solar zenith angle. Between 10 and 1 hPa the smoothing errors for the SBUV monthly zonal mean retrievals are of the order of 1 %, but start to increase above and below this layer. The largest smoothing errors, as large as 15-20%, were detected in in the troposphere. The SBUV averaging kernels, provided with the ozone profiles in version 8.6, help to eliminate the smoothing effect when comparing the SBUV profiles with high vertical resolution measurements, and make it convenient to use the SBUV ozone profiles for data assimilation and model validation purposes. The smoothing error can also be minimized by combining layers of data, and we will discuss recommendations for this approach as well. The SBUV ozone profiles have been intensively validated against satellite profile measurements obtained from the Microwave Limb Sounders (MLS) (on board the UARS and AURA satellites), Stratospheric Aerosol and Gas Experiment (SAGE) and Michelson Interferometer for Passive Atmospheric Sounding (MIPAS). Also, we compare coincident and collocated SBUV ozone retrievals with observations made by ground-based instruments, such as microwave spectrometers, lidars, Umkehr instruments and balloon-borne ozonosondes. Finally, we compare the SBUV ozone profiles with output from the NASA GSFC GEOS-CCM model. In the stratosphere between 25 and 1 hPa the mean biases and standard deviations are within 5% for monthly mean ozone profiles. Above and below this layer the vertical resolution of the SBUV algorithm decreases and the effects of vertical smoothing should be taken into account. Though the SBUV algorithm has a coarser vertical resolution in the lower stratosphere and troposphere, it is capable of precisely estimating the integrated ozone column between the surface and 25 hPa. The time series of the tropospheric - lower stratospheric ozone column derived from SBUV agrees within 5% with the corresponding values observed by an ensemble of ozone sonde stations in North Hemisphere. Drift of the ozone time series obtained from each SBUV(/2) instrument relative to ground based and satellite measurements are evaluated and some features of individual SBUV(l2) instruments are discussed. In addition to evaluating individual instruments against independent observations, we also focus on the instrument to instrument consistency in the series. Overall, Version 8.6 ozone profiles obtained from two different SBUV(l2) instruments compare within a couple of percent during overlap periods and are consistently varying in time, with some exceptions. Some of the noted discrepancies might bssociated with ozone diurnal variations, since the difference in the local time of the observations for a pair of SBUV(l2) instruments could be several hours. Other issues include the potential short-term drift in measurements as the instrument orbit drifts, and measurements are obtained at high solar zenith angles (>85 ). Based on the results of the validation, a consistent, calibrated dataset of SBUV ozone profiles has been created based on internal calibration only.

Multiannual tropical tropospheric ozone columns and the case of the 2015 el Niño event

NASA Astrophysics Data System (ADS)

Leventidou, Elpida; Eichmann, Kai-Uwe; Weber, Mark; Burrows, John P.

2016-04-01

Stratospheric ozone is well known for protecting the surface from harmful ultraviolet solar radiation whereas ozone in the troposphere plays a more complex role. In the lower troposphere ozone can be extremely harmful for human health as it can oxidize biological tissues and causes respiratory problems. Several studies have shown that the tropospheric ozone burden (300±30Tg (IPCC, 2007)) increases by 1-7% per decade in the tropics (Beig and Singh, 2007; Cooper et al., 2014) which makes the need to monitor it on a global scale crucial. Remote sensing from satellites has been proven to be very useful in providing consistent information of tropospheric ozone concentrations over large areas. Tropical tropospheric ozone columns can be retrieved with the Convective Cloud Differential (CCD) technique (Ziemke et al. 1998) using retrieved total ozone columns and cloud parameters from space-borne observations. We have developed a CCD-IUP algorithm which was applied to GOME/ ERS-2 (1995-2003), SCIAMACHY/ Envisat (2002-2012), and GOME-2/ MetOpA (2007-2012) weighting function DOAS (Coldewey-Egbers et al., 2005, Weber et al., 2005) total ozone data. A unique long-term record of monthly averaged tropical tropospheric ozone columns (20°S - 20°N) was created starting in 1996. This dataset has been extensively validated by comparisons with SHADOZ (Thompson et al., 2003) ozonesonde data and limb-nadir Matching (Ebojie et al. 2014) tropospheric ozone data. The comparison shows good agreement with respect to range, inter-annual variation, and variance. Biases where found to be within 5DU and the RMS errors less than 10 DU. This 17-years dataset has been harmonized into one consistent time series, taking into account the three instruments' difference in ground pixel size. The harmonised dataset is used to determine tropical tropospheric ozone trends and climatological values. The 2015 el Niño event has been characterised as one of the top three strongest el Niños since 1950. El Niño events are major sources of the tropospheric ozone variability (Ziemke and Chandra,2003) due to changes in the convection pattern and large-scale circulation in the tropical Pacific region. More clouds and rainfall appear in the central and/or eastern Pacific whereas more dryness over Indonesia and as a result strongest forest fires. These effects cause enhanced tropospheric ozone columns over the Indonesian region and reduced over the eastern Pacific. The focus of this work is to present the first results of tropospheric ozone trends the last 17 years as long as to understand and quantify the tropical tropospheric ozone (TTCO) anomalies due to the 2015 el Niño event.

An incremental DPMM-based method for trajectory clustering, modeling, and retrieval.

PubMed

Hu, Weiming; Li, Xi; Tian, Guodong; Maybank, Stephen; Zhang, Zhongfei

2013-05-01

Trajectory analysis is the basis for many applications, such as indexing of motion events in videos, activity recognition, and surveillance. In this paper, the Dirichlet process mixture model (DPMM) is applied to trajectory clustering, modeling, and retrieval. We propose an incremental version of a DPMM-based clustering algorithm and apply it to cluster trajectories. An appropriate number of trajectory clusters is determined automatically. When trajectories belonging to new clusters arrive, the new clusters can be identified online and added to the model without any retraining using the previous data. A time-sensitive Dirichlet process mixture model (tDPMM) is applied to each trajectory cluster for learning the trajectory pattern which represents the time-series characteristics of the trajectories in the cluster. Then, a parameterized index is constructed for each cluster. A novel likelihood estimation algorithm for the tDPMM is proposed, and a trajectory-based video retrieval model is developed. The tDPMM-based probabilistic matching method and the DPMM-based model growing method are combined to make the retrieval model scalable and adaptable. Experimental comparisons with state-of-the-art algorithms demonstrate the effectiveness of our algorithm.

Application of the LSQR algorithm in non-parametric estimation of aerosol size distribution

NASA Astrophysics Data System (ADS)

He, Zhenzong; Qi, Hong; Lew, Zhongyuan; Ruan, Liming; Tan, Heping; Luo, Kun

2016-05-01

Based on the Least Squares QR decomposition (LSQR) algorithm, the aerosol size distribution (ASD) is retrieved in non-parametric approach. The direct problem is solved by the Anomalous Diffraction Approximation (ADA) and the Lambert-Beer Law. An optimal wavelength selection method is developed to improve the retrieval accuracy of the ASD. The proposed optimal wavelength set is selected by the method which can make the measurement signals sensitive to wavelength and decrease the degree of the ill-condition of coefficient matrix of linear systems effectively to enhance the anti-interference ability of retrieval results. Two common kinds of monomodal and bimodal ASDs, log-normal (L-N) and Gamma distributions, are estimated, respectively. Numerical tests show that the LSQR algorithm can be successfully applied to retrieve the ASD with high stability in the presence of random noise and low susceptibility to the shape of distributions. Finally, the experimental measurement ASD over Harbin in China is recovered reasonably. All the results confirm that the LSQR algorithm combined with the optimal wavelength selection method is an effective and reliable technique in non-parametric estimation of ASD.

Measurements of Atmospheric CO2 Column in Cloudy Weather Conditions using An IM-CW Lidar at 1.57 Micron

NASA Technical Reports Server (NTRS)

Lin, Bing; Obland, Michael; Harrison, F. Wallace; Nehrir, Amin; Browell, Edward; Campbell, Joel; Dobler, Jeremy; Meadows, Bryon; Fan, Tai-Fang; Kooi, Susan;

Fast Simulators for Satellite Cloud Optical Centroid Pressure Retrievals, 1. Evaluation of OMI Cloud Retrievals

NASA Technical Reports Server (NTRS)

Joiner, J.; Vasilkov, A. P.; Gupta, Pawan; Bhartia, P. K.; Veefkind, Pepijn; Sneep, Maarten; deHaan, Johan; Polonsky, Igor; Spurr, Robert

2011-01-01

We have developed a relatively simple scheme for simulating retrieved cloud optical centroid pressures (OCP) from satellite solar backscatter observations. We have compared simulator results with those from more detailed retrieval simulators that more fully account for the complex radiative transfer in a cloudy atmosphere. We used this fast simulator to conduct a comprehensive evaluation of cloud OCPs from the two OMI algorithms using collocated data from CloudSat and Aqua MODIS, a unique situation afforded by the A-train formation of satellites. We find that both OMI algorithms perform reasonably well and that the two algorithms agree better with each other than either does with the collocated CloudSat data. This indicates that patchy snow/ice, cloud 3D, and aerosol effects not simulated with the CloudSat data are affecting both algorithms similarly. We note that the collocation with CloudSat occurs mainly on the East side of OMI's swath. Therefore, we are not able to address cross-track biases in OMI cloud OCP retrievals. Our fast simulator may also be used to simulate cloud OCP from output generated by general circulation models (GCM) with appropriate account of cloud overlap. We have implemented such a scheme and plan to compare OMI data with GCM output in the near future.

Retrieval of total water vapour in the Arctic using microwave humidity sounders

NASA Astrophysics Data System (ADS)

Cristian Scarlat, Raul; Melsheimer, Christian; Heygster, Georg

2018-04-01

Quantitative retrievals of atmospheric water vapour in the Arctic present numerous challenges because of the particular climate characteristics of this area. Here, we attempt to build upon the work of Melsheimer and Heygster (2008) to retrieve total atmospheric water vapour (TWV) in the Arctic from satellite microwave radiometers. While the above-mentioned algorithm deals primarily with the ice-covered central Arctic, with this work we aim to extend the coverage to partially ice-covered and ice-free areas. By using modelled values for the microwave emissivity of the ice-free sea surface, we develop two sub-algorithms using different sets of channels that deal solely with open-ocean areas. The new algorithm extends the spatial coverage of the retrieval throughout the year but especially in the warmer months when higher TWV values are frequent. The high TWV measurements over both sea-ice and open-water surfaces are, however, connected to larger uncertainties as the retrieval values are close to the instrument saturation limits.This approach allows us to apply the algorithm to regions where previously no data were available and ensures a more consistent physical analysis of the satellite measurements by taking into account the contribution of the surface emissivity to the measured signal.

Retrieving the properties of ice-phase precipitation with multi-frequency radar measurements

NASA Astrophysics Data System (ADS)

Mace, G. G.; Gergely, M.; Mascio, J.

2017-12-01

The objective of most retrieval algorithms applied to remote sensing measurements is the microphysical properties that a model might predict such as condensed water content, particle number, or effective size. However, because ice crystals grow and aggregate into complex non spherical shapes, the microphysical properties of interest are very much dependent on the physical characteristics of the precipitation such as how mass and crystal area are distributed as a function of particle size. Such physical properties also have a strong influence on how microwave electromagnetic energy scatters from ice crystals causing significant ambiguity in retrieval algorithms. In fact, passive and active microwave remote sensing measurements are typically nearly as sensitive to the ice crystal physical properties as they are to the microphysical characteristics that are typically the aim of the retrieval algorithm. There has, however, been active development of multi frequency algorithms recently that attempt to ameliorate and even exploit this sensitivity. In this paper, we will review these approaches and present practical applications of retrieving ice crystal properties such as mass- and area dimensional relationships from single and dual frequency radar measurements of precipitating ice using data collected aboard ship in the Southern Ocean and from remote sensors in the Rocky Mountains of the Western U.S.

Limb Retrievals of TES solarband/IR data (and MCS solarband data)

NASA Astrophysics Data System (ADS)

Wolff, M. J.; Pankine, A.

2016-12-01

Vertical variations in aerosol distributions (and their microphysicalproperties) can have a dramatic impact on the state and evolution of theMartian atmosphere. This has been clearly delineated recent work usingretrieval products produced by the Mars Climate Sounder (MCS) teamfrom limb observations by the MCS IR bolometers. However, similarproducts for Thermal EmissionSpectrometer (TES) limb observationshave not been as widely disseminated. In addition, the solar bandchannels of both datasets have been essentially unanalyzed. Ouroverarching goal has been to fill these gaps in order to addressparticle size studies, as well as to generate products that can beused by the wider community. In our presentation we will include: 1) A summary of our limb radiative transfer algorithms and retrievalscheme; 2) The limitations imposed by "Smoothing Error" and by systematicradiometric error on retrievals in lower and upper atmosphere, respectively;3) vertical profiles of opacity and particle size associated with theevolution of the 2001 TES dust storm; and 4) the use of limbretrievals to estimate integrated-column optical depths (validatedagainst Mars Exploration Rover and TES emission phase functionmeasurements); and 5) the plans for an ongoing archive to be used forthe distribution of the derived profiles and associated retrievalmetadata. This work has been supported by NASA with a Mars Data AnalysisProgram award (grant NNX10AO23G).

Development of MODIS data-based algorithm for retrieving sea surface temperature in coastal waters.

PubMed

Wang, Jiao; Deng, Zhiqiang

2017-06-01

A new algorithm was developed for retrieving sea surface temperature (SST) in coastal waters using satellite remote sensing data from Moderate Resolution Imaging Spectroradiometer (MODIS) aboard Aqua platform. The new SST algorithm was trained using the Artificial Neural Network (ANN) method and tested using 8 years of remote sensing data from MODIS Aqua sensor and in situ sensing data from the US coastal waters in Louisiana, Texas, Florida, California, and New Jersey. The ANN algorithm could be utilized to map SST in both deep offshore and particularly shallow nearshore waters at the high spatial resolution of 1 km, greatly expanding the coverage of remote sensing-based SST data from offshore waters to nearshore waters. Applications of the ANN algorithm require only the remotely sensed reflectance values from the two MODIS Aqua thermal bands 31 and 32 as input data. Application results indicated that the ANN algorithm was able to explaining 82-90% variations in observed SST in US coastal waters. While the algorithm is generally applicable to the retrieval of SST, it works best for nearshore waters where important coastal resources are located and existing algorithms are either not applicable or do not work well, making the new ANN-based SST algorithm unique and particularly useful to coastal resource management.

Optimal estimation retrieval of aerosol microphysical properties from SAGE~II satellite observations in the volcanically unperturbed lower stratosphere

NASA Astrophysics Data System (ADS)

Wurl, D.; Grainger, R. G.; McDonald, A. J.; Deshler, T.

2010-05-01

Stratospheric aerosol particles under non-volcanic conditions are typically smaller than 0.1 μm. Due to fundamental limitations of the scattering theory in the Rayleigh limit, these tiny particles are hard to measure by satellite instruments. As a consequence, current estimates of global aerosol properties retrieved from spectral aerosol extinction measurements tend to be strongly biased. Aerosol surface area densities, for instance, are observed to be about 40% smaller than those derived from correlative in situ measurements (Deshler et al., 2003). An accurate knowledge of the global distribution of aerosol properties is, however, essential to better understand and quantify the role they play in atmospheric chemistry, dynamics, radiation and climate. To address this need a new retrieval algorithm was developed, which employs a nonlinear Optimal Estimation (OE) method to iteratively solve for the monomodal size distribution parameters which are statistically most consistent with both the satellite-measured multi-wavelength aerosol extinction data and a priori information. By thus combining spectral extinction measurements (at visible to near infrared wavelengths) with prior knowledge of aerosol properties at background level, even the smallest particles are taken into account which are practically invisible to optical remote sensing instruments. The performance of the OE retrieval algorithm was assessed based on synthetic spectral extinction data generated from both monomodal and small-mode-dominant bimodal sulphuric acid aerosol size distributions. For monomodal background aerosol, the new algorithm was shown to fairly accurately retrieve the particle sizes and associated integrated properties (surface area and volume densities), even in the presence of large extinction uncertainty. The associated retrieved uncertainties are a good estimate of the true errors. In the case of bimodal background aerosol, where the retrieved (monomodal) size distributions naturally differ from the correct bimodal values, the associated surface area (A) and volume densities (V) are, nevertheless, fairly accurately retrieved, except at values larger than 1.0 μm2 cm-3 (A) and 0.05 μm3 cm-3 (V), where they tend to underestimate the true bimodal values. Due to the limited information content in the SAGE II spectral extinction measurements this kind of forward model error cannot be avoided here. Nevertheless, the retrieved uncertainties are a good estimate of the true errors in the retrieved integrated properties, except where the surface area density exceeds the 1.0 μm2 cm-3 threshold. When applied to near-global SAGE II satellite extinction measured in 1999 the retrieved OE surface area and volume densities are observed to be larger by, respectively, 20-50% and 10-40% compared to those estimates obtained by the SAGE~II operational retrieval algorithm. An examination of the OE algorithm biases with in situ data indicates that the new OE aerosol property estimates tend to be more realistic than previous estimates obtained from remotely sensed data through other retrieval techniques. Based on the results of this study we therefore suggest that the new Optimal Estimation retrieval algorithm is able to contribute to an advancement in aerosol research by considerably improving current estimates of aerosol properties in the lower stratosphere under low aerosol loading conditions.

Numerical phase retrieval from beam intensity measurements in three planes

NASA Astrophysics Data System (ADS)

Bruel, Laurent

2003-05-01

A system and method have been developed at CEA to retrieve phase information from multiple intensity measurements along a laser beam. The device has been patented. Commonly used devices for beam measurement provide phase and intensity information separately or with a rather poor resolution whereas the MIROMA method provides both at the same time, allowing direct use of the results in numerical models. Usual phase retrieval algorithms use two intensity measurements, typically the image plane and the focal plane (Gerschberg-Saxton algorithm) related by a Fourier transform, or the image plane and a lightly defocus plane (D.L. Misell). The principal drawback of such iterative algorithms is their inability to provide unambiguous convergence in all situations. The algorithms can stagnate on bad solutions and the error between measured and calculated intensities remains unacceptable. If three planes rather than two are used, the data redundancy created confers to the method good convergence capability and noise immunity. It provides an excellent agreement between intensity determined from the retrieved phase data set in the image plane and intensity measurements in any diffraction plane. The method employed for MIROMA is inspired from GS algorithm, replacing Fourier transforms by a beam-propagating kernel with gradient search accelerating techniques and special care for phase branch cuts. A fast one dimensional algorithm provides an initial guess for the iterative algorithm. Applications of the algorithm on synthetic data find out the best reconstruction planes that have to be chosen. Robustness and sensibility are evaluated. Results on collimated and distorted laser beams are presented.

New approach to the retrieval of AOD and its uncertainty from MISR observations over dark water

NASA Astrophysics Data System (ADS)

Witek, Marcin L.; Garay, Michael J.; Diner, David J.; Bull, Michael A.; Seidel, Felix C.

2018-01-01

A new method for retrieving aerosol optical depth (AOD) and its uncertainty from Multi-angle Imaging SpectroRadiometer (MISR) observations over dark water is outlined. MISR's aerosol retrieval algorithm calculates cost functions between observed and pre-simulated radiances for a range of AODs (from 0.0 to 3.0) and a prescribed set of aerosol mixtures. The previous version 22 (V22) operational algorithm considered only the AOD that minimized the cost function for each aerosol mixture and then used a combination of these values to compute the final, best estimate AOD and associated uncertainty. The new approach considers the entire range of cost functions associated with each aerosol mixture. The uncertainty of the reported AOD depends on a combination of (a) the absolute values of the cost functions for each aerosol mixture, (b) the widths of the cost function distributions as a function of AOD, and (c) the spread of the cost function distributions among the ensemble of mixtures. A key benefit of the new approach is that, unlike the V22 algorithm, it does not rely on empirical thresholds imposed on the cost function to determine the success or failure of a particular mixture. Furthermore, a new aerosol retrieval confidence index (ARCI) is established that can be used to screen high-AOD retrieval blunders caused by cloud contamination or other factors. Requiring ARCI ≥ 0.15 as a condition for retrieval success is supported through statistical analysis and outperforms the thresholds used in the V22 algorithm. The described changes to the MISR dark water algorithm will become operational in the new MISR aerosol product (V23), planned for release in 2017.

New Approach to the Retrieval of AOD and its Uncertainty from MISR Observations Over Dark Water

NASA Astrophysics Data System (ADS)

Witek, M. L.; Garay, M. J.; Diner, D. J.; Bull, M. A.; Seidel, F.

2017-12-01

A new method for retrieving aerosol optical depth (AOD) and its uncertainty from Multi-angle Imaging SpectroRadiometer (MISR) observations over dark water is outlined. MISR's aerosol retrieval algorithm calculates cost functions between observed and pre-simulated radiances for a range of AODs (from 0.0 to 3.0) and a prescribed set of aerosol mixtures. The previous Version 22 (V22) operational algorithm considered only the AOD that minimized the cost function for each aerosol mixture, then used a combination of these values to compute the final, "best estimate" AOD and associated uncertainty. The new approach considers the entire range of cost functions associated with each aerosol mixture. The uncertainty of the reported AOD depends on a combination of a) the absolute values of the cost functions for each aerosol mixture, b) the widths of the cost function distributions as a function of AOD, and c) the spread of the cost function distributions among the ensemble of mixtures. A key benefit of the new approach is that, unlike the V22 algorithm, it does not rely on arbitrary thresholds imposed on the cost function to determine the success or failure of a particular mixture. Furthermore, a new Aerosol Retrieval Confidence Index (ARCI) is established that can be used to screen high-AOD retrieval blunders caused by cloud contamination or other factors. Requiring ARCI≥0.15 as a condition for retrieval success is supported through statistical analysis and outperforms the thresholds used in the V22 algorithm. The described changes to the MISR dark water algorithm will become operational in the new MISR aerosol product (V23), planned for release in 2017.

Application of randomly oriented spheroids for retrieval of dust particle parameters from multiwavelength lidar measurements

NASA Astrophysics Data System (ADS)

Veselovskii, I.; Dubovik, O.; Kolgotin, A.; Lapyonok, T.; di Girolamo, P.; Summa, D.; Whiteman, D. N.; Mishchenko, M.; Tanré, D.

2010-11-01

Multiwavelength (MW) Raman lidars have demonstrated their potential to profile particle parameters; however, until now, the physical models used in retrieval algorithms for processing MW lidar data have been predominantly based on the Mie theory. This approach is applicable to the modeling of light scattering by spherically symmetric particles only and does not adequately reproduce the scattering by generally nonspherical desert dust particles. Here we present an algorithm based on a model of randomly oriented spheroids for the inversion of multiwavelength lidar data. The aerosols are modeled as a mixture of two aerosol components: one composed only of spherical and the second composed of nonspherical particles. The nonspherical component is an ensemble of randomly oriented spheroids with size-independent shape distribution. This approach has been integrated into an algorithm retrieving aerosol properties from the observations with a Raman lidar based on a tripled Nd:YAG laser. Such a lidar provides three backscattering coefficients, two extinction coefficients, and the particle depolarization ratio at a single or multiple wavelengths. Simulations were performed for a bimodal particle size distribution typical of desert dust particles. The uncertainty of the retrieved particle surface, volume concentration, and effective radius for 10% measurement errors is estimated to be below 30%. We show that if the effect of particle nonsphericity is not accounted for, the errors in the retrieved aerosol parameters increase notably. The algorithm was tested with experimental data from a Saharan dust outbreak episode, measured with the BASIL multiwavelength Raman lidar in August 2007. The vertical profiles of particle parameters as well as the particle size distributions at different heights were retrieved. It was shown that the algorithm developed provided substantially reasonable results consistent with the available independent information about the observed aerosol event.

Subspace aware recovery of low rank and jointly sparse signals

PubMed Central

Biswas, Sampurna; Dasgupta, Soura; Mudumbai, Raghuraman; Jacob, Mathews

2017-01-01

We consider the recovery of a matrix X, which is simultaneously low rank and joint sparse, from few measurements of its columns using a two-step algorithm. Each column of X is measured using a combination of two measurement matrices; one which is the same for every column, while the the second measurement matrix varies from column to column. The recovery proceeds by first estimating the row subspace vectors from the measurements corresponding to the common matrix. The estimated row subspace vectors are then used to recover X from all the measurements using a convex program of joint sparsity minimization. Our main contribution is to provide sufficient conditions on the measurement matrices that guarantee the recovery of such a matrix using the above two-step algorithm. The results demonstrate quite significant savings in number of measurements when compared to the standard multiple measurement vector (MMV) scheme, which assumes same time invariant measurement pattern for all the time frames. We illustrate the impact of the sampling pattern on reconstruction quality using breath held cardiac cine MRI and cardiac perfusion MRI data, while the utility of the algorithm to accelerate the acquisition is demonstrated on MR parameter mapping. PMID:28630889