Simultaneous inversion of multiple land surface parameters from MODIS optical-thermal observations

NASA Astrophysics Data System (ADS)

Ma, Han; Liang, Shunlin; Xiao, Zhiqiang; Shi, Hanyu

2017-06-01

Land surface parameters from remote sensing observations are critical in monitoring and modeling of global climate change and biogeochemical cycles. Current methods for estimating land surface variables usually focus on individual parameters separately even from the same satellite observations, resulting in inconsistent products. Moreover, no efforts have been made to generate global products from integrated observations from the optical to Thermal InfraRed (TIR) spectrum. Particularly, Middle InfraRed (MIR) observations have received little attention due to the complexity of the radiometric signal, which contains both reflected and emitted radiation. In this paper, we propose a unified algorithm for simultaneously retrieving six land surface parameters - Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), land surface albedo, Land Surface Emissivity (LSE), Land Surface Temperature (LST), and Upwelling Longwave radiation (LWUP) by exploiting MODIS visible-to-TIR observations. We incorporate a unified physical radiative transfer model into a data assimilation framework. The MODIS visible-to-TIR time series datasets include the daily surface reflectance product and MIR-to-TIR surface radiance, which are atmospherically corrected from the MODIS data using the Moderate Resolution Transmittance program (MODTRAN, ver. 5.0). LAI was first estimated using a data assimilation method that combines MODIS daily reflectance data and a LAI phenology model, and then the LAI was input to the unified radiative transfer model to simulate spectral surface reflectance and surface emissivity for calculating surface broadband albedo and emissivity, and FAPAR. LST was estimated from the MIR-TIR surface radiance data and the simulated emissivity, using an iterative optimization procedure. Lastly, LWUP was estimated using the LST and surface emissivity. The retrieved six parameters were extensively validated across six representative sites with different biome types, and compared with MODIS, GLASS, and GlobAlbedo land surface products. The results demonstrate that the unified inversion algorithm can retrieve temporally complete and physically consistent land surface parameters, and provides more accurate estimates of surface albedo, LST, and LWUP than existing products, with R2 values of 0.93 and 0.62, RMSE of 0.029 and 0.037, and BIAS values of 0.016 and 0.012 for the retrieved and MODIS albedo products, respectively, compared with field albedo measurements; R2 values of 0.95 and 0.93, RMSE of 2.7 and 4.2 K, and BIAS values of -0.6 and -2.7 K for the retrieved and MODIS LST products, respectively, compared with field LST measurements; and R2 values of 0.93 and 0.94, RMSE of 18.2 and 22.8 W/m2, and BIAS values of -2.7 and -14.6 W/m2 for the retrieved and MODIS LWUP products, respectively, compared with field LWUP measurements.

Monitoring Surface Climate With its Emissivity Derived From Satellite Measurements

NASA Technical Reports Server (NTRS)

Zhou, Daniel K.; Larar, Allen M.; Liu, Xu

2012-01-01

Satellite thermal infrared (IR) spectral emissivity data have been shown to be significant for atmospheric research and monitoring the Earth fs environment. Long-term and large-scale observations needed for global monitoring and research can be supplied by satellite-based remote sensing. Presented here is the global surface IR emissivity data retrieved from the last 5 years of Infrared Atmospheric Sounding Interferometer (IASI) measurements observed from the MetOp-A satellite. Monthly mean surface properties (i.e., skin temperature T(sub s) and emissivity spectra epsilon(sub v) with a spatial resolution of 0.5x0.5-degrees latitude-longitude are produced to monitor seasonal and inter-annual variations. We demonstrate that surface epsilon(sub v) and T(sub s) retrieved with IASI measurements can be used to assist in monitoring surface weather and surface climate change. Surface epsilon(sub v) together with T(sub s) from current and future operational satellites can be utilized as a means of long-term and large-scale monitoring of Earth 's surface weather environment and associated changes.

Estimation of Multiple Parameters over Vegetated Surfaces by Integrating Optical-Thermal Remote Sensing Observations

NASA Astrophysics Data System (ADS)

Ma, H.

2016-12-01

Land surface parameters from remote sensing observations are critical in monitoring and modeling of global climate change and biogeochemical cycles. Current methods for estimating land surface parameters are generally parameter-specific algorithms and are based on instantaneous physical models, which result in spatial, temporal and physical inconsistencies in current global products. Besides, optical and Thermal Infrared (TIR) remote sensing observations are usually separated to use based on different models , and the Middle InfraRed (MIR) observations have received little attention due to the complexity of the radiometric signal that mixes both reflected and emitted fluxes. In this paper, we proposed a unified algorithm for simultaneously retrieving a total of seven land surface parameters, including Leaf Area Index (LAI), Fraction of Absorbed Photosynthetically Active Radiation (FAPAR), land surface albedo, Land Surface Temperature (LST), surface emissivity, downward and upward longwave radiation, by exploiting remote sensing observations from visible to TIR domain based on a common physical Radiative Transfer (RT) model and a data assimilation framework. The coupled PROSPECT-VISIR and 4SAIL RT model were used for canopy reflectance modeling. At first, LAI was estimated using a data assimilation method that combines MODIS daily reflectance observation and a phenology model. The estimated LAI values were then input into the RT model to simulate surface spectral emissivity and surface albedo. Besides, the background albedo and the transmittance of solar radiation, and the canopy albedo were also calculated to produce FAPAR. Once the spectral emissivity of seven MODIS MIR to TIR bands were retrieved, LST can be estimated from the atmospheric corrected surface radiance by exploiting an optimization method. At last, the upward longwave radiation were estimated using the retrieved LST, broadband emissivity (converted from spectral emissivity) and the downward longwave radiation (modeled by MODTRAN). These seven parameters were validated over several representative sites with different biome type, and compared with MODIS and GLASS product. Results showed that this unified inversion algorithm can retrieve temporally complete and physical consistent land surface parameters with high accuracy.

Land Surface Modeling and Data Assimilation to Support Physical Precipitation Retrievals for GPM

NASA Technical Reports Server (NTRS)

Peters-Lidard, Christa D.; Tian. Yudong; Kumar, Sujay; Geiger, James; Choudhury, Bhaskar

2010-01-01

Objective: The objective of this proposal is to provide a routine land surface modeling and data assimilation capability for GPM in order to provide global land surface states that are necessary to support physical precipitation retrieval algorithms over land. It is well-known that surface emission, particularly over the range of frequencies to be included in GPM, is sensitive to land surface states, including soil properties, vegetation type and greenness, soil moisture, surface temperature, and snow cover, density, and grain size. Therefore, providing a robust capability to routinely provide these critical land states is essential to support GPM-era physical retrieval algorithms over land.

Innovative approach to retrieve land surface emissivity and land surface temperature in areas of highly dynamic emissivity changes by using thermal infrared data

NASA Astrophysics Data System (ADS)

Heinemann, S.

2015-12-01

The land surface temperature (LST) is an extremely significant parameter in order to understand the processes of energetic interactions between Earth's surface and atmosphere. This knowledge is significant for various environmental research questions, particularly with regard to the recent climate change. This study shows an innovative approach to retrieve land surface emissivity (LSE) and LST by using thermal infrared (TIR) data from satellite sensors, such as SEVIRI and AATSR. So far there are no methods to derive LSE/LST particularly in areas of highly dynamic emissivity changes. Therefore especially for regions with large surface temperature amplitude in the diurnal cycle such as bare and uneven soil surfaces but also for regions with seasonal changes in vegetation cover including various surface areas such as grassland, mixed forests or agricultural land different methods were investigated to identify the most appropriate one. The LSE is retrieved by using the day/night Temperature-Independent Spectral Indices (TISI) method, and the Generalised Split-Window (GSW) method is used to retrieve the LST. Nevertheless different GSW algorithms show that equal LSEs lead to large LST differences. Additionally LSE is also measured using a NDVI-based threshold method (NDVITHM) to distinguish between soil, dense vegetation cover and pixel composed of soil and vegetation. The data used for this analysis were derived from MODIS TIR. The analysis is implemented with IDL and an intercomparison is performed to determine the most effective methods. To compensate temperature differences between derived and ground truth data appropriate correction terms by comparing derived LSE/LST data with ground-based measurements are developed. One way to calibrate LST retrievals is by comparing the canopy leaf temperature of conifers derived from TIR data with the surrounding air temperature (e.g. from synoptic stations). Prospectively, the derived LSE/LST data become validated with near infrared data obtained from an UVA with a TIR camera (TIRC) onboard, and also compared with ground-based measurements. This study aims to generate an appropriate method by integrating developed correction terms to eventually obtain a high correlation between all, LSE/LST, TIRC and ground truth data.

Discrepancy Between ASTER- and MODIS- Derived Land Surface Temperatures: Terrain Effects

PubMed Central

Liu, Yuanbo; Noumi, Yousuke; Yamaguchi, Yasushi

2009-01-01

The MODerate resolution Imaging Spectroradiometer (MODIS) and the Advanced Spaceborne Thermal Emission Reflection Radiometer (ASTER) are onboard the same satellite platform NASA TERRA. Both MODIS and ASTER offer routine retrieval of land surface temperatures (LSTs), and the ASTER- and MODIS-retrieved LST products have been used worldwide. Because a large fraction of the earth surface consists of mountainous areas, variations in elevation, terrain slope and aspect angles can cause biases in the retrieved LSTs. However, terrain-induced effects are generally neglected in most satellite retrievals, which may generate discrepancy between ASTER and MODIS LSTs. In this paper, we reported the terrain effects on the LST discrepancy with a case examination over a relief area at the Loess Plateau of China. Results showed that the terrain-induced effects were not major, but nevertheless important for the total LST discrepancy. A large local slope did not necessarily lead to a large LST discrepancy. The angle of emitted radiance was more important than the angle of local slope in generating the LST discrepancy. Specifically, the conventional terrain correction may be unsuitable for densely vegetated areas. The distribution of ASTER-to-MODIS emissivity suggested that the terrain correction was included in the generalized split window (GSW) based approach used to rectify MODIS LSTs. Further study should include the classification-induced uncertainty in emissivity for reliable use of satellite-retrieved LSTs over relief areas. PMID:22399955

How Well Can Infrared Sounders Observe the Atmosphere and Surface Through Clouds?

NASA Technical Reports Server (NTRS)

Zhou, Daniel K.; Larar, Allen M.; Liu, Xu; Smith, William L.; Strow, L. Larrabee; Yang, Ping

2010-01-01

Infrared sounders, such as the Atmospheric Infrared Sounder (AIRS), the Infrared Atmospheric Sounding Interferometer (IASI), and the Cross-track Infrared sounder (CrIS), have a cloud-impenetrable disadvantage in observing the atmosphere and surface under opaque cloudy conditions. However, recent studies indicate that hyperspectral, infrared sounders have the ability to detect cloud effective-optical and microphysical properties and to penetrate optically thin clouds in observing the atmosphere and surface to a certain degree. We have developed a retrieval scheme dealing with atmospheric conditions with cloud presence. This scheme can be used to analyze the retrieval accuracy of atmospheric and surface parameters under clear and cloudy conditions. In this paper, we present the surface emissivity results derived from IASI global measurements under both clear and cloudy conditions. The accuracy of surface emissivity derived under cloudy conditions is statistically estimated in comparison with those derived under clear sky conditions. The retrieval error caused by the clouds is shown as a function of cloud optical depth, which helps us to understand how well infrared sounders can observe the atmosphere and surface through clouds.

The effects of cloud inhomogeneities upon radiative fluxes, and the supply of a cloud truth validation dataset

NASA Technical Reports Server (NTRS)

Welch, Ronald M.

1993-01-01

A series of cloud and sea ice retrieval algorithms are being developed in support of the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Science Team objectives. These retrievals include the following: cloud fractional area, cloud optical thickness, cloud phase (water or ice), cloud particle effective radius, cloud top heights, cloud base height, cloud top temperature, cloud emissivity, cloud 3-D structure, cloud field scales of organization, sea ice fractional area, sea ice temperature, sea ice albedo, and sea surface temperature. Due to the problems of accurately retrieving cloud properties over bright surfaces, an advanced cloud classification method was developed which is based upon spectral and textural features and artificial intelligence classifiers.

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.

Implementation of Cloud Retrievals for Tropospheric Emission Spectrometer (TES) Atmospheric Retrievals: Part 1. Description and Characterization of Errors on Trace Gas Retrievals

NASA Technical Reports Server (NTRS)

Kulawik, Susan S.; Worden, John; Eldering, Annmarie; Bowman, Kevin; Gunson, Michael; Osterman, Gregory B.; Zhang, Lin; Clough, Shepard A.; Shephard, Mark W.; Beer, Reinhard

2006-01-01

We develop an approach to estimate and characterize trace gas retrievals in the presence of clouds in high spectral measurements of upwelling radiance in the infrared spectral region (650-2260/cm). The radiance contribution of clouds is parameterized in terms of a set of frequency-dependent nonscattering optical depths and a cloud height. These cloud parameters are retrieved jointly with surface temperature, emissivity, atmospheric temperature, and trace gases such as ozone from spectral data. We demonstrate the application of this approach using data from the Tropospheric Emission Spectrometer (TES) and test data simulated with a scattering radiative transfer model. We show the value of this approach in that it results in accurate estimates of errors for trace gas retrievals, and the retrieved values improve over the initial guess for a wide range of cloud conditions. Comparisons are made between TES retrievals of ozone, temperature, and water to model fields from the Global Modeling and Assimilation Office (GMAO), temperature retrievals from the Atmospheric Infrared Sounder (AIRS), tropospheric ozone columns from the Goddard Earth Observing System (GEOS) GEOS-Chem, and ozone retrievals from the Total Ozone Mapping Spectrometer (TOMS). In each of these cases, this cloud retrieval approach does not introduce observable biases into TES retrievals.

On the relationship between land surface infrared emissivity and soil moisture

NASA Astrophysics Data System (ADS)

Zhou, Daniel K.; Larar, Allen M.; Liu, Xu

2018-01-01

The relationship between surface infrared (IR) emissivity and soil moisture content has been investigated based on satellite measurements. Surface soil moisture content can be estimated by IR remote sensing, namely using the surface parameters of IR emissivity, temperature, vegetation coverage, and soil texture. It is possible to separate IR emissivity from other parameters affecting surface soil moisture estimation. The main objective of this paper is to examine the correlation between land surface IR emissivity and soil moisture. To this end, we have developed a simple yet effective scheme to estimate volumetric soil moisture (VSM) using IR land surface emissivity retrieved from satellite IR spectral radiance measurements, assuming those other parameters impacting the radiative transfer (e.g., temperature, vegetation coverage, and surface roughness) are known for an acceptable time and space reference location. This scheme is applied to a decade of global IR emissivity data retrieved from MetOp-A infrared atmospheric sounding interferometer measurements. The VSM estimated from these IR emissivity data (denoted as IR-VSM) is used to demonstrate its measurement-to-measurement variations. Representative 0.25-deg spatially-gridded monthly-mean IR-VSM global datasets are then assembled to compare with those routinely provided from satellite microwave (MW) multisensor measurements (denoted as MW-VSM), demonstrating VSM spatial variations as well as seasonal-cycles and interannual variability. Initial positive agreement is shown to exist between IR- and MW-VSM (i.e., R2 = 0.85). IR land surface emissivity contains surface water content information. So, when IR measurements are used to estimate soil moisture, this correlation produces results that correspond with those customarily achievable from MW measurements. A decade-long monthly-gridded emissivity atlas is used to estimate IR-VSM, to demonstrate its seasonal-cycle and interannual variation, which is spatially coherent and consistent with that from MW measurements, and, moreover, to achieve our objective of investigating the relationship between land surface IR emissivity and soil moisture.

A Consistent Treatment of Microwave Emissivity and Radar Backscatter for Retrieval of Precipitation over Water Surfaces

NASA Technical Reports Server (NTRS)

Munchak, S. Joseph; Meneghini, Robert; Grecu, Mircea; Olson, William S.

2016-01-01

The Global Precipitation Measurement satellite's Microwave Imager (GMI) and Dual-frequency Precipitation Radar (DPR) are designed to provide the most accurate instantaneous precipitation estimates currently available from space. The GPM Combined Algorithm (CORRA) plays a key role in this process by retrieving precipitation profiles that are consistent with GMI and DPR measurements; therefore, it is desirable that the forward models in CORRA use the same geophysical input parameters. This study explores the feasibility of using internally consistent emissivity and surface backscatter cross-sectional (sigma(sub 0)) models for water surfaces in CORRA. An empirical model for DPR Ku and Ka sigma(sub 0) as a function of 10m wind speed and incidence angle is derived from GMI-only wind retrievals under clear-sky conditions. This allows for the sigma(sub 0) measurements, which are also influenced by path-integrated attenuation (PIA) from precipitation, to be used as input to CORRA and for wind speed to be retrieved as output. Comparisons to buoy data give a wind rmse of 3.7 m/s for Ku+GMI and 3.2 m/s for Ku+Ka+GMI retrievals under precipitation (compared to 1.3 m/s for clear-sky GMI-only), and there is a reduction in bias from GANAL background data (-10%) to the Ku+GMI (-3%) and Ku+Ka+GMI (-5%) retrievals. Ku+GMI retrievals of precipitation increase slightly in light (less than 1 mm/h) and decrease in moderate to heavy precipitation (greater than 1 mm/h). The Ku+Ka+GMI retrievals, being additionally constrained by the Ka reflectivity, increase only slightly in moderate and heavy precipitation at low wind speeds (less than 5 m/s) relative to retrievals using the surface reference estimate of PIA as input.

Evaluation of Space-Based Constraints on Global Nitrogen Oxide Emissions with Regional Aircraft Measurements over and Downwind of Eastern North America

NASA Technical Reports Server (NTRS)

Martin, Randall V.; Sioris, Christopher E.; Chance, Kelly; Ryerson, Thomas B.; Flocke, Frank M.; Bertram, Timothy H.; Wooldridge, Paul J.; Cohen, Ronald C.; Neuman, J. Andy; Swanson, Aaron

2006-01-01

We retrieve tropospheric nitrogen dioxide (NO 2) columns for May 2004 to April 2005 from the SCIAMACHY satellite instrument to derive top-down emissions of nitrogen oxides (NO(x) = NO + NO2) via inverse modeling with a global chemical transport model (GEOS-Chem). Simulated NO 2 vertical profiles used in the retrieval are evaluated with airborne measurements over and downwind of North America (ICARTT); a northern midlatitude lightning source of 1.6 Tg N/yr minimizes bias in the retrieval. Retrieved NO2 columns are validated (r2 = 0.60, slope = 0.82) with coincident airborne in situ measurements. The top-down emissions are combined with a priori information from a bottom-up emission inventory with error weighting to achieve an improved a posteriori estimate of the global distribution of surface NOx emissions. Our a posteriori NOx emission inventory for land surface NOx emissions (46.1 Tg N/yr) is 22% larger than the GEIA-based a priori bottom-up inventory for 1998, a difference that reflects rising anthropogenic emissions, especially from East Asia A posteriori NOx emissions for East Asia (9.8 Tg N/yr) exceed those from other continents. The a posteriori inventory improves the GEOS-Chem simulation of NOx, peroxyacetylnitrate, and nitric acid with respect to airborne in situ measurements over and downwind of New York City. The a posteriori is 7% larger than the EDGAR 3.2FT2000 global inventory, 3% larger than the NEI99 inventory for the United States, and 68% larger than a regional inventory for 2000 for eastern Asia. SCIAMACHY NO2 columns over the North Atlantic show a weak plume from lightning NO(x).

Intercomparison of Satellite Dust Retrieval Products over the West African Sahara During the Fennec Campaign in June 2011

NASA Technical Reports Server (NTRS)

Banks, J.R.; Brindley, H. E.; Flamant, C.; Garay, M. J.; Hsu, N. C.; Kalashnikova, O. V.; Klueser, L.; Sayer, A. M.

2013-01-01

Dust retrievals over the Sahara Desert during June 2011 from the IASI, MISR, MODIS, and SEVIRI satellite instruments are compared against each other in order to understand the strengths and weaknesses of each retrieval approach. Particular attention is paid to the effects of meteorological conditions, land surface properties, and the magnitude of the dust loading. The period of study corresponds to the time of the first Fennec intensive measurement campaign, which provides new ground-based and aircraft measurements of the dust characteristics and loading. Validation using ground-based AERONET sunphotometer data indicate that of the satellite instruments, SEVIRI is most able to retrieve dust during optically thick dust events, whereas IASI and MODIS perform better at low dust loadings. This may significantly affect observations of dust emission and the mean dust climatology. MISR and MODIS are least sensitive to variations in meteorological conditions, while SEVIRI tends to overestimate the aerosol optical depth (AOD) under moist conditions (with a bias against AERONET of 0.31), especially at low dust loadings where the AOD<1. Further comparisons are made with airborne LIDAR measurements taken during the Fennec campaign, which provide further evidence for the inferences made from the AERONET comparisons. The effect of surface properties on the retrievals is also investigated. Over elevated surfaces IASI retrieves AODs which are most consistent with AERONET observations, while the AODs retrieved by MODIS tend to be biased low. In contrast, over the least emissive surfaces IASI significantly underestimates the AOD (with a bias of -0.41), while MISR and SEVIRI show closest agreement.

An Algorithm for Retrieving Land Surface Temperatures Using VIIRS Data in Combination with Multi-Sensors

PubMed Central

Xia, Lang; Mao, Kebiao; Ma, Ying; Zhao, Fen; Jiang, Lipeng; Shen, Xinyi; Qin, Zhihao

2014-01-01

A practical algorithm was proposed to retrieve land surface temperature (LST) from Visible Infrared Imager Radiometer Suite (VIIRS) data in mid-latitude regions. The key parameter transmittance is generally computed from water vapor content, while water vapor channel is absent in VIIRS data. In order to overcome this shortcoming, the water vapor content was obtained from Moderate Resolution Imaging Spectroradiometer (MODIS) data in this study. The analyses on the estimation errors of vapor content and emissivity indicate that when the water vapor errors are within the range of ±0.5 g/cm2, the mean retrieval error of the present algorithm is 0.634 K; while the land surface emissivity errors range from −0.005 to +0.005, the mean retrieval error is less than 1.0 K. Validation with the standard atmospheric simulation shows the average LST retrieval error for the twenty-three land types is 0.734 K, with a standard deviation value of 0.575 K. The comparison between the ground station LST data indicates the retrieval mean accuracy is −0.395 K, and the standard deviation value is 1.490 K in the regions with vegetation and water cover. Besides, the retrieval results of the test data have also been compared with the results measured by the National Oceanic and Atmospheric Administration (NOAA) VIIRS LST products, and the results indicate that 82.63% of the difference values are within the range of −1 to 1 K, and 17.37% of the difference values are within the range of ±2 to ±1 K. In a conclusion, with the advantages of multi-sensors taken fully exploited, more accurate results can be achieved in the retrieval of land surface temperature. PMID:25397919

Global Precipitation Measurement, Validation, and Applications Integrated Hydrologic Validation to Improve Physical Precipitation Retrievals for GPM

NASA Technical Reports Server (NTRS)

Peters-Lidar, Christa D.; Tian, Yudong; Kenneth, Tian; Harrison, Kenneth; Kumar, Sujay

2011-01-01

Land surface modeling and data assimilation can provide dynamic land surface state variables necessary to support physical precipitation retrieval algorithms over land. It is well-known that surface emission, particularly over the range of frequencies to be included in the Global Precipitation Measurement Mission (GPM), is sensitive to land surface states, including soil properties, vegetation type and greenness, soil moisture, surface temperature, and snow cover, density, and grain size. In order to investigate the robustness of both the land surface model states and the microwave emissivity and forward radiative transfer models, we have undertaken a multi-site investigation as part of the NASA Precipitation Measurement Missions (PMM) Land Surface Characterization Working Group. Specifically, we will demonstrate the performance of the Land Information System (LIS; http://lis.gsfc.nasa.gov; Peters-Lidard et aI., 2007; Kumar et al., 2006) coupled to the Joint Center for Satellite Data Assimilation (JCSDA's) Community Radiative Transfer Model (CRTM; Weng, 2007; van Deist, 2009). The land surface is characterized by complex physical/chemical constituents and creates temporally and spatially heterogeneous surface properties in response to microwave radiation scattering. The uncertainties in surface microwave emission (both surface radiative temperature and emissivity) and very low polarization ratio are linked to difficulties in rainfall detection using low-frequency passive microwave sensors (e.g.,Kummerow et al. 2001). Therefore, addressing these issues is of utmost importance for the GPM mission. There are many approaches to parameterizing land surface emission and radiative transfer, some of which have been customized for snow (e.g., the Helsinki University of Technology or HUT radiative transfer model;) and soil moisture (e.g., the Land Surface Microwave Emission Model or LSMEM).

Experiment of Rain Retrieval over Land Using Surface Emissivity Map Derived from TRMM TMI and JRA25

NASA Astrophysics Data System (ADS)

Furuzawa, Fumie; Masunaga, Hirohiko; Nakamura, Kenji

2010-05-01

We are developing a data-set of global land surface emissivity calculated from TRMM TMI brightness temperature (TB) and atmospheric profile data of Japanese 25-year Reanalysis Project (JRA-25) for the region identified as no-rain by TRMM PR, assuming zero cloud liquid water beyond 0-C level. For the evaluation, some characteristics of global monthly emissivity maps, for example, dependency of emissivity on each TMI frequency or each local time or seasonal/annual variation are checked. Moreover, these data are classified based on JRA25 land type or soilwetness and compared. Histogram of polarization difference of emissivity is similar to that of TB and mostly reflects the variability of land type or soil wetness, while histogram of vertical emissivity show a small difference. Next, by interpolating this instantaneous dataset with Gaussian function weighting, we derive an emissivity over neighboring rainy region and assess the interpolated emissivity by running radiative transfer model using PR rain profile and comparing with observed TB. Preliminary rain retrieval from the emissivities for some frequencies and TBs is evaluated based on PR rain profile and TMI rain rate. Moreover, another method is tested to estimate surface temperature from two emissivities, based on their statistical relation for each land type. We will show the results for vertical and horizontal emissivities of each frequency.

Retrieving Land Surface Temperature and Emissivity from Multispectral and Hyperspectral Thermal Infrared Instruments

NASA Astrophysics Data System (ADS)

Hook, Simon; Hulley, Glynn; Nicholson, Kerry

2017-04-01

Land Surface Temperature and Emissivity (LST&E) data are critical variables for studying a variety of Earth surface processes and surface-atmosphere interactions such as evapotranspiration, surface energy balance and water vapor retrievals. LST&E have been identified as an important Earth System Data Record (ESDR) by NASA and many other international organizations Accurate knowledge of the LST&E is a key requirement for many energy balance models to estimate important surface biophysical variables such as evapotranspiration and plant-available soil moisture. LST&E products are currently generated from sensors in low earth orbit (LEO) such as the NASA Moderate Resolution Imaging Spectroradiometer (MODIS) instruments on the Terra and Aqua satellites as well as from sensors in geostationary Earth orbit (GEO) such as the Geostationary Operational Environmental Satellites (GOES) and airborne sensors such as the Hyperspectral Thermal Emission Spectrometer (HyTES). LST&E products are generated with varying accuracies depending on the input data, including ancillary data such as atmospheric water vapor, as well as algorithmic approaches. NASA has identified the need to develop long-term, consistent, and calibrated data and products that are valid across multiple missions and satellite sensors. We will discuss the different approaches that can be used to retrieve surface temperature and emissivity from multispectral and hyperspectral thermal infrared sensors using examples from a variety of different sensors such as those mentioned, and planned new sensors like the ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) and the Hyperspectral Infrared Imager (HyspIRI). We will also discuss a project underway at NASA to develop a single unified product from some the individual sensor products and assess the errors associated with the product.

Advancing the retrievals of surface emissivity by modelling the spatial distribution of temperature in the thermal hyperspectral scene

NASA Astrophysics Data System (ADS)

Shimoni, M.; Haelterman, R.; Lodewyckx, P.

2016-05-01

Land Surface Temperature (LST) and Land Surface Emissivity (LSE) are commonly retrieved from thermal hyperspectral imaging. However, their retrieval is not a straightforward procedure because the mathematical problem is ill-posed. This procedure becomes more challenging in an urban area where the spatial distribution of temperature varies substantially in space and time. For assessing the influence of several spatial variances on the deviation of the temperature in the scene, a statistical model is created. The model was tested using several images from various times in the day and was validated using in-situ measurements. The results highlight the importance of the geometry of the scene and its setting relative to the position of the sun during day time. It also shows that when the position of the sun is in zenith, the main contribution to the thermal distribution in the scene is the thermal capacity of the landcover materials. In this paper we propose a new Temperature and Emissivity Separation (TES) method which integrates 3D surface and landcover information from LIDAR and VNIR hyperspectral imaging data in an attempt to improve the TES procedure for a thermal hyperspectral scene. The experimental results prove the high accuracy of the proposed method in comparison to another conventional TES model.

Retrieving Single Scattering Albedos and Temperatures from CRISM Hyperspectral Data Using Neural Networks

NASA Astrophysics Data System (ADS)

He, L.; Arvidson, R. E.; O'Sullivan, J. A.

2018-04-01

We use a neural network (NN) approach to simultaneously retrieve surface single scattering albedos and temperature maps for CRISM data from 1.40 to 3.85 µm. It approximates the inverse of DISORT which simulates solar and emission radiative streams.

A Unified and Coherent Land Surface Emissivity Earth System Data Record

NASA Astrophysics Data System (ADS)

Knuteson, R. O.; Borbas, E. E.; Hulley, G. C.; Hook, S. J.; Anderson, M. C.; Pinker, R. T.; Hain, C.; Guillevic, P. C.

2014-12-01

Land Surface Temperature and Emissivity (LST&E) data are essential for a wide variety of studies from calculating the evapo-transpiration of plant canopies to retrieving atmospheric water vapor. LST&E products are generated from data acquired by sensors in low Earth orbit (LEO) and by sensors in geostationary Earth orbit (GEO). Although these products represent the same measure, they are produced at different spatial, spectral and temporal resolutions using different algorithms. The different approaches used to retrieve the temperatures and emissivities result in discrepancies and inconsistencies between the different products. NASA has identified a major need to develop long-term, consistent, and calibrated data and products that are valid across multiple missions and satellite sensors. This poster will introduce the land surface emissivity product of the NASA MEASUREs project called A Unified and Coherent Land Surface Temperature and Emissivity (LST&E) Earth System Data Record (ESDR). To develop a unified high spectral resolution emissivity database, the MODIS baseline-fit emissivity database (MODBF) produced at the University of Wisconsin-Madison and the ASTER Global Emissivity Database (ASTER GED) produced at JPL will be merged. The unified Emissivity ESDR will be produced globally at 5km in mean monthly time-steps and for 12 bands from 3.6-14.3 micron and extended to 417 bands using a PC regression approach. The poster will introduce this data product. LST&E is a critical ESDR for a wide variety of studies in particular ecosystem and climate modeling.

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.

[Study of the microwave emissivity characteristics over different land cover types].

PubMed

Zhang, Yong-Pan; Jiang, Ling-Mei; Qiu, Yu-Bao; Wu, Sheng-Li; Shi, Jian-Cheng; Zhang, Li-Xin

2010-06-01

The microwave emissivity over land is very important for describing the characteristics of the lands, and it is also a key factor for retrieving the parameters of land and atmosphere. Different land covers have their emission behavior as a function of structure, water content, and surface roughness. In the present study the global land surface emissivities were calculated using six month (June, 2003-August, 2003, Dec, 2003-Feb, 2004) AMSR-E L2A brightness temperature, MODIS land surface temperature and the layered atmosphere temperature, and humidity and pressure profiles data retrieved from MODIS/Aqua under clear sky conditions. With the information of IGBP land cover types, "pure" pixels were used, which are defined when the fraction cover of each land type is larger than 85%. Then, the emissivity of sixteen land covers at different frequencies, polarization and their seasonal variation were analyzed respectively. The results show that the emissivity of vegetation including forests, grasslands and croplands is higher than that over bare soil, and the polarization difference of vegetation is smaller than that of bare soil. In summer, the emissivity of vegetation is relatively stable because it is in bloom, therefore the authors can use it as its emissivity in our microwave emissivity database over different land cover types. Furthermore, snow cover can heavily impact the change in land cover emissivity, especially in winter.

Satellite-based emission constraint for nitrogen oxides: Capability and uncertainty

NASA Astrophysics Data System (ADS)

Lin, J.; McElroy, M. B.; Boersma, F.; Nielsen, C.; Zhao, Y.; Lei, Y.; Liu, Y.; Zhang, Q.; Liu, Z.; Liu, H.; Mao, J.; Zhuang, G.; Roozendael, M.; Martin, R.; Wang, P.; Spurr, R. J.; Sneep, M.; Stammes, P.; Clemer, K.; Irie, H.

2013-12-01

Vertical column densities (VCDs) of tropospheric nitrogen dioxide (NO2) retrieved from satellite remote sensing have been employed widely to constrain emissions of nitrogen oxides (NOx). A major strength of satellite-based emission constraint is analysis of emission trends and variability, while a crucial limitation is errors both in satellite NO2 data and in model simulations relating NOx emissions to NO2 columns. Through a series of studies, we have explored these aspects over China. We separate anthropogenic from natural sources of NOx by exploiting their different seasonality. We infer trends of NOx emissions in recent years and effects of a variety of socioeconomic events at different spatiotemporal scales including the general economic growth, global financial crisis, Chinese New Year, and Beijing Olympics. We further investigate the impact of growing NOx emissions on particulate matter (PM) pollution in China. As part of recent developments, we identify and correct errors in both satellite NO2 retrieval and model simulation that ultimately affect NOx emission constraint. We improve the treatments of aerosol optical effects, clouds and surface reflectance in the NO2 retrieval process, using as reference ground-based MAX-DOAS measurements to evaluate the improved retrieval results. We analyze the sensitivity of simulated NO2 to errors in the model representation of major meteorological and chemical processes with a subsequent correction of model bias. Future studies will implement these improvements to re-constrain NOx emissions.

GPM Pre-Launch Algorithm Development for Physically-Based Falling Snow Retrievals

NASA Technical Reports Server (NTRS)

Jackson, Gail Skofronick; Tokay, Ali; Kramer, Anne W.; Hudak, David

2008-01-01

In this work we compare and correlate the long time series (Nov.-March) neasurements of precipitation rate from the Parsivels and 2DVD to the passive (89, 150, 183+/-1, +/-3, +/-7 GHz) observations of NOAA's AMSU-B radiometer. There are approximately 5-8 AMSU-B overpass views of the CARE site a day. We separate the comparisons into categories of no precipitation, liquid rain and falling snow precipitation. Scatterplots between the Parsivel snowfall rates and AMSU-B brightness temperatures (TBs) did not show an exploitable relationship for retrievals. We further compared and contrasted brightness temperatures to other surface measurements such as temperature and relative humidity with equally unsatisfying results. We found that there are similar TBs (especially at 89 and 150 GHz) for cases with falling snow and for non-precipitating cases. The comparisons indicate that surface emissivity contributions to the satellite observed TB over land can add uncertainty in detecting and estimating falling snow. The newest results show that the cloud icc scattering signal in the AMSU-B data call be detected by computing clear air TBs based on CARE radiosonde data and a rough estimate of surface emissivity. That is the differences in computed TI3 and AMSU-B TB for precipitating and nonprecipitating cases are unique such that the precipitating versus lon-precipitating cases can be identified. These results require that the radiosonde releases are within an hour of the AMSU-B data and allow for three surface types: no snow on the ground, less than 5 cm snow on the ground, and greater than 5 cm on the ground (as given by ground station data). Forest fraction and measured emissivities were combined to calculate the surface emissivities. The above work and future work to incorporate knowledge about falling snow retrievals into the framework of the expected GPM Bayesian retrievals will be described during this presentation.

A Prototype Physical Database for Passive Microwave Retrievals of Precipitation over the US Southern Great Plains

NASA Technical Reports Server (NTRS)

Ringerud, S.; Kummerow, C. D.; Peters-Lidard, C. D.

2015-01-01

An accurate understanding of the instantaneous, dynamic land surface emissivity is necessary for a physically based, multi-channel passive microwave precipitation retrieval scheme over land. In an effort to assess the feasibility of the physical approach for land surfaces, a semi-empirical emissivity model is applied for calculation of the surface component in a test area of the US Southern Great Plains. A physical emissivity model, using land surface model data as input, is used to calculate emissivity at the 10GHz frequency, combining contributions from the underlying soil and vegetation layers, including the dielectric and roughness effects of each medium. An empirical technique is then applied, based upon a robust set of observed channel covariances, extending the emissivity calculations to all channels. For calculation of the hydrometeor contribution, reflectivity profiles from the Tropical Rainfall Measurement Mission Precipitation Radar (TRMM PR) are utilized along with coincident brightness temperatures (Tbs) from the TRMM Microwave Imager (TMI), and cloud-resolving model profiles. Ice profiles are modified to be consistent with the higher frequency microwave Tbs. Resulting modeled top of the atmosphere Tbs show correlations to observations of 0.9, biases of 1K or less, root-mean-square errors on the order of 5K, and improved agreement over the use of climatological emissivity values. The synthesis of these models and data sets leads to the creation of a simple prototype Tb database that includes both dynamic surface and atmospheric information physically consistent with the land surface model, emissivity model, and atmospheric information.

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.

Soil moisture retrieval by active/passive microwave remote sensing data

NASA Astrophysics Data System (ADS)

Wu, Shengli; Yang, Lijuan

2012-09-01

This study develops a new algorithm for estimating bare surface soil moisture using combined active / passive microwave remote sensing on the basis of TRMM (Tropical Rainfall Measuring Mission). Tropical Rainfall Measurement Mission was jointly launched by NASA and NASDA in 1997, whose main task was to observe the precipitation of the area in 40 ° N-40 ° S. It was equipped with active microwave radar sensors (PR) and passive sensor microwave imager (TMI). To accurately estimate bare surface soil moisture, precipitation radar (PR) and microwave imager (TMI) are simultaneously used for observation. According to the frequency and incident angle setting of PR and TMI, we first need to establish a database which includes a large range of surface conditions; and then we use Advanced Integral Equation Model (AIEM) to calculate the backscattering coefficient and emissivity. Meanwhile, under the accuracy of resolution, we use a simplified theoretical model (GO model) and the semi-empirical physical model (Qp Model) to redescribe the process of scattering and radiation. There are quite a lot of parameters effecting backscattering coefficient and emissivity, including soil moisture, surface root mean square height, correlation length, and the correlation function etc. Radar backscattering is strongly affected by the surface roughness, which includes the surface root mean square roughness height, surface correlation length and the correlation function we use. And emissivity is differently affected by the root mean square slope under different polarizations. In general, emissivity decreases with the root mean square slope increases in V polarization, and increases with the root mean square slope increases in H polarization. For the GO model, we found that the backscattering coefficient is only related to the root mean square slope and soil moisture when the incident angle is fixed. And for Qp Model, through the analysis, we found that there is a quite good relationship between Qpparameter and root mean square slope. So here, root mean square slope is a parameter that both models shared. Because of its big influence to backscattering and emissivity, we need to throw it out during the process of the combination of GO model and Qp model. The result we obtain from the combined model is the Fresnel reflection coefficient in the normal direction gama(0). It has a good relationship with the soil dielectric constant. In Dobson Model, there is a detailed description about Fresnel reflection coefficient and soil moisture. With the help of Dobson model and gama(0) that we have obtained, we can get the soil moisture that we want. The backscattering coefficient and emissivity data used in combined model is from TRMM/PR, TMI; with this data, we can obtain gama(0); further, we get the soil moisture by the relationship of the two parameters-- gama(0) and soil moisture. To validate the accuracy of the retrieval soil moisture, there is an experiment conducted in Tibet. The soil moisture data which is used to validate the retrieval algorithm is from GAME-Tibet IOP98 Soil Moisture and Temperature Measuring System (SMTMS). There are 9 observing sites in SMTMS to validate soil moisture. Meanwhile, we use the SMTMS soil moisture data obtained by Time Domain Reflectometer (TDR) to do the validation. And the result shows the comparison of retrieval and measured results is very good. Through the analysis, we can see that the retrieval and measured results in D66 is nearly close; and in MS3608, the measured result is a little higher than retrieval result; in MS3637, the retrieval result is a little higher than measured result. According to the analysis of the simulation results, we found that this combined active and passive approach to retrieve the soil moisture improves the retrieval accuracy.

Inverse modeling of pan-Arctic methane emissions at high spatial resolution: what can we learn from assimilating satellite retrievals and using different process-based wetland and lake biogeochemical models?

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

Tan, Zeli; Zhuang, Qianlai; Henze, Daven K.

Understanding methane emissions from the Arctic, a fast-warming carbon reservoir, is important for projecting future changes in the global methane cycle. Here we optimized methane emissions from north of 60° N (pan-Arctic) regions using a nested-grid high-resolution inverse model that assimilates both high-precision surface measurements and column-average SCanning Imaging Absorption spectroMeter for Atmospheric CHartogrphY (SCIAMACHY) satellite retrievals of methane mole fraction. For the first time, methane emissions from lakes were integrated into an atmospheric transport and inversion estimate, together with prior wetland emissions estimated with six biogeochemical models. In our estimates, in 2005, global methane emissions were in the range ofmore » 496.4–511.5 Tg yr −1, and pan-Arctic methane emissions were in the range of 11.9–28.5 Tg yr −1. Methane emissions from pan-Arctic wetlands and lakes were 5.5–14.2 and 2.4–14.2 Tg yr −1, respectively. Methane emissions from Siberian wetlands and lakes are the largest and also have the largest uncertainty. Our results indicate that the uncertainty introduced by different wetland models could be much larger than the uncertainty of each inversion. We also show that assimilating satellite retrievals can reduce the uncertainty of the nested-grid inversions. The significance of lake emissions cannot be identified across the pan-Arctic by high-resolution inversions, but it is possible to identify high lake emissions from some specific regions. In contrast to global inversions, high-resolution nested-grid inversions perform better in estimating near-surface methane concentrations.« less

Inverse modeling of pan-Arctic methane emissions at high spatial resolution: what can we learn from assimilating satellite retrievals and using different process-based wetland and lake biogeochemical models?

DOE PAGES

Tan, Zeli; Zhuang, Qianlai; Henze, Daven K.; ...

2016-10-12

Understanding methane emissions from the Arctic, a fast-warming carbon reservoir, is important for projecting future changes in the global methane cycle. Here we optimized methane emissions from north of 60° N (pan-Arctic) regions using a nested-grid high-resolution inverse model that assimilates both high-precision surface measurements and column-average SCanning Imaging Absorption spectroMeter for Atmospheric CHartogrphY (SCIAMACHY) satellite retrievals of methane mole fraction. For the first time, methane emissions from lakes were integrated into an atmospheric transport and inversion estimate, together with prior wetland emissions estimated with six biogeochemical models. In our estimates, in 2005, global methane emissions were in the range ofmore » 496.4–511.5 Tg yr −1, and pan-Arctic methane emissions were in the range of 11.9–28.5 Tg yr −1. Methane emissions from pan-Arctic wetlands and lakes were 5.5–14.2 and 2.4–14.2 Tg yr −1, respectively. Methane emissions from Siberian wetlands and lakes are the largest and also have the largest uncertainty. Our results indicate that the uncertainty introduced by different wetland models could be much larger than the uncertainty of each inversion. We also show that assimilating satellite retrievals can reduce the uncertainty of the nested-grid inversions. The significance of lake emissions cannot be identified across the pan-Arctic by high-resolution inversions, but it is possible to identify high lake emissions from some specific regions. In contrast to global inversions, high-resolution nested-grid inversions perform better in estimating near-surface methane concentrations.« less

GOME-2 Tropospheric Ozone Profile Retrievals from Joint UV/Visible Measurement

NASA Astrophysics Data System (ADS)

Liu, X.; Zoogman, P.; Chance, K.; Cai, Z.; Nowlan, C. R.; Huang, G.; Gonzalez Abad, G.

2016-12-01

It has been shown from sensitivity studies that adding visible measurements in the Chappuis ozone band to UV measurements in the Hartley/Huggins ozone bands can significantly enhance retrieval sensitivity to lower tropospheric ozone from backscattered solar radiances due to deeper photon penetration in the visible to the surface than in the ultraviolet. The first NASA EVI (Earth Venture Instrument) TEMPO (Tropospheric Emissions: Monitoring of Pollution) instrument is being developed to measure backscattered solar radiation in two channels ( 290-490 and 540-740 nm) and make atmospheric pollution measurements over North America from the Geostationary orbit. However, this retrieval enhancement has yet to be demonstrated from existing measurements due to the weak ozone absorption in the visible and strong interferences from surface reflectance and aerosols and the requirement of accurate radiometric calibration across different spectral channels. We present GOME-2 retrievals from joint UV/visible measurements using the SAO ozone profile retrieval algorithm, to directly explore the retrieval improvement in lower tropospheric ozone from additional visible measurements. To reduce the retrieval interference from surface reflectance, we add characterization of surface spectral reflectance in the visible based on combining EOFs (Empirical Orthogonal Functions) derived from ASTER and other surface reflectance spectra with MODIS BRDF climatology into the ozone profile algorithm. The impacts of various types of aerosols and surface BRDF on the retrievals will be investigated. In addition, we will also perform empirical radiometric calibration of the GOME-2 data based on radiative transfer simulations. We will evaluate the retrieval improvement of joint UV/visible retrieval over the UV retrieval based on fitting quality and validation against ozonesonde observations.

The Impact of Dielectric Constant Model and Surface Reference on Differences Between SMOS and Aquarius Sea Surface Salinity

NASA Technical Reports Server (NTRS)

Dinnat, E. P.; Boutin, J.; Yin, X.; LeVine, D. M.

2014-01-01

Two ongoing space missions share the scientific objective of mapping the global Sea Surface Salinity (SSS), yet their observations show significant discrepancies. ESA's Soil Moisture and Ocean Salinity (SMOS) and NASA's Aquarius use L-band (1.4 GHz) radiometers to measure emission from the sea surface and retrieve SSS. Significant differences in SSS retrieved by both sensors are observed, with SMOS SSS being generally lower than Aquarius SSS, except for very cold waters where SMOS SSS is the highest overall. Figure 1 is an example of the difference between the SSS retrieved by SMOS and Aquarius averaged over one month and 1 degree in longitude and latitude. Differences are mostly between -1 psu and +1 psu (psu, practical salinity unit), with a significant regional and latitudinal dependence. We investigate the impact of the vicarious calibration and retrieval algorithm used by both mission on these differences.

Atmospheric CH4 in the first decade of the 21st century: Inverse modeling analysis using SCIAMACHY satellite retrievals and NOAA surface measurements

NASA Astrophysics Data System (ADS)

Bergamaschi, P.; Houweling, S.; Segers, A.; Krol, M.; Frankenberg, C.; Scheepmaker, R. A.; Dlugokencky, E.; Wofsy, S. C.; Kort, E. A.; Sweeney, C.; Schuck, T.; Brenninkmeijer, C.; Chen, H.; Beck, V.; Gerbig, C.

2013-07-01

causes of renewed growth in the atmospheric CH4 burden since 2007 are still poorly understood and subject of intensive scientific discussion. We present a reanalysis of global CH4 emissions during the 2000s, based on the TM5-4DVAR inverse modeling system. The model is optimized using high-accuracy surface observations from NOAA ESRL's global air sampling network for 2000-2010 combined with retrievals of column-averaged CH4 mole fractions from SCIAMACHY onboard ENVISAT (starting 2003).Using climatological OH fields, derived global total emissions for 2007-2010 are 16-20 Tg CH4/yr higher compared to 2003-2005. Most of the inferred emission increase was located in the tropics (9-14 Tg CH4/yr) and mid-latitudes of the northern hemisphere (6-8 Tg CH4/yr), while no significant trend was derived for Arctic latitudes. The atmospheric increase can be attributed mainly to increased anthropogenic emissions, but the derived trend is significantly smaller than estimated in the EDGARv4.2 emission inventory. Superimposed on the increasing trend in anthropogenic CH4 emissions are significant inter-annual variations (IAV) of emissions from wetlands (up to ±10 Tg CH4/yr), and biomass burning (up to ±7 Tg CH4/yr). Sensitivity experiments, which investigated the impact of the SCIAMACHY observations (versus inversions using only surface observations), of the OH fields used, and of a priori emission inventories, resulted in differences in the detailed latitudinal attribution of CH4 emissions, but the IAV and trends aggregated over larger latitude bands were reasonably robust. All sensitivity experiments show similar performance against independent shipboard and airborne observations used for validation, except over Amazonia where satellite retrievals improved agreement with observations in the free troposphere.

Space-based retrieval of NO2 over biomass burning regions: quantifying and reducing uncertainties

NASA Astrophysics Data System (ADS)

Bousserez, N.

2014-10-01

The accuracy of space-based nitrogen dioxide (NO2) retrievals from solar backscatter radiances critically depends on a priori knowledge of the vertical profiles of NO2 and aerosol optical properties. This information is used to calculate an air mass factor (AMF), which accounts for atmospheric scattering and is used to convert the measured line-of-sight "slant" columns into vertical columns. In this study we investigate the impact of biomass burning emissions on the AMF in order to quantify NO2 retrieval errors in the Ozone Monitoring Instrument (OMI) products over these sources. Sensitivity analyses are conducted using the Linearized Discrete Ordinate Radiative Transfer (LIDORT) model. The NO2 and aerosol profiles are obtained from a 3-D chemistry-transport model (GEOS-Chem), which uses the Fire Locating and Monitoring of Burning Emissions (FLAMBE) daily biomass burning emission inventory. Aircraft in situ data collected during two field campaigns, the Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) and the Dust and Biomass-burning Experiment (DABEX), are used to evaluate the modeled aerosol optical properties and NO2 profiles over Canadian boreal fires and West African savanna fires, respectively. Over both domains, the effect of biomass burning emissions on the AMF through the modified NO2 shape factor can be as high as -60%. A sensitivity analysis also revealed that the effect of aerosol and shape factor perturbations on the AMF is very sensitive to surface reflectance and clouds. As an illustration, the aerosol correction can range from -20 to +100% for different surface reflectances, while the shape factor correction varies from -70 to -20%. Although previous studies have shown that in clear-sky conditions the effect of aerosols on the AMF was in part implicitly accounted for by the modified cloud parameters, here it is suggested that when clouds are present above a surface layer of scattering aerosols, an explicit aerosol correction would be beneficial to the NO2 retrieval. Finally, a new method that uses slant column information to correct for shape-factor-related AMF error over NOx emission sources is proposed, with possible application to near-real-time OMI retrievals.

Crop effect to soil moisture retrieval at different microwave frequencies

NASA Astrophysics Data System (ADS)

Zhang, Zhongjun; Luan, Jinzhe

2006-12-01

In soil moisture retrieval by microwave remote sensing technology, vegetation effect is important, due to its emission upward as well as masking the soil surface contribution. Because of good penetration characteristics through crop at low frequencies, L-band is often used, where crop is treated as a uniform layer, and 0 th-order Brightness Temperature model is used. Higher frequencies upper than L-band, the frequencies both on NASA AQUA AMSR-E and FY-3 to be launched next year in CHINA, may be more informative in SM retrieval. The multiple-scattering effects inside crop and that between crop layer and soil surface will be increasing when frequencies go higher from L-band. In this paper, a Matrix-Doubling model that account for multiple-scattering based on ray tracing technique is used to simulate the microwave emission of vegetated-surface at C- and X-band. The orientation and size of crop element such as leaves and cylinders are accounted for in crop layer, and AIEM is used for calculation of ground surface scattering. Simulation results from this model for corn and SGP99 experiment data are in good agreement. Since complicated theoretical model as used in this paper involves too many parameters, to make SM retrieval more directly, corresponding terms from the developed model are matched with 0 th-order,so as to derive effective single scattering albedo and vegetation opacity at C- and X-band.

NASA's MODIS/VIIRS Land Surface Temperature and Emissivity Products: Asssessment of Accuracy, Continuity and Science Uses

NASA Astrophysics Data System (ADS)

Hulley, G. C.; Malakar, N.; Islam, T.

2017-12-01

Land Surface Temperature and Emissivity (LST&E) are an important Earth System Data Record (ESDR) and Environmental Climate Variable (ECV) defined by NASA and GCOS respectively. LST&E data are key variables used in land cover/land use change studies, in surface energy balance and atmospheric water vapor retrieval models and retrievals, and in climate research. LST&E products are currently produced on a routine basis using data from the MODIS instruments on the NASA EOS platforms and by the VIIRS instrument on the Suomi-NPP platform that serves as a bridge between NASA EOS and the next-generation JPSS platforms. Two new NASA LST&E products for MODIS (MxD21) and VIIRS (VNP21) are being produced during 2017 using a new approach that addresses discrepancies in accuracy and consistency between the current suite of split-window based LST products. The new approach uses a Temperature Emissivity Separation (TES) algorithm, originally developed for the ASTER instrument, to physically retrieve both LST and spectral emissivity consistently for both sensors with high accuracy and well defined uncertainties. This study provides a rigorous assessment of accuracy of the MxD21/VNP21 products using temperature- and radiance-based validation strategies and demonstrates continuity between the products using collocated matchups over CONUS. We will further demonstrate potential science use of the new products with studies related to heat waves, monitoring snow melt dynamics, and land cover/land use change.

The Effects of Surface Properties and Albedo on Methane Retrievals with the Airborne Visible/Infrared Imaging Spectrometer Next Generation (AVIRIS-NG)

NASA Astrophysics Data System (ADS)

Ayasse, A.; Thorpe, A. K.; Roberts, D. A.

2017-12-01

Atmospheric methane has increased by a factor of 2.5 since the beginning of the industrial era in response to anthropogenic emissions (Ciais et al., 2013). Although it is less abundant than carbon dioxide it is 86 time more potent on a 20 year time scale (Myhre et al., 2013) and is therefore responsible for about 20% of the total global warming induced by anthropogenic greenhouse gasses (Kirschke et al., 2013). Given the importance of methane to global climate change, monitoring and measuring methane emissions using techniques such as remote sensing is of increasing interest. Recently the Airborne Visible-Infrared Imaging Spectrometer - Next Generation (AVIRIS-NG) has proven to be a valuable instrument for quantitative mapping of methane plumes (Frankenberg et al., 2016; Thorpe et al., 2016; Thompson et al., 2015). In this study, we applied the Iterative Maximum a Posterior Differential Optical Spectroscopy (IMAP-DOAS) methane retrieval algorithm to a synthetic image with variable methane concentrations, albedo, and land cover. This allowed for characterizing retrieval performance, including potential sensitivity to variable land cover, low albedo surfaces, and surfaces known to cause spurious signals. We conclude that albedo had little influence on the IMAP-DOAS results except at very low radiance levels. Water (without sun glint) was found to be the most challenging surface for methane retrievals while hydrocarbons and some green vegetation also caused error. Understanding the effect of surface properties on methane retrievals is important given the increased use of AVIRIS-NG to map gas plumes over diverse locations and methane sources. This analysis could be expanded to include additional gas species like carbon dioxide and to further investigate gas sensitivity of proposed instruments for dedicated gas mapping from airborne and spaceborne platforms.

Inter-Sensor Comparison of Microwave Land Surface Emissivity Products to Improve Precipitation Retrievals

NASA Astrophysics Data System (ADS)

Norouzi, H.; Temimi, M.; Turk, J.; Prigent, C.; Furuzawa, F.; Tian, Y.

2013-12-01

Microwave land surface emissivity acts as the background signal to estimate rain rate, cloud liquid water, and total precipitable water. Therefore, its accuracy can directly affect the uncertainty of such measurements. Over land, unlike over oceans, the microwave emissivity is relatively high and and varies significantly as surface conditions and land cover change. Lack of ground truth measurement of microwave emissivity especially on global scale has made the uncertainty analysis of this parameter very challenging. The present study investigates the consistency among the existing global land emissivity estimates from different microwave sensors. The products are determined from various sensors and frequencies ranging from 7 to 90 GHz. The selected emissivity products in this study are from the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) by NOAA - Cooperative remote Sensing and Science and Technology Center (CREST), the Special Sensor Microwave Imager (SSM/I) by The Centre National de la Recherche Scientifique (CNRS) in France, TRMM Microwave Imager (TMI) by Nagoya University, Japan, and WindSat by NASA Jet Propulsion Laboratory (JPL). The emissivity estimates are based on different algorithms and ancillary data sets. This work investigates the difference among these emissivity products from 2003 to 2008 dynamically and spectrally. The similarities and discrepancies of the retrievals are studied at different land cover types. The mean relative difference (MRD) and other statistical parameters are calculated temporally for all five years of the study. Some inherent discrepancies between the selected products can be attributed to the difference in geometry in terms of incident angle, spectral response, and the foot print size which can affect the estimations. The results reveal that in lower frequencies (=<19 GHz) ancillary data especially skin temperature data set is the major source of difference in emissivity retrievals, while in higher frequencies (>19 GHz) the residuals of atmospheric effect on the signal cause inconsistency among the products. The time series and correlation between emissivity maps were analyzed over different land classes to assess the consistency of emissivity variations with geophysical variable such as soil moisture, precipitation, and vegetation.

On the capability of IASI measurements to inform about CO surface emissions

NASA Astrophysics Data System (ADS)

Fortems-Cheiney, A.; Chevallier, F.; Pison, I.; Bousquet, P.; Carouge, C.; Clerbaux, C.; Coheur, P.-F.; George, M.; Hurtmans, D.; Szopa, S.

2009-03-01

Between July and November 2008, simultaneous observations were conducted by several orbiting instruments that monitor carbon monoxide in the atmosphere, among them the Infrared Atmospheric Sounding Instrument (IASI) and Measurements Of Pollution In The Troposphere (MOPITT). In this paper, the concentration retrievals at about 700 hPa from these two instruments are successively used in a variational Bayesian system to infer the global distribution of CO emissions. Our posterior estimate of CO emissions using IASI retrievals gives a total of 793 Tg for the considered period, which is 40% higher than the global budget calculated with the MOPITT data (566 Tg). Over six continental regions (Eurasian Boreal, South Asia, South East Asia, North American Boreal, Northern Africa and South American Temperate) and thanks to a better observation density, the theoretical uncertainty reduction obtained with the IASI retrievals is better or similar than with MOPITT. For the other continental regions, IASI constrains the emissions less than MOPITT because of lesser sensitivity in the lower troposphere. These first results indicate that IASI may play a major role in the quantification of the emissions of CO.

Performance evaluation of four directional emissivity analytical models with thermal SAIL model and airborne images.

PubMed

Ren, Huazhong; Liu, Rongyuan; Yan, Guangjian; Li, Zhao-Liang; Qin, Qiming; Liu, Qiang; Nerry, Françoise

2015-04-06

Land surface emissivity is a crucial parameter in the surface status monitoring. This study aims at the evaluation of four directional emissivity models, including two bi-directional reflectance distribution function (BRDF) models and two gap-frequency-based models. Results showed that the kernel-driven BRDF model could well represent directional emissivity with an error less than 0.002, and was consequently used to retrieve emissivity with an accuracy of about 0.012 from an airborne multi-angular thermal infrared data set. Furthermore, we updated the cavity effect factor relating to multiple scattering inside canopy, which improved the performance of the gap-frequency-based models.

Leaf Level Chlorophyll Fluorescence Emission Spectra: Narrow Band versus Full 650-800 nm Retrievals

NASA Astrophysics Data System (ADS)

Middleton, E.; Zhang, Q.; Campbell, P. K.; Huemmrich, K. F.; Corp, L.; Cheng, Y.

2012-12-01

Recently, chlorophyll fluorescence (ChlF) retrievals in narrow spectral regions (< 1 nm, between 750-770 nm) of the near infrared (NIR) region of Earth's reflected radiation have been achieved from satellites, including the Japanese GOSAT and the European Space Agency's Sciamachy/Envisat. However, these retrievals sample the total full-spectrum ChlF and are made at non-optimal wavelengths since they are not located at the peak fluorescence emission features. We wish to estimate the total full-spectrum ChlF based on emissions obtained at selected wavelengths. For this, we drew upon leaf emission spectra measured on corn leaves obtained from a USDA experimental cornfield in MD (USA). These emission spectra were determined for the adaxial and abaxial (i.e., top and underside) surfaces of leaves measured throughout the 2008 and 2011 growing seasons (n>400) using a laboratory instrument (Fluorolog-3, Horiba Scientific, USA), recorded in either 1 nm or 5 nm increments with monochromatic excitation wavelengths of either 532 or 420 nm. The total ChlF signal was computed as the area under the continuous spectral emission curves, summing the emission intensities (counts per second) per waveband. The individual narrow (1 or 5 nm) waveband emission intensities were linearly related to full emission values, with variable success across the spectrum. Equations were developed to estimate total ChlF from these individual wavebands. Here, we report the results for the average adaxial/abaxial emissions. Very strong relationships were achieved for the relatively high fluorescence intensities at the red chlorophyll peak, centered at 685 nm (r2= 0.98, RMSE = 5.53 x 107 photons/s) and in the nearby O2-B atmospheric absorption feature centered at 688 nm (r2 = 0.94, RMSE = 4.04 x 107), as well as in the far-red peak centered at 740 nm (r2=0.94, RMSE = 5.98 x107). Very good retrieval success occurred for the O2-A atmospheric absorption feature on the declining NIR shoulder centered at 760 nm (r2 = 0.88, RMSE = 7.54 x 107). When perfect retrievals were assumed (0% noise), retrievals remained good in the low emission regions on either side of the peaks-- those associated with the H alpha line at 655 nm (r2 = 0.83, RMSE =8.87 x 107) and the far-NIR wavelengths recently utilized for satellite retrievals: a K line at 770 nm (r2 = 0.85, RMSE = 8.36 x 107) and the 750-770 nm interval (r2 = 0.88, RMSE = 6.92 x 107). However, the atmosphere and satellite observations are expected to add noise to retrievals. Adding 5% random error to these relationships did not seriously impair the retrieval successes in the red and far-red peaks (r2 ~ 0.85, RMSEs = 6.31 x 107). A greater impact occurred (reducing retrieval success by ~10%) when adding 5% noise for the far-NIR narrow band at 770 nm (r2 ~ 0.70, RMSE ~ 8.5 x 107). When a 10% random error was added, the retrieval successes fell to ~68 ± 7% for all retrieval wavebands, and RMSEs increased by a factor of 10. This laboratory approach will be critical to calibrate space borne retrievals, but additional information across plant species is needed. Furthermore, this experiment indicates that ChlF retrievals from space should include information from the red and far-red peak emission regions, since the true total fluorescence signal is the desired parameter for Earth carbon and energy budgets.

Trans-Pacific transport and evolution of aerosols: evaluation of quasi-global WRF-Chem simulation with multiple observations

NASA Astrophysics Data System (ADS)

Hu, Zhiyuan; Zhao, Chun; Huang, Jianping; Leung, L. Ruby; Qian, Yun; Yu, Hongbin; Huang, Lei; Kalashnikova, Olga V.

2016-05-01

A fully coupled meteorology-chemistry model (WRF-Chem, the Weather Research and Forecasting model coupled with chemistry) has been configured to conduct quasi-global simulation for 5 years (2010-2014) and evaluated with multiple observation data sets for the first time. The evaluation focuses on the simulation over the trans-Pacific transport region using various reanalysis and observational data sets for meteorological fields and aerosol properties. The simulation generally captures the overall spatial and seasonal variability of satellite retrieved aerosol optical depth (AOD) and absorbing AOD (AAOD) over the Pacific that is determined by the outflow of pollutants and dust and the emissions of marine aerosols. The assessment of simulated extinction Ångström exponent (EAE) indicates that the model generally reproduces the variability of aerosol size distributions as seen by satellites. In addition, the vertical profile of aerosol extinction and its seasonality over the Pacific are also well simulated. The difference between the simulation and satellite retrievals can be mainly attributed to model biases in estimating marine aerosol emissions as well as the satellite sampling and retrieval uncertainties. Compared with the surface measurements over the western USA, the model reasonably simulates the observed magnitude and seasonality of dust, sulfate, and nitrate surface concentrations, but significantly underestimates the peak surface concentrations of carbonaceous aerosol likely due to model biases in the spatial and temporal variability of biomass burning emissions and secondary organic aerosol (SOA) production. A sensitivity simulation shows that the trans-Pacific transported dust, sulfate, and nitrate can make significant contribution to surface concentrations over the rural areas of the western USA, while the peaks of carbonaceous aerosol surface concentrations are dominated by the North American emissions. Both the retrievals and simulation show small interannual variability of aerosol characteristics for 2010-2014 averaged over three Pacific sub-regions. The evaluation in this study demonstrates that the WRF-Chem quasi-global simulation can be used for investigating trans-Pacific transport of aerosols and providing reasonable inflow chemical boundaries for the western USA, allowing one to further understand the impact of transported pollutants on the regional air quality and climate with high-resolution nested regional modeling.

Comparison of SMOS and Aquarius Sea Surface Salinity and Analysis of Possible Causes for the Differences

NASA Technical Reports Server (NTRS)

Dinnat, E. P.; Boutin, J.; Yin, X.; Le Vine, D. M.; Waldteufel, P.; Vergely, J. -L.

2014-01-01

Two ongoing space missions share the scientific objective of mapping the global Sea Surface Salinity (SSS), yet their observations show significant discrepancies. ESA's Soil Moisture and Ocean Salinity (SMOS) and NASA's Aquarius use L-band (1.4 GHz) radiometers to measure emission from the sea surface and retrieve SSS. Significant differences in SSS retrieved by both sensors are observed, with SMOS SSS being generally lower than Aquarius SSS, except for very cold waters where SMOS SSS is the highest overall. Figure 1 is an example of the difference between the SSS retrieved by SMOS and Aquarius averaged over one month and 1 degree in longitude and latitude. Differences are mostly between -1 psu and +1 psu (psu, practical salinity unit), with a significant regional and latitudinal dependence. We investigate the impact of the vicarious calibration and some components of the retrieval algorithm used by both mission on these differences.

Retrieval of Methane Source Strengths in Europe Using a Simple Modeling Approach to Assess the Potential of Spaceborne Lidar Observations

NASA Technical Reports Server (NTRS)

Weaver, C.; Kiemle, C.; Kawa, S. R.; Aalto, T.; Necki, J.; Steinbacher, M.; Arduini, J.; Apadula, F.; Berkhout, H.; Hatakka, J.

2014-01-01

We investigate the sensitivity of future spaceborne lidar measurements to changes in surface methane emissions. We use surface methane observations from nine European ground stations and a Lagrangian transport model to infer surface methane emissions for 2010. Our inversion shows the strongest emissions from the Netherlands, the coal mines in Upper Silesia, Poland, and wetlands in southern Finland. The simulated methane surface concentrations capture at least half of the daily variability in the observations, suggesting that the transport model is correctly simulating the regional transport pathways over Europe. With this tool we can test whether proposed methane lidar instruments will be sensitive to changes in surface emissions. We show that future lidar instruments should be able to detect a 50% reduction in methane emissions from the Netherlands and Germany, at least during summer.

Reassessment of the temperature-emissivity separation from multispectral thermal infrared data: Introducing the impact of vegetation canopy by simulating the cavity effect with the SAIL-Thermique model

USDA-ARS?s Scientific Manuscript database

We investigated the use of multispectral thermal imagery to retrieve land surface emissivity and temperature. Conversely to concurrent methods, the temperature emissivity separation (TES) method simply requires single overpass without any ancillary information. This is possible since TES makes use o...

Multi-layer Retrievals of Greenhouse Gases from a Combined Use of GOSAT TANSO-FTS SWIR and TIR

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.; Yokota, T.

2016-12-01

The TANSO-FTS sensor onboard GOSAT has three frequency bands in the shortwave infrared (SWIR) and the fourth band in the thermal infrared (TIR). Observations of high-resolution spectra of reflected sunlight in the SWIR are extensively utilized to retrieve column-averaged concentrations of the major greenhouse gases such as carbon dioxide (XCO2) and methane (XCH4). Although global XCO2 and XCH4 distribution retrieved from SWIR data can reduce the uncertainty in the current knowledge about sources and sinks of these gases, information on the vertical profiles would be more useful to constrain the surface flux and also to identify the local emission sources. Based on the degrees of freedom for signal, Kulawik et al. (2016, IWGGMS-12 presentation) shows that 2-layer information on the concentration of CO2 can be extracted from TANSO-FTS SWIR measurements, and the retrieval error is predicted to be about 5 ppm in the lower troposphere. In this study, we present multi-layer retrievals of CO2 and CH4 from a combined use of measurements of TANSO-FTS SWIR and TIR. We selected GOSAT observations at Railroad Valley Playa in Nevada, USA, which is a vicarious calibration site for TANSO-FTS, as we have various ancillary data including atmospheric temperature and humidity taken by a radiosonde, surface temperature, and surface emissivity with a ground based FTS. All of these data are useful especially for retrievals using TIR spectra. Currently, we use the 700-800 cm-1 and 1200-1300 cm-1 TIR windows for CO2 and CH4 retrievals, respectively, in addition to the SWIR bands. We found that by adding TIR windows, 3-layer information can be extracted, and the predicted retrieval error in the CO2 concentration was reduced about 1 ppm in the lower troposphere. We expect that the retrieval error could be further reduced by optimizing TIR windows and by reducing systematic forward model errors.

New Technique for Retrieving Liquid Water Path over Land using Satellite Microwave Observations

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

Deeter, M.N.; Vivekanandan, J.

2005-03-18

We present a new methodology for retrieving liquid water path over land using satellite microwave observations. As input, the technique exploits the Advanced Microwave Scanning Radiometer for earth observing plan (EOS) (AMSR-E) polarization-difference signals at 37 and 89 GHz. Regression analysis performed on model simulations indicates that over variable atmospheric and surface conditions the polarization-difference signals can be simply parameterized in terms of the surface emissivity polarization difference ({Delta}{var_epsilon}), surface temperature, liquid water path (LWP), and precipitable water vapor (PWV). The resulting polarization-difference parameterization (PDP) enables fast and direct (noniterative) retrievals of LWP with minimal requirements for ancillary data. Single-more » and dual-channel retrieval methods are described and demonstrated. Data gridding is used to reduce the effects of instrumental noise. The methodology is demonstrated using AMSR-E observations over the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site during a six day period in November and December, 2003. Single- and dual-channel retrieval results mostly agree with ground-based microwave retrievals of LWP to within approximately 0.04 mm.« less

MEaSUReS Land Surface Temperature and Emissivity data records

NASA Astrophysics Data System (ADS)

Cawse-Nicholson, K.; Hook, S. J.; Gulley, G.; Borbas, E. E.; Knuteson, R. O.

2017-12-01

The NASA MEaSUReS program was put into place to produce long-term, well calibrated and validated data records for Earth Science research. As part of this program, we have developed three Earth System Data Records (ESDR) to measure Land Surface Temperature (LST) and emissivity: a high spatial resolution (1km) LST product using Low Earth Orbiting (LEO) satellites; a high temporal resolution (hourly over North America) LST product using Geostationary (GEO) satellites; and a Combined ASTER MODIS Emissivity for Land (CAMEL) ESDR. CAMEL was produced by merging two state-of-the-art emissivity datasets: the UW-Madison MODIS Infrared emissivity dataset (UWIREMIS), and the JPL ASTER Global Emissivity Dataset v4 (GEDv4). The CAMEL ESDR is currently available for download, and is being tested in sounder retrieval schemes (e.g. CrIS, IASI, AIRS) to reduce uncertainties in water vapor retrievals, and has already been implemented in the radiative transfer software RTTOV v12 for immediate use in numerical weather modeling and data assimilation systems. The LEO-LST product combines two existing MODIS products, using an uncertainty analysis approach to optimize accuracy over different landcover classes. Validation of these approaches for retrieving LST have shown that they are complementary, with the split-window approach (MxD11) being more stable over heavily vegetated regions and the physics-based approach (MxD21) demonstrating higher accuracy in semi-arid and arid regions where the largest variations in emissivity exist, both spatially and spectrally. The GEO LST-ESDR product uses CAMEL ESDR for improved temperature-emissivity separation, and the same atmospheric correction as the LEO LST product to ensure consistency across all three data records.

Surface and Atmospheric Contributions to Passive Microwave Brightness Temperatures

NASA Technical Reports Server (NTRS)

Jackson, Gail Skofronick; Johnson, Benjamin T.

2010-01-01

Physically-based passive microwave precipitation retrieval algorithms require a set of relationships between satellite observed brightness temperatures (TB) and the physical state of the underlying atmosphere and surface. These relationships are typically non-linear, such that inversions are ill-posed especially over variable land surfaces. In order to better understand these relationships, this work presents a theoretical analysis using brightness temperature weighting functions to quantify the percentage of the TB resulting from absorption/emission/reflection from the surface, absorption/emission/scattering by liquid and frozen hydrometeors in the cloud, the emission from atmospheric water vapor, and other contributors. The results are presented for frequencies from 10 to 874 GHz and for several individual precipitation profiles as well as for three cloud resolving model simulations of falling snow. As expected, low frequency channels (<89 GHz) respond to liquid hydrometeors and the surface, while the higher frequency channels become increasingly sensitive to ice hydrometeors and the water vapor sounding channels react to water vapor in the atmosphere. Low emissivity surfaces (water and snow-covered land) permit energy downwelling from clouds to be reflected at the surface thereby increasing the percentage of the TB resulting from the hydrometeors. The slant path at a 53deg viewing angle increases the hydrometeor contributions relative to nadir viewing channels and show sensitivity to surface polarization effects. The TB percentage information presented in this paper answers questions about the relative contributions to the brightness temperatures and provides a key piece of information required to develop and improve precipitation retrievals over land surfaces.

Multispectrum retrieval techniques applied to Venus deep atmosphere and surface problems

NASA Astrophysics Data System (ADS)

Kappel, David; Arnold, Gabriele; Haus, Rainer

The Visible and Infrared Thermal Imaging Spectrometer (VIRTIS) aboard ESA's Venus Express is continuously collecting nightside emission data (among others) from Venus. A radiative transfer model of Venus' atmosphere in conjunction with a suitable retrieval algorithm can be used to estimate atmospheric and surface parameters by fitting simulated spectra to the measured data. Because of the limited spectral resolution of VIRTIS-M-IR-spectra, that have been used so far, many different parameter sets can explain the same measurement equally well. As a common regulative measure, reasonable a priori knowledge of some parameters is applied to suppress solutions implausibly far from the expected range. It is beneficial to introduce a parallel coupled retrieval of several measurements. Since spa-tially and temporally contiguous measurements are not expected to originate from completely unrelated parameters, an assumed a priori correlation of the parameters during the retrieval can help to reduce arbitrary fluctuations of the solutions, to avoid subsidiary solutions, and to attenuate the interference of measurement noise by keeping the parameters close to a gen-eral trend. As an illustration, the resulting improvements for some swaths on the Northern hemisphere are presented. Some atmospheric features are still not very well constrained, for instance CO2 absorption under the extreme environmental conditions close to the surface. A broad band continuum due to far wing and collisional induced absorptions is commonly used to correct individual line absorption. Since the spectrally dependent continuum is constant for all measurements, the retrieval of parameters common to all spectra may be used to give some estimates of the continuum absorption. These estimates are necessary, for example, for the coupled parallel retrieval of a consistent local cloud modal composition, which in turn enables a refined surface emissivity retrieval. We gratefully acknowledge the support from the VIRTIS/Venus Express Team, from ASI, CNES, CNRS, and from the DFG funding the ongoing work.

Bridging the Global Precipitation and Soil Moisture Active Passive Missions: Variability of Microwave Surface Emissivity from In situ and Remote Sensing Perspectives

NASA Astrophysics Data System (ADS)

Zheng, Y.; Kirstetter, P.; Hong, Y.; Turk, J.

2016-12-01

The overland precipitation retrievals from satellite passive microwave (PMW) sensors such as the Global Precipitation Mission (GPM) microwave imager (GMI) are impacted by the land surface emissivity. The estimation of PMW emissivity faces challenges because it is highly variable under the influence of surface properties such as soil moisture, surface roughness and vegetation. This study proposes an improved quantitative understanding of the relationship between the emissivity and surface parameters. Surface parameter information is obtained through (i) in-situ measurements from the International Soil Moisture Network and (ii) satellite measurements from the Soil Moisture Active and Passive mission (SMAP) which provides global scale soil moisture estimates. The variation of emissivity is quantified with soil moisture, surface temperature and vegetation at various frequencies/polarization and over different types of land surfaces to sheds light into the processes governing the emission of the land. This analysis is used to estimate the emissivity under rainy conditions. The framework built with in-situ measurements serves as a benchmark for satellite-based analyses, which paves a way toward global scale emissivity estimates using SMAP.

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.

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.

The difference between laboratory and in-situ pixel-averaged emissivity: The effects on temperature-emissivity separation

NASA Technical Reports Server (NTRS)

Matsunaga, Tsuneo

1993-01-01

Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) is a Japanese future imaging sensor which has five channels in thermal infrared (TIR) region. To extract spectral emissivity information from ASTER and/or TIMS data, various temperature-emissivity (T-E) separation methods have been developed to date. Most of them require assumptions on surface emissivity, in which emissivity measured in a laboratory is often used instead of in-situ pixel-averaged emissivity. But if these two emissivities are different, accuracies of separated emissivity and surface temperature are reduced. In this study, the difference between laboratory and in-situ pixel-averaged emissivity and its effect on T-E separation are discussed. TIMS data of an area containing both rocks and vegetation were also processed to retrieve emissivity spectra using two T-E separation methods.

A Proposed Extension to the Soil Moisture and Ocean Salinity Level 2 Algorithm for Mixed Forest and Moderate Vegetation Pixels

NASA Technical Reports Server (NTRS)

Panciera, Rocco; Walker, Jeffrey P.; Kalma, Jetse; Kim, Edward

2011-01-01

The Soil Moisture and Ocean Salinity (SMOS)mission, launched in November 2009, provides global maps of soil moisture and ocean salinity by measuring the L-band (1.4 GHz) emission of the Earth's surface with a spatial resolution of 40-50 km.Uncertainty in the retrieval of soilmoisture over large heterogeneous areas such as SMOS pixels is expected, due to the non-linearity of the relationship between soil moisture and the microwave emission. The current baseline soilmoisture retrieval algorithm adopted by SMOS and implemented in the SMOS Level 2 (SMOS L2) processor partially accounts for the sub-pixel heterogeneity of the land surface, by modelling the individual contributions of different pixel fractions to the overall pixel emission. This retrieval approach is tested in this study using airborne L-band data over an area the size of a SMOS pixel characterised by a mix Eucalypt forest and moderate vegetation types (grassland and crops),with the objective of assessing its ability to correct for the soil moisture retrieval error induced by the land surface heterogeneity. A preliminary analysis using a traditional uniform pixel retrieval approach shows that the sub-pixel heterogeneity of land cover type causes significant errors in soil moisture retrieval (7.7%v/v RMSE, 2%v/v bias) in pixels characterised by a significant amount of forest (40-60%). Although the retrieval approach adopted by SMOS partially reduces this error, it is affected by errors beyond the SMOS target accuracy, presenting in particular a strong dry bias when a fraction of the pixel is occupied by forest (4.1%v/v RMSE,-3.1%v/v bias). An extension to the SMOS approach is proposed that accounts for the heterogeneity of vegetation optical depth within the SMOS pixel. The proposed approach is shown to significantly reduce the error in retrieved soil moisture (2.8%v/v RMSE, -0.3%v/v bias) in pixels characterised by a critical amount of forest (40-60%), at the limited cost of only a crude estimate of the optical depth of the forested area (better than 35% uncertainty). This study makes use of an unprecedented data set of airborne L-band observations and ground supporting data from the National Airborne Field Experiment 2005 (NAFE'05), which allowed accurate characterisation of the land surface heterogeneity over an area equivalent in size to a SMOS pixel.

Inter-comparison between AIRS and IASI through Retrieved Parameters

NASA Technical Reports Server (NTRS)

Zhou, Daniel K.; Larar, Allen M.; Smith, William L.; Taylor, Jonathan P.; Schluessel, Peter; Strow, L. Larrabee; Mango, Steve

2008-01-01

A State-of-the-art retrieval algorithm dealing with all-weather conditions has been applied to satellite/aircraft instruments retrieving cloud/surface and atmospheric conditions. High quality retrievals have been achieved from IASI data. Surface, cloud, and atmospheric structure and variation are well captured by IASI measurements and/or retrievals. The same retrieval algorithm is also applied to AIRS for retrieval inter-comparison. Both AIRS and IASI have a similar FOV size but AIRS has a higher horizontal resolution. AIRS data can be interpolated to IASI horizontal resolution for inter-comparison at the same geophysical locations, however a temporal variation between AIRS and IASI observations need to be considered. JAIVEx has employed aircraft to obtain the atmospheric variation filling the temporal gap between two satellites. First results show that both AIRS and IASI have a very similar vertical resolving power, atmospheric conditions are well captured by both instruments, and radiances are well calibrated. AIRS data shown in retrievals (e.g., surface emissivity and moisture) have a relatively higher noise level. Since the this type of retrieval is very sensitive to its radiance quality, retrieval products inter-comparison is an effective way to identify/compare their radiance quality, in terms of a combination of spectral resolution and noise level, and to assess instrument performance. Additional validation analyses are needed to provide more-definitive conclusions.

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

Evaluation of the effects of varying moisture contents on microwave thermal emissions from agriculture fields

NASA Technical Reports Server (NTRS)

Burke, H. H. K.

1980-01-01

Three tasks related to soil moisture sensing at microwave wavelengths were undertaken: (1) analysis of data at L, X and K sub 21 band wavelengths over bare and vegetated fields from the 1975 NASA sponsored flight experiment over Phoenix, Arizona; (2) modeling of vegetation canopy at microwave wavelengths taking into consideration both absorption and volume scattering effects; and (3) investigation of overall atmospheric effects at microwave wavelengths that can affect soil moisture retrieval. Data for both bare and vegetated fields are found to agree well with theoretical estimates. It is observed that the retrieval of surface and near surface soil moisture information is feasible through multi-spectral and multi-temporal analysis. It is also established that at long wavelengths, which are optimal for surface sensing, atmospheric effects are generally minimal. At shorter wavelengths, which are optimal for atmosheric retrieval, the background surface properties are also established.

Modeling and analysis of LWIR signature variability associated with 3D and BRDF effects

NASA Astrophysics Data System (ADS)

Adler-Golden, Steven; Less, David; Jin, Xuemin; Rynes, Peter

2016-05-01

Algorithms for retrieval of surface reflectance, emissivity or temperature from a spectral image almost always assume uniform illumination across the scene and horizontal surfaces with Lambertian reflectance. When these algorithms are used to process real 3-D scenes, the retrieved "apparent" values contain the strong, spatially dependent variations in illumination as well as surface bidirectional reflectance distribution function (BRDF) effects. This is especially problematic with horizontal or near-horizontal viewing, where many observed surfaces are vertical, and where horizontal surfaces can show strong specularity. The goals of this study are to characterize long-wavelength infrared (LWIR) signature variability in a HSI 3-D scene and develop practical methods for estimating the true surface values. We take advantage of synthetic near-horizontal imagery generated with the high-fidelity MultiService Electro-optic Signature (MuSES) model, and compare retrievals of temperature and directional-hemispherical reflectance using standard sky downwelling illumination and MuSES-based non-uniform environmental illumination.

Simulations of aerosol constituents and their sources of origin over Indo-Gangetic plain (IGP) to Himalayan foothills: a new perspective of GCM estimates

NASA Astrophysics Data System (ADS)

Kumar, B. D.; Verma, S.; Wang, R.; Boucher, O.

2016-12-01

In the present study, we evaluated aerosol constituents of the model using the measurements during premonsoon over Indo-Gangetic plain (IGP) to Himalayan foothills. Aerosol transport simulations were carried out in general circulation model (GCM) of Laboratoire de M ´et ´eorologie Dynamique (LMD-GCM) with three set of emissions including Indian emissions in GCM-Indemiss, global emissions in GCM coupled with aerosol interactive chemistry (GCM-INCA-I), and the global emissions with updated BC emission inventory over Asia in GCM-INCA-II. Among three models, GCM-indemiss reproduced measured single scattering albedo (SSA) at 670 nm with a relative bias of 5%. However, the estimated 30-50% of the measured aerosol optical depth (AOD) at 550 nm and 20-60% of the measured surface concentration of aerosol constituents (e.g. black carbon (BC), organic carbon (OC), and sulfate) at most of the times over the study period. Inability of model to reproduce observed AOD changes was attributed to the paucity of emissions represented in the model. Design of retrieval simulations using existing GCM-indemiss estimates was further carried out. Retrieval simulations have produced better results, which showed constituent surface concentration in the vicinity of the measurements with normalized mean bias (NMB) of <30%. Scatter analysis between surface and elevated contribution of region's emissions showed anthropogenic emissions from the IGP on anthropogenic days and the north west India (NWI) on anthropogenic with dust days influence aerosols over northern India (NI). Our analysis showed BC emissions from base inventory for the corresponding grids of source region influencing NI were lower by 200% compared to that of modified scenario. These emissions will further be implemented in an atmospheric GCM to evaluate their performance validating with measurements data.

Retrieving Land Surface Temperature from Hyperspectral Thermal Infrared Data Using a Multi-Channel Method

PubMed Central

Zhong, Xinke; Huo, Xing; Ren, Chao; Labed, Jelila; Li, Zhao-Liang

2016-01-01

Land Surface Temperature (LST) is a key parameter in climate systems. The methods for retrieving LST from hyperspectral thermal infrared data either require accurate atmospheric profile data or require thousands of continuous channels. We aim to retrieve LST for natural land surfaces from hyperspectral thermal infrared data using an adapted multi-channel method taking Land Surface Emissivity (LSE) properly into consideration. In the adapted method, LST can be retrieved by a linear function of 36 brightness temperatures at Top of Atmosphere (TOA) using channels where LSE has high values. We evaluated the adapted method using simulation data at nadir and satellite data near nadir. The Root Mean Square Error (RMSE) of the LST retrieved from the simulation data is 0.90 K. Compared with an LST product from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on Meteosat, the error in the LST retrieved from the Infared Atmospheric Sounding Interferometer (IASI) is approximately 1.6 K. The adapted method can be used for the near-real-time production of an LST product and to provide the physical method to simultaneously retrieve atmospheric profiles, LST, and LSE with a first-guess LST value. The limitations of the adapted method are that it requires the minimum LSE in the spectral interval of 800–950 cm−1 larger than 0.95 and it has not been extended for off-nadir measurements. PMID:27187408

Unpolarized infrared emissivity with shadow from anisotropic rough sea surfaces with non-Gaussian statistics.

PubMed

Bourlier, Christophe

2005-07-10

The emissivity of two-dimensional anisotropic rough sea surfaces with non-Gaussian statistics is investigated. The emissivity derivation is of importance for retrieval of the sea-surface temperature or equivalent temperature of a rough sea surface by infrared thermal imaging. The well-known Cox-Munk slope probability-density function, considered non-Gaussian, is used for the emissivity derivation, in which the skewness and the kurtosis (related to the third- and fourth-order statistics, respectively) are included. The shadowing effect, which is significant for grazing angles, is also taken into account. The geometric optics approximation is assumed to be valid, which means that the rough surface is modeled as a collection of facets reflecting locally the light in the specular direction. In addition, multiple reflections are ignored. Numerical results of the emissivity are presented for Gaussian and non-Gaussian statistics, for moderate wind speeds, for near-infrared wavelengths, for emission angles ranging from 0 degrees (nadir) to 90 degrees (horizon), and according to the wind direction. In addition, the emissivity is compared with both measurements and a Monte Carlo ray-tracing method.

[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.

Use of Air Quality Observations by the National Air Quality Forecast Capability

NASA Astrophysics Data System (ADS)

Stajner, I.; McQueen, J.; Lee, P.; Stein, A. F.; Kondragunta, S.; Ruminski, M.; Tong, D.; Pan, L.; Huang, J. P.; Shafran, P.; Huang, H. C.; Dickerson, P.; Upadhayay, S.

2015-12-01

The National Air Quality Forecast Capability (NAQFC) operational predictions of ozone and wildfire smoke for the United States (U.S.) and predictions of airborne dust for continental U.S. are available at http://airquality.weather.gov/. NOAA National Centers for Environmental Prediction (NCEP) operational North American Mesoscale (NAM) weather predictions are combined with the Community Multiscale Air Quality (CMAQ) model to produce the ozone predictions and test fine particulate matter (PM2.5) predictions. The Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model provides smoke and dust predictions. Air quality observations constrain emissions used by NAQFC predictions. NAQFC NOx emissions from mobile sources were updated using National Emissions Inventory (NEI) projections for year 2012. These updates were evaluated over large U.S. cities by comparing observed changes in OMI NO2 observations and NOx measured by surface monitors. The rate of decrease in NOx emission projections from year 2005 to year 2012 is in good agreement with the observed changes over the same period. Smoke emissions rely on the fire locations detected from satellite observations obtained from NESDIS Hazard Mapping System (HMS). Dust emissions rely on a climatology of areas with a potential for dust emissions based on MODIS Deep Blue aerosol retrievals. Verification of NAQFC predictions uses AIRNow compilation of surface measurements for ozone and PM2.5. Retrievals of smoke from GOES satellites are used for verification of smoke predictions. Retrievals of dust from MODIS are used for verification of dust predictions. In summary, observations are the basis for the emissions inputs for NAQFC, they are critical for evaluation of performance of NAQFC predictions, and furthermore they are used in real-time testing of bias correction of PM2.5 predictions, as we continue to work on improving modeling and emissions important for representation of PM2.5.

Iterative retrieval of surface emissivity and temperature for a hyperspectral sensor

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

Borel, C.C.

1997-11-01

The central problem of temperature-emissivity separation is that we obtain N spectral measurements of radiance and need to find N + 1 unknowns (N emissivities and one temperature). To solve this problem in the presence of the atmosphere we need to find even more unknowns: N spectral transmissions {tau}{sub atmo}({lambda}) up-welling path radiances L{sub path}{up_arrow}({lambda}) and N down-welling path radiances L{sub path}{down_arrow}({lambda}). Fortunately there are radiative transfer codes such as MODTRAN 3 and FASCODE available to get good estimates of {tau}{sub atmo}({lambda}), L{sub path}{up_arrow}({lambda}) and L{sub path}{down_arrow}({lambda}) in the order of a few percent. With the growing use of hyperspectralmore » imagers, e.g. AVIRIS in the visible and short-wave infrared there is hope of using such instruments in the mid-wave and thermal IR (TIR) some day. We believe that this will enable us to get around using the present temperature - emissivity separation (TES) algorithms using methods which take advantage of the many channels available in hyperspectral imagers. The first idea we had is to take advantage of the simple fact that a typical surface emissivity spectrum is rather smooth compared to spectral features introduced by the atmosphere. Thus iterative solution techniques can be devised which retrieve emissivity spectra {epsilon} based on spectral smoothness. To make the emissivities realistic, atmospheric parameters are varied using approximations, look-up tables derived from a radiative transfer code and spectral libraries. By varying the surface temperature over a small range a series of emissivity spectra are calculated. The one with the smoothest characteristic is chosen. The algorithm was tested on synthetic data using MODTRAN and the Salisbury emissivity database.« less

Geometric-Optical Modeling of Directional Thermal Radiance for Improvement of Land Surface Temperature Retrievals from MODIS, ASTER, and Landsat-7 Instruments

NASA Technical Reports Server (NTRS)

Li, Xiaowen; Friedl, Mark; Strahler, Alan

2002-01-01

The general objectives of this project were to improve understanding of the directional emittance properties of land surfaces in the thermal infrared (TIR) region of the electro-magnetic spectrum. To accomplish these objectives our research emphasized a combination of theoretical model development and empirical studies designed to improve land surface temperature (LST) retrievals from space-borne remote sensing instruments. Following the proposal, the main tasks for this project were to: (1) Participate in field campaigns; (2) Acquire and process field, aircraft, and ancillary data; (3) Develop and refine models of LST emission; (4) Develop algorithms for LST retrieval; and (5) Explore LST retrieval methods for use in energy balance models. In general all of these objectives were addressed, and for the most part achieved. The main results from this project are described in the publications arising from this effort. We summarize our efforts related to each of the objectives.

Validation of Aquarius Measurements Using Radiative Transfer Models at L-Band

NASA Technical Reports Server (NTRS)

Dinnat, E.; LeVine, David M.; Abraham, S.; DeMattheis, P.; Utku, C.

2012-01-01

Aquarius/SAC-D was launched in June 2011 by NASA and CONAE (Argentine space agency). Aquarius includes three L-band (1.4 GHz) radiometers dedicated to measuring sea surface salinity. We report detailed comparisons of Aquarius measurements with radiative transfer model predictions. These comparisons were used as part ofthe initial assessment of Aquarius data. In particular, they were used successfully to estimate the radiometer calibration bias and stability. Further comparisons are being performed to assess the performance of models in the retrieval algorithm for correcting the effect of sources of geophysical "noise" (e.g. the galactic background, atmospheric attenuation and reflected signal from the Sun). Such corrections are critical in bringing the error in retrieved salinity down to the required 0.2 practical salinity unit (psu) on monthly global maps at 150 km by 150 km resolution. The forward models making up the Aquarius simulator have been very useful for preparatory studies in the years leading to Aquarius' launch. The simulator includes various components to compute effects ofthe following processes on the measured signal: 1) emission from Earth surfaces (ocean, land, ice), 2) atmospheric emission and absorption, 3) emission from the Sun, Moon and celestial Sky (directly through the antenna sidelobes or after reflection/scattering at the Earth surface), 4) Faraday rotation, and 5) convolution of the scene by the antenna gain patterns. Since the Aquarius radiometers tum-on in late July 2011, the simulator has been used to perform a first order validation of the data. This included checking the order of magnitude ofthe signal over ocean, land and ice surfaces, checking the relative amplitude of signal at different polarizations, and checking the variation with incidence angle. The comparisons were also used to assess calibration bias and monitor instruments calibration drift. The simulator is also being used in the salinity retrieval. For example, initial assessments of the salinity retrieved from Aquarius data showed degradation in accuracy at locations where glint from the galactic sky background was important. This was traced to an inaccurate correction for the Sky glint. We present comparisons of the simulator prediction to the Aquarius data in order to assess the performances of the models of various physical processes impacting the measurements, such as the effect of sea surface roughness, the impact of the celestial Sky and the Sun emission scattered at the rough ocean surface. We discuss what components of the simulator appear reliable and which ones need improvements. Improved knowledge on the radiative transfer models at L-band will not only lead to better salinity retrieved from Aquarius data, it will also allow be beneficial for SMOS or the upcoming SMAP mission.

Evaluation of the operational Aerosol Layer Height retrieval algorithm for Sentinel-5 Precursor: application to O2 A band observations from GOME-2A

NASA Astrophysics Data System (ADS)

Sanders, A. F. J.; de Haan, J. F.; Sneep, M.; Apituley, A.; Stammes, P.; Vieitez, M. O.; Tilstra, L. G.; Tuinder, O. N. E.; Koning, C. E.; Veefkind, J. P.

2015-06-01

An algorithm setup for the operational Aerosol Layer Height product for TROPOMI on the Sentinel-5 Precursor mission is described and discussed, applied to GOME-2A data, and evaluated with lidar measurements. The algorithm makes a spectral fit of reflectance at the O2 A band in the near-infrared and the fit window runs from 758 to 770 nm. The aerosol profile is parameterized by a scattering layer with constant aerosol volume extinction coefficient and aerosol single scattering albedo and with a fixed pressure thickness. The algorithm's target parameter is the height of this layer. In this paper, we apply the algorithm to observations from GOME-2A in a number of systematic and extensive case studies and we compare retrieved aerosol layer heights with lidar measurements. Aerosol scenes cover various aerosol types, both elevated and boundary layer aerosols, and land and sea surfaces. The aerosol optical thicknesses for these scenes are relatively moderate. Retrieval experiments with GOME-2A spectra are used to investigate various sensitivities, in which particular attention is given to the role of the surface albedo. From retrieval simulations with the single-layer model, we learn that the surface albedo should be a fit parameter when retrieving aerosol layer height from the O2 A band. Current uncertainties in surface albedo climatologies cause biases and non-convergences when the surface albedo is fixed in the retrieval. Biases disappear and convergence improves when the surface albedo is fitted, while precision of retrieved aerosol layer pressure is still largely within requirement levels. Moreover, we show that fitting the surface albedo helps to ameliorate biases in retrieved aerosol layer height when the assumed aerosol model is inaccurate. Subsequent retrievals with GOME-2A spectra confirm that convergence is better when the surface albedo is retrieved simultaneously with aerosol parameters. However, retrieved aerosol layer pressures are systematically low (i.e., layer high in the atmosphere) to the extent that retrieved values are not realistically representing actual extinction profiles anymore. When the surface albedo is fixed in retrievals with GOME-2A spectra, convergence deteriorates as expected, but retrieved aerosol layer pressures become much higher (i.e., layer lower in atmosphere). The comparison with lidar measurements indicates that retrieved aerosol layer heights are indeed representative of the underlying profile in that case. Finally, subsequent retrieval simulations with two-layer aerosol profiles show that a model error in the assumed profile (two layers in the simulation but only one in the retrieval) is partly absorbed by the surface albedo when this parameter is fitted. This is expected in view of the correlations between errors in fit parameters and the effect is relatively small for elevated layers (less than 100 hPa). In case one of the scattering layers is near the surface (boundary layer aerosols), the effect becomes surprisingly large such that the retrieved height of the single layer is above the two-layer profile. Furthermore, we find that the retrieval solution, once retrieval converges, hardly depends on the starting values for the fit. Sensitivity experiments with GOME-2A spectra also show that aerosol layer height is indeed relatively robust against inaccuracies in the assumed aerosol model, even when the surface albedo is not fitted. We show spectral fit residuals, which can be used for further investigations. Fit residuals may be partly explained by spectroscopic uncertainties, which is suggested by an experiment showing the improvement of convergence when the absorption cross section is scaled in agreement with Butz et al. (2012) and Crisp et al. (2012) and a temperature offset to the a priori ECMWF temperature profile is fitted. Retrieved temperature offsets are always negative and quite large (ranging between -4 and -8 K), which is not expected if temperature offsets absorb remaining inaccuracies in meteorological data. Other sensitivity experiments investigate fitting of stray light and fluorescence emissions. We find negative radiance offsets and negative fluorescence emissions, also for non-vegetated areas, but from the results it is not clear whether fitting these parameters improves the retrieval. Based on the present results, the operational baseline for the Aerosol Layer Height product currently will not fit the surface albedo. The product will be particularly suited for elevated, optically thick aerosol layers. In addition to its scientific value in climate research, anticipated applications of the product for TROPOMI are providing aerosol height information for aviation safety and improving interpretation of the Absorbing Aerosol Index.

Evaluation of the operational Aerosol Layer Height retrieval algorithm for Sentinel-5 Precursor: application to O2 A band observations from GOME-2A

NASA Astrophysics Data System (ADS)

Sanders, A. F. J.; de Haan, J. F.; Sneep, M.; Apituley, A.; Stammes, P.; Vieitez, M. O.; Tilstra, L. G.; Tuinder, O. N. E.; Koning, C. E.; Veefkind, J. P.

2015-11-01

An algorithm setup for the operational Aerosol Layer Height product for TROPOMI on the Sentinel-5 Precursor mission is described and discussed, applied to GOME-2A data, and evaluated with lidar measurements. The algorithm makes a spectral fit of reflectance at the O2 A band in the near-infrared and the fit window runs from 758 to 770 nm. The aerosol profile is parameterised by a scattering layer with constant aerosol volume extinction coefficient and aerosol single scattering albedo and with a fixed pressure thickness. The algorithm's target parameter is the height of this layer. In this paper, we apply the algorithm to observations from GOME-2A in a number of systematic and extensive case studies, and we compare retrieved aerosol layer heights with lidar measurements. Aerosol scenes cover various aerosol types, both elevated and boundary layer aerosols, and land and sea surfaces. The aerosol optical thicknesses for these scenes are relatively moderate. Retrieval experiments with GOME-2A spectra are used to investigate various sensitivities, in which particular attention is given to the role of the surface albedo. From retrieval simulations with the single-layer model, we learn that the surface albedo should be a fit parameter when retrieving aerosol layer height from the O2 A band. Current uncertainties in surface albedo climatologies cause biases and non-convergences when the surface albedo is fixed in the retrieval. Biases disappear and convergence improves when the surface albedo is fitted, while precision of retrieved aerosol layer pressure is still largely within requirement levels. Moreover, we show that fitting the surface albedo helps to ameliorate biases in retrieved aerosol layer height when the assumed aerosol model is inaccurate. Subsequent retrievals with GOME-2A spectra confirm that convergence is better when the surface albedo is retrieved simultaneously with aerosol parameters. However, retrieved aerosol layer pressures are systematically low (i.e., layer high in the atmosphere) to the extent that retrieved values no longer realistically represent actual extinction profiles. When the surface albedo is fixed in retrievals with GOME-2A spectra, convergence deteriorates as expected, but retrieved aerosol layer pressures become much higher (i.e., layer lower in atmosphere). The comparison with lidar measurements indicates that retrieved aerosol layer heights are indeed representative of the underlying profile in that case. Finally, subsequent retrieval simulations with two-layer aerosol profiles show that a model error in the assumed profile (two layers in the simulation but only one in the retrieval) is partly absorbed by the surface albedo when this parameter is fitted. This is expected in view of the correlations between errors in fit parameters and the effect is relatively small for elevated layers (less than 100 hPa). If one of the scattering layers is near the surface (boundary layer aerosols), the effect becomes surprisingly large, in such a way that the retrieved height of the single layer is above the two-layer profile. Furthermore, we find that the retrieval solution, once retrieval converges, hardly depends on the starting values for the fit. Sensitivity experiments with GOME-2A spectra also show that aerosol layer height is indeed relatively robust against inaccuracies in the assumed aerosol model, even when the surface albedo is not fitted. We show spectral fit residuals, which can be used for further investigations. Fit residuals may be partly explained by spectroscopic uncertainties, which is suggested by an experiment showing the improvement of convergence when the absorption cross section is scaled in agreement with Butz et al. (2013) and Crisp et al. (2012), and a temperature offset to the a priori ECMWF temperature profile is fitted. Retrieved temperature offsets are always negative and quite large (ranging between -4 and -8 K), which is not expected if temperature offsets absorb remaining inaccuracies in meteorological data. Other sensitivity experiments investigate fitting of stray light and fluorescence emissions. We find negative radiance offsets and negative fluorescence emissions, also for non-vegetated areas, but from the results it is not clear whether fitting these parameters improves the retrieval. Based on the present results, the operational baseline for the Aerosol Layer Height product currently will not fit the surface albedo. The product will be particularly suited for elevated, optically thick aerosol layers. In addition to its scientific value in climate research, anticipated applications of the product for TROPOMI are providing aerosol height information for aviation safety and improving interpretation of the Absorbing Aerosol Index.

Trans-Pacific transport and evolution of aerosols: Evaluation of quasi-global WRF-Chem simulation with multiple observations

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

Hu, Zhiyuan; Zhao, Chun; Huang, Jianping

A fully coupled meteorology-chemistry model (WRF-Chem, the Weather Research and Forecasting model coupled with chemistry) has been configured to conduct quasi-global simulation for 5 years (2010–2014) and evaluated with multiple observation data sets for the first time. The evaluation focuses on the simulation over the trans-Pacific transport region using various reanalysis and observational data sets for meteorological fields and aerosol properties. The simulation generally captures the overall spatial and seasonal variability of satellite retrieved aerosol optical depth (AOD) and absorbing AOD (AAOD) over the Pacific that is determined by the outflow of pollutants and dust and the emissions of marine aerosols.more » The assessment of simulated extinction Ångström exponent (EAE) indicates that the model generally reproduces the variability of aerosol size distributions as seen by satellites. In addition, the vertical profile of aerosol extinction and its seasonality over the Pacific are also well simulated. The difference between the simulation and satellite retrievals can be mainly attributed to model biases in estimating marine aerosol emissions as well as the satellite sampling and retrieval uncertainties. Compared with the surface measurements over the western USA, the model reasonably simulates the observed magnitude and seasonality of dust, sulfate, and nitrate surface concentrations, but significantly underestimates the peak surface concentrations of carbonaceous aerosol likely due to model biases in the spatial and temporal variability of biomass burning emissions and secondary organic aerosol (SOA) production. A sensitivity simulation shows that the trans-Pacific transported dust, sulfate, and nitrate can make significant contribution to surface concentrations over the rural areas of the western USA, while the peaks of carbonaceous aerosol surface concentrations are dominated by the North American emissions. Both the retrievals and simulation show small interannual variability of aerosol characteristics for 2010–2014 averaged over three Pacific sub-regions. Furthermore, the evaluation in this study demonstrates that the WRF-Chem quasi-global simulation can be used for investigating trans-Pacific transport of aerosols and providing reasonable inflow chemical boundaries for the western USA, allowing one to further understand the impact of transported pollutants on the regional air quality and climate with high-resolution nested regional modeling.« less

Trans-Pacific transport and evolution of aerosols: Evaluation of quasi-global WRF-Chem simulation with multiple observations

DOE PAGES

Hu, Zhiyuan; Zhao, Chun; Huang, Jianping; ...

2016-05-10

A fully coupled meteorology-chemistry model (WRF-Chem, the Weather Research and Forecasting model coupled with chemistry) has been configured to conduct quasi-global simulation for 5 years (2010–2014) and evaluated with multiple observation data sets for the first time. The evaluation focuses on the simulation over the trans-Pacific transport region using various reanalysis and observational data sets for meteorological fields and aerosol properties. The simulation generally captures the overall spatial and seasonal variability of satellite retrieved aerosol optical depth (AOD) and absorbing AOD (AAOD) over the Pacific that is determined by the outflow of pollutants and dust and the emissions of marine aerosols.more » The assessment of simulated extinction Ångström exponent (EAE) indicates that the model generally reproduces the variability of aerosol size distributions as seen by satellites. In addition, the vertical profile of aerosol extinction and its seasonality over the Pacific are also well simulated. The difference between the simulation and satellite retrievals can be mainly attributed to model biases in estimating marine aerosol emissions as well as the satellite sampling and retrieval uncertainties. Compared with the surface measurements over the western USA, the model reasonably simulates the observed magnitude and seasonality of dust, sulfate, and nitrate surface concentrations, but significantly underestimates the peak surface concentrations of carbonaceous aerosol likely due to model biases in the spatial and temporal variability of biomass burning emissions and secondary organic aerosol (SOA) production. A sensitivity simulation shows that the trans-Pacific transported dust, sulfate, and nitrate can make significant contribution to surface concentrations over the rural areas of the western USA, while the peaks of carbonaceous aerosol surface concentrations are dominated by the North American emissions. Both the retrievals and simulation show small interannual variability of aerosol characteristics for 2010–2014 averaged over three Pacific sub-regions. Furthermore, the evaluation in this study demonstrates that the WRF-Chem quasi-global simulation can be used for investigating trans-Pacific transport of aerosols and providing reasonable inflow chemical boundaries for the western USA, allowing one to further understand the impact of transported pollutants on the regional air quality and climate with high-resolution nested regional modeling.« less

The Operational MODIS Cloud Optical and Microphysical Property Product: Overview of the Collection 6 Algorithm and Preliminary Results

NASA Technical Reports Server (NTRS)

Platnick, Steven; King, Michael D.; Wind, Galina; Amarasinghe, Nandana; Marchant, Benjamin; Arnold, G. Thomas

2012-01-01

Operational Moderate Resolution Imaging Spectroradiometer (MODIS) retrievals of cloud optical and microphysical properties (part of the archived products MOD06 and MYD06, for MODIS Terra and Aqua, respectively) are currently being reprocessed along with other MODIS Atmosphere Team products. The latest "Collection 6" processing stream, which is expected to begin production by summer 2012, includes updates to the previous cloud retrieval algorithm along with new capabilities. The 1 km retrievals, based on well-known solar reflectance techniques, include cloud optical thickness, effective particle radius, and water path, as well as thermodynamic phase derived from a combination of solar and infrared tests. Being both global and of high spatial resolution requires an algorithm that is computationally efficient and can perform over all surface types. Collection 6 additions and enhancements include: (i) absolute effective particle radius retrievals derived separately from the 1.6 and 3.7 !-lm bands (instead of differences relative to the standard 2.1 !-lm retrieval), (ii) comprehensive look-up tables for cloud reflectance and emissivity (no asymptotic theory) with a wind-speed interpolated Cox-Munk BRDF for ocean surfaces, (iii) retrievals for both liquid water and ice phases for each pixel, and a subsequent determination of the phase based, in part, on effective radius retrieval outcomes for the two phases, (iv) new ice cloud radiative models using roughened particles with a specified habit, (v) updated spatially-complete global spectral surface albedo maps derived from MODIS Collection 5, (vi) enhanced pixel-level uncertainty calculations incorporating additional radiative error sources including the MODIS L1 B uncertainty index for assessing band and scene-dependent radiometric uncertainties, (v) and use of a new 1 km cloud top pressure/temperature algorithm (also part of MOD06) for atmospheric corrections and low cloud non-unity emissivity temperature adjustments.

Spatial Surface PM2.5 Concentration Estimates for Wildfire Smoke Plumes in the Western U.S. Using Satellite Retrievals and Data Assimilation Techniques

NASA Astrophysics Data System (ADS)

Loria Salazar, S. M.; Holmes, H.

2015-12-01

Health effects studies of aerosol pollution have been extended spatially using data assimilation techniques that combine surface PM2.5 concentrations and Aerosol Optical Depth (AOD) from satellite retrievals. While most of these models were developed for the dark-vegetated eastern U.S. they are being used in the semi-arid western U.S. to remotely sense atmospheric aerosol concentrations. These models are helpful to understand the spatial variability of surface PM2.5concentrations in the western U.S. because of the sparse network of surface monitoring stations. However, the models developed for the eastern U.S. are not robust in the western U.S. due to different aerosol formation mechanisms, transport phenomena, and optical properties. This region is a challenge because of complex terrain, anthropogenic and biogenic emissions, secondary organic aerosol formation, smoke from wildfires, and low background aerosol concentrations. This research concentrates on the use and evaluation of satellite remote sensing to estimate surface PM2.5 concentrations from AOD satellite retrievals over California and Nevada during the summer months of 2012 and 2013. The aim of this investigation is to incorporate a spatial statistical model that uses AOD from AERONET as well as MODIS, surface PM2.5 concentrations, and land-use regression to characterize spatial surface PM2.5 concentrations. The land use regression model uses traditional inputs (e.g. meteorology, population density, terrain) and non-traditional variables (e.g. FIre Inventory from NCAR (FINN) emissions and MODIS albedo product) to account for variability related to smoke plume trajectories and land use. The results will be used in a spatially resolved health study to determine the association between wildfire smoke exposure and cardiorespiratory health endpoints. This relationship can be used with future projections of wildfire emissions related to climate change and droughts to quantify the expected health impact.

Towards better understanding of high-mountain cryosphere changes using GPM data: A Joint Snowfall and Snow-cover Passive Microwave Retrieval Algorithm

NASA Astrophysics Data System (ADS)

Ebtehaj, A.; Foufoula-Georgiou, E.

2016-12-01

Scientific evidence suggests that the duration and frequency of snowfall and the extent of snow cover are rapidly declining under global warming. Both precipitation and snow cover scatter the upwelling surface microwave emission and decrease the observed high-frequency brightness temperatures. The mixture of these two scattering signals is amongst the largest sources of ambiguities and errors in passive microwave retrievals of both precipitation and snow-cover. The dual frequency radar and the high-frequency radiometer on board the GPM satellite provide a unique opportunity to improve passive retrievals of precipitation and snow-cover physical properties and fill the gaps in our understating of their variability in view of climate change. Recently, a new Bayesian rainfall retrieval algorithm (called ShARP) was developed using modern approximation methods and shown to yield improvements against other algorithms in retrieval of rainfall over radiometrically complex land surfaces. However, ShARP uses a large database of input rainfall and output brightness temperatures, which might be undersampled. Furthermore, it is not capable to discriminate between solid and liquid phase of precipitation and specifically discriminate the background snow-cover emission and its contamination effects on the retrievals. We address these problems by extending it to a new Bayesian land-atmosphere retrieval framework (ShARP-L) that allows joint retrievals of atmospheric constituents and land surface physical properties. Using modern sparse approximation techniques, the database is reduced to atomic microwave signatures in a family of compact class consistent dictionaries. These dictionaries can efficiently represent the entire database and allow us to discriminate between different land-atmosphere states. First the algorithm makes use of the dictionaries to detect the phase of the precipitation and type of the land-cover and then it estimates the physical properties of precipitation and snow cover using an extended version of the Dantzig Selector, which is robust to non-Gaussian and correlated geophysical noise. Promising results are presented in retrievals of snowfall and snow-cover over coastal orographic features of North America's Coast Range and South America's Andes.

Analytical Retrieval of Global Land Surface Emissivity Maps at AMSR-E passive microwave frequencies

NASA Astrophysics Data System (ADS)

Norouzi, H.; Temimi, M.; Khanbilvardi, R.

2009-12-01

Land emissivity is a crucial boundary condition in Numerical Weather Prediction (NWP) modeling. Land emissivity is also a key indicator of land surface and subsurface properties. The objective of this study, supported by NOAA-NESDIS, is to develop global land emissivity maps using AMSR-E passive microwave measurements along with several ancillary data. The International Satellite Cloud Climatology Project (ISCCP) database has been used to obtain several inputs for the proposed approach such as land surface temperature, cloud mask and atmosphere profile. The Community Radiative Transfer Model (CRTM) has been used to estimate upwelling and downwelling atmospheric contributions. Although it is well known that correction of the atmospheric effect on brightness temperature is required at higher frequencies (over 19 GHz), our preliminary results have shown that a correction at 10.7 GHz is also necessary over specific areas. The proposed approach is based on three main steps. First, all necessary data have been collected and processed. Second, a global cloud free composite of AMSR-E data and corresponding ancillary images is created. Finally, monthly composting of emissivity maps has been performed. AMSR-E frequencies at 6.9, 10.7, 18.7, 36.5 and 89.0 GHz have been used to retrieve the emissivity. Water vapor information obtained from ISCCP (TOVS data) was used to calculate upwelling, downwelling temperatures and atmospheric transmission in order to assess the consistency of those derived from the CRTM model. The frequent land surface temperature (LST) determination (8 times a day) in the ISCCP database has allowed us to assess the diurnal cycle effect on emissivity retrieval. Differences in magnitude and phase between thermal temperature and low frequencies microwave brightness temperature have been noticed. These differences seem to vary in space and time. They also depend on soil texture and thermal inertia. The proposed methodology accounts for these factors and resultant differences in phase and magnitude between LST and microwave brightness temperature. Additional factors such as topography and vegetation cover are under investigation. In addition, the potential of extrapolating the obtained land emissivity maps to different window and sounding channels has been also investigated in this study. The extrapolation of obtained emissivities to different incident angles is also under investigation. Land emissivity maps have been developed at different AMSR-E frequencies. Obtained product has been validated and compared to global land use distribution. Moreover, global soil moisture AMSR-E product maps have been also used to assess to the spatial distribution of the emissivity. Moreover, obtained emissivity maps seem to be consistent with landuse/land cover maps. They also agree well with land emissivity maps obtained from the ISCCP database and developed using SSM/I observations (for frequencies over 19 GHz).

Improved MODIS aerosol retrieval in urban areas using a land classification approach and empirical orthogonal functions

NASA Astrophysics Data System (ADS)

Levitan, Nathaniel; Gross, Barry

2016-10-01

New, high-resolution aerosol products are required in urban areas to improve the spatial coverage of the products, in terms of both resolution and retrieval frequency. These new products will improve our understanding of the spatial variability of aerosols in urban areas and will be useful in the detection of localized aerosol emissions. Urban aerosol retrieval is challenging for existing algorithms because of the high spatial variability of the surface reflectance, indicating the need for improved urban surface reflectance models. This problem can be stated in the language of novelty detection as the problem of selecting aerosol parameters whose effective surface reflectance spectrum is not an outlier in some space. In this paper, empirical orthogonal functions, a reconstruction-based novelty detection technique, is used to perform single-pixel aerosol retrieval using the single angular and temporal sample provided by the MODIS sensor. The empirical orthogonal basis functions are trained for different land classes using the MODIS BRDF MCD43 product. Existing land classification products are used in training and aerosol retrieval. The retrieval is compared against the existing operational MODIS 3 KM Dark Target (DT) aerosol product and co-located AERONET data. Based on the comparison, our method allows for a significant increase in retrieval frequency and a moderate decrease in the known biases of MODIS urban aerosol retrievals.

Inverse modelling of CH4 emissions for 2010-2011 using different satellite retrieval products from GOSAT and SCIAMACHY

NASA Astrophysics Data System (ADS)

Alexe, M.; Bergamaschi, P.; Segers, A.; Detmers, R.; Butz, A.; Hasekamp, O.; Guerlet, S.; Parker, R.; Boesch, H.; Frankenberg, C.; Scheepmaker, R. A.; Dlugokencky, E.; Sweeney, C.; Wofsy, S. C.; Kort, E. A.

2015-01-01

At the beginning of 2009 new space-borne observations of dry-air column-averaged mole fractions of atmospheric methane (XCH4) became available from the Thermal And Near infrared Sensor for carbon Observations-Fourier Transform Spectrometer (TANSO-FTS) instrument on board the Greenhouse Gases Observing SATellite (GOSAT). Until April 2012 concurrent {methane (CH4) retrievals} were provided by the SCanning Imaging Absorption spectroMeter for Atmospheric CartograpHY (SCIAMACHY) instrument on board the ENVironmental SATellite (ENVISAT). The GOSAT and SCIAMACHY XCH4 retrievals can be compared during the period of overlap. We estimate monthly average CH4 emissions between January 2010 and December 2011, using the TM5-4DVAR inverse modelling system. In addition to satellite data, high-accuracy measurements from the Cooperative Air Sampling Network of the National Oceanic and Atmospheric Administration Earth System Research Laboratory (NOAA ESRL) are used, providing strong constraints on the remote surface atmosphere. We discuss five inversion scenarios that make use of different GOSAT and SCIAMACHY XCH4 retrieval products, including two sets of GOSAT proxy retrievals processed independently by the Netherlands Institute for Space Research (SRON)/Karlsruhe Institute of Technology (KIT), and the University of Leicester (UL), and the RemoTeC "Full-Physics" (FP) XCH4 retrievals available from SRON/KIT. The GOSAT-based inversions show significant reductions in the root mean square (rms) difference between retrieved and modelled XCH4, and require much smaller bias corrections compared to the inversion using SCIAMACHY retrievals, reflecting the higher precision and relative accuracy of the GOSAT XCH4. Despite the large differences between the GOSAT and SCIAMACHY retrievals, 2-year average emission maps show overall good agreement among all satellite-based inversions, with consistent flux adjustment patterns, particularly across equatorial Africa and North America. Over North America, the satellite inversions result in a significant redistribution of CH4 emissions from North-East to South-Central United States. This result is consistent with recent independent studies suggesting a systematic underestimation of CH4 emissions from North American fossil fuel sources in bottom-up inventories, likely related to natural gas production facilities. Furthermore, all four satellite inversions yield lower CH4 fluxes across the Congo basin compared to the NOAA-only scenario, but higher emissions across tropical East Africa. The GOSAT and SCIAMACHY inversions show similar performance when validated against independent shipboard and aircraft observations, and XCH4 retrievals available from the Total Carbon Column Observing Network (TCCON).

Retrieval and Validation of Aerosol Optical Depth by using the GF-1 Remote Sensing Data

NASA Astrophysics Data System (ADS)

Zhang, L.; Xu, S.; Wang, L.; Cai, K.; Ge, Q.

2017-05-01

Based on the characteristics of GF-1 remote sensing data, the method and data processing procedure to retrieve the Aerosol Optical Depth (AOD) are developed in this study. The surface contribution over dense vegetation and urban bright target areas are respectively removed by using the dark target and deep blue algorithms. Our method is applied for the three serious polluted Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD) and Pearl River Delta (PRD) regions. The retrieved AOD are validated by ground-based AERONET data from Beijing, Hangzhou, Hong Kong sites. Our results show that, 1) the heavy aerosol loadings are usually distributed in high industrial emission and dense populated cities, with the AOD value near 1. 2) There is a good agreement between satellite-retrievals and in-site observations, with the coefficient factors of 0.71 (BTH), 0.55 (YRD) and 0.54(PRD). 3) The GF-1 retrieval uncertainties are mainly from the impact of cloud contamination, high surface reflectance and assumed aerosol model.

Surface spectral emissivity derived from MODIS data

NASA Astrophysics Data System (ADS)

Chen, Yan; Sun-Mack, Sunny; Minnis, Patrick; Smith, William L.; Young, David F.

2003-04-01

Surface emissivity is essential for many remote sensing applications including the retrieval of the surface skin temperature from satellite-based infrared measurements, determining thresholds for cloud detection and for estimating the emission of longwave radiation from the surface, an important component of the energy budget of the surface-atmosphere interface. In this paper, data from the Terra MODIS (MODerate-resolution Imaging Spectroradiometer) taken at 3.7, 8.5, 10.8, 12.0 micron are used to simultaneously derive the skin temperature and the surface emissivities at the same wavelengths. The methodology uses separate measurements of the clear-sky temperatures that are determined by the CERES (Clouds and Earth's Radiant Energy System) scene classification in each channel during the daytime and at night. The relationships between the various channels at night are used during the day when solar reflectance affects the 3.7 micron data. A set of simultaneous equations is then solved to derive the emissivities. Global results are derived from MODIS. Numerical weather analyses are used to provide soundings for correcting the observed radiances for atmospheric absorption. These results are verified and will be available for remote sensing applications.

Least Square Approach for Estimating of Land Surface Temperature from LANDSAT-8 Satellite Data Using Radiative Transfer Equation

NASA Astrophysics Data System (ADS)

Jouybari-Moghaddam, Y.; Saradjian, M. R.; Forati, A. M.

2017-09-01

Land Surface Temperature (LST) is one of the significant variables measured by remotely sensed data, and it is applied in many environmental and Geoscience studies. The main aim of this study is to develop an algorithm to retrieve the LST from Landsat-8 satellite data using Radiative Transfer Equation (RTE). However, LST can be retrieved from RTE, but, since the RTE has two unknown parameters including LST and surface emissivity, estimating LST from RTE is an under the determined problem. In this study, in order to solve this problem, an approach is proposed an equation set includes two RTE based on Landsat-8 thermal bands (i.e.: band 10 and 11) and two additional equations based on the relation between the Normalized Difference Vegetation Index (NDVI) and emissivity of Landsat-8 thermal bands by using simulated data for Landsat-8 bands. The iterative least square approach was used for solving the equation set. The LST derived from proposed algorithm is evaluated by the simulated dataset, built up by MODTRAN. The result shows the Root Mean Squared Error (RMSE) is less than 1.18°K. Therefore; the proposed algorithm can be a suitable and robust method to retrieve the LST from Landsat-8 satellite data.

Evaluating a Priori Ozone Profile Information Used in TEMPO (Tropospheric Emissions: Monitoring of Pollution) Tropospheric Ozone Retrievals

NASA Technical Reports Server (NTRS)

Johnson, Matthew Stephen

2017-01-01

A primary objective for TOLNet is the evaluation and validation of space-based tropospheric O3 retrievals from future systems such as the Tropospheric Emissions: Monitoring of Pollution (TEMPO) satellite. This study is designed to evaluate the tropopause-based O3 climatology (TB-Clim) dataset which will be used as the a priori profile information in TEMPO O3 retrievals. This study also evaluates model simulated O3 profiles, which could potentially serve as a priori O3 profile information in TEMPO retrievals, from near-real-time (NRT) data assimilation model products (NASA Global Modeling and Assimilation Office (GMAO) Goddard Earth Observing System (GEOS-5) Forward Processing (FP) and Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA2)) and full chemical transport model (CTM), GEOS-Chem, simulations. The TB-Clim dataset and model products are evaluated with surface (0-2 km) and tropospheric (0-10 km) TOLNet observations to demonstrate the accuracy of the suggested a priori dataset and information which could potentially be used in TEMPO O3 algorithms. This study also presents the impact of individual a priori profile sources on the accuracy of theoretical TEMPO O3 retrievals in the troposphere and at the surface. Preliminary results indicate that while the TB-Clim climatological dataset can replicate seasonally-averaged tropospheric O3 profiles observed by TOLNet, model-simulated profiles from a full CTM (GEOS-Chem is used as a proxy for CTM O3 predictions) resulted in more accurate tropospheric and surface-level O3 retrievals from TEMPO when compared to hourly (diurnal cycle evaluation) and daily-averaged (daily variability evaluation) TOLNet observations. Furthermore, it was determined that when large daily-averaged surface O3 mixing ratios are observed (65 ppb), which are important for air quality purposes, TEMPO retrieval values at the surface display higher correlations and less bias when applying CTM a priori profile information compared to all other data products. The primary reason for this is that CTM predictions better capture the spatio-temporal variability of the vertical profiles of observed tropospheric O3 compared to the TB-Clim dataset and other NRT data assimilation models evaluated during this study.

Sensitivity of Satellite-Based Skin Temperature to Different Surface Emissivity and NWP Reanalysis Sources Demonstrated Using a Single-Channel, Viewing-Angle-Corrected Retrieval Algorithm

NASA Astrophysics Data System (ADS)

Scarino, B. R.; Minnis, P.; Yost, C. R.; Chee, T.; Palikonda, R.

2015-12-01

Single-channel algorithms for satellite thermal-infrared- (TIR-) derived land and sea surface skin temperature (LST and SST) are advantageous in that they can be easily applied to a variety of satellite sensors. They can also accommodate decade-spanning instrument series, particularly for periods when split-window capabilities are not available. However, the benefit of one unified retrieval methodology for all sensors comes at the cost of critical sensitivity to surface emissivity (ɛs) and atmospheric transmittance estimation. It has been demonstrated that as little as 0.01 variance in ɛs can amount to more than a 0.5-K adjustment in retrieved LST values. Atmospheric transmittance requires calculations that employ vertical profiles of temperature and humidity from numerical weather prediction (NWP) models. Selection of a given NWP model can significantly affect LST and SST agreement relative to their respective validation sources. Thus, it is necessary to understand the accuracies of the retrievals for various NWP models to ensure the best LST/SST retrievals. The sensitivities of the single-channel retrievals to surface emittance and NWP profiles are investigated using NASA Langley historic land and ocean clear-sky skin temperature (Ts) values derived from high-resolution 11-μm TIR brightness temperature measured from geostationary satellites (GEOSat) and Advanced Very High Resolution Radiometers (AVHRR). It is shown that mean GEOSat-derived, anisotropy-corrected LST can vary by up to ±0.8 K depending on whether CERES or MODIS ɛs sources are used. Furthermore, the use of either NOAA Global Forecast System (GFS) or NASA Goddard Modern-Era Retrospective Analysis for Research and Applications (MERRA) for the radiative transfer model initial atmospheric state can account for more than 0.5-K variation in mean Ts. The results are compared to measurements from the Surface Radiation Budget Network (SURFRAD), an Atmospheric Radiation Measurement (ARM) Program ground station, and NOAA ESRL high-resolution Optimum Interpolation SST (OISST). Precise understanding of the influence these auxiliary inputs have on final satellite-based Ts retrievals may help guide refinement in ɛs characterization and NWP development, e.g., future Goddard Earth Observing System Data Assimilation System versions.

Road Asphalt Pavements Analyzed by Airborne Thermal Remote Sensing: Preliminary Results of the Venice Highway.

PubMed

Pascucci, Simone; Bassani, Cristiana; Palombo, Angelo; Poscolieri, Maurizio; Cavalli, Rosa

2008-02-22

This paper describes a fast procedure for evaluating asphalt pavement surface defects using airborne emissivity data. To develop this procedure, we used airborne multispectral emissivity data covering an urban test area close to Venice (Italy).For this study, we first identify and select the roads' asphalt pavements on Multispectral Infrared Visible Imaging Spectrometer (MIVIS) imagery using a segmentation procedure. Next, since in asphalt pavements the surface defects are strictly related to the decrease of oily components that cause an increase of the abundance of surfacing limestone, the diagnostic absorption emissivity peak at 11.2μm of the limestone was used for retrieving from MIVIS emissivity data the areas exhibiting defects on asphalt pavements surface.The results showed that MIVIS emissivity allows establishing a threshold that points out those asphalt road sites on which a check for a maintenance intervention is required. Therefore, this technique can supply local government authorities an efficient, rapid and repeatable road mapping procedure providing the location of the asphalt pavements to be checked.

Roughness effects on thermal-infrared emissivities estimated from remotely sensed images

NASA Astrophysics Data System (ADS)

Mushkin, Amit; Danilina, Iryna; Gillespie, Alan R.; Balick, Lee K.; McCabe, Matthew F.

2007-10-01

Multispectral thermal-infrared images from the Mauna Loa caldera in Hawaii, USA are examined to study the effects of surface roughness on remotely retrieved emissivities. We find up to a 3% decrease in spectral contrast in ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) 90-m/pixel emissivities due to sub-pixel surface roughness variations on the caldera floor. A similar decrease in spectral contrast of emissivities extracted from MASTER (MODIS/ASTER Airborne Simulator) ~12.5-m/pixel data can be described as a function of increasing surface roughness, which was measured remotely from ASTER 15-m/pixel stereo images. The ratio between ASTER stereo images provides a measure of sub-pixel surface-roughness variations across the scene. These independent roughness estimates complement a radiosity model designed to quantify the unresolved effects of multiple scattering and differential solar heating due to sub-pixel roughness elements and to compensate for both sub-pixel temperature dispersion and cavity radiation on TIR measurements.

An Overview of Plume Tracker: Mapping Volcanic Emissions with Interactive Radiative Transfer Modeling

NASA Astrophysics Data System (ADS)

Realmuto, V. J.; Berk, A.; Guiang, C.

2014-12-01

Infrared remote sensing is a vital tool for the study of volcanic plumes, and radiative transfer (RT) modeling is required to derive quantitative estimation of the sulfur dioxide (SO2), sulfate aerosol (SO4), and silicate ash (pulverized rock) content of these plumes. In the thermal infrared, we must account for the temperature, emissivity, and elevation of the surface beneath the plume, plume altitude and thickness, and local atmospheric temperature and humidity. Our knowledge of these parameters is never perfect, and interactive mapping allows us to evaluate the impact of these uncertainties on our estimates of plume composition. To enable interactive mapping, the Jet Propulsion Laboratory is collaborating with Spectral Sciences, Inc., (SSI) to develop the Plume Tracker toolkit. This project is funded by a NASA AIST Program Grant (AIST-11-0053) to SSI. Plume Tracker integrates (1) retrieval procedures for surface temperature and emissivity, SO2, NH3, or CH4 column abundance, and scaling factors for H2O vapor and O3 profiles, (2) a RT modeling engine based on MODTRAN, and (3) interactive visualization and analysis utilities under a single graphics user interface. The principal obstacle to interactive mapping is the computational overhead of the RT modeling engine. Under AIST-11-0053 we have achieved a 300-fold increase in the performance of the retrieval procedures through the use of indexed caches of model spectra, optimization of the minimization procedures, and scaling of the effects of surface temperature and emissivity on model radiance spectra. In the final year of AIST-11-0053 we will implement parallel processing to exploit multi-core CPUs and cluster computing, and optimize the RT engine to eliminate redundant calculations when iterating over a range of gas concentrations. These enhancements will result in an additional 8 - 12X increase in performance. In addition to the improvements in performance, we have improved the accuracy of the Plume Tracker retrievals through refinements in the description of surface emissivity and use of vector projection to define the misfit between model and observed spectra. Portions of this research were conducted at the Jet Propulsion Laboratory, California Institute of Technology, under contract to the National Aeronautics and Space Administration.

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.

Temperature and dust profiles in Martian dust storm conditions retrieved from Mars Climate Sounder measurements

NASA Astrophysics Data System (ADS)

Kleinboehl, A.; Kass, D. M.; Schofield, J. T.; McCleese, D. J.

2013-12-01

Mars Climate Sounder (MCS) is a mid- and far-infrared thermal emission radiometer on board the Mars Reconnaissance Orbiter. It measures radiances in limb and nadir/on-planet geometry from which vertical profiles of atmospheric temperature, water vapor, dust and condensates can be retrieved in an altitude range from 0 to 80 km and with a vertical resolution of ~5 km. Due to the limb geometry used as the MCS primary observation mode, retrievals in conditions with high aerosol loading are challenging. We have developed several modifications to the MCS retrieval algorithm that will facilitate profile retrievals in high-dust conditions. Key modifications include a retrieval option that uses a surface pressure climatology if a pressure retrieval is not possible in high dust conditions, an extension of aerosol retrievals to higher altitudes, and a correction to the surface temperature climatology. In conditions of a global dust storm, surface temperatures tend to be lower compared to standard conditions. Taking this into account using an adaptive value based on atmospheric opacity leads to improved fits to the radiances measured by MCS and improves the retrieval success rate. We present first results of these improved retrievals during the global dust storm in 2007. Based on the limb opacities observed during the storm, retrievals are typically possible above ~30 km altitude. Temperatures around 240 K are observed in the middle atmosphere at mid- and high southern latitudes after the onset of the storm. Dust appears to be nearly homogeneously mixed at lower altitudes. Significant dust opacities are detected at least up to 70 km altitude. During much of the storm, in particular at higher altitudes, the retrieved dust profiles closely resemble a Conrath-profile.

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.

Modeling the diurnal variability of agricultural ammonia in Bakersfield, California, during the CalNex campaign

NASA Astrophysics Data System (ADS)

Lonsdale, Chantelle R.; Hegarty, Jennifer D.; Cady-Pereira, Karen E.; Alvarado, Matthew J.; Henze, Daven K.; Turner, Matthew D.; Capps, Shannon L.; Nowak, John B.; Neuman, J. Andy; Middlebrook, Ann M.; Bahreini, Roya; Murphy, Jennifer G.; Markovic, Milos Z.; VandenBoer, Trevor C.; Russell, Lynn M.; Scarino, Amy Jo

2017-02-01

NH3 retrievals from the NASA Tropospheric Emission Spectrometer (TES), as well as surface and aircraft observations of NH3(g) and submicron NH4(p), are used to evaluate modeled concentrations of NH3(g) and NH4(p) from the Community Multiscale Air Quality (CMAQ) model in the San Joaquin Valley (SJV) during the California Research at the Nexus of Air Quality and Climate Change (CalNex) campaign. We find that simulations of NH3 driven with the California Air Resources Board (CARB) emission inventory are qualitatively and spatially consistent with TES satellite observations, with a correlation coefficient (r2) of 0.64. However, the surface observations at Bakersfield indicate a diurnal cycle in the model bias, with CMAQ overestimating surface NH3 at night and underestimating it during the day. The surface, satellite, and aircraft observations all suggest that daytime NH3 emissions in the CARB inventory are underestimated by at least a factor of 2, while the nighttime overestimate of NH3(g) is likely due to a combination of overestimated NH3 emissions and underestimated deposition.Running CMAQ v5.0.2 with the bi-directional NH3 scheme reduces NH3 concentrations at night and increases them during the day. This reduces the model bias when compared to the surface and satellite observations, but the increased concentrations aloft significantly increase the bias relative to the aircraft observations. We attempt to further reduce model bias by using the surface observations at Bakersfield to derive an empirical diurnal cycle of NH3 emissions in the SJV, in which nighttime and midday emissions differ by about a factor of 4.5. Running CMAQv5.0.2 with a bi-directional NH3 scheme together with this emissions diurnal profile further reduces model bias relative to the surface observations. Comparison of these simulations with the vertical profile retrieved by TES shows little bias except for the lowest retrieved level, but the model bias relative to flight data aloft increases slightly. Our results indicate that both diurnally varying emissions and a bi-directional NH3 scheme should be applied when modeling NH3(g) and NH4(p) in this region. The remaining model errors suggest that the bi-directional NH3 scheme in CMAQ v5.0.2 needs further improvements to shift the peak NH3 land-atmosphere flux to earlier in the day. We recommend that future work include updates to the current CARB NH3 inventory to account for NH3 from fertilizer application, livestock, and other farming practices separately; adding revised information on crop management practices specific to the SJV region to the bi-directional NH3 scheme; and top-down studies focused on determining the diurnally varying biases in the canopy compensation point that determines the net land-atmosphere NH3 fluxes.

Frequency and Angular Variations of Land Surface Microwave Emissivities: Can we Estimate SSM/T and AMSU Emissivities from SSM/I Emissivities?

NASA Technical Reports Server (NTRS)

Prigent, Catherine; Wigneron, Jean-Pierre; Rossow, William B.; Pardo-Carrion, Juan R.

1999-01-01

To retrieve temperature and humidity profiles from SSM/T and AMSU, it is important to quantify the contribution of the Earth surface emission. So far, no global estimates of the land surface emissivities are available at SSM/T and AMSU frequencies and scanning conditions. The land surface emissivities have been previously calculated for the globe from the SSM/I conical scanner between 19 and 85 GHz. To analyze the feasibility of deriving SSM/T and AMSU land surface emissivities from SSM/I emissivities, the spectral and angular variations of the emissivities are studied, with the help of ground-based measurements, models and satellite estimates. Up to 100 GHz, for snow and ice free areas, the SSM/T and AMSU emissivities can be derived with useful accuracy from the SSM/I emissivities- The emissivities can be linearly interpolated in frequency. Based on ground-based emissivity measurements of various surface types, a simple model is proposed to estimate SSM/T and AMSU emissivities for all zenith angles knowing only the emissivities for the vertical and horizontal polarizations at 53 deg zenith angle. The method is tested on the SSM/T-2 91.655 GHz channels. The mean difference between the SSM/T-2 and SSM/I-derived emissivities is less than or equal to 0.01 for all zenith angles with an r.m.s. difference of approx. = 0.02. Above 100 GHz, preliminary results are presented at 150 GHz, based on SSM/T-2 observations and are compared with the very few estimations available in the literature.

Surface-induced brightness temperature variations and their effects on detecting thin cirrus clouds using IR emission channels in the 8-12 microns region

NASA Technical Reports Server (NTRS)

Gao, Bo-Cai; Wiscombe, W. J.

1994-01-01

A method for detecting cirrus clouds in terms of brightness temperature differences between narrowbands at 8, 11, and 12 microns has been proposed by Ackerman et al. In this method, the variation of emissivity with wavelength for different surface targets was not taken into consideration. Based on state-of-the-art laboratory measurements of reflectance spectra of terrestrial materials by Salisbury and D'Aria, it is found that the brightness temperature differences between the 8- and 11-microns bands for soils, rocks, and minerals, and dry vegetation can vary between approximately -8 and +8 K due solely to surface emissivity variations. The large brightness temperature differences are sufficient to cause false detection of cirrus clouds from remote sensing data acquired over certain surface targets using the 8-11-12-microns method directly. It is suggested that the 8-11-12-microns method should be improved to include the surface emissivity effects. In addition, it is recommended that in the future the variation of surface emissivity with wavelength should be taken into account in algorithms for retrieving surface temperatures and low-level atmospheric temperature and water vapor profiles.

Recent advances in the salinity retrieval algorithms for Aquarius and Soil Moisture Active Passive (SMAP)

NASA Astrophysics Data System (ADS)

Meissner, Thomas; Wentz, Frank; Lee, Tong

2017-04-01

Our presentation discusses the latest improvements in the salinity retrievals both for Aquarius and Soil Moisture Active-Passive (SMAP) since the last releases. The Aquarius V4.0 was released in June 2015. The final V5.0 release is planned for late 2017. SMAP V 2.0 has been released in September 2016. We will present validation results for both Aquarius V5.0 pre-release and SMAP V2.0 salinity comparing with near-surface salinity measurements from Argo floats. We show that salty biases at higher northern latitudes in Aquarius V4.0 can be explained by inaccuracy in the model used in correcting for the absorption by atmospheric oxygen. These biases will be mitigated in V5.0 by fine-tuning the parameters in the oxygen absorption model. The full 360-degree look capability of SMAP makes it possible to take observations from the forward and backward looking direction at the same instance of time. This two-look capability aids the salinity retrievals. One of the largest spurious contaminations in the salinity retrievals is caused by the galactic reflection from the ocean surface. Because in most instances the reflected galaxy appears only in either the forward or the backward look, it is possible to determine its contribution by taking the difference of the measured SMAP brightness temperatures between the two looks. Our result suggests that the surface roughness that is used in the galactic correction needs to be increased and also the estimated strength of some of the galactic sources need to be slightly adjusted. The improved galaxy correction has been implemented in SMAP V2.0 retrieval and will be included in Aquarius V5.0 as well. It helps the mitigation of residual zonal and temporal biases that were present in both products. Another major cause of the observed zonal biases in SMAP is the emissive SMAP mesh antenna. In order to correct for it, an accurate knowledge of the emissivity of the antenna and its physical temperature are required. We discuss the improvements in the correction for the emissive SMAP antenna in SMAP V2.0 over V1.0.

Atmospheric Compensation and Surface Temperature and Emissivity Retrieval with LWIR Hyperspectral Imagery

NASA Astrophysics Data System (ADS)

Pieper, Michael

Accurate estimation or retrieval of surface emissivity spectra from long-wave infrared (LWIR) or Thermal Infrared (TIR) hyperspectral imaging data acquired by airborne or space-borne sensors is necessary for many scientific and defense applications. The at-aperture radiance measured by the sensor is a function of the ground emissivity and temperature, modified by the atmosphere. Thus the emissivity retrieval process consists of two interwoven steps: atmospheric compensation (AC) to retrieve the ground radiance from the measured at-aperture radiance and temperature-emissivity separation (TES) to separate the temperature and emissivity from the ground radiance. In-scene AC (ISAC) algorithms use blackbody-like materials in the scene, which have a linear relationship between their ground radiances and at-aperture radiances determined by the atmospheric transmission and upwelling radiance. Using a clear reference channel to estimate the ground radiance, a linear fitting of the at-aperture radiance and estimated ground radiance is done to estimate the atmospheric parameters. TES algorithms for hyperspectral imaging data assume that the emissivity spectra for solids are smooth compared to the sharp features added by the atmosphere. The ground temperature and emissivity are found by finding the temperature that provides the smoothest emissivity estimate. In this thesis we develop models to investigate the sensitivity of AC and TES to the basic assumptions enabling their performance. ISAC assumes that there are perfect blackbody pixels in a scene and that there is a clear channel, which is never the case. The developed ISAC model explains how the quality of blackbody-like pixels affect the shape of atmospheric estimates and the clear channel assumption affects their magnitude. Emissivity spectra for solids usually have some roughness. The TES model identifies four sources of error: the smoothing error of the emissivity spectrum, the emissivity error from using the incorrect temperature, and the errors caused by sensor noise and wavelength calibration. The ways these errors interact determines the overall TES performance. Since the AC and TES processes are interwoven, any errors in AC are transferred to TES and the final temperature and emissivity estimates. Combining the two models, shape errors caused by the blackbody assumption are transferred to the emissivity estimates, where magnitude errors from the clear channel assumption are compensated by TES temperature induced emissivity errors. The ability for the temperature induced error to compensate for such atmospheric errors makes it difficult to determine the correct atmospheric parameters for a scene. With these models we are able to determine the expected quality of estimated emissivity spectra based on the quality of blackbody-like materials on the ground, the emissivity of the materials being searched for, and the properties of the sensor. The quality of material emissivity spectra is a key factor in determining detection performance for a material in a scene.

Methane from the Tropospheric Emission Spectrometer (TES)

NASA Technical Reports Server (NTRS)

Payne, Vivienne; Worden, John; Kulawik, Susan; Frankenberg, Christian; Bowman, Kevin; Wecht, Kevin

2012-01-01

TES V5 CH4 captures latitudinal gradients, regional variability and interannual variation in the free troposphere. V5 joint retrievals offer improved sensitivity to lower troposphere. Time series extends from 2004 to present. V5 reprocessing in progress. Upper tropospheric bias. Mitigated by N2O correction. Appears largely spatially uniform, so can be corrected. How to relate free-tropospheric values to surface emissions.

Improvement of Aerosol Optical Depth Retrieval over Hong Kong from a Geostationary Meteorological Satellite Using Critical Reflectance with Background Optical Depth Correction

NASA Technical Reports Server (NTRS)

Kim, Mijin; Kim, Jhoon; Wong, Man Sing; Yoon, Jongmin; Lee, Jaehwa; Wu, Dong L.; Chan, P.W.; Nichol, Janet E.; Chung, Chu-Yong; Ou, Mi-Lim

2014-01-01

Despite continuous efforts to retrieve aerosol optical depth (AOD) using a conventional 5-channelmeteorological imager in geostationary orbit, the accuracy in urban areas has been poorer than other areas primarily due to complex urban surface properties and mixed aerosol types from different emission sources. The two largest error sources in aerosol retrieval have been aerosol type selection and surface reflectance. In selecting the aerosol type from a single visible channel, the season-dependent aerosol optical properties were adopted from longterm measurements of Aerosol Robotic Network (AERONET) sun-photometers. With the aerosol optical properties obtained fromthe AERONET inversion data, look-up tableswere calculated by using a radiative transfer code: the Second Simulation of the Satellite Signal in the Solar Spectrum (6S). Surface reflectance was estimated using the clear sky composite method, awidely used technique for geostationary retrievals. Over East Asia, the AOD retrieved from the Meteorological Imager showed good agreement, although the values were affected by cloud contamination errors. However, the conventional retrieval of the AOD over Hong Kong was largely underestimated due to the lack of information on the aerosol type and surface properties. To detect spatial and temporal variation of aerosol type over the area, the critical reflectance method, a technique to retrieve single scattering albedo (SSA), was applied. Additionally, the background aerosol effect was corrected to improve the accuracy of the surface reflectance over Hong Kong. The AOD retrieved froma modified algorithmwas compared to the collocated data measured by AERONET in Hong Kong. The comparison showed that the new aerosol type selection using the critical reflectance and the corrected surface reflectance significantly improved the accuracy of AODs in Hong Kong areas,with a correlation coefficient increase from0.65 to 0.76 and a regression line change from tMI [basic algorithm] = 0.41tAERONET + 0.16 to tMI [new algorithm] = 0.70tAERONET + 0.01.

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.

Incorporating GOES Satellite Photosynthetically Active Radiation (PAR) Retrievals to Improve Biogenic Emission Estimates in Texas

NASA Astrophysics Data System (ADS)

Zhang, Rui; White, Andrew T.; Pour Biazar, Arastoo; McNider, Richard T.; Cohan, Daniel S.

2018-01-01

This study examines the influence of insolation and cloud retrieval products from the Geostationary Operational Environmental Satellite (GOES) system on biogenic emission estimates and ozone simulations in Texas. Compared to surface pyranometer observations, satellite-retrieved insolation and photosynthetically active radiation (PAR) values tend to systematically correct the overestimation of downwelling shortwave radiation in the Weather Research and Forecasting (WRF) model. The correlation coefficient increases from 0.93 to 0.97, and the normalized mean error decreases from 36% to 21%. The isoprene and monoterpene emissions estimated by the Model of Emissions of Gases and Aerosols from Nature are on average 20% and 5% less, respectively, when PAR from the direct satellite retrieval is used rather than the control WRF run. The reduction in biogenic emission rates using satellite PAR reduced the predicted maximum daily 8 h ozone concentration by up to 5.3 ppbV over the Dallas-Fort Worth (DFW) region on some days. However, episode average ozone response is less sensitive, with a 0.6 ppbV decrease near DFW and 0.3 ppbV increase over East Texas. The systematic overestimation of isoprene concentrations in a WRF control case is partially corrected by using satellite PAR, which observes more clouds than are simulated by WRF. Further, assimilation of GOES-derived cloud fields in WRF improved CAMx model performance for ground-level ozone over Texas. Additionally, it was found that using satellite PAR improved the model's ability to replicate the spatial pattern of satellite-derived formaldehyde columns and aircraft-observed vertical profiles of isoprene.

Characterization of Different Land Classes and Disaster Monitoring Using Microwave Land Emissivity for the Indian Subcontinent

NASA Astrophysics Data System (ADS)

Saha, Korak; Raju, Suresh; Antony, Tinu; Krishna Moorthy, K.

Despite the ability of satellite borne microwave radiometers to measure the atmospheric pa-rameters, liquid water and the microphysical properties of clouds, they have serious limitations over the land owing its large and spatially heterogeneous emissivity compared to the relatively low and homogenous oceans. This calls for determination of the spatial maps of land-surface emissivity with accuracies better than ˜2%. In this study, the characterization of microwave emissivity of different land surface classes over the Indian region is carried out with the forth-coming Indo-French microwave satellite program Megha-Tropiques in focus. The land emissivity is retrieved using satellite microwave radiometer data from Special Sensor Microwave/Imager (SSM/I) and TRMM Microwave Imager (TMI) at 10, 19, 22, 37 and 85 GHz. After identify-ing the clear sky daily data, the microwave radiative transfer computation, is applied to the respective daily atmospheric profile for deducing the upwelling and downwelling atmospheric radiations. This, along with the skin temperature data, is used to retrieve land emission from satellites data. The emissivity maps of placecountry-regionIndia for three months representing winter (January) and post-monsoon (September-October) seasons of 2008 at V and H polar-izations of all the channels (except for 22 GHz) are generated. Though the land emissivity values in V-polarization vary between 0.5 and ˜1, some land surface classes such as the desert region, marshy land, fresh snow covered region and evergreen forest region, etc, show distinct emissivity characteristics. On this basis few typical classes having uniform physical properties over sufficient area are identified. Usually the Indian desert region is dry and shows low emis-sivity (˜0.88 in H-polarisation) and high polarization difference, V-H (˜0.1). Densely vegetated zones of tropical rain forests exhibit high emissivity values (˜0.95) and low polarization dif-ference (lt;0.01). The mangrove forest region and marshy areas exhibit very low emissivities (˜0.8) with very high polarization difference (˜0.2). The usefulness of microwave emissivity to identify and quantify natural disasters such as the inundated regions in the vast Ganga basin during the severe floods in 2008 over country-regionIndia and placecountry-regionBangladesh is also demonstrated as a case study Keywords: Land surface emissivity, Microwave Remote sensing, Megha-Tropiques, Disaster monitoring *corresponding author: koraksaha@gmail.com

Methods for LWIR Radiometric Calibration and Characterization

NASA Technical Reports Server (NTRS)

Ryan, Robert; Harrington, Gary; Howell, Dane; Pagnutti, Mary; Zanoni, Vicki

2002-01-01

The utility of a remote sensing system increases with its ability to retrieve surface temperature or radiance accurately. Research applications, such as sea temperature and power plant discharge, require a 0.2 C resolution or better for absolute temperature retrievals. Other applications, including agriculture water stress detection, require at least a 1 C resolution. To achieve these levels of accuracy routinely, scientists must perform laboratory and onboard calibration, as well as in-flight vicarious radiometric characterization. A common approach used for in-flight radiometric characterization incorporates a well-calibrated infrared radiometer that is mounted on a bouy and placed on a uniform water body. The radiometer monitors radiant temperature along with pressure, humidity, and temperature measurements of an associated column of atmosphere. On very still waters, however, a buoy can significantly distrub these measurements. Researchers at NASA's Stennis Space Center (SSC) have developed a novel approach of using an uncooled infrared camera mounted on a boom to quantify buoy effects. Another critical aspect of using buoy-mounted infrared radiometers is the need for extensive laboratory characterization of the instruments' radiometric sensitivity, field of view, and spectral response. Proper surface temperature retrieval also requires detailed knowledge of both the upward emission and the reflected sky emission. Recent work at SSC has demonstrated that the use of a polarization-based radiometer operating at the Brewster angle can greatly simplify temperature retrieval as well as improve overall accuracy.

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,

Surface Emissivity Maps for Satellite Retrieval of the Longwave Radiation Budget

NASA Technical Reports Server (NTRS)

Gupta, Shashi K.; Wilber, Anne C.; Kratz, David P.

1999-01-01

This paper presents a brief description of the procedure used to produce global surface emissivity maps for the broadband LW, the 8-12 micrometer window, and 12 narrow LW bands. For a detailed description of the methodology and the input data, the reader is referred to Wilber et al. (1999). These maps are based on a time-independent surface type map published by the IGBP, and laboratory measurements of spectral reflectances of surface materials. These maps represent a first attempt to characterize emissivity based on surface types, and many improvements to the methodology presented here are already underway. Effects of viewing zenith angle and sea state on the emissivity of ocean surface (Smith et al. 1996, Wu and Smith 1997, Masuda et al. 1988) will be taken into account. Measurements form ASTER and MODIS will be incorporated as they become available. Seasonal variation of emissivity based on changes in the characteristics of vegetation will be considered, and the variability of emissivity of barren land areas will be accounted for with the use of Zobler World Soil Maps (Zobler 1986). The current maps have been made available to the scientific community from the web site: http://tanalo.larc.nasa.gov:8080/surf_htmls/ SARB_surf.html

Solfatara Crater Seen Through Hyperspectral Dais Sensor Data In The Tir Region: Temperature Map and Spectral Emissivity Image For Mineralogical Species Identification.

NASA Astrophysics Data System (ADS)

Merucci, L.; Buongiorno, M. F.; Teggi, S.; Bogliolo, M. P.

Temperature map and spectral emissivity have been retrieved by means of the TIR re- gion data collected by the DAIS airborne hyperspectral sensor on the Solfatara, Campi Flegrei, Italy, during the July 27, 1997 flight. During the 7915 DAIS flight a contem- poraneous field campaign was carried out in order to measure the surface temperature in the Solfatara crater and a radiosonde has been launched to measure the local at- mospheric profile. A normalized vegetation index filter has been used to select in the Solfatara crater scene the areas not covered by vegetation upon which the temperature and emissivity retrieval algorithms have been applied. The atmospheric contribute has been estimated by means of the MODTRAN radiative transfer code. The temperature map has been finally validated with the field measurements and the spectral emissivity image has been compared with the spectra available for the mineralogical species that cover the Solfatara crater.

Road Asphalt Pavements Analyzed by Airborne Thermal Remote Sensing: Preliminary Results of the Venice Highway

PubMed Central

Pascucci, Simone; Bassani, Cristiana; Palombo, Angelo; Poscolieri, Maurizio; Cavalli, Rosa

2008-01-01

This paper describes a fast procedure for evaluating asphalt pavement surface defects using airborne emissivity data. To develop this procedure, we used airborne multispectral emissivity data covering an urban test area close to Venice (Italy).For this study, we first identify and select the roads' asphalt pavements on Multispectral Infrared Visible Imaging Spectrometer (MIVIS) imagery using a segmentation procedure. Next, since in asphalt pavements the surface defects are strictly related to the decrease of oily components that cause an increase of the abundance of surfacing limestone, the diagnostic absorption emissivity peak at 11.2μm of the limestone was used for retrieving from MIVIS emissivity data the areas exhibiting defects on asphalt pavements surface.The results showed that MIVIS emissivity allows establishing a threshold that points out those asphalt road sites on which a check for a maintenance intervention is required. Therefore, this technique can supply local government authorities an efficient, rapid and repeatable road mapping procedure providing the location of the asphalt pavements to be checked. PMID:27879765

Development of a modified two-scale electromagnetic model simulating both active and passive microwave measurements: Comparison to data remotely sensed over the ocean

NASA Astrophysics Data System (ADS)

Boukabara, S. A.; Eymard, L.; Guillou, C.; Lemaire, D.; Sobieski, P.; Guissard, A.

2002-08-01

Spaceborne microwave remote sensing allows the determination of oceanic and atmospheric parameters. Operational payloads such as ERS-1 and ERS-2 and TOPEX/Poseidon as well as missions such as Jason (from NASA-Centre National d'Etudes) or Envisat (from the European Space Agency), have contained or contain paired microwave instruments looking at the nadir direction. This combination consists of microwave radiometers and a radar-altimeter. For the frequencies chosen in oceanographic satellite payloads, the active mode signal is mostly dependent on the surface state through its reflectivity and thus used for the near-surface wind speed retrieval. The active mode can also be attenuated by the atmosphere. On the other hand, the passive mode is related to the surface emissivity and the atmospheric radiation through the radiative transfer equation. Until now, the oceanic and atmospheric parameters have been retrieved separately, the latter being used to correct radar measurements. However, the reflectivity and the emissivity of a target are not independent quantities; hence the synergistic use of these two kinds of microwave measurements should allow one to improve the retrieval quality of the sea and atmosphere parameters. For this purpose, a unified model has been developed for the simulation of both the microwave backscattering coefficient σ° (active measurement) and the microwave emissivity, an important factor for the brightness temperature TB simulation, for every configuration (incidence angles, frequency, polarizations), taking into account the fact that the reflectivity and the emissivity are complementary to unity. The atmospheric absorption is computed following a widely used model from the literature. This paper gives a description and a first attempt of validation of this approach through a comparison with real data. The performance of the model is assessed by comparing the simulations to both brightness temperatures and backscattering coefficients from ERS-1 and TOPEX/Poseidon's instruments during the SEMAPHORE experiment, over a two-month period.

Surface emissivity and temperature retrieval for a hyperspectral sensor

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

Borel, C.C.

1998-12-01

With the growing use of hyper-spectral imagers, e.g., AVIRIS in the visible and short-wave infrared there is hope of using such instruments in the mid-wave and thermal IR (TIR) some day. The author believes that this will enable him to get around using the present temperature-emissivity separation algorithms using methods which take advantage of the many channels available in hyper-spectral imagers. A simple fact used in coming up with a novel algorithm is that a typical surface emissivity spectrum are rather smooth compared to spectral features introduced by the atmosphere. Thus, a iterative solution technique can be devised which retrievesmore » emissivity spectra based on spectral smoothness. To make the emissivities realistic, atmospheric parameters are varied using approximations, look-up tables derived from a radiative transfer code and spectral libraries. One such iterative algorithm solves the radiative transfer equation for the radiance at the sensor for the unknown emissivity and uses the blackbody temperature computed in an atmospheric window to get a guess for the unknown surface temperature. By varying the surface temperature over a small range a series of emissivity spectra are calculated. The one with the smoothest characteristic is chosen. The algorithm was tested on synthetic data using MODTRAN and the Salisbury emissivity database.« less

Improved Surface and Tropospheric Temperatures Determined Using Only Shortwave Channels: The AIRS Science Team Version-6 Retrieval Algorithm

NASA Technical Reports Server (NTRS)

Susskind, Joel; Blaisdell, John; Iredell, Lena

2011-01-01

The Goddard DISC has generated products derived from AIRS/AMSU-A observations, starting from September 2002 when the AIRS instrument became stable, using the AIRS Science Team Version-5 retrieval algorithm. The AIRS Science Team Version-6 retrieval algorithm will be finalized in September 2011. This paper describes some of the significant improvements contained in the Version-6 retrieval algorithm, compared to that used in Version-5, with an emphasis on the improvement of atmospheric temperature profiles, ocean and land surface skin temperatures, and ocean and land surface spectral emissivities. AIRS contains 2378 spectral channels covering portions of the spectral region 650 cm(sup -1) (15.38 micrometers) - 2665 cm(sup -1) (3.752 micrometers). These spectral regions contain significant absorption features from two CO2 absorption bands, the 15 micrometers (longwave) CO2 band, and the 4.3 micrometers (shortwave) CO2 absorption band. There are also two atmospheric window regions, the 12 micrometer - 8 micrometer (longwave) window, and the 4.17 micrometer - 3.75 micrometer (shortwave) window. Historically, determination of surface and atmospheric temperatures from satellite observations was performed using primarily observations in the longwave window and CO2 absorption regions. According to cloud clearing theory, more accurate soundings of both surface skin and atmospheric temperatures can be obtained under partial cloud cover conditions if one uses observations in longwave channels to determine coefficients which generate cloud cleared radiances R(sup ^)(sub i) for all channels, and uses R(sup ^)(sub i) only from shortwave channels in the determination of surface and atmospheric temperatures. This procedure is now being used in the AIRS Version-6 Retrieval Algorithm. Results are presented for both daytime and nighttime conditions showing improved Version-6 surface and atmospheric soundings under partial cloud cover.

Finding Blackbody Temperature and Emissivity on a Sub-Pixel Scale

NASA Astrophysics Data System (ADS)

Bernstein, D. J.; Bausell, J.; Grigsby, S.; Kudela, R. M.

2015-12-01

Surface temperature and emissivity provide important insight into the ecosystem being remotely sensed. Dozier (1981) proposed a an algorithm to solve for percent coverage and temperatures of two different surface types (e.g. sea surface, cloud cover, etc.) within a given pixel, with a constant value for emissivity assumed. Here we build on Dozier (1981) by proposing an algorithm that solves for both temperature and emissivity of a water body within a satellite pixel by assuming known percent coverage of surface types within the pixel. Our algorithm generates thermal infrared (TIR) and emissivity end-member spectra for the two surface types. Our algorithm then superposes these end-member spectra on emissivity and TIR spectra emitted from four pixels with varying percent coverage of different surface types. The algorithm was tested preliminarily (48 iterations) using simulated pixels containing more than one surface type, with temperature and emissivity percent errors of ranging from 0 to 1.071% and 2.516 to 15.311% respectively[1]. We then tested the algorithm using a MASTER image from MASTER collected as part of the NASA Student Airborne Research Program (NASA SARP). Here the temperature of water was calculated to be within 0.22 K of in situ data. The algorithm calculated emissivity of water with an accuracy of 0.13 to 1.53% error for Salton Sea pixels collected with MASTER, also collected as part of NASA SARP. This method could improve retrievals for the HyspIRI sensor. [1] Percent error for emissivity was generated by averaging percent error across all selected bands widths.

Satellite Observations of Tropospheric Ammonia

NASA Astrophysics Data System (ADS)

Shephard, M. W.; Luo, M.; Rinsland, C. P.; Cady-Pereira, K. E.; Beer, R.; Pinder, R. W.; Henze, D.; Payne, V. H.; Clough, S.; Rodgers, C. D.; Osterman, G. B.; Bowman, K. W.; Worden, H. M.

2008-12-01

Global high-spectral resolution (0.06 cm-1) nadir measurements from TES-Aura enable the simultaneous retrieval of a number of tropospheric pollutants and trace gases in addition to the TES standard operationally retrieved products (e.g. carbon monoxide, ozone). Ammonia (NH3) is one of the additional species that can be retrieved in conjunction with the TES standard products, and is important for local, regional, and global tropospheric chemistry studies. Ammonia emissions contribute significantly to several well-known environmental problems, yet the magnitude and seasonal/spatial variability of the emissions are poorly constrained. In the atmosphere, an important fraction of fine particulate matter is composed of ammonium nitrate and ammonium sulfate. These particles are statistically associated with health impacts. When deposited to ecosystems in excess, nitrogen, including ammonia can cause nutrient imbalances, change in ecosystem species composition, eutrophication, algal blooms and hypoxia. Ammonia is also challenging to measure in-situ. Observations of surface concentrations are rare and are particularly sparse in North America. Satellite observations of ammonia are therefore highly desirable. We recently demonstrated that tropospheric ammonia is detectable in the TES spectra and presented some corresponding preliminary retrievals over a very limited range of conditions (Beer et al., 2008). Presented here are results that expand upon these initial TES ammonia retrievals in order to evaluate/validate the retrieval results utilizing in-situ surface observations (e.g. LADCO, CASTNet, EPA /NC State) and chemical models (e.g. GEOS-Chem and CMAQ). We also present retrievals over regions of interest that have the potential to help further understand air quality and the active nitrogen cycle. Beer, R., M. W. Shephard, S. S. Kulawik, S. A. Clough, A. Eldering, K. W. Bowman, S. P. Sander, B. M. Fisher, V. H. Payne, M. Luo, G. B. Osterman, and J. R. Worden, First satellite observations of lower tropospheric ammonia and methanol, Geophysical Res. Letters, 35, L09801, doi:10.1029/2008GL033642, 2008.

Empirical retrieval of sea spray aerosol production using satellite microwave radiometry

NASA Astrophysics Data System (ADS)

Savelyev, I. B.; Yelland, M. J.; Norris, S. J.; Salisbury, D.; Pascal, R. W.; Bettenhausen, M. H.; Prytherch, J.; Anguelova, M. D.; Brooks, I. M.

2017-12-01

This study presents a novel approach to obtaining global sea spray aerosol (SSA) production source term by relying on direct satellite observations of the ocean surface, instead of more traditional approaches driven by surface meteorology. The primary challenge in developing this empirical algorithm is to compile a calibrated, consistent dataset of SSA surface flux collected offshore over a variety of conditions (i.e., regions and seasons), thus representative of the global SSA production variability. Such dataset includes observations from SEASAW, HiWASE, and WAGES field campaigns, during which the SSA flux was measured from the bow of a research vessel using consistent and state-of-the-art eddy covariance methodology. These in situ data are matched to observations of the state of the ocean surface from Windsat polarimetric microwave satellite radiometer. Previous studies demonstrated the ability of WindSat to detect variations in surface waves slopes, roughness and foam, which led to the development of retrieval algorithms for surface wind vector and more recently whitecap fraction. Similarly, in this study, microwave emissions from the ocean surface are matched to and calibrated against in situ observations of the SSA production flux. The resulting calibrated empirical algorithm is applicable for retrieval of SSA source term throughout the duration of Windsat mission, from 2003 to present.

GPM Precipitation Estimates over the Walnut Gulch Experimental Watershed/LTAR site in Southeastern Arizona

NASA Astrophysics Data System (ADS)

Goodrich, D. C.; Tan, J.; Petersen, W. A.; Unkrich, C. C.; Demaria, E. M.; Hazenberg, P.; Lakshmi, V.

2017-12-01

Precipitation profiles from the GPM Core Observatory Dual-frequency Precipitation Radar (DPR) form part of the a priori database used in GPM Goddard Profiling (GPROF) algorithm passive microwave radiometer retrievals of rainfall. The GPROF retrievals are in turn used as high quality precipitation estimates in gridded products such as IMERG. Due to the variability in and high surface emissivity of land surfaces, GPROF performs precipitation retrievals as a function of surface classes. As such, different surface types may possess different error characteristics, especially over arid regions where high quality ground measurements are often lacking. Importantly, the emissive properties of land also result in GPROF rainfall estimates being driven primarily by the higher frequency radiometer channels (e.g., > 89 GHz) where precipitation signals are most sensitive to coupling between the ice-phase and rainfall production. In this study, we evaluate the rainfall estimates from the Ku channel of the DPR as well as GPROF estimates from various passive microwave sensors. Our evaluation is conducted at the level of individual satellite pixels (5 to 15 km in diameter), against a dense network of weighing rain gauges (90 in 150 km2) in the USDA-ARS Walnut Gulch Experimental Watershed and Long-Term Agroecosystem Research (LTAR) site in southeastern Arizona. The multiple gauges in each satellite pixel and precise accumulation about the overpass time allow a spatially and temporally representative comparison between the satellite estimates and ground reference. Over Walnut Gulch, both the Ku and GPROF estimates are challenged to delineate between rain and no-rain. Probabilities of detection are relatively high, but false alarm ratios are also high. The rain intensities possess a negative bias across nearly all sensors. It is likely that storm types, arid conditions and the highly variable precipitation regime present a challenge to both rainfall retrieval algorithms. An array of ground-based sensors is being deployed during the 2017 monsoon season to better understand possible reasons for this discrepancy.

SMOS first results over land

NASA Astrophysics Data System (ADS)

Kerr, Yann; Waldteufel, Philippe; Cabot, François; Richaume, Philippe; Jacquette, Elsa; Bitar, Ahmad Al; Mamhoodi, Ali; Delwart, Steven; Wigneron, Jean-Pierre

2010-05-01

The Soil Moisture and Ocean Salinity (SMOS) mission is ESA's (European Space Agency ) second Earth Explorer Opportunity mission, launched in November 2009. It is a joint programme between ESA CNES (Centre National d'Etudes Spatiales) and CDTI (Centro para el Desarrollo Tecnologico Industrial). SMOS carries a single payload, an L-band 2D interferometric radiometer in the 1400-1427 MHz protected band. This wavelength penetrates well through the atmosphere and hence the instrument probes the Earth surface emissivity. Surface emissivity can then be related to the moisture content in the first few centimeters of soil, and, after some surface roughness and temperature corrections, to the sea surface salinity over ocean. In order to prepare the data use and dissemination, the ground segment will produce level 1 and 2 data. Level 1 consists mainly of angular brightness temperatures while level 2 consists of geophysical products. In this context, a group of institutes prepared the soil moisture and ocean salinity Algorithm Theoretical Basis documents (ATBD) to be used to produce the operational algorithm. The principle of the soil moisture retrieval algorithm is based on an iterative approach which aims at minimizing a cost function given by the sum of the squared weighted differences between measured and modelled brightness temperature (TB) data, for a variety of incidence angles. This is achieved by finding the best suited set of the parameters which drive the direct TB model, e.g. soil moisture (SM) and vegetation characteristics. Despite the simplicity of this principle, the main reason for the complexity of the algorithm is that SMOS "pixels" can correspond to rather large, inhomogeneous surface areas whose contribution to the radiometric signal is difficult to model. Moreover, the exact description of pixels, given by a weighting function which expresses the directional pattern of the SMOS interferometric radiometer, depends on the incidence angle. The goal is to retrieve soil moisture over fairly large and thus inhomogeneous areas. The retrieval is carried out at nodes of a fixed Earth surface grid. To achieve this purpose, after checking input data quality and ingesting auxiliary data, the retrieval process per se can be initiated. This cannot be done blindly as the direct model will be dependent upon surface characteristics. It is thus necessary to first assess what is the dominant land use of a node. For this, an average weighing function (MEAN_WEF) which takes into account the "antenna"pattern is run over the high resolution land use map to assess the dominant cover type. This is used to drive the decision tree which, step by step, selects the type of model to be used as per surface conditions. All this being said and done the retrieval procedure starts if all the conditions are satisfied, ideally to retrieve 3 parameters over the dominant class (the so-called rich retrieval). If the algorithm does not converge satisfactorily, a new trial is made with less floating parameters ("poorer retrieval") until either results are satisfactory or the algorithm is considered to fail. The retrieval algorithm also delivers whenever possible a dielectric constant parameter (using the-so called cardioid approach). Finally, once the retrieval converged, it is possible to compute the brightness temperature at a given fixed angle (42.5°) using the selected forward models applied to the set of parameters obtained at the end of the retrieval process. So the output product of the level 2 soil moisture algorithm should be node position, soil moisture, dielectric constants, computed brightness temperature at 42.5°, flags and quality indices. During the presentation we will describe in more details the algorithm and accompanying work in particular decision tree principle and characteristics, the auxiliary data used and the special and "exotic"cases. We will also be more explicit on the algorithm validation and verification through the data collected during the commissioning phase. The main hurdle being working in spite of spurious signals (RFI) on some areas of the globe.

Role of lightning phenomenon over surface O3 and NOx at a semi-arid tropical site Hyderabad, India: inter-comparison with satellite retrievals

NASA Astrophysics Data System (ADS)

Venkanna, R.; Nikhil, G. N.; Sinha, P. R.; Siva Rao, T.; Swamy, Y. V.

2016-08-01

The influence of lightning over surface-level trace gases was examined for pre-monsoon and monsoon seasons in the year 2012. Lightning events were measured using ground-based electric field monitor (EFM) and space-based lightning imaging sensor (LIS). The results showed that lightning frequency was higher during pre-monsoon period compared to monsoon, which is in good agreement with the satellite retrievals. The increase in concentration of NOx on lightning event led to a subsequent decrease in surface O3 due to the titration reaction. Source apportionment study of SO2/NOx (S/N) and CO/NOx (C/N) ratios and poor correlation of NOx vs CO and NOx vs SO2 on the lightning day confirmed the emission of NOx from dissimilar sources.

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.

Towards an improved soil moisture retrieval for organic-rich soils from SMOS passive microwave L-band observations

NASA Astrophysics Data System (ADS)

Bircher, Simone; Richaume, Philippe; Mahmoodi, Ali; Mialon, Arnaud; Fernandez-Moran, Roberto; Wigneron, Jean-Pierre; Demontoux, François; Jonard, François; Weihermüller, Lutz; Andreasen, Mie; Rautiainen, Kimmo; Ikonen, Jaakko; Schwank, Mike; Drusch, Mattias; Kerr, Yann H.

2017-04-01

From the passive L-band microwave radiometer onboard the Soil Moisture and Ocean Salinity (SMOS) space mission global surface soil moisture data is retrieved every 2 - 3 days. Thus far, the empirical L-band Microwave Emission of the Biosphere (L-MEB) radiative transfer model applied in the SMOS soil moisture retrieval algorithm is exclusively calibrated over test sites in dry and temperate climate zones. Furthermore, the included dielectric mixing model relating soil moisture to relative permittivity accounts only for mineral soils. However, soil moisture monitoring over the higher Northern latitudes is crucial since these regions are especially sensitive to climate change. A considerable positive feedback is expected if thawing of these extremely organic soils supports carbon decomposition and release to the atmosphere. Due to differing structural characteristics and thus varying bound water fractions, the relative permittivity of organic material is lower than that of the most mineral soils at a given water content. This assumption was verified by means of L-band relative permittivity laboratory measurements of organic and mineral substrates from various sites in Denmark, Finland, Scotland and Siberia using a resonant cavity. Based on these data, a simple empirical dielectric model for organic soils was derived and implemented in the SMOS Soil Moisture Level 2 Prototype Processor (SML2PP). Unfortunately, the current SMOS retrieved soil moisture product seems to show unrealistically low values compared to in situ soil moisture data collected from organic surface layers in North America, Europe and the Tibetan Plateau so that the impact of the dielectric model for organic soils cannot really be tested. A simplified SMOS processing scheme yielding higher soil moisture levels has recently been proposed and is presently under investigation. Furthermore, recalibration of the model parameters accounting for vegetation and roughness effects that were thus far only evaluated using the default dielectric model for mineral soils is ongoing for the "organic" L-MEB version. Additionally, in order to decide where a soil moisture retrieval using the "organic" dielectric model should be triggered, information on soil organic matter content in the soil surface layer has to be considered in the retrieval algorithm. For this purpose, SoilGrids (www.soilgrids.org) providing soil organic carbon content (SOCC) in g/kg is under study. A SOCC threshold based on the relation between the SoilGrids' SOCC and the presence of organic soil surface layers (relevant to alter the microwave L-band emissions from the land surface) in the SoilGrids' source soil profile information has to be established. In this communication, we present the current status of the above outlined studies with the objective to advance towards an improved soil moisture retrieval for organic-rich soils from SMOS passive microwave L-band observations.

Combined Radar-Radiometer Surface Soil Moisture and Roughness Estimation

NASA Technical Reports Server (NTRS)

Akbar, Ruzbeh; Cosh, Michael H.; O'Neill, Peggy E.; Entekhabi, Dara; Moghaddam, Mahta

2017-01-01

A robust physics-based combined radar-radiometer, or Active-Passive, surface soil moisture and roughness estimation methodology is presented. Soil moisture and roughness retrieval is performed via optimization, i.e., minimization, of a joint objective function which constrains similar resolution radar and radiometer observations simultaneously. A data-driven and noise-dependent regularization term has also been developed to automatically regularize and balance corresponding radar and radiometer contributions to achieve optimal soil moisture retrievals. It is shown that in order to compensate for measurement and observation noise, as well as forward model inaccuracies, in combined radar-radiometer estimation surface roughness can be considered a free parameter. Extensive Monte-Carlo numerical simulations and assessment using field data have been performed to both evaluate the algorithms performance and to demonstrate soil moisture estimation. Unbiased root mean squared errors (RMSE) range from 0.18 to 0.03 cm3cm3 for two different land cover types of corn and soybean. In summary, in the context of soil moisture retrieval, the importance of consistent forward emission and scattering development is discussed and presented.

Combined Radar-Radiometer Surface Soil Moisture and Roughness Estimation.

PubMed

Akbar, Ruzbeh; Cosh, Michael H; O'Neill, Peggy E; Entekhabi, Dara; Moghaddam, Mahta

2017-07-01

A robust physics-based combined radar-radiometer, or Active-Passive, surface soil moisture and roughness estimation methodology is presented. Soil moisture and roughness retrieval is performed via optimization, i.e., minimization, of a joint objective function which constrains similar resolution radar and radiometer observations simultaneously. A data-driven and noise-dependent regularization term has also been developed to automatically regularize and balance corresponding radar and radiometer contributions to achieve optimal soil moisture retrievals. It is shown that in order to compensate for measurement and observation noise, as well as forward model inaccuracies, in combined radar-radiometer estimation surface roughness can be considered a free parameter. Extensive Monte-Carlo numerical simulations and assessment using field data have been performed to both evaluate the algorithm's performance and to demonstrate soil moisture estimation. Unbiased root mean squared errors (RMSE) range from 0.18 to 0.03 cm3/cm3 for two different land cover types of corn and soybean. In summary, in the context of soil moisture retrieval, the importance of consistent forward emission and scattering development is discussed and presented.

Surface-induced brightness temperature variations and their effects on detecting thin cirrus clouds using IR emission channels in the 8-12 micrometer region

NASA Technical Reports Server (NTRS)

Gao, Bo-Cai; Wiscombe, W. J.

1993-01-01

A method for detecting cirrus clouds in terms of brightness temperature differences between narrow bands at 8, 11, and 12 mu m has been proposed by Ackerman et al. (1990). In this method, the variation of emissivity with wavelength for different surface targets was not taken into consideration. Based on state-of-the-art laboratory measurements of reflectance spectra of terrestrial materials by Salisbury and D'Aria (1992), we have found that the brightness temperature differences between the 8 and 11 mu m bands for soils, rocks and minerals, and dry vegetation can vary between approximately -8 K and +8 K due solely to surface emissivity variations. We conclude that although the method of Ackerman et al. is useful for detecting cirrus clouds over areas covered by green vegetation, water, and ice, it is less effective for detecting cirrus clouds over areas covered by bare soils, rocks and minerals, and dry vegetation. In addition, we recommend that in future the variation of surface emissivity with wavelength should be taken into account in algorithms for retrieving surface temperatures and low-level atmospheric temperature and water vapor profiles.

Coupling the snow thermodynamic model SNOWPACK with the microwave emission model of layered snowpacks for subarctic and arctic snow water equivalent retrievals

NASA Astrophysics Data System (ADS)

Langlois, A.; Royer, A.; Derksen, C.; Montpetit, B.; Dupont, F.; GoïTa, K.

2012-12-01

Satellite-passive microwave remote sensing has been extensively used to estimate snow water equivalent (SWE) in northern regions. Although passive microwave sensors operate independent of solar illumination and the lower frequencies are independent of atmospheric conditions, the coarse spatial resolution introduces uncertainties to SWE retrievals due to the surface heterogeneity within individual pixels. In this article, we investigate the coupling of a thermodynamic multilayered snow model with a passive microwave emission model. Results show that the snow model itself provides poor SWE simulations when compared to field measurements from two major field campaigns. Coupling the snow and microwave emission models with successive iterations to correct the influence of snow grain size and density significantly improves SWE simulations. This method was further validated using an additional independent data set, which also showed significant improvement using the two-step iteration method compared to standalone simulations with the snow model.

Tropospheric Ozone Near-Nadir-Viewing IR Spectral Sensitivity and Ozone Measurements from NAST-I

NASA Technical Reports Server (NTRS)

Zhou, Daniel K.; Smith, William L.; Larar, Allen M.

2001-01-01

Infrared ozone spectra from near nadir observations have provided atmospheric ozone information from the sensor to the Earth's surface. Simulations of the NPOESS Airborne Sounder Testbed-Interferometer (NAST-I) from the NASA ER-2 aircraft (approximately 20 km altitude) with a spectral resolution of 0.25/cm were used for sensitivity analysis. The spectral sensitivity of ozone retrievals to uncertainties in atmospheric temperature and water vapor is assessed in order to understand the relationship between the IR emissions and the atmospheric state. In addition, ozone spectral radiance sensitivity to its ozone layer densities and radiance weighting functions reveals the limit of the ozone profile retrieval accuracy from NAST-I measurements. Statistical retrievals of ozone with temperature and moisture retrievals from NAST-I spectra have been investigated and the preliminary results from NAST-I field campaigns are presented.

Retrieval of constituent mixing ratios from limb thermal emission spectra

NASA Technical Reports Server (NTRS)

Shaffer, William A.; Kunde, Virgil G.; Conrath, Barney J.

1988-01-01

An onion-peeling iterative, least-squares relaxation method to retrieve mixing ratio profiles from limb thermal emission spectra is presented. The method has been tested on synthetic data, containing various amounts of added random noise for O3, HNO3, and N2O. The retrieval method is used to obtain O3 and HNO3 mixing ratio profiles from high-resolution thermal emission spectra. Results of the retrievals compare favorably with those obtained previously.

Improvement and further development of SSM/I overland parameter algorithms using the WetNet workstation

NASA Technical Reports Server (NTRS)

Neale, Christopher M. U.; Mcdonnell, Jeffrey J.; Ramsey, Douglas; Hipps, Lawrence; Tarboton, David

1993-01-01

Since the launch of the DMSP Special Sensor Microwave/Imager (SSM/I), several algorithms have been developed to retrieve overland parameters. These include the present operational algorithms resulting from the Navy calibration/validation effort such as land surface type (Neale et al. 1990), land surface temperature (McFarland et al. 1990), surface moisture (McFarland and Neale, 1991) and snow parameters (McFarland and Neale, 1991). In addition, other work has been done including the classification of snow cover and precipitation using the SSM/I (Grody, 1991). Due to the empirical nature of most of the above mentioned algorithms, further research is warranted and improvements can probably be obtained through a combination of radiative transfer modelling to study the physical processes governing the microwave emissions at the SSM/I frequencies, and the incorporation of additional ground truth data and special cases into the regression data sets. We have proposed specifically to improve the retrieval of surface moisture and snow parameters using the WetNet SSM/I data sets along with ground truth information namely climatic variables from the NOAA cooperative network of weather stations as well as imagery from other satellite sensors such as the AVHRR and Thematic Mapper. In the case of surface moisture retrievals the characterization of vegetation density is of primary concern. The higher spatial resolution satellite imagery collected at concurrent periods will be used to characterize vegetation types and amounts which, along with radiative transfer modelling should lead to more physically based retrievals. Snow parameter retrieval algorithm improvement will initially concentrate on the classification of snowpacks (dry snow, wet snow, refrozen snow) and later on specific products such as snow water equivalent. Significant accomplishments in the past year are presented.

Land Surface Temperature Measurements from EOS MODIS Data

NASA Technical Reports Server (NTRS)

Wan, Zhengming

1997-01-01

We applied the multi-method strategy of land-surface temperature (LST) and emissivity measurements in two field campaigns this year for validating the MODIS LST algorithm. The first field campaign was conducted in Death Valley, CA, on March 3rd and the second one in Railroad Valley, NV, on June 23-27. ER2 MODIS Airborne Simulator (MAS) data were acquired in morning and evening for these two field campaigns. TIR spectrometer, radiometer, and thermistor data were also collected in the field campaigns. The LST values retrieved from MAS data with the day/night LST algorithm agree with those obtained from ground-based measurements within 1 C and show close correlations with topographic maps. The band emissivities retrieved from MAS data show close correlations with geological maps in the Death Valley field campaign. The comparison of measurement data in the latest Railroad Valley field campaign indicates that we are approaching the goals of the LST validation: LST uncertainty less than 0.5 C, and emissivity uncertainty less than 0.005 in the 10-13 spectral range. Measurement data show that the spatial variation in LST is the major uncertainty in the LST validation. In order to reduce this uncertainty, a new component of the multi-method strategy has been identified.

A Tropospheric Emission Spectrometer HDO/H2O Retrieval Simulator for Climate Models

NASA Technical Reports Server (NTRS)

Field, R. D.; Risi, C.; Schmidt, G. A.; Worden, J.; Voulgarakis, A.; LeGrande, A. N.; Sobel, A. H.; Healy, R. J.

2012-01-01

Retrievals of the isotopic composition of water vapor from the Aura Tropospheric Emission Spectrometer (TES) have unique value in constraining moist processes in climate models. Accurate comparison between simulated and retrieved values requires that model profiles that would be poorly retrieved are excluded, and that an instrument operator be applied to the remaining profiles. Typically, this is done by sampling model output at satellite measurement points and using the quality flags and averaging kernels from individual retrievals at specific places and times. This approach is not reliable when the model meteorological conditions influencing retrieval sensitivity are different from those observed by the instrument at short time scales, which will be the case for free-running climate simulations. In this study, we describe an alternative, categorical approach to applying the instrument operator, implemented within the NASA GISS ModelE general circulation model. Retrieval quality and averaging kernel structure are predicted empirically from model conditions, rather than obtained from collocated satellite observations. This approach can be used for arbitrary model configurations, and requires no agreement between satellite-retrieved and model meteorology at short time scales. To test this approach, nudged simUlations were conducted using both the retrieval-based and categorical operators. Cloud cover, surface temperature and free-tropospheric moisture content were the most important predictors of retrieval quality and averaging kernel structure. There was good agreement between the D fields after applying the retrieval-based and more detailed categorical operators, with increases of up to 30 over the ocean and decreases of up to 40 over land relative to the raw model fields. The categorical operator performed better over the ocean than over land, and requires further refinement for use outside of the tropics. After applying the TES operator, ModelE had D biases of 8 over ocean and 34 over land compared to TES D, which were less than the biases using raw model D fields.

The Aquarius Salinity Retrieval Algorithm

NASA Technical Reports Server (NTRS)

Meissner, Thomas; Wentz, Frank; Hilburn, Kyle; Lagerloef, Gary; Le Vine, David

2012-01-01

The first part of this presentation gives an overview over the Aquarius salinity retrieval algorithm. The instrument calibration [2] converts Aquarius radiometer counts into antenna temperatures (TA). The salinity retrieval algorithm converts those TA into brightness temperatures (TB) at a flat ocean surface. As a first step, contributions arising from the intrusion of solar, lunar and galactic radiation are subtracted. The antenna pattern correction (APC) removes the effects of cross-polarization contamination and spillover. The Aquarius radiometer measures the 3rd Stokes parameter in addition to vertical (v) and horizontal (h) polarizations, which allows for an easy removal of ionospheric Faraday rotation. The atmospheric absorption at L-band is almost entirely due to molecular oxygen, which can be calculated based on auxiliary input fields from numerical weather prediction models and then successively removed from the TB. The final step in the TA to TB conversion is the correction for the roughness of the sea surface due to wind, which is addressed in more detail in section 3. The TB of the flat ocean surface can now be matched to a salinity value using a surface emission model that is based on a model for the dielectric constant of sea water [3], [4] and an auxiliary field for the sea surface temperature. In the current processing only v-pol TB are used for this last step.

Decreasing Lower Tropospheric Ozone over the North China Plain Observed by IASI: Looking for Explanations

NASA Astrophysics Data System (ADS)

Dufour, G.; Eremenko, M.; Lachâtre, M.; Hauglustaine, D.; Fortems-Cheiney, A.; Cuesta, J.; Zhang, Y.; Cai, Z.; Liu, Y.; Xu, X.; Lin, W.; Cooper, O. R.

2017-12-01

China, and especially the North China Plain (NCP), is a highly polluted region. Emission reductions have been applied since about 10 years, starting with SO2 emissions in 2006 and with NOx emissions in 2010. Recent satellite observations series show a decrease of NO2 tropospheric columns since 2013 and attributed to the NOx emissions reduction. The question of the impact of such reduction on ozone is then arising. In this study, we use the capabilities of the IASI satellite instrument to retrieve 2 semi-independent columns of ozone in the lower (surface-6km asl) and the upper (6-12km) troposphere - the lower tropospheric (LT) column having a sensitivity maximum at 3-4 km - and we evaluate the variability and trend of LT ozone over the NCP for 2008-2016. Deseasonalized monthly timeseries show two distinct periods: a first period (2008-2012) with no significant trend (slope of the linear fit < -0.1 %/yr) and a second period (2013-2016) with a highly significant negative trend of -1.2 %/yr, leading to an overall trend of -0.77 %/yr for 2008-2016. A first temptation is to attribute this decrease to the NOx emissions changes. However, negative trends have not been reported from background surface measurements in this Chinese region. Furthermore recent work made within the framework of the TOAR initiative reveals discrepancies in the sign of the trends of tropospheric column ozone derived from infrared and ultraviolet satellite instruments. As yet there is no conclusive explanation for the discrepancy. We then investigate the IASI retrieval stability and robustness in terms of vertical sensitivity, interferences with large aerosol loading, and comparing with surface and ozonesonde measurements and the IASI instrument aboard the Metop-B satellite. One issue arises concerning the temporal sampling of IASI that may induce significant change in the trend derived from surface stations. We also explore the possible variables, other than emissions, which could explain the observed negative trends using both a statistical regression model and simulations from global and regional chemistry transport models.

Retrievals of Sea Surface Emissivity and Skin Temperature from M-AERI Observations from the ACAPEX/CalWater2 Campaign

NASA Astrophysics Data System (ADS)

Gero, P. J.; Westphall, M.; Knuteson, R.; Knuteson, R. O.; Smith, W.

2016-12-01

The Atmospheric Emitted Radiance Interferometer (AERI) is a ground-based instrument developed at the University of Wisconsin-Madison that measures downwelling thermal infrared radiance from the atmosphere. Observations are made in the 520-3020 cm-1 (3.3-19 μm) spectral range with a resolution of 1 cm-1, with an accuracy better than 1% of ambient radiance. These observations can be used to obtain vertical profiles of tropospheric temperature and water vapor in the lowest 3 km of the troposphere, as well as measurements of the concentration of various trace gases and microphysical and optical properties of clouds and aerosols. The U.S Department of Energy's (DOE) Atmospheric Radiation Measurement (ARM) program currently operates about ten AERIs at various fixed and mobile sites worldwide, addressing a diverse range of scientific goals from process studies to long-term climate observations. One of the instruments is a marine version (M-AERI) that has the capability to view scenes ±45° from the horizon, and can be used to observe sea surface properties such as skin temperature and emissivity. The M-AERI was deployed on the NOAA Ship Ronald Brown in 2015 as part of the ACAPEX/CalWater2 campaign to study atmospheric rivers in the Pacific Ocean. We present results from the M-AERI from this campaign of retrievals of skin temperature and sea surface emissivity as a function of view angle and wind speed, as well as comparisons to various models.

CO2 Annual and Semiannual Cycles from Satellite Retrievals and Models

NASA Astrophysics Data System (ADS)

Jiang, X.; Crisp, D.; Olsen, E. T.; Kulawik, S. S.; Miller, C. E.; Pagano, T. S.; Yung, Y. L.

2014-12-01

We have compared satellite CO2 retrievals from the Greenhouse gases Observing SATellite (GOSAT), Atmospheric Infrared Sounder (AIRS), and Tropospheric Emission Spectrometer (TES) with in-situ measurements from the Earth System Research Laboratory (NOAA-ESRL) Surface CO2 and Total Carbon Column Observing Network (TCCON), and utilized zonal means to characterize variability and distribution of CO2. In general, zonally averaged CO2 from the three satellite data sets are consistent with the surface and TCCON XCO2 data. Retrievals of CO2 from the three satellites show more (less) CO2 in the northern hemisphere than that in the southern hemisphere in the northern hemispheric winter (summer) season. The difference between the three satellite CO2 retrievals might be related to the different averaging kernels in the satellites CO2 retrievals. A multiple regression method was used to calculate the CO2 annual cycle and semiannual cycle amplitudes from different satellite CO2 retrievals. The CO2 annual cycle and semiannual cycle amplitudes are largest at the surface, as seen in the NOAA-ESRL CO2 data sets. The CO2 annual cycle and semiannual cycle amplitudes in the GOSAT XCO2, AIRS mid-tropospheric CO2, and TES mid-tropospheric CO2 are smaller compared with those from the surface CO2. Similar regression analysis was applied to the Model for OZone And Related chemical Tracers-2 (MOZART-2) and CarbonTracker model CO2. The convolved model CO2 annual cycle and semiannual cycle amplitudes are similar to those from the satellite CO2 retrievals, although the model tends to under-estimate the CO2 seasonal cycle amplitudes in the northern hemisphere mid-latitudes from the comparison with GOSAT and TES CO2 and underestimate the CO2 semi-annual cycle amplitudes in the high latitudes from the comparison with AIRS CO2. The difference between model and satellite CO2 can be used to identify possible deficiency in the model and improve the model in the future.

Quantifying fire emissions and associated aerosols species using assimilation of satellite carbon monoxide retrievals.

NASA Astrophysics Data System (ADS)

Barre, J.; Edwards, D. P.; Worden, H. M.

2016-12-01

Wildfires tend to be more intense and hence costly and are predicted to increase in frequency under a warming climate. For example, the recent August 2015 Washington State fires were the largest in the state's history. Also in September and October 2015 very intense fires over Indonesia produced some of the highest concentration of carbon monoxide (CO) ever seen from space. Such larges fires impact not only the local environment but also affects air quality far downwind through the long-range transport of pollutants. Global to continental scale coverage showing the evolution of CO resulting from fire emission is available from satellite observations. Carbon monoxide is the only atmospheric trace gas for which satellite multispectral retrievals have demonstrated reliable independent profile information close to the surface and also higher in the free troposphere. The unique CO profile product from Terra/MOPITT clearly distinguishes near-surface CO from the free troposphere CO. Also previous studies have suggested strong correlations between primary emissions of fire organic and black carbon aerosols and CO. We will present results from the Ensemble Adjustement Kalman Filter (DART) system that has been developed to assimilate MOPITT CO in the global scale chemistry-climate model CAM-Chem. The ensemble technique allows inference on various fire model state variables such as CO emissions and also aerosol species resulting from fires such as organic and black carbon. The benefit of MOPITT CO assimilation on the Washington and Indonesian fire cases studies will be diagnosed regarding the CO fire emissions, black and organic carbon inference using the ensemble information.

Validation of NH3 satellite observations by ground-based FTIR measurements

NASA Astrophysics Data System (ADS)

Dammers, Enrico; Palm, Mathias; Van Damme, Martin; Shephard, Mark; Cady-Pereira, Karen; Capps, Shannon; Clarisse, Lieven; Coheur, Pierre; Erisman, Jan Willem

2016-04-01

Global emissions of reactive nitrogen have been increasing to an unprecedented level due to human activities and are estimated to be a factor four larger than pre-industrial levels. Concentration levels of NOx are declining, but ammonia (NH3) levels are increasing around the globe. While NH3 at its current concentrations poses significant threats to the environment and human health, relatively little is known about the total budget and global distribution. Surface observations are sparse and mainly available for north-western Europe, the United States and China and are limited by the high costs and poor temporal and spatial resolution. Since the lifetime of atmospheric NH3 is short, on the order of hours to a few days, due to efficient deposition and fast conversion to particulate matter, the existing surface measurements are not sufficient to estimate global concentrations. Advanced space-based IR-sounders such as the Tropospheric Emission Spectrometer (TES), the Infrared Atmospheric Sounding Interferometer (IASI), and the Cross-track Infrared Sounder (CrIS) enable global observations of atmospheric NH3 that help overcome some of the limitations of surface observations. However, the satellite NH3 retrievals are complex requiring extensive validation. Presently there have only been a few dedicated satellite NH3 validation campaigns performed with limited spatial, vertical or temporal coverage. Recently a retrieval methodology was developed for ground-based Fourier Transform Infrared Spectroscopy (FTIR) instruments to obtain vertical concentration profiles of NH3. Here we show the applicability of retrieved columns from nine globally distributed stations with a range of NH3 pollution levels to validate satellite NH3 products.

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.

The Aquarius Salinity Retrieval Algorithm: Early Results

NASA Technical Reports Server (NTRS)

Meissner, Thomas; Wentz, Frank J.; Lagerloef, Gary; LeVine, David

2012-01-01

The Aquarius L-band radiometer/scatterometer system is designed to provide monthly salinity maps at 150 km spatial scale to a 0.2 psu accuracy. The sensor was launched on June 10, 2011, aboard the Argentine CONAE SAC-D spacecraft. The L-band radiometers and the scatterometer have been taking science data observations since August 25, 2011. The first part of this presentation gives an overview over the Aquarius salinity retrieval algorithm. The instrument calibration converts Aquarius radiometer counts into antenna temperatures (TA). The salinity retrieval algorithm converts those TA into brightness temperatures (TB) at a flat ocean surface. As a first step, contributions arising from the intrusion of solar, lunar and galactic radiation are subtracted. The antenna pattern correction (APC) removes the effects of cross-polarization contamination and spillover. The Aquarius radiometer measures the 3rd Stokes parameter in addition to vertical (v) and horizontal (h) polarizations, which allows for an easy removal of ionospheric Faraday rotation. The atmospheric absorption at L-band is almost entirely due to O2, which can be calculated based on auxiliary input fields from numerical weather prediction models and then successively removed from the TB. The final step in the TA to TB conversion is the correction for the roughness of the sea surface due to wind. This is based on the radar backscatter measurements by the scatterometer. The TB of the flat ocean surface can now be matched to a salinity value using a surface emission model that is based on a model for the dielectric constant of sea water and an auxiliary field for the sea surface temperature. In the current processing (as of writing this abstract) only v-pol TB are used for this last process and NCEP winds are used for the roughness correction. Before the salinity algorithm can be operationally implemented and its accuracy assessed by comparing versus in situ measurements, an extensive calibration and validation (cal/val) activity needs to be completed. This is necessary in order to tune the inputs to the algorithm and remove biases that arise due to the instrument calibration, foremost the values of the noise diode injection temperatures and the losses that occur in the feedhorns. This is the subject of the second part of our presentation. The basic tool is to analyze the observed difference between the Aquarius measured TA and an expected TA that is computed from a reference salinity field. It is also necessary to derive a relation between the scatterometer backscatter measurements and the radiometer emissivity that is induced by surface winds. In order to do this we collocate Aquarius radiometer and scatterometer measurements with wind speed retrievals from the WindSat and SSMIS F17 microwave radiometers. Both of these satellites fly in orbits that have the same equatorial ascending crossing time (6 pm) as the Aquarius/SAC-D observatory. Rain retrievals from WindSat and SSMIS F 17 can be used to remove Aquarius observations that are rain contaminated. A byproduct of this analysis is a prediction for the wind-induced sea surface emissivity at L-band.

3D model of auroral emissions for Europa

NASA Astrophysics Data System (ADS)

Cessateur, G.; Barthelemy, M.; Rubin, M.; Lilensten, J.; Maggiolo, R.; De Keyser, J.; Gunell, H.; Loreau, J.

2017-12-01

As archetype of icy satellites, Europa will be one of the primary targets of the ESA JUICE and NASA Europa Clipper missions. Through surface sputtering, Europa does possess a thin neutral gas atmosphere, mainly composed of O2 and H2O. Valuable information can therefore be retrieved from auroral and airglow measurements. We present here a 3D electron-excitation-transport-emission coupled model of oxygen line emissions produced through precipitating electrons. The density and temperature of the electrons are first derived from the multifluid MHD model from Rubin et al. (2015). Oxygen emission lines in the UV have first been modelled, such as those at 130.5 and 135.6 nm, and there is a nonhomogenous distribution of the emission. For 135.6 nm, the line emission can be significant and reach 700 Rayleigh close to the surface for a polar limb viewing angle. Visible emissions with the red-doublet (630-636.4 nm) and green (577.7 nm) oxygen lines are also considered with emission intensities reaching 7150 R and 200 R, respectively, for limb polar viewing. Using different cross section data, a sensitivity study has also been performed to assess the impact of the uncertainties on the auroral emissions.

Coincident Retrieval of Ocean Surface Roughness and Salinity Using Airborne and Satellite Microwave Radiometry and Reflectometry Measurements during the Carolina Offshore (Caro) Experiment.

NASA Astrophysics Data System (ADS)

Burrage, D. M.; Wesson, J. C.; Wang, D. W.; Garrison, J. L.; Zhang, H.

2017-12-01

The launch of the Cyclone Global Navigation Satellite System (CYGNSS) constellation of 8 microsats carrying GPS L-band reflectometers on 15 Dec., 2016, and continued operation of the L-band radiometer on the European Space Agency (ESA) Soil Moisture and Ocean Salinity (SMOS) satellite, allow these complementary technologies to coincidentally retrieve Ocean surface roughness (Mean Square Slope, MSS), Surface Wind speed (WSP), and Sea Surface Salinity (SSS). The Carolina Offshore (Caro) airborne experiment was conducted jointly by NRL SSC and Purdue University from 7-11 May, 2017 with the goal of under-flying CYGNSS and SMOS and overflying NOAA buoys, to obtain high-resolution reflectometer and radiometer data for combined retrieval of MSS, SSS and WSP on the continental shelf. Airborne instruments included NRL's Salinity Temperature and Roughness Remote Scanner (STARRS) L-, C- and IR-band radiometer system, and a 4-channel dual-pol L-band (GPS) and S-band (XM radio) reflectometer, built by Purdue University. Flights either crossed NOAA buoys on various headings, or intersected with specular point ground tracks at predicted CYGNSS overpass times. Prevailing winds during Caro were light to moderate (1-8 m/s), so specular returns dominated the reflectometer Delay Doppler Maps (DDMs), and MSS was generally low. In contrast, stronger winds (1-12 m/s) and rougher seas (wave heights 1-5 m) were experienced during the preceding Maine Offshore (Maineo) experiment in March, 2016. Several DDM observables were used to retrieve MSS and WSP, and radiometer brightness temperatures produced Sea Surface Temperature (SST), SSS and also WSP estimates. The complementary relationship of Kirchoff's formula e+r=1, between radiometric emissivity, e, and reflectivity, r, was exploited to seek consistent estimates of MSS, and use it to correct the SSS retrievals for sea surface roughness effects. The relative performance and utility of the various airborne and satellite retrieval algorithms were assessed, and the coincident buoy, aircraft and satellite retrievals of MSS, WSP and SSS were compared. During Caro WSP from the different instruments generally agreed. Some anomalously high wind retrievals found here and elsewhere in current CYGNSS Level 2 data may yield to the science team's recent L1 calibration revision.

Improved Surface Parameter Retrievals using AIRS/AMSU Data

NASA Technical Reports Server (NTRS)

Susskind, Joel; Blaisdell, John

2008-01-01

The AIRS Science Team Version 5.0 retrieval algorithm became operational at the Goddard DAAC in July 2007 generating near real-time products from analysis of AIRS/AMSU sounding data. This algorithm contains many significant theoretical advances over the AIRS Science Team Version 4.0 retrieval algorithm used previously. Two very significant developments of Version 5 are: 1) the development and implementation of an improved Radiative Transfer Algorithm (RTA) which allows for accurate treatment of non-Local Thermodynamic Equilibrium (non-LTE) effects on shortwave sounding channels; and 2) the development of methodology to obtain very accurate case by case product error estimates which are in turn used for quality control. These theoretical improvements taken together enabled a new methodology to be developed which further improves soundings in partially cloudy conditions. In this methodology, longwave C02 channel observations in the spectral region 700 cm(exp -1) to 750 cm(exp -1) are used exclusively for cloud clearing purposes, while shortwave C02 channels in the spectral region 2195 cm(exp -1) 2395 cm(exp -1) are used for temperature sounding purposes. This allows for accurate temperature soundings under more difficult cloud conditions. This paper further improves on the methodology used in Version 5 to derive surface skin temperature and surface spectral emissivity from AIRS/AMSU observations. Now, following the approach used to improve tropospheric temperature profiles, surface skin temperature is also derived using only shortwave window channels. This produces improved surface parameters, both day and night, compared to what was obtained in Version 5. These in turn result in improved boundary layer temperatures and retrieved total O3 burden.

Lexical Retrieval Constrained by Sound Structure: The Role of the Left Inferior Frontal Gyrus

ERIC Educational Resources Information Center

Sharp, David J.; Scott, Sophie K.; Cutler, Anne; Wise, Richard J. S.

2005-01-01

Positron emission tomography was used to investigate two competing hypotheses about the role of the left inferior frontal gyrus (IFG) in word generation. One proposes a domain-specific organization, with neural activation dependent on the type of information being processed, i.e., surface sound structure or semantic. The other proposes a…

Local Time Variation of Water Vapor on Mars using TES Aerobraking Spectra

NASA Astrophysics Data System (ADS)

AlShamsi, M. R.; AlJanaahi, A. A.; Smith, M. D.; Altunaiji, E. S.; Edwards, C. S.

2016-12-01

During the Mars Global Surveyor (MGS) aerobraking phase, the spacecraft was in a large elliptical orbit that enabled the Thermal Emission Spectrometer (TES) instrument to sample many local times of Mars. The observed TES aerobraking spectra during that phase cover the time range between Mars Year 23, Ls=180° and Mars Year 24, Ls=30°. These TES aerobraking spectra have never been analyzed to study local time variations on Mars. Through radiative transfer modeling of the spectra, surface and atmospheric temperature, dust and water ice optical depth, and water vapor were retrieved. Specifically, the water vapor retrievals during aerobraking have similar seasonal and latitudinal trends to those in other Mars years observed by TES. These retrievals show somewhat higher water vapor during the morning hours (09:00-12:00) than in the afternoon (12:00-17:00) during southern summer (Ls=270°-330°) and little variation as a function of local time for southern fall (Ls=0°-30°). These retrievals show water vapor has a positive correlation with surface pressure (or negative correlation with altitude) indicating that water vapor is mixed in the lowest 10-20 km.

Titan's Surface Temperatures Maps from Cassini - CIRS Observations

NASA Astrophysics Data System (ADS)

Cottini, Valeria; Nixon, C. A.; Jennings, D. E.; Anderson, C. M.; Samuelson, R. E.; Irwin, P. G. J.; Flasar, F. M.

2009-09-01

The Cassini Composite Infrared Spectrometer (CIRS) observations of Saturn's largest moon, Titan, are providing us with the ability to detect the surface temperature of the planet by studying its outgoing radiance through a spectral window in the thermal infrared at 19 μm (530 cm-1) characterized by low opacity. Since the first acquisitions of CIRS Titan data the instrument has gathered a large amount of spectra covering a wide range of latitudes, longitudes and local times. We retrieve the surface temperature and the atmospheric temperature profile by modeling proper zonally averaged spectra of nadir observations with radiative transfer computations. Our forward model uses the correlated-k approximation for spectral opacity to calculate the emitted radiance, including contributions from collision induced pairs of CH4, N2 and H2, haze, and gaseous emission lines (Irwin et al. 2008). The retrieval method uses a non-linear least-squares optimal estimation technique to iteratively adjust the model parameters to achieve a spectral fit (Rodgers 2000). We show an accurate selection of the wide amount of data available in terms of footprint diameter on the planet and observational conditions, together with the retrieved results. Our results represent formal retrievals of surface brightness temperatures from the Cassini CIRS dataset using a full radiative transfer treatment, and we compare to the earlier findings of Jennings et al. (2009). In future, application of our methodology over wide areas should greatly increase the planet coverage and accuracy of our knowledge of Titan's surface brightness temperature. References: Irwin, P.G.J., et al.: "The NEMESIS planetary atmosphere radiative transfer and retrieval tool" (2008). JQSRT, Vol. 109, pp. 1136-1150, 2008. Rodgers, C. D.: "Inverse Methods For Atmospheric Sounding: Theory and Practice". World Scientific, Singapore, 2000. Jennings, D.E., et al.: "Titan's Surface Brightness Temperatures." Ap. J. L., Vol. 691, pp. L103-L105, 2009.

Retrieval of land surface temperature (LST) from landsat TM6 and TIRS data by single channel radiative transfer algorithm using satellite and ground-based inputs

NASA Astrophysics Data System (ADS)

Chatterjee, R. S.; Singh, Narendra; Thapa, Shailaja; Sharma, Dravneeta; Kumar, Dheeraj

2017-06-01

The present study proposes land surface temperature (LST) retrieval from satellite-based thermal IR data by single channel radiative transfer algorithm using atmospheric correction parameters derived from satellite-based and in-situ data and land surface emissivity (LSE) derived by a hybrid LSE model. For example, atmospheric transmittance (τ) was derived from Terra MODIS spectral radiance in atmospheric window and absorption bands, whereas the atmospheric path radiance and sky radiance were estimated using satellite- and ground-based in-situ solar radiation, geographic location and observation conditions. The hybrid LSE model which is coupled with ground-based emissivity measurements is more versatile than the previous LSE models and yields improved emissivity values by knowledge-based approach. It uses NDVI-based and NDVI Threshold method (NDVITHM) based algorithms and field-measured emissivity values. The model is applicable for dense vegetation cover, mixed vegetation cover, bare earth including coal mining related land surface classes. The study was conducted in a coalfield of India badly affected by coal fire for decades. In a coal fire affected coalfield, LST would provide precise temperature difference between thermally anomalous coal fire pixels and background pixels to facilitate coal fire detection and monitoring. The derived LST products of the present study were compared with radiant temperature images across some of the prominent coal fire locations in the study area by graphical means and by some standard mathematical dispersion coefficients such as coefficient of variation, coefficient of quartile deviation, coefficient of quartile deviation for 3rd quartile vs. maximum temperature, coefficient of mean deviation (about median) indicating significant increase in the temperature difference among the pixels. The average temperature slope between adjacent pixels, which increases the potential of coal fire pixel detection from background pixels, is significantly larger in the derived LST products than the corresponding radiant temperature images.

Improvement in thin cirrus retrievals using an emissivity-adjusted CO2 slicing algorithm

NASA Astrophysics Data System (ADS)

Zhang, Hong; Menzel, W. Paul

2002-09-01

CO2 slicing has been generally accepted as a useful algorithm for determining cloud top pressure (CTP) and effective cloud amount (ECA) for tropospheric clouds above 600 hPa. To date, the technique has assumed that the surface emissivity is that of a blackbody in the long-wavelength infrared radiances and that the cloud emissivities in spectrally close bands are approximately equal. The modified CO2 slicing algorithm considers adjustments of both surface emissivity and cloud emissivity ratio. Surface emissivity is adjusted according to the surface types. The ratio of cloud emissivities in spectrally close bands is adjusted away from unity according to radiative transfer calculations. The new CO2 slicing algorithm is examined with Moderate Resolution Imaging Spectroradiometer (MODIS) Airborne Simulator (MAS) CO2 band radiance measurements over thin clouds and validated against Cloud Lidar System (CLS) measurements of the same clouds; it is also applied to Geostationary Operational Environmental Satellite (GOES) Sounder data to study the overall impact on cloud property determinations. For high thin clouds an improved product emerges, while for thick and opaque clouds there is little change. For very thin clouds, the CTP increases by about 10-20 hPa and RMS (root mean square bias) difference is approximately 50 hPa; for thin clouds, the CTP increase is about 10 hPa bias and RMS difference is approximately 30 hPa. The new CO2 slicing algorithm places the clouds lower in the troposphere.

Technical development to improve satellite sounding over radiatively complex terrain

NASA Technical Reports Server (NTRS)

Schreiner, A. J.

1985-01-01

High resolution topography was acquired and applied on the McIDAS system. A technique for finding the surface skin temperature in the presence of cloud and reflected sunlight was implemented in the ALPEX retrieval software and the variability of surface emissivity at microwave wavelength was examined. Data containing raw radiances for all HIRS and MSU channels for NOAA-6 and 7 were used. METEOSAT data were used to derive cloud drift and water vapor winds over the Alpine region.

Seasonal Surface Spectral Emissivity Derived from Terra MODIS Data

NASA Technical Reports Server (NTRS)

Sun-Mack, Sunny; Chen, Yan; Minnis, Patrick; Young, DavidF.; Smith, William J., Jr.

2004-01-01

The CERES (Clouds and the Earth's Radiant Energy System) Project is measuring broadband shortwave and longwave radiances and deriving cloud properties form various images to produce a combined global radiation and cloud property data set. In this paper, simultaneous data from Terra MODIS (Moderate Resolution Imaging Spectroradiometer) taken at 3.7, 8.5, 11.0, and 12.0 m are used to derive the skin temperature and the surface emissivities at the same wavelengths. The methodology uses separate measurements of clear sky temperature in each channel determined by scene classification during the daytime and at night. The relationships between the various channels at night are used during the day when solar reflectance affects the 3.7- m radiances. A set of simultaneous equations is then solved to derive the emissivities. Global monthly emissivity maps are derived from Terra MODIS data while numerical weather analyses provide soundings for correcting the observed radiances for atmospheric absorption. These maps are used by CERES and other cloud retrieval algorithms.

Quantifying Wildfire Emissions and associated Aerosol Species using Assimilation of Satellite Carbon Monoxide Retrievals

NASA Astrophysics Data System (ADS)

Edwards, David; Barre, Jerome; Worden, Helen; Gaubert, Benjamin

2017-04-01

Intense and costly wildfires tend are predicted to increase in frequency under a warming climate. For example, the recent August 2015 Washington State fires were the largest in the state's history. Also in September and October 2015 very intense fires over Indonesia produced some of the highest concentrations of carbon monoxide (CO) ever seen from satellite. Such larges fires impact not only the local environment but also affect air quality far downwind through the long-range transport of pollutants. Global to continental scale coverage showing the evolution of CO resulting from fire emission is available from satellite observations. Carbon monoxide is the only atmospheric trace gas for which satellite multispectral retrievals have demonstrated reliable independent profile information close to the surface and also higher in the free troposphere. The unique CO profile product from Terra/MOPITT clearly distinguishes near-surface CO from the free troposphere CO. Also previous studies have suggested strong correlations between primary emissions of fire organic and black carbon aerosols and CO. We will present results from the Ensemble Adjustement Kalman Filter (DART) system that has been developed to assimilate MOPITT CO in the global-scale chemistry-climate model CAM-Chem. The ensemble technique allows inference on various fire model state variables such as CO emissions, and also aerosol species resulting from fires such as organic and black carbon. The benefit of MOPITT CO profile assimilation for estimating the CO emissions from the Washington and Indonesian fire cases will be discussed, along with the ability of the ensemble approach to infer information on the black and organic carbon aerosol distribution. This study builds on capability to quantitatively integrate satellite observations and models developed in recent years through projects funded by the NASA ACMAP Program.

Quantifying the Seasonal and Interannual Variability of North American Isoprene Emissions Using Satellite Observations of the Formaldehyde Column

NASA Technical Reports Server (NTRS)

Palmer, Paul I.; Abbot, Dorian S.; Fu, Tzung-May; Jacob, Daniel J.; Chance, Kelly; Kurosu, Thomas P.; Guenther, Alex; Wiedinmyer, Christine; Stanton, Jenny C.; Pilling, Michael J.;

Diurnal Variations of Titan's Surface Temperatures From Cassini -CIRS Observations

NASA Astrophysics Data System (ADS)

Cottini, Valeria; Nixon, Conor; Jennings, Don; Anderson, Carrie; Samuelson, Robert; Irwin, Patrick; Flasar, F. Michael

The Cassini Composite Infrared Spectrometer (CIRS) observations of Saturn's largest moon, Titan, are providing us with the ability to detect the surface temperature of the planet by studying its outgoing radiance through a spectral window in the thermal infrared at 19 m (530 cm-1) characterized by low opacity. Since the first acquisitions of CIRS Titan data the in-strument has gathered a large amount of spectra covering a wide range of latitudes, longitudes and local times. We retrieve the surface temperature and the atmospheric temperature pro-file by modeling proper zonally averaged spectra of nadir observations with radiative transfer computations. Our forward model uses the correlated-k approximation for spectral opacity to calculate the emitted radiance, including contributions from collision induced pairs of CH4, N2 and H2, haze, and gaseous emission lines (Irwin et al. 2008). The retrieval method uses a non-linear least-squares optimal estimation technique to iteratively adjust the model parameters to achieve a spectral fit (Rodgers 2000). We show an accurate selection of the wide amount of data available in terms of footprint diameter on the planet and observational conditions, together with the retrieved results. Our results represent formal retrievals of surface brightness temperatures from the Cassini CIRS dataset using a full radiative transfer treatment, and we compare to the earlier findings of Jennings et al. (2009). The application of our methodology over wide areas has increased the planet coverage and accuracy of our knowledge of Titan's surface brightness temperature. In particular we had the chance to look for diurnal variations in surface temperature around the equator: a trend with slowly increasing temperature toward the late afternoon reveals that diurnal temperature changes are present on Titan surface. References: Irwin, P.G.J., et al.: "The NEMESIS planetary atmosphere radiative transfer and retrieval tool" (2008). JQSRT, Vol. 109, pp. 1136-1150, 2008. Rodgers, C. D.: "Inverse Methods For Atmospheric Sounding: Theory and Practice". World Scientific, Singapore, 2000. Jennings, D.E., et al.: "Titan's Surface Brightness Temperatures." Ap. J. L., Vol. 691, pp. L103-L105, 2009.

Estimating NOx emissions and surface concentrations at high spatial resolution using OMI

NASA Astrophysics Data System (ADS)

Goldberg, D. L.; Lamsal, L. N.; Loughner, C.; Swartz, W. H.; Saide, P. E.; Carmichael, G. R.; Henze, D. K.; Lu, Z.; Streets, D. G.

2017-12-01

In many instances, NOx emissions are not measured at the source. In these cases, remote sensing techniques are extremely useful in quantifying NOx emissions. Using an exponential modified Gaussian (EMG) fitting of oversampled Ozone Monitoring Instrument (OMI) NO2 data, we estimate NOx emissions and lifetimes in regions where these emissions are uncertain. This work also presents a new high-resolution OMI NO2 dataset derived from the NASA retrieval that can be used to estimate surface level concentrations in the eastern United States and South Korea. To better estimate vertical profile shape factors, we use high-resolution model simulations (Community Multi-scale Air Quality (CMAQ) and WRF-Chem) constrained by in situ aircraft observations to re-calculate tropospheric air mass factors and tropospheric NO2 vertical columns during summertime. The correlation between our satellite product and ground NO2 monitors in urban areas has improved dramatically: r2 = 0.60 in new product, r2 = 0.39 in operational product, signifying that this new product is a better indicator of surface concentrations than the operational product. Our work emphasizes the need to use both high-resolution and high-fidelity models in order to re-calculate vertical column data in areas with large spatial heterogeneities in NOx emissions. The methodologies developed in this work can be applied to other world regions and other satellite data sets to produce high-quality region-specific emissions estimates.

Operational prediction of air quality for the United States: applications of satellite observations

NASA Astrophysics Data System (ADS)

Stajner, Ivanka; Lee, Pius; Tong, Daniel; Pan, Li; McQueen, Jeff; Huang, Jianping; Huang, Ho-Chun; Draxler, Roland; Kondragunta, Shobha; Upadhayay, Sikchya

2015-04-01

Operational predictions of ozone and wildfire smoke over United States (U.S.) and predictions of airborne dust over the contiguous 48 states are provided by NOAA at http://airquality.weather.gov/. North American Mesoscale (NAM) weather predictions with inventory based emissions estimates from the U.S. Environmental Protection Agency (EPA) and chemical processes within the Community Multiscale Air Quality (CMAQ) model are combined together to produce ozone predictions. Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model is used to predict wildfire smoke and dust storm predictions. Routine verification of ozone predictions relies on AIRNow compilation of observations from surface monitors. Retrievals of smoke column integrals from GOES satellites and dust column integrals from MODIS satellite instruments are used for verification of smoke and dust predictions. Recent updates of NOAA's operational air quality predictions have focused on mobile emissions using the projections of mobile sources for 2012. Since emission inventories are complex and take years to assemble and evaluate causing a lag of information, we recently began combing inventory information with projections of mobile sources. In order to evaluate this emission update, these changes in projected NOx emissions from 2005-2012 were compared with observed changes in Ozone Monitoring Instrument (OMI) NO2 observations and NOx measured by surface monitors over large U.S. cities over the same period. Comparisons indicate that projected decreases in NOx emissions from 2005 to 2012 are similar, but not as strong as the decreases in the observed NOx concentrations and in OMI NO2 retrievals. Nevertheless, the use of projected mobile NOx emissions in the predictions reduced biases in predicted NOx concentrations, with the largest improvement in the urban areas. Ozone biases are reduced as well, with the largest improvement seen in rural areas. Recent testing of PM2.5 predictions is relying on emissions inventories augmented by real time sources from wildfires and dust storms. The evaluation of these test predictions relies on surface monitor data, but efforts are in progress to include comparisons with satellite observed aerosol optical depth (AOD) products. Testing of PM2.5 predictions continues to exhibit seasonal biases: overprediction in the winter and underprediction in the summer. The current efforts focus on bias correction and development of linkages with global atmospheric composition predictions.

Differences in liquid cloud droplet effective radius and number concentration estimates between MODIS Collections 5.1 and 6 over global oceans.

PubMed

Rausch, John; Meyer, Kerry; Bennartz, Ralf; Platnick, Steven

2017-01-01

Differences in cloud droplet effective radius and cloud droplet number concentration (CDNC) estimates inferred from the Aqua MODIS Collections 5.1 and 6 cloud products (MYD06) are examined for warm clouds over global oceans for the year 2008. Individual pixel level retrievals for both collections are aggregated to 1° × 1° and compared globally and regionally for the three main spectral channel pairs used for MODIS cloud optical property retrievals. Comparisons between both collections are performed for cases in which all three effective radii retrievals are classified by the MODIS Cloud Product as valid. The contribution to the observed differences of several key MYD06 Collection 6 algorithm updates are also explored, with a focus on changes to the surface reflectance model, assumed solar irradiance, above cloud emission, cloud top pressure, and pixel registration. Global results show a neutral to positive (> 50 cm -3 ) change for C6-derived CDNC relative to C5.1 for the 1.6 µm and 2.1 µm channel retrievals, corresponding to a neutral to -2 µm difference in droplet effective radius. For 3.7 µm retrievals, CDNC results show a negative change in the tropics, with differences transitioning toward positive values with increasing latitude spanning -25 to +50 cm -3 related to a +2.5 to -1 µm transition in effective radius. Cloud optical thickness differences were small relative to effective radius, and found to not significantly impact CDNC estimates. Regionally, the magnitude and behavior of the annual CDNC cycle are compared for each effective radius retrieval. Results from this study indicate significant intercollection differences in aggregated values of effective radius due to changes to the pre-computed retrieval lookup tables for ocean scenes, changes to retrieved cloud top pressure, solar irradiance, or above cloud thermal emission, depending upon spectral channel. The observed differences between collections may have implications for existing MODIS derived climatologies and validation studies of effective radius and CDNC.

Topographic Effects on the Surface Emissivity of a Mountainous Area Observed by a Spaceborne Microwave Radiometer

PubMed Central

Pulvirenti, Luca; Pierdicca, Nazzareno; Marzano, Frank S.

2008-01-01

A simulation study to understand the influence of topography on the surface emissivity observed by a satellite microwave radiometer is carried out. We analyze the effects due to changes in observation angle, including the rotation of the polarization plane. A mountainous area in the Alps (Northern Italy) is considered and the information on the relief extracted from a digital elevation model is exploited. The numerical simulation refers to a radiometric image, acquired by a conically-scanning radiometer similar to AMSR-E, i.e., flying at 705 km of altitude with an observation angle of 55°. To single out the impact on surface emissivity, scattering of the radiation due to the atmosphere or neighboring elevated surfaces is not considered. C and X bands, for which atmospheric effects are negligible, and Ka band are analyzed. The results indicate that the changes in the local observation angle tend to lower the apparent emissivity of a radiometric pixel with respect to the corresponding flat surface characteristics. The effect of the rotation of the polarization plane enlarges (vertical polarization), or attenuates (horizontal polarization) this decrease. By doing some simplifying assumptions for the radiometer antenna, the conclusion is that the microwave emissivity at vertical polarization is underestimated, whilst the opposite occurs for horizontal polarization, except for Ka band, for which both under- and overprediction may occur. A quantification of the differences with respect to a flat soil and an approximate evaluation of their impact on soil moisture retrieval are yielded. PMID:27879773

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.

Hemispheric encoding/retrieval asymmetry in episodic memory: positron emission tomography findings.

PubMed Central

Tulving, E; Kapur, S; Craik, F I; Moscovitch, M; Houle, S

1994-01-01

Data are reviewed from positron emission tomography studies of encoding and retrieval processes in episodic memory. These data suggest a hemispheric encoding/retrieval asymmetry model of prefrontal involvement in encoding and retrieval of episodic memory. According to this model, the left and right prefrontal lobes are part of an extensive neuronal network that subserves episodic remembering, but the two prefrontal hemispheres play different roles. Left prefrontal cortical regions are differentially more involved in retrieval of information from semantic memory and in simultaneously encoding novel aspects of the retrieved information into episodic memory. Right prefrontal cortical regions, on the other hand, are differentially more involved in episodic memory retrieval. PMID:8134342

Global distribution of surface NO2 inferred from Ozone Monitoring Instrument measurements: Relationship between NO2 and population

NASA Astrophysics Data System (ADS)

Lamsal, L.; Martin, R. V.; Parrish, D. D.

2011-12-01

Nitrogen dioxide (NO2) is a short-lived atmospheric pollutant released from combustion processes and is an indicator of air quality. We derive a global distribution of ground-level NO2 concentrations by applying local scaling factors from a global three-dimensional model to tropospheric NO2 columns retrieved from the Ozone Monitoring Instrument. The OMI-derived surface NO2 data are compared with in situ surface NO2 data obtained from the SEARCH, AQS/EPA, and NAPS networks. The correlation between the OMI-derived surface NO2 and the ground-based measurements is generally > 0.5. We examine how NO2 columns measured by satellite, ground-level NO2 derived from satellite, and NOx emissions obtained from bottom-up inventories relate to city population in North America, Europe, and Asia. NO2 increases proportional to population raised to an exponent that is in the range 0.25-0.55. This relationship provides insights into per capita emissions and the quality of air people breathe.

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.

Evaluation of Long-term Aerosol Data Records from SeaWiFS over Land and Ocean

NASA Astrophysics Data System (ADS)

Bettenhausen, C.; Hsu, C.; Jeong, M.; Huang, J.

2010-12-01

Deserts around the globe produce mineral dust aerosols that may then be transported over cities, across continents, or even oceans. These aerosols affect the Earth’s energy balance through direct and indirect interactions with incoming solar radiation. They also have a biogeochemical effect as they deliver scarce nutrients to remote ecosystems. Large dust storms regularly disrupt air traffic and are a general nuisance to those living in transport regions. In the past, measuring dust aerosols has been incomplete at best. Satellite retrieval algorithms were limited to oceans or vegetated surfaces and typically neglected desert regions due to their high surface reflectivity in the mid-visible and near-infrared wavelengths, which have been typically used for aerosol retrievals. The Deep Blue aerosol retrieval algorithm was developed to resolve these shortcomings by utilizing the blue channels from instruments such as the Sea-Viewing Wide-Field-of-View Sensor (SeaWiFS) and the Moderate Resolution Imaging Spectroradiometer (MODIS) to infer aerosol properties over these highly reflective surfaces. The surface reflectivity of desert regions is much lower in the blue channels and thus it is easier to separate the aerosol and surface signals than at the longer wavelengths used in other algorithms. More recently, the Deep Blue algorithm has been expanded to retrieve over vegetated surfaces and oceans as well. A single algorithm can now follow dust from source to sink. In this work, we introduce the SeaWiFS instrument and the Deep Blue aerosol retrieval algorithm. We have produced global aerosol data records over land and ocean from 1997 through 2009 using the Deep Blue algorithm and SeaWiFS data. We describe these data records and validate them with data from the Aerosol Robotic Network (AERONET). We also show the relative performance compared to the current MODIS Deep Blue operational aerosol data in desert regions. The current results are encouraging and this dataset will be useful to future studies in understanding the effects of dust aerosols on global processes, long-term aerosol trends, quantifying dust emissions, transport, and inter-annual variability.

Retrieval of exoplanet emission spectra with HyDRA

NASA Astrophysics Data System (ADS)

Gandhi, Siddharth; Madhusudhan, Nikku

2018-02-01

Thermal emission spectra of exoplanets provide constraints on the chemical compositions, pressure-temperature (P-T) profiles, and energy transport in exoplanetary atmospheres. Accurate inferences of these properties rely on the robustness of the atmospheric retrieval methods employed. While extant retrieval codes have provided significant constraints on molecular abundances and temperature profiles in several exoplanetary atmospheres, the constraints on their deviations from thermal and chemical equilibria have yet to be fully explored. Our present work is a step in this direction. We report HyDRA, a disequilibrium retrieval framework for thermal emission spectra of exoplanetary atmospheres. The retrieval code uses the standard architecture of a parametric atmospheric model coupled with Bayesian statistical inference using the Nested Sampling algorithm. For a given dataset, the retrieved compositions and P-T profiles are used in tandem with the GENESIS self-consistent atmospheric model to constrain layer-by-layer deviations from chemical and radiative-convective equilibrium in the observable atmosphere. We demonstrate HyDRA on the Hot Jupiter WASP-43b with a high-precision emission spectrum. We retrieve an H2O mixing ratio of log(H2O) = -3.54^{+0.82}_{-0.52}, consistent with previous studies. We detect H2O and a combined CO/CO2 at 8-sigma significance. We find the dayside P-T profile to be consistent with radiative-convective equilibrium within the 1-sigma limits and with low day-night redistribution, consistent with previous studies. The derived compositions are also consistent with thermochemical equilibrium for the corresponding distribution of P-T profiles. In the era of high precision and high resolution emission spectroscopy, HyDRA provides a path to retrieve disequilibrium phenomena in exoplanetary atmospheres.

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.

Development of improved wildfire smoke exposure estimates for health studies in the western U.S.

NASA Astrophysics Data System (ADS)

Ivey, C.; Holmes, H.; Loria Salazar, S. M.; Pierce, A.; Liu, C.

2016-12-01

Wildfire smoke exposure is a significant health concern in the western U.S. because large wildfires have increased in size and frequency over the past four years due to drought conditions. The transport phenomena in complex terrain and timing of the wildfire emissions make the smoke plumes difficult to simulate using conventional air quality models. Monitoring data can be used to estimate exposure metrics, but in rural areas the monitoring networks are too sparse to calculate wildfire exposure metrics for the entire population in a region. Satellite retrievals provide global, spatiotemporal air quality information and are used to track pollution plumes, estimate human exposures, model emissions, and determine sources (i.e., natural versus anthropogenic) in regulatory applications. Particulate matter (PM) exposures can be estimated using columnar aerosol optical depth (AOD), where satellite AOD retrievals serve as a spatial surrogate to simulate surface PM gradients. These exposure models have been successfully used in health effects studies in the eastern U.S. where complex mountainous terrain and surface reflectance do not limit AOD retrival from satellites. Using results from a chemical transport model (CTM) is another effective method to determine spatial gradients of pollutants. However, the CTM does not adequately capture the temporal and spatial distribution of wildfire smoke plumes. By combining the spatiotemporal pollutant fields from both satellite retrievals and CTM results with ground based pollutant observations the spatial wildfire smoke exposure model can be improved. This work will address the challenge of understanding the spatiotemporal distributions of pollutant concentrations to model human exposures of wildfire smoke in regions with complex terrain, where meteorological conditions as well as emission sources significantly influence the spatial distribution of pollutants. The focus will be on developing models to enhance exposure estimates of elevated PM and ozone concentrations from wildfire smoke plumes in the western U.S.

Comparisons of Spectral Aerosol Single Scattering Albedo in Seoul, South Korea

NASA Technical Reports Server (NTRS)

Mok, Jungbin; Krotkov, Nickolay A.; Torres, Omar; Jethva, Hiren; Loughman, Robert P.; Spinei, Elena; Campanelli, Monica; Li, Zhanqing; Go, Sujung; Labow, Gordon;

Ground-based remote sensing of thin clouds in the Arctic

NASA Astrophysics Data System (ADS)

Garrett, T. J.; Zhao, C.

2012-11-01

This paper describes a method for using interferometer measurements of downwelling thermal radiation to retrieve the properties of single-layer clouds. Cloud phase is determined from ratios of thermal emission in three "micro-windows" where absorption by water vapor is particularly small. Cloud microphysical and optical properties are retrieved from thermal emission in two micro-windows, constrained by the transmission through clouds of stratospheric ozone emission. Assuming a cloud does not approximate a blackbody, the estimated 95% confidence retrieval errors in effective radius, visible optical depth, number concentration, and water path are, respectively, 10%, 20%, 38% (55% for ice crystals), and 16%. Applied to data from the Atmospheric Radiation Measurement program (ARM) North Slope of Alaska - Adjacent Arctic Ocean (NSA-AAO) site near Barrow, Alaska, retrievals show general agreement with ground-based microwave radiometer measurements of liquid water path. Compared to other retrieval methods, advantages of this technique include its ability to characterize thin clouds year round, that water vapor is not a primary source of retrieval error, and that the retrievals of microphysical properties are only weakly sensitive to retrieved cloud phase. The primary limitation is the inapplicability to thicker clouds that radiate as blackbodies.

Modification of Jupiter's Stratosphere Three Weeks After the 2009 Impact

NASA Technical Reports Server (NTRS)

Fast, Kelly Elizabeth; Kostiuk, T.; Livengood, T. A.; Hewagama, T.; Annen, J.

2010-01-01

Infrared spectroscopy sensitive to thermal emission from Jupiter's stratosphere reveals effects persisting 3 1/2 weeks after the impact of a body in late July 2009. Measurements obtained at 11.7 microns on 2009 August 11 UT at the impact latitude of 56degS (planetocentric), using the Goddard Heterodyne Instrument for Planetary Winds and Composition (HIPWAC) mounted on the NASA Infrared Telescope facility, reveal an interval of reduced thermal continuum emission that extends approx.60deg-80deg towards planetary East of the impact site, estimated to be at 305deg longitude (System III). Retrieved stratospheric ethane mole fraction in the near vicinity of the impact site is enhanced by up to approx.60% relative to quiescent regions at this latitude. Thermal continuum emission at the impact site, and somewhat west of it, is significantly enhanced in the same spectra that retrieve enhanced ethane mole fraction. Assuming that the enhanced continuum brightness near the impact site results from thermalized aerosol debris, then continuum emission by a haze layer can be approximated by an opaque surface inserted at the 45-60 mbar pressure level in the stratosphere in an unperturbed thermal profile, setting a lower limit on the altitude of the top of the ejecta cloud at this time. The reduced continuum brightness east of the impact site can be modeled by an opaque surface near the cold tropopause, consistent with a lower altitude of ejecta/impactor-formed opacity or significantly lesser column density of opaque haze material. The physical extent of the observed region of reduced continuum implies a minimum average velocity of 21 m/s transporting material prograde (East) from the impact. Spectra acquired further East, with quiescent characteristics, imply an average zonal velocity of less than 63 m/s.

Modification of Jupiter's Stratosphere Three Weeks After the 2009 Impact

NASA Technical Reports Server (NTRS)

Fast, Kelly E.; Kostiuk, Theodor; Livengood, Timothy A.; Hewagama, Tilak; Annen, John

2011-01-01

Infrared spectroscopy sensitive to thermal emission from Jupiter's stratosphere reveals effects persisting 23 days after the impact of a body in late July 2009. Measurements obtained on 2009 August II UT at the impact latitude of 56 S (planetocentric), using the Goddard Heterodyne Instrument for Planetary Wind and Composition mounted on the NASA Infrared Telescope Facility, reveal increased ethane abundance and the effects of aerosol opacity. An interval of reduced thermal continuum emission at 11. 744 lm is measured 60o-80 towards planetary east of the impact site, estimated to be at 3050 longitude (System Ill). Retrieved stratospheric ethane mole fraction in the near vicinity of the impact site is enhanced by up to -60% relative to quiescent regions at this latitude. Thermal continuum emission at the impact site, and somewhat west of it, is significantly enhanced in the same spectra that retrieve enhanced ethane mole fraction. Assuming that the enhanced continuum brightness near the impact site results from thermalized aerosol debris blocking contribution from the continuum formed in the upper troposphere and indicating the local temperature, then continuum emission by a haze layer can be approximated by an opaque surface inserted at the 45-60 mbar pressure level in the stratosphere in an unperturbed thermal profile, setting an upper limit on the pressure and therefore a lower limit on the altitude of the top of the impact debris at this time. The reduced continuum brightness east of the impact site can be modeled by an opaque surface near the cold tropopause, which is consistent with a lower altitude of ejecta/impactor-formed opacity or significantly lesser column density of opaque haze material. The physical extent of the observed region of reduced continuum implies a minimum average velocity of 21 m/s transporting material prograde (planetary east) from the impact.

The Status of the NASA MEaSUREs Combined ASTER and MODIS Emissivity Over Land (CAMEL) Products

NASA Astrophysics Data System (ADS)

Borbas, E. E.; Feltz, M.; Hulley, G. C.; Knuteson, R. O.; Hook, S. J.

2017-12-01

As part of a NASA MEaSUREs Land Surface Temperature and Emissivity project, the University of Wisconsin, Space Science and Engineering Center and the NASA's Jet Propulsion Laboratory have developed a global monthly mean emissivity Earth System Data Record (ESDR). The CAMEL ESDR was produced by merging two current state-of-the-art emissivity datasets: the UW-Madison MODIS Infrared emissivity dataset (UWIREMIS), and the JPL ASTER Global Emissivity Dataset v4 (GEDv4). The dataset includes monthly global data records of emissivity, uncertainty at 13 hinge points between 3.6-14.3 µm, and Principal Components Analysis (PCA) coefficients at 5 kilometer resolution for years 2003 to 2015. A high spectral resolution algorithm is also provided for HSR applications. The dataset is currently being tested in sounder retrieval algorithm (e.g. CrIS, IASI) and has already been implemented in RTTOV-12 for immediate use in numerical weather modeling and data assimilation. This poster will present the current status of the dataset.

Retrieval of the Nitrous Oxide Profiles using the AIRS Data in China

NASA Astrophysics Data System (ADS)

Chen, L.; Ma, P.; Tao, J.; Li, X.; Zhang, Y.; Wang, Z.; Li, S.; Xiong, X.

2014-12-01

As an important greenhouse gas and ozone-depleting substance, the 100-year global warming potential of Nitrous Oxide (N2O) is almost 300 times higher than that of carbon dioxide. However, there are still large uncertainties about the quantitative N2O emission and its feedback to climate change due to the coarse ground-based network. This approach attempts to retrieve the N2O profiles from the Atmospheric InfraRed Sounder (AIRS) data. First, the sensitivity of atmospheric temperature and humidity profiles and surface parameters between two spectral absorption bands were simulated by using the radiative transfer model. Second, the eigenvector regression algorithm is used to construct a priori state. Third, an optimal estimate method was developed based on the band selection of N2O. Finally, we compared our retrieved AIRS profiles with HIPPO data, and analyzed the seasonal and annual N2O distribution in China from 2004 to 2013.

Estimation of Land Surface Energy Balance Using Satellite Data of Spatial Reduced Resolution

NASA Astrophysics Data System (ADS)

Vintila, Ruxandra; Radnea, Cristina; Savin, Elena; Poenaru, Violeta

2010-12-01

The paper presents preliminary results concerning the monitoring at national level of several geo-biophysical variables retrieved by remote sensing, in particular those related to drought or aridisation. The study, which is in progress, represents also an exercise for to the implementation of a Land Monitoring Core Service for Romania, according to the Kopernikus Program and in compliance with the INSPIRE Directive. The SEBS model has been used to retrieve land surface energy balance variables, such as turbulent heat fluxes, evaporative fraction and daily evaporation, based on three information types: (1) surface albedo, emissivity, temperature, fraction of vegetation cover (fCover), leaf area index (LAI) and vegetation height; (2) air pressure, temperature, humidity and wind speed at the planetary boundary layer (PBL) height; (3) downward solar radiation and downward longwave radiation. AATSR and MERIS archived reprocessed images have provided several types of information. Thus, surface albedo, emissivity, and land surface temperature have been retrieved from AATSR, while LAI and fCover have been estimated from MERIS. The vegetation height has been derived from CORINE Land Cover and PELCOM Land Use databases, while the meteorological information at the height of PBL have been estimated from the measurements provided by the national weather station network. Other sources of data used during this study have been the GETASSE30 digital elevation model with 30" spatial resolution, used for satellite image orthorectification, and the SIGSTAR-200 geographical information system of soil resources of Romania, used for water deficit characterisation. The study will continue by processing other AATSR and MERIS archived images, complemented by the validation of SEBS results with ground data collected on the most important biomes for Romania at various phenological stages, and the transformation of evaporation / evapotranspiration into a drought index using the soil texture data. It is also foreseen to develop procedures for processing near-real time AATSR and MERIS images from the rolling archives, as well as procedures for dealing with SENTINEL 3 images in the future, for timely delivery of reliable information to authorities and planning for drought to reduce its effects on citizens.

On the Response of the Special Sensor Microwave/Imager to the Marine Environment: Implications for Atmospheric Parameter Retrievals. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Petty, Grant W.

1990-01-01

A reasonably rigorous basis for understanding and extracting the physical information content of Special Sensor Microwave/Imager (SSM/I) satellite images of the marine environment is provided. To this end, a comprehensive algebraic parameterization is developed for the response of the SSM/I to a set of nine atmospheric and ocean surface parameters. The brightness temperature model includes a closed-form approximation to microwave radiative transfer in a non-scattering atmosphere and fitted models for surface emission and scattering based on geometric optics calculations for the roughened sea surface. The combined model is empirically tuned using suitable sets of SSM/I data and coincident surface observations. The brightness temperature model is then used to examine the sensitivity of the SSM/I to realistic variations in the scene being observed and to evaluate the theoretical maximum precision of global SSM/I retrievals of integrated water vapor, integrated cloud liquid water, and surface wind speed. A general minimum-variance method for optimally retrieving geophysical parameters from multichannel brightness temperature measurements is outlined, and several global statistical constraints of the type required by this method are computed. Finally, a unified set of efficient statistical and semi-physical algorithms is presented for obtaining fields of surface wind speed, integrated water vapor, cloud liquid water, and precipitation from SSM/I brightness temperature data. Features include: a semi-physical method for retrieving integrated cloud liquid water at 15 km resolution and with rms errors as small as approximately 0.02 kg/sq m; a 3-channel statistical algorithm for integrated water vapor which was constructed so as to have improved linear response to water vapor and reduced sensitivity to precipitation; and two complementary indices of precipitation activity (based on 37 GHz attenuation and 85 GHz scattering, respectively), each of which are relatively insensitive to variations in other environmental parameters.

Pre-Launch Performance Assessment of the VIIRS Land Surface Temperature Environmental Data Record

NASA Astrophysics Data System (ADS)

Hauss, B.; Ip, J.; Agravante, H.

2009-12-01

The Visible/Infrared Imager Radiometer Suite (VIIRS) Land Surface Temperature (LST) Environmental Data Record (EDR) provides the surface temperature of land surface including coastal and inland-water pixels at VIIRS moderate resolution (750m) during both day and night. To predict the LST under optimal conditions, the retrieval algorithm utilizes a dual split-window approach with both Short-wave Infrared (SWIR) channels at 3.70 µm (M12) and 4.05 µm (M13), and Long-wave Infrared (LWIR) channels at 10.76 µm (M15) and 12.01 µm (M16) to correct for atmospheric water vapor. Under less optimal conditions, the algorithm uses a fallback split-window approach with M15 and M16 channels. By comparison, the MODIS generalized split-window algorithm only uses the LWIR bands in the retrieval of surface temperature because of the concern for both solar contamination and large emissivity variations in the SWIR bands. In this paper, we assess whether these concerns are real and whether there is an impact on the precision and accuracy of the LST retrieval. The algorithm relies on the VIIRS Cloud Mask IP for identifying cloudy and ocean pixels, the VIIRS Surface Type EDR for identifying the IGBP land cover type for the pixels, and the VIIRS Aerosol Optical Thickness (AOT) IP for excluding pixels with AOT greater than 1.0. In this paper, we will report the pre-launch performance assessment of the LST EDR based on global synthetic data and proxy data from Terra MODIS. Results of both the split-window and dual split-window algorithms will be assessed by comparison either to synthetic "truth" or results of the MODIS retrieval. We will also show that the results of the assessment with proxy data are consistent with those obtained using the global synthetic data.

Non-Contact Measurement of the Spectral Emissivity through Active/Passive Synergy of CO₂ Laser at 10.6 µm and 102F FTIR (Fourier Transform Infrared) Spectrometer.

PubMed

Zhang, Ren-Hua; Su, Hong-Bo; Tian, Jing; Mi, Su-Juan; Li, Zhao-Liang

2016-06-24

In the inversion of land surface temperature (LST) from satellite data, obtaining the information on land surface emissivity is most challenging. How to solve both the emissivity and the LST from the underdetermined equations for thermal infrared radiation is a hot research topic related to quantitative thermal infrared remote sensing. The academic research and practical applications based on the temperature-emissivity retrieval algorithms show that directly measuring the emissivity of objects at a fixed thermal infrared waveband is an important way to close the underdetermined equations for thermal infrared radiation. Based on the prior research results of both the authors and others, this paper proposes a new approach of obtaining the spectral emissivity of the object at 8-14 µm with a single-band CO₂ laser at 10.6 µm and a 102F FTIR spectrometer. Through experiments, the spectral emissivity of several key samples, including aluminum plate, iron plate, copper plate, marble plate, rubber sheet, and paper board, at 8-14 µm is obtained, and the measured data are basically consistent with the hemispherical emissivity measurement by a Nicolet iS10 FTIR spectrometer for the same objects. For the rough surface of materials, such as marble and rusty iron, the RMSE of emissivity is below 0.05. The differences in the field of view angle and in the measuring direction between the Nicolet FTIR method and the method proposed in the paper, and the heterogeneity in the degree of oxidation, polishing and composition of the samples, are the main reasons for the differences of the emissivities between the two methods.

Non-Contact Measurement of the Spectral Emissivity through Active/Passive Synergy of CO2 Laser at 10.6 µm and 102F FTIR (Fourier Transform Infrared) Spectrometer

PubMed Central

Zhang, Ren-Hua; Su, Hong-Bo; Tian, Jing; Mi, Su-Juan; Li, Zhao-Liang

2016-01-01

In the inversion of land surface temperature (LST) from satellite data, obtaining the information on land surface emissivity is most challenging. How to solve both the emissivity and the LST from the underdetermined equations for thermal infrared radiation is a hot research topic related to quantitative thermal infrared remote sensing. The academic research and practical applications based on the temperature-emissivity retrieval algorithms show that directly measuring the emissivity of objects at a fixed thermal infrared waveband is an important way to close the underdetermined equations for thermal infrared radiation. Based on the prior research results of both the authors and others, this paper proposes a new approach of obtaining the spectral emissivity of the object at 8–14 µm with a single-band CO2 laser at 10.6 µm and a 102F FTIR spectrometer. Through experiments, the spectral emissivity of several key samples, including aluminum plate, iron plate, copper plate, marble plate, rubber sheet, and paper board, at 8–14 µm is obtained, and the measured data are basically consistent with the hemispherical emissivity measurement by a Nicolet iS10 FTIR spectrometer for the same objects. For the rough surface of materials, such as marble and rusty iron, the RMSE of emissivity is below 0.05. The differences in the field of view angle and in the measuring direction between the Nicolet FTIR method and the method proposed in the paper, and the heterogeneity in the degree of oxidation, polishing and composition of the samples, are the main reasons for the differences of the emissivities between the two methods. PMID:27347964

Thermal measurements of dark and bright surface features on Vesta as derived from Dawn/VIR

USGS Publications Warehouse

Tosi, Federico; Capria, Maria Teresa; De Sanctis, M.C.; Combe, J.-Ph.; Zambon, F.; Nathues, A.; Schröder, S.E.; Li, J.-Y.; Palomba, E.; Longobardo, A.; Blewett, D.T.; Denevi, B.W.; Palmer, E.; Capaccioni, F.; Ammannito, E.; Titus, Timothy N.; Mittlefehldt, D.W.; Sunshine, J.M.; Russell, C.T.; Raymond, C.A.; Dawn/VIR Team,

2014-01-01

Remote sensing data acquired during Dawn’s orbital mission at Vesta showed several local concentrations of high-albedo (bright) and low-albedo (dark) material units, in addition to spectrally distinct meteorite impact ejecta. The thermal behavior of such areas seen at local scale (1-10 km) is related to physical properties that can provide information about the origin of those materials. We use Dawn’s Visible and InfraRed (VIR) mapping spectrometer hyperspectral data to retrieve surface temperatures and emissivities, with high accuracy as long as temperatures are greater than 220 K. Some of the dark and bright features were observed multiple times by VIR in the various mission phases at variable spatial resolution, illumination and observation angles, local solar time, and heliocentric distance. This work presents the first temperature maps and spectral emissivities of several kilometer-scale dark and bright material units on Vesta. Results retrieved from the infrared data acquired by VIR show that bright regions generally correspond to regions with lower temperature, while dark regions correspond to areas with higher temperature. During maximum daily insolation and in the range of heliocentric distances explored by Dawn, i.e. 2.23-2.54 AU, the warmest dark unit found on Vesta rises to a temperature of 273 K, while bright units observed under comparable conditions do not exceed 266 K. Similarly, dark units appear to have higher emissivity on average compared to bright units. Dark-material units show a weak anticorrelation between temperature and albedo, whereas the relation is stronger for bright material units observed under the same conditions. Individual features may show either evanescent or distinct margins in the thermal images, as a consequence of the cohesion of the surface material. Finally, for the two categories of dark and bright materials, we were able to highlight the influence of heliocentric distance on surface temperatures, and estimate an average temperature rate change of 1% following a variation of 0.04 AU in the solar distance.

SMOS after 2 YEARS and a half in orbit

NASA Astrophysics Data System (ADS)

Kerr, Y.; Richaume, P.; Wigneron, J.-P.; Waldteufel, P.; Mecklenburg, S.; Cabot, F.; Boutin, J.; Font, J.; Reul, N.

2012-04-01

The SMOS (Soil Moisture and Ocean Salinity) satellite was successfully launched in November 2009. This ESA led mission for Earth Observation is dedicated to provide soil moisture over continental surface (with an accuracy goal of 0.04 m3/m3) and ocean salinity. These two geophysical features are important as they control the energy balance between the surface and the atmosphere. Their knowledge at a global scale is of interest for climatic and weather researches in particular in improving models forecasts. The purpose of this communication is to present the mission results after more than two years in orbit as well as some outstanding results already obtained. A special attention will be devoted to level 2 products. Modeling multi-angular brightness temperatures is not straightforward. The radiative model transfer model L-MEB (L-band Microwave Emission) is used over land while different models with different approaches as to the modeling of sea surface roughness are used over ocean surfaces. Over land the approach is based on semi-empirical relationships, adapted to different type of surface. The model computes a dielectric constant leading to surface emissivity. Surface features (roughness, vegetation) are also considered in the models. However, considering SMOS spatial resolution a wide area is seen by the instrument with strong heterogeneity. The L2 soil moisture retrieval scheme takes this into account. Brightness temperatures are computed for every classes composing a working area. A weighted function is applied for the incidence angle and the antenna beam. Once the brightness temperature is computed for the entire working area, the minimizing process starts. If no soil moisture is derived (not attempted or process failed) a dielectric constant is still derived from an simplified modeled (the cardioid model). SMOS data enabled very quickly to infer Sea surface salinity fields. As salinity retrieval is quite challenging, retrieving it enable to assess very finely the characteristics of the complete system in terms of stability, drift etc. Some anomalies such as the ascending descending temperature differences, temporal drifts or land sea contamination were used to infer issues and improve data quality. The modeling has to account for several perturbing factors 'galactic reflection, sea state, atmospheric path and Faraday rotation etc…as the useful signal is quite small when compared to the perturbing factors impact as well as the instrument sensitivity. Over sea ice several studies showed that it was possible to infer thin ice (first year ice, 50 cm or less) from SMOS measurements. Other studies focused on the Antarctic plateau with also very interesting new results. This presentation will show in detail the SMOS in flight results. The retrieval schemes have been developed to reach science requirements, that is to derive the surface soil moisture over continental surface with an accuracy better than 0,04m3/m3. Over the ocean the goals are not yet satisfied but results are already getting close to the requirements.

Combining Passive Microwave Sounders with CYGNSS information for improved retrievals: Observations during Hurricane Harvey

NASA Astrophysics Data System (ADS)

Schreier, M. M.

2017-12-01

The launch of CYGNSS (Cyclone Global Navigation Satellite System) has added an interesting component to satellite observations: it can provide wind speeds in the tropical area with a high repetition rate. Passive microwave sounders that are overpassing the same region can benefit from this information, when it comes to the retrieval of temperature or water profiles: the uncertainty about wind speeds has a strong impact on emissivity and reflectivity calculations with respect to surface temperature. This has strong influences on the uncertainty of retrieval of temperature and water content, especially under extreme weather conditions. Adding CYGNSS information to the retrieval can help to reduce errors and provide a significantly better sounder retrieval. Based on observations during Hurricane Harvey, we want to show the impact of CYGNSS data on the retrieval of passive microwave sensors. We will show examples on the impact on the retrieval from polar orbiting instruments, like the Advanced Technology Microwave Sounder (ATMS) and AMSU-A/B on NOAA-18 and 19. In addition we will also show the impact on retrievals from HAMSR (High Altitude MMIC Sounding Radiometer), which was flying on the Global Hawk during the EPOCH campaign. We will compare the results with other observations and estimate the impact of additional CYGNSS information on the microwave retrieval, especially on the impact in error and uncertainty reduction. We think, that a synergetic use of these different data sources could significantly help to produce better assimilation products for forecast assimilation.

Recent Advances in the Salinity Retrieval Algorithms for Aquarius and SMAP

NASA Astrophysics Data System (ADS)

Meissner, T.; Wentz, F. J.

2016-12-01

Our presentation discusses the latest improvements in the salinity retrievals for both Aquarius and SMAP since the last releases. The Aquarius V4.0 was released in June 2015 and the SMAP V 1.0 was released in November 2015. Upcoming releases are planned for SMAP (V 2.0) in August 2016 and for Aquarius (V 5.0) late 2017. The full 360o look capability of SMAP makes it possible to take observations from the forward and backward looking direction at the same instance of time. This two-look capability strongly aids the salinity retrievals. One of the largest spurious contaminations in the salinity retrievals is caused by the galaxy that is reflected from the ocean surface. Because in most instances the reflected galaxy appears only in either the forward or the backward look, it is possible to determine its contribution by taking the difference of the measured SMAP brightness temperatures between the two looks. Our result suggests that the surface roughness that is used in the galactic correction needs to be increased and also the strength of some of the galactic sources need to be slightly adjusted. The improved galaxy correction is getting implemented in upcoming Aquarius and SMAP salinity releases and strongly aids the mitigation of residual zonal and temporal biases that are observed in both products. Another major cause of the observed zonal biases in SMAP is the emissive SMAP mesh antenna. In order to correct for it the physical temperature of the antenna is needed. No direct measurements but only a thermal model are available. We discuss recent improvements in the correction for the emissive SMAP antenna and show how most of the zonal biases in V1.0 can be mitigated. Finally, we show that observed salty biases at higher Northern latitudes can be explained by inaccuracies in the model that is used in correcting for the absorption by atmospheric oxygen. These biases can be decreased by fine-tuning the parameters in the absorption model.

Quantification of CO emissions from the city of Madrid using MOPITT satellite retrievals and WRF simulations

NASA Astrophysics Data System (ADS)

Dekker, Iris N.; Houweling, Sander; Aben, Ilse; Röckmann, Thomas; Krol, Maarten; Martínez-Alonso, Sara; Deeter, Merritt N.; Worden, Helen M.

2017-12-01

The growth of mega-cities leads to air quality problems directly affecting the citizens. Satellite measurements are becoming of higher quality and quantity, which leads to more accurate satellite retrievals of enhanced air pollutant concentrations over large cities. In this paper, we compare and discuss both an existing and a new method for estimating urban-scale trends in CO emissions using multi-year retrievals from the MOPITT satellite instrument. The first method is mainly based on satellite data, and has the advantage of fewer assumptions, but also comes with uncertainties and limitations as shown in this paper. To improve the reliability of urban-to-regional scale emission trend estimation, we simulate MOPITT retrievals using the Weather Research and Forecast model with chemistry core (WRF-Chem). The difference between model and retrieval is used to optimize CO emissions in WRF-Chem, focusing on the city of Madrid, Spain. This method has the advantage over the existing method in that it allows both a trend analysis of CO concentrations and a quantification of CO emissions. Our analysis confirms that MOPITT is capable of detecting CO enhancements over Madrid, although significant differences remain between the yearly averaged model output and satellite measurements (R2 = 0.75) over the city. After optimization, we find Madrid CO emissions to be lower by 48 % for 2002 and by 17 % for 2006 compared with the EdgarV4.2 emission inventory. The MOPITT-derived emission adjustments lead to better agreement with the European emission inventory TNO-MAC-III for both years. This suggests that the downward trend in CO emissions over Madrid is overestimated in EdgarV4.2 and more realistically represented in TNO-MACC-III. However, our satellite and model based emission estimates have large uncertainties, around 20 % for 2002 and 50 % for 2006.

Constraining the uncertainty in emissions over India with a regional air quality model evaluation

NASA Astrophysics Data System (ADS)

Karambelas, Alexandra; Holloway, Tracey; Kiesewetter, Gregor; Heyes, Chris

2018-02-01

To evaluate uncertainty in the spatial distribution of air emissions over India, we compare satellite and surface observations with simulations from the U.S. Environmental Protection Agency (EPA) Community Multi-Scale Air Quality (CMAQ) model. Seasonally representative simulations were completed for January, April, July, and October 2010 at 36 km × 36 km using anthropogenic emissions from the Greenhouse Gas-Air Pollution Interaction and Synergies (GAINS) model following version 5a of the Evaluating the Climate and Air Quality Impacts of Short-Lived Pollutants project (ECLIPSE v5a). We use both tropospheric columns from the Ozone Monitoring Instrument (OMI) and surface observations from the Central Pollution Control Board (CPCB) to closely examine modeled nitrogen dioxide (NO2) biases in urban and rural regions across India. Spatial average evaluation with satellite retrievals indicate a low bias in the modeled tropospheric column (-63.3%), which reflects broad low-biases in majority non-urban regions (-70.1% in rural areas) across the sub-continent to slightly lesser low biases reflected in semi-urban areas (-44.7%), with the threshold between semi-urban and rural defined as 400 people per km2. In contrast, modeled surface NO2 concentrations exhibit a slight high bias of +15.6% when compared to surface CPCB observations predominantly located in urban areas. Conversely, in examining extremely population dense urban regions with more than 5000 people per km2 (dense-urban), we find model overestimates in both the column (+57.8) and at the surface (+131.2%) compared to observations. Based on these results, we find that existing emission fields for India may overestimate urban emissions in densely populated regions and underestimate rural emissions. However, if we rely on model evaluation with predominantly urban surface observations from the CPCB, comparisons reflect model high biases, contradictory to the knowledge gained using satellite observations. Satellites thus serve as an important emissions and model evaluation metric where surface observations are lacking, such as rural India, and support improved emissions inventory development.

Simultaneous retrieval of the solar EUV flux and neutral thermospheric O, O2, N2, and temperature from twilight airglow

NASA Technical Reports Server (NTRS)

Fennelly, J. A.; Torr, D. G.; Richards, P. G.; Torr, M. R.

1994-01-01

We present a method to retrieve neutral thermospheric composition and the solar EUV flux from ground-based twilight optical measurements of the O(+) ((exp 2)P) 7320 A and O((exp 1)D) 6300 A airglow emissions. The parameters retrieved are the neutral temperature, the O, O2, N2 density profiles, and a scaling factor for the solar EUV flux spectrum. The temperature, solar EUV flux scaling factor, and atomic oxygen density are first retrieved from the 7320-A emission, which are then used with the 6300-A emission to retrieve the O2 and N2 densities. The retrieval techniques have been verified by computer simulations. We have shown that the retrieval technique is able to statistically retrieve values, between 200 and 400 km, within an average error of 3.1 + or - 0.6% for thermospheric temperature, 3.3 + or - 2.0% for atomic oxygen, 2.3 + or - 1.3% for molecular oxygen, and 2.4 + or - 1.3% for molecular nitrogen. The solar EUV flux scaling factor was found to have a retrieval error of 5.1 + or - 2.3%. All the above errors have a confidence level of 95%. The purpose of this paper is to prove the viability and usefulness of the retrieval technique by demonstrating the ability to retrieve known quantities under a realistic simulation of the measurement process, excluding systematic effects.

Polarizability tensor retrieval for magnetic and plasmonic antenna design

NASA Astrophysics Data System (ADS)

Bernal Arango, Felipe; Femius Koenderink, A.

2013-07-01

A key quantity in the design of plasmonic antennas and metasurfaces, as well as metamaterials, is the electrodynamic polarizability of a single scattering building block. In particular, in the current merging of plasmonics and metamaterials, subwavelength scatterers are judged by their ability to present a large, generally anisotropic electric and magnetic polarizability, as well as a bi-anisotropic magnetoelectric polarizability. This bi-anisotropic response, whereby a magnetic dipole is induced through electric driving, and vice versa, is strongly linked to the optical activity and chiral response of plasmonic metamolecules. We present two distinct methods to retrieve the polarizibility tensor from electrodynamic simulations. As a basis for both, we use the surface integral equation (SIE) method to solve for the scattering response of arbitrary objects exactly. In the first retrieval method, we project scattered fields onto vector spherical harmonics with the aid of an exact discrete spherical harmonic Fourier transform on the unit sphere. In the second, we take the effective current distributions generated by SIE as a basis to calculate dipole moments. We verify that the first approach holds for scatterers of any size, while the second is only approximately correct for small scatterers. We present benchmark calculations, revisiting the zero-forward scattering paradox of Kerker et al (1983 J. Opt. Soc. Am. 73 765-7) and Alù and Engheta (2010 J. Nanophoton. 4 041590), relevant in dielectric scattering cancelation and sensor cloaking designs. Finally, we report the polarizability tensor of split rings, and show that split rings will strongly influence the emission of dipolar single emitters. In the context of plasmon-enhanced emission, split rings can imbue their large magnetic dipole moment on the emission of simple electric dipole emitters. We present a split ring antenna array design that is capable of converting the emission of a single linear dipole emitter in forward and backward beams of directional emission of opposite handedness. This design can, for instance, find application in the spin angular momentum encoding of quantum information.

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.

Estimation of Methane Emissions in the Los Angeles Basin using CLARS-FTS Observations

NASA Astrophysics Data System (ADS)

Sander, S.; Zeng, Z. C.; Pongetti, T.; Duren, R. M.; Shia, R. L.; Yung, Y. L.; He, L.; Gurney, K. R.

2017-12-01

The Los Angeles Basin (LA Basin), covering almost 10,743 square miles, is home to over 16.8 million people - about half the population of the state of California. It is also the second most populated urban area in the United States and one of the major source of anthropogenic greenhouse gases. Using FTIR observations from the California Laboratory for Atmospheric Remote Sensing (CLARS) located on Mount Wilson at an altitude of 1673m, we measure the reflected near infrared sunlight from 33 surface targets in the Los Angeles megacity including the direct solar beam which gives the free tropospheric background. We then retrieve the excess slant column abundances of important trace gases such as carbon dioxide (CO2) and methane (CH4) in the LA basin. Using atmospheric tracer - tracer correlations for CH4 and CO2 to eliminate the effect of aerosol scattering in the retrieval, we infer methane emissions based on the ratio of XCH4 excess to XCO2 excess. Significant variability is observed in the spatial distributions of excess CH4. Methane emissions in the LA basin show consistent peaks in late summer and winter during the period from Sep 2011 to the present. The strong correlation between natural gas usage data and derived CLARS methane emissions (r2 = 0.5) implies that natural gas leakage during transmission and/or consumption accounts for a significant fraction of the inferred seasonal variability of methane emissions in the LA basin. We will report updated annual trends in CH4 emissions from 2011 to the present. Copyright 2017. All rights reserved.

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.

Synegies Between Visible/Near-Infrared Imaging Spectrometry and the Thermal Infrared in an Urban Environment: An Evaluation of the Hyperspectral Infrared Imager (HYSPIRI) Mission

NASA Technical Reports Server (NTRS)

Roberts, Dar A.; Quattrochi, Dale A.; Hulley, Glynn C.; Hook, Simon J.; Green, Robert O.

2012-01-01

A majority of the human population lives in urban areas and as such, the quality of urban environments is becoming increasingly important to the human population. Furthermore, these areas are major sources of environmental contaminants and sinks of energy and materials. Remote sensing provides an improved understanding of urban areas and their impacts by mapping urban extent, urban composition (vegetation and impervious cover fractions), and urban radiation balance through measures of albedo, emissivity and land surface temperature (LST). Recently, the National Research Council (NRC) completed an assessment of remote sensing needs for the next decade (NRC, 2007), proposing several missions suitable for urban studies, including a visible, near-infrared and shortwave infrared (VSWIR) imaging spectrometer and a multispectral thermal infrared (TIR) instrument called the Hyperspectral Infrared Imagery (HyspIRI). In this talk, we introduce the HyspIRI mission, focusing on potential synergies between VSWIR and TIR data in an urban area. We evaluate potential synergies using an Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and MODIS-ASTER (MASTER) image pair acquired over Santa Barbara, United States. AVIRIS data were analyzed at their native spatial resolutions (7.5m VSWIR and 15m TIR), and aggregated 60 m spatial resolution similar to HyspIRI. Surface reflectance was calculated using ACORN and a ground reflectance target to remove atmospheric and sensor artifacts. MASTER data were processed to generate estimates of spectral emissivity and LST using Modtran radiative transfer code and the ASTER Temperature Emissivity Separation algorithm. A spectral library of common urban materials, including urban vegetation, roofs and roads was assembled from combined AVIRIS and field-measured reflectance spectra. LST and emissivity were also retrieved from MASTER and reflectance/emissivity spectra for a subset of urban materials were retrieved from co-located MASTER and AVIRIS pixels. Fractions of Impervious, Soil, Green Vegetation (GV) and Non-photosynthetic Vegetation (NPV), were estimated using Multiple Endmember Spectral Mixture Analysis (MESMA) applied to AVIRIS data at 7.5, 15 and 60 m spatial scales. Surface energy parameters, including albedo, vegetation cover fraction, broadband emissivity and LST were also determined for urban and natural land-cover classes in the region. Fractions were validated using 1m digital photography.

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.;

An assessment of the land surface emissivity in the 8 - 12 micrometer window determined from ASTER and MODIS data

NASA Astrophysics Data System (ADS)

Schmugge, T.; Hulley, G.; Hook, S.

2009-04-01

The land surface emissivity is often overlooked when considering surface properties that effect the energy balance. However, knowledge of the emissivity in the window region is important for determining the longwave radiation balance and its subsequent effect on surface temperature. The net longwave radiation (NLR) is strongly affected by the difference between the temperature of the emitting surface and the sky brightness temperature, this difference will be the greatest in the window region. Outside the window region any changes in the emitted radiation by emissivity variability are mostly compensated for by changes in the reflected sky brightness. The emissivity variability is typically greatest in arid regions where the exposed soil and rock surfaces display the widest range of emissivity. For example, the dune regions of North Africa have emissivities of 0.7 or less in the 8 to 9 micrometer wavelength band due to the quartz sands of the region, which can produce changes in NLR of more than 10 w/m*m compared to assuming a constant emissivity. The errors in retrievals of atmospheric temperature and moisture profiles from hyperspectral infrared radiances, such as those from the Atmospheric Infrared Sounder (AIRS) on the NASA Aqua satellite result from using constant or inaccurate surface emissivities, particularly over arid and semi-arid regions here the variation in emissivity is large, both spatially and spectrally. The multispectral thermal infrared data obtained from the Advanced Spaceborne Thermal Emission and Reflection (ASTER) radiometer and MODerate resolution Imaging Spectrometer (MODIS) sensors on NASA's Terra satellite have been shown to be of good quality and provide a unique new tool for studying the emissivity of the land surface. ASTER has 5 channels in the 8 to 12 micrometer waveband with 90 m spatial resolution, when the data are combined with the Temperature Emissivity Separation (TES) algorithm the surface emissivity over this wavelength region can be determined. The TES algorithm has been validated with field measurements using a multi-spectral radiometer having similar bands to ASTER. The ASTER data have now been used to produce a seasonal gridded database of the emissivity for North America and the results compared to laboratory measured emissivities of in-situ rock/sand samples collected at ten validation sites in the Western USA during 2008. The directional hemispherical reflectance of the in-situ samples are measured in the laboratory using a Nicolet Fourier Transform Interferometer (FTIR), converted to emissivity using Kirchoff's law, and convolving to the appropriate sensor spectral response functions. This ASTER database, termed the North American ASTER Land Surface Emissivity Database (NAALSED), was validated using the laboratory results from these ten sites to within 0.015 (1.5%) in emissivity. MODIS has 3 channels in this waveband with 1km spatial resolution and almost daily global coverage. The MODIS data are composited to 5 km resolution and day night pairs of observations are used to derive the emissivities. These results have been validated using the ASTER emissivities over selected test areas.

Differences in liquid cloud droplet effective radius and number concentration estimates between MODIS Collections 5.1 and 6 over global oceans

PubMed Central

Rausch, John; Meyer, Kerry; Bennartz, Ralf; Platnick, Steven

2017-01-01

Differences in cloud droplet effective radius and cloud droplet number concentration (CDNC) estimates inferred from the Aqua MODIS Collections 5.1 and 6 cloud products (MYD06) are examined for warm clouds over global oceans for the year 2008. Individual pixel level retrievals for both collections are aggregated to 1° × 1° and compared globally and regionally for the three main spectral channel pairs used for MODIS cloud optical property retrievals. Comparisons between both collections are performed for cases in which all three effective radii retrievals are classified by the MODIS Cloud Product as valid. The contribution to the observed differences of several key MYD06 Collection 6 algorithm updates are also explored, with a focus on changes to the surface reflectance model, assumed solar irradiance, above cloud emission, cloud top pressure, and pixel registration. Global results show a neutral to positive (> 50 cm−3) change for C6-derived CDNC relative to C5.1 for the 1.6 µm and 2.1 µm channel retrievals, corresponding to a neutral to −2 µm difference in droplet effective radius. For 3.7 µm retrievals, CDNC results show a negative change in the tropics, with differences transitioning toward positive values with increasing latitude spanning −25 to +50 cm−3 related to a +2.5 to −1 µm transition in effective radius. Cloud optical thickness differences were small relative to effective radius, and found to not significantly impact CDNC estimates. Regionally, the magnitude and behavior of the annual CDNC cycle are compared for each effective radius retrieval. Results from this study indicate significant intercollection differences in aggregated values of effective radius due to changes to the pre-computed retrieval lookup tables for ocean scenes, changes to retrieved cloud top pressure, solar irradiance, or above cloud thermal emission, depending upon spectral channel. The observed differences between collections may have implications for existing MODIS derived climatologies and validation studies of effective radius and CDNC. PMID:29098040

Differences in Liquid Cloud Droplet Effective Radius and Number Concentration Estimates Between MODIS Collections 5.1 and 6 Over Global Oceans

NASA Technical Reports Server (NTRS)

Rausch, John; Meyer, Kerry; Bennartz, Ralf; Platnick, Steven

2017-01-01

Differences in cloud droplet effective radius and cloud droplet number concentration (CDNC) estimates inferred from the Aqua MODIS Collections 5.1 and 6 cloud products (MYD06) are examined for warm clouds over global oceans for the year 2008. Individual pixel level retrievals for both collections are aggregated to 1 degree x 1 degree and compared globally and regionally for the three main spectral channel pairs used for MODIS cloud optical property retrievals. Comparisons between both collections are performed for cases in which all three effective radii retrievals are classified by the MODIS Cloud Product as valid. The contribution to the observed differences of several key MYD06 Collection 6 algorithm updates are also explored, with a focus on changes to the surface reflectance model, assumed solar irradiance, above cloud emission, cloud top pressure, and pixel registration. Global results show a neutral to positive ( greater than 50cm(exp. -3) change for C6-derived CDNC relative to C5.1 for the 1.6 micrometers and 2.1 micrometers channel retrievals, corresponding to a neutral to -2 micrometers difference in droplet effective radius. For 3.7 micrometer retrievals, CDNC results show a negative change in the tropics, with differences transitioning toward positive values with increasing latitude spanning -25 to +50 cm(exp. -3) related to a +2.5 to -1 micrometers transition in effective radius. Cloud optical thickness differences were small relative to effective radius, and found to not significantly impact CDNC estimates. Regionally, the magnitude and behavior of the annual CDNC cycle are compared for each effective radius retrieval. Results from this study indicate significant intercollection differences in aggregated values of effective radius due to changes to the pre-computed retrieval lookup tables for ocean scenes, changes to retrieved cloud top pressure, solar irradiance, or above cloud thermal emission, depending upon spectral channel. The observed differences between collections may have implications for existing MODIS derived climatologies and validation studies of effective radius and CDNC.

Considering Combined or Separated Roughness and Vegetation Effects in Soil Moisture Retrievals

NASA Technical Reports Server (NTRS)

Parrens, Marie; Wigernon, Jean-Pierre; Richaume, Philippe; Al Bitar, Ahmad; Mialon, Arnaud; Fernandez-Moran, Roberto; Al-Yarri, Amen; O'Neill, Peggy; Kerr, Yann

2016-01-01

For more than six years, the Soil Moisture and Ocean Salinity (SMOS) mission has provided multi angular and full-polarization brightness temperature (TB) measurements at L-band. Geophysical products such as soil moisture (SM) and vegetation optical depth at nadir (tau(sub nad)) are retrieved by an operational algorithm using TB observations at different angles of incidence and polarizations. However, the quality of the retrievals depends on several surface effects, such as vegetation, soil roughness and texture, etc. In the microwave forward emission model used in the retrievals (L-band Microwave Emission Model, L-MEB),soil roughness is modeled with a semi-empirical equation using four main parameters (Q(sub r), H(sub r), N(sub rp), with p = H or V polarizations). At present, these parameters are calibrated with data provided by airborne studies and in situ measurements made at a local scale that is not necessarily representative of the large SMOS footprints (43 km on average) at global scale. In this study, we evaluate the impact of the calibrated values of N(sub rp) and H(sub r) on the SM and tau(sub nad) retrievals based on SMOS TB measurements (SMOS Level 3 product) over the Soil Climate Analysis Network (SCAN) network located in North America over five years (2011-2015). In this study, Qr was set equal to zero and we assumed that N(sub rH)= N(sub rV). The retrievals were performed by varying N(sub rp) from -1 to 2 by steps of 1 and H(sub r) from 0 to 0.6 by steps of 0.1. At satellite scale, the results show that combining vegetation and roughness effects in a single parameter provides the best results in terms of soil moisture retrievals, as evaluated against the in situ SM data. Even though our retrieval approach was very simplified, as we did not account for pixel heterogeneity, the accuracy we obtained in the SM retrievals was almost systematically better than those of the Level 3 product. Improved results were also obtained in terms of optical depth retrievals. These new results may have key consequences in terms of calibration of roughness effects within the algorithms of the SMOS (ESA) and the SMAP (NASA) space missions.

Improved optical flow velocity analysis in SO2 camera images of volcanic plumes - implications for emission-rate retrievals investigated at Mt Etna, Italy and Guallatiri, Chile

NASA Astrophysics Data System (ADS)

Gliß, Jonas; Stebel, Kerstin; Kylling, Arve; Sudbø, Aasmund

2018-02-01

Accurate gas velocity measurements in emission plumes are highly desirable for various atmospheric remote sensing applications. The imaging technique of UV SO2 cameras is commonly used to monitor SO2 emissions from volcanoes and anthropogenic sources (e.g. power plants, ships). The camera systems capture the emission plumes at high spatial and temporal resolution. This allows the gas velocities in the plume to be retrieved directly from the images. The latter can be measured at a pixel level using optical flow (OF) algorithms. This is particularly advantageous under turbulent plume conditions. However, OF algorithms intrinsically rely on contrast in the images and often fail to detect motion in low-contrast image areas. We present a new method to identify ill-constrained OF motion vectors and replace them using the local average velocity vector. The latter is derived based on histograms of the retrieved OF motion fields. The new method is applied to two example data sets recorded at Mt Etna (Italy) and Guallatiri (Chile). We show that in many cases, the uncorrected OF yields significantly underestimated SO2 emission rates. We further show that our proposed correction can account for this and that it significantly improves the reliability of optical-flow-based gas velocity retrievals. In the case of Mt Etna, the SO2 emissions of the north-eastern crater are investigated. The corrected SO2 emission rates range between 4.8 and 10.7 kg s-1 (average of 7.1 ± 1.3 kg s-1) and are in good agreement with previously reported values. For the Guallatiri data, the emissions of the central crater and a fumarolic field are investigated. The retrieved SO2 emission rates are between 0.5 and 2.9 kg s-1 (average of 1.3 ± 0.5 kg s-1) and provide the first report of SO2 emissions from this remotely located and inaccessible volcano.

A new technique for fire risk estimation in the wildland urban interface

NASA Astrophysics Data System (ADS)

Dasgupta, S.; Qu, J. J.; Hao, X.

A novel technique based on the physical variable of pre-ignition energy is proposed for assessing fire risk in the Grassland-Urban-Interface The physical basis lends meaning a site and season independent applicability possibilities for computing spread rates and ignition probabilities features contemporary fire risk indices usually lack The method requires estimates of grass moisture content and temperature A constrained radiative-transfer inversion scheme on MODIS NIR-SWIR reflectances which reduces solution ambiguity is used for grass moisture retrieval while MODIS land surface temperature emissivity products are used for retrieving grass temperature Subpixel urban contamination of the MODIS reflective and thermal signals over a Grassland-Urban-Interface pixel is corrected using periodic estimates of urban influence from high spatial resolution ASTER

Top-down estimate of dust emissions through integration of MODIS and MISR aerosol retrievals with the GEOS-Chem adjoint model

NASA Astrophysics Data System (ADS)

Wang, Jun; Xu, Xiaoguang; Henze, Daven K.; Zeng, Jing; Ji, Qiang; Tsay, Si-Chee; Huang, Jianping

2012-04-01

Predicting the influences of dust on atmospheric composition, climate, and human health requires accurate knowledge of dust emissions, but large uncertainties persist in quantifying mineral sources. This study presents a new method for combined use of satellite-measured radiances and inverse modeling to spatially constrain the amount and location of dust emissions. The technique is illustrated with a case study in May 2008; the dust emissions in Taklimakan and Gobi deserts are spatially optimized using the GEOS-Chem chemical transport model and its adjoint constrained by aerosol optical depth (AOD) that are derived over the downwind dark-surface region in China from MODIS (Moderate Resolution Imaging Spectroradiometer) reflectance with the aerosol single scattering properties consistent with GEOS-chem. The adjoint inverse modeling yields an overall 51% decrease in prior dust emissions estimated by GEOS-Chem over the Taklimakan-Gobi area, with more significant reductions south of the Gobi Desert. The model simulation with optimized dust emissions shows much better agreement with independent observations from MISR (Multi-angle Imaging SpectroRadiometer) AOD and MODIS Deep Blue AOD over the dust source region and surface PM10 concentrations. The technique of this study can be applied to global multi-sensor remote sensing data for constraining dust emissions at various temporal and spatial scales, and hence improving the quantification of dust effects on climate, air quality, and human health.

Top-down Estimate of Dust Emissions Through Integration of MODIS and MISR Aerosol Retrievals With the Geos-chem Adjoint Model

NASA Technical Reports Server (NTRS)

Wang, Jun; Xu, Xiaoguang; Henze, Daven K.; Zeng, Jing; Ji, Qiang; Tsay, Si-Chee; Huang, Jianping

2012-01-01

Predicting the influences of dust on atmospheric composition, climate, and human health requires accurate knowledge of dust emissions, but large uncertainties persist in quantifying mineral sources. This study presents a new method for combined use of satellite-measured radiances and inverse modeling to spatially constrain the amount and location of dust emissions. The technique is illustrated with a case study in May 2008; the dust emissions in Taklimakan and Gobi deserts are spatially optimized using the GEOSChem chemical transport model and its adjoint constrained by aerosol optical depth (AOD) that are derived over the downwind dark-surface region in China from MODIS (Moderate Resolution Imaging Spectroradiometer) reflectance with the aerosol single scattering properties consistent with GEOS-chem. The adjoint inverse modeling yields an overall 51% decrease in prior dust emissions estimated by GEOS-Chem over the Taklimakan-Gobi area, with more significant reductions south of the Gobi Desert. The model simulation with optimized dust emissions shows much better agreement with independent observations from MISR (Multi-angle Imaging SpectroRadiometer) AOD and MODIS Deep Blue AOD over the dust source region and surface PM10 concentrations. The technique of this study can be applied to global multi-sensor remote sensing data for constraining dust emissions at various temporal and spatial scales, and hence improving the quantification of dust effects on climate, air quality, and human health.

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.

Constraining East Asian CO2 emissions with GOSAT retrievals: methods and policy implications

NASA Astrophysics Data System (ADS)

Shim, C.; Henze, D. K.; Deng, F.

2017-12-01

The world largest CO2 emissions are from East Asia. However, there are large uncertainties in CO2 emission inventories, mainly because of imperfections in bottom-up statistics and a lack of observations for validating emission fluxes, particularly over China. Here we tried to constrain East Asian CO2 emissions with GOSAT retrievals applying 4-Dvar GEOS-Chem and its adjoint model. We applied the inversion to only the cold season (November - February) in 2009 - 2010 since the summer monsoon and greater transboundary impacts in spring and fall greatly reduced the GOSAT retrievals. In the cold season, the a posteriori CO2 emissions over East Asia generally higher by 5 - 20%, particularly Northeastern China shows intensively higher in a posteriori emissions ( 20%), where the Chinese government is recently focusing on mitigating the air pollutants. In another hand, a posteriori emissions from Southern China are lower 10 - 25%. A posteriori emissions in Korea and Japan are mostly higher by 10 % except over Kyushu region. With our top-down estimates with 4-Dvar CO2 inversion, we will evaluate the current regional CO2 emissions inventories and potential uncertainties in the sectoral emissions. This study will help understand the quantitative information on anthropogenic CO2 emissions over East Asia and will give policy implications for the mitigation targets.

Interannual variability of ammonia concentrations over the United States: sources and implications

NASA Astrophysics Data System (ADS)

Schiferl, Luke D.; Heald, Colette L.; Van Damme, Martin; Clarisse, Lieven; Clerbaux, Cathy; Coheur, Pierre-François; Nowak, John B.; Neuman, J. Andrew; Herndon, Scott C.; Roscioli, Joseph R.; Eilerman, Scott J.

2016-09-01

The variability of atmospheric ammonia (NH3), emitted largely from agricultural sources, is an important factor when considering how inorganic fine particulate matter (PM2.5) concentrations and nitrogen cycling are changing over the United States. This study combines new observations of ammonia concentration from the surface, aboard aircraft, and retrieved by satellite to both evaluate the simulation of ammonia in a chemical transport model (GEOS-Chem) and identify which processes control the variability of these concentrations over a 5-year period (2008-2012). We find that the model generally underrepresents the ammonia concentration near large source regions (by 26 % at surface sites) and fails to reproduce the extent of interannual variability observed at the surface during the summer (JJA). Variability in the base simulation surface ammonia concentration is dominated by meteorology (64 %) as compared to reductions in SO2 and NOx emissions imposed by regulation (32 %) over this period. Introduction of year-to-year varying ammonia emissions based on animal population, fertilizer application, and meteorologically driven volatilization does not substantially improve the model comparison with observed ammonia concentrations, and these ammonia emissions changes have little effect on the simulated ammonia concentration variability compared to those caused by the variability of meteorology and acid-precursor emissions. There is also little effect on the PM2.5 concentration due to ammonia emissions variability in the summer when gas-phase changes are favored, but variability in wintertime emissions, as well as in early spring and late fall, will have a larger impact on PM2.5 formation. This work highlights the need for continued improvement in both satellite-based and in situ ammonia measurements to better constrain the magnitude and impacts of spatial and temporal variability in ammonia concentrations.

Atmospheric correction for retrieving ground brightness temperature at commonly-used passive microwave frequencies.

PubMed

Han, Xiao-Jing; Duan, Si-Bo; Li, Zhao-Liang

2017-02-20

An analysis of the atmospheric impact on ground brightness temperature (Tg) is performed for numerous land surface types at commonly-used frequencies (i.e., 1.4 GHz, 6.93 GHz, 10.65 GHz, 18.7 GHz, 23.8 GHz, 36.5 GHz and 89.0 GHz). The results indicate that the atmosphere has a negligible impact on Tg at 1.4 GHz for land surfaces with emissivities greater than 0.7, at 6.93 GHz for land surfaces with emissivities greater than 0.8, and at 10.65 GHz for land surfaces with emissivities greater than 0.9 if a root mean square error (RMSE) less than 1 K is desired. To remove the atmospheric effect on Tg, a generalized atmospheric correction method is proposed by parameterizing the atmospheric transmittance τ and upwelling atmospheric brightness temperature Tba↑. Better accuracies with Tg RMSEs less than 1 K are achieved at 1.4 GHz, 6.93 GHz, 10.65 GHz, 18.7 GHz and 36.5 GHz, and worse accuracies with RMSEs of 1.34 K and 4.35 K are obtained at 23.8 GHz and 89.0 GHz, respectively. Additionally, a simplified atmospheric correction method is developed when lacking sufficient input data to perform the generalized atmospheric correction method, and an emissivity-based atmospheric correction method is presented when the emissivity is known. Consequently, an appropriate atmospheric correction method can be selected based on the available data, frequency and required accuracy. Furthermore, this study provides a method to estimate τ and Tba↑ of different frequencies using the atmospheric parameters (total water vapor content in observation direction Lwv, total cloud liquid water content Lclw and mean temperature of cloud Tclw), which is important for simultaneously determining the land surface parameters using multi-frequency passive microwave satellite data.

Constraints on Eurasian ship NOx emissions using OMI NO2 observations and GEOS-Chem

NASA Astrophysics Data System (ADS)

Vinken, Geert C. M.; Boersma, Folkert; van Donkelaar, Aaron; Zhang, Lin

2013-04-01

Ships emit large quantities of nitrogen oxides (NOx = NO + NO2), important precursors for ozone (O3) and particulate matter formation. Ships burn low-grade marine heavy fuel due to the limited regulations that exist for the maritime sector in international waters. Previous studies showed that global ship NOx emission inventories amount to 3.0-10.4 Tg N per year (15-30% of total NOx emissions), with most emissions close to land and affecting air quality in densely populated coastal regions. Bottom-up inventories depend on the extrapolation of a relatively small number of measurements that are often unable to capture annual emission changes and can suffer from large uncertainties. Satellites provide long-term, high-resolution retrievals that can be used to improve emission estimates. In this study we provide top-down constraints on ship NOx emissions in major European ship routes, using observed NO2 columns from the Ozone Monitoring Instrument (OMI) and NO2 columns simulated with the nested (0.5°×0.67°) version of the GEOS-Chem chemistry transport model. We use a plume-in-grid treatment of ship NOx emissions to account for in-plume chemistry in our model. We ensure consistency between the retrievals and model simulations by using the high-resolution GEOS-Chem NO2 profiles as a priori. We find evidence that ship emissions in the Mediterranean Sea are geographically misplaced by up to 150 km and biased high by a factor of 4 as compared to the most recent (EMEP) ship emission inventory. Better agreement is found over the shipping lane between Spain and the English Channel. We extend our approach and also provide constraints for major ship routes in the Red Sea and Indian Ocean. Using the full benefit of the long-term retrieval record of OMI, we present a new Eurasian ship emission inventory for the years 2005 to 2010, based on the EMEP and AMVER-ICOADS inventories, and top-down constraints from the satellite retrievals. Our work shows that satellite retrievals can improve the characterization of emission locations, magnitudes and trends over sparsely monitored areas such as seas or oceans.

Remote Sensing of Evapotranspiration and Carbon Uptake at Harvard Forest

NASA Technical Reports Server (NTRS)

Min, Qilong; Lin, Bing

2005-01-01

A land surface vegetation index, defined as the difference of microwave land surface emissivity at 19 and 37 GHz, was calculated for a heavily forested area in north central Massachusetts. The microwave emissivity difference vegetation index (EDVI) was estimated from satellite SSM/I measurements at the defined wavelengths and used to estimate land surface turbulent fluxes. Narrowband visible and infrared measurements and broadband solar radiation observations were used in the EDVI retrievals and turbulent flux estimations. The EDVI values represent physical properties of crown vegetation such as vegetation water content of crown canopies. The collocated land surface turbulent and radiative fluxes were empirically linked together by the EDVI values. The EDVI values are statistically sensitive to evapotranspiration fractions (EF) with a correlation coefficient (R) greater than 0.79 under all-sky conditions. For clear skies, EDVI estimates exhibit a stronger relationship with EF than normalized difference vegetation index (NDVI). Furthermore, the products of EDVI and input energy (solar and photosynthetically-active radiation) are statistically significantly correlated to evapotranspiration (R=0.95) and CO2 uptake flux (R=0.74), respectively.

Quantifying Spatial and Seasonal Variability in Atmospheric Ammonia with In Situ and Space-Based Observations

NASA Technical Reports Server (NTRS)

Pinder, Robert W.; Walker, John T.; Bash, Jesse O.; Cady-Pereira, Karen E.; Henze, Daven K.; Luo, Mingzhao; Osterman, Gregory B.; Shepard, Mark W.

2011-01-01

Ammonia plays an important role in many biogeochemical processes, yet atmospheric mixing ratios are not well known. Recently, methods have been developed for retrieving NH3 from space-based observations, but they have not been compared to in situ measurements. We have conducted a field campaign combining co-located surface measurements and satellite special observations from the Tropospheric Emission Spectrometer (TES). Our study includes 25 surface monitoring sites spanning 350 km across eastern North Carolina, a region with large seasonal and spatial variability in NH3. From the TES spectra, we retrieve a NH3 representative volume mixing ratio (RVMR), and we restrict our analysis to times when the region of the atmosphere observed by TES is representative of the surface measurement. We find that the TES NH3 RVMR qualitatively captures the seasonal and spatial variability found in eastern North Carolina. Both surface measurements and TES NH3 show a strong correspondence with the number of livestock facilities within 10 km of the observation. Furthermore, we find that TES H3 RVMR captures the month-to-month variability present in the surface observations. The high correspondence with in situ measurements and vast spatial coverage make TES NH3 RVMR a valuable tool for understanding regional and global NH3 fluxes.

Top-down NOx and SO2 emissions simultaneously estimated from different OMI retrievals and inversion frameworks

NASA Astrophysics Data System (ADS)

Qu, Z.; Henze, D. K.; Wang, J.; Xu, X.; Wang, Y.

2017-12-01

Quantifying emissions trends of nitrogen oxides (NOx) and sulfur dioxide (SO2) is important for improving understanding of air pollution and the effectiveness of emission control strategies. We estimate long-term (2005-2016) global (2° x 2.5° resolution) and regional (North America and East Asia at 0.5° x 0.667° resolution) NOx emissions using a recently developed hybrid (mass-balance / 4D-Var) method with GEOS-Chem. NASA standard product and DOMINO retrievals of NO2 column are both used to constrain emissions; comparison of these results provides insight into regions where trends are most robust with respect to retrieval uncertainties, and highlights regions where seemingly significant trends are retrieval-specific. To incorporate chemical interactions among species, we extend our hybrid method to assimilate NO2 and SO2 observations and optimize NOx and SO2 emissions simultaneously. Due to chemical interactions, inclusion of SO2 observations leads to 30% grid-scale differences in posterior NOx emissions compared to those constrained only by NO2 observations. When assimilating and optimizing both species in pseudo observation tests, the sum of the normalized mean squared error (compared to the true emissions) of NOx and SO2 posterior emissions are 54-63% smaller than when observing/constraining a single species. NOx and SO2 emissions are also correlated through the amount of fuel combustion. To incorporate this correlation into the inversion, we optimize seven sector-specific emission scaling factors, including industry, energy, residential, aviation, transportation, shipping and agriculture. We compare posterior emissions from inversions optimizing only species' emissions, only sector-based emissions, and both species' and sector-based emissions. In situ measurements of NOx and SO2 are applied to evaluate the performance of these inversions. The impacts of the inversion on PM2.5 and O3 concentrations and premature deaths are also evaluated.

Two-dimensional radiative transfer for the retrieval of limb emission measurements in the martian atmosphere

NASA Astrophysics Data System (ADS)

Kleinböhl, Armin; Friedson, A. James; Schofield, John T.

2017-01-01

The remote sounding of infrared emission from planetary atmospheres using limb-viewing geometry is a powerful technique for deriving vertical profiles of structure and composition on a global scale. Compared with nadir viewing, limb geometry provides enhanced vertical resolution and greater sensitivity to atmospheric constituents. However, standard limb profile retrieval techniques assume spherical symmetry and are vulnerable to biases produced by horizontal gradients in atmospheric parameters. We present a scheme for the correction of horizontal gradients in profile retrievals from limb observations of the martian atmosphere. It characterizes horizontal gradients in temperature, pressure, and aerosol extinction along the line-of-sight of a limb view through neighboring measurements, and represents these gradients by means of two-dimensional radiative transfer in the forward model of the retrieval. The scheme is applied to limb emission measurements from the Mars Climate Sounder instrument on Mars Reconnaissance Orbiter. Retrieval simulations using data from numerical models indicate that biases of up to 10 K in the winter polar region, obtained with standard retrievals using spherical symmetry, are reduced to about 2 K in most locations by the retrieval with two-dimensional radiative transfer. Retrievals from Mars atmospheric measurements suggest that the two-dimensional radiative transfer greatly reduces biases in temperature and aerosol opacity caused by observational geometry, predominantly in the polar winter regions.

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.

Performance limitations of temperature-emissivity separation techniques in long-wave infrared hyperspectral imaging applications

NASA Astrophysics Data System (ADS)

Pieper, Michael; Manolakis, Dimitris; Truslow, Eric; Cooley, Thomas; Brueggeman, Michael; Jacobson, John; Weisner, Andrew

2017-08-01

Accurate estimation or retrieval of surface emissivity from long-wave infrared or thermal infrared (TIR) hyperspectral imaging data acquired by airborne or spaceborne sensors is necessary for many scientific and defense applications. This process consists of two interwoven steps: atmospheric compensation and temperature-emissivity separation (TES). The most widely used TES algorithms for hyperspectral imaging data assume that the emissivity spectra for solids are smooth compared to the atmospheric transmission function. We develop a model to explain and evaluate the performance of TES algorithms using a smoothing approach. Based on this model, we identify three sources of error: the smoothing error of the emissivity spectrum, the emissivity error from using the incorrect temperature, and the errors caused by sensor noise. For each TES smoothing technique, we analyze the bias and variability of the temperature errors, which translate to emissivity errors. The performance model explains how the errors interact to generate temperature errors. Since we assume exact knowledge of the atmosphere, the presented results provide an upper bound on the performance of TES algorithms based on the smoothness assumption.

Automatic Jet Contrail Detection and Segmentation

NASA Technical Reports Server (NTRS)

Weiss, J.; Christopher, S. A.; Welch, R. M.

1997-01-01

Jet contrails are an important subset of cirrus clouds in the atmosphere, and thin cirrus are thought to enhance the greenhouse effect due to their semi-transparent nature. They are nearly transparent to the solar energy reaching the surface, but they reduce the planetary emission to space due to their cold ambient temperatures. Having 'seeded' the environment, contrails often elongate and widen into cirrus-like features. However, there is great uncertainty regarding the impact of contrails on surface temperature and precipitation. With increasing numbers of subsonic aircraft operating in the upper troposphere, there is the possibility of increasing cloudiness which could lead to changes in the radiation balance. Automatic detection and seg- mentation of jet contrails in satellite imagery is important because (1) it is impractical to compile a contrail climatology by hand, and (2) with the segmented images it will be possible to retrieve contrail physical properties such as optical thickness, effective ice crystal diameter and emissivity.

Ground-based remote sensing of thin clouds in the Arctic

NASA Astrophysics Data System (ADS)

Garrett, T. J.; Zhao, C.

2013-05-01

This paper describes a method for using interferometer measurements of downwelling thermal radiation to retrieve the properties of single-layer clouds. Cloud phase is determined from ratios of thermal emission in three "micro-windows" at 862.5 cm-1, 935.8 cm-1, and 988.4 cm-1 where absorption by water vapour is particularly small. Cloud microphysical and optical properties are retrieved from thermal emission in the first two of these micro-windows, constrained by the transmission through clouds of primarily stratospheric ozone emission at 1040 cm-1. Assuming a cloud does not approximate a blackbody, the estimated 95% confidence retrieval errors in effective radius re, visible optical depth τ, number concentration N, and water path WP are, respectively, 10%, 20%, 38% (55% for ice crystals), and 16%. Applied to data from the Atmospheric Radiation Measurement programme (ARM) North Slope of Alaska - Adjacent Arctic Ocean (NSA-AAO) site near Barrow, Alaska, retrievals show general agreement with both ground-based microwave radiometer measurements of liquid water path and a method that uses combined shortwave and microwave measurements to retrieve re, τ and N. Compared to other retrieval methods, advantages of this technique include its ability to characterise thin clouds year round, that water vapour is not a primary source of retrieval error, and that the retrievals of microphysical properties are only weakly sensitive to retrieved cloud phase. The primary limitation is the inapplicability to thicker clouds that radiate as blackbodies and that it relies on a fairly comprehensive suite of ground based measurements.

Expected trace gas and aerosol retrieval accuracy of the Geostationary Environment Monitoring Spectrometer

NASA Astrophysics Data System (ADS)

Jeong, U.; Kim, J.; Liu, X.; Lee, K. H.; Chance, K.; Song, C. H.

2015-12-01

The predicted accuracy of the trace gases and aerosol retrievals from the geostationary environment monitoring spectrometer (GEMS) was investigated. The GEMS is one of the first sensors to monitor NO2, SO2, HCHO, O3, and aerosols onboard geostationary earth orbit (GEO) over Asia. Since the GEMS is not launched yet, the simulated measurements and its precision were used in this study. The random and systematic component of the measurement error was estimated based on the instrument design. The atmospheric profiles were obtained from Model for Ozone And Related chemical Tracers (MOZART) simulations and surface reflectances were obtained from climatology of OMI Lambertian equivalent reflectance. The uncertainties of the GEMS trace gas and aerosol products were estimated based on the OE method using the atmospheric profile and surface reflectance. Most of the estimated uncertainties of NO2, HCHO, stratospheric and total O3 products satisfied the user's requirements with sufficient margin. However, about 26% of the estimated uncertainties of SO2 and about 30% of the estimated uncertainties of tropospheric O3 do not meet the required precision. Particularly the estimated uncertainty of SO2 is high in winter, when the emission is strong in East Asia. Further efforts are necessary in order to improve the retrieval accuracy of SO2 and tropospheric O3 in order to reach the scientific goal of GEMS. Random measurement error of GEMS was important for the NO2, SO2, and HCHO retrieval, while both the random and systematic measurement errors were important for the O3 retrievals. The degree of freedom for signal of tropospheric O3 was 0.8 ± 0.2 and that for stratospheric O3 was 2.9 ± 0.5. The estimated uncertainties of the aerosol retrieval from GEMS measurements were predicted to be lower than the required precision for the SZA range of the trace gas retrievals.

Martian Radiative Transfer Modeling Using the Optimal Spectral Sampling Method

NASA Technical Reports Server (NTRS)

Eluszkiewicz, J.; Cady-Pereira, K.; Uymin, G.; Moncet, J.-L.

2005-01-01

The large volume of existing and planned infrared observations of Mars have prompted the development of a new martian radiative transfer model that could be used in the retrievals of atmospheric and surface properties. The model is based on the Optimal Spectral Sampling (OSS) method [1]. The method is a fast and accurate monochromatic technique applicable to a wide range of remote sensing platforms (from microwave to UV) and was originally developed for the real-time processing of infrared and microwave data acquired by instruments aboard the satellites forming part of the next-generation global weather satellite system NPOESS (National Polarorbiting Operational Satellite System) [2]. As part of our on-going research related to the radiative properties of the martian polar caps, we have begun the development of a martian OSS model with the goal of using it to perform self-consistent atmospheric corrections necessary to retrieve caps emissivity from the Thermal Emission Spectrometer (TES) spectra. While the caps will provide the initial focus area for applying the new model, it is hoped that the model will be of interest to the wider Mars remote sensing community.

Estimation of snow emissivity via assimilation of multi-frequency passive microwave data into an ensemble-based data assimilation system

NASA Astrophysics Data System (ADS)

Farhadi, L.; Bateni, S. M.; Auligne, T.; Navari, M.

2017-12-01

Snow emissivity is a key parameter for the estimation of snow surface temperature, which is needed as an initial value in climate models and determination of the outgoing long-wave radiation. Moreover, snow emissivity is required for retrieval of atmospheric parameters (e.g., temperature and humidity profiles) from satellite measurements and satellite data assimilations in numerical weather prediction systems. Microwave emission models and remote sensing data cannot accurately estimate snow emissivity due to limitations attributed to each of them. Existing microwave emission models introduce significant uncertainties in their snow emissivity estimates. This is mainly due to shortcomings of the dense media theory for snow medium at high frequencies, and erroneous forcing variables. The well-known limitations of passive microwave data such as coarse spatial resolution, saturation in deep snowpack, and signal loss in wet snow are the major drawbacks of passive microwave retrieval algorithms for estimation of snow emissivity. A full exploitation of the information contained in the remote sensing data can be achieved by merging them with snow emission models within a data assimilation framework. Such an optimal merging can overcome the specific limitations of models and remote sensing data. An Ensemble Batch Smoother (EnBS) data assimilation framework was developed in this study to combine the synthetically generated passive microwave brightness temperatures at 1.4-, 18.7-, 36.5-, and 89-GHz frequencies with the MEMLS microwave emission model to reduce the uncertainty of the snow emissivity estimates. We have used the EnBS algorithm in the context of observing system simulation experiment (or synthetic experiment) at the local scale observation site (LSOS) of the NASA CLPX field campaign. Our findings showed that the developed methodology significantly improves the estimates of the snow emissivity. The simultaneous assimilation of passive microwave brightness temperatures at all frequencies (i.e., 1.4-, 18.7-, 36.5-, and 89-GHz) reduce the root-mean-square-error (RMSE) of snow emissivity at 1.4-, 18.7-, 36.5-, and 89-GHz (H-pol.) by 80%, 42%, 52%, 40%, respectively compared to the corresponding snow emissivity estimates from the open-loop model.

Enhanced methane emissions from tropical wetlands during the 2011 La Niña

PubMed Central

Pandey, Sudhanshu; Houweling, Sander; Krol, Maarten; Aben, Ilse; Monteil, Guillaume; Nechita-Banda, Narcisa; Dlugokencky, Edward J.; Detmers, Rob; Hasekamp, Otto; Xu, Xiyan; Riley, William J.; Poulter, Benjamin; Zhang, Zhen; McDonald, Kyle C.; White, James W. C.; Bousquet, Philippe; Röckmann, Thomas

2017-01-01

Year-to-year variations in the atmospheric methane (CH4) growth rate show significant correlation with climatic drivers. The second half of 2010 and the first half of 2011 experienced the strongest La Niña since the early 1980s, when global surface networks started monitoring atmospheric CH4 mole fractions. We use these surface measurements, retrievals of column-averaged CH4 mole fractions from GOSAT, new wetland inundation estimates, and atmospheric δ13C-CH4 measurements to estimate the impact of this strong La Niña on the global atmospheric CH4 budget. By performing atmospheric inversions, we find evidence of an increase in tropical CH4 emissions of ∼6–9 TgCH4 yr−1 during this event. Stable isotope data suggest that biogenic sources are the cause of this emission increase. We find a simultaneous expansion of wetland area, driven by the excess precipitation over the Tropical continents during the La Niña. Two process-based wetland models predict increases in wetland area consistent with observationally-constrained values, but substantially smaller per-area CH4 emissions, highlighting the need for improvements in such models. Overall, tropical wetland emissions during the strong La Niña were at least by 5% larger than the long-term mean. PMID:28393869

Emissions of nitrogen oxides from US urban areas: estimation from Ozone Monitoring Instrument retrievals for 2005-2014

DOE PAGES

Lu, Z.; Streets, D. G.; de Foy, B.; ...

2015-05-28

Satellite remote sensing of tropospheric nitrogen dioxide (NO 2) can provide valuable information for estimating surface nitrogen oxides (NO x) emissions. Using an exponentially-modified Gaussian (EMG) method and taking into account the effect of wind on observed NO 2 distributions, we estimate three-year moving-average emissions of summertime NO x from 35 US urban areas directly from NO 2 retrievals of the Ozone Monitoring Instrument (OMI) during 2005–2014. Following the conclusions of previous studies that the EMG method provides robust and accurate emission estimates under strong-wind conditions, we derive top-down NO x emissions from each urban area by applying the EMGmore » method to OMI data with wind speeds greater than 3–5 m s -1. Meanwhile, we find that OMI NO 2 observations under weak-wind conditions (i.e., < 3 m s -1) are qualitatively better correlated with the surface NO x source strength in comparison to all-wind OMI maps; and therefore we use them to calculate the satellite-observed NO 2 burdens of urban areas and compare with NO x emission estimates. The EMG results show that OMI-derived NO x emissions are highly correlated ( R > 0.93) with weak-wind OMI NO 2 burdens as well as bottom-up NO x emission estimates over 35 urban areas, implying a linear response of the OMI observations to surface emissions under weak-wind conditions. The simultaneous, EMG-obtained, effective NO 2 lifetimes (~3.5 ± 1.3 h), however, are biased low in comparison to the summertime NO 2 chemical lifetimes. In general, isolated urban areas with NO x emission intensities greater than ~ 2 Mg h -1 produce statistically significant weak-wind signals in three-year average OMI data. From 2005 to 2014, we estimate that total OMI-derived NO x emissions over all selected US urban areas decreased by 49%, consistent with reductions of 43, 47, 49, and 44% in the total bottom-up NO x emissions, the sum of weak-wind OMI NO 2 columns, the total weak-wind OMI NO 2 burdens, and the averaged NO 2 concentrations, respectively, reflecting the success of NO x control programs for both mobile sources and power plants. The decrease rates of these NO x-related quantities are found to be faster (i.e., -6.8 to -9.3% yr -1) before 2010 and slower (i.e., -3.4 to -4.9% yr -1) after 2010. For individual urban areas, we calculate the R values of pair-wise trends among the OMI-derived and bottom-up NO x emissions, the weak-wind OMI NO 2 burdens, and ground-based NO 2 measurements; and high correlations are found for all urban areas (median R = 0.8), particularly large ones ( R up to 0.97). The results of the current work indicate that using the EMG method and considering the wind effect, the OMI data allow for the estimation of NO x emissions from urban areas and the direct constraint of emission trends with reasonable accuracy.« less

Emissions of nitrogen oxides from US urban areas: estimation from Ozone Monitoring Instrument retrievals for 2005–2014

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

Lu, Z.; Streets, D. G.; de Foy, B.

Satellite remote sensing of tropospheric nitrogen dioxide (NO 2) can provide valuable information for estimating surface nitrogen oxides (NO x) emissions. Using an exponentially modified Gaussian (EMG) method and taking into account the effect of wind on observed NO 2 distributions, we estimate 3-year moving-average emissions of summertime NO x from 35 US (United States) urban areas directly from NO 2 retrievals of the Ozone Monitoring Instrument (OMI) during 2005–2014. Following conclusions of previous studies that the EMG method provides robust and accurate emission estimates under strong-wind conditions, we derive top-down NO x emissions from each urban area by applyingmore » the EMG method to OMI data with wind speeds greater than 3–5 m s -1. Meanwhile, we find that OMI NO 2 observations under weak-wind conditions (i.e., < 3 m s −1) are qualitatively better correlated to the surface NO x source strength in comparison to all-wind OMI maps; therefore, we use them to calculate the satellite-observed NO 2 burdens of urban areas and compare with NO x emission estimates. The EMG results show that OMI-derived NO x emissions are highly correlated ( R > 0.93) with weak-wind OMI NO 2 burdens as well as with bottom-up NO x emission estimates over 35 urban areas, implying a linear response of the OMI observations to surface emissions under weak-wind conditions. The simultaneous EMG-obtained effective NO 2 lifetimes (~ 3.5 ± 1.3 h), however, are biased low in comparison to the summertime NO 2 chemical lifetimes. In general, isolated urban areas with NO x emission intensities greater than ~ 2 Mg h -1 produce statistically significant weak-wind signals in 3-year average OMI data. From 2005 to 2014, we estimate that total OMI-derived NO x emissions over all selected US urban areas decreased by 49 %, consistent with reductions of 43, 47, 49, and 44 % in the total bottom-up NO x emissions, the sum of weak-wind OMI NO 2 columns, the total weak-wind OMI NO 2 burdens, and the averaged NO 2 concentrations, respectively, reflecting the success of NO x control programs for both mobile sources and power plants. The decrease rates of these NO x-related quantities are found to be faster (i.e., -6.8 to -9.3 % yr −1) before 2010 and slower (i.e., -3.4 to -4.9 % yr −1) after 2010. For individual urban areas, we calculate the R values of pair-wise trends among the OMI-derived and bottom-up NO x emissions, the weak-wind OMI NO 2 burdens, and ground-based NO 2 measurements, and high correlations are found for all urban areas (median R= 0.8), particularly large ones ( R up to 0.97). The results of the current work indicate that using the EMG method and considering the wind effect, the OMI data allow for the estimation of NO x emissions from urban areas and the direct constraint of emission trends with reasonable accuracy.« less

Emissions of nitrogen oxides from US urban areas: estimation from Ozone Monitoring Instrument retrievals for 2005-2014

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

Lu, Z.; Streets, D. G.; de Foy, B.

Satellite remote sensing of tropospheric nitrogen dioxide (NO 2) can provide valuable information for estimating surface nitrogen oxides (NO x) emissions. Using an exponentially-modified Gaussian (EMG) method and taking into account the effect of wind on observed NO 2 distributions, we estimate three-year moving-average emissions of summertime NO x from 35 US urban areas directly from NO 2 retrievals of the Ozone Monitoring Instrument (OMI) during 2005–2014. Following the conclusions of previous studies that the EMG method provides robust and accurate emission estimates under strong-wind conditions, we derive top-down NO x emissions from each urban area by applying the EMGmore » method to OMI data with wind speeds greater than 3–5 m s -1. Meanwhile, we find that OMI NO 2 observations under weak-wind conditions (i.e., < 3 m s -1) are qualitatively better correlated with the surface NO x source strength in comparison to all-wind OMI maps; and therefore we use them to calculate the satellite-observed NO 2 burdens of urban areas and compare with NO x emission estimates. The EMG results show that OMI-derived NO x emissions are highly correlated ( R > 0.93) with weak-wind OMI NO 2 burdens as well as bottom-up NO x emission estimates over 35 urban areas, implying a linear response of the OMI observations to surface emissions under weak-wind conditions. The simultaneous, EMG-obtained, effective NO 2 lifetimes (~3.5 ± 1.3 h), however, are biased low in comparison to the summertime NO 2 chemical lifetimes. In general, isolated urban areas with NO x emission intensities greater than ~ 2 Mg h -1 produce statistically significant weak-wind signals in three-year average OMI data. From 2005 to 2014, we estimate that total OMI-derived NO x emissions over all selected US urban areas decreased by 49%, consistent with reductions of 43, 47, 49, and 44% in the total bottom-up NO x emissions, the sum of weak-wind OMI NO 2 columns, the total weak-wind OMI NO 2 burdens, and the averaged NO 2 concentrations, respectively, reflecting the success of NO x control programs for both mobile sources and power plants. The decrease rates of these NO x-related quantities are found to be faster (i.e., -6.8 to -9.3% yr -1) before 2010 and slower (i.e., -3.4 to -4.9% yr -1) after 2010. For individual urban areas, we calculate the R values of pair-wise trends among the OMI-derived and bottom-up NO x emissions, the weak-wind OMI NO 2 burdens, and ground-based NO 2 measurements; and high correlations are found for all urban areas (median R = 0.8), particularly large ones ( R up to 0.97). The results of the current work indicate that using the EMG method and considering the wind effect, the OMI data allow for the estimation of NO x emissions from urban areas and the direct constraint of emission trends with reasonable accuracy.« less

Multi-source SO2 emission retrievals and consistency of satellite and surface measurements with reported emissions

NASA Astrophysics Data System (ADS)

Fioletov, Vitali; McLinden, Chris A.; Kharol, Shailesh K.; Krotkov, Nickolay A.; Li, Can; Joiner, Joanna; Moran, Michael D.; Vet, Robert; Visschedijk, Antoon J. H.; Denier van der Gon, Hugo A. C.

2017-10-01

Reported sulfur dioxide (SO2) emissions from US and Canadian sources have declined dramatically since the 1990s as a result of emission control measures. Observations from the Ozone Monitoring Instrument (OMI) on NASA's Aura satellite and ground-based in situ measurements are examined to verify whether the observed changes from SO2 abundance measurements are quantitatively consistent with the reported changes in emissions. To make this connection, a new method to link SO2 emissions and satellite SO2 measurements was developed. The method is based on fitting satellite SO2 vertical column densities (VCDs) to a set of functions of OMI pixel coordinates and wind speeds, where each function represents a statistical model of a plume from a single point source. The concept is first demonstrated using sources in North America and then applied to Europe. The correlation coefficient between OMI-measured VCDs (with a local bias removed) and SO2 VCDs derived here using reported emissions for 1° by 1° gridded data is 0.91 and the best-fit line has a slope near unity, confirming a very good agreement between observed SO2 VCDs and reported emissions. Having demonstrated their consistency, seasonal and annual mean SO2 VCD distributions are calculated, based on reported point-source emissions for the period 1980-2015, as would have been seen by OMI. This consistency is further substantiated as the emission-derived VCDs also show a high correlation with annual mean SO2 surface concentrations at 50 regional monitoring stations.

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.

Quantifying errors in surface ozone predictions associated with clouds over the CONUS: a WRF-Chem modeling study using satellite cloud retrievals

NASA Astrophysics Data System (ADS)

Ryu, Young-Hee; Hodzic, Alma; Barre, Jerome; Descombes, Gael; Minnis, Patrick

2018-05-01

Clouds play a key role in radiation and hence O3 photochemistry by modulating photolysis rates and light-dependent emissions of biogenic volatile organic compounds (BVOCs). It is not well known, however, how much error in O3 predictions can be directly attributed to error in cloud predictions. This study applies the Weather Research and Forecasting with Chemistry (WRF-Chem) model at 12 km horizontal resolution with the Morrison microphysics and Grell 3-D cumulus parameterization to quantify uncertainties in summertime surface O3 predictions associated with cloudiness over the contiguous United States (CONUS). All model simulations are driven by reanalysis of atmospheric data and reinitialized every 2 days. In sensitivity simulations, cloud fields used for photochemistry are corrected based on satellite cloud retrievals. The results show that WRF-Chem predicts about 55 % of clouds in the right locations and generally underpredicts cloud optical depths. These errors in cloud predictions can lead to up to 60 ppb of overestimation in hourly surface O3 concentrations on some days. The average difference in summertime surface O3 concentrations derived from the modeled clouds and satellite clouds ranges from 1 to 5 ppb for maximum daily 8 h average O3 (MDA8 O3) over the CONUS. This represents up to ˜ 40 % of the total MDA8 O3 bias under cloudy conditions in the tested model version. Surface O3 concentrations are sensitive to cloud errors mainly through the calculation of photolysis rates (for ˜ 80 %), and to a lesser extent to light-dependent BVOC emissions. The sensitivity of surface O3 concentrations to satellite-based cloud corrections is about 2 times larger in VOC-limited than NOx-limited regimes. Our results suggest that the benefits of accurate predictions of cloudiness would be significant in VOC-limited regions, which are typical of urban areas.

Infrared and Passive Microwave Radiometric Sea Surface Temperatures and Their Relationships to Atmospheric Forcing

NASA Technical Reports Server (NTRS)

Castro, Sandra L.

2004-01-01

The current generation of infrared (IR) and passive microwave (MW) satellite sensors provides highly complementary information for monitoring sea surface temperature (SST). On the one hand, infrared sensors provide high resolution and high accuracy but are obscured by clouds. Microwave sensors on the other hand, provide coverage through non-precipitating clouds but have coarser resolution and generally poorer accuracy. Assuming that the satellite SST measurements do not have spatially variable biases, they can be blended combining the merits of both SST products. These factors have motivated recent work in blending the MW and IR data in an attempt to produce high-accuracy SST products with improved coverage in regions with persistent clouds. The primary sources of retrieval uncertainty are, however, different for the two sensors. The main uncertainty in the MW retrievals lies in the effects of wind-induced surface roughness and foam on emissivity, whereas the IR retrievals are more sensitive to the atmospheric water vapor and aerosol content. Average nighttime differences between the products for the month periods of January 1999 and June 2000 are shown. These maps show complex spatial and temporal differences as indicated by the strong spatially coherent features in the product differences and the changes between seasons. Clearly such differences need to be understood and accounted for if the products are to be combined. The overall goals of this project are threefold: (1) To understand the sources of uncertainty in the IR and MW SST retrievals and to characterize the errors affecting the two types of retrieval as a fiction of atmospheric forcing; (2) To demonstrate how representative the temperature difference between the two satellite products is of Delta T; (3) To apply bias adjustments and to device a comprehensive treatment of the behavior of the temperature difference across the oceanic skin layer to determine the best method for blending thermal infrared and passive microwave measurements of SSTs.

Infrared atmospheric sounding interferometer correlation interferometry for the retrieval of atmospheric gases: the case of H2O and CO2.

PubMed

Grieco, Giuseppe; Masiello, Guido; Serio, Carmine; Jones, Roderic L; Mead, Mohammed I

2011-08-01

Correlation interferometry is a particular application of Fourier transform spectroscopy with partially scanned interferograms. Basically, it is a technique to obtain the difference between the spectra of atmospheric radiance at two diverse spectral resolutions. Although the technique could be exploited to design an appropriate correlation interferometer, in this paper we are concerned with the analytical aspects of the method and its application to high-spectral-resolution infrared observations in order to separate the emission of a given atmospheric gas from a spectral signal dominated by surface emission, such as in the case of satellite spectrometers operated in the nadir looking mode. The tool will be used to address some basic questions concerning the vertical spatial resolution of H2O and to develop an algorithm to retrieve the columnar amount of CO2. An application to complete interferograms from the Infrared Atmospheric Sounding Interferometer will be presented and discussed. For H2O, we have concluded that the vertical spatial resolution in the lower troposphere mostly depends on broad features associated with the spectrum, whereas for CO2, we have derived a technique capable of retrieving a CO2 columnar amount with accuracy of ≈±7 parts per million by volume at the level of each single field of view.

New Developments for Physically-based Falling Snow Retrievals over Land in Preparation for GPM

NASA Technical Reports Server (NTRS)

Jackson, Gail S.; Tokay, Ali; Kramer, Anne W.; Hudak, David

2008-01-01

The NASA Global Precipitation Measurement mission (GPM) concept centers on deploying a Core spacecraft carrying a dual-frequency precipitation radar and a microwave radiometric imager with channels from 10 to 183 GHz to serve as a precipitation physics observatory and a calibration reference to unify a constellation of dedicated and operational passive microwave sensors. Because of the extended orbit of the Core (plus or minus 65 deg) and the enhanced dual frequency radar and high frequency radiometer, GPM will be able to sense falling snow precipitation and light rain over land. Accordingly, GPM has partnered with the Canadian CloudSat/CALIPSO Validation Project (C3VP) to obtain observations to provide one of several important ground-based validation data sets around which the falling snow models and retrieval algorithms can be further developed and tested. In this work we compare and correlate the long time series (Nov.'06 - March '07) measurements of precipitation rate from parsivels to the passive (89, 150, 183 plus or minus 1, plus or minus 3, plus or minus 7 GHz) observations of NOAA's AMSU-B radiometer. We separate the comparisons into categories of no precipitation, liquid rain and falling snow precipitation. We found that there are similar TBs (especially at 89 and 150 GHz) for cases with falling snow and for non-precipitating cases. The comparisons indicate that surface emissivity contributions to the satellite observed TB over land can add uncertainty in detecting and estimating falling snow. The newest results show that by computing brightness temperatures based on CARE radiosonde data and a rough estimate of surface emissivity show that the cloud ice scattering signal in the AMSU-B data is detected. That is the differences in computed TB and AMSU-B TB for precipitating and non-precipitating cases are unique such that the precipitating and non-precipitating cases can be identified. These results require that the radiosonde releases are within an hour of the AMSU-B data. Forest fraction, snow cover, and measured emissivities were combined to calculate the surface emissivities.

Validation of AIRS/AMSU Cloud Retrievals Using MODIS Cloud Analyses

NASA Technical Reports Server (NTRS)

Molnar, Gyula I.; Susskind, Joel

2005-01-01

The AIRS/AMSU (flying on the EOS-AQUA satellite) sounding retrieval methodology allows for the retrieval of key atmospheric/surface parameters under partially cloudy conditions (Susskind et al.). In addition, cloud parameters are also derived from the AIRS/AMSU observations. Within each AIRS footprint, cloud parameters at up to 2 cloud layers are determined with differing cloud top pressures and effective (product of infrared emissivity at 11 microns and physical cloud fraction) cloud fractions. However, so far the AIRS cloud product has not been rigorously evaluated/validated. Fortunately, collocated/coincident radiances measured by MODIS/AQUA (at a much lower spectral resolution but roughly an order of-magnitude higher spatial resolution than that of AIRS) are used to determine analogous cloud products from MODIS. This allows us for a rather rare and interesting possibility: the intercomparisons and mutual validation of imager vs. sounder-based cloud products obtained from the same satellite positions. First, we present results of small-scale (granules) instantaneous intercomparisons. Next, we will evaluate differences of temporally averaged (monthly) means as well as the representation of inter-annual variability of cloud parameters as presented by the two cloud data sets. In particular, we present statistical differences in the retrieved parameters of cloud fraction and cloud top pressure. We will investigate what type of cloud systems are retrieved most consistently (if any) with both retrieval schemes, and attempt to assess reasons behind statistically significant differences.

Retrieval of Kinetic Temperature and Carbon Dioxide Abundance from Non-Local Thermodynamic Equilibrium Limb Emission Measurements made by the SABER Experiment on the TIMED Satellite

NASA Technical Reports Server (NTRS)

Mertens, Christopher J.; Mlynczak, Martin G.; Lopez-Puertas, Manuel; Wintersteiner, Peter P.; Picard, Richard H.; Winick, Jeremy R.; Gordley, Larry L.; Russell, James M., III

2002-01-01

The Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) experiment was launched onboard the TIMED satellite in December, 2001. SABER is designed to provide measurements of the key radiative and chemical sources and sinks of energy in the mesosphere and lower thermosphere (MLT). SABER measures Earth limb emission in 10 broadband radiometer channels ranging from 1.27 micrometers to 17 micrometers. Measurements are made both day and night over the latitude range from 54 deg. S to 87 deg. N with alternating hemisphere coverage every 60 days. In this paper we concentrate on retrieved profiles of kinetic temperature (T(sub k)) and CO2 volume mixing ratio (vmr), inferred from SABER-observed 15 micrometer and 4.3 micrometer limb emissions, respectively. SABER-measured limb radiances are in non-local thermodynamic equilibrium (non-LTE) in the MLT region. The complexity of non-LTE radiation transfer combined with the large volume of data measured by SABER requires new retrieval approaches and radiative transfer techniques to accurately and efficiently retrieve the data products. In this paper we present the salient features of the coupled non-LTE T(sub k)/CO2 retrieval algorithm, along with preliminary results.

Retrievals of aerosol optical and microphysical properties from Imaging Polar Nephelometer scattering measurements

NASA Astrophysics Data System (ADS)

Reed Espinosa, W.; Remer, Lorraine A.; Dubovik, Oleg; Ziemba, Luke; Beyersdorf, Andreas; Orozco, Daniel; Schuster, Gregory; Lapyonok, Tatyana; Fuertes, David; Vanderlei Martins, J.

2017-03-01

A method for the retrieval of aerosol optical and microphysical properties from in situ light-scattering measurements is presented and the results are compared with existing measurement techniques. The Generalized Retrieval of Aerosol and Surface Properties (GRASP) is applied to airborne and laboratory measurements made by a novel polar nephelometer. This instrument, the Polarized Imaging Nephelometer (PI-Neph), is capable of making high-accuracy field measurements of phase function and degree of linear polarization, at three visible wavelengths, over a wide angular range of 3 to 177°. The resulting retrieval produces particle size distributions (PSDs) that agree, within experimental error, with measurements made by commercial optical particle counters (OPCs). Additionally, the retrieved real part of the refractive index is generally found to be within the predicted error of 0.02 from the expected values for three species of humidified salt particles, with a refractive index that is well established. The airborne measurements used in this work were made aboard the NASA DC-8 aircraft during the Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) field campaign, and the inversion of this data represents the first aerosol retrievals of airborne polar nephelometer data. The results provide confidence in the real refractive index product, as well as in the retrieval's ability to accurately determine PSD, without assumptions about refractive index that are required by the majority of OPCs.

Assimilation of Feng-Yun-3B satellite microwave humidity sounder data over land

NASA Astrophysics Data System (ADS)

Chen, Keyi; Bormann, Niels; English, Stephen; Zhu, Jiang

2018-03-01

The ECMWF has been assimilating Feng-Yun-3B (FY-3B) satellite microwave humidity sounder (MWHS) data over ocean in an operational forecasting system since 24 September 2014. It is more difficult, however, to assimilate microwave observations over land and sea ice than over the open ocean due to higher uncertainties in land surface temperature, surface emissivity and less effective cloud screening. We compare approaches in which the emissivity is retrieved dynamically from MWHS channel 1 [150 GHz (vertical polarization)] with the use of an evolving emissivity atlas from 89 GHz observations from the MWHS onboard NOAA and EUMETSAT satellites. The assimilation of the additional data over land improves the fit of short-range forecasts to other observations, notably ATMS (Advanced Technology Microwave Sounder) humidity channels, and the forecast impacts are mainly neutral to slightly positive over the first five days. The forecast impacts are better in boreal summer and the Southern Hemisphere. These results suggest that the techniques tested allow for effective assimilation of MWHS/FY-3B data over land.

Toward all weather, long record, and real-time land surface temperature retrievals from microwave satellite observations

NASA Astrophysics Data System (ADS)

Jimenez, Carlos; Prigent, Catherine; Aires, Filipe; Ermida, Sofia

2017-04-01

The land surface temperature can be estimated from satellite passive microwave observations, with limited contamination from the clouds as compared to the infrared satellite retrievals. With ˜60% cloud cover in average over the globe, there is a need for "all weather," long record, and real-time estimates of land surface temperature (Ts) from microwaves. A simple yet accurate methodology is developed to derive the land surface temperature from microwave conical scanner observations, with the help of pre-calculated land surface microwave emissivities. The method is applied to the Special Sensor Microwave/Imagers (SSM/I) and the Earth observation satellite (EOS) Advanced Microwave Scanning Radiometer (AMSR-E) observations?, regardless of the cloud cover. The SSM/I results are compared to infrared estimates from International Satellite Cloud Climatology Project (ISCCP) and from Advanced Along Track Scanning Radiometer (AATSR), under clear-sky conditions. Limited biases are observed (˜0.5 K for both comparisons) with a root-mean-square difference (RMSD) of ˜5 K, to be compared to the RMSE of ˜3.5 K between ISCCP et AATSR. AMSR-E results are compared with the Moderate Resolution Imaging Spectroradiometer (MODIS) clear-sky estimates. As both instruments are on board the same satellite, this reduces the uncertainty associated to the observations match-up, resulting in a lower RMSD of ˜ 4K. The microwave Ts is compared to in situ Ts time series from a collection of ground stations over a large range of environments. For 22 stations available in the 2003-2004 period, SSM/I Ts agrees very well for stations in vegetated environments (down to RMSD of ˜2.5 K for several stations), but the retrieval methodology encounters difficulties under cold conditions due to the large variability of snow and ice surface emissivities. For 10 stations in the year 2010, AMSR-E presents an all-station mean RMSD of ˜4.0 K with respect tom the ground Ts. Over the same stations, MODIS agrees better (RMSD of 2.4 K), ?but AMSR-E provides a larger number of Ts estimates by being able to measure under cloudy conditions, with an approximated ratio of 3 to 1 over the analysed stations. At many stations the RMSD of the AMSR-E clear and cloudy-sky are comparable, highlighting the ability of the microwave inversions to provide Ts under most atmospheric and surface conditions.

Estimation of vegetative mercury emissions in China.

PubMed

Quan, Jiannong; Zhang, Xiaoshan; Shim, Shang Gyoo

2008-01-01

Vegetative mercury emissions were estimated within the framework of Biogenic Emission Inventory System (BEIS3 V3.11). In this estimation, the 19 categories of U.S. Geological Survey landcover data were incorporated to generate the vegetation-specific mercury emissions in a 81-km Lambert Conformal model grid covering the total Chinese continent. The surface temperature and cloud-corrected solar radiation from a Mesoscale Meteorological model (MM5) were retrieved and used for calculating the diurnal variation. The implemented emission factors were either evaluated from the measured mercury flux data for forest, agriculture and water, or assumed for other land fields without available flux data. Annual simulations using the MM5 data were performed to investigate the seasonal emission variation. From the sensitivity analysis using two sets of emission factors, the vegetative mercury emissions in China domain were estimated to range from a lower limit of 79 x 10(3) kg/year to an upper limit of 177 x 10(3) kg/year. The modeled vegetative emissions were mainly generated from the eastern and southern China. Using the estimated data, it is shown that mercury emissions from vegetation are comparable to that from anthropogenic sources during summer. However, the vegetative emissions decrease greatly during winter, leaving anthropogenic sources as the major sources of emission.

Quantification of point sources of carbon monoxide using satellite measurements

NASA Astrophysics Data System (ADS)

Dekker, Iris; Houweling, Sander; Aben, Ilse; Roeckmann, Thomas; Krol, Maarten

2017-04-01

The growth of mega-cities leads to air quality problems directly affecting the citizens. With satellite measurements becoming of higher quality and quantity, satellite instruments can more accurately retrieve the enhanced air pollutant concentrations over large cities. The aim of this research is to quantify carbon monoxide emissions from megacities and their trends using satellite retrievals, combined with an atmospheric chemistry and transport model. Earlier emission estimations of cities have been done using MOPITT satellite data only. To improve the reliability of the emission estimation, we simulate MOPITT retrievals using the Weather Research and Forecast model with chemistry core (WRF-Chem). The difference between model and retrieval is used to optimize CO emissions in WRF-Chem, focusing on the city of Madrid, Spain. A reasonable agreement is obtained between the yearly averaged model output and satellite measurements (R2=0.75) for Madrid. After optimization, the emission of Madrid is reduced by 48% for 2002 and by 17% for 2006 compared with EdgarV4.2. The MOPITT derived emission adjustments lead to a better agreement with a European emission inventory TNO-MAC-III for both years. This suggested that the downward trend in CO emissions over Madrid is overestimated in EdgarV4.2 and more realistically represented in TNO-MAC-III. However, uncertainties remain large using our satellite-based emission estimation method, in the order of 20% for 2002 and 50% for 2006. Therefore, different options to increase the degrees of freedom in the optimization are investigated, to account for the noise in the MOPITT data. We also show comparisons with IASI data, which have a higher temporal resolution. The method is developed for application to Sentinel 5P TROPOMI, to be launched in June 2017.

An End-to-End simulator for the development of atmospheric corrections and temperature - emissivity separation algorithms in the TIR spectral domain

NASA Astrophysics Data System (ADS)

Rock, Gilles; Fischer, Kim; Schlerf, Martin; Gerhards, Max; Udelhoven, Thomas

2017-04-01

The development and optimization of image processing algorithms requires the availability of datasets depicting every step from earth surface to the sensor's detector. The lack of ground truth data obliges to develop algorithms on simulated data. The simulation of hyperspectral remote sensing data is a useful tool for a variety of tasks such as the design of systems, the understanding of the image formation process, and the development and validation of data processing algorithms. An end-to-end simulator has been set up consisting of a forward simulator, a backward simulator and a validation module. The forward simulator derives radiance datasets based on laboratory sample spectra, applies atmospheric contributions using radiative transfer equations, and simulates the instrument response using configurable sensor models. This is followed by the backward simulation branch, consisting of an atmospheric correction (AC), a temperature and emissivity separation (TES) or a hybrid AC and TES algorithm. An independent validation module allows the comparison between input and output dataset and the benchmarking of different processing algorithms. In this study, hyperspectral thermal infrared scenes of a variety of surfaces have been simulated to analyze existing AC and TES algorithms. The ARTEMISS algorithm was optimized and benchmarked against the original implementations. The errors in TES were found to be related to incorrect water vapor retrieval. The atmospheric characterization could be optimized resulting in increasing accuracies in temperature and emissivity retrieval. Airborne datasets of different spectral resolutions were simulated from terrestrial HyperCam-LW measurements. The simulated airborne radiance spectra were subjected to atmospheric correction and TES and further used for a plant species classification study analyzing effects related to noise and mixed pixels.

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.

Chlorophyll induced fluorescence retrieved from GOME2 for improving gross primary productivity estimates of vegetation

NASA Astrophysics Data System (ADS)

van Leth, Thomas C.; Verstraeten, Willem W.; Sanders, Abram F. J.

2014-05-01

Mapping terrestrial chlorophyll fluorescence is a crucial activity to obtain information on the functional status of vegetation and to improve estimates of light-use efficiency (LUE) and global primary productivity (GPP). GPP quantifies carbon fixation by plant ecosystems and is therefore an important parameter for budgeting terrestrial carbon cycles. Satellite remote sensing offers an excellent tool for investigating GPP in a spatially explicit fashion across different scales of observation. The GPP estimates, however, still remain largely uncertain due to biotic and abiotic factors that influence plant production. Sun-induced fluorescence has the ability to enhance our knowledge on how environmentally induced changes affect the LUE. This can be linked to optical derived remote sensing parameters thereby reducing the uncertainty in GPP estimates. Satellite measurements provide a relatively new perspective on global sun-induced fluorescence, enabling us to quantify spatial distributions and changes over time. Techniques have recently been developed to retrieve fluorescence emissions from hyperspectral satellite measurements. We use data from the Global Ozone Monitoring Instrument 2 (GOME2) to infer terrestrial fluorescence. The spectral signatures of three basic components atmospheric: absorption, surface reflectance, and fluorescence radiance are separated using reference measurements of non-fluorescent surfaces (desserts, deep oceans and ice) to solve for the atmospheric absorption. An empirically based principal component analysis (PCA) approach is applied similar to that of Joiner et al. (2013, ACP). Here we show our first global maps of the GOME2 retrievals of chlorophyll fluorescence. First results indicate fluorescence distributions that are similar with that obtained by GOSAT and GOME2 as reported by Joiner et al. (2013, ACP), although we find slightly higher values. In view of optimizing the fluorescence retrieval, we will show the effect of the references selection procedure on the retrieval product.

Non-LTE diagnositics of infrared radiation of Titan's atmosphere

NASA Astrophysics Data System (ADS)

Feofilov, Artem; Rezac, Ladislav; Kutepov, Alexander; Vinatier, Sandrine; Rey, Michael; Nikitin, Andrew; Tyuterev, Vladimir

2016-06-01

Yelle (1991) and Garcia-Comas et al, (2011) demonstrated the importance of accounting for the local thermodynamic equilibrium (LTE) breakdown in the middle and upper atmosphere of Titan for the interpretation of infrared radiances measured at these heights. In this work, we make further advance in this field by: • updating the non-LTE model of CH4 emissions in Titan's atmosphere and including a new extended database of CH4 spectroscopic parameters • studying the non-LTE CH4 vibrational level populations and the impact of non-LTE on limb infrared emissions of various CH4 ro-vibrational bands including those at 7.6 and 3.3 µm • implementing our non-LTE model into the LTE-based retrieval algorithm applied by Vinatier et al., (2015) for processing the Cassini/CIRS spectra. We demonstrate that accounting for non-LTE leads to an increase in temperatures retrieved from CIRS 7.6 µm limb emissions spectra (˜10 K at 600 km altitude) and estimate how this affects the trace gas density retrieval. Finally, we discuss the effects of including a large number of weak one-quantum and combinational bands on the calculated daytime limb 3.3 µm emissions and the impact they may have on the CH4 density retrievals from the Cassini VIMS 3.3 µm limb emission observations.

New Non-LTE Model of OH and CO2 Emission in the Mesosphere-Lower Thermosphere and its Application to Retrieving Nighttime Parameters

NASA Astrophysics Data System (ADS)

Panka, Peter A.

The hydroxyl, OH, and carbon dioxide, CO2, molecules and oxygen atoms, O(3P), are important parameters that characterize the chemistry, energetics, and dynamics of the nighttime mesosphere and lower thermosphere (MLT) region. Hence, there is much interest in obtaining high quality observations of these parameters in order to study the short-term variability as well as the long-term trends in characteristics of the MLT region. The Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) instrument on board the Thermosphere, Ionosphere, Mesosphere, Energetics, and Dynamics (TIMED) satellite has been taking global, simultaneous measurements of limb infrared radiance in 10 spectral channels, including the OH 2.0 and 1.6-micron and CO2 4.3-micron emissions channels, continuously since late January 2002. These measurements can be interpreted using sophisticated non-Local Thermodynamic Equilibrium (non-LTE) models of OH and CO2 infrared emissions which can then be applied to obtain densities of these parameters (2.0 and 1.6-micron channel for O(3P)/OH and 4.3-micron channel for CO2). The latest non-LTE models of these molecules, however, do not fully represent all the dominant energy transfer mechanisms which influence their vibrational level distributions and infrared emissions. In particular, non-LTE models of CO2 4.3-micron emissions currently under-predict SABER measurements by up to 80%, and its application for the retrieval of CO2 will result in unrealistic densities. Additionally, current O(3P) retrievals from SABER OH emissions have been reported to be at least 30% higher compared to studies using other instruments. Methods to obtain OH total densities from SABER measurements have yet to be developed. Recent studies, however, have discovered a new energy transfer mechanism which influences both OH and CO2 infrared emissions, OH(v) → O(1D) → N2( v) → CO2(v3). This study focuses on the impact of this new mechanism on OH and CO2 infrared emissions as well as model applications for the retrieval of nighttime O( 3P), OH, and CO2 densities. We first study in detail the impact of the new mechanism on OH( v) vibrational level populations and emissions. We compared our calculations with the SABER/TIMED OH 1.6 and 2.0-micron limb radiances of the MLT and with ground and space observations of OH(v) densities in the nighttime mesosphere. We find that the new mechanism produces OH(v) density distributions which are in good agreement with both SABER limb OH emission observations and ground and space measurements. We then couple our OH non-LTE model with CO2 to study the impact of the new mechanism on CO2(v3) vibrational level populations and emissions. We compare our calculations with the SABER/TIMED 4.3-micron CO2 limb radiances and find that the new mechanism provides a strong enhancement of the 4.3-micron CO2 emissions, agreeing to within a 10-30% range. Further, a two-channel retrieval algorithm is developed to self-consistently invert the SABER measured radiances in the OH 2.0 and 1.6-micron channel to obtain vertical profiles of OH and O(3P) Volume Mixing Ratio (VMR). Studies of the inversion algorithm made with synthetic radiances indicate that a stable solution of the inverse problem can be obtained that is nearly independent of the starting conditions. The results presented from the two-channel algorithm to the SABER v2.0 data include comparisons of retrieved O(3P) with current SABER O(3P), in addition to O(3P) retrievals measured by the SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY) instrument, as well as those calculated by the WACCM (Whole Atmosphere Community Climate Model) model for four different days. The O( 3P) density retrieved between 90-95 km are, on average, lower than current SABER O(3P) by 10-50%. OH retrievals are performed over the same days and are compared with OH WACCM calculations as well as other studies. Finally, a similar self-consistent algorithm used for the retrieval of daytime CO2 densities is adopted for nighttime. The situation, however, is more complex for nighttime CO2, where lack of solar irradiation excitation greatly reduce 4.3-micron emission sensitivity to CO 2 density and, therefore, produces unrealistic retrievals. Alternative retrieval methods will be required to overcome these obstacles. For daytime, retrieval of temperature and CO2 are performed simultaneously due to strong coupling between these two parameters. Consideration of this effect will be crucial to obtain accurate nighttime CO2 densities.

The impact of conventional surface data upon VAS regression retrievals in the lower troposphere

NASA Technical Reports Server (NTRS)

Lee, T. H.; Chesters, D.; Mostek, A.

1983-01-01

Surface temperature and dewpoint reports are added to the infrared radiances from the VISSR Atmospheric Sounder (VAS) in order to improve the retrieval of temperature and moisture profiles in the lower troposphere. The conventional (airways) surface data are combined with the twelve VAS channels as additional predictors in a ridge regression retrieval scheme, with the aim of using all available data to make high resolution space-time interpolations of the radiosonde network. For one day of VAS observations, retrievals using only VAS radiances are compared with retrievals using VAS radiances plus surface data. Temperature retrieval accuracy evaluated at coincident radiosonde sites shows a significant impact within the boundary layer. Dewpoint retrieval accuracy shows a broader improvement within the lowest tropospheric layers. The most dramatic impact of surface data is observed in the improved relative spatial and temporal continuity of low-level fields retrieved over the Midwestern United States.

A New Retrieval Algorithm for OMI NO2: Tropospheric Results and Comparisons with Measurements and Models

NASA Technical Reports Server (NTRS)

Swartz, W. H.; Bucesla, E. J.; Lamsal, L. N.; Celarier, E. A.; Krotkov, N. A.; Bhartia, P, K,; Strahan, S. E.; Gleason, J. F.; Herman, J.; Pickering, K.

2012-01-01

Nitrogen oxides (NOx =NO+NO2) are important atmospheric trace constituents that impact tropospheric air pollution chemistry and air quality. We have developed a new NASA algorithm for the retrieval of stratospheric and tropospheric NO2 vertical column densities using measurements from the nadir-viewing Ozone Monitoring Instrument (OMI) on NASA's Aura satellite. The new products rely on an improved approach to stratospheric NO2 column estimation and stratosphere-troposphere separation and a new monthly NO2 climatology based on the NASA Global Modeling Initiative chemistry-transport model. The retrieval does not rely on daily model profiles, minimizing the influence of a priori information. We evaluate the retrieved tropospheric NO2 columns using surface in situ (e.g., AQS/EPA), ground-based (e.g., DOAS), and airborne measurements (e.g., DISCOVER-AQ). The new, improved OMI tropospheric NO2 product is available at high spatial resolution for the years 200S-present. We believe that this product is valuable for the evaluation of chemistry-transport models, examining the spatial and temporal patterns of NOx emissions, constraining top-down NOx inventories, and for the estimation of NOx lifetimes.

SO2 Emissions and Lifetimes: Estimates from Inverse Modeling Using In Situ and Global, Space-Based (SCIAMACHY and OMI) Observations

NASA Technical Reports Server (NTRS)

Lee, Chulkyu; Martin Randall V.; vanDonkelaar, Aaron; Lee, Hanlim; Dickerson, RUssell R.; Hains, Jennifer C.; Krotkov, Nickolay; Richter, Andreas; Vinnikov, Konstantine; Schwab, James J.

2011-01-01

Top-down constraints on global sulfur dioxide (SO2) emissions are inferred through inverse modeling using SO2 column observations from two satellite instruments (SCIAMACHY and OMI). We first evaluated the S02 column observations with surface SO2 measurements by applying local scaling factors from a global chemical transport model (GEOS-Chem) to SO2 columns retrieved from the satellite instruments. The resulting annual mean surface SO2 mixing ratios for 2006 exhibit a significant spatial correlation (r=0.86, slope=0.91 for SCIAMACHY and r=0.80, slope = 0.79 for OMI) with coincident in situ measurements from monitoring networks throughout the United States and Canada. We evaluate the GEOS-Chem simulation of the SO2 lifetime with that inferred from in situ measurements to verity the applicability of GEOS-Chem for inversion of SO2 columns to emissions. The seasonal mean SO2 lifetime calculated with the GEOS-Chem model over the eastern United States is 13 h in summer and 48 h in winter, compared to lifetimes inferred from in situ measurements of 19 +/- 7 h in summer and 58 +/- 20 h in winter. We apply SO2 columns from SCIAMACHY and OMI to derive a top-down anthropogenic SO2 emission inventory over land by using the local GEOS-Chem relationship between SO2 columns and emissions. There is little seasonal variation in the top-down emissions (<15%) over most major industrial regions providing some confidence in the method. Our global estimate for annual land surface anthropogenic SO2 emissions (52.4 Tg S/yr from SCIAMACHY and 49.9 Tg S / yr from OMI) closely agrees with the bottom-up emissions (54.6 Tg S/yr) in the GEOS-Chem model and exhibits consistency in global distributions with the bottom-up emissions (r = 0.78 for SCIAMACHY, and r = 0.77 for OMI). However, there are significant regional differences.

First microwave map of the Moon with Chang'E-1 data: The role of local time in global imaging

NASA Astrophysics Data System (ADS)

Zheng, Y. C.; Tsang, K. T.; Chan, K. L.; Zou, Y. L.; Zhang, F.; Ouyang, Z. Y.

2012-05-01

Among recent lunar orbiters, only the Chinese Chang'E-1 (CE-1) was equipped with a passive microwave radiometer (MRM) to measure the natural microwave emission from the lunar surface. The microwave emission, characterized by a frequency-dependent brightness temperature (TB), is related to the physical temperature and dielectric properties of the lunar surface. By measuring the brightness temperature at different frequencies, detailed thermal behavior and properties of the lunar surface can be retrieved. Using CE-1's microwave data, we present here a set of microwave maps of the Moon constructed through a rescaling of TB to noontime or midnight. The adopted processing technique helps to reduce the effect of mixing up the temporal and spatial variations introduced by the satellite's localized measurements which cover different locations of the globe at different lunar local times. The resulting maps show fine structures unseen in previous microwave maps that disregarded the local time effect. We discussed the new features revealed and their possible connections with the lunar geology.

Derivation and evaluation of land surface temperature from the geostationary operational environmental satellite series

NASA Astrophysics Data System (ADS)

Fang, Li

The Geostationary Operational Environmental Satellites (GOES) have been continuously monitoring the earth surface since 1970, providing valuable and intensive data from a very broad range of wavelengths, day and night. The National Oceanic and Atmospheric Administration's (NOAA's) National Environmental Satellite, Data, and Information Service (NESDIS) is currently operating GOES-15 and GOES-13. The design of the GOES series is now heading to the 4 th generation. GOES-R, as a representative of the new generation of the GOES series, is scheduled to be launched in 2015 with higher spatial and temporal resolution images and full-time soundings. These frequent observations provided by GOES Image make them attractive for deriving information on the diurnal land surface temperature (LST) cycle and diurnal temperature range (DTR). These parameters are of great value for research on the Earth's diurnal variability and climate change. Accurate derivation of satellite-based LSTs from thermal infrared data has long been an interesting and challenging research area. To better support the research on climate change, the generation of consistent GOES LST products for both GOES-East and GOES-West from operational dataset as well as historical archive is in great demand. The derivation of GOES LST products and the evaluation of proposed retrieval methods are two major objectives of this study. Literature relevant to satellite-based LST retrieval techniques was reviewed. Specifically, the evolution of two LST algorithm families and LST retrieval methods for geostationary satellites were summarized in this dissertation. Literature relevant to the evaluation of satellite-based LSTs was also reviewed. All the existing methods are a valuable reference to develop the GOES LST product. The primary objective of this dissertation is the development of models for deriving consistent GOES LSTs with high spatial and high temporal coverage. Proper LST retrieval algorithms were studied according to the characteristics of the imager onboard the GOES series. For the GOES 8-11 and GOES R series with split window (SW) channels, a new temperature and emissivity separation (TES) approach was proposed for deriving LST and LSE simultaneously by using multiple-temporal satellite observations. Two split-window regression formulas were selected for this approach, and two satellite observations over the same geo-location within a certain time interval were utilized. This method is particularly applicable to geostationary satellite missions from which qualified multiple-temporal observations are available. For the GOES M(12)-Q series without SW channels, the dual-window LST algorithm was adopted to derive LST. Instead of using the conventional training method to generate coefficients for the LST regression algorithms, a machine training technique was introduced to automatically select the criteria and the boundary of the sub-ranges for generating algorithm coefficients under different conditions. A software package was developed to produce a brand new GOES LST product from both operational GOES measurements and historical archive. The system layers of the software and related system input and output were illustrated in this work. Comprehensive evaluation of GOES LST products was conducted by validating products against multiple ground-based LST observations, LST products from fine-resolution satellites (e.g. MODIS) and GSIP LST products. The key issues relevant to the cloud diffraction effect were studied as well. GOES measurements as well as ancillary data, including satellite and solar geometry, water vapor, cloud mask, land emissivity etc., were collected to generate GOES LST products. In addition, multiple in situ temperature measurements were collected to test the performance of the proposed GOES LST retrieval algorithms. The ground-based dataset included direct surface temperature measurements from the Atmospheric Radiation Measurement program (ARM), and indirect measurements (surface long-wave radiation observations) from the SURFace RADiation Budget (SURFRAD) Network. A simulated dataset was created to analyse the sensitivity of the proposed retrieval algorithms. In addition, the MODIS LST and GSIP LST products were adopted to cross-evaluate the accuracy of the GOES LST products. Evaluation results demonstrate that the proposed GOES LST system is capable of deriving consistent land surface temperatures with good retrieval precision. Consistent GOES LST products with high spatial/temporal coverage and reliable accuracy will better support detections and observations of meteorological over land surfaces.

Retrieval of O+ Density From Combined OII 83.4 nm and OII 61.7 nm Limb Emissions

NASA Astrophysics Data System (ADS)

Geddes, G.; Finn, S. C.; Stephan, A. W.; Cook, T.; Chakrabarti, S.

2016-12-01

OII 83.4 nm and OII 61.7 nm emissions are produced by photoionization of neutral oxygen in the thermosphere. While OII 83.4 nm photons are resonantly scattered by O+ ions, OII 61.7 nm photons do not interact with the ionosphere. Combined observations of these two features, which share a production mechanism but have different paths through the ionosphere, can be used to infer the O+ density causing the scattering of OII 83.4 nm. We retrieve O+ density from synthetic measurements of the OII 83.4 nm and OII 61.7 nm emission features using a Markov chain Monte Carlo technique. This method allows us to quantify constraints on retrieved ionospheric parameters, giving an estimate of O+ density retrieval capability in preparation for the Limb-Imaging Ionospheric and Thermospheric Extreme-ultraviolet Spectrograph (LITES), scheduled to fly on the International Space Station in November 2016. This work is also applicable to observations from the Ionospheric Connection Explorer (ICON), scheduled for launch in June 2017.

Space-based observations of nitrogen dioxide: Trends in anthropogenic emissions

NASA Astrophysics Data System (ADS)

Russell, Ashley Ray

Space-based instruments provide routine global observations, offering a unique perspective on the spatial and temporal variation of atmospheric constituents. In this dissertation, trends in regional-scale anthropogenic nitrogen oxide emissions (NO + NO2 ≡ NOx) are investigated using high resolution observations from the Ozone Monitoring Instrument (OMI). By comparing trends in OMI observations with those from ground-based measurements and an emissions inventory, I show that satellite observations are well-suited for capturing changes in emissions over time. The high spatial and temporal resolutions of the observations provide a uniquely complete view of regional-scale changes in the spatial patterns of NO 2. I show that NOx concentrations have decreased significantly in urban regions of the United States between 2005 and 2011, with an average reduction of 32 ± 7%. By examining day-of-week and interannual trends, I show that these reductions can largely be attributed to improved emission control technology in the mobile source fleet; however, I also show that the economic downturn of the late 2000's has impacted emissions. Additionally, I describe the development of a high-resolution retrieval of NO2 from OMI observations known as the Berkeley High Resolution (BEHR) retrieval. The BEHR product uses higher spatial and temporal resolution terrain and profile parameters than the operational retrievals and is shown to provide a more quantitative measure of tropospheric NO2 column density. These results have important implications for future retrievals of NO2 from space-based observations.

Comparing Landsat-7 ETM+ and ASTER Imageries to Estimate Daily Evapotranspiration Within a Mediterranean Vineyard Watershed

NASA Technical Reports Server (NTRS)

Montes, Carlo; Jacob, Frederic

2017-01-01

We compared the capabilities of Landsat-7 Enhanced Thematic Mapper Plus (ETM+) and Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) imageries for mapping daily evapotranspiration (ET) within a Mediterranean vineyard watershed. We used Landsat and ASTER data simultaneously collected on four dates in 2007 and 2008, along with the simplified surface energy balance index (S-SEBI) model. We used previously ground-validated good quality ASTER estimates as reference, and we analyzed the differences with Landsat retrievals in light of the instrumental factors and methodology. Although Landsat and ASTER retrievals of S-SEBI inputs were different, estimates of daily ET from the two imageries were similar. This is ascribed to the S-SEBI spatial differencing in temperature, and opens the path for using historical Landsat time series over vineyards.

A Physical Model to Determine Snowfall over Land by Microwave Radiometry

NASA Technical Reports Server (NTRS)

Skofronick-Jackson, G.; Kim, M.-J.; Weinman, J. A.; Chang, D.-E.

2003-01-01

Because microwave brightness temperatures emitted by snow covered surfaces are highly variable, snowfall above such surfaces is difficult to observe using window channels that occur at low frequencies (v less than 100 GHz). Furthermore, at frequencies v less than or equal to 37 GHz, sensitivity to liquid hydrometeors is dominant. These problems are mitigated at high frequencies (v greater than 100 GHz) where water vapor screens the surface emission and sensitivity to frozen hydrometeors is significant. However the scattering effect of snowfall in the atmosphere at those higher frequencies is also impacted by water vapor in the upper atmosphere. This work describes the methodology and results of physically-based retrievals of snow falling over land surfaces. The theory of scattering by randomly oriented dry snow particles at high microwave frequencies appears to be better described by regarding snow as a concatenation of equivalent ice spheres rather than as a sphere with the effective dielectric constant of an air-ice mixture. An equivalent sphere snow scattering model was validated against high frequency attenuation measurements. Satellite-based high frequency observations from an Advanced Microwave Sounding Unit (AMSU-B) instrument during the March 5-6, 2001 New England blizzard were used to retrieve snowfall over land. Vertical distributions of snow, temperature and relative humidity profiles were derived from the Pennsylvania State University-National Center for Atmospheric Research (PSU-NCAR) fifth-generation Mesoscale Model (MM5). Those data were applied and modified in a radiative transfer model that derived brightness temperatures consistent with the AMSU-B observations. The retrieved snowfall distribution was validated with radar reflectivity measurements obtained from the National Oceanic and Atmospheric Administration (NOAA) National Weather Service (NWS) ground-based radar network.

Satellite microwave detection of contrasting changes in surface inundation across pan-Arctic permafrost zones

NASA Astrophysics Data System (ADS)

Watts, J.; Kimball, J. S.; Jones, L. A.; Schroeder, R.; McDonald, K. C.

2012-12-01

Surface water inundation in the Arctic is concomitant with soil permafrost and strongly influences land-atmosphere water, energy and carbon (CO2, CH4) exchange, and plant community structure. We examine recent (2003-2010) surface water inundation patterns across the pan-Arctic (≥ 50 deg.N) and within major permafrost zones using satellite passive microwave remote sensing retrievals of fractional open water extent (Fw) derived from Advanced Microwave Scanning Radiometer for EOS (AMSR-E) 18.7 and 23.8 GHz brightness temperatures. The AMSR-E Fw retrievals are insensitive to atmosphere contamination and solar illumination effects, enabling daily Fw monitoring across the Arctic. The Fw retrievals are sensitive to sub-grid scale open water inundation area, including lakes and wetlands, within the relatively coarse (~25-km resolution) satellite footprint. A forward model error sensitivity analysis indicates that total Fw retrieval uncertainty is within ±4.1% (RMSE), and AMSR-E Fw compares favorably (0.71 < R2 < 0.84) with alternative static open water maps derived from finer scale (30-m to 250-m resolution) Landsat, MODIS and SRTM radar-based products. The Fw retrievals also show dynamic seasonal and annual variability in surface inundation that corresponds (0.71 < R < 0.87) with regional wet/dry cycles inferred from basin discharge records, including Yukon, Mackenzie, Ob, Yenisei, and Lena basins. A regional change analysis of the 8-yr AMSR-E record shows no significant trend in pan-Arctic wide Fw, and instead reveals contrasting inundation changes within permafrost zones. Widespread Fw wetting is observed within continuous (92% of grid cells with significant trend show wetting; p < 0.1) and discontinuous (82%) permafrost zones, while areas with sporadic/isolated permafrost show widespread (71%) Fw drying. These results are consistent with previous studies showing evidence of changes in regional surface hydrology influenced by permafrost degradation under recent climate warming. Changes in Fw may also be linked to shifts in regional precipitation patterns and a lengthening non-frozen season. Regional changes observed in the AMSR-E Fw record compliment finer-scale permafrost monitoring efforts and documented variability in surface inundation extent may help constrain pan-Arctic lake and wetland CO2, CH4 emission estimates. This work was supported under the Jet Propulsion Laboratory, California Institute of Technology under contract to the National Aeronautics and Space Administration, NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) programs.

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.

Correction of the angular dependence of satellite retrieved LST at global scale using parametric models

NASA Astrophysics Data System (ADS)

Ermida, S. L.; Trigo, I. F.; DaCamara, C.; Ghent, D.

2017-12-01

Land surface temperature (LST) values retrieved from satellite measurements in the thermal infrared (TIR) may be strongly affected by spatial anisotropy. This effect introduces significant discrepancies among LST estimations from different sensors, overlapping in space and time, that are not related to uncertainties in the methodologies or input data used. Furthermore, these directional effects deviate LST products from an ideally defined LST, which should represent to the ensemble of directional radiometric temperature of all surface elements within the FOV. Angular effects on LST are here conveniently estimated by means of a parametric model of the surface thermal emission, which describes the angular dependence of LST as a function of viewing and illumination geometry. Two models are consistently analyzed to evaluate their performance of and to assess their respective potential to correct directional effects on LST for a wide range of surface conditions, in terms of tree coverage, vegetation density, surface emissivity. We also propose an optimization of the correction of directional effects through a synergistic use of both models. The models are calibrated using LST data as provided by two sensors: MODIS on-board NASA's TERRA and AQUA; and SEVIRI on-board EUMETSAT's MSG. As shown in our previous feasibility studies the sampling of illumination and view angles has a high impact on the model parameters. This impact may be mitigated when the sampling size is increased by aggregating pixels with similar surface conditions. Here we propose a methodology where land surface is stratified by means of a cluster analysis using information on land cover type, fraction of vegetation cover and topography. The models are then adjusted to LST data corresponding to each cluster. It is shown that the quality of the cluster based models is very close to the pixel based ones. Furthermore, the reduced number of parameters allows improving the model trough the incorporation of a seasonal component. The application of the procedure discussed here towards the harmonization of LST products from multi-sensors has been tested within the framework of the ESA DUE GlobTemperature project. It is also expected to help the characterization of directional effects of LST products generated within the EUMETSAT LSA SAF.

Improved Remote Sensing Retrieval of Land Surface Temperature in the Thermal Infrared (TIR) Using Visible/Short Wave Infrared (VSWIR) Imaging Spectrometer Estimated Water Vapor

NASA Astrophysics Data System (ADS)

Grigsby, S.; Hulley, G. C.; Roberts, D. A.; Scheele, C. J.; Ustin, S.; Alsina, M. M.

2014-12-01

Land surface temperature (LST) is an important parameter in many ecological studies, where processes such as evapotranspiration have impacts at temperature gradients less than 1 K. Current errors in standard MODIS and ASTER LST products are greater than 1 K, and for ASTER can be greater than 2 K in humid conditions due to incomplete atmospheric correction of atmospheric water vapor. Estimates of water vapor, either derived from visible-to-shortwave-infrared (VSWIR) remote sensing data or taken from weather simulation data such as NCEP, can be combined with coincident Thermal-Infrared (TIR) remote sensing data to yield improved accuracy in LST measurements. This study compares LST retrieval accuracies derived using the standard JPL MASTER Temperature Emissivity Separation (TES) algorithm, and the Water Vapor Scaling (WVS) atmospheric correction method proposed for the Hyperspectral Infrared Imager, or HyspIRI, mission with ground observations. The 2011 ER-2 Delano/Lost Hills flights acquired TIR data from the MODIS/ASTER Simulator (MASTER) and VSWIR data from Airborne Visible InfraRed Imaging Spectrometer (AVIRIS) instruments flown concurrently. The TES and WVS retrieval methods are run with and without high spatial resolution AVIRIS-derived water vapor maps to assess the improvement using VSWIR water vapor estimates. We find improvement using VSWIR derived water vapor maps in both cases, with the WVS method being most accurate overall. For closed canopy agricultural vegetation we observed canopy temperature retrieval RMSEs of 0.49 K and 0.70 K using the WVS method on MASTER data with and without AVIRIS derived water vapor, respectively.

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.

Atmospheric Parameter Climatologies from AIRS: Monitoring Short-, and Longer-Term Climate Variabilities and 'Trends'

NASA Technical Reports Server (NTRS)

Molnar, Gyula; Susskind, Joel

2008-01-01

The AIRS instrument is currently the best space-based tool to simultaneously monitor the vertical distribution of key climatically important atmospheric parameters as well as surface properties, and has provided high quality data for more than 5 years. AIRS analysis results produced at the GODDARD/DAAC, based on Versions 4 & 5 of the AIRS retrieval algorithm, are currently available for public use. Here, first we present an assessment of interrelationships of anomalies (proxies of climate variability based on 5 full years, since Sept. 2002) of various climate parameters at different spatial scales. We also present AIRS-retrievals-based global, regional and 1x1 degree grid-scale "trend"-analyses of important atmospheric parameters for this 5-year period. Note that here "trend" simply means the linear fit to the anomaly (relative the mean seasonal cycle) time series of various parameters at the above-mentioned spatial scales, and we present these to illustrate the usefulness of continuing AIRS-based climate observations. Preliminary validation efforts, in terms of intercomparisons of interannual variabilities with other available satellite data analysis results, will also be addressed. For example, we show that the outgoing longwave radiation (OLR) interannual spatial variabilities from the available state-of-the-art CERES measurements and from the AIRS computations are in remarkably good agreement. Version 6 of the AIRS retrieval scheme (currently under development) promises to further improve bias agreements for the absolute values by implementing a more accurate radiative transfer model for the OLR computations and by improving surface emissivity retrievals.

Using High-Resolution Airborne Remote Sensing to Study Aerosol Near Clouds

NASA Technical Reports Server (NTRS)

Levy, Robert; Munchak, Leigh; Mattoo, Shana; Marshak, Alexander; Wilcox, Eric; Gao, Lan; Yorks, John; Platnick, Steven

2016-01-01

The horizontal space in between clear and cloudy air is very complex. This so-called twilight zone includes activated aerosols that are not quite clouds, thin cloud fragments that are not easily observable, and dying clouds that have not quite disappeared. This is a huge challenge for satellite remote sensing, specifically for retrieval of aerosol properties. Identifying what is cloud versus what is not cloud is critically important for attributing radiative effects and forcings to aerosols. At the same time, the radiative interactions between clouds and the surrounding media (molecules, surface and aerosols themselves) will contaminate retrieval of aerosol properties, even in clear skies. Most studies on aerosol cloud interactions are relevant to moderate resolution imagery (e.g. 500 m) from sensors such as MODIS. Since standard aerosol retrieval algorithms tend to keep a distance (e.g. 1 km) from the nearest detected cloud, it is impossible to evaluate what happens closer to the cloud. During Studies of Emissions, Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS), the NASA ER-2 flew with the enhanced MODIS Airborne Simulator (eMAS), providing MODIS-like spectral observations at high (50 m) spatial resolution. We have applied MODIS-like aerosol retrieval for the eMAS data, providing new detail to characterization of aerosol near clouds. Interpretation and evaluation of these eMAS aerosol retrievals is aided by independent MODIS-like cloud retrievals, as well as profiles from the co-flying Cloud Physics Lidar (CPL). Understanding aerosolcloud retrieval at high resolution will lead to better characterization and interpretation of long-term, global products from lower resolution (e.g.MODIS) satellite retrievals.

Advances in Assimilation of Satellite-Based Passive Microwave Observations for Soil-Moisture Estimation

NASA Technical Reports Server (NTRS)

De Lannoy, Gabrielle J. M.; Pauwels, Valentijn; Reichle, Rolf H.; Draper, Clara; Koster, Randy; Liu, Qing

2012-01-01

Satellite-based microwave measurements have long shown potential to provide global information about soil moisture. The European Space Agency (ESA) Soil Moisture and Ocean Salinity (SMOS, [1]) mission as well as the future National Aeronautics and Space Administration (NASA) Soil Moisture Active and Passive (SMAP, [2]) mission measure passive microwave emission at L-band frequencies, at a relatively coarse (40 km) spatial resolution. In addition, SMAP will measure active microwave signals at a higher spatial resolution (3 km). These new L-band missions have a greater sensing depth (of -5cm) compared with past and present C- and X-band microwave sensors. ESA currently also disseminates retrievals of SMOS surface soil moisture that are derived from SMOS brightness temperature observations and ancillary data. In this research, we address two major challenges with the assimilation of recent/future satellite-based microwave measurements: (i) assimilation of soil moisture retrievals versus brightness temperatures for surface and root-zone soil moisture estimation and (ii) scale-mismatches between satellite observations, models and in situ validation data.

Performance assessment of femoral knee components made from cobalt-chromium alloy and oxidized zirconium.

PubMed

Brandt, J-M; Guenther, L; O'Brien, S; Vecherya, A; Turgeon, T R; Bohm, E R

2013-12-01

The surface characteristics of the femoral component affect polyethylene wear in modular total knee replacements. In the present retrieval study, the surface characteristics of cobalt-chromium (CoCr) alloy and oxidized zirconium (OxZr) femoral components were assessed and compared. Twenty-six retrieved CoCr alloy femoral components were matched with twenty-six retrieved OxZr femoral components for implantation period, body-mass index, patient gender, implant type, and polyethylene insert thickness. The surface damage on the retrieved femoral components was evaluated using a semi-quantitative assessment method, scanning electron microscopy, and contact profilometry. The retrieved CoCr alloy femoral components showed less posterior surface gouging than OxZr femoral components; however, at a higher magnification, the grooving damage features on the retrieved CoCr alloy femoral components confirmed an abrasive wear mechanism. The surface roughness values Rp, Rpm, and Rpk for the retrieved CoCr alloy femoral components were found to be significantly higher than those of the retrieved OxZr femoral components (p≤0.031). The surface roughness values were higher on the medial condyles than on the lateral condyles of the retrieved CoCr alloy femoral components; such a difference was not observed on the retrieved OxZr femoral components. The surface roughness of CoCr alloy femoral components increased while the surface roughness of the OxZr femoral components remained unchanged after in vivo service. Therefore, the OxZr femoral components' resistance to abrasive wear may enable lower polyethylene wear and ensure long-term durability in vivo. Level IV. Crown Copyright © 2013. Published by Elsevier B.V. All rights reserved.

Validation of the MODIS MOD21 and MOD11 land surface temperature and emissivity products in an arid area of Northwest China

NASA Astrophysics Data System (ADS)

Li, H.; Yang, Y.; Yongming, D.; Cao, B.; Qinhuo, L.

2017-12-01

Land surface temperature (LST) is a key parameter for hydrological, meteorological, climatological and environmental studies. During the past decades, many efforts have been devoted to the establishment of methodology for retrieving the LST from remote sensing data and significant progress has been achieved. Many operational LST products have been generated using different remote sensing data. MODIS LST product (MOD11) is one of the most commonly used LST products, which is produced using a generalized split-window algorithm. Many validation studies have showed that MOD11 LST product agrees well with ground measurements over vegetated and inland water surfaces, however, large negative biases of up to 5 K are present over arid regions. In addition, land surface emissivity of MOD11 are estimated by assigning fixed emissivities according to a land cover classification dataset, which may introduce large errors to the LST product due to misclassification of the land cover. Therefore, a new MODIS LSE&E product (MOD21) is developed based on the temperature emissivity separation (TES) algorithm, and the water vapor scaling (WVS) method has also been incorporated into the MODIS TES algorithm for improving the accuracy of the atmospheric correction. The MOD21 product will be released with MODIS collection 6 Tier-2 land products in 2017. Due to the MOD21 products are not available right now, the MODTES algorithm was implemented including the TES and WVS methods as detailed in the MOD21 Algorithm Theoretical Basis Document. The MOD21 and MOD11 C6 LST products are validated using ground measurements and ASTER LST products collected in an arid area of Northwest China during the Heihe Watershed Allied Telemetry Experimental Research (HiWATER) experiment. In addition, lab emissivity spectra of four sand dunes in the Northwest China are also used to validate the MOD21 and MOD11 emissivity products.

On the angular variation of thermal infrared emissivity of inorganic soils

NASA Astrophysics Data System (ADS)

GarcíA-Santos, Vicente; Valor, Enric; Caselles, Vicente; ÁNgeles Burgos, M.; Coll, CéSar

2012-10-01

Land surface temperature (LST), a key parameter for many environmental studies, can be most readily estimated by using thermal infrared (TIR) sensors onboard satellites. Accurate LST are contingent upon simultaneously accurate estimates of land surface emissivity (ɛ), which depend on sensor viewing angle and the anisotropy of optical and structural properties of surfaces. In the case of inorganic bare soils (IBS), there are still few data that quantify emissivity angular effects. The present work deals with the angular variation of TIR emissivity for twelve IBS types, representative of nine of the twelve soil textures found on Earth according to United States Department of Agriculture classification. Emissivity was measured with a maximum error of ±0.01, in several spectral ranges within the atmospheric window 7.7-14.3 μm, at different zenithal (θ) and azimuthal (φ) angles. Results showed that ɛ of all IBS studied is almost azimuthally isotropic, and also zenithally up to θ = 40°, from which ɛ values decrease with the increase of θ. This decrease is most pronounced in sandy IBS which is rich in quartz reaching a maximum difference from nadir of +0.101 at θ = 70°. On the other hand, clayey IBS did not show a significant decrease of ɛ up to θ= 60°. A parameterization of the relative-to-nadir emissivity in terms ofθ and sand and clay percentage was established. Finally, the impact of ignoring ɛangular effects on the retrievals of LST, using split-window-type algorithms, and of outgoing longwave radiation, was analyzed. Results showed systematic errors ranging between ±0.4 K to ±1.3 K for atmospheres with water vapor values lower than 4 cm in the case of LST, and errors between 2%-8%, in the estimation of different terms of the surface energy balance.

Effects of varying soil moisture contents and vegetation canopies on microwave emissions

NASA Technical Reports Server (NTRS)

Burke, H.-H. K.; Schmugge, T. J.

1982-01-01

Results of NASA airborne passive microwave scans of bare and vegetated fields for comparison with ground truth tests are discussed and a model for atmospheric scattering of radiation by vegetation is detailed. On-board radiometers obtained data at 21, 2.8, and 1.67 cm during three passes over each of 46 fields, 28 of which were bare and the others having wheat or alfalfa. Ground-based sampling included moisture in five layers down to 15 cm in addition to soil temperature. The relationships among the brightness temperature and soil moisture, as well as the surface roughness and the vegetation canopy were examined. A model was developed for the dielectric coefficient and volume scattering for a vegetation medium. L- to C-band data were found useful for retrieving soil information directly. A surface moisture content of 5-35% yielded an emissivity of 0.9-0.7. The data agreed well with a combined multilayer radiative transfer model with simple roughness correction.

The influence of Vegetation Water Content (VWC) dynamics on microwave observations of a corn canopy during SMAPVEX16-IA

NASA Astrophysics Data System (ADS)

Steele-Dunne, Susan; Polo Bermejo, Jaime; Judge, Jasmeet; Bongiovanni, Tara; Chakrabarti, Subit; Liu, Pang-Wei; Bragdon, James; Hornbuckle, Brian

2017-04-01

Vegetation cover confounds soil moisture retrieval from both active and passive microwave remote sensing observations. Vegetation attenuates the signal from the soil as well as contributing to emission and scattering. The goal of this study was to characterize the vertical distribution of moisture within an agricultural canopy, to examine how this varies during the growing season and to determine the influence these changes have on emission and backscatter from the surface. To this end, an extensive campaign of destructive sampling was conducted in a rain-fed corn field at Buckeye, Iowa within the SMAPVEX16-IA study domain. The experiment duration extended from the beginning of IOP1 to the end of IOP2, i.e. from May 18 to August 16 2016. Destructive vegetation sampling was performed on most days upon which SMAP had both an ascending and a descending pass. On these days, destructive samples were collected at 6pm and 6pm unless the weather conditions were prohibitive. In addition to measuring the bulk vegetation water content for comparison to the SMAP retrieved VWC, the samples were split into leaves and stems. To study the vertical profiles, leaf moisture content was measured as a function of collar height and the stem was cut into 10cm sections. The influence of plant development on the bulk and profile VWC was clearly discernible in the observations. Diurnal variations in bulk VWC were relatively small due to moisture availability in the root zone. SMAP brightness temperatures, and tower-based observations from the University of Florida radiometer and radar systems were analyzed to investigate the impact of VWC variations on emission and backscatter. Dynamic variations in SMAP retrieved soil moisture were notably larger than those observed in-situ, particularly during the early growing season. This may be attributed to the difference between observed VWC and that used in the SMAP retrieval during the early growing season. Backscatter (and RVI) increased, as expected, in response to accumulating biomass, though retaining some sensitivity to soil moisture variations. Polarization-dependent diurnal differences of up to 2dB were observed in the backscatter from the fully grown corn canopy.

Land surface dynamics monitoring using microwave passive satellite sensors

NASA Astrophysics Data System (ADS)

Guijarro, Lizbeth Noemi

Soil moisture, surface temperature and vegetation are variables that play an important role in our environment. There is growing demand for accurate estimation of these geophysical parameters for the research of global climate models (GCMs), weather, hydrological and flooding models, and for the application to agricultural assessment, land cover change, and a wide variety of other uses that meet the needs for the study of our environment. The different studies covered in this dissertation evaluate the capabilities and limitations of microwave passive sensors to monitor land surface dynamics. The first study evaluates the 19 GHz channel of the SSM/I instrument with a radiative transfer model and in situ datasets from the Illinois stations and the Oklahoma Mesonet to retrieve land surface temperature and surface soil moisture. The surface temperatures were retrieved with an average error of 5 K and the soil moisture with an average error of 6%. The results show that the 19 GHz channel can be used to qualitatively predict the spatial and temporal variability of surface soil moisture and surface temperature at regional scales. In the second study, in situ observations were compared with sensor observations to evaluate aspects of low and high spatial resolution at multiple frequencies with data collected from the Southern Great Plains Experiment (SGP99). The results showed that the sensitivity to soil moisture at each frequency is a function of wavelength and amount of vegetation. The results confirmed that L-band is more optimal for soil moisture, but each sensor can provide soil moisture information if the vegetation water content is low. The spatial variability of the emissivities reveals that resolution suffers considerably at higher frequencies. The third study evaluates C- and X-bands of the AMSR-E instrument. In situ datasets from the Soil Moisture Experiments (SMEX03) in South Central Georgia were utilized to validate the AMSR-E soil moisture product and to derive surface soil moisture with a radiative transfer model. The soil moisture was retrieved with an average error of 2.7% at X-band and 6.7% at C-band. The AMSR-E demonstrated its ability to successfully infer soil moisture during the SMEX03 experiment.

A Numerical Testbed for Remote Sensing of Aerosols, and its Demonstration for Evaluating Retrieval Synergy from a Geostationary Satellite Constellation of GEO-CAPE and GOES-R

NASA Technical Reports Server (NTRS)

Wang, Jun; Xu, Xiaoguang; Ding, Shouguo; Zeng, Jing; Spurr, Robert; Liu, Xiong; Chance, Kelly; Mishchenko, Michael I.

2014-01-01

We present a numerical testbed for remote sensing of aerosols, together with a demonstration for evaluating retrieval synergy from a geostationary satellite constellation. The testbed combines inverse (optimal-estimation) software with a forward model containing linearized code for computing particle scattering (for both spherical and non-spherical particles), a kernel-based (land and ocean) surface bi-directional reflectance facility, and a linearized radiative transfer model for polarized radiance. Calculation of gas absorption spectra uses the HITRAN (HIgh-resolution TRANsmission molecular absorption) database of spectroscopic line parameters and other trace species cross-sections. The outputs of the testbed include not only the Stokes 4-vector elements and their sensitivities (Jacobians) with respect to the aerosol single scattering and physical parameters (such as size and shape parameters, refractive index, and plume height), but also DFS (Degree of Freedom for Signal) values for retrieval of these parameters. This testbed can be used as a tool to provide an objective assessment of aerosol information content that can be retrieved for any constellation of (planned or real) satellite sensors and for any combination of algorithm design factors (in terms of wavelengths, viewing angles, radiance and/or polarization to be measured or used). We summarize the components of the testbed, including the derivation and validation of analytical formulae for Jacobian calculations. Benchmark calculations from the forward model are documented. In the context of NASA's Decadal Survey Mission GEOCAPE (GEOstationary Coastal and Air Pollution Events), we demonstrate the use of the testbed to conduct a feasibility study of using polarization measurements in and around the O2 A band for the retrieval of aerosol height information from space, as well as an to assess potential improvement in the retrieval of aerosol fine and coarse mode aerosol optical depth (AOD) through the synergic use of two future geostationary satellites, GOES-R (Geostationary Operational Environmental Satellite R-series) and TEMPO (Tropospheric Emissions: Monitoring of Pollution). Strong synergy between GEOS-R and TEMPO are found especially in their characterization of surface bi-directional reflectance, and thereby, can potentially improve the AOD retrieval to the accuracy required by GEO-CAPE.

Retrieve Aerosol Concentration Based On Surface Model and Distribution of Concentration of PM2.5 ——A Case Study of Beijing

NASA Astrophysics Data System (ADS)

Cui, H.

2017-12-01

As China's economy continues to grow, urbanization continues to advance, along with growth in all areas to pollutant emissions in the air industry, air quality also continued to deteriorate. Aerosol concentrations as a measure of air quality of the most important part of are more and more people's attention. Traditional monitoring stations measuring aerosol concentration method is accurate, but time-consuming and can't be done simultaneously measure a large area, can only rely on data from several monitoring sites to predict the concentration of the panorama. Remote Sensing Technology retrieves aerosol concentrations being by virtue of their efficient, fast advantages gradually into sight. In this paper, by the method of surface model to start with the physical processes of atmospheric transport, innovative aerosol concentration coefficient proposed to replace the traditional aerosol concentrations, pushed to a set of retrieval of aerosol concentration coefficient method, enabling fast and efficient Get accurate air pollution target area. At the same paper also monitoring data for PM2.5 in Beijing were analyzed from different angles, from the perspective of the data summarized in Beijing PM2.5 concentration of time, space, geographical distribution and concentration of PM2.5 and explored the relationship between aerosol concentration coefficient and concentration of PM2.5.

Aerosol and Surface Parameter Retrievals for a Multi-Angle, Multiband Spectrometer

NASA Technical Reports Server (NTRS)

Broderick, Daniel

2012-01-01

This software retrieves the surface and atmosphere parameters of multi-angle, multiband spectra. The synthetic spectra are generated by applying the modified Rahman-Pinty-Verstraete Bidirectional Reflectance Distribution Function (BRDF) model, and a single-scattering dominated atmosphere model to surface reflectance data from Multiangle Imaging SpectroRadiometer (MISR). The aerosol physical model uses a single scattering approximation using Rayleigh scattering molecules, and Henyey-Greenstein aerosols. The surface and atmosphere parameters of the models are retrieved using the Lavenberg-Marquardt algorithm. The software can retrieve the surface and atmosphere parameters with two different scales. The surface parameters are retrieved pixel-by-pixel while the atmosphere parameters are retrieved for a group of pixels where the same atmosphere model parameters are applied. This two-scale approach allows one to select the natural scale of the atmosphere properties relative to surface properties. The software also takes advantage of an intelligent initial condition given by the solution of the neighbor pixels.

On the remote sensing of cloud properties from satellite infrared sounder data

NASA Technical Reports Server (NTRS)

Yeh, H. Y. M.

1984-01-01

A method for remote sensing of cloud parameters by using infrared sounder data has been developed on the basis of the parameterized infrared transfer equation applicable to cloudy atmospheres. The method is utilized for the retrieval of the cloud height, amount, and emissivity in 11 micro m region. Numerical analyses and retrieval experiments have been carried out by utilizing the synthetic sounder data for the theoretical study. The sensitivity of the numerical procedures to the measurement and instrument errors are also examined. The retrieved results are physically discussed and numerically compared with the model atmospheres. Comparisons reveal that the recovered cloud parameters agree reasonably well with the pre-assumed values. However, for cases when relatively thin clouds and/or small cloud fractional cover within a field of view are present, the recovered cloud parameters show considerable fluctuations. Experiments on the proposed algorithm are carried out utilizing High Resolution Infrared Sounder (HIRS/2) data of NOAA 6 and TIROS-N. Results of experiments show reasonably good comparisons with the surface reports and GOES satellite images.

Wind Retrievals under Rain for Passive Satellite Microwave Radiometers and its Applications to Hurricane Tracking

NASA Technical Reports Server (NTRS)

Meissner, Thomas; Wentz, Frank J.

2008-01-01

We have developed an algorithm that retrieves wind speed under rain using C-hand and X-band channels of passive microwave satellite radiometers. The spectral difference of the brightness temperature signals due to wind or rain allows to find channel combinations that are sufficiently sensitive to wind speed but little or not sensitive to rain. We &ve trained a statistical algorithm that applies under hurricane conditions and is able to measure wind speeds in hurricanes to an estimated accuracy of about 2 m/s. We have also developed a global algorithm, that is less accurate but can be applied under all conditions. Its estimated accuracy is between 2 and 5 mls, depending on wind speed and rain rate. We also extend the wind speed region in our model for the wind induced sea surface emissivity from currently 20 m/s to 40 mls. The data indicate that the signal starts to saturate above 30 mls. Finally, we make an assessment of the performance of wind direction retrievals from polarimetric radiometers as function of wind speed and rain rate

Global inter-comparison of microwave and infrared LST from multiple sensors (AMSR-E, MODIS, SEVIRI, GOES, and MTSAT-2)

NASA Astrophysics Data System (ADS)

Ermida, Sofia L.; Jiménez, Carlos; Prigent, Catherine; Trigo, Isabel F.; DaCamara, Carlos C.

2017-04-01

Land Surface Temperature (LST) is an important diagnostic parameter of land surface conditions. Satellite LST products generally rely on measurements in the thermal infrared (IR) atmospheric window, which only allows clear sky estimates. Microwave (MW) observations can alternatively be used to derive an all-weather LST. Here we present an inter-comparison between LST derived from the Advanced Microwave Scanning Radiometer - Earth observation system (AMSR-E), the MODerate resolution Imaging Spectroradiometer (MODIS) on-board Aqua, the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on-board Meteosat Second Generation (MSG) satellites, the Geostationary Operational Environmental Satellite (GOES) and the Japanese Meteorological Imager (JAMI) on-board the Multifunction Transport SATellite (MTSAT-2). The higher discrepancies between MW and IR products are observed over snow covered areas. MW emissivity is highly variable for snow-covered ground and not always properly accounted for by the climatological emissivity used in the retrieval. There is a conspicuous bias between MODIS and AMSR-E over desert areas, which is most likely related to the underestimation of LST by MODIS as previously reported in other studies. Inter-comparison between all IR and MW retrievals shows that the STD of the differences between MW and IR LST is generally higher than between IR retrievals. However, the biases between MW and IR LST are, in some cases, of the same order as the ones observed among infrared products. In particular, GOES presents a daytime bias with respect to AMSR-E of 0.45 K whereas the bias with respect to MODIS is 0.60 K. Given that AMSR-E can provide LST under cloudy conditions, the use of microwaves, considering simultaneous overpasses with IR, represents an increase of more than 250% of the number of available LST estimates over equatorial regions. With the MW products of a comparable quality to the IR ones, the MW LST is a very powerful complement of the IR estimates.

Spatio-temporal PM and AOD estimations over Northeast Asia during DRAGON NE-Asia campaign

NASA Astrophysics Data System (ADS)

Park, M.; Song, C.; Kim, J.

2013-12-01

Particulate matter (PM) is closely related to human health, air quality, and climate changes. It has been directly measured on the surface level. However, ground-based measurements have a limitation in spatial coverage of PM concentrations. In order to overcome this spatial limitation of ground measurements, AOD, which is considered as a proxy to PM concentration, was used in this study. AOD was first utilized to figure out the characteristics of PM and was then used to estimate the PM concentrations in Northeast Asia during the DRAGON Northeast-Asia campaign (March-May 2012), using CMAQ-estimated AOD, COMS/GOCI-retrieved AOD, and the AOD data from the DRAGON NE-Asia campaign. First of all, current emission inventories (MEIC and INTEX-B based emission inventories) were evaluated to improve CMAQ modeling results. Next, several algorithms to convert aerosol composition to AOD were evaluated using intensive measurement data from the DRAGON NE-Asia campaign. The accuracy of the CMAQ-estimated AOD was further evaluated with hourly observing GOCI-retrieved AOD. After the evaluation, CMAQ-calculated AOD was mathematically combined with GOCI-retrieved AOD via data assimilation. After this, AERONET AOD measured by the DRAGON NE-Asia campaign was again combined with the assimilated AOD from CMAQ and GOCI AODs to produce more accurate spatio-temporal AOD fields over Northeast Asia. Using several relationships between PM (PM10 and PM2.5) and AOD, the best surface-PM concentrations over the entire domain were calculated. It was then evaluated with ground-based PM2.5 measurements from the DRAGON NE-Asia campaign. A good agreement between estimated PM2.5 and measured PM2.5 over the domain was found. Finally, the PM and AOD information was used to investigate the effects of transboundary PM pollution from China to the Korean peninsula.

Analyzing land surface temperature variations during Fogo Island (Cape Verde) 2014-2015 eruption with Landsat 8 images

NASA Astrophysics Data System (ADS)

Vieira, D.; Teodoro, A.; Gomes, A.

2016-10-01

Land Surface Temperature (LST) is an important parameter related to land surface processes that changes continuously through time. Assessing its dynamics during a volcanic eruption has both environmental and socio-economical interest. Lava flows and other volcanic materials produced and deposited throughout an eruption transform the landscape, contributing to its heterogeneity and altering LST measurements. This paper aims to assess variations of satellite-derived LST and to detect patterns during the latest Fogo Island (Cape Verde) eruption, extending from November 2014 through February 2015. LST data was obtained through four processed Landsat 8 images, focused on the caldera where Pico do Fogo volcano sits. QGIS' plugin Semi-Automatic Classification was used in order to apply atmospheric corrections and radiometric calibrations. The algorithm used to retrieve LST values is a single-channel method, in which emissivity values are known. The absence of in situ measurements is compensated by the use of MODIS sensor-derived LST data, used to compare with Landsat retrieved measurements. LST data analysis shows as expected that the highest LST values are located inside the caldera. High temperature values were also founded on the south-facing flank of the caldera. Although spatial patterns observed on the retrieved data remained roughly the same during the time period considered, temperature values changed throughout the area and over time, as it was also expected. LST values followed the eruption dynamic experiencing a growth followed by a decline. Moreover, it seems possible to recognize areas affected by lava flows of previous eruptions, due to well-defined LST spatial patterns.

High-resolution fluorescence imaging for red and far-red SIF retrieval at leaf and canopy scales

NASA Astrophysics Data System (ADS)

Albert, L.; Alonso, L.; Cushman, K.; Kellner, J. R.

2017-12-01

New commercial-off-the-shelf imaging spectrometers promise the combination of high spatial and spectral resolution needed to retrieve solar induced fluorescence (SIF) at multiple wavelengths for individual plants and even individual leaves from low-altitude airborne or ground-based platforms. Data from these instruments could provide insight into the status of the photosynthetic apparatus at scales of space and time not observable from high-altitude and space-based platforms, and could support calibration and validation activities of current and forthcoming space missions to quantify SIF (OCO-2, OCO-3, FLEX, and GEOCARB). High-spectral resolution enables SIF retrieval from regions of strong telluric absorption by molecular oxygen, and also within numerous solar Fraunhofer lines in atmospheric windows not obscured by oxygen or water absorptions. Here we evaluate algorithms for SIF retrieval using a commercial-off-the-shelf diffraction-grating imaging spectrometer with a spectral sampling interval of 0.05 nm and a FWHM < 0.2 nm throughout the 670 - 780 nm range. We demonstrate the tradeoffs between spatial resolution and signal-to-noise ratio using frame stacking and binning, and evaluate the consequences of these tradeoffs for SIF retrieval using three approaches: (1) oxygen-A and B retrieval; (2) retrieval based exclusively on solar Fraunhofer lines outside regions of telluric gas absorption; and (3) a retrieval based on the combination of these approaches. We evaluate the quality of these methods by comparison with coincident SIF spectra of leaves measured using a hand-held field spectrometer and short-pass filters that block incoming light at wavelengths > 650 or 700 nm. These filters enable a direct measurement of SIF emission > 650 or 700 nm that serves as a benchmark against which retrievals from reflectance spectra can be evaluated. We repeated this comparison between leaf-level SIF emission spectra and retrieved SIF emission spectra for leaves treated with drought stress and an herbicide (DCMU) that inhibits electron transfer from QA to QB of PSII.

Inverse modelling estimates of N2O surface emissions and stratospheric losses using a global dataset

NASA Astrophysics Data System (ADS)

Thompson, R. L.; Bousquet, P.; Chevallier, F.; Dlugokencky, E. J.; Vermeulen, A. T.; Aalto, T.; Haszpra, L.; Meinhardt, F.; O'Doherty, S.; Moncrieff, J. B.; Popa, M.; Steinbacher, M.; Jordan, A.; Schuck, T. J.; Brenninkmeijer, C. A.; Wofsy, S. C.; Kort, E. A.

2010-12-01

Nitrous oxide (N2O) levels have been steadily increasing in the atmosphere over the past few decades at a rate of approximately 0.3% per year. This trend is of major concern as N2O is both a long-lived Greenhouse Gas (GHG) and an Ozone Depleting Substance (ODS), as it is a precursor of NO and NO2, which catalytically destroy ozone in the stratosphere. Recently, N2O emissions have been recognised as the most important ODS emissions and are now of greater importance than emissions of CFC's. The growth in atmospheric N2O is predominantly due to the enhancement of surface emissions by human activities. Most notably, the intensification and proliferation of agriculture since the mid-19th century, which has been accompanied by the increased input of reactive nitrogen to soils and has resulted in significant perturbations to the natural N-cycle and emissions of N2O. There exist two approaches for estimating N2O emissions, the so-called 'bottom-up' and 'top-down' approaches. Top-down approaches, based on the inversion of atmospheric measurements, require an estimate of the loss of N2O via photolysis and oxidation in the stratosphere. Uncertainties in the loss magnitude contribute uncertainties of 15 to 20% to the global annual surface emissions, complicating direct comparisons between bottom-up and top-down estimates. In this study, we present a novel inversion framework for the simultaneous optimization of N2O surface emissions and the magnitude of the loss, which avoids errors in the emissions due to incorrect assumptions about the lifetime of N2O. We use a Bayesian inversion with a variational formulation (based on 4D-Var) in order to handle very large datasets. N2O fluxes are retrieved at 4-weekly resolution over a global domain with a spatial resolution of 3.75° x 2.5° longitude by latitude. The efficacy of the simultaneous optimization of emissions and losses is tested using a global synthetic dataset, which mimics the available atmospheric data. Lastly, using real atmospheric data from the networks of NOAA, AGAGE, and CHIOTTO, and additionally aircraft data from the CARIBIC and NOAA programmes and the START campaign, we infer N2O emissions for the years 2006 to 2008. We find large N2O emissions in the tropics, namely in tropical south-east Asia, America and Africa, with notable emissions also in Europe and south Asia.

Space based inverse modeling of seasonal variations of anthropogenic and natural emissions of nitrogen oxides over China and effects of uncertainties in model meteorology and chemistry

NASA Astrophysics Data System (ADS)

Lin, J.

2011-12-01

Nitrogen oxides (NOx ≡ NO + NO2) are important atmospheric constituents affecting the tropospheric chemistry, surface air quality and climatic forcing. They are emitted both from anthropogenic and from natural (soil, lightning, biomass burning, etc.) sources, which can be estimated inversely from satellite remote sensing of the vertical column densities (VCDs) of nitrogen dioxide (NO2) in the troposphere. Based on VCDs of NO2 retrieved from OMI, a novel approach is developed in this study to separate anthropogenic emissions of NOx from natural sources over East China for 2006. It exploits the fact that anthropogenic and natural emissions vary with seasons with distinctive patterns. The global chemical transport model (CTM) GEOS-Chem is used to establish the relationship between VCDs of NO2 and emissions of NOx for individual sources. Derived soil emissions are compared to results from a newly developed bottom-up approach. Effects of uncertainties in model meteorology and chemistry over China, an important source of errors in the emission inversion, are evaluated systematically for the first time. Meteorological measurements from space and the ground are used to analyze errors in meteorological parameters driving the CTM.

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.

Ground and satellite-based remote sensing of mineral dust using AERI spectra and MODIS thermal infrared window brightness temperatures

NASA Astrophysics Data System (ADS)

Hansell, Richard Allen, Jr.

The radiative effects of dust aerosol on our climate system have yet to be fully understood and remain a topic of contemporary research. To investigate these effects, detection/retrieval methods for dust events over major dust outbreak and transport areas have been developed using satellite and ground-based approaches. To this end, both the shortwave and longwave surface radiative forcing of dust aerosol were investigated. The ground-based remote sensing approach uses the Atmospheric Emitted Radiance Interferometer brightness temperature spectra to detect mineral dust events and to retrieve their properties. Taking advantage of the high spectral resolution of the AERI instrument, absorptive differences in prescribed thermal IR window sub-band channels were exploited to differentiate dust from cirrus clouds. AERI data collected during the UAE2 at Al-Ain UAE was employed for dust retrieval. Assuming a specified dust composition model a priori and using the light scattering programs of T-matrix and the finite difference time domain methods for oblate spheroids and hexagonal plates, respectively, dust optical depths have been retrieved and compared to those inferred from a collocated and coincident AERONET sun-photometer dataset. The retrieved optical depths were then used to determine the dust longwave surface forcing during the UAE2. Likewise, dust shortwave surface forcing is investigated employing a differential technique from previous field studies. The satellite-based approach uses MODIS thermal infrared brightness temperature window data for the simultaneous detection/separation of mineral dust and cirrus clouds. Based on the spectral variability of dust emissivity at the 3.75, 8.6, 11 and 12 mum wavelengths, the D*-parameter, BTD-slope and BTD3-11 tests are combined to identify dust and cirrus. MODIS data for the three dust-laden scenes have been analyzed to demonstrate the effectiveness of this detection/separation method. Detected daytime dust and cloud coverage for the Persian Gulf case compare reasonably well to those from the "Deep Blue" algorithm developed at NASA-GSFC. The nighttime dust/cloud detection for the cases surrounding Cape Verde and Niger, West Africa has been validated by comparing to coincident and collocated ground-based micro-pulse lidar measurements.

Arctic Methane: the View from Space

NASA Astrophysics Data System (ADS)

Leifer, I.; Yurganov, L.; Xiong, X.

2014-12-01

Global increase of methane that started in 2007-2008 after a decade of stability requires investigation and explanation. Recent Arctic warming has stimulated speculation about dissociation of Arctic Ocean methane hydrates providing a potentially important new climatic positive feedback. Satellite thermal infrared (TIR) data do not require sunlight, providing key advantages for Arctic data collection compared to shortwave infrared spectroscopy. The US Atmospheric IR Sounder (AIRS) has been delivering CH4 tropospheric data since 2002; NOAA CH4 retrievals from the European Infrared Atmospheric Sounding Interferometer (IASI) radiation data are available since 2008 and analyzed here since 2009. Accuracy of TIR satellite retrievals, especially for the lower troposphere, diminishes for a cold, underlying surface. In this analysis the dependence is parameterized using the Thermal Contrast (a difference between surface temperature and air temperature at the altitude of 4 km, defined THC). A correction function was applied to CH4 data based on a data-derived relationship between THC and retrieved CH4 for areas with positive THC (in other words, without temperature inversions). The seasonal cycles of the adjusted low tropospheric data are in agreement with the surface in situ measurements. Instantaneous IASI retrievals exhibit less variability than AIRS v6 data. Maximum positive deviation of methane concentration measured by IASI for the study period was found for Baffin Bay in November-December, 2013 (Figure). It was concluded that the methane anomaly could indicate both coastal and off-shore emissions. Off-shore data were spatially consistent with a hydrate dissociation mechanisms, active for water depths below the hydrate stability zone top at ~300 m. These are hypothesized to dissociate during seasonal temperature maximum in the bottom layer of the ocean, which occurs in fall. IASI data may be considered as a reliable source of information about Arctic CH4 for conditions of sufficiently high atmospheric vertical thermal contrast. Figure caption. Standard adjusted NOAA/IASI retrievals of 0-4 km mean methane concentration over areas with positive THC. Black points are for the entire Baffin Bay, red points are for locations with seawater depth below 300 m. Blue line is the all-Arctic mean.

Retrieval of background surface reflectance with BRD components from pre-running BRDF

NASA Astrophysics Data System (ADS)

Choi, Sungwon; Lee, Kyeong-Sang; Jin, Donghyun; Lee, Darae; Han, Kyung-Soo

2016-10-01

Many countries try to launch satellite to observe the Earth surface. As important of surface remote sensing is increased, the reflectance of surface is a core parameter of the ground climate. But observing the reflectance of surface by satellite have weakness such as temporal resolution and being affected by view or solar angles. The bidirectional effects of the surface reflectance may make many noises to the time series. These noises can lead to make errors when determining surface reflectance. To correct bidirectional error of surface reflectance, using correction model for normalized the sensor data is necessary. A Bidirectional Reflectance Distribution Function (BRDF) is making accuracy higher method to correct scattering (Isotropic scattering, Geometric scattering, Volumetric scattering). To correct bidirectional error of surface reflectance, BRDF was used in this study. To correct bidirectional error of surface reflectance, we apply Bidirectional Reflectance Distribution Function (BRDF) to retrieve surface reflectance. And we apply 2 steps for retrieving Background Surface Reflectance (BSR). The first step is retrieving Bidirectional Reflectance Distribution (BRD) coefficients. Before retrieving BSR, we did pre-running BRDF to retrieve BRD coefficients to correct scatterings (Isotropic scattering, Geometric scattering, Volumetric scattering). In pre-running BRDF, we apply BRDF with observed surface reflectance of SPOT/VEGETATION (VGT-S1) and angular data to get BRD coefficients for calculating scattering. After that, we apply BRDF again in the opposite direction with BRD coefficients and angular data to retrieve BSR as a second step. As a result, BSR has very similar reflectance to one of VGT-S1. And reflectance in BSR is shown adequate. The highest reflectance of BSR is not over 0.4μm in blue channel, 0.45μm in red channel, 0.55μm in NIR channel. And for validation we compare reflectance of clear sky pixel from SPOT/VGT status map data. As a result of comparing BSR with VGT-S1, bias is from 0.0116 to 0.0158 and RMSE is from 0.0459 to 0.0545. They are very reasonable results, so we confirm that BSR is similar to VGT-S1. And weakness of this study is missing pixel in BSR which are observed less time to retrieve BRD components. If missing pixels are filled, BSR is better to retrieve surface products with more accuracy. And we think that after filling the missing pixel and being more accurate, it can be useful data to retrieve surface product which made by surface reflectance like cloud masking and retrieving aerosol.

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.

Constraining methane emissions from the Indo-Gangetic Plains and South Asia using combined surface and satellite data

NASA Astrophysics Data System (ADS)

Ganesan, A.; Lunt, M. F.; Rigby, M. L.; Chatterjee, A.; Boesch, H.; Parker, R.; Prinn, R. G.; van der Schoot, M. V.; Krummel, P. B.; Tiwari, Y. K.; Mukai, H.; Machida, T.; Terao, Y.; Nomura, S.; Patra, P. K.

2015-12-01

We present an analysis of the regional methane (CH4) budget from South Asia, using new measurements and new modelling techniques. South Asia contains some of the largest anthropogenic CH4 sources in the world, mainly from rice agriculture and ruminants. However, emissions from this region have been highly uncertain largely due to insufficient constraints from atmospheric measurements. Compared to parts of the developed world, which have well-developed monitoring networks, South Asia is very under-sampled, particularly given its importance to the global CH4 budget. Over the past few years, data have been collected from a variety of surface sites around the region, ranging from in situ to flask-based sampling. We have used these data, in conjunction with column methane data from the GOSAT satellite, to quantify emissions at a regional scale. Using the Met Office's Lagrangian NAME model, we calculated sensitivities to surface fluxes at 12 km resolution, allowing us to simulate the high-resolution impacts of emissions on concentrations. In addition, we used a newly developed hierarchical Bayesian inverse estimation scheme to estimate regional fluxes over the period of 2012-2014 in addition to ancillary "hyper-parameters" that characterize uncertainties in the system. Through this novel approach, we have characterized the effect of "aggregation" errors, model uncertainties as well as the effects of correlated errors when using regional measurement networks. We have also assessed the effects of biases on the GOSAT CH4 retrievals, which has been made possible for the first time for this region through the expanded surface measurements. In this talk, we will discuss a) regional CH4 fluxes from South Asia, with a particular focus on the densely populated Indo-Gangetic Plains b) derived model uncertainties, including the effects of correlated errors c) the impacts of combining surface and satellite data for emissions estimation in regions where poor satellite validation exists and d) the challenges in estimating emissions for regions of the world with a sparse measurement network.

Validation of Land Surface Temperature from Sentinel-3

NASA Astrophysics Data System (ADS)

Ghent, D.

2017-12-01

One of the main objectives of the Sentinel-3 mission is to measure sea- and land-surface temperature with high-end accuracy and reliability in support of environmental and climate monitoring in an operational context. Calibration and validation are thus key criteria for operationalization within the framework of the Sentinel-3 Mission Performance Centre (S3MPC). Land surface temperature (LST) has a long heritage of satellite observations which have facilitated our understanding of land surface and climate change processes, such as desertification, urbanization, deforestation and land/atmosphere coupling. These observations have been acquired from a variety of satellite instruments on platforms in both low-earth orbit and in geostationary orbit. Retrieval accuracy can be a challenge though; surface emissivities can be highly variable owing to the heterogeneity of the land, and atmospheric effects caused by the presence of aerosols and by water vapour absorption can give a bias to the underlying LST. As such, a rigorous validation is critical in order to assess the quality of the data and the associated uncertainties. Validation of the level-2 SL_2_LST product, which became freely available on an operational basis from 5th July 2017 builds on an established validation protocol for satellite-based LST. This set of guidelines provides a standardized framework for structuring LST validation activities. The protocol introduces a four-pronged approach which can be summarised thus: i) in situ validation where ground-based observations are available; ii) radiance-based validation over sites that are homogeneous in emissivity; iii) intercomparison with retrievals from other satellite sensors; iv) time-series analysis to identify artefacts on an interannual time-scale. This multi-dimensional approach is a necessary requirement for assessing the performance of the LST algorithm for the Sea and Land Surface Temperature Radiometer (SLSTR) which is designed around biome-based coefficients, thus emphasizing the importance of non-traditional forms of validation such as radiance-based techniques. Here we present examples of the ongoing routine application of the protocol to operational Sentinel-3 LST data.

Analysis of uncertainties in GOSAT-inferred regional CO2 fluxes

NASA Astrophysics Data System (ADS)

Ishizawa, M.; Shirai, T.; Maksyutov, S. S.; Yoshida, Y.; Morino, I.; Inoue, M.; Nakatsuru, T.; Uchino, O.; Mabuchi, K.

2016-12-01

Satellite-based CO2 measurements have potential for improving our understanding global carbon cycle because of more spatiotemporal coverage than those from ground-based observations. Since the Greenhouse gases Observing Satellite (GOSAT) was launched in January 2009, it has been measuring the column-average dry air-mole function of CO2 (XCO2) from the space. To utilize the GOSAT XCO2 for better CO2 flux estimates, several challenges should be overcome. Systematic errors (biases) in XCO2 retrievals are a major factor which leads to large differences among inverted CO2 fluxes. Temporally variable data coverage and density are also taken into account when interpreting the estimated surface fluxes. In this study, we employ an atmospheric inverse model to investigate the impacts of retrievals biases and temporally varying global distribution of GOSAT XCO2 on surface CO2 flux estimates. Inversions are performed for 2009-2013, with several subsets of the 5-year record of GOSAT XCO2 (v2.21) and its bias-corrected XCO2. GOSAT XCO2 data consist of three types: H-gain for vegetated lands, M-gain for bright surfaces (desert areas), and sun-glint for ocean surface. The results show that the global spatial distributions of estimated CO2 fluxes depend on the subset of XCO2 used. M-gain XCO2 results in unrealistically high CO2 emissions in and around the Middle East, including the neighboring ocean regions. On the other hand, M-gain XCO2 causes compensating unrealistic uptakes far beyond M-gain regions in low latitudes, also partially contributing on the summer uptake in Europe. The joint inversions with both surface measurements and GOSAT XCO2 data obtain larger flux gradient between the northern extra-tropics and the tropics than the inversion with surface measurements only for the first 2 years. Recently, these North-South gradients seem to be gradually reducing as the tropics become a weaker source or turn into a sink, while the net emission strength in East Asia is increasing. The 5-year XCO2 data allows us detailed analysis of uncertainties in GOSAT-inferred fluxes and assessment of GOSAT XCO2 biases.

Why is SMOS Drier than the South Fork In-situ Soil Moisture Network?

NASA Astrophysics Data System (ADS)

Walker, V. A.; Hornbuckle, B. K.; Cosh, M. H.

2014-12-01

Global maps of near-surface soil moisture are currently being produced by the European Space Agency's Soil Moisture and Ocean Salinity (SMOS) satellite mission at 40 km. Within the next few months NASA's Soil Moisture Active Passive (SMAP) satellite mission will begin producing observations of near-surface soil moisture at 10 km. Near-surface soil moisture is the water content of the first 3 to 5 cm of the soil. Observations of near-surface soil moisture are expected to improve weather and climate forecasts. These satellite observations must be validated. We define validation as determining the space/time statistical characteristics of the uncertainty. A standard that has been used for satellite validation is in-situ measurements of near-surface soil moisture made with a network of sensors spanning the extent of a satellite footprint. Such a network of sensors has been established in the South Fork of the Iowa River in Central Iowa by the USDA ARS. Our analysis of data in 2013 indicates that SMOS has a dry bias: SMOS near-surface soil moisture is between 0.05 to 0.10 m^3m^{-3} lower than what is observed by the South Fork network. A dry bias in SMOS observations has also been observed in other regions of North America. There are many possible explanations for this difference: underestimation of vegetation, or soil surface roughness; undetected radio frequency interference (RFI); a retrieval model that is not appropriate for agricultural areas; or the use of an incorrect surface temperature in the retrieval process. We will begin our investigation by testing this last possibility: that SMOS is using a surface temperature that is too low which results in a drier soil moisture that compensates for this error. We will present a comparison of surface temperatures from the European Center for Medium-range Weather Forecasting (ECMWF) used to retrieve near-surface soil moisture from SMOS measurements of brightness temperature, and surface temperatures in the South Fork obtained from both tower and in-situ sensors. We will also use a long-term data set of tower and in-situ sensors collected in agricultural fields to develop a relationship between air temperature and the surface temperature relevant to the terrestrial microwave emission that is detected by SMOS.

Daytime Land Surface Temperature Extraction from MODIS Thermal Infrared Data under Cirrus Clouds

PubMed Central

Fan, Xiwei; Tang, Bo-Hui; Wu, Hua; Yan, Guangjian; Li, Zhao-Liang

2015-01-01

Simulated data showed that cirrus clouds could lead to a maximum land surface temperature (LST) retrieval error of 11.0 K when using the generalized split-window (GSW) algorithm with a cirrus optical depth (COD) at 0.55 μm of 0.4 and in nadir view. A correction term in the COD linear function was added to the GSW algorithm to extend the GSW algorithm to cirrus cloudy conditions. The COD was acquired by a look up table of the isolated cirrus bidirectional reflectance at 0.55 μm. Additionally, the slope k of the linear function was expressed as a multiple linear model of the top of the atmospheric brightness temperatures of MODIS channels 31–34 and as the difference between split-window channel emissivities. The simulated data showed that the LST error could be reduced from 11.0 to 2.2 K. The sensitivity analysis indicated that the total errors from all the uncertainties of input parameters, extension algorithm accuracy, and GSW algorithm accuracy were less than 2.5 K in nadir view. Finally, the Great Lakes surface water temperatures measured by buoys showed that the retrieval accuracy of the GSW algorithm was improved by at least 1.5 K using the proposed extension algorithm for cirrus skies. PMID:25928059

Multispectral pyrometry for surface temperature measurement of oxidized Zircaloy claddings

NASA Astrophysics Data System (ADS)

Bouvry, B.; Cheymol, G.; Ramiandrisoa, L.; Javaudin, B.; Gallou, C.; Maskrot, H.; Horny, N.; Duvaut, T.; Destouches, C.; Ferry, L.; Gonnier, C.

2017-06-01

Non-contact temperature measurement in a nuclear reactor is still a huge challenge because of the numerous constraints to consider, such as the high temperature, the steam atmosphere, and irradiation. A device is currently developed at CEA to study the nuclear fuel claddings behavior during a Loss-of-Coolant Accident. As a first step of development, we designed and tested an optical pyrometry procedure to measure the surface temperature of nuclear fuel claddings without any contact, under air, in the temperature range 700-850 °C. The temperature of Zircaloy-4 cladding samples was retrieved at various temperature levels. We used Multispectral Radiation Thermometry with the hypothesis of a constant emissivity profile in the spectral ranges 1-1.3 μm and 1.45-1.6 μm. To allow for comparisons, a reference temperature was provided by a thermocouple welded on the cladding surface. Because of thermal losses induced by the presence of the thermocouple, a heat transfer simulation was also performed to estimate the bias. We found a good agreement between the pyrometry measurement and the temperature reference, validating the constant emissivity profile hypothesis used in the MRT estimation. The expanded measurement uncertainty (k = 2) of the temperature obtained by the pyrometry method was ±4 °C, for temperatures between 700 and 850 °C. Emissivity values, between 0.86 and 0.91 were obtained.

Surface reflectance retrieval from imaging spectrometer data using three atmospheric codes

NASA Astrophysics Data System (ADS)

Staenz, Karl; Williams, Daniel J.; Fedosejevs, Gunar; Teillet, Phil M.

1994-12-01

Surface reflectance retrieval from imaging spectrometer data has become important for quantitative information extraction in many application areas. In order to calculate surface reflectance from remotely measured radiance, radiative transfer codes play an important role for removal of the scattering and gaseous absorption effects of the atmosphere. The present study evaluates surface reflectances retrieved from airborne visible/infrared imaging spectrometer (AVIRIS) data using three radiative transfer codes: modified 5S (M5S), 6S, and MODTRAN2. Comparisons of the retrieved surface reflectance with ground-based reflectance were made for different target types such as asphalt, gravel, grass/soil mixture (soccer field), and water (Sooke Lake). The results indicate that the estimation of the atmospheric water vapor content is important for an accurate surface reflectance retrieval regardless of the radiative transfer code used. For the present atmospheric conditions, a difference of 0.1 in aerosol optical depth had little impact on the retrieved surface reflectance. The performance of MODTRAN2 is superior in the gas absorption regions compared to M5S and 6S.

Quantifying emissions of CO and NOx using observations from MOPITT, OMI, TES, and OSIRIS

NASA Astrophysics Data System (ADS)

Zhang, X.; Jones, D. B. A.; Keller, M.; Walker, T. W.; Jiang, Z.; Henze, D. K.; Bourassa, A. E.; Degenstein, D. A.; Rochon, Y. J.

2016-12-01

We use the GEOS-Chem four-dimensional variational (4D-var) data assimilation with satellite observations of multiple chemical species to estimate emissions of CO and NOx, as well as the tropospheric concentrations of O3. In doing so, we utilize CO retrievals from The Measurements of Pollution In The Troposphere (MOPITT), O3 retrievals from the Tropospheric Emission Spectrometer (TES), O3 retrievals from the Optical Spectrograph and InfraRed Imager System (OSIRIS), and NO2 columns from the Ozone Monitoring Instrument (OMI). By integrating these data in the 4D-Var scheme, we obtain a chemical state in the model that is consistent with all of the data over the assimilation period. In this context, for example, we find that combining TES and OSIRIS improves O3, particularly in the tropical upper troposphere (by 10-20%), which leads to a reduction in the uncertainty of the NOx emission estimates. However, although assimilating multiple chemical species provides a stronger constraint on the chemical, state, there are still large uncertainties on the CO and NOx emission estimates, due to the dependence of the results on the selection of the assimilation window and how the datasets are weighted in the cost function.

GHGSat-D: Greenhouse gas plume imaging and quantification from space using a Fabry-Perot imaging spectrometer

NASA Astrophysics Data System (ADS)

McKeever, J.; Durak, B. O. A.; Gains, D.; Jervis, D.; Varon, D. J.; Germain, S.; Sloan, J. J.

2017-12-01

GHGSat, Inc. has launched the first satellite designed to detect and quantify greenhouse gas emissions from individual industrial sites. Our demonstration satellite GHGSat-D or "CLAIRE" was launched in June 2016. It weighs less than 15 kg and its primary instrument is a miniaturized Fabry-Perot imaging spectrometer with spectral resolution on the order of 0.1 nm. The spectral bandpass is 1635-1670 nm, giving the instrument access to absorption bands of both CO2 and CH4. Our system is based on targeted observations rather than global coverage, and our spatial imaging resolution is a key differentiator. Specifically, with a ground sampling distance of <50 m within a 12 km field of view, we are able to spatially resolve the increased column densities associated with individual emission plumes. For a given emission rate and wind speed the magnitude of the local excess column increases approximately linearly as pixel resolution decreases. Consequently, at GHGSat's resolution the total column can exceed local background by well over 10% for many industrial sites with strong but realistic emission rates. GHGSat uses a novel measurement and retrievals concept where the emitter site of interest is captured in a sequence of 150-200 overlapping two-dimensional images. The combined effect of the Fabry-Perot resonator and the scrolling scene gives a different spectral sampling of each surface location in every image. While our data processing toolchain does not produce a conventional hyperspectral dataset, it does yield a spectral decomposition of the spatially resolved signal that is compared to a model that includes atmospheric radiative transfer and the instrument's pixel-dependent spectral responsivity. Our presentation will describe the instrument design, concept of operations and retrievals approach. We will also present images and results from GHGSat-D at different processing levels, including high-resolution column density retrievals. An observation of the degassing flux of methane from the outlet of a recently impounded hydroelectric reservoir will be shown as an example. Finally we discuss some performance limitations of GHGSat-D and our plans to overcome them as we update the instrument design for the next satellites.

Use of In Situ Cloud Condensation Nuclei, Extinction, and Aerosol Size Distribution Measurements to Test a Method for Retrieving Cloud Condensation Nuclei Profiles From Surface Measurements

NASA Technical Reports Server (NTRS)

Ghan, Stephen J.; Rissman, Tracey A.; Ellman, Robert; Ferrare, Richard A.; Turner, David; Flynn, Connor; Wang, Jian; Ogren, John; Hudson, James; Jonsson, Haflidi H.;

Retrieval of daytime [O3] altitude profile from measurements of 1.27 μm O2 emission in the mesosphere: a comparison of methods

NASA Astrophysics Data System (ADS)

Yankovsky, Valentine A.; Manuilova, Rada O.

2017-11-01

The altitude profiles of ozone concentration are retrieved from measurements of the volume emission rate in the 1.27 μm oxygen band in the TIMED-SABER experiment. In this study we compare the methods of retrieval of daytime [O3] altitude profile in the framework of two models: electronic-vibrational kinetics and a purely electronic kinetics of excited products of ozone and oxygen photolysis. In order to retrieve the [O3] altitude profile from the measurements of the intensity of the O2 band in the region of 1.27 μm correctly, it is necessary to use the photochemical model of the electronic-vibrational kinetics of excited products of ozone and oxygen photolysis in the mesosphere and lower thermosphere.

Retrieval of reflections from ambient noise using illumination diagnosis

NASA Astrophysics Data System (ADS)

Vidal, C. Almagro; Draganov, D.; van der Neut, J.; Drijkoningen, G.; Wapenaar, K.

2014-09-01

Seismic interferometry (SI) enables the retrieval of virtual sources at the location of receivers. In the case of passive SI, no active sources are used for the retrieval of the reflection response of the subsurface, but ambient-noise recordings only. The resulting retrieved response is determined by the illumination characteristics of the recorded ambient noise. Characteristics like geometrical distribution and signature of the noise sources, together with the complexity of the medium and the length of the noise records, determine the quality of the retrieved virtual-shot events. To retrieve body wave reflections, one needs to correlate body-wave noise. A source of such noise might be regional seismicity. In regions with notable human presence, the dominant noise sources are generally located at or close to the surface. In the latter case, the noise will be dominated by surface waves and consequently also the retrieved virtual common-source panels will contain dominant retrieved surface waves, drowning out possible retrieved reflections. In order to retrieve reflection events, suppression of the surface waves becomes the most important pre-processing goal. Because of the reasons mentioned above, we propose a fast method to evaluate the illumination characteristics of ambient noise using the correlation results from ambient-noise records. The method is based on the analysis of the so-called source function of the retrieved virtual-shot panel, and evaluates the apparent slowness of arrivals in the correlation results that pass through the position of the virtual source and at zero time. The results of the diagnosis are used to suppress the retrieval of surface waves and therefore to improve the quality of the retrieved reflection response. We explain the approach using modelled data from transient and continuous noise sources and an example from a passive field data set recorded at Annerveen, Northern Netherlands.

Comparison of Different Global Information Sources Used in Surface Radiative Flux Calculation: Radiative Properties of the Surface

NASA Technical Reports Server (NTRS)

Zhang, Yuanchong; Rossow, William B.; Stackhouse, Paul W., Jr.

2007-01-01

Direct estimates of surface radiative fluxes that resolve regional and weather-scale variabilty over the whole globe with reasonable accuracy have only become possible with the advent of extensive global, mostly satellite, datasets within the past couple of decades. The accuracy of these fluxes, estimated to be about 10-15 W per square meter is largely limited by the accuracy of the input datasets. The leading uncertainties in the surface fluxes are no longer predominantly induced by clouds but are now as much associated with uncertainties in the surface and near-surface atmospheric properties. This study presents a fuller, more quantitative evaluation of the uncertainties for the surface albedo and emissivity and surface skin temperatures by comparing the main available global datasets from the Moderate-Resolution Imaging Spectroradiometer product, the NASA Global Energy and Water Cycle Experiment Surface Radiation Budget project, the European Centre for Medium-Range Weather Forecasts, the National Aeronautics and Space Administration, the National Centers for Environmental Prediction, the International Satellite Cloud Climatology Project (ISCCP), the Laboratoire de Meteorologie Dynamique, NOAA/NASA Pathfinder Advanced Very High Resolution Radiometer project, NOAA Optimum Interpolation Sea Surface Temperature Analysis and the Tropical Rainfall Measuring Mission (TRMM) Microwave Image project. The datasets are, in practice, treated as an ensemble of realizations of the actual climate such that their differences represent an estimate of the uncertainty in their measurements because we do not possess global truth datasets for these quantities. The results are globally representative and may be taken as a generalization of our previous ISCCP-based uncertainty estimates for the input datasets. Surface properties have the primary role in determining the surface upward shortwave (SW) and longwave (LW) flux. From this study, the following conclusions are obtained. Although land surface albedos in the near near-infrared remain poorly constrained (highly uncertain), they do not cause too much error in total surface SW fluxes; the more subtle regional and seasonal variations associated with vegetation and snow are still on doubt. The uncertainty of the broadband black-sky SW albedo for land surface from this study is about 7%, which can easily induce 5-10 W per square meter uncertainty in (upwelling) surface SW flux estimates. Even though available surface (broadband) LW emissivity datasets differ significantly (3%-5% uncertainty), this disagreement is confined to wavelengths greater than 20 micrometers so that there is little practical effect (1-3 W per square meters) on the surface upwelling LW fluxes. The surface skin temperature is one of two leading factors that cause problems with surface LW fluxes. Even though the differences among the various datasets are generally only 2-4 K, this can easily cause 10-15 W per square meter uncertainty in calculated surface (upwelling) LW fluxes. Significant improvements could be obtained for surface LW flux calculations by improving the retrievals of (in order of decreasing importance): (1) surface skin temperature, (2) surface air and near-surface-layer temperature, (3) column precipitable water amount and (4) broadband emissivity. And for surface SW fluxes, improvements could be obtained (excluding improved cloud treatment) by improving the retrievals of (1) aerosols (from our sensitivity studies but not discussed in this work), and (2) surface (black-sky) albedo, of which, NIR part of the spectrum has much larger uncertainty.

Evaluation of a new inference method for estimating ammonia volatilisation from multiple agronomic plots

NASA Astrophysics Data System (ADS)

Loubet, Benjamin; Carozzi, Marco; Voylokov, Polina; Cohan, Jean-Pierre; Trochard, Robert; Génermont, Sophie

2018-06-01

Tropospheric ammonia (NH3) is a threat to the environment and human health and is mainly emitted by agriculture. Ammonia volatilisation following application of nitrogen in the field accounts for more than 40 % of the total NH3 emissions in France. This represents a major loss of nitrogen use efficiency which needs to be reduced by appropriate agricultural practices. In this study we evaluate a novel method to infer NH3 volatilisation from small agronomic plots consisting of multiple treatments with repetition. The method is based on the combination of a set of NH3 diffusion sensors exposed for durations of 3 h to 1 week and a short-range atmospheric dispersion model, used to retrieve the emissions from each plot. The method is evaluated by mimicking NH3 emissions from an ensemble of nine plots with a resistance analogue-compensation point-surface exchange scheme over a yearly meteorological database separated into 28-day periods. A multifactorial simulation scheme is used to test the effects of sensor numbers and heights, plot dimensions, source strengths, and background concentrations on the quality of the inference method. We further demonstrate by theoretical considerations in the case of an isolated plot that inferring emissions with diffusion sensors integrating over daily periods will always lead to underestimations due to correlations between emissions and atmospheric transfer. We evaluated these underestimations as -8 % ± 6 % of the emissions for a typical western European climate. For multiple plots, we find that this method would lead to median underestimations of -16 % with an interquartile [-8-22 %] for two treatments differing by a factor of up to 20 and a control treatment with no emissions. We further evaluate the methodology for varying background concentrations and NH3 emissions patterns and demonstrate the low sensitivity of the method to these factors. The method was also tested in a real case and proved to provide sound evaluations of NH3 losses from surface applied and incorporated slurry. We hence showed that this novel method should be robust and suitable for estimating NH3 emissions from agronomic plots. We believe that the method could be further improved by using Bayesian inference and inferring surface concentrations rather than surface fluxes. Validating against controlled source is also a remaining challenge.

Thermal Analysis of Unusual Local-scale Features on the Surface of Vesta

NASA Technical Reports Server (NTRS)

Tosi, F.; Capria, M. T.; DeSanctis, M. C.; Capaccioni, F.; Palomba, E.; Zambon, F.; Ammannito, E.; Blewett, D. T.; Combe, J.-Ph.; Denevi, B. W.;

Mars atmosphere studies with the SPICAM IR emission phase function observations

NASA Astrophysics Data System (ADS)

Trokhimovskiy, Alexander; Fedorova, Anna; Montmessin, Franck; Korablev, Oleg; Bertaux, Jean-Loup

Emission Phase Function (EPF) observations is a powerful tool for characterization of atmosphere and surface. EPF sequence provides the extensive coverage of scattering angles above the targeted surface location which allow to separate the surface and aerosol scattering, study a vertical distribution of minor species and aerosol properties. SPICAM IR instrument on Mars Express mission provides continuous atmospheric observations in near IR (1-1.7 mu) in nadir and limb starting from 2004. For the first years of SPICAM operation only a very limited number of EPFs was performed. But from the mid 2013 (Ls=225, MY31) SPICAM EPF observations become rather regular. Based on the multiple-scattering radiative transfer model SHDOM, we analyze equivalent depths of carbon dioxide (1,43 mu) and water vapour (1,38 mu) absorption bands and their dependence on airmass during observation sequence to get aerosol optical depths and properties. The derived seasonal dust opacities from near IR can be used to retrieve the size distribution from comparison with simultaneous results of other instruments in different spectral ranges. Moreover, the EPF observations of water vapour band allow to access poorly known H2O vertical distribution for different season and locations.

Quantifying the influence of agricultural fires in northwest India on urban air pollution in Delhi, India

NASA Astrophysics Data System (ADS)

Cusworth, Daniel H.; Mickley, Loretta J.; Sulprizio, Melissa P.; Liu, Tianjia; Marlier, Miriam E.; DeFries, Ruth S.; Guttikunda, Sarath K.; Gupta, Pawan

2018-04-01

Since at least the 1980s, many farmers in northwest India have switched to mechanized combine harvesting to boost efficiency. This harvesting technique leaves abundant crop residue on the fields, which farmers typically burn to prepare their fields for subsequent planting. A key question is to what extent the large quantity of smoke emitted by these fires contributes to the already severe pollution in Delhi and across other parts of the heavily populated Indo-Gangetic Plain located downwind of the fires. Using a combination of observed and modeled variables, including surface measurements of PM2.5, we quantify the magnitude of the influence of agricultural fire emissions on surface air pollution in Delhi. With surface measurements, we first derive the signal of regional PM2.5 enhancements (i.e. the pollution above an anthropogenic baseline) during each post-monsoon burning season for 2012–2016. We next use the Stochastic Time-Inverted Lagrangian Transport model (STILT) to simulate surface PM2.5 using five fire emission inventories. We reproduce up to 25% of the weekly variability in total observed PM2.5 using STILT. Depending on year and emission inventory, our method attributes 7.0%–78% of the maximum observed PM2.5 enhancements in Delhi to fires. The large range in these attribution estimates points to the uncertainties in fire emission parameterizations, especially in regions where thick smoke may interfere with hotspots of fire radiative power. Although our model can generally reproduce the largest PM2.5 enhancements in Delhi air quality for 1–3 consecutive days each fire season, it fails to capture many smaller daily enhancements, which we attribute to the challenge of detecting small fires in the satellite retrieval. By quantifying the influence of upwind agricultural fire emissions on Delhi air pollution, our work underscores the potential health benefits of changes in farming practices to reduce fires.

A Prognostic Methodology for Precipitation Phase Detection using GPM Microwave Observations —With Focus on Snow Cover

NASA Astrophysics Data System (ADS)

Takbiri, Z.; Ebtehaj, A.; Foufoula-Georgiou, E.; Kirstetter, P.

2017-12-01

Improving satellite retrieval of precipitation requires increased understanding of its passive microwave signature over different land surfaces. Passive microwave signals over snow-covered surfaces are notoriously difficult to interpret because they record both emission from the land below and absorption/scattering from the liquid/ice crystals. Using data from the Global Precipitation Measurement (GPM) core satellite, we demonstrate that the microwave brightness temperatures of rain and snowfall shifts from a scattering to an emission regime from summer to winter, due to expansion of the less emissive snow cover underneath. We present evidence that the combination of low- (10-19 GHz) and high-frequency (89-166 GHz) channels provides the maximum amount of information for snowfall detection. The study also examines a prognostic nearest neighbor matching method for the detection of precipitation and its phase from passive microwave observations using GPM data. The nearest neighbor uses the weighted Euclidean distance metric to search through an a priori database that is populated with coincident GPM radiometer and radar data as well as ancillary snow cover fraction. The results demonstrate prognostic capabilities of the proposed method in detection of terrestrial snowfall. At the global scale, the average probability of hit and false alarm reaches to 0.80 and remains below 0.10, respectively. Surprisingly, the results show that the snow cover may help to better detect precipitation as the detection rate of terrestrial precipitation is increased from 0.75 (no snow cover) to 0.84 (snow-covered surfaces). For solid precipitation, this increased rate of detection is larger than its liquid counterpart by almost 8%. The main reasons are found to be related to the multi-frequency capabilities of the nearest neighbor matching that can properly isolate the atmospheric signal from the background emission and the fact that the precipitation can exhibit an emission-like (warmer than surface) signature over fresh snow cover.

How ground-based observations can support satellite greenhouse gas retrievals

NASA Astrophysics Data System (ADS)

Butler, J. H.; Tans, P. P.; Sweeney, C.; Dlugokencky, E. J.

2012-04-01

Global society will eventually accelerate efforts to reduce greenhouse gas emissions in a variety of ways. These would likely involve international treaties, national policies, and regional strategies that will affect a number of economic, social, and environmental sectors. Some strategies will work better than others and some will not work at all. Because trillions of dollars will be involved in pursuing greenhouse gas emission reductions - through realignment of energy production, improvement of efficiencies, institution of taxes, implementation of carbon trading markets, and use of offsets - it is imperative that society be given all the tools at its disposal to ensure the ultimate success of these efforts. Providing independent, globally coherent information on the success of these efforts will give considerable strength to treaties, policies, and strategies. Doing this will require greenhouse gas observations greatly expanded from what we have today. Satellite measurements may ultimately be indispensable in achieving global coverage, but the requirements for accuracy and continuity of measurements over time are demanding if the data are to be relevant. Issues such as those associated with sensor drift, aging electronics, and retrieval artifacts present challenges that can be addressed in part by close coordination with ground-based and in situ systems. This presentation identifies the information that ground-based systems provide very well, but it also looks at what would be deficient even in a greatly expanded surface system, where satellites can fill these gaps, and how on-going, ground and in situ measurements can aid in addressing issues associated with accuracy, long-term continuity, and retrieval artifacts.

Using satellite observations in performance evaluation for regulatory air quality modeling: Comparison with ground-level measurements

NASA Astrophysics Data System (ADS)

Odman, M. T.; Hu, Y.; Russell, A.; Chai, T.; Lee, P.; Shankar, U.; Boylan, J.

2012-12-01

Regulatory air quality modeling, such as State Implementation Plan (SIP) modeling, requires that model performance meets recommended criteria in the base-year simulations using period-specific, estimated emissions. The goal of the performance evaluation is to assure that the base-year modeling accurately captures the observed chemical reality of the lower troposphere. Any significant deficiencies found in the performance evaluation must be corrected before any base-case (with typical emissions) and future-year modeling is conducted. Corrections are usually made to model inputs such as emission-rate estimates or meteorology and/or to the air quality model itself, in modules that describe specific processes. Use of ground-level measurements that follow approved protocols is recommended for evaluating model performance. However, ground-level monitoring networks are spatially sparse, especially for particulate matter. Satellite retrievals of atmospheric chemical properties such as aerosol optical depth (AOD) provide spatial coverage that can compensate for the sparseness of ground-level measurements. Satellite retrievals can also help diagnose potential model or data problems in the upper troposphere. It is possible to achieve good model performance near the ground, but have, for example, erroneous sources or sinks in the upper troposphere that may result in misleading and unrealistic responses to emission reductions. Despite these advantages, satellite retrievals are rarely used in model performance evaluation, especially for regulatory modeling purposes, due to the high uncertainty in retrievals associated with various contaminations, for example by clouds. In this study, 2007 was selected as the base year for SIP modeling in the southeastern U.S. Performance of the Community Multiscale Air Quality (CMAQ) model, at a 12-km horizontal resolution, for this annual simulation is evaluated using both recommended ground-level measurements and non-traditional satellite retrievals. Evaluation results are assessed against recommended criteria and peer studies in the literature. Further analysis is conducted, based upon these assessments, to discover likely errors in model inputs and potential deficiencies in the model itself. Correlations as well as differences in input errors and model deficiencies revealed by ground-level measurements versus satellite observations are discussed. Additionally, sensitivity analyses are employed to investigate errors in emission-rate estimates using either ground-level measurements or satellite retrievals, and the results are compared against each other considering observational uncertainties. Recommendations are made for how to effectively utilize satellite retrievals in regulatory air quality modeling.

Surface and Atmospheric Contributions to Passive Microwave Brightness Temperatures for Falling Snow Events

NASA Technical Reports Server (NTRS)

Skofronick-Jackson, Gail; Johnson, Benjamin T.

2011-01-01

Physically based passive microwave precipitation retrieval algorithms require a set of relationships between satellite -observed brightness temperatures (TBs) and the physical state of the underlying atmosphere and surface. These relationships are nonlinear, such that inversions are ill ]posed especially over variable land surfaces. In order to elucidate these relationships, this work presents a theoretical analysis using TB weighting functions to quantify the percentage influence of the TB resulting from absorption, emission, and/or reflection from the surface, as well as from frozen hydrometeors in clouds, from atmospheric water vapor, and from other contributors. The percentage analysis was also compared to Jacobians. The results are presented for frequencies from 10 to 874 GHz, for individual snow profiles, and for averages over three cloud-resolving model simulations of falling snow. The bulk structure (e.g., ice water path and cloud depth) of the underlying cloud scene was found to affect the resultant TB and percentages, producing different values for blizzard, lake effect, and synoptic snow events. The slant path at a 53 viewing angle increases the hydrometeor contributions relative to nadir viewing channels. Jacobians provide the magnitude and direction of change in the TB values due to a change in the underlying scene; however, the percentage analysis provides detailed information on how that change affected contributions to the TB from the surface, hydrometeors, and water vapor. The TB percentage information presented in this paper provides information about the relative contributions to the TB and supplies key pieces of information required to develop and improve precipitation retrievals over land surfaces.

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

NASA Technical Reports Server (NTRS)

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;

Retrieving CO2 from Orbiting Carbon Observatory-2 (OCO-2) Spectra

NASA Astrophysics Data System (ADS)

Crisp, David

2014-06-01

Fossil fuel combustion, deforestation, and other human activities are currently adding almost 40 billion tons of carbon dioxide (CO2) to the atmosphere each year. These emissions have increased by roughly a factor of 3 over the past half century and are still growing by more than 2% per year. The developing world is now responsible for the majority (57%) of these emissions and their rapid growth rates. Precise measurements collected by a global network of surface stations show that these emissions have contributed to a 25% increase in the atmospheric CO2 concentration over the past half century. Surprisingly, comparisons of these measurements with fossil fuel emission inventories indicate that only about half of the CO2 emitted into the atmosphere by human activities stays there. The rest is apparently being absorbed by natural CO2 "sinks" at the Earth's surface. Measurements of the pH of the ocean indicate that it absorbs roughly one quarter of these emissions. The remainder has been attributed to the land biosphere, but the identity and location of the land sinks is still unknown. In addition, the fraction of the anthropogenic CO2 absorbed by these natural sinks has varied dramatically from year to year, but has remained near 1/2 on decadal time scales as the emissions have steadily increased. Uncertainties in the nature, location, and processes controlling these natural sink largely preclude reliable predictions of future atmospheric CO2 buildup rates. The existing greenhouse gas monitoring network can accurately track CO2 changes on hemispheric to global scales, but does not have the resolution or coverage needed to quantify emission sources on regional scales or to identify the natural sinks responsible for absorbing CO2. One way to improve the measurement density is to retrieve precise, spatially-resolved estimates of the column-averaged CO2 dry air mole fraction, XCO2, from satellites. Surface-weighted estimates of XCO2 can be retrieved from measurements of reflected sunlight in near infrared CO2 and O2 bands. However, this is among the most challenging space-based remote sensing applications because even the largest CO2 sources and sinks produce changes in the background XCO2 distribution no larger than 1%, and most are smaller 0.25% (˜1 ppm). This approach was pioneered by the European Space Agency's EnviSat SCIAMACHY and Japanese GOSAT TANSO-FTS instruments. These sensors have provided valuable insights into space based XCO2 measurement techniques, but still do not have the sensitivity, resolution, and coverage needed to quantify CO2 sources and sinks on regional scales. The Orbiting Carbon Observatory-2 (OCO-2) is the first NASA spacecraft designed to exploit this measurement approach. This spacecraft carries and points a 3channel, imaging, grating spectrometer that collects high resolution spectra of reflected sunlight in the 765 nm O2 A-band and in the 1610 and 2060 nm CO2 bands. Coincident O2 and CO2 spectra are combined into "soundings" that are analyzed with a full-physics retrieval algorithm to yield estimates of XCO2. Each spectrometer channel will collect 24 spectra per second, yielding up to a million soundings per day over the sunlit hemisphere. Between 10 and 30% of these soundings are expected to be sufficiently cloud free to yield full-column estimates of XCO2. OCO-2 is currently scheduled for launch from Space Launch Complex 2 at Vandenberg Air Force Base in California on a United Launch Alliance Delta-II 7320-10 Launch Vehicle at 02:56:44 AM PDT (12:56:44 GMT) on 1 July 2014. The nominal spacecraft checkout and orbit raising plan will take about 37 days to insert the observatory into the 705-km Afternoon Constellation (A-Train). This 98.8-minute, sun-synchronous orbit has a 98.2-degree inclination, a 1:36:30 PM mean ascending equator crossing time time, and a 16-day (233 orbit) ground track repeat cycle. Once in the A-Train, the instrument's optical bench and detectors will be cooled to their operating temperatures, and a ˜7-day instrument check-out period will commence. OCO-2 will then start routinely collecting and returning science data. For routine science operations, the instrument's bore sight will be pointed to the local nadir or at the "glint spot," where sunlight is specularly reflected from the Earth's surface. Nadir observations provide the best spatial resolution and are expected to yield more cloud-free XCO2 soundings over land. Glint observations will have much better signal-to-noise ratios (SNR) over dark, ocean surfaces. As often as once each day, the satellite will target a selected surface calibration and validation site and collect thousands of observations as the spacecraft flies overhead. The instrument's rapid sampling, relatively small (< 3 km2) sounding footprint, and high SNR, combined with the spacecraft's ability to point the instrument's bore sight toward the glint spot over the entire sunlit hemisphere, are expected to provide more complete coverage of the ocean, cloudy regions, and high latitude continents than earlier CO2 monitoring spacecraft. The first calibrated, geo-located spectral radiances will be delivered to the NASA Earth Sciences Data and Information Services Center (GES DISC) approximately 90 days after nominal science operations begin. The first XCO2 products will start being delivered 90 days after that. The OCO-2 mission is required to return estimates of XCO2 with accuracies of 0.3% on regional scales at monthly intervals. To meet this stringent requirement, the OCO2 team has developed a "full-physics" retrieval algorithm that incorporates a forward radiative-transfer model based on a spectrum-resolving multiple scattering algorithm, an OCO-2 instrument model, and an inverse model based on Optimal Estimation. To yield XCO2 estimates with accuracies of 0.3%, the forward radiative-transfer model must simulate reflected solar radiances with biases no larger than ˜ 0.1%. The accuracy of our XCO2 estimates retrieved from spectra collected by the GOSAT TANSO-FTS and the ground based Total Carbon Column Observing Network (TCCON) has improved steadily over the past 5 years, but these retrievals still yield biases as large as 1%. Persistent biases and spectrally-dependent residuals in fits to the O2 A-band and the two CO2 bands sampled by OCO-2 indicate that shortcomings in gas absorption cross sections are a leading cause of these errors. To address this issue, the OCO-2 project has supported an ambitious molecular spectroscopy measurement and analysis effort. Laboratory spectra of CO2 and O2 collected with cavity ringdown and photoacoustic techniques are being combined with new low-temperature Fourier transform spectra and analyzed with multi-spectral fitting techniques to yield a new, self-consistent description of the line positions, strengths, shapes, and mixing in these bands. This presentation will provide a quick overview of the OCO-2 mission and summarize the recent progress in our molecular spectroscopy effort.

Retriever, a multiprotein complex for retromer-independent endosomal cargo recycling

PubMed Central

McNally, Kerrie E.; Faulkner, Rebecca; Steinberg, Florian; Gallon, Matthew; Ghai, Rajesh; Pim, David; Langton, Paul; Pearson, Neil; Danson, Chris M.; Nägele, Heike; Morris, Lindsey M; Singla, Arnika; Overlee, Brittany L; Heesom, Kate J.; Sessions, Richard; Banks, Lawrence; Collins, Brett M; Berger, Imre; Billadeau, Daniel D.; Burstein, Ezra; Cullen, Peter J.

2018-01-01

Following endocytosis and entry into the endosomal network, integral membrane proteins undergo sorting for lysosomal degradation or are alternatively retrieved and recycled back to the cell surface. Here we describe the discovery of an ancient and conserved multi-protein complex which orchestrates cargo retrieval and recycling and importantly, is biochemically and functionally distinct to the established retromer pathway. Composed of a heterotrimer of DSCR3, C16orf62 and VPS29, and bearing striking similarity with retromer, we have called this complex ‘retriever’. We establish that retriever associates with the cargo adaptor sorting nexin 17 (SNX17) and couples to the CCC and WASH complexes to prevent lysosomal degradation and promote cell surface recycling of α5β1-integrin. Through quantitative proteomic analysis we identify over 120 cell surface proteins, including numerous integrins, signalling receptors and solute transporters, which require SNX17-retriever to maintain their surface levels. Our identification of retriever establishes a major new endosomal retrieval and recycling pathway. PMID:28892079

Uncertainty of Passive Imager Cloud Optical Property Retrievals to Instrument Radiometry and Model Assumptions: Examples from MODIS

NASA Technical Reports Server (NTRS)

Platnick, Steven; Wind, Galina; Meyer, Kerry; Amarasinghe, Nandana; Arnold, G. Thomas; Zhang, Zhibo; King, Michael D.

2013-01-01

The optical and microphysical structure of clouds is of fundamental importance for understanding a variety of cloud radiation and precipitation processes. With the advent of MODIS on the NASA EOS Terra and Aqua platforms, simultaneous global-daily 1 km retrievals of cloud optical thickness (COT) and effective particle radius (CER) are provided, as well as the derived water path (WP). The cloud product (MOD06/MYD06 for MODIS Terra and Aqua, respectively) provides separate retrieval datasets for various two-channel retrievals, typically a VISNIR channel paired with a 1.6, 2.1, and 3.7 m spectral channel. The MOD06 forward model is derived from on a homogeneous plane-parallel cloud. In Collection 5 processing (completed in 2007 with a modified Collection 5.1 completed in 2010), pixel-level retrieval uncertainties were calculated for the following non-3-D error sources: radiometry, surface spectral albedo, and atmospheric corrections associated with model analysis uncertainties (water vapor only). The latter error source includes error correlation across the retrieval spectral channels. Estimates of uncertainty in 1 aggregated (Level-3) means were also provided assuming unity correlation between error sources for all pixels in a grid for a single day, and zero correlation of error sources from one day to the next. I n Collection 6 (expected to begin in late summer 2013) we expanded the uncertainty analysis to include: (a) scene-dependent calibration uncertainty that depends on new band and detector-specific Level 1B uncertainties, (b) new model error sources derived from the look-up tables which includes sensitivities associated with wind direction over the ocean and uncertainties in liquid water and ice effective variance, (c) thermal emission uncertainties in the 3.7 m band associated with cloud and surface temperatures that are needed to extract reflected solar radiation from the total radiance signal, (d) uncertainty in the solar spectral irradiance at 3.7 m, and (e) addition of stratospheric ozone uncertainty in visible atmospheric corrections. A summary of the approach and example Collection 6 results will be shown.

Uncertainty of passive imager cloud retrievals to instrument radiometry and model assumptions: Examples from MODIS Collection 6

NASA Astrophysics Data System (ADS)

Platnick, S.; Wind, G.; Amarasinghe, N.; Arnold, G. T.; Zhang, Z.; Meyer, K.; King, M. D.

2013-12-01

The optical and microphysical structure of clouds is of fundamental importance for understanding a variety of cloud radiation and precipitation processes. With the advent of MODIS on the NASA EOS Terra and Aqua platforms, simultaneous global/daily 1km retrievals of cloud optical thickness (COT) and effective particle radius (CER) are provided, as well as the derived water path (WP). The cloud product (MOD06/MYD06 for MODIS Terra and Aqua, respectively) provides separate retrieval datasets for various two-channel retrievals, typically a VIS/NIR channel paired with a 1.6, 2.1, and 3.7 μm spectral channel. The MOD06 forward model is derived from a homogeneous plane-parallel cloud. In Collection 5 processing (completed in 2007 with a modified Collection 5.1 completed in 2010), pixel-level retrieval uncertainties were calculated for the following non-3-D error sources: radiometry, surface spectral albedo, and atmospheric corrections associated with model analysis uncertainties (water vapor only). The latter error source includes error correlation across the retrieval spectral channels. Estimates of uncertainty in 1° aggregated (Level-3) means were also provided assuming unity correlation between error sources for all pixels in a grid for a single day, and zero correlation of error sources from one day to the next. In Collection 6 (expected to begin in late summer 2013) we expanded the uncertainty analysis to include: (a) scene-dependent calibration uncertainty that depends on new band and detector-specific Level 1B uncertainties, (b) new model error sources derived from the look-up tables which includes sensitivities associated with wind direction over the ocean and uncertainties in liquid water and ice effective variance, (c) thermal emission uncertainties in the 3.7 μm band associated with cloud and surface temperatures that are needed to extract reflected solar radiation from the total radiance signal, (d) uncertainty in the solar spectral irradiance at 3.7 μm, and (e) addition of stratospheric ozone uncertainty in visible atmospheric corrections. A summary of the approach and example Collection 6 results will be shown.

Improved surface-wave retrieval from ambient seismic noise by multi-dimensional deconvolution

NASA Astrophysics Data System (ADS)

Wapenaar, Kees; Ruigrok, Elmer; van der Neut, Joost; Draganov, Deyan

2011-01-01

The methodology of surface-wave retrieval from ambient seismic noise by crosscorrelation relies on the assumption that the noise field is equipartitioned. Deviations from equipartitioning degrade the accuracy of the retrieved surface-wave Green's function. A point-spread function, derived from the same ambient noise field, quantifies the smearing in space and time of the virtual source of the Green's function. By multidimensionally deconvolving the retrieved Green's function by the point-spread function, the virtual source becomes better focussed in space and time and hence the accuracy of the retrieved surface-wave Green's function may improve significantly. We illustrate this at the hand of a numerical example and discuss the advantages and limitations of this new methodology.

A study of remotely sensed aerosol properties from ground-based sun and sky scanning radiometers

NASA Astrophysics Data System (ADS)

Giles, David M.

Aerosol particles impact human health by degrading air quality and affect climate by heating or cooling the atmosphere. The Indo-Gangetic Plain (IGP) of Northern India, one of the most populous regions in the world, produces and is impacted by a variety of aerosols including pollution, smoke, dust, and mixtures of them. The NASA Aerosol Robotic Network (AERONET) mesoscale distribution of Sun and sky-pointing instruments in India was established to measure aerosol characteristics at sites across the IGP and around Kanpur, India, a large urban and industrial center in the IGP, during the 2008 pre-monsoon (April-June). This study focused on detecting spatial and temporal variability of aerosols, validating satellite retrievals, and classifying the dominant aerosol mixing states and origins. The Kanpur region typically experiences high aerosol loading due to pollution and smoke during the winter and high aerosol loading due to the addition of dust to the pollution and smoke mixture during the pre-monsoon. Aerosol emissions in Kanpur likely contribute up to 20% of the aerosol loading during the pre-monsoon over the IGP. Aerosol absorption also increases significantly downwind of Kanpur indicating the possibility of the black carbon emissions from aerosol sources such as coal-fired power plants and brick kilns. Aerosol retrievals from satellite show a high bias when compared to the mesoscale distributed instruments around Kanpur during the pre-monsoon with few high quality retrievals due to imperfect aerosol type and land surface characteristic assumptions. Aerosol type classification using the aerosol absorption, size, and shape properties can identify dominant aerosol mixing states of absorbing dust and black carbon particles. Using 19 long-term AERONET sites near various aerosol source regions (Dust, Mixed, Urban/Industrial, and Biomass Burning), aerosol absorption property statistics are expanded upon and show significant differences when compared to previous work. The sensitivity of absorption properties is evaluated and quantified with respect to aerosol retrieval uncertainty. Using clustering analysis, aerosol absorption and size relationships provide a simple method to classify aerosol mixing states and origins and potentially improve aerosol retrievals from ground-based and satellite-based instrumentation.

A protocol for validating Land Surface Temperature from Sentinel-3

NASA Astrophysics Data System (ADS)

Ghent, D.

2015-12-01

One of the main objectives of the Sentinel-3 mission is to measure sea- and land-surface temperature with high-end accuracy and reliability in support of environmental and climate monitoring in an operational context. Calibration and validation are thus key criteria for operationalization within the framework of the Sentinel-3 Mission Performance Centre (S3MPC).Land surface temperature (LST) has a long heritage of satellite observations which have facilitated our understanding of land surface and climate change processes, such as desertification, urbanization, deforestation and land/atmosphere coupling. These observations have been acquired from a variety of satellite instruments on platforms in both low-earth orbit and in geostationary orbit. Retrieval accuracy can be a challenge though; surface emissivities can be highly variable owing to the heterogeneity of the land, and atmospheric effects caused by the presence of aerosols and by water vapour absorption can give a bias to the underlying LST. As such, a rigorous validation is critical in order to assess the quality of the data and the associated uncertainties. The Sentinel-3 Cal-Val Plan for evaluating the level-2 SL_2_LST product builds on an established validation protocol for satellite-based LST. This set of guidelines provides a standardized framework for structuring LST validation activities, and is rapidly gaining international recognition. The protocol introduces a four-pronged approach which can be summarised thus: i) in situ validation where ground-based observations are available; ii) radiance-based validation over sites that are homogeneous in emissivity; iii) intercomparison with retrievals from other satellite sensors; iv) time-series analysis to identify artefacts on an interannual time-scale. This multi-dimensional approach is a necessary requirement for assessing the performance of the LST algorithm for SLSTR which is designed around biome-based coefficients, thus emphasizing the importance of non-traditional forms of validation such as radiance-based techniques. Here we present examples of the application of the protocol to data produced within the ESA DUE GlobTemperature Project. The lessons learnt here are helping to fine-tune the methodology in preparation for Sentinel-3 commissioning.

High-resolution airborne imaging DOAS measurements of NO2 above Bucharest during AROMAT

NASA Astrophysics Data System (ADS)

Meier, Andreas Carlos; Schönhardt, Anja; Bösch, Tim; Richter, Andreas; Seyler, André; Ruhtz, Thomas; Constantin, Daniel-Eduard; Shaiganfar, Reza; Wagner, Thomas; Merlaud, Alexis; Van Roozendael, Michel; Belegante, Livio; Nicolae, Doina; Georgescu, Lucian; Burrows, John Philip

2017-05-01

In this study we report on airborne imaging DOAS measurements of NO2 from two flights performed in Bucharest during the AROMAT campaign (Airborne ROmanian Measurements of Aerosols and Trace gases) in September 2014. These measurements were performed with the Airborne imaging Differential Optical Absorption Spectroscopy (DOAS) instrument for Measurements of Atmospheric Pollution (AirMAP) and provide nearly gapless maps of column densities of NO2 below the aircraft with a high spatial resolution of better than 100 m. The air mass factors, which are needed to convert the measured differential slant column densities (dSCDs) to vertical column densities (VCDs), have a strong dependence on the surface reflectance, which has to be accounted for in the retrieval. This is especially important for measurements above urban areas, where the surface properties vary strongly. As the instrument is not radiometrically calibrated, we have developed a method to derive the surface reflectance from intensities measured by AirMAP. This method is based on radiative transfer calculation with SCIATRAN and a reference area for which the surface reflectance is known. While surface properties are clearly apparent in the NO2 dSCD results, this effect is successfully corrected for in the VCD results. Furthermore, we investigate the influence of aerosols on the retrieval for a variety of aerosol profiles that were measured in the context of the AROMAT campaigns. The results of two research flights are presented, which reveal distinct horizontal distribution patterns and strong spatial gradients of NO2 across the city. Pollution levels range from background values in the outskirts located upwind of the city to about 4 × 1016 molec cm-2 in the polluted city center. Validation against two co-located mobile car-DOAS measurements yields good agreement between the datasets, with correlation coefficients of R = 0.94 and R = 0.85, respectively. Estimations on the NOx emission rate of Bucharest for the two flights yield emission rates of 15.1 ± 9.4 and 13.6 ± 8.4 mol s-1, respectively.

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

Potential Applications of JNPP to Infrared-Based Remote Sensing of Volcanic Emissions

NASA Astrophysics Data System (ADS)

Realmuto, V. J.

2016-12-01

The simultaneous collection of VIIRS, CrIS, and OMPS data will make JNPP an ideal platform for monitoring volcanic emissions. For daytime overpasses we will obtain three contemporaneous, but independent, estimates of SO2 column density, as well as information on the quantity and composition of aerosols and volcanic ash. We will use the independent measurements to validate individual retrieval techniques, and exploit the synergy between UV and TIR remote sensing. The finer spatial resolution of VIIRS (750 m at nadir), relative to OMPS (50 km) and CrIS (14 km), will allow us to characterize variations in surface conditions, plume composition, and the distribution of clouds within an IFOV of CrIS or OMPS, and assess the impact of these variations on the SO2retrievals. Atmospheric profiles are an essential input to the retrieval procedures, and the profiles derived from CrIS soundings will provide us with an accurate description of atmospheric conditions local to the plumes. In addition, the fine spectral resolution of CrIS will enable us to identify and quantify the components of heterogeneous (gas + particulate) plumes. We will demonstrate the potential use of JPSS to map volcanic planes through the analyses of TIR data acquired by EOS (ASTER, MODIS, and AIRS) and SNPP (VIIRS and CrIS) instruments over the plumes generated by recent eruptions of Eyjafallajökull, Bardarbunga (Iceland), Calbuco (Chile), and Ontake (Japan) Volcanoes. We will present comparisons of the TIR-based retrievals to OMI and SNPP-OMPS data products. Finally, we will outline a path to operations through collaboration with the Alaska Volcano Observatory (USGS), Anchorage Volcanic Ash Advisory Center (NWS + FAA), NASA-GSFC Direct Readout Lab, and University of Alaska-Fairbanks. This research was conducted at the Jet Propulsion Laboratory, California Institute of Technology, under contract to National Atmospheric and Space Administration.

Inferring Cirrus Size Distributions Through Satellite Remote Sensing and Microphysical Databases

NASA Technical Reports Server (NTRS)

Mitchell, David; D'Entremont, Robert P.; Lawson, R. Paul

2010-01-01

Since cirrus clouds have a substantial influence on the global energy balance that depends on their microphysical properties, climate models should strive to realistically characterize the cirrus ice particle size distribution (PSD), at least in a climatological sense. To date, the airborne in situ measurements of the cirrus PSD have contained large uncertainties due to errors in measuring small ice crystals (D<60 m). This paper presents a method to remotely estimate the concentration of the small ice crystals relative to the larger ones using the 11- and 12- m channels aboard several satellites. By understanding the underlying physics producing the emissivity difference between these channels, this emissivity difference can be used to infer the relative concentration of small ice crystals. This is facilitated by enlisting temperature-dependent characterizations of the PSD (i.e., PSD schemes) based on in situ measurements. An average cirrus emissivity relationship between 12 and 11 m is developed here using the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite instrument and is used to retrieve the PSD based on six different PSD schemes. The PSDs from the measurement-based PSD schemes are compared with corresponding retrieved PSDs to evaluate differences in small ice crystal concentrations. The retrieved PSDs generally had lower concentrations of small ice particles, with total number concentration independent of temperature. In addition, the temperature dependence of the PSD effective diameter De and fall speed Vf for these retrieved PSD schemes exhibited less variability relative to the unmodified PSD schemes. The reduced variability in the retrieved De and Vf was attributed to the lower concentrations of small ice crystals in the retrieved PSD.

piscope - A Python based software package for the analysis of volcanic SO2 emissions using UV SO2 cameras

NASA Astrophysics Data System (ADS)

Gliss, Jonas; Stebel, Kerstin; Kylling, Arve; Solvejg Dinger, Anna; Sihler, Holger; Sudbø, Aasmund

2017-04-01

UV SO2 cameras have become a common method for monitoring SO2 emission rates from volcanoes. Scattered solar UV radiation is measured in two wavelength windows, typically around 310 nm and 330 nm (distinct / weak SO2 absorption) using interference filters. The data analysis comprises the retrieval of plume background intensities (to calculate plume optical densities), the camera calibration (to convert optical densities into SO2 column densities) and the retrieval of gas velocities within the plume as well as the retrieval of plume distances. SO2 emission rates are then typically retrieved along a projected plume cross section, for instance a straight line perpendicular to the plume propagation direction. Today, for most of the required analysis steps, several alternatives exist due to ongoing developments and improvements related to the measurement technique. We present piscope, a cross platform, open source software toolbox for the analysis of UV SO2 camera data. The code is written in the Python programming language and emerged from the idea of a common analysis platform incorporating a selection of the most prevalent methods found in literature. piscope includes several routines for plume background retrievals, routines for cell and DOAS based camera calibration including two individual methods to identify the DOAS field of view (shape and position) within the camera images. Gas velocities can be retrieved either based on an optical flow analysis or using signal cross correlation. A correction for signal dilution (due to atmospheric scattering) can be performed based on topographic features in the images. The latter requires distance retrievals to the topographic features used for the correction. These distances can be retrieved automatically on a pixel base using intersections of individual pixel viewing directions with the local topography. The main features of piscope are presented based on dataset recorded at Mt. Etna, Italy in September 2015.

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.

MISR Decadal Observations of Mineral Dust: Property Characterization and Climate Applications

NASA Technical Reports Server (NTRS)

Kalashnikova, Olga V.; Garay, Michael J.; Sokolik, Irina; Kahn, Ralph A.; Lyapustin, A.; Diner, David J.; Lee, Jae N.; Torres, Omar; Leptoukh, Gregory G.; Sabbah, Ismail

2012-01-01

The Multi-angle Imaging SpectroRadiometer (MISR) provides a unique, independent source of data for studying dust emission and transport. MISR's multiple view angles allow the retrieval of aerosol properties over bright surfaces, and such retrievals have been shown to be sensitive to the non-sphericity of dust aerosols over both land and water. MISR stereographic views of thick aerosol plumes allow height and instantaneous wind derivations at spatial resolutions of better than 1.1 km horizontally and 200m vertically. We will discuss the radiometric and stereo-retrieval capabilities of MISR specifically for dust, and demonstrate the use of MISR data in conjunction with other available satellite observations for dust property characterization and climate studies.First, we will discuss MISR non-spherical (dust) fraction product over the global oceans. We will show that over the Atlantic Ocean, changes in the MISR-derived non-spherical AOD fraction illustrate the evolution of dust during transport. Next, we will present a MISR satellite perspective on dust climatology in major dust source regions with a particular emphasis on the West Africa and Middle East and discuss MISR's unique strengths as well as current product biases. Finally, we will discuss MISR dust plume product and climatological applications.

Special cases of AIRS v4.0.x retrievals: missing forecast surface pressure and regression-only retrieval

NASA Technical Reports Server (NTRS)

Hearty, Thomas; Manning, Evan

2005-01-01

This memo examines the differences that can be expected when performing two special cases of retrievals with the v.4.0.x PGE: (1) retrivals without the surface pressure from the NOAA Global Forecast System (GFS) and (2) regression only retrievals. An understanding of these differences is important for users who may want to give up some accuracy in the retrieval in exchange for a rapid solution.

Synergistic estimation of surface parameters from jointly using optical and microwave observations in EOLDAS

NASA Astrophysics Data System (ADS)

Timmermans, Joris; Gomez-Dans, Jose; Lewis, Philip; Loew, Alexander; Schlenz, Florian

2017-04-01

The large amount of remote sensing data nowadays available provides a huge potential for monitoring crop development, drought conditions and water efficiency. This potential however not been realized yet because algorithms for land surface parameter retrieval mostly use data from only a single sensor. Consequently products that combine different low-level observations from different sensors are hard to find. The lack of synergistic retrieval is caused because it is easier to focus on single sensor types/footprints and temporal observation times, than to find a way to compensate for differences. Different sensor types (microwave/optical) require different radiative transfer (RT) models and also require consistency between the models to have any impact on the retrieval of soil moisture by a microwave instrument. Varying spatial footprints require first proper collocation of the data before one can scale between different resolutions. Considering these problems, merging optical and microwave observations have not been performed yet. The goal of this research was to investigate the potential of integrating optical and microwave RT models within the Earth Observation Land Data Assimilation System (EOLDAS) synergistically to derive biophysical parameters. This system uses a Bayesian data assimilation approach together with observation operators such as the PROSAIL model to estimate land surface parameters. For the purpose of enabling the system to integrate passive microwave radiation (from an ELBARRA II passive microwave radiometer), the Community Microwave Emission Model (CMEM) RT-model, was integrated within the EOLDAS system. In order to quantify the potential, a variety of land surface parameters was chosen to be retrieved from the system, in particular variables that a) impact only optical RT (such as leaf water content and leaf dry matter), b) only impact the microwave RT (such as soil moisture and soil temperature), and c) Leaf Area Index (LAI) that impacts both optical and microwave RT. The results show a high potential when both optical and microwave are used independently. Using only RapidEye only with SAIL RT model, LAI was estimated with R=0.68 with p=0.09, although estimating leaf water content and dry matter showed lower correlations |R|<0.4. The results for retrieving soil temperature and leaf area index retrievals using only (passive microwave) Elbarra-II observations were good with respectively R=[0.85, 0.79], P=[0.0, 0.0], when focusing on dry-spells (of at least 9 days) only the results respectively [R=0.73, and P=0.0], and R=0.89 and R=0.77 for respectively the trend and anomalies. Synergistically using optical and microwave shows also a good potential. This scenario shows that absolute errors improved (with RMSE=1.22 and S=0.89), but with degrading correlations (R=0.59 and P=0.04); the sparse optical observations only improved part of the temporal domain. However in general the synergistic retrieval showed good potential; microwave data provides better information concerning the overall trend of the retrieved LAI due to the regular acquisitions, while optical data provides better information concerning the absolute values of the LAI.

The effect of row structure on soil moisture retrieval accuracy from passive microwave data.

PubMed

Xingming, Zheng; Kai, Zhao; Yangyang, Li; Jianhua, Ren; Yanling, Ding

2014-01-01

Row structure causes the anisotropy of microwave brightness temperature (TB) of soil surface, and it also can affect soil moisture retrieval accuracy when its influence is ignored in the inversion model. To study the effect of typical row structure on the retrieved soil moisture and evaluate if there is a need to introduce this effect into the inversion model, two ground-based experiments were carried out in 2011. Based on the observed C-band TB, field soil and vegetation parameters, row structure rough surface assumption (Q p model and discrete model), including the effect of row structure, and flat rough surface assumption (Q p model), ignoring the effect of row structure, are used to model microwave TB of soil surface. Then, soil moisture can be retrieved, respectively, by minimizing the difference of the measured and modeled TB. The results show that soil moisture retrieval accuracy based on the row structure rough surface assumption is approximately 0.02 cm(3)/cm(3) better than the flat rough surface assumption for vegetated soil, as well as 0.015 cm(3)/cm(3) better for bare and wet soil. This result indicates that the effect of row structure cannot be ignored for accurately retrieving soil moisture of farmland surface when C-band is used.

Impact of a highly detailed emission inventory on modeling accuracy

NASA Astrophysics Data System (ADS)

Taghavi, M.; Cautenet, S.; Arteta, J.

2005-03-01

During Expérience sur Site pour COntraindre les Modèles de Pollution atmosphérique et de Transport d'Emissions (ESCOMPTE) campaign (June 10 to July 14, 2001), two pollution events observed during an intensive measurement period (IOP2a and IOP2b) have been simulated. The comprehensive Regional Atmospheric Modeling Systems (RAMS) model, version 4.3, coupled online with a chemical module including 29 species is used to follow the chemistry of a polluted zone over Southern France. This online method takes advantage of a parallel code and use of the powerful computer SGI 3800. Runs are performed with two emission inventories: the Emission Pre Inventory (EPI) and the Main Emission Inventory (MEI). The latter is more recent and has a high resolution. The redistribution of simulated chemical species (ozone and nitrogen oxides) is compared with aircraft and surface station measurements for both runs at regional scale. We show that the MEI inventory is more efficient than the EPI in retrieving the redistribution of chemical species in space (three-dimensional) and time. In surface stations, MEI is superior especially for primary species, like nitrogen oxides. The ozone pollution peaks obtained from an inventory, such as EPI, have a large uncertainty. To understand the realistic geographical distribution of pollutants and to obtain a good order of magnitude in ozone concentration (in space and time), a high-resolution inventory like MEI is necessary. Coupling RAMS-Chemistry with MEI provides a very efficient tool able to simulate pollution plumes even in a region with complex circulations, such as the ESCOMPTE zone.

Improvements to the swath-level near-surface atmospheric state parameter retrievals within the NRL Ocean Surface Flux System (NFLUX)

NASA Astrophysics Data System (ADS)

May, J. C.; Rowley, C. D.; Meyer, H.

2017-12-01

The Naval Research Laboratory (NRL) Ocean Surface Flux System (NFLUX) is an end-to-end data processing and assimilation system used to provide near-real-time satellite-based surface heat flux fields over the global ocean. The first component of NFLUX produces near-real-time swath-level estimates of surface state parameters and downwelling radiative fluxes. The focus here will be on the satellite swath-level state parameter retrievals, namely surface air temperature, surface specific humidity, and surface scalar wind speed over the ocean. Swath-level state parameter retrievals are produced from satellite sensor data records (SDRs) from four passive microwave sensors onboard 10 platforms: the Special Sensor Microwave Imager/Sounder (SSMIS) sensor onboard the DMSP F16, F17, and F18 platforms; the Advanced Microwave Sounding Unit-A (AMSU-A) sensor onboard the NOAA-15, NOAA-18, NOAA-19, Metop-A, and Metop-B platforms; the Advanced Technology Microwave Sounder (ATMS) sensor onboard the S-NPP platform; and the Advanced Microwave Scannin Radiometer 2 (AMSR2) sensor onboard the GCOM-W1 platform. The satellite SDRs are translated into state parameter estimates using multiple polynomial regression algorithms. The coefficients to the algorithms are obtained using a bootstrapping technique with all available brightness temperature channels for a given sensor, in addition to a SST field. For each retrieved parameter for each sensor-platform combination, unique algorithms are developed for ascending and descending orbits, as well as clear vs cloudy conditions. Each of the sensors produces surface air temperature and surface specific humidity retrievals. The SSMIS and AMSR2 sensors also produce surface scalar wind speed retrievals. Improvement is seen in the SSMIS retrievals when separate algorithms are used for the even and odd scans, with the odd scans performing better than the even scans. Currently, NFLUX treats all SSMIS scans as even scans. Additional improvement in all of the surface retrievals comes from using a 3-hourly SST field, as opposed to a daily SST field.

The DMRT-ML Model: Numerical Simulations of the Microwave Emission of Snowpacks Based on the Dense Media Radiative Transfer Theory

NASA Technical Reports Server (NTRS)

Picard, Ghislain; Brucker, Ludovic; Roy, Alexandre; DuPont, FLorent; Champollion, Nicolas; Morin, Samuel

2014-01-01

Microwave radiometer observations have been used to retrieve snow depth and snow water equivalent on both land and sea ice, snow accumulation on ice sheets, melt events, snow temperature, and snow grain size. Modeling the microwave emission from snow and ice physical properties is crucial to improve the quality of these retrievals. It also is crucial to improve our understanding of the radiative transfer processes within the snow cover, and the snow properties most relevant in microwave remote sensing. Our objective is to present a recent microwave emission model and its validation. The model is named DMRT-ML (DMRT Multi-Layer).

Community Radiative Transfer Model for Satellite Radiance Simulation

NASA Astrophysics Data System (ADS)

Liu, Q.; Han, Y.; Chen, Y.; van Delst, P.; Weng, F.

2007-12-01

The Community Radiative Transfer Model (CRTM) [Weng et al., 2005], developed at U.S. Joint Center for Satellite Data Assimilation (JCSDA), has been used for the satellite radiance simulation and the radiance derivatives to the surface/atmospheric parameters in the physical retrieval [Boukabara et al., 2007], data assimilation [Le Marshall et al., 2006] and many others [Han et al., 2006; Liu and Weng, 2006]. CRTM has been become a key component in U.S. data assimilation at the National Center for Environmental Prediction (NCEP) [Okamoto and. Derber, 2006]. It is a core engine for NOAA/NESDIS Microwave Integrated Retrieval System (MIRS) [Boukabara et al., 2007]. The CRTM has also been implemented into Weather Research Forecasting (WRF) model. The CRTM is known as modular program development [van Delst et al., 2006], which breaks down the radiative transfer model into components, each of which is encapsulated in one or several program modules and can be developed independently of the others. The key components of the CRTM are the advanced surface emissivity and reflectivity models [van Delst and Wu, 2000; English 1999; Weng et al. 2001] including a polarimetric surface emissivity model [Liu and Weng, 2003], the fast Optical Path Transmittance (OPTRAN) model [Xiong et al., 2006], the cloud absorption/scattering look-up tables [Yang et al., 2000], and the advanced radiative solver [Liu and Weng, 2006]. The CRTM can also compute aerosol radiance. The CRTM can deal with Zeeman splitting effect, the energy received in the channels for the stratosphere and mesosphere depends strongly on the geomagnetic field and its orientation with respect to the direction of observation [Han et al., 2007]. We will also present the applications of the CRTM in hurricane detection and forecasting, in the determination of stratospheric temperature, a key contributing factor to photochemical ozone depletion, and in reanalysis and climate studies.

On the Soil Roughness Parameterization Problem in Soil Moisture Retrieval of Bare Surfaces from Synthetic Aperture Radar

PubMed Central

Verhoest, Niko E.C; Lievens, Hans; Wagner, Wolfgang; Álvarez-Mozos, Jesús; Moran, M. Susan; Mattia, Francesco

2008-01-01

Synthetic Aperture Radar has shown its large potential for retrieving soil moisture maps at regional scales. However, since the backscattered signal is determined by several surface characteristics, the retrieval of soil moisture is an ill-posed problem when using single configuration imagery. Unless accurate surface roughness parameter values are available, retrieving soil moisture from radar backscatter usually provides inaccurate estimates. The characterization of soil roughness is not fully understood, and a large range of roughness parameter values can be obtained for the same surface when different measurement methodologies are used. In this paper, a literature review is made that summarizes the problems encountered when parameterizing soil roughness as well as the reported impact of the errors made on the retrieved soil moisture. A number of suggestions were made for resolving issues in roughness parameterization and studying the impact of these roughness problems on the soil moisture retrieval accuracy and scale. PMID:27879932

MERIS albedo climatology and its effect on the FRESCO+ O2 A-band cloud retrieval from SCIAMACHY data

NASA Astrophysics Data System (ADS)

Popp, Christoph; Wang, Ping; Brunner, Dominik; Stammes, Piet; Zhou, Yipin

2010-05-01

Accurate cloud information is an important prerequisite for the retrieval of atmospheric trace gases from spaceborne UV/VIS sensors. Errors in the estimated cloud fraction and cloud height (pressure) result in an erroneous air mass factor and thus can lead to inaccuracies in the vertical column densities of the retrieved trace gas. In ESA's TEMIS (Tropospheric Emission Monitoring Internet Service) project, the FRESCO+ (Fast Retrieval Scheme for Clouds from the Oxygen A-band) cloud retrieval is applied to, amongst others, SCIAMACHY (SCanning Imaging Absorption SpectroMeter for Atmospheric CartograpHY) data to determine these quantities. Effective cloud fraction and pressure are inverted by (i) radiative transfer simulations of top-of-atmosphere reflectance based on O2 absorption, single Rayleigh scattering, surface and cloud albedo in three spectral windows covering the O2 A-band and (ii) a subsequent fitting of the simulated to the measured spectrum. However, FRESCO+ relies on a relatively coarse resolution surface albedo climatology (1° x 1°) compiled from GOME (Global Ozone Monitoring Experiment) measurements in the 1990's which introduces several artifacts, e.g. an overestimation of cloud fraction at coastlines or over some mountainous regions. Therefore, we test the substitution of the GOME climatology with a new land surface albedo climatology compiled for every month from MEdium Resolution Imaging Spectrometer (MERIS) Albedomap data (0.05° x 0.05°) covering the period January 2003 to October 2006. The MERIS channels at 754nm and 775nm are located spectrally close to the corresponding GOME channels (758nm and 772nm) on both sides of the O2 A-band. Further, the increased spatial resolution of the MERIS product allows to better account for SCIAMACHY's pixel size of approximately 30x60km. The aim of this study is to describe and assess (i) the compilation and quality of the MERIS climatology (ii) the differences to the GOME climatology, and (iii) possible enhancements of the SCIAMACHY cloud retrieval after integrating the MERIS climatology into FRESCO+. First results indicate that in areas where FRESCO+ is overestimating cloud fraction using the GOME climatology, MERIS generally reveals higher albedo values which in turn will lead to lower cloud fractions, e.g. at coastlines, some arid or mountainous areas. The differences between the two data sets are also higher in winter than in summer. It can therefore be expected that the new data base with increased spatial resolution improves SCIAMACHY cloud retrieval with FRESCO+. The most limiting factors for the compilation of the MERIS climatology can be assigned to inappropriate snow cover masking and occasionally unfavorable illumination conditions in high northern latitudes during winter.

Air quality simulation over South Asia using Hemispheric Transport of Air Pollution version-2 (HTAP-v2) emission inventory and Model for Ozone and Related chemical Tracers (MOZART-4)

NASA Astrophysics Data System (ADS)

Surendran, Divya E.; Ghude, Sachin D.; Beig, G.; Emmons, L. K.; Jena, Chinmay; Kumar, Rajesh; Pfister, G. G.; Chate, D. M.

2015-12-01

This study presents the distribution of tropospheric ozone and related species for South Asia using the Model for Ozone and Related chemical Tracers (MOZART-4) and Hemispheric Transport of Air Pollution version-2 (HTAP-v2) emission inventory. The model present-day simulated ozone (O3), carbon monoxide (CO) and nitrogen dioxide (NO2) are evaluated against surface-based, balloon-borne and satellite-based (MOPITT and OMI) observations. The model systematically overestimates surface O3 mixing ratios (range of mean bias about: 1-30 ppbv) at different ground-based measurement sites in India. Comparison between simulated and observed vertical profiles of ozone shows a positive bias from the surface up to 600 hPa and a negative bias above 600 hPa. The simulated seasonal variation in surface CO mixing ratio is consistent with the surface observations, but has a negative bias of about 50-200 ppb which can be attributed to a large part to the coarse model resolution. In contrast to the surface evaluation, the model shows a positive bias of about 15-20 × 1017 molecules/cm2 over South Asia when compared to satellite derived CO columns from the MOPITT instrument. The model also overestimates OMI retrieved tropospheric column NO2 abundance by about 100-250 × 1013 molecules/cm2. A response to 20% reduction in all anthropogenic emissions over South Asia shows a decrease in the anuual mean O3 mixing ratios by about 3-12 ppb, CO by about 10-80 ppb and NOX by about 3-6 ppb at the surface level. During summer monsoon, O3 mixing ratios at 200 hPa show a decrease of about 6-12 ppb over South Asia and about 1-4 ppb over the remote northern hemispheric western Pacific region.

Direct Top-down Estimates of Biomass Burning CO Emissions Using TES and MOPITT Versus Bottom-up GFED Inventory

NASA Technical Reports Server (NTRS)

Pechony, Olga; Shindell, Drew T.; Faluvegi, Greg

2013-01-01

In this study, we utilize near-simultaneous observations from two sets of multiple satellite sensors to segregate Tropospheric Emission Spectrometer (TES) and Measurements of Pollution in the Troposphere (MOPITT) CO observations over active fire sources from those made over clear background. Hence, we obtain direct estimates of biomass burning CO emissions without invoking inverse modeling as in traditional top-down methods. We find considerable differences between Global Fire Emissions Database (GFED) versions 2.1 and 3.1 and satellite-based emission estimates in many regions. Both inventories appear to greatly underestimate South and Southeast Asia emissions, for example. On global scales, however, CO emissions in both inventories and in the MOPITT-based analysis agree reasonably well, with the largest bias (30%) found in the Northern Hemisphere spring. In the Southern Hemisphere, there is a one-month shift between the GFED and MOPITT-based fire emissions peak. Afternoon tropical fire emissions retrieved from TES are about two times higher than the morning MOPITT retrievals. This appears to be both a real difference due to the diurnal fire activity variations, and a bias due to the scarcity of TES data.

New nighttime retrievals of O(3P) and OH densities in the mesosphere/lower thermosphere using SABER/TIMED observations

NASA Astrophysics Data System (ADS)

Panka, P.; Kutepov, A. A.; Kalogerakis, K. S.; Janches, D.; Feofilov, A.; Rezac, L.; Marsh, D. R.; Yigit, E.

2017-12-01

We present first retrievals of O(3P) and OH densities in the mesosphere/lower thermosphere (MLT) using SABER/TIMED OH 2.0 and 1.6 μm limb emission observations. Recently, Kaufmann et al. [2014] reported that current SABER O(3P) densities are on average 30% higher compared to other observations. In this study we applied new detailed non-LTE model [Panka et al. 2017] of nighttime OH(v), which accounts for the new mechanism OH(v≥5)+O(3P)→O(1D)+OH(v-5) of energy transfer recently suggested by Sharma et al. [2015] and confirmed through laboratory studies by Kalogerakis et al. [2016]. Based on this model we developed a new self-consistent two channel retrieval approach for O(3P) and OH density. Using this approach, we retrieved O(3P) densities that are 10-40% lower than current SABER O(3P), as well as total OH density which is retrieved for the first time using SABER observations. We compare our retrieveals with the results of other observations and models. As it was recently shown by Panka et al. [2017], the new mechanism of OH quenching produces a significant pumping of CO2 4.3 µm emission. We discuss the effects these new O(3P) and OH retrievals have on the nighttime CO2 density retrievals from the SABER 4.3 µm channel.

MODIS Observation of Aerosols over Southern Africa During SAFARI 2000: Data, Validation, and Estimation of Aerosol Radiative Forcing

NASA Technical Reports Server (NTRS)

Ichoku, Charles; Kaufman, Yoram; Remer, Lorraine; Chu, D. Allen; Mattoo, Shana; Tanre, Didier; Levy, Robert; Li, Rong-Rong; Kleidman, Richard; Lau, William K. M. (Technical Monitor)

2001-01-01

Aerosol properties, including optical thickness and size parameters, are retrieved operationally from the MODIS sensor onboard the Terra satellite launched on 18 December 1999. The predominant aerosol type over the Southern African region is smoke, which is generated from biomass burning on land and transported over the southern Atlantic Ocean. The SAFARI-2000 period experienced smoke aerosol emissions from the regular biomass burning activities as well as from the prescribed burns administered on the auspices of the experiment. The MODIS Aerosol Science Team (MAST) formulates and implements strategies for the retrieval of aerosol products from MODIS, as well as for validating and analyzing them in order to estimate aerosol effects in the radiative forcing of climate as accurately as possible. These activities are carried out not only from a global perspective, but also with a focus on specific regions identified as having interesting characteristics, such as the biomass burning phenomenon in southern Africa and the associated smoke aerosol, particulate, and trace gas emissions. Indeed, the SAFARI-2000 aerosol measurements from the ground and from aircraft, along with MODIS, provide excellent data sources for a more intensive validation and a closer study of the aerosol characteristics over Southern Africa. The SAFARI-2000 ground-based measurements of aerosol optical thickness (AOT) from both the automatic Aerosol Robotic Network (AERONET) and handheld Sun photometers have been used to validate MODIS retrievals, based on a sophisticated spatio-temporal technique. The average global monthly distribution of aerosol from MODIS has been combined with other data to calculate the southern African aerosol daily averaged (24 hr) radiative forcing over the ocean for September 2000. It is estimated that on the average, for cloud free conditions over an area of 9 million square kin, this predominantly smoke aerosol exerts a forcing of -30 W/square m C lose to the terrestrial surface and -10 W/square m at the top of the atmosphere (TOA). While cooling the surface and Earth system, the difference of 20 W/square m is energy that heats the atmosphere.

A data-driven and physics-based single-pass retrieval of active-passive microwave covariation and vegetation parameters for the SMAP mission

NASA Astrophysics Data System (ADS)

Entekhabi, D.; Jagdhuber, T.; Das, N. N.; Baur, M.; Link, M.; Piles, M.; Akbar, R.; Konings, A. G.; Mccoll, K. A.; Alemohammad, S. H.; Montzka, C.; Kunstmann, H.

2016-12-01

The active-passive soil moisture retrieval algorithm of NASA's SMAP mission depends on robust statistical estimation of active-passive covariation (β) and vegetation structure (Γ) parameters in order to provide reliable global measurements of soil moisture on an intermediate level (9km) compared to the native resolution of the radiometer (36km) and radar (3km) instruments. These parameters apply to the SMAP radiometer-radar combination over the period of record that was cut short with the end of the SMAP radar transmission. They also apply to the current SMAP radiometer and Sentinel 1A/B radar combination for high-resolution surface soil moisture mapping. However, the performance of the statistically-based approach is directly dependent on the selection of a representative time frame in which these parameters can be estimated assuming dynamic soil moisture and stationary soil roughness and vegetation cover. Here, we propose a novel, data-driven and physics-based single-pass retrieval of active-passive microwave covariation and vegetation parameters for the SMAP mission. The algorithm does not depend on time series analyses and can be applied using minimum one pair of an active-passive acquisition. The algorithm stems from the physical link between microwave emission and scattering via conservation of energy. The formulation of the emission radiative transfer is combined with the Distorted Born Approximation of radar scattering for vegetated land surfaces. The two formulations are simultaneously solved for the covariation and vegetation structure parameters. Preliminary results from SMAP active-passive observations (April 13th to July 7th 2015) compare well with the time-series statistical approach and confirms the capability of this method to estimate these parameters. Moreover, the method is not restricted to a given frequency (applies to both L-band and C-band combinations for the radar) or incidence angle (all angles and not just the fixed 40° incidence). Therefore, the approach is applicable to the combination of SMAP and Sentinel-1A/B data for active-passive and high-resolution soil moisture estimation.

Characterization of the Atmospheric Boundary Layer Over Aburrá Valley Region (Colombia) Using Remote Sensing and Radiosonde Data

NASA Astrophysics Data System (ADS)

Herrera, L.; Hoyos Ortiz, C. D.

2017-12-01

The spatio-temporal evolution of the Atmospheric Boundary Layer (ABL) in the Aburrá Valley, a narrow highly complex mountainous terrain located in the Colombian Andes, is studied using different datasets including radiosonde and remote sensors from the meteorological network of the Aburrá Valley Early Warning System. Different techniques are developed in order to estimate Mixed Layer Height (MLH) based on variance of the ceilometer backscattering profiles. The Medellín metropolitan area, home of 4.5 million people, is located on the base and the hills of the valley. The generally large aerosol load within the valley from anthropogenic emissions allows the use of ceilometer retrievals of the MLH, especially under stable atmospheric conditions (late at night and early in the morning). Convective atmospheres, however, favor the aerosol dispersion which in turns increases the uncertainty associated with the estimation of the Convective Boundary Layer using ceilometer retrievals. A multi-sensor technique is also developed based on Richardson Number estimations using a Radar Wind Profiler combined with a Microwave Radiometer. Results of this technique seem to be more accurate thorough the diurnal cycle. ABL retrievals are available from October 2014 to April 2017. The diurnal cycle of the ABL exhibits monomodal behavior, highly influenced by the evolution of the potential temperature profile, and the turbulent fluxes near the surface. On the other hand, the backscattering diurnal cycle presents a bimodal structure, showing that the amount of aerosol particles at the lower troposphere is strongly influenced by anthropogenic emissions, dispersion conditioned by topography and by the ABL dynamics, conditioning the available vertical height for the pollutants to interact and disperse. Nevertheless, the amount, distribution or type of atmospheric aerosols does not appear to have a first order influence on the MLH variations or evolution. Results also show that intra-annual and interannual variations of cloudiness and surface incident radiation strongly condition the ABL expansion rate leading to oscillatory patterns. March (July) is the month with the lowest (highest) ABL mean. In March, the ABL at the base of the Valley is less than the height of surrounding mountains, leading to particulate matter accumulation.

Characterization of the Atmospheric Boundary Layer Over Aburrá Valley Region (Colombia) Using Remote Sensing and Radiosonde Data

NASA Astrophysics Data System (ADS)

Harlow, R. C.; Blockley, E. W.; Brooks, I. M.; Essery, R.; Milton, S.; Renfrew, I.; Vosper, S.

2016-12-01

The spatio-temporal evolution of the Atmospheric Boundary Layer (ABL) in the Aburrá Valley, a narrow highly complex mountainous terrain located in the Colombian Andes, is studied using different datasets including radiosonde and remote sensors from the meteorological network of the Aburrá Valley Early Warning System. Different techniques are developed in order to estimate Mixed Layer Height (MLH) based on variance of the ceilometer backscattering profiles. The Medellín metropolitan area, home of 4.5 million people, is located on the base and the hills of the valley. The generally large aerosol load within the valley from anthropogenic emissions allows the use of ceilometer retrievals of the MLH, especially under stable atmospheric conditions (late at night and early in the morning). Convective atmospheres, however, favor the aerosol dispersion which in turns increases the uncertainty associated with the estimation of the Convective Boundary Layer using ceilometer retrievals. A multi-sensor technique is also developed based on Richardson Number estimations using a Radar Wind Profiler combined with a Microwave Radiometer. Results of this technique seem to be more accurate thorough the diurnal cycle. ABL retrievals are available from October 2014 to April 2017. The diurnal cycle of the ABL exhibits monomodal behavior, highly influenced by the evolution of the potential temperature profile, and the turbulent fluxes near the surface. On the other hand, the backscattering diurnal cycle presents a bimodal structure, showing that the amount of aerosol particles at the lower troposphere is strongly influenced by anthropogenic emissions, dispersion conditioned by topography and by the ABL dynamics, conditioning the available vertical height for the pollutants to interact and disperse. Nevertheless, the amount, distribution or type of atmospheric aerosols does not appear to have a first order influence on the MLH variations or evolution. Results also show that intra-annual and interannual variations of cloudiness and surface incident radiation strongly condition the ABL expansion rate leading to oscillatory patterns. March (July) is the month with the lowest (highest) ABL mean. In March, the ABL at the base of the Valley is less than the height of surrounding mountains, leading to particulate matter accumulation.

Detecting volcanic SO2 emissions with the Infrared Atmospheric Sounding Interferometer

NASA Astrophysics Data System (ADS)

Taylor, Isabelle; Carboni, Elisa; Mather, Tamsin; Grainger, Don

2017-04-01

Sulphur dioxide (SO2) emissions are one of the many hazards associated with volcanic activity. Close to the volcano they have negative impacts on human and animal health and affect the environment. Further afield they present a hazard to aviation (as well as being a proxy for volcanic ash) and can cause global changes to climate. These are all good reasons for monitoring gas emissions at volcanoes and this monitoring can also provide insight into volcanic, magmatic and geothermal processes. Advances in satellite technology mean that it is now possible to monitor these emissions from space. The Infrared Atmospheric Sounding Interferometer (IASI) on board the European Space Agency's MetOp satellites is commonly used, alongside other satellite products, for detecting SO2 emissions across the globe. A fast linear retrieval developed in Oxford separates the signal of the target species (SO2) from the spectral background by representing background variability (determined from pixels containing no SO2) in a background covariance matrix. SO2 contaminated pixels can be distinguished from this quickly, facilitating the use of this algorithm for near real time monitoring and for scanning of large datasets for signals to explore further with a full retrieval. In this study, the retrieval has been applied across the globe to identify volcanic emissions. Elevated signals are identified at numerous volcanoes including both explosive and passive emissions, which match reports of activity from other sources. Elevated signals are also evident from anthropogenic activity. These results imply that this tool could be successfully used to identify and monitor activity across the globe.

Estimates of Power Plant NOx Emissions and Lifetimes from OMI NO2 Satellite Retrievals

NASA Technical Reports Server (NTRS)

de Foy, Benjamin; Lu, Zifeng; Streets, David G.; Lamsal, Lok N.; Duncan, Bryan N.

2015-01-01

Isolated power plants with well characterized emissions serve as an ideal test case of methods to estimate emissions using satellite data. In this study we evaluate the Exponentially-Modified Gaussian (EMG) method and the box model method based on mass balance for estimating known NOx emissions from satellite retrievals made by the Ozone Monitoring Instrument (OMI). We consider 29 power plants in the USA which have large NOx plumes that do not overlap with other sources and which have emissions data from the Continuous Emission Monitoring System (CEMS). This enables us to identify constraints required by the methods, such as which wind data to use and how to calculate background values. We found that the lifetimes estimated by the methods are too short to be representative of the chemical lifetime. Instead, we introduce a separate lifetime parameter to account for the discrepancy between estimates using real data and those that theory would predict. In terms of emissions, the EMG method required averages from multiple years to give accurate results, whereas the box model method gave accurate results for individual ozone seasons.

A Satellite-Based Imaging Instrumentation Concept for Hyperspectral Thermal Remote Sensing.

PubMed

Udelhoven, Thomas; Schlerf, Martin; Segl, Karl; Mallick, Kaniska; Bossung, Christian; Retzlaff, Rebecca; Rock, Gilles; Fischer, Peter; Müller, Andreas; Storch, Tobias; Eisele, Andreas; Weise, Dennis; Hupfer, Werner; Knigge, Thiemo

2017-07-01

This paper describes the concept of the hyperspectral Earth-observing thermal infrared (TIR) satellite mission HiTeSEM (High-resolution Temperature and Spectral Emissivity Mapping). The scientific goal is to measure specific key variables from the biosphere, hydrosphere, pedosphere, and geosphere related to two global problems of significant societal relevance: food security and human health. The key variables comprise land and sea surface radiation temperature and emissivity, surface moisture, thermal inertia, evapotranspiration, soil minerals and grain size components, soil organic carbon, plant physiological variables, and heat fluxes. The retrieval of this information requires a TIR imaging system with adequate spatial and spectral resolutions and with day-night following observation capability. Another challenge is the monitoring of temporally high dynamic features like energy fluxes, which require adequate revisit time. The suggested solution is a sensor pointing concept to allow high revisit times for selected target regions (1-5 days at off-nadir). At the same time, global observations in the nadir direction are guaranteed with a lower temporal repeat cycle (>1 month). To account for the demand of a high spatial resolution for complex targets, it is suggested to combine in one optic (1) a hyperspectral TIR system with ~75 bands at 7.2-12.5 µm (instrument NEDT 0.05 K-0.1 K) and a ground sampling distance (GSD) of 60 m, and (2) a panchromatic high-resolution TIR-imager with two channels (8.0-10.25 µm and 10.25-12.5 µm) and a GSD of 20 m. The identified science case requires a good correlation of the instrument orbit with Sentinel-2 (maximum delay of 1-3 days) to combine data from the visible and near infrared (VNIR), the shortwave infrared (SWIR) and TIR spectral regions and to refine parameter retrieval.

Extending the Deep Blue aerosol record from SeaWiFS and MODIS to NPP-VIIRS

NASA Technical Reports Server (NTRS)

Sayer, Andrew M.; Hsu, Nai-Yung Christina; Bettenhausen, Corey; Lee, Jaehwa

2015-01-01

Deep Blue expands AOD coverage to deserts and other bright surfaces. Using multiple similar satellite sensors enables us to obtain a long data record. The Deep Blue family consists of three separate aerosol optical depth (AOD) retrieval algorithms: 1. Bright Land: Surface reflectance database, BRDF correction. AOD retrieved separately at each of 412, 470/490, (650) nm. SSA retrieved for heavy dust events. 2. Dark Land: Spectral/directional surface reflectance relationship. AOD retrieved separately at 470/490 and 650 nm. 3. Water: Surface BRDF including glint, foam, underlight. Multispectral inversion (Not present in MODISdataset) All report the AOD at 550 nm, and Ångström exponent (AE).

Towards Interpreting the Signal of CO2 Emissions from Megacities by Applying a Lagrangian Receptor-oriented Model to OCO-2 XCO2 data

NASA Astrophysics Data System (ADS)

Wu, D.; Lin, J. C.; Oda, T.; Ye, X.; Lauvaux, T.; Yang, E. G.; Kort, E. A.

2017-12-01

Urban regions are large emitters of CO2 whose emission inventories are still associated with large uncertainties. Therefore, a strong need exists to better quantify emissions from megacities using a top-down approach. Satellites — e.g., the Orbiting Carbon Observatory 2 (OCO-2), provide a platform for monitoring spatiotemporal column CO2 concentrations (XCO2). In this study, we present a Lagrangian receptor-oriented model framework and evaluate "model-retrieved" XCO2 by comparing against OCO-2-retrieved XCO2, for three megacities/regions (Riyadh, Cairo and Pearl River Delta). OCO-2 soundings indicate pronounced XCO2 enhancements (dXCO2) when crossing Riyadh, which are successfully captured by our model with a slight latitude shift. From this model framework, we can identify and compare the relative contributions of dXCO2 resulted from anthropogenic emission versus biospheric fluxes. In addition, to impose constraints on emissions for Riyadh through inversion methods, three uncertainties sources are addressed in this study, including 1) transport errors, 2) receptor and model setups in atmospheric models, and 3) urban emission uncertainties. For 1), we calculate transport errors by adding a wind error component to randomize particle distributions. For 2), a set of sensitivity tests using bootstrap method is performed to describe proper ways to setup receptors in Lagrangian models. For 3), both emission uncertainties from the Fossil Fuel Data Assimilation System (FFDAS) and the spread among three emission inventories are used to approximate an overall fractional uncertainty in modeled anthropogenic signal (dXCO2.anthro). Lastly, we investigate the definition of background (clean) XCO2 for megacities from retrieved XCO2 by means of statistical tools and our model framework.

Observations of C-Band Brightness Temperature and Ocean Surface Wind Speed and Rain Rate in Hurricanes Earl And Karl (2010)

NASA Technical Reports Server (NTRS)

Miller, Timothy; James, Mark; Roberts, Brent J.; Biswax, Sayak; Uhlhorn, Eric; Black, Peter; Linwood Jones, W.; Johnson, Jimmy; Farrar, Spencer; Sahawneh, Saleem

2012-01-01

Ocean surface emission is affected by: a) Sea surface temperature. b) Wind speed (foam fraction). c) Salinity After production of calibrated Tb fields, geophysical fields wind speed and rain rate (or column) are retrieved. HIRAD utilizes NASA Instrument Incubator Technology: a) Provides unique observations of sea surface wind, temp and rain b) Advances understanding & prediction of hurricane intensity c) Expands Stepped Frequency Microwave Radiometer capabilities d) Uses synthetic thinned array and RFI mitigation technology of Lightweight Rain Radiometer (NASA Instrument Incubator) Passive Microwave C-Band Radiometer with Freq: 4, 5, 6 & 6.6 GHz: a) Version 1: H-pol for ocean wind speed, b) Version 2: dual ]pol for ocean wind vectors. Performance Characteristics: a) Earth Incidence angle: 0deg - 60deg, b) Spatial Resolution: 2-5 km, c) Swath: approx.70 km for 20 km altitude. Observational Goals: WS 10 - >85 m/s RR 5 - > 100 mm/hr.

Water Cycling in the North Polar Region of Mars

NASA Technical Reports Server (NTRS)

Tamppari, L. K.; Smith, M. D.; Bass, D. S.

2003-01-01

To date, there has been no comprehensive study to understand the partitioning of water into vapor and ice clouds, and the associated effects of dust and surface temperature in the north polar region. Ascertaining the degree to which water is transported out of the cap region versus within the cap region will give much needed insight into the overall story of water cycling on a seasonal basis. In particular, understanding the mechanism for the polar cap surface albedo changes would go along way in comprehending the sources and sinks of water in the northern polar region. We approach this problem by examining Thermal Emission Spectrometer (TES) atmospheric and surface data acquired in the northern summer season and comparing it to Viking data when possible. Because the TES instrument spans the absorption bands of water vapor, water ice, dust, and measures surface temperature, all three aerosols and surface temperature can be retrieved simultaneously. This presentation will show our latest results on the water vapor, water-ice clouds seasonal and spatial distributions, as well as surface temperatures and dust distribution which may lend insight into where the water is going.

Surface Reflectance of Mars Observed by CRISM-MRO: 1. Multi-angle Approach for Retrieval of Surface Reflectance from CRISM Observations (mars-reco)

NASA Technical Reports Server (NTRS)

Ceamanos, Xavier; Doute, S.; Fernando, J.; Pinet, P.; Lyapustin, A.

2013-01-01

This article addresses the correction for aerosol effects in near-simultaneous multiangle observations acquired by the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) aboard the Mars Reconnaissance Orbiter. In the targeted mode, CRISM senses the surface of Mars using 11 viewing angles, which allow it to provide unique information on the scattering properties of surface materials. In order to retrieve these data, however, appropriate strategies must be used to compensate the signal sensed by CRISM for aerosol contribution. This correction is particularly challenging as the photometric curve of these suspended particles is often correlated with the also anisotropic photometric curve of materials at the surface. This article puts forward an innovative radiative transfer based method named Multi-angle Approach for Retrieval of Surface Reflectance from CRISM Observations (MARS-ReCO). The proposed method retrieves photometric curves of surface materials in reflectance units after removing aerosol contribution. MARS-ReCO represents a substantial improvement regarding previous techniques as it takes into consideration the anisotropy of the surface, thus providing more realistic surface products. Furthermore, MARS-ReCO is fast and provides error bars on the retrieved surface reflectance. The validity and accuracy of MARS-ReCO is explored in a sensitivity analysis based on realistic synthetic data. According to experiments, MARS-ReCO provides accurate results (up to 10 reflectance error) under favorable acquisition conditions. In the companion article, photometric properties of Martian materials are retrieved using MARS-ReCO and validated using in situ measurements acquired during the Mars Exploration Rovers mission.

USER'S GUIDE FOR GLOED VERSION 1.0 - THE GLOBAL EMISSIONS DATABASE

EPA Science Inventory

The document is a user's guide for the EPA-developed, powerful software package, Global Emissions Database (GloED). GloED is a user-friendly, menu-driven tool for storing and retrieving emissions factors and activity data on a country-specific basis. Data can be selected from dat...

Intercomparison of MODIS Albedo Retrievals and In Situ Measurements Across the Global FLUXNET Network

NASA Technical Reports Server (NTRS)

Cescatti, Alessandro; Marcolla, Barbara; Vannan, Suresh K. Santhana; Pan, Jerry Yun; Roman, Miguel O.; Yang, Xiaoyuan; Ciais, Philippe; Cook, Robert B.; Law, Beverly E.; Matteucci, Girogio;

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.

Analysis of Retrieved Hubble Space Telescope Thermal Control Materials

NASA Technical Reports Server (NTRS)

Townsend, Jacqueline A.; Hansen, Patricia A.; Dever, Joyce A.; Triolo, Jack J.

1998-01-01

The mechanical and optical properties of the thermal control materials on the Hubble Space Telescope (HST) have degraded over the nearly seven years the telescope has been in orbit. Astronaut observations and photographs from the Second Servicing Mission (SM2) revealed large cracks in the metallized Teflon FEP, the outer-layer of the multi-layer insulation (MLI), in many locations around the telescope. Also, the emissivity of the bonded metallized Teflon FEP radiator surfaces of the telescope has increased over time. Samples of the top layer of the MLI and radiator material were retrieved during SM2, and a thorough investigation into the de-radiation followed in order to determine the primary cause of the damage. Mapping of the cracks on HST and the ground testing showed that thermal cycling with deep-layer damage from electron and proton radiation are necessary to cause the observed embrittlement. Further, strong, evidence was found indicating that chain scission (reduced molecular weight) is the dominant form of damage to the metallized Teflon FEP.

Local Time Variation of Water Ice Clouds on Mars as Observed by TES During Aerobraking.

NASA Astrophysics Data System (ADS)

AlJanaahi, A. A.; AlShamsi, M. R.; Smith, M. D.; Altunaiji, E. S.; Edwards, C. S.

2016-12-01

The large elliptical orbit during Mars Global Surveyor aerobraking enabled sampling the martian atmosphere over many local times. The Thermal Emission Spectrometer (TES) aerobraking spectra were taken between Mars Year 23, Ls=180° and Mars Year 24, Ls=30°. These early data from before the main "mapping" part of the mission have been mostly overlooked, and relatively little analysis has been done with them. These datasets have not been used before to study local time variation. Radiative transfer modeling is used to fit the spectra to retrieve surface and atmospheric temperature, and dust and water ice optical depths. Retrievals show significant and systematic variation in water ice cloud optical depth as a function of local time. Cloud optical depth is higher in the early morning (before 9:00) and in the evening (after 17:00) for all seasons observed (Ls=180°-30°). Clouds form consistently in the Tyrrhena region and in the area around Tharsis.

The Global Search for Abiogenic GHGs, via Methane Isotopes and Ethane

NASA Astrophysics Data System (ADS)

Malina, Edward; Muller, Jan-Peter; Walton, David; Potts, Dale

2015-04-01

The importance of Methane as an anthropogenic Green House Gas (GHG) is well recognized in the scientific community, and is second only to Carbon Dioxide in terms of influence on the Earth's radiation budget (Parker, et al, 2011) suggesting that the ability to apportion the source of the methane (whether it is biogenic, abiogenic or thermogenic) has never been more important. It has been proposed (Etiope, 2009) that it may be possible to distinguish between a biogenic methane source (e.g. bacteria fermentation) and an abiogenic source (e.g. gas seepage or fugitive emissions) via the retrieval of the abundances of methane isotopes (12CH4 and 13CH4) and through the ratio of ethane (C2H6) to methane (CH4) concentrations. Using ultra fine spectroscopy (<0.2cm-1 spectral resolution) from Fourier Transform Spectrometers (FTS) based on the SCISAT-1 (ACE-FTS) and GOSAT (TANSO-FTS) we are developing a retrieval scheme to map global emissions of abiogenic and biogenic methane, and provide insight into how these variations in methane might drive atmospheric chemistry, focusing on the lower levels of the atmosphere. Using HiTran2012 simulations, we show that it is possible to distinguish between methane isotopes using the FTS based instruments on ACE and GOSAT, and retrieve the abundances in the Short Wave Infra-red (SWIR) at 1.65μm, 2.3μm, 3.3μm and Thermal IR, 7.8μm wavebands for methane, and the 3.3μm and 7μm wavebands for ethane. Initially we use the spectral line database HITRAN to determine the most appropriate spectral waveband to retrieve methane isotopes (and ethane) with minimal water vapour, CO2 and NO2 impact. Following this, we have evaluated the detectability of these trace gases using the more sophisticated Radiative Transfer Models (RTMs) SCIATRAN, the Oxford RFM and MODTRAN 5 in the SWIR, in order to determine the barriers to retrieving methane isotopes in both ACE (limb profile) and GOSAT (nadir measurements) instruments, including a preliminary investigation into the effects of clouds, aerosols, surface reflectance on the retrieval of methane isotopes. The aim of these RTM simulations is to further narrow down the spectral regions (originally identified in the HITRAN assessment) where methane isotopes can/may be retrieved from orbit. The key outputs from the RTM study are absorption and radiance data, which allow us to identify the cleanest methane regions, and the likely SNR achievable in these regions. Finally we show some of the results of a study where we compare the output from each of the RTMs used in this study (SCIATRAN, ORFM and MODTRAN), in order to gain some confidence and insight into the strengths and weaknesses of the RTM outputs, using MODTRAN as a benchmark. References: Bernath, P. F. (2005). Atmospheric Chemistry Experiment (ACE): Mission overview. Geophys. Res. Lett. 32: L15S01. Etiope, G. (2009). Natural emissions of methane from geological seepage in Europe. Atmospheric Environment Journal. 2009 vol. 43(7) pp. 1430-1443. JAXA (2012). "Overview of the "IBUKI"(GOSAT)." Retrieved 05-03-2014, 2014, from http://www.jaxa.jp/countdown/f15/overview/ibuki_e.html. Parker, R, et al (2011). GOSAT "Proxy" Methane v4 - Updated March 2013. Accessed 11/04/14 at 08:13. URL: http://www.leos.le.ac.uk/GHG/data/styled/index.html.

Cloud characterization and clear-sky correction from Landsat-7

USGS Publications Warehouse

Cahalan, Robert F.; Oreopoulos, L.; Wen, G.; Marshak, S.; Tsay, S. -C.; DeFelice, Tom

2001-01-01

Landsat, with its wide swath and high resolution, fills an important mesoscale gap between atmospheric variations seen on a few kilometer scale by local surface instrumentation and the global view of coarser resolution satellites such as MODIS. In this important scale range, Landsat reveals radiative effects on the few hundred-meter scale of common photon mean-free-paths, typical of scattering in clouds at conservative (visible) wavelengths, and even shorter mean-free-paths of absorptive (near-infrared) wavelengths. Landsat also reveals shadowing effects caused by both cloud and vegetation that impact both cloudy and clear-sky radiances. As a result, Landsat has been useful in development of new cloud retrieval methods and new aerosol and surface retrievals that account for photon diffusion and shadowing effects. This paper discusses two new cloud retrieval methods: the nonlocal independent pixel approximation (NIPA) and the normalized difference nadir radiance method (NDNR). We illustrate the improvements in cloud property retrieval enabled by the new low gain settings of Landsat-7 and difficulties found at high gains. Then, we review the recently developed “path radiance” method of aerosol retrieval and clear-sky correction using data from the Department of Energy Atmospheric Radiation Measurement (ARM) site in Oklahoma. Nearby clouds change the solar radiation incident on the surface and atmosphere due to indirect illumination from cloud sides. As a result, if clouds are nearby, this extra side-illumination causes clear pixels to appear brighter, which can be mistaken for extra aerosol or higher surface albedo. Thus, cloud properties must be known in order to derive accurate aerosol and surface properties. A three-dimensional (3D) Monte Carlo (MC) radiative transfer simulation illustrates this point and suggests a method to subtract the cloud effect from aerosol and surface retrievals. The main conclusion is that cloud, aerosol, and surface retrievals are linked and must be treated as a combined system. Landsat provides the range of scales necessary to observe the 3D cloud radiative effects that influence joint surface-atmospheric retrievals.

Characterizing a New Surface-Based Shortwave Cloud Retrieval Technique, Based on Transmitted Radiance for Soil and Vegetated Surface Types

NASA Technical Reports Server (NTRS)

Coddington, Odele; Pilewskie, Peter; Schmidt, K. Sebastian; McBride, Patrick J.; Vukicevic, Tomislava

2013-01-01

This paper presents an approach using the GEneralized Nonlinear Retrieval Analysis (GENRA) tool and general inverse theory diagnostics including the maximum likelihood solution and the Shannon information content to investigate the performance of a new spectral technique for the retrieval of cloud optical properties from surface based transmittance measurements. The cumulative retrieval information over broad ranges in cloud optical thickness (tau), droplet effective radius (r(sub e)), and overhead sun angles is quantified under two conditions known to impact transmitted radiation; the variability in land surface albedo and atmospheric water vapor content. Our conclusions are: (1) the retrieved cloud properties are more sensitive to the natural variability in land surface albedo than to water vapor content; (2) the new spectral technique is more accurate (but still imprecise) than a standard approach, in particular for tau between 5 and 60 and r(sub e) less than approximately 20 nm; and (3) the retrieved cloud properties are dependent on sun angle for clouds of tau from 5 to 10 and r(sub e) less than 10 nm, with maximum sensitivity obtained for an overhead sun.

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.

Synergy of the SimSphere land surface process model with ASTER imagery for the retrieval of spatially distributed estimates of surface turbulent heat fluxes and soil moisture content

NASA Astrophysics Data System (ADS)

Petropoulos, George; Wooster, Martin J.; Carlson, Toby N.; Drake, Nick

2010-05-01

Accurate information on spatially explicit distributed estimates of key land-atmosphere fluxes and related land surface parameters is of key importance in a range of disciplines including hydrology, meteorology, agriculture and ecology. Estimation of those parameters from remote sensing frequently employs the integration of such data with mathematical representations of the transfers of energy, mass and radiation between soil, vegetation and atmosphere continuum, known as Soil Vegetation Atmosphere Transfer (SVAT) models. The ability of one such inversion modelling scheme to resolve for key surface energy fluxes and of soil surface moisture content is examined here using data from a multispectral high spatial resolution imaging instrument, the Advanced Spaceborne Thermal Emission and Reflection Scanning Radiometer (ASTER) and SimSphere one-dimensional SVAT model. Accuracy of the investigated methodology, so-called as the "triangle" method, is verified using validated ground observations obtained from selected days collected from nine CARBOEUROPE IP sites representing a variety of climatic, topographic and environmental conditions. Subsequently, a new framework is suggested for the retrieval of two additional parameters by the investigated method, namely the Evaporative (EF) and the Non-Evaporative (NEF) Fractions. Results indicated a close agreement between the inverted surface fluxes and surface moisture availability maps as well as of the EF and NEF parameters with the observations both spatially and temporally with accuracies comparable to those obtained in similar experiments with high spatial resolution data. Inspection of the inverted surface fluxes maps regionally, showed an explainable distribution in the range of the inverted parameters in relation with the surface heterogeneity. Overall performance of the "triangle" inversion methodology was found to be affected predominantly by the SVAT model "correct" initialisation representative of the test site environment, most importantly the atmospheric conditions required in the SVAT model initial conditions. This study represents the first comprehensive evaluation of the performance of this particular methodological implementation at a European setting using the SimSphere SVAT with the ASTER data. The present work is also very timely in that, a variation of this specific inversion methodology has been proposed for the operational retrieval of the soil surface moisture content by National Polar-orbiting Operational Environmental Satellite System (NPOESS), in a series of satellite platforms that are due to be launched in the next 12 years starting from 2012. KEYWORDS: micrometeorology, surface heat fluxes, soil moisture content, ASTER, triangle method, SimSphere, CarboEurope IP

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.

Retrieval with Infrared Atmospheric Sounding Interferometer and Validation during JAIVEx

NASA Technical Reports Server (NTRS)

Zhou, Daniel K.; Liu, Xu; Larar, Allen M.; Smith, William L.; Taylor, Jonathan P.; Schluessel, Peter; Strow, L. Larrabee; Mango, Stephen A.

2008-01-01

A state-of-the-art IR-only retrieval algorithm has been developed with an all-season-global EOF Physical Regression and followed by 1-D Var. Physical Iterative Retrieval for IASI, AIRS, and NAST-I. The benefits of this retrieval are to produce atmospheric structure with a single FOV horizontal resolution (approx. 15 km for IASI and AIRS), accurate profiles above the cloud (at least) or down to the surface, surface parameters, and/or cloud microphysical parameters. Initial case study and validation indicates that surface, cloud, and atmospheric structure (include TBL) are well captured by IASI and AIRS measurements. Coincident dropsondes during the IASI and AIRS overpasses are used to validate atmospheric conditions, and accurate retrievals are obtained with an expected vertical resolution. JAIVEx has provided the data needed to validate the retrieval algorithm and its products which allows us to assess the instrument ability and/or performance. Retrievals with global coverage are under investigation for detailed retrieval assessment. It is greatly desired that these products be used for testing the impact on Atmospheric Data Assimilation and/or Numerical Weather Prediction.

Atmospheric, Cloud, and Surface Parameters Retrieved from Satellite Ultra-spectral Infrared Sounder Measurements

NASA Technical Reports Server (NTRS)

Zhou, Daniel K.; Liu, Xu; Larar, Allen M.; Smith, William L.; Yang, Ping; Schluessel, Peter; Strow, Larrabee

2007-01-01

An advanced retrieval algorithm with a fast radiative transfer model, including cloud effects, is used for atmospheric profile and cloud parameter retrieval. This physical inversion scheme has been developed, dealing with cloudy as well as cloud-free radiance observed with ultraspectral infrared sounders, to simultaneously retrieve surface, atmospheric thermodynamic, and cloud microphysical parameters. A fast radiative transfer model, which applies to the clouded atmosphere, is used for atmospheric profile and cloud parameter retrieval. A one-dimensional (1-d) variational multivariable inversion solution is used to improve an iterative background state defined by an eigenvector-regression-retrieval. The solution is iterated in order to account for non-linearity in the 1-d variational solution. This retrieval algorithm is applied to the MetOp satellite Infrared Atmospheric Sounding Interferometer (IASI) launched on October 19, 2006. IASI possesses an ultra-spectral resolution of 0.25 cm(exp -1) and a spectral coverage from 645 to 2760 cm(exp -1). Preliminary retrievals of atmospheric soundings, surface properties, and cloud optical/microphysical properties with the IASI measurements are obtained and presented.

Multiscale comparison of GPM radar and passive microwave precipitation fields over oceans and land: effective resolution and global/regional/local diagnostics for improving retrieval algorithms

NASA Astrophysics Data System (ADS)

Guilloteau, C.; Foufoula-Georgiou, E.; Kummerow, C.; Kirstetter, P. E.

2017-12-01

A multiscale approach is used to compare precipitation fields retrieved from GMI using the last version of the GPROF algorithm (GPROF-2017) to the DPR fields all over the globe. Using a wavelet-based spectral analysis, which renders the multi-scale decompositions of the original fields independent of each other spatially and across scales, we quantitatively assess the various scales of variability of the retrieved fields, and thus define the spatially-variable "effective resolution" (ER) of the retrievals. Globally, a strong agreement is found between passive microwave and radar patterns at scales coarser than 80km. Over oceans the patterns match down to the 20km scale. Over land, comparison statistics are spatially heterogeneous. In most areas a strong discrepancy is observed between passive microwave and radar patterns at scales finer than 40-80km. The comparison is also supported by ground-based observations over the continental US derived from the NOAA/NSSL MRMS suite of products. While larger discrepancies over land than over oceans are classically explained by land complex surface emissivity perturbing the passive microwave retrieval, other factors are investigated here, such as intricate differences in the storm structure over oceans and land. Differences in term of statistical properties (PDF of intensities and spatial organization) of precipitation fields over land and oceans are assessed from radar data, as well as differences in the relation between the 89GHz brightness temperature and precipitation. Moreover, the multiscale approach allows quantifying the part of discrepancies caused by miss-match of the location of intense cells and instrument-related geometric effects. The objective is to diagnose shortcomings of current retrieval algorithms such that targeted improvements can be made to achieve over land the same retrieval performance as over oceans.

Could we constrain some major properties of hot Super-Earths with NIRSPEC-JWT spectra?

NASA Astrophysics Data System (ADS)

Rouan, D.; Samuel, B.; Leconte, J.; Léger, A.

2014-03-01

CoRot-7b and Kepler-10b were the first super-earths with solid surfaces identified thanks to transits detection from space using ultra-precise photometry. At only a few stellar radii from their host stars, these two rocky planets are very hot. The current model (Leger et al., 2011) is that they are atmosphere-free, in a synchronous rotation state, receive strong stellar winds and fluxes and that they feature a lava ocean on their hot dayside. We show how observations with NIRSPEC-JWST could further confirm and constrain, or reject the atmosphere-free lava ocean planet model for very hot super earths. Taking CoRoT-7b as a baseline, we explore the consequences on the phase-curve of a non tidal-locked rotation, of the presence/absence of an atmosphere, and of different values of the surface albedo. Simulated observations of the reflected light and thermal emission using NIRSPEC-JWST are used to look for detectable signatures of those peculiar conditions. We also study how to retrieve the temperature map of the surface. We demonstrate that thanks to the broad range of wavelengths accessible with JWST, we should be able to constrain several parameters: i) the Bond albedo is retrieved to within ±0.03 in most cases; ii) the lag effect allows to retrieve the rotation period of a non phaselocked planet to within 3 hours; iii) the shortest rotation period compatible with an actually phase-locked planet is in the range 30 - 800 h depending on the thermal properties of the soil; iv) the presence of a thick atmosphere with a pressure of one bar, and an specific opacity higher than 10-5m-2kg-1 is detectable; v) The latitudinal temperature profile can be retrieved to within 30 K for a signal to noise ratio of 7.5. We conclude that it should thus be possible to distinguish the situation of a lava ocean with phase-locking and no atmosphere from other cases. In addition, obtaining the surface temperature map and the albedo will bring important constraints on the nature or the physical state of the soil of hot super-earths. We examine the extension of this method to other cases of super-earths.

AATSR land surface temperature product algorithm verification over a WATERMED site

NASA Astrophysics Data System (ADS)

Noyes, E. J.; Sòria, G.; Sobrino, J. A.; Remedios, J. J.; Llewellyn-Jones, D. T.; Corlett, G. K.

A new operational Land Surface Temperature (LST) product generated from data acquired by the Advanced Along-Track Scanning Radiometer (AATSR) provides the opportunity to measure LST on a global scale with a spatial resolution of 1 km2. The target accuracy of the product, which utilises nadir data from the AATSR thermal channels at 11 and 12 μm, is 2.5 K for daytime retrievals and 1.0 K at night. We present the results of an experiment where the performance of the algorithm has been assessed for one daytime and one night time overpass occurring over the WATERMED field site near Marrakech, Morocco, on 05 March 2003. Top of atmosphere (TOA) brightness temperatures (BTs) are simulated for 12 pixels from each overpass using a radiative transfer model, with the LST product and independent emissivity values and atmospheric data as inputs. We have estimated the error in the LST product over this biome for this set of conditions by applying the operational AATSR LST retrieval algorithm to the modelled BTs and comparing the results with the original AATSR LSTs input into the model. An average bias of -1.00 K (standard deviation 0.07 K) for the daytime data, and -1.74 K (standard deviation 0.02 K) for the night time data is obtained, which indicates that the algorithm is yielding an LST that is too cold under these conditions. While these results are within specification for daytime retrievals, this suggests that the target accuracy of 1.0 K at night is not being met within this biome.

Evaluation of black carbon estimations in global aerosol models

NASA Astrophysics Data System (ADS)

Koch, D.; Schulz, M.; Kinne, S.; McNaughton, C.; Spackman, J. R.; Balkanski, Y.; Bauer, S.; Berntsen, T.; Bond, T. C.; Boucher, O.; Chin, M.; Clarke, A.; de Luca, N.; Dentener, F.; Diehl, T.; Dubovik, O.; Easter, R.; Fahey, D. W.; Feichter, J.; Fillmore, D.; Freitag, S.; Ghan, S.; Ginoux, P.; Gong, S.; Horowitz, L.; Iversen, T.; Kirkevåg, A.; Klimont, Z.; Kondo, Y.; Krol, M.; Liu, X.; Miller, R.; Montanaro, V.; Moteki, N.; Myhre, G.; Penner, J. E.; Perlwitz, J.; Pitari, G.; Reddy, S.; Sahu, L.; Sakamoto, H.; Schuster, G.; Schwarz, J. P.; Seland, Ø.; Stier, P.; Takegawa, N.; Takemura, T.; Textor, C.; van Aardenne, J. A.; Zhao, Y.

2009-11-01

We evaluate black carbon (BC) model predictions from the AeroCom model intercomparison project by considering the diversity among year 2000 model simulations and comparing model predictions with available measurements. These model-measurement intercomparisons include BC surface and aircraft concentrations, aerosol absorption optical depth (AAOD) retrievals from AERONET and Ozone Monitoring Instrument (OMI) and BC column estimations based on AERONET. In regions other than Asia, most models are biased high compared to surface concentration measurements. However compared with (column) AAOD or BC burden retreivals, the models are generally biased low. The average ratio of model to retrieved AAOD is less than 0.7 in South American and 0.6 in African biomass burning regions; both of these regions lack surface concentration measurements. In Asia the average model to observed ratio is 0.7 for AAOD and 0.5 for BC surface concentrations. Compared with aircraft measurements over the Americas at latitudes between 0 and 50N, the average model is a factor of 8 larger than observed, and most models exceed the measured BC standard deviation in the mid to upper troposphere. At higher latitudes the average model to aircraft BC ratio is 0.4 and models underestimate the observed BC loading in the lower and middle troposphere associated with springtime Arctic haze. Low model bias for AAOD but overestimation of surface and upper atmospheric BC concentrations at lower latitudes suggests that most models are underestimating BC absorption and should improve estimates for refractive index, particle size, and optical effects of BC coating. Retrieval uncertainties and/or differences with model diagnostic treatment may also contribute to the model-measurement disparity. Largest AeroCom model diversity occurred in northern Eurasia and the remote Arctic, regions influenced by anthropogenic sources. Changing emissions, aging, removal, or optical properties within a single model generated a smaller change in model predictions than the range represented by the full set of AeroCom models. Upper tropospheric concentrations of BC mass from the aircraft measurements are suggested to provide a unique new benchmark to test scavenging and vertical dispersion of BC in global models.

Space based inverse modeling of anthropogenic and natural emissions of nitrogen oxides over China: seasonal and interannual variability

NASA Astrophysics Data System (ADS)

Lin, J.-T.

2012-04-01

Nitrogen oxides (NOx ≡ NO + NO2) are important atmospheric constituents affecting the tropospheric chemistry and climate. They are emitted both from anthropogenic and from natural (soil, lightning, biomass burning, etc.) sources, and China has become a major region of increasing importance for anthropogenic sources. In a series of studies, satellite remote sensing for the vertical column densities (VCDs) of tropospheric nitrogen dioxide (NO2) is used to estimate anthropogenic and natural emissions of NOx over China. Focus is set on variations of emissions over a variety of time scales in response to the economic development of China, from the general growth in recent years to the economic downturn during late 2008 - mid 2009 to the holiday associated with the Chinese New Year. An attempt is made to reduce the effect of potential systematic errors in satellite retrievals by coupling data from multiple satellite instruments flying over China at different time of day. For 2006, anthropogenic emissions are separated from lightning and soil sources over East China by exploiting their different seasonality. For the first time, a systematic evaluation is conducted to quantify uncertainties in various aspects of model meteorology and chemistry affecting emission inversion for China and implications for simulations of other air pollution (e.g., near-surface ozone).

Quantifying the Influence of Agricultural Fires in Northwest India on Urban Air Pollution in Delhi, India.

NASA Astrophysics Data System (ADS)

Cusworth, D.; Mickley, L. J.; Payer Sulprizio, M.; Marlier, M. E.; DeFries, R. S.; Liu, T.; Guttikunda, S. K.

2017-12-01

In recent decades, farmers in northwest India have switched to mechanized combine harvesting to boost efficiency. This harvesting technique leaves abundant crop residue on the fields, which farmers burn to ready their fields for subsequent planting. A key question is to what extent the intense smoke emitted by these fires contributes to the already severe pollution in Delhi and across the heavily populated Indus-Ganges Plain, downwind of the fires. Using a combination of observed and modeled variables, including surface measurements of PM2.5, we quantify the magnitude of the influence of agricultural fire emissions on surface air pollution in Delhi. We first derive the signal of regional PM2.5 enhancements from the Delhi network of surface air monitors during each winter burning season (Oct. 17 - Nov. 30) for 2012-2016. We next use the Stochastic Time-Inverted Lagrangian Transport model (STILT) to generate particle back-trajectories from Delhi, which allows us to map the sensitivity of Delhi pollution to agricultural fires in each grid cell upwind. By combining these sensitivity maps with emissions from a suite of fire inventories, we can reproduce 15-36% of the weekly variability in observed PM2.5. Our method attributes 7-84% of maximum observed PM2.5 enhancement in Delhi to fires upwind, depending on the year and emission inventory. The large range of these attribution estimates points to the uncertainties in fire emission parameterizations, especially in regions where thick smoke may mask the hotspots of fire radiative power. Although our model can generally reproduce the largest PM2.5 enhancements in Delhi air quality for 1-3 consecutive days each fire season, it fails to capture many smaller daily enhancements, which we attribute to the challenge of detecting small fires in the satellite retrieval. By quantifying the magnitude of the influence of agricultural fire emissions on Delhi air pollution, our work helps clarify the pollution exposure and potential health risk of this harvesting practice.

The DMRT-ML Model: Numerical Simulations of the Microwave Emission of Snowpacks Based on the Dense Media Radiative Transfer Theory

NASA Technical Reports Server (NTRS)

Brucker, Ludovic; Picard, Ghislain; Roy, Alexandre; Dupont, Florent; Fily, Michel; Royer, Alain

2014-01-01

Microwave radiometer observations have been used to retrieve snow depth and snow water equivalent on both land and sea ice, snow accumulation on ice sheets, melt events, snow temperature, and snow grain size. Modeling the microwave emission from snow and ice physical properties is crucial to improve the quality of these retrievals. It also is crucial to improve our understanding of the radiative transfer processes within the snow cover, and the snow properties most relevant in microwave remote sensing. Our objective is to present a recent microwave emission model and its validation. The model is named DMRT-ML (DMRT Multi-Layer), and is available at http:lgge.osug.frpicarddmrtml.

Neural Systems behind Word and Concept Retrieval

ERIC Educational Resources Information Center

Damasio, H.; Tranel, D.; Grabowski, T.; Adolphs, R.; Damasio, A.

2004-01-01

Using both the lesion method and functional imaging (positron emission tomography) in large cohorts of subjects investigated with the same experimental tasks, we tested the following hypotheses: (A) that the retrieval of words which denote concrete entities belonging to distinct conceptual categories depends upon partially segregated regions in…

Simultaneous retrieval of daytime O(3P) and O3 concentrations in the altitude interval 80 - 100 km.

NASA Astrophysics Data System (ADS)

Yankovsky, Valentine; Manuilova, Rada; Koval, Andrey

2017-04-01

We propose methods of simultaneously independent retrievals of the key components of Mesosphere and Lower Thermosphere (MLT) [O3] and [O(3P)]. The altitude profile of ozone concentration, [O3], can be measured by direct method of the measurement of absorbing radiation from the Sun or the stars in the UV range of the spectrum. However, this method is most often realized in twilight. Retrieval of daytime [O3] depends on a prior information about the O(3P) altitude profile. Vice versa, atomic oxygen concentration, [O(3P)], is usually retrieved from the measured values of [O3]. The problem of independent and simultaneous retrieval of [O3] and [O(3P)] can be solved by using individual proxy for each of the target component. Using a sensitivity study and uncertainty analysis of the contemporary model of O3 and O2 photolysis in the MLT, YM2011, we determined that populations of three excited electronic-vibrational levels O2(b1, v = 0, 1, 2) and of metastable O(1D) atom depend on [O(3P)] and [O3] concentrations. For [O(3P)] retrieval the following transitions should be used: O2(b1, v') -> O2(X3, v") which produce emissions: (a) at 780.4 nm in the band (v' = 2, v" = 2) and at 697.0 nm in the band (2, 1) with the uncertainty of retrieval smaller than 30% for the whole altitude range 80 - 100 km; (b) at 771.0 nm in the band (1, 1), 688.4 nm in the band (1, 0) and at 874.4 nm in the band (1, 2) with the uncertainty of retrieval about 30% above 90 km. For [O3] retrieval the following transitions should be used: O2(b1, v') -> O2(X3, v") which produce emissions: (c) at 762.1 nm in the band (0, 0) and at 864.7 nm in the band (0, 1) with the uncertainty of retrieval 20 - 25% for the altitude range 80 - 85 km and smaller than 20% in the interval 85 - 95 km; (d) in the line of O(1D) 630.0 nm with the uncertainty of retrieval 10 - 15% in the interval 80 - 95 km. Above 95 km the uncertainty of [O3] retrieval grows and reaches up to 80% at 100 km for all suggested proxies. For simultaneously [O3] and [O(3P)] retrievals the observations of above mentioned emissions (a) or (b) and (c) or (d) could be used.

Atmospheric retrievals with the Tropospheric Emission Spectrometer (TES)

NASA Technical Reports Server (NTRS)

Bowman, K. W.

2003-01-01

The Tropospheric Emission Spectrometer (TES) on the EOS-Aura spacecraft will measure the global 3-dimensional distribution of ozone in the troposphere and many of the chemical species that are part of its formation and destruction.

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.

First Atmospheric Science Results from the Mars Exploration Rovers Mini-TES

NASA Technical Reports Server (NTRS)

Smith, Michael D.; Wolff, Michael J.; Lemmon, Mark T.; Spanovich, Nicole; Banfield, Don; Budney, Charles J.; Clancy, R. Todd; Ghosh, Amitabha; Landis, Geoffrey A.; Smith, Peter;

First Atmospheric Science Results from the Mars Exploration Rovers Mini-TES.

PubMed

Smith, Michael D; Wolff, Michael J; Lemmon, Mark T; Spanovich, Nicole; Banfield, Don; Budney, Charles J; Clancy, R Todd; Ghosh, Amitabha; Landis, Geoffrey A; Smith, Peter; Whitney, Barbara; Christensen, Philip R; Squyres, Steven W

2004-12-03

Thermal infrared spectra of the martian atmosphere taken by the Miniature Thermal Emission Spectrometer (Mini-TES) were used to determine the atmospheric temperatures in the planetary boundary layer and the column-integrated optical depth of aerosols. Mini-TES observations show the diurnal variation of the martian boundary layer thermal structure, including a near-surface superadiabatic layer during the afternoon and an inversion layer at night. Upward-looking Mini-TES observations show warm and cool parcels of air moving through the Mini-TES field of view on a time scale of 30 seconds. The retrieved dust optical depth shows a downward trend at both sites.

Polarimetric infrared imaging simulation of a synthetic sea surface with Mie scattering.

PubMed

He, Si; Wang, Xia; Xia, Runqiu; Jin, Weiqi; Liang, Jian'an

2018-03-01

A novel method to simulate the polarimetric infrared imaging of a synthetic sea surface with atmospheric Mie scattering effects is presented. The infrared emission, multiple reflections, and infrared polarization of the sea surface and the Mie scattering of aerosols are all included for the first time. At first, a new approach to retrieving the radiative characteristics of a wind-roughened sea surface is introduced. A two-scale method of sea surface realization and the inverse ray tracing of light transfer calculation are combined and executed simultaneously, decreasing the consumption of time and memory dramatically. Then the scattering process that the infrared light emits from the sea surface and propagates in the aerosol particles is simulated with a polarized light Monte Carlo model. Transformations of the polarization state of the light are calculated with the Mie theory. Finally, the polarimetric infrared images of the sea surface of different environmental conditions and detection parameters are generated based on the scattered light detected by the infrared imaging polarimeter. The results of simulation examples show that our polarimetric infrared imaging simulation can be applied to predict the infrared polarization characteristics of the sea surface, model the oceanic scene, and guide the detection in the oceanic environment.

Aerosol variation over Continental Europe from 1980 to 2015 Using ALAD Aerosol Retrievals

NASA Astrophysics Data System (ADS)

Che, Yahui; Xue, Yong; Mei, Linlu; Guang, Jie; She, Lu

2017-04-01

The Advanced Very High Resolution Radiometer (AVHRR) on-board National Oceanic and Atmospheric Administration (NOAA) series satellites has been used to observe the Earth and is the only spaceborne instrument which can provide users continuous long time series global coverage for more than 35 years since 1979. The initial purpose of AVHRR is for cloud detection and monitoring thermal emission of the Earth so that it lacks visible channels (only 0.64μm) and spaceborne which is unignorably unfavourable to its applications in aerosol retrieving over bright and inhomogeneous surface. Using AVHRR data, an Algorithm for the retrieval over Land of the Aerosol optical Depth (ALAD) was developed data which has great potential to be used to retrieve long time series aerosol globally from 1979 to now. The core of ALAD is to assume that the contribution of aerosol at 3.75μm wavelength to reflectance at top of the atmosphere (TOA) is negligible. At this basis, one stable and firm relationship between surface reflectance at 0.64μm and 3.75μm will be found by regression analysis at different land types after separating reflectance from radiance at 3.75μm. Then, an atmospheric transfer model is applied to calculate AOD at 0.64μm. In this study, we recalibrate AVHRR Global Area Coverage (GAC) data and then apply ALAD to calculate AOD over continental Europe (30°N to 80°N, 170°W to 40°E) to investigate aerosol changes and possible reason in past 35 years from 1981 to 2015. The retrieved AOD has been validated with ground-based data from Aerosols, Clouds, and Trace gases Research InfraStructure (ACTRIS) and AErosol RObotic NETwork (AERONET). The correlation of ALAD AOD with AERONET and ACTRIS is 0.77 and 0.66, respectively. Further, we also make long time series comparison of monthly averaged ALAD AOD with AERONET, ACTRIS and MODIS, showing that ALAD underestimate AOD a little. Finally, we find that the AOD over most areas in Continental Europe are less than 0.3, even less than 0.1, changing little without any obvious increase.

AIRS Version 6 Products and Data Services at NASA GES DISC

NASA Astrophysics Data System (ADS)

Ding, F.; Savtchenko, A. K.; Hearty, T. J.; Theobald, M. L.; Vollmer, B.; Esfandiari, E.

2013-12-01

The NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) is the home of processing, archiving, and distribution services for data from the Atmospheric Infrared Sounder (AIRS) mission. The AIRS mission is entering its 11th year of global observations of the atmospheric state, including temperature and humidity profiles, outgoing longwave radiation, cloud properties, and trace gases. The GES DISC, in collaboration with the AIRS Project, released data from the Version 6 algorithm in early 2013. The new algorithm represents a significant improvement over previous versions in terms of greater stability, yield, and quality of products. Among the most substantial advances are: improved soundings of Tropospheric and Sea Surface Temperatures; larger improvements with increasing cloud cover; improved retrievals of surface spectral emissivity; near-complete removal of spurious temperature bias trends seen in earlier versions; substantially improved retrieval yield (i.e., number of soundings accepted for output) for climate studies; AIRS-Only retrievals with comparable accuracy to AIRS+AMSU (Advanced Microwave Sounding Unit) retrievals; and more realistic hemispheric seasonal variability and global distribution of carbon monoxide. The GES DISC is working to bring the distribution services up-to-date with these new developments. Our focus is on popular services, like variable subsetting and quality screening, which are impacted by the new elements in Version 6. Other developments in visualization services, such as Giovanni, Near-Real Time imagery, and a granule-map viewer, are progressing along with the introduction of the new data; each service presents its own challenge. This presentation will demonstrate the most significant improvements in Version 6 AIRS products, such as newly added variables (higher resolution outgoing longwave radiation, new cloud property products, etc.), the new quality control schema, and improved retrieval yields. We will also demonstrate the various distribution and visualization services for AIRS data products. The cloud properties, model physics, and water and energy cycles research communities are invited to take advantage of the improvements in Version 6 AIRS products and the various services at GES DISC which provide them.

Extending MGS-TES Temperature Retrievals in the Martian Atmosphere up to 90 Km: Retrieval Approach and Results

NASA Technical Reports Server (NTRS)

Feofilov, A. G.; Kutepov, A. A.; Rezac, L.; Smith, M. D.

2015-01-01

This paper describes a methodology for performing a temperature retrieval in the Martian atmosphere in the 50-90 km altitude range using spectrally integrated 15 micrometers C02 limb emissions measured by the Thermal Emission Spectrometer (TES), the thermal infrared spectrometer on board the Mars Global Surveyor (MGS). We demonstrate that temperature retrievals from limb observations in the 75-90 km altitude range require accounting for the non-local thermodynamic equilibrium (non-LTE) populations of the C02(v2) vibrational levels. Using the methodology described in the paper, we have retrieved approximately 1200 individual temperature profiles from MGS TES limb observations in the altitude range between 60 and 90 km. 0ur dataset of retrieved temperature profiles is available for download in supplemental materials of this paper. The temperature retrieval uncertainties are mainly caused by radiance noise, and are estimated to be about 2 K at 60 km and below, 4 K at 70 km, 7 K at 80 km, 10 K at 85 km, and 20 K at 90 km. We compare the retrieved profiles to Mars Climate Database temperature profiles and find good qualitative agreement. Quantitatively, our retrieved profiles are in general warmer and demonstrate strong variability with the following values for bias and standard deviations (in brackets) compared to the Martian Year 24 dataset of the Mars Climate Database: 6 (+/-20) K at 60 km, 7.5 (+/-25) K at 65 km, 9 (+/-27) K at 70 km, 9.5 (+/-27) K at 75 km, 10 (+/-28) K at 80 km, 11 (+/-29) K at 85 km, and 11.5 (+/-31) K at 90 km. Possible reasons for the positive temperature bias are discussed. carbon dioxide molecular vibrations

Water Ice Clouds in the Martian Atmosphere: A View from MGS TES

NASA Technical Reports Server (NTRS)

Hale, A. S.; Tamppari, L. K.; Christensen, P. R.; Smith, M. D.; Bass, Deborah; Qu, Zheng; Pearl, J. C.

2005-01-01

We use the method of Tamppari et al. to map water ice clouds in the Martian atmosphere. This technique was originally developed to analyze the broadband Viking IRTM channels and we have now applied it to the TES data. To do this, the TES spectra are convolved to the IRTM bandshapes and spatial resolutions, enabling use of the same processing techniques as were used in Tamppari et al.. This retrieval technique relies on using the temperature difference recorded in the 20 micron and 11 micron IRTM bands (or IRTM convolved TES bands) to map cold water ice clouds above the warmer Martian surface. Careful removal of surface contributions to the observed radiance is therefore necessary, and we have used both older Viking-derived basemaps of the surface emissivity and albedo, and new MGS derived basemaps in order the explore any possible differences on cloud retrieval due to differences in surface contribution removal. These results will be presented in our poster. Our previous work has concentrated primarily on comparing MGS TES to Viking data; that work saw that large-scale cloud features, such as the aphelion cloud belt, are quite repeatable from year to year, though small scale behavior shows some variation. Comparison of Viking and MGS era cloud maps will be presented in our poster. In the current stage of our study, we have concentrated our efforts on close analysis of water ice cloud behavior in the northern summer of the three MGS mapping years on relatively small spatial scales, and present our results below. Additional information is included in the original extended abstract.

Emissions Estimation from Satellite Retrievals: a Review of Current Capability

NASA Technical Reports Server (NTRS)

Streets, David; Canty, Timothy; Carmichael, Gregory R.; deFoy, Benjamin; Dickerson, Russell R.; Duncan, Bryan N.; Edwards, David P.; Haynes, John A.; Henze, Daven K.; Houyoux, Marc R.;

Emissions estimation from satellite retrievals: A review of current capability

NASA Astrophysics Data System (ADS)

Streets, David G.; Canty, Timothy; Carmichael, Gregory R.; de Foy, Benjamin; Dickerson, Russell R.; Duncan, Bryan N.; Edwards, David P.; Haynes, John A.; Henze, Daven K.; Houyoux, Marc R.; Jacob, Daniel J.; Krotkov, Nickolay A.; Lamsal, Lok N.; Liu, Yang; Lu, Zifeng; Martin, Randall V.; Pfister, Gabriele G.; Pinder, Robert W.; Salawitch, Ross J.; Wecht, Kevin J.

2013-10-01

Since the mid-1990s a new generation of Earth-observing satellites has been able to detect tropospheric air pollution at increasingly high spatial and temporal resolution. Most primary emitted species can be measured by one or more of the instruments. This review article addresses the question of how well we can relate the satellite measurements to quantification of primary emissions and what advances are needed to improve the usability of the measurements by U.S. air quality managers. Built on a comprehensive literature review and comprising input by both satellite experts and emission inventory specialists, the review identifies several targets that seem promising: large point sources of NOx and SO2, species that are difficult to measure by other means (NH3 and CH4, for example), area sources that cannot easily be quantified by traditional bottom-up methods (such as unconventional oil and gas extraction, shipping, biomass burning, and biogenic sources), and the temporal variation of emissions (seasonal, diurnal, episodic). Techniques that enhance the usefulness of current retrievals (data assimilation, oversampling, multi-species retrievals, improved vertical profiles, etc.) are discussed. Finally, we point out the value of having new geostationary satellites like GEO-CAPE and TEMPO over North America that could provide measurements at high spatial (few km) and temporal (hourly) resolution.

The MIGHTI Wind Retrieval Algorithm: Description and Verification

NASA Astrophysics Data System (ADS)

Harding, Brian J.; Makela, Jonathan J.; Englert, Christoph R.; Marr, Kenneth D.; Harlander, John M.; England, Scott L.; Immel, Thomas J.

2017-10-01

We present an algorithm to retrieve thermospheric wind profiles from measurements by the Michelson Interferometer for Global High-resolution Thermospheric Imaging (MIGHTI) instrument on NASA's Ionospheric Connection Explorer (ICON) mission. MIGHTI measures interferometric limb images of the green and red atomic oxygen emissions at 557.7 nm and 630.0 nm, spanning 90-300 km. The Doppler shift of these emissions represents a remote measurement of the wind at the tangent point of the line of sight. Here we describe the algorithm which uses these images to retrieve altitude profiles of the line-of-sight wind. By combining the measurements from two MIGHTI sensors with perpendicular lines of sight, both components of the vector horizontal wind are retrieved. A comprehensive truth model simulation that is based on TIME-GCM winds and various airglow models is used to determine the accuracy and precision of the MIGHTI data product. Accuracy is limited primarily by spherical asymmetry of the atmosphere over the spatial scale of the limb observation, a fundamental limitation of space-based wind measurements. For 80% of the retrieved wind samples, the accuracy is found to be better than 5.8 m/s (green) and 3.5 m/s (red). As expected, significant errors are found near the day/night boundary and occasionally near the equatorial ionization anomaly, due to significant variations of wind and emission rate along the line of sight. The precision calculation includes pointing uncertainty and shot, read, and dark noise. For average solar minimum conditions, the expected precision meets requirements, ranging from 1.2 to 4.7 m/s.

Simutaneous Variational Retrievals of Temperature, Humidity, Surface and Cloud Properties from Satellite and Airborne Hyperspectral Infrared Sounder Data using the Havemann-Taylor Fast Radiative Transfer Code (HT-FRTC) as the Forward Model Operator

NASA Astrophysics Data System (ADS)

Havemann, S.; Thelen, J. C.; Harlow, R. C.

2016-12-01

Full scattering radiative transfer simulations for hyperspectral infrared and shortwave sounders are essential in order to be able to extract the maximal information content from these instruments for cloudy scenes and those with significant aerosol loading, but have been rarely done because of the high computational demands. The Havemann-Taylor Fast Radiative Transfer Code works in Principal Component space, reducing the computational demand by orders of magnitude thereby making fast simultaneous retrievals of vertical profiles of temperature and humidity, surface temperature and emissivity as well as cloud and aerosol properties feasible. Results of successful retrievals using IASI sounder data as well as data taken during flights of the Airborne Research Interferometer Evaluation System (ARIES) on board the FAAM Bae 146 aircraft will be presented. These will demonstrate that the use of all the instrument channels in PC space can provide valuable information both on temperature and humidity profiles relevant for NWP and on the cirrus cloud properties at the same time. There is very significant information on the humidity profile below semi-transparent cirrus to be gained from IR sounder data. The retrieved ice water content is in good agreement with airborne in-situ measurements during Lagrangian spiral descents. In addition to the full scattering calculations, the HT-FRTC has also been trained with a fast approximation to the scattering problem which reduces it to a clear-sky calculation but with a modified extinction (Chou scaling). Chou scaling is a reasonable approximation in the infrared but is very poor where the solar contribution becomes significant. The comparison of the retrieval performance with the full scattering solution and the Chou scaling solution in the forward model operator for infrared sounders shows that temperature and humidity profiles are only marginally degraded by the use of the Chou scaling approximation. Retrievals of the specific cloud parameters (ice water content, cirrus cloud thickness and cirrus cloud horizontal fraction) are however strongly negatively affected under the Chou scaling approximation. The aim is also to use HT-FRTC to run clear and cloudy simulations for the atmospheric state test set which has been prepared by the NASA/JPL/AIRS project.

Resolution Enhancement of Spaceborne Radiometer Images

NASA Technical Reports Server (NTRS)

Krim, Hamid

2001-01-01

Our progress over the last year has been along several dimensions: 1. Exploration and understanding of Earth Observatory System (EOS) mission with available data from NASA. 2. Comprehensive review of state of the art techniques and uncovering of limitations to be investigated (e.g. computational, algorithmic ...). and 3. Preliminary development of resolution enhancement algorithms. With the advent of well-collaborated satellite microwave radiometers, it is now possible to obtain long time series of geophysical parameters that are important for studying the global hydrologic cycle and earth radiation budget. Over the world's ocean, these radiometers simultaneously measure profiles of air temperature and the three phases of atmospheric water (vapor, liquid, and ice). In addition, surface parameters such as the near surface wind speed, the sea surface temperature, and the sea ice type and concentration can be retrieved. The special sensor microwaves imager SSM/I has wide application in atmospheric remote sensing over the ocean and provide essential inputs to numerical weather-prediction models. SSM/I data has also been used for land and ice studies, including snow cover classification measurements of soil and plant moisture contents, atmospheric moisture over land, land surface temperature and mapping polar ice. The brightness temperature observed by SSM/I is function of the effective brightness temperature of the earth's surface and the emission scattering and attenuation of the atmosphere. Advanced Microwave Scanning Radiometer (AMSR) is a new instrument that will measure the earth radiation over the spectral range from 7 to 90 GHz. Over the world's ocean, it will be possible to retrieve the four important geographical parameters SST, wind speed, vertically integrated water vapor, vertically integrated cloud liquid water L.

Advances in Satellite Remote Sensing of Particulate Air Pollution: From MISR to MAIA

NASA Astrophysics Data System (ADS)

Diner, D. J.; Burke, K.; Xu, F.; Garay, M. J.; Kalashnikova, O. V.; Liu, Y.; Meng, X.; Wang, J.; Martin, R.; Ostro, B.

2017-12-01

Airborne particulate matter (PM) is a well-known cause of cardiovascular and respiratory disease. To estimate human exposure to PM pollution, satellite instruments such as the Terra Multi-angle Imaging SpectroRadiometer (MISR) and the Moderate resolution Imaging Spectroradiometer (MODIS) have been used in conjunction with surface monitors to map near-surface PM concentrations. The relative toxicity of different size and compositional mixtures of PM is not well understood. To address this, we are developing the Multi-Angle Imager for Aerosols (MAIA) investigation. The satellite instrument extends MISR's multiangular visible and near-infrared (VNIR) spectral coverage to 14 bands in the ultraviolet, VNIR, and shortwave IR; three of the bands are polarimetric to enhance sensitivity to aerosol size and composition. To constrain the retrievals, the observations will be combined with data from surface monitors and the WRF-Chem and GEOS-Chem chemical transport models. Existing surface PM speciation monitors will be supplemented by adding new stations to the Surface PARTiculate mAtter Network (SPARTAN). Unlike MISR, MAIA is a targeting instrument. Primary areas of interest include metropolitan areas in North and South America, Europe, the Middle East, Africa, India, and East Asia. PM retrieval algorithms are being developed using data from MISR and the high-altitude Airborne Multiangle SpectroPolarimetric Imager (AirMSPI). Epidemiologists on the MAIA science team will use the derived PM data products and birth, death, and hospital records to investigate adverse health impacts of different types of airborne particulates. MAIA's earliest possible launch date is mid-2020, making it possible for the data to be complemented by global observations from Terra as well as high temporal resolution atmospheric chemistry measurements from TEMPO (Tropospheric Emissions: Monitoring Pollution), GEMS (Geostationary Environment Monitoring Spectrometer), and Sentinel-4.

Physical Retrievals of Over-Ocean Rain Rate from Multichannel Microwave Imagery. Part 1; Theoretical Characteristics of Normalized Polarization and Scattering Indices

NASA Technical Reports Server (NTRS)

Petty, G. W.

1994-01-01

Microwave rain rate retrieval algorithms have most often been formulated in terms of the raw brightness temperatures observed by one or more channels of a satellite radiometer. Taken individually, single-channel brightness temperatures generally represent a near-arbitrary combination of positive contributions due to liquid water emission and negative contributions due to scattering by ice and/or visibility of the radiometrically cold ocean surface. Unfortunately, for a given rain rate, emission by liquid water below the freezing level and scattering by ice particles above the freezing level are rather loosely coupled in both a physical and statistical sense. Furthermore, microwave brightness temperatures may vary significantly (approx. 30-70 K) in response to geophysical parameters other than liquid water and precipitation. Because of these complications, physical algorithms which attempt to directly invert observed brightness temperatures have typically relied on the iterative adjustment of detailed micro-physical profiles or cloud models, guided by explicit forward microwave radiative transfer calculations. In support of an effort to develop a significantly simpler and more efficient inversion-type rain rate algorithm, the physical information content of two linear transformations of single-frequency, dual-polarization brightness temperatures is studied: the normalized polarization difference P of Petty and Katsaros (1990, 1992), which is intended as a measure of footprint-averaged rain cloud transmittance for a given frequency; and a scattering index S (similar to the polarization corrected temperature of Spencer et al.,1989) which is sensitive almost exclusively to ice. A reverse Monte Carlo radiative transfer model is used to elucidate the qualitative response of these physically distinct single-frequency indices to idealized 3-dimensional rain clouds and to demonstrate their advantages over raw brightness temperatures both as stand-alone indices of precipitation activity and as primary variables in physical, multichannel rain rate retrieval schemes. As a byproduct of the present analysis, it is shown that conventional plane-parallel analyses of the well-known foot-print-filling problem for emission-based algorithms may in some cases give seriously misleading results.

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.

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).

The EUSTACE project: delivering global, daily information on surface air temperature

NASA Astrophysics Data System (ADS)

Rayner, Nick

2017-04-01

Day-to-day variations in surface air temperature affect society in many ways; however, daily surface air temperature measurements are not available everywhere. A global daily analysis cannot be achieved with measurements made in situ alone, so incorporation of satellite retrievals is needed. To achieve this, in the EUSTACE project (2015-June 2018, https://www.eustaceproject.eu) we are developing an understanding of the relationships between traditional (land and marine) surface air temperature measurements and retrievals of surface skin temperature from satellite measurements, i.e. Land Surface Temperature, Ice Surface Temperature, Sea Surface Temperature and Lake Surface Water Temperature. Here we discuss the science needed to produce a fully-global daily analysis (or ensemble of analyses) of surface air temperature on the centennial scale, integrating different ground-based and satellite-borne data types. Information contained in the satellite retrievals is used to create globally-complete fields in the past, using statistical models of how surface air temperature varies in a connected way from place to place. As the data volumes involved are considerable, such work needs to include development of new "Big Data" analysis methods. We will present recent progress along this road in the EUSTACE project: 1. providing new, consistent, multi-component estimates of uncertainty in surface skin temperature retrievals from satellites; 2. identifying inhomogeneities in daily surface air temperature measurement series from weather stations and correcting for these over Europe; 3. estimating surface air temperature over all surfaces of Earth from surface skin temperature retrievals; 4. using new statistical techniques to provide information on higher spatial and temporal scales than currently available, making optimum use of information in data-rich eras. Information will also be given on how interested users can become involved.

The EUSTACE project: delivering global, daily information on surface air temperature

NASA Astrophysics Data System (ADS)

Ghent, D.; Rayner, N. A.

2016-12-01

Day-to-day variations in surface air temperature affect society in many ways; however, daily surface air temperature measurements are not available everywhere. A global daily analysis cannot be achieved with measurements made in situ alone, so incorporation of satellite retrievals is needed. To achieve this, in the EUSTACE project (2015-June 2018, https://www.eustaceproject.eu) we are developing an understanding of the relationships between traditional (land and marine) surface air temperature measurements and retrievals of surface skin temperature from satellite measurements, i.e. Land Surface Temperature, Ice Surface Temperature, Sea Surface Temperature and Lake Surface Water Temperature. Here we discuss the science needed to produce a fully-global daily analysis (or ensemble of analyses) of surface air temperature on the centennial scale, integrating different ground-based and satellite-borne data types. Information contained in the satellite retrievals is used to create globally-complete fields in the past, using statistical models of how surface air temperature varies in a connected way from place to place. As the data volumes involved are considerable, such work needs to include development of new "Big Data" analysis methods. We will present recent progress along this road in the EUSTACE project, i.e.: • providing new, consistent, multi-component estimates of uncertainty in surface skin temperature retrievals from satellites; • identifying inhomogeneities in daily surface air temperature measurement series from weather stations and correcting for these over Europe; • estimating surface air temperature over all surfaces of Earth from surface skin temperature retrievals; • using new statistical techniques to provide information on higher spatial and temporal scales than currently available, making optimum use of information in data-rich eras. Information will also be given on how interested users can become involved.

Ozone correlations between mid-tropospheric partial columns and the near-surface at two mid-atlantic sites during the DISCOVER-AQ campaign in July 2011.

PubMed

Martins, Douglas K; Stauffer, Ryan M; Thompson, Anne M; Halliday, Hannah S; Kollonige, Debra; Joseph, Everette; Weinheimer, Andrew J

The current network of ground-based monitors for ozone (O 3 ) is limited due to the spatial heterogeneity of O 3 at the surface. Satellite measurements can provide a solution to this limitation, but the lack of sensitivity of satellites to O 3 within the boundary layer causes large uncertainties in satellite retrievals at the near-surface. The vertical variability of O 3 was investigated using ozonesondes collected as part of NASA's D eriving I nformation on S urface Conditions from CO lumn and VER tically Resolved Observations Relevant to A ir Q uality (DISCOVER-AQ) campaign during July 2011 in the Baltimore, MD/Washington D.C. metropolitan area. A subset of the ozonesonde measurements was corrected for a known bias from the electrochemical solution strength using new procedures based on laboratory and field tests. A significant correlation of O 3 over the two sites with ozonesonde measurements (Edgewood and Beltsville, MD) was observed between the mid-troposphere (7-10 km) and the near-surface (1-3 km). A linear regression model based on the partial column amounts of O 3 within these subregions was developed to calculate the near-surface O 3 using mid-tropospheric satellite measurements from the Tropospheric Emission Spectrometer (TES) onboard the Aura spacecraft. The uncertainties of the calculated near-surface O 3 using TES mid-tropospheric satellite retrievals and a linear regression model were less than 20 %, which is less than that of the observed variability of O 3 at the surface in this region. These results utilize a region of the troposphere to which existing satellites are more sensitive compared to the boundary layer and can provide information of O 3 at the near-surface using existing satellite infrastructure and algorithms.

Development and Testing of the New Surface LER Climatology for OMI UV Aerosol Retrievals

NASA Technical Reports Server (NTRS)

Gupta, Pawan; Torres, Omar; Jethva, Hiren; Ahn, Changwoo

2014-01-01

Ozone Monitoring Instrument (OMI) onboard Aura satellite retrieved aerosols properties using UV part of solar spectrum. The OMI near UV aerosol algorithm (OMAERUV) is a global inversion scheme which retrieves aerosol properties both over ocean and land. The current version of the algorithm makes use of TOMS derived Lambertian Equivalent Reflectance (LER) climatology. A new monthly climatology of surface LER at 354 and 388 nm have been developed. This will replace TOMS LER (380 nm and 354nm) climatology in OMI near UV aerosol retrieval algorithm. The main objectives of this study is to produce high resolution (quarter degree) surface LER sets as compared to existing one degree TOMS surface LERs, to product instrument and wavelength consistent surface climatology. Nine years of OMI observations have been used to derive monthly climatology of surface LER. MODIS derived aerosol optical depth (AOD) have been used to make aerosol corrections on OMI wavelengths. MODIS derived BRDF adjusted reflectance product has been also used to capture seasonal changes in the surface characteristics. Finally spatial and temporal averaging techniques have been used to fill the gaps around the globes, especially in the regions with consistent cloud cover such as Amazon. After implementation of new surface data in the research version of algorithm, comparisons of AOD and single scattering albedo (SSA) have been performed over global AERONET sites for year 2007. Preliminary results shows improvements in AOD retrievals globally but more significance improvement were observed over desert and bright locations. We will present methodology of deriving surface data sets and will discuss the observed changes in retrieved aerosol properties with respect to reference AERONET measurements.

Error in Radar-Derived Soil Moisture due to Roughness Parameterization: An Analysis Based on Synthetical Surface Profiles

PubMed Central

Lievens, Hans; Vernieuwe, Hilde; Álvarez-Mozos, Jesús; De Baets, Bernard; Verhoest, Niko E.C.

2009-01-01

In the past decades, many studies on soil moisture retrieval from SAR demonstrated a poor correlation between the top layer soil moisture content and observed backscatter coefficients, which mainly has been attributed to difficulties involved in the parameterization of surface roughness. The present paper describes a theoretical study, performed on synthetical surface profiles, which investigates how errors on roughness parameters are introduced by standard measurement techniques, and how they will propagate through the commonly used Integral Equation Model (IEM) into a corresponding soil moisture retrieval error for some of the currently most used SAR configurations. Key aspects influencing the error on the roughness parameterization and consequently on soil moisture retrieval are: the length of the surface profile, the number of profile measurements, the horizontal and vertical accuracy of profile measurements and the removal of trends along profiles. Moreover, it is found that soil moisture retrieval with C-band configuration generally is less sensitive to inaccuracies in roughness parameterization than retrieval with L-band configuration. PMID:22399956

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).

Evaluation of reported NOx emission trends between 2005 and 2013 by assimilation of OMI-NO2 data into LOTOS-EUROS

NASA Astrophysics Data System (ADS)

Schaap, Martijn; Segers, Arjo; Curier, Lyana; Timmermans, Renske

2016-04-01

Consistent and long time series of remotely sensed trace gas levels may provide a useful tool to estimate surface emissions and emission trends. We use the OMI-NO2 product in conjunction with the LOTOS-EUROS CTM to estimate European emission trends through correction of the OMI-time series for meteorological variability as well as through assimilation using an ensemble kalman filter system (EnKF). The chemistry transport model captures a large fraction of the variability in NO2 columns at a synoptic timescale, although a seasonal signal in the bias between the modeled and retrieved column data remains. Prior to the assimilation, the OMI-NO2 data have been analyzed to establish the spatially variable temporal and spatial correlation lengths, required for the settings in the EnKF system. The assimilation run for 2005-2013 was performed using constant 2005 emissions to be able to quantify the emission change. The assimilation reduces the model-observation differences considerably. Significant negative trends of 2-3 % per year (as compared to 2005) were found in highly industrialized areas across Western Europe. The assimilation system also identifies the areas with major emission reductions in e.g. northern Spain as identified in earlier studies. Comparison of the trends derived from the assimilation and the data itself shows a high level of agreement, both the trends found in this way are smaller than those reported.

Characterizing soil moisture and snow cover effects on boreal-arctic soil freeze/thaw dynamics and cold-season carbon emissions

NASA Astrophysics Data System (ADS)

Yi, Y.; Kimball, J. S.; Moghaddam, M.; Chen, R. H.; Reichle, R. H.; Oechel, W. C.; Zona, D.

2017-12-01

The contribution of cold season respiration to boreal-arctic carbon cycle and its potential feedbacks to climate change remain poorly quantified. Here, we developed an integrated modeling framework combining airborne low frequency (L+P-band) airborne radar retrievals and landscape level (≥1km) environmental observations from satellite optical and microwave sensors with a detailed permafrost carbon model to investigate underlying processes controlling soil freeze/thaw (FT) dynamics and cold season carbon emissions. The permafrost carbon model simulates the snow and soil thermal dynamics with soil water phase change included and accounts for soil carbon decomposition up to 3m below surface. Local-scale ( 50m) radar retrievals of active layer thickness (ALT), soil moisture and freeze/thaw (FT) status from NASA airborne UAVSAR and AirMOSS sensors are used to inform the model parameterizations of soil moisture effects on soil FT dynamics, and scaling properties of active layer processes. Both tower observed land-atmosphere fluxes and atmospheric CO2 measurements are used to evaluate the model processes controlling cold season carbon respiration, particularly the effects of snow cover and soil moisture on deep soil carbon emissions during the early cold season. Initial comparisons showed that the model can well capture the seasonality of cold season respiration in both tundra and boreal forest areas, with large emissions in late fall and early winter and gradually diminishing throughout the winter. Model sensitivity analyses are used to clarify how changes in soil thermodynamics at depth control the magnitude and seasonality of cold season respiration, and how a deeper unfrozen active layer with warming may contribute to changes in cold season respiration. Model outputs include ALT and regional carbon fluxes at 1-km resolution spanning recent satellite era (2001-present) across Alaska. These results will be used to quantify cold season respiration contributions to the annual carbon cycle and help close the boreal-arctic annual carbon budget.

Observation of angular effects on thermal infrared emissivity derived with the MODTES algorithm and MODIS data

NASA Astrophysics Data System (ADS)

García-Santos, Vicente; Niclòs, Raquel; Coll, César; Valor, Enric; Caselles, Vicente

2015-04-01

The MOD21 Land Surface Temperature and Emissivity (LST&E) product will be included in forthcoming MODIS Collection 6. Surface temperature and emissivities for thermal infrared (TIR) bands 29 (8.55 μm), 31 (11 μm) and 32 (12 μm) will be retrieved using the ASTER TES method adapted to MODIS at-sensor spectral radiances, previously corrected with the Water Vapor Scaling method (MODTES algorithm). LSE of most natural surfaces changes with soil moisture content, type of surface cover, surface roughness or sensor viewing geometry. The present study addresses the observation of anisotropy effects on LSE of bare soils using MODIS data and a processor simulator of the MOD21 product, since it is not available yet. Two highly homogeneous and quasi-invariant desert sites were selected to carry out the present study. The first one is the White Sands National Monument, located in Tularosa Valley (South-central New Mexico, USA), which is a dune system desert at 1216 m above sea level, with an area of 704 km2 and a maximum dune height of 10 m. The grain size is considered fine sand and the major mineralogy component is gypsum. The second site selected was the Great Sands National Park, located in the San Luis Valley (Colorado, USA). Great Sands is also a sand dune system desert, created from quartz and volcanic fragments derived from Santa Fe and Alamosa formations. The major mineral is quartz, with minor traces of potassium and feldspar. The grain size of the sand is medium to coarse according to the X-Ray Diffraction measurements. Great Sands covers an area of 104 km2 at 2560 m above sea level and the maximum dune height is 230 m. The obtained LSEs and their dependence on azimuth and zenith viewing angles were analyzed, based on series of MODIS scenes from 2010 to 2013. MODTES nadir and off-nadir LSEs showed a good agreement with laboratory emissivity measurements. Results show that band 29 LSE decreases with the zenithal angle up to 0.041 from its nadir value, while LSEs for bands 31 and 32 do not show significant changes with zenith angle.

Sensor Performance Requirements for the Retrieval of Atmospheric Aerosols by Airborne Optical Remote Sensing

PubMed Central

Seidel, Felix; Schläpfer, Daniel; Nieke, Jens; Itten, Klaus I.

2008-01-01

This study explores performance requirements for the retrieval of the atmospheric aerosol optical depth (AOD) by airborne optical remote sensing instruments. Independent of any retrieval techniques, the calculated AOD retrieval requirements are compared with the expected performance parameters of the upcoming hyperspectral sensor APEX at the reference wavelength of 550nm. The AOD accuracy requirements are defined to be capable of resolving transmittance differences of 0.01 to 0.04 according to the demands of atmospheric corrections for remote sensing applications. For the purposes of this analysis, the signal at the sensor level is simulated by radiation transfer equations. The resulting radiances are translated into the AOD retrieval sensitivity (Δτλaer) and compared to the available measuring sensitivity of the sensor (NEΔLλsensor). This is done for multiple signal-to-noise ratios (SNR) and surface reflectance values. It is shown that an SNR of 100 is adequate for AOD retrieval at 550nm under typical remote sensing conditions and a surface reflectance of 10% or less. Such dark surfaces require the lowest SNR values and therefore offer the best sensitivity for measuring AOD. Brighter surfaces with up to 30% reflectance require an SNR of around 300. It is shown that AOD retrieval for targets above 50% surface reflectance is more problematic with the current sensor performance as it may require an SNR larger than 1000. In general, feasibility is proven for the analyzed cases under simulated conditions. PMID:27879801

Sensor Performance Requirements for the Retrieval of Atmospheric Aerosols by Airborne Optical Remote Sensing.

PubMed

Seidel, Felix; Schläpfer, Daniel; Nieke, Jens; Itten, Klaus I

2008-03-18

This study explores performance requirements for the retrieval of the atmospheric aerosol optical depth (AOD) by airborne optical remote sensing instruments. Independent of any retrieval techniques, the calculated AOD retrieval requirements are compared with the expected performance parameters of the upcoming hyperspectral sensor APEX at the reference wavelength of 550nm. The AOD accuracy requirements are defined to be capable of resolving transmittance differences of 0.01 to 0.04 according to the demands of atmospheric corrections for remote sensing applications. For the purposes of this analysis, the signal at the sensor level is simulated by radiation transfer equations. The resulting radiances are translated into the AOD retrieval sensitivity (Δτ λ aer ) and compared to the available measuring sensitivity of the sensor (NE ΔL λ sensor ). This is done for multiple signal-to-noise ratios (SNR) and surface reflectance values. It is shown that an SNR of 100 is adequate for AOD retrieval at 550nm under typical remote sensing conditions and a surface reflectance of 10% or less. Such dark surfaces require the lowest SNR values and therefore offer the best sensitivity for measuring AOD. Brighter surfaces with up to 30% reflectance require an SNR of around 300. It is shown that AOD retrieval for targets above 50% surface reflectance is more problematic with the current sensor performance as it may require an SNR larger than 1000. In general, feasibility is proven for the analyzed cases under simulated conditions.

U.S. NO₂ trends (2005–2013): EPA air quality system (AQS) data versus improved observations from the Ozone Monitoring Instrument (OMI)

DOE PAGES

Lamsal, Lok N.; Duncan, Bryan N.; Yoshida, Yasuko; ...

2015-06-01

Emissions of nitrogen oxides (NO x) and, subsequently, atmospheric levels of nitrogen dioxide (NO₂) have decreased over the U.S. due to a combination of environmental policies and technological change. Consequently, NO₂ levels have decreased by 30–40% in the last decade. We quantify NO₂ trends (2005–2013) over the U.S. using surface measurements from the U.S. Environmental Protection Agency (EPA) Air Quality System (AQS) and an improved tropospheric NO₂ vertical column density (VCD) data product from the Ozone Monitoring Instrument (OMI) on the Aura satellite.We demonstrate that the current OMI NO₂ algorithm is of sufficient maturity to allow a favorable correspondence ofmore » trends and variations in OMI and AQS data. Our trend model accounts for the non-linear dependence of NO₂ concentration on emissions associated with the seasonal variation of the chemical lifetime, including the change in the amplitude of the seasonal cycle associated with the significant change in NO x emissions that occurred over the last decade. The direct relationship between observations and emissions becomes more robust when one accounts for these non-linear dependencies. We improve the OMI NO₂ standard retrieval algorithm and, subsequently, the data product by using monthly vertical concentration profiles, a required algorithm input, from a high-resolution chemistry and transport model (CTM) simulation with varying emissions (2005-2013). The impact of neglecting the time-dependence of the profiles leads to errors in trend estimation, particularly in regions where emissions have changed substantially. For example, trends calculated from retrievals based on time-dependent profiles offer 18% more instances of significant trends and up to 15% larger total NO₂ reduction versus the results based on profiles for 2005. Using a CTM, we explore the theoretical relation of the trends estimated from NO₂ VCDs to those estimated from ground-level concentrations. The model-simulated trends in VCDs strongly correlate with those estimated from surface concentrations (r = 0.83, N = 355). We then explore the observed correspondence of trends estimated from OMI and AQS data. We find a significant, but slightly weaker, correspondence (i.e., r = 0.68, N = 208) than predicted by the model and discuss some of the important factors affecting the relationship, including known problems (e.g., NO z interferents) associated with the AQS data. This significant correspondence gives confidence in trend and surface concentration estimates from OMI VCDs for locations, such as the majority of the U.S. and globe, that are not covered by surface monitoring networks. Using our improved trend model and our enhanced OMI data product, we find that both OMI and AQS data show substantial downward trends from 2005 to 2013, with an average reduction of 38% for each over the U.S. The annual reduction rates inferred from OMI and AQS measurements are larger (–4.8 ± 1.9%/yr, –3.7 ± 1.5%/yr) from 2005 to 2008 than 2010 to 2013 (–1.2 ± 1.2%/yr, –2.1 ± 1.4%/yr). We quantify NO₂ trends for major U.S. cities and power plants; the latter suggest larger negative trend (–4.0 ± 1.5%/yr) between 2005 and 2008 and smaller or insignificant changes (–0.5 ± 1.2%/yr) during 2010-2013.« less

U.S. NO₂ trends (2005–2013): EPA air quality system (AQS) data versus improved observations from the Ozone Monitoring Instrument (OMI)

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

Lamsal, Lok N.; Duncan, Bryan N.; Yoshida, Yasuko

Emissions of nitrogen oxides (NO x) and, subsequently, atmospheric levels of nitrogen dioxide (NO₂) have decreased over the U.S. due to a combination of environmental policies and technological change. Consequently, NO₂ levels have decreased by 30–40% in the last decade. We quantify NO₂ trends (2005–2013) over the U.S. using surface measurements from the U.S. Environmental Protection Agency (EPA) Air Quality System (AQS) and an improved tropospheric NO₂ vertical column density (VCD) data product from the Ozone Monitoring Instrument (OMI) on the Aura satellite.We demonstrate that the current OMI NO₂ algorithm is of sufficient maturity to allow a favorable correspondence ofmore » trends and variations in OMI and AQS data. Our trend model accounts for the non-linear dependence of NO₂ concentration on emissions associated with the seasonal variation of the chemical lifetime, including the change in the amplitude of the seasonal cycle associated with the significant change in NO x emissions that occurred over the last decade. The direct relationship between observations and emissions becomes more robust when one accounts for these non-linear dependencies. We improve the OMI NO₂ standard retrieval algorithm and, subsequently, the data product by using monthly vertical concentration profiles, a required algorithm input, from a high-resolution chemistry and transport model (CTM) simulation with varying emissions (2005-2013). The impact of neglecting the time-dependence of the profiles leads to errors in trend estimation, particularly in regions where emissions have changed substantially. For example, trends calculated from retrievals based on time-dependent profiles offer 18% more instances of significant trends and up to 15% larger total NO₂ reduction versus the results based on profiles for 2005. Using a CTM, we explore the theoretical relation of the trends estimated from NO₂ VCDs to those estimated from ground-level concentrations. The model-simulated trends in VCDs strongly correlate with those estimated from surface concentrations (r = 0.83, N = 355). We then explore the observed correspondence of trends estimated from OMI and AQS data. We find a significant, but slightly weaker, correspondence (i.e., r = 0.68, N = 208) than predicted by the model and discuss some of the important factors affecting the relationship, including known problems (e.g., NO z interferents) associated with the AQS data. This significant correspondence gives confidence in trend and surface concentration estimates from OMI VCDs for locations, such as the majority of the U.S. and globe, that are not covered by surface monitoring networks. Using our improved trend model and our enhanced OMI data product, we find that both OMI and AQS data show substantial downward trends from 2005 to 2013, with an average reduction of 38% for each over the U.S. The annual reduction rates inferred from OMI and AQS measurements are larger (–4.8 ± 1.9%/yr, –3.7 ± 1.5%/yr) from 2005 to 2008 than 2010 to 2013 (–1.2 ± 1.2%/yr, –2.1 ± 1.4%/yr). We quantify NO₂ trends for major U.S. cities and power plants; the latter suggest larger negative trend (–4.0 ± 1.5%/yr) between 2005 and 2008 and smaller or insignificant changes (–0.5 ± 1.2%/yr) during 2010-2013.« less

Retrieving background surface reflectance of Himawari-8/AHI using BRDF modeling

NASA Astrophysics Data System (ADS)

Choi, Sungwon; Seo, Minji; Lee, Kyeong-sang; Han, Kyung-soo

2017-04-01

In these days, remote sensing is more important than past. And retrieving surface reflectance in remote sensing is also important. So there are many ways to retrieve surface reflectance by my countries with polar orbit and geostationary satellite. We studied Bidirectional Reflectance Distribution Function (BRDF) which is used to retrieve surface reflectance. In BRDF equation, we calculate surface reflectance using BRD components and angular data. BRD components are to calculate 3 of scatterings, isotropic geometric and volumetric scattering. To make Background Surface Reflectance (BSR) of Himawari-8/AHI. We used 5 bands (band1, band2, band3, band4, band5) with BRDF. And we made 5 BSR for 5 channels. For validation, we compare BSR with Top of canopy (TOC) reflectance of AHI. As a result, bias are from -0.00223 to 0.008328 and Root Mean Square Error (RMSE) are from 0.045 to 0.049. We think BSR can be used to replace TOC reflectance in remote sensing to improve weakness of TOC reflectance.

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.

Global Scale Simultaneous Retrieval of Smoothened Vegetation Optical Depth and Surface Roughness Parameter using AMSR-E X-band Observations

NASA Astrophysics Data System (ADS)

Lanka, Karthikeyan; Pan, Ming; Konings, Alexandra; Piles, María; D, Nagesh Kumar; Wood, Eric

2017-04-01

Traditionally, passive microwave retrieval algorithms such as Land Parameter Retrieval Model (LPRM) estimate simultaneously soil moisture and Vegetation Optical Depth (VOD) using brightness temperature (Tb) data. The algorithm requires a surface roughness parameter which - despite implications - is generally assumed to be constant at global scale. Due to inherent noise in the satellite data and retrieval algorithm, the VOD retrievals are usually observed to be highly fluctuating at daily scale which may not occur in reality. Such noisy VOD retrievals along with spatially invariable roughness parameter may affect the quality of soil moisture retrievals. The current work aims to smoothen the VOD retrievals (with an assumption that VOD remains constant over a period of time) and simultaneously generate, for the first time, global surface roughness map using multiple descending X-band Tb observations of AMSR-E. The methodology utilizes Tb values under a moving-time-window-setup to estimate concurrently the soil moisture of each day and a constant VOD in the window. Prior to this step, surface roughness parameter is estimated using the complete time series of Tb record. Upon carrying out the necessary sensitivity analysis, the smoothened VOD along with soil moisture retrievals is generated for the 10-year duration of AMSR-E (2002-2011) with a 7-day moving window using the LPRM framework. The spatial patterns of resulted global VOD maps are in coherence with vegetation biomass and climate conditions. The VOD results also exhibit a smoothening effect in terms of lower values of standard deviation. This is also evident from time series comparison of VOD and LPRM VOD retrievals without optimization over moving windows at several grid locations across the globe. The global surface roughness map also exhibited spatial patterns that are strongly influenced by topography and land use conditions. Some of the noticeable features include high roughness over mountainous regions and heavily vegetated tropical rainforests, low roughness in desert areas and moderate roughness value over higher latitudes. The new datasets of VOD and surface roughness can help improving the quality of soil moisture retrievals. Also, the methodology proposed is generic by nature and can be implemented over currently operating AMSR2, SMOS, and SMAP soil moisture missions.

A New Satellite Aerosol Retrieval Using High Spectral Resolution Oxygen A-Band Measurements

NASA Astrophysics Data System (ADS)

Winker, D. M.; Zhai, P.

2014-12-01

Efforts to advance current satellite aerosol retrieval capabilities have mostly focused on polarimetric techniques. While there has been much interest in recent decades in the use of the oxygen A-band for retrievals of cloud height or surface pressure, these techniques are mostly based on A-band measurements with relatively low spectral resolution. We report here on a new aerosol retrieval technique based on high-resolution A-band spectra. Our goal is the development of a technique to retrieve aerosol absorption, one of the critical parameters affecting the global radiation budget and one which is currently poorly constrained by satellite measurements. Our approach relies on two key factors: 1) the use of high spectral resolution measurements which resolve the A-band line structure, and 2) the use of co-located lidar profile measurements to constrain the vertical distribution of scatterers. The OCO-2 satellite, launched in July this year and now flying in formation with the CALIPSO satellite, carries an oxygen A-band spectrometer with a spectral resolution of 21,000:1. This is sufficient to resolve the A-band line structure, which contains information on atmospheric photon path lengths. Combining channels with oxygen absorption ranging from weak to strong allows the separation of atmospheric and surface scattering. An optimal estimation algorithm for simultaneous retrieval of aerosol optical depth, aerosol absorption, and surface albedo has been developed. Lidar profile data is used for scene identification and to provide constraints on the vertical distribution of scatterers. As calibrated OCO-2 data is not expected until the end of this year, the algorithm has been developed and tested using simulated OCO-2 spectra. The simulations show that AOD and surface albedo can be retrieved with high accuracy. Retrievals of aerosol single scatter albedo are encouraging, showing good performance when AOD is larger than about 0.15. Retrieval performance improves as the albedo of the underlying surface increases. Thus, the technique shows great promise for retrieving the absorption optical depth of aerosols located above clouds. This presentation will discuss the basis of the approach and results of the A-band/lidar retrievals based on simulated data.

Remote sensing of rain over the ocean

NASA Technical Reports Server (NTRS)

1978-01-01

Computer models of the microwave emission from the earth's atmosphere were used to study the problem of retrieving meteorological information from the SMMR instrument that will be flown on NIMBUS-G. Methods for retrieving rain rate, wind speed, cloud height, and ocean temperature are described for the case when the satellite is over the ocean.

Retrieval of Surface Lambert Albedos and Aerosols Optical Depths Using OMEGA Near-IR EPF Observations of Mars

NASA Astrophysics Data System (ADS)

Vincendon, M.; Langevin, Y.; Poulet, F.; Bibring, J.-P.; Gondet, B.

2007-03-01

We have analyzed five EPF sequences acquired by OMEGA/Mars Express in the near-IR over ice-free and ice-covered surfaces to retrieve simultaneously the Lambert albedo of the surface and the optical depth of aerosols.

Histologic analysis of resorbable blasting media surface implants retrieved from humans: a report of two cases

PubMed Central

2016-01-01

The purpose of this study is to evaluate the degree of osseointegration of resorbable blasting media (RBM) surface implants retrieved from humans. Three implants in the mandibular molar region that were surface-treated with RBM were retrieved from two patients. The implants were used to manufacture specimens in order to measure the bone-implant contact (BIC) ratio. The BIC ratios of the three implants were found to be an average of 69.0%±9.1%. In conclusion, that RBM surface implants are integrated into the host environment with histological significance and the BIC ratio of the RBM surface-treated implant was not significantly different from that of other surface-treated implants. PMID:26904493

Comparison of different methods to retrieve optical-equivalent snow grain size in central Antarctica

NASA Astrophysics Data System (ADS)

Carlsen, Tim; Birnbaum, Gerit; Ehrlich, André; Freitag, Johannes; Heygster, Georg; Istomina, Larysa; Kipfstuhl, Sepp; Orsi, Anaïs; Schäfer, Michael; Wendisch, Manfred

2017-11-01

The optical-equivalent snow grain size affects the reflectivity of snow surfaces and, thus, the local surface energy budget in particular in polar regions. Therefore, the specific surface area (SSA), from which the optical snow grain size is derived, was observed for a 2-month period in central Antarctica (Kohnen research station) during austral summer 2013/14. The data were retrieved on the basis of ground-based spectral surface albedo measurements collected by the COmpact RAdiation measurement System (CORAS) and airborne observations with the Spectral Modular Airborne Radiation measurement sysTem (SMART). The snow grain size and pollution amount (SGSP) algorithm, originally developed to analyze spaceborne reflectance measurements by the MODerate Resolution Imaging Spectroradiometer (MODIS), was modified in order to reduce the impact of the solar zenith angle on the retrieval results and to cover measurements in overcast conditions. Spectral ratios of surface albedo at 1280 and 1100 nm wavelength were used to reduce the retrieval uncertainty. The retrieval was applied to the ground-based and airborne observations and validated against optical in situ observations of SSA utilizing an IceCube device. The SSA retrieved from CORAS observations varied between 27 and 89 m2 kg-1. Snowfall events caused distinct relative maxima of the SSA which were followed by a gradual decrease in SSA due to snow metamorphism and wind-induced transport of freshly fallen ice crystals. The ability of the modified algorithm to include measurements in overcast conditions improved the data coverage, in particular at times when precipitation events occurred and the SSA changed quickly. SSA retrieved from measurements with CORAS and MODIS agree with the in situ observations within the ranges given by the measurement uncertainties. However, SSA retrieved from the airborne SMART data slightly underestimated the ground-based results.

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.

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).

EM Bias-Correction for Ice Thickness and Surface Roughness Retrievals over Rough Deformed Sea Ice

NASA Astrophysics Data System (ADS)

Li, L.; Gaiser, P. W.; Allard, R.; Posey, P. G.; Hebert, D. A.; Richter-Menge, J.; Polashenski, C. M.

2016-12-01

The very rough ridge sea ice accounts for significant percentage of total ice areas and even larger percentage of total volume. The commonly used Radar altimeter surface detection techniques are empirical in nature and work well only over level/smooth sea ice. Rough sea ice surfaces can modify the return waveforms, resulting in significant Electromagnetic (EM) bias in the estimated surface elevations, and thus large errors in the ice thickness retrievals. To understand and quantify such sea ice surface roughness effects, a combined EM rough surface and volume scattering model was developed to simulate radar returns from the rough sea ice `layer cake' structure. A waveform matching technique was also developed to fit observed waveforms to a physically-based waveform model and subsequently correct the roughness induced EM bias in the estimated freeboard. This new EM Bias Corrected (EMBC) algorithm was able to better retrieve surface elevations and estimate the surface roughness parameter simultaneously. In situ data from multi-instrument airborne and ground campaigns were used to validate the ice thickness and surface roughness retrievals. For the surface roughness retrievals, we applied this EMBC algorithm to co-incident LiDAR/Radar measurements collected during a Cryosat-2 under-flight by the NASA IceBridge missions. Results show that not only does the waveform model fit very well to the measured radar waveform, but also the roughness parameters derived independently from the LiDAR and radar data agree very well for both level and deformed sea ice. For sea ice thickness retrievals, validation based on in-situ data from the coordinated CRREL/NRL field campaign demonstrates that the physically-based EMBC algorithm performs fundamentally better than the empirical algorithm over very rough deformed sea ice, suggesting that sea ice surface roughness effects can be modeled and corrected based solely on the radar return waveforms.

Satellite Estimation of Daily Land Surface Water Vapor Pressure Deficit from AMSR- E

NASA Astrophysics Data System (ADS)

Jones, L. A.; Kimball, J. S.; McDonald, K. C.; Chan, S. K.; Njoku, E. G.; Oechel, W. C.

2007-12-01

Vapor pressure deficit (VPD) is a key variable for monitoring land surface water and energy exchanges, and estimating plant water stress. Multi-frequency day/night brightness temperatures from the Advanced Microwave Scanning Radiometer on EOS Aqua (AMSR-E) were used to estimate daily minimum and average near surface (2 m) air temperatures across a North American boreal-Arctic transect. A simple method for determining daily mean VPD (Pa) from AMSR-E air temperature retrievals was developed and validated against observations across a regional network of eight study sites ranging from boreal grassland and forest to arctic tundra. The method assumes that the dew point and minimum daily air temperatures tend to equilibrate in areas with low night time temperatures and relatively moist conditions. This assumption was tested by comparing the VPD algorithm results derived from site daily temperature observations against results derived from AMSR-E retrieved temperatures alone. An error analysis was conducted to determine the amount of error introduced in VPD estimates given known levels of error in satellite retrieved temperatures. Results indicate that the assumption generally holds for the high latitude study sites except for arid locations in mid-summer. VPD estimates using the method with AMSR-E retrieved temperatures compare favorably with site observations. The method can be applied to land surface temperature retrievals from any sensor with day and night surface or near-surface thermal measurements and shows potential for inferring near-surface wetness conditions where dense vegetation may hinder surface soil moisture retrievals from low-frequency microwave sensors. This work was carried out at The University of Montana, at San Diego State University, and at the Jet Propulsion Laboratory, California Institute of Technology, under contract to the National Aeronautics and Space Administration.

Inference of precipitation through thermal infrared measurements of soil moisture

NASA Technical Reports Server (NTRS)

Wetzel, P. J.; Atlas, D.

1981-01-01

The physics of microwave radiative transfer is well understood so that causal models can be assembled which relate the observed brightness temperatures to assumed distributions of hydrometeors (both liquid and ice), non-precipitating clouds, water vapor oxygen, and surface conditions. Present models assume a Marshall Palmer size distribution of liquid hydrometers from the surface to the freezing level (near the 0 C isotherm) and a variable thickness of frozen hydrometeors above that with various reasonable distribution of the other relevant constituents. The validity of such models is discussed. All uncertainties in the rain rate retrieval algorithms can be expressed in terms of specific model uncertainties which can be addressed through appropriate measurements. Those factors which must be known to achieve umambiguous results can be identified so that rainfall measuring algorithms can be developed and improved. The emissivity of the underlying surface significantly affects the contrast that may be measured between areas covered by rain and those which are dry. Sensing strategies for measuring rain over the ocean and rain over land are reviewed.

Convection and thermal radiation analytical models applicable to a nuclear waste repository room

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

Davis, B.W.

1979-01-17

Time-dependent temperature distributions in a deep geologic nuclear waste repository have a direct impact on the physical integrity of the emplaced canisters and on the design of retrievability options. This report (1) identifies the thermodynamic properties and physical parameters of three convection regimes - forced, natural, and mixed; (2) defines the convection correlations applicable to calculating heat flow in a ventilated (forced-air) and in a nonventilated nuclear waste repository room; and (3) delineates a computer code that (a) computes and compares the floor-to-ceiling heat flow by convection and radiation, and (b) determines the nonlinear equivalent conductivity table for a repositorymore » room. (The tables permit the use of the ADINAT code to model surface-to-surface radiation and the TRUMP code to employ two different emissivity properties when modeling radiation exchange between the surface of two different materials.) The analysis shows that thermal radiation dominates heat flow modes in a nuclear waste repository room.« less

A radiation closure study of Arctic stratus cloud microphysical properties using the collocated satellite-surface data and Fu-Liou radiative transfer model

NASA Astrophysics Data System (ADS)

Dong, Xiquan; Xi, Baike; Qiu, Shaoyue; Minnis, Patrick; Sun-Mack, Sunny; Rose, Fred

2016-09-01

Retrievals of cloud microphysical properties based on passive satellite imagery are especially difficult over snow-covered surfaces because of the bright and cold surface. To help quantify their uncertainties, single-layered overcast liquid-phase Arctic stratus cloud microphysical properties retrieved by using the Clouds and the Earth's Radiant Energy System Edition 2 and Edition 4 (CERES Ed2 and Ed4) algorithms are compared with ground-based retrievals at the Atmospheric Radiation Measurement North Slope of Alaska (ARM NSA) site at Barrow, AK, during the period from March 2000 to December 2006. A total of 206 and 140 snow-free cases (Rsfc ≤ 0.3), and 108 and 106 snow cases (Rsfc > 0.3), respectively, were selected from Terra and Aqua satellite passes over the ARM NSA site. The CERES Ed4 and Ed2 optical depth (τ) and liquid water path (LWP) retrievals from both Terra and Aqua are almost identical and have excellent agreement with ARM retrievals under snow-free and snow conditions. In order to reach a radiation closure study for both the surface and top of atmosphere (TOA) radiation budgets, the ARM precision spectral pyranometer-measured surface albedos were adjusted (63.6% and 80% of the ARM surface albedos for snow-free and snow cases, respectively) to account for the water and land components of the domain of 30 km × 30 km. Most of the radiative transfer model calculated SW↓sfc and SW↑TOA fluxes by using ARM and CERES cloud retrievals and the domain mean albedos as input agree with the ARM and CERES flux observations within 10 W m-2 for both snow-free and snow conditions. Sensitivity studies show that the ARM LWP and re retrievals are less dependent on solar zenith angle (SZA), but all retrieved optical depths increase with SZA.

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.

Integrated Active Fire Retrievals and Biomass Burning Emissions Using Complementary Near-Coincident Ground, Airborne and Spaceborne Sensor Data

NASA Technical Reports Server (NTRS)

Schroeder, Wilfrid; Ellicott, Evan; Ichoku, Charles; Ellison, Luke; Dickinson, Matthew B.; Ottmar, Roger D.; Clements, Craig; Hall, Dianne; Ambrosia, Vincent; Kremens, Robert

2013-01-01

Ground, airborne and spaceborne data were collected for a 450 ha prescribed fire implemented on 18 October 2011 at the Henry W. Coe State Park in California. The integration of various data elements allowed near coincident active fire retrievals to be estimated. The Autonomous Modular Sensor-Wildfire (AMS) airborne multispectral imaging system was used as a bridge between ground and spaceborne data sets providing high quality reference information to support satellite fire retrieval error analyses and fire emissions estimates. We found excellent agreement between peak fire radiant heat flux data (less than 1% error) derived from near-coincident ground radiometers and AMS. Both MODIS and GOES imager active fire products were negatively influenced by the presence of thick smoke, which was misclassified as cloud by their algorithms, leading to the omission of fire pixels beneath the smoke, and resulting in the underestimation of their retrieved fire radiative power (FRP) values for the burn plot, compared to the reference airborne data. Agreement between airborne and spaceborne FRP data improved significantly after correction for omission errors and atmospheric attenuation, resulting in as low as 5 difference between AquaMODIS and AMS. Use of in situ fuel and fire energy estimates in combination with a collection of AMS, MODIS, and GOES FRP retrievals provided a fuel consumption factor of 0.261 kg per MJ, total energy release of 14.5 x 10(exp 6) MJ, and total fuel consumption of 3.8 x 10(exp 6) kg. Fire emissions were calculated using two separate techniques, resulting in as low as 15 difference for various species

High Vertically Resolved Atmospheric and Surface/Cloud Parameters Retrieved with Infrared Atmospheric Sounding Interferometer (IASI)

NASA Technical Reports Server (NTRS)

Zhou, Daniel K.; Liu, Xu; Larar, Allen M.; Smith, WIlliam L.; Taylor, Jonathan P.; Schluessel, Peter; Strow, L. Larrabee; Mango, Stephen A.

2008-01-01

The Joint Airborne IASI Validation Experiment (JAIVEx) was conducted during April 2007 mainly for validation of the IASI on the MetOp satellite. IASI possesses an ultra-spectral resolution of 0.25/cm and a spectral coverage from 645 to 2760/cm. Ultra-spectral resolution infrared spectral radiance obtained from near nadir observations provide atmospheric, surface, and cloud property information. An advanced retrieval algorithm with a fast radiative transfer model, including cloud effects, is used for atmospheric profile and cloud parameter retrieval. This physical inversion scheme has been developed, dealing with cloudy as well as cloud-free radiance observed with ultraspectral infrared sounders, to simultaneously retrieve surface, atmospheric thermodynamic, and cloud microphysical parameters. A fast radiative transfer model, which applies to the cloud-free and/or clouded atmosphere, is used for atmospheric profile and cloud parameter retrieval. A one-dimensional (1-d) variational multi-variable inversion solution is used to improve an iterative background state defined by an eigenvector-regression-retrieval. The solution is iterated in order to account for non-linearity in the 1-d variational solution. It is shown that relatively accurate temperature and moisture retrievals are achieved below optically thin clouds. For optically thick clouds, accurate temperature and moisture profiles down to cloud top level are obtained. For both optically thin and thick cloud situations, the cloud top height can be retrieved with relatively high accuracy (i.e., error < 1 km). Preliminary retrievals of atmospheric soundings, surface properties, and cloud optical/microphysical properties with the IASI observations are obtained and presented. These retrievals will be further inter-compared with those obtained from airborne FTS system, such as the NPOESS Airborne Sounder Testbed - Interferometer (NAST-I), dedicated dropsondes, radiosondes, and ground based Raman Lidar. The capabilities of satellite ultra-spectral sounder such as the IASI are investigated indicating a high vertical structure of atmosphere is retrieved.

Surface Soil Moisture Retrieval Using SSM/I and Its Comparison with ESTAR: A Case Study Over a Grassland Region

NASA Technical Reports Server (NTRS)

Jackson, T.; Hsu, A. Y.; ONeill, P. E.

1999-01-01

This study extends a previous investigation on estimating surface soil moisture using the Special Sensor Microwave/Imager (SSM/I) over a grassland region. Although SSM/I is not optimal for soil moisture retrieval, it can under some conditions provide information. Rigorous analyses over land have been difficult due to the lack of good validation data sets. A scientific objective of the Southern Great Plains 1997 (SGP97) Hydrology Experiment was to investigate whether the retrieval algorithms for surface soil moisture developed at higher spatial resolution using truck-and aircraft-based passive microwave sensors can be extended to the coarser resolutions expected from satellite platform. With the data collected for the SGP97, the objective of this study is to compare the surface soil moisture estimated from the SSM/I data with those retrieved from the L-band Electronically Scanned Thinned Array Radiometer (ESTAR) data, the core sensor for the experiment, using the same retrieval algorithm. The results indicated that an error of estimate of 7.81% could be achieved with SSM/I data as contrasted to 2.82% with ESTAR data over three intensive sampling areas of different vegetation regimes. It confirms the results of previous study that SSM/I data can be used to retrieve surface soil moisture information at a regional scale under certain conditions.

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.

The Effect of Sea-Surface Sun Glitter on Microwave Radiometer Measurements

NASA Technical Reports Server (NTRS)

Wentz, F. J.

1981-01-01

A relatively simple model for the microwave brightness temperature of sea surface Sun glitter is presented. The model is an accurate closeform approximation for the fourfold Sun glitter integral. The model computations indicate that Sun glitter contamination of on orbit radiometer measurements is appreciable over a large swath area. For winds near 20 m/s, Sun glitter affects the retrieval of environmental parameters for Sun angles as large as 20 to 25 deg. The model predicted biases in retrieved wind speed and sea surface temperature due to neglecting Sun glitter are consistent with those experimentally observed in SEASAT SMMR retrievals. A least squares retrieval algorithm that uses a combined sea and Sun model function shows the potential of retrieving accurate environmental parameters in the presence of Sun glitter so long as the Sun angles and wind speed are above 5 deg and 2 m/s, respectively.

LANL MTI science team experience

NASA Astrophysics Data System (ADS)

Balick, Lee K.; Borel, Christopher C.; Chylek, Petr; Clodius, William B.; Davis, Anthony B.; Henderson, Bradley G.; Galbraith, Amy E.; Lawson, Stefanie L.; Pope, Paul A.; Rodger, Andrew P.; Theiler, James P.

2003-12-01

The Multispectral Thermal Imager (MTI) is a technology test and demonstration satellite whose primary mission involved a finite number of technical objectives. MTI was not designed, or supported, to become a general purpose operational satellite. The role of the MTI science team is to provide a core group of system-expert scientists who perform the scientific development and technical evaluations needed to meet programmatic objectives. Another mission for the team is to develop algorithms to provide atmospheric compensation and quantitative retrieval of surface parameters to a relatively small community of MTI users. Finally, the science team responds and adjusts to unanticipated events in the life of the satellite. Broad or general lessons learned include the value of working closely with the people who perform the calibration of the data as well as those providing archived image and retrieval products. Close interaction between the Los Alamos National Laboratory (LANL) teams was very beneficial to the overall effort as well as the science effort. Secondly, as time goes on we make increasing use of gridded global atmospheric data sets which are products of global weather model data assimilation schemes. The Global Data Assimilation System information is available globally every six hours and the Rapid Update Cycle products are available over much of the North America and its coastal regions every hour. Additionally, we did not anticipate the quantity of validation data or time needed for thorough algorithm validation. Original validation plans called for a small number of intensive validation campaigns soon after launch. One or two intense validation campaigns are needed but are not sufficient to define performance over a range of conditions or for diagnosis of deviations between ground and satellite products. It took more than a year to accumulate a good set of validation data. With regard to the specific programmatic objectives, we feel that we can do a reasonable job on retrieving surface water temperatures well within the 1°C objective under good observing conditions. Before the loss of the onboard calibration system, sea surface retrievals were usually within 0.5°C. After that, the retrievals are usually within 0.8°C during the day and 0.5°C at night. Daytime atmospheric water vapor retrievals have a scatter that was anticipated: within 20%. However, there is error in using the Aerosol Robotic Network retrievals as validation data which may be due to some combination of calibration uncertainties, errors in the ground retrievals, the method of comparison, and incomplete physics. Calibration of top-of-atmosphere radiance measurements to surface reflectance has proven daunting. We are not alone here: it is a difficult problem to solve generally and the main issue is proper compensation for aerosol effects. Getting good reflectance validation data over a number of sites has proven difficult but, when assumptions are met, the algorithm usually performs quite well. Aerosol retrievals for off-nadir views seem to perform better than near-nadir views and the reason for this is under investigation. Land surface temperature retrieval and temperature-emissivity separations are difficult to perform accurately with multispectral sensors. An interactive cloud masking system was implemented for production use. Clouds are so spectrally and spatially variable that users are encouraged to carefully evaluate the delivered mask for their own needs. The same is true for the water mask. This mask is generated from a spectral index that works well for deep, clear water, but there is much variability in water spectral reflectance inland and along coasts. The value of the second-look maneuvers has not yet been fully or systematically evaluated. Early experiences indicated that the original intentions have marginal value for MTI objectives, but potentially important new ideas have been developed. Image registration (the alignment of data from different focal planes) and band-to-band registration has been a difficult problem to solve, at least for mass production of the images in a processing pipeline. The problems, and their solutions, are described in another paper.

LANL MTI science team experience

NASA Astrophysics Data System (ADS)

Balick, Lee K.; Borel, Christopher C.; Chylek, Petr; Clodius, William B.; Davis, Anthony B.; Henderson, Bradley G.; Galbraith, Amy E.; Lawson, Stefanie L.; Pope, Paul A.; Rodger, Andrew P.; Theiler, James P.

2004-01-01

The Multispectral Thermal Imager (MTI) is a technology test and demonstration satellite whose primary mission involved a finite number of technical objectives. MTI was not designed, or supported, to become a general purpose operational satellite. The role of the MTI science team is to provide a core group of system-expert scientists who perform the scientific development and technical evaluations needed to meet programmatic objectives. Another mission for the team is to develop algorithms to provide atmospheric compensation and quantitative retrieval of surface parameters to a relatively small community of MTI users. Finally, the science team responds and adjusts to unanticipated events in the life of the satellite. Broad or general lessons learned include the value of working closely with the people who perform the calibration of the data as well as those providing archived image and retrieval products. Close interaction between the Los Alamos National Laboratory (LANL) teams was very beneficial to the overall effort as well as the science effort. Secondly, as time goes on we make increasing use of gridded global atmospheric data sets which are products of global weather model data assimilation schemes. The Global Data Assimilation System information is available globally every six hours and the Rapid Update Cycle products are available over much of the North America and its coastal regions every hour. Additionally, we did not anticipate the quantity of validation data or time needed for thorough algorithm validation. Original validation plans called for a small number of intensive validation campaigns soon after launch. One or two intense validation campaigns are needed but are not sufficient to define performance over a range of conditions or for diagnosis of deviations between ground and satellite products. It took more than a year to accumulate a good set of validation data. With regard to the specific programmatic objectives, we feel that we can do a reasonable job on retrieving surface water temperatures well within the 1°C objective under good observing conditions. Before the loss of the onboard calibration system, sea surface retrievals were usually within 0.5°C. After that, the retrievals are usually within 0.8°C during the day and 0.5°C at night. Daytime atmospheric water vapor retrievals have a scatter that was anticipated: within 20%. However, there is error in using the Aerosol Robotic Network retrievals as validation data which may be due to some combination of calibration uncertainties, errors in the ground retrievals, the method of comparison, and incomplete physics. Calibration of top-of-atmosphere radiance measurements to surface reflectance has proven daunting. We are not alone here: it is a difficult problem to solve generally and the main issue is proper compensation for aerosol effects. Getting good reflectance validation data over a number of sites has proven difficult but, when assumptions are met, the algorithm usually performs quite well. Aerosol retrievals for off-nadir views seem to perform better than near-nadir views and the reason for this is under investigation. Land surface temperature retrieval and temperature-emissivity separations are difficult to perform accurately with multispectral sensors. An interactive cloud masking system was implemented for production use. Clouds are so spectrally and spatially variable that users are encouraged to carefully evaluate the delivered mask for their own needs. The same is true for the water mask. This mask is generated from a spectral index that works well for deep, clear water, but there is much variability in water spectral reflectance inland and along coasts. The value of the second-look maneuvers has not yet been fully or systematically evaluated. Early experiences indicated that the original intentions have marginal value for MTI objectives, but potentially important new ideas have been developed. Image registration (the alignment of data from different focal planes) and band-to-band registration has been a difficult problem to solve, at least for mass production of the images in a processing pipeline. The problems, and their solutions, are described in another paper.

Solving for the Surface: An Automated Approach to THEMIS Atmospheric Correction

NASA Astrophysics Data System (ADS)

Ryan, A. J.; Salvatore, M. R.; Smith, R.; Edwards, C. S.; Christensen, P. R.

2013-12-01

Here we present the initial results of an automated atmospheric correction algorithm for the Thermal Emission Imaging System (THEMIS) instrument, whereby high spectral resolution Thermal Emission Spectrometer (TES) data are queried to generate numerous atmospheric opacity values for each THEMIS infrared image. While the pioneering methods of Bandfield et al. [2004] also used TES spectra to atmospherically correct THEMIS data, the algorithm presented here is a significant improvement because of the reduced dependency on user-defined inputs for individual images. Additionally, this technique is particularly useful for correcting THEMIS images that have captured a range of atmospheric conditions and/or surface elevations, issues that have been difficult to correct for using previous techniques. Thermal infrared observations of the Martian surface can be used to determine the spatial distribution and relative abundance of many common rock-forming minerals. This information is essential to understanding the planet's geologic and climatic history. However, the Martian atmosphere also has absorptions in the thermal infrared which complicate the interpretation of infrared measurements obtained from orbit. TES has sufficient spectral resolution (143 bands at 10 cm-1 sampling) to linearly unmix and remove atmospheric spectral end-members from the acquired spectra. THEMIS has the benefit of higher spatial resolution (~100 m/pixel vs. 3x5 km/TES-pixel) but has lower spectral resolution (8 surface sensitive spectral bands). As such, it is not possible to isolate the surface component by unmixing the atmospheric contribution from the THEMIS spectra, as is done with TES. Bandfield et al. [2004] developed a technique using atmospherically corrected TES spectra as tie-points for constant radiance offset correction and surface emissivity retrieval. This technique is the primary method used to correct THEMIS but is highly susceptible to inconsistent results if great care in the selection of TES spectra is not exercised. Our algorithm implements a newly populated TES database that was created using PostgreSQL/PostGIS geospatial database. TES pixels that meet user-defined quality criteria and that intersect a THEMIS observation of interest may be quickly retrieved using this new database. The THEMIS correction process [Bandfield et al. 2004] is then run using all TES pixels that pass an additional set of TES-THEMIS relational quality checks. The result is a spatially correlated set of atmospheric opacity values, determined from the difference between each atmospherically corrected TES pixel and the overlapping portion of the THEMIS image. The dust and ice contributions to the atmospheric opacity are estimated using known dust and ice spectral dependencies [Smith et al. 2003]. These opacity values may be used to determine atmospheric variation across the scene, from which topography- and temperature-scaled atmospheric contribution may be calculated and removed. References: Bandfield, JL et al. [2004], JGR 109, E10008. Smith, MD et al. [2003], JGR 108, E11, 5115.

Sensitivity analysis of observed reflectivity to ice particle surface roughness using MISR satellite observations

NASA Astrophysics Data System (ADS)

Bell, A.; Hioki, S.; Wang, Y.; Yang, P.; Di Girolamo, L.

2016-12-01

Previous studies found that including ice particle surface roughness in forward light scattering calculations significantly reduces the differences between observed and simulated polarimetric and radiometric observations. While it is suggested that some degree of roughness is desirable, the appropriate degree of surface roughness to be assumed in operational cloud property retrievals and the sensitivity of retrieval products to this assumption remains uncertain. In an effort to extricate this ambiguity, we will present a sensitivity analysis of space-borne multi-angle observations of reflectivity, to varying degrees of surface roughness. This process is two fold. First, sampling information and statistics of Multi-angle Imaging SpectroRadiometer (MISR) sensor data aboard the Terra platform, will be used to define the most coming viewing observation geometries. Using these defined geometries, reflectivity will be simulated for multiple degrees of roughness using results from adding-doubling radiative transfer simulations. Sensitivity of simulated reflectivity to surface roughness can then be quantified, thus yielding a more robust retrieval system. Secondly, sensitivity of the inverse problem will be analyzed. Spherical albedo values will be computed by feeding blocks of MISR data comprising cloudy pixels over ocean into the retrieval system, with assumed values of surface roughness. The sensitivity of spherical albedo to the inclusion of surface roughness can then be quantified, and the accuracy of retrieved parameters can be determined.

Optimisation of sea surface current retrieval using a maximum cross correlation technique on modelled sea surface temperature

NASA Astrophysics Data System (ADS)

Heuzé, Céline; Eriksson, Leif; Carvajal, Gisela

2017-04-01

Using sea surface temperature from satellite images to retrieve sea surface currents is not a new idea, but so far its operational near-real time implementation has not been possible. Validation studies are too region-specific or uncertain, due to the errors induced by the images themselves. Moreover, the sensitivity of the most common retrieval method, the maximum cross correlation, to the three parameters that have to be set is unknown. Using model outputs instead of satellite images, biases induced by this method are assessed here, for four different seas of Western Europe, and the best of nine settings and eight temporal resolutions are determined. For all regions, tracking a small 5 km pattern from the first image over a large 30 km region around its original location on a second image, separated from the first image by 6 to 9 hours returned the most accurate results. Moreover, for all regions, the problem is not inaccurate results but missing results, where the velocity is too low to be picked by the retrieval. The results are consistent both with limitations caused by ocean surface current dynamics and with the available satellite technology, indicating that automated sea surface current retrieval from sea surface temperature images is feasible now, for search and rescue operations, pollution confinement or even for more energy efficient and comfortable ship navigation.

On the wintertime low bias of Northern Hemisphere carbon monoxide found in global model simulations

NASA Astrophysics Data System (ADS)

Stein, O.; Schultz, M. G.; Bouarar, I.; Clark, H.; Huijnen, V.; Gaudel, A.; George, M.; Clerbaux, C.

2014-09-01

Despite the developments in the global modelling of chemistry and of the parameterization of the physical processes, carbon monoxide (CO) concentrations remain underestimated during Northern Hemisphere (NH) winter by most state-of-the-art chemistry transport models. The consequential model bias can in principle originate from either an underestimation of CO sources or an overestimation of its sinks. We address both the role of surface sources and sinks with a series of MOZART (Model for Ozone And Related Tracers) model sensitivity studies for the year 2008 and compare our results to observational data from ground-based stations, satellite observations, and vertical profiles from measurements on passenger aircraft. In our base case simulation using MACCity (Monitoring Atmospheric Composition and Climate project) anthropogenic emissions, the near-surface CO mixing ratios are underestimated in the Northern Hemisphere by more than 20 ppb from December to April, with the largest bias of up to 75 ppb over Europe in January. An increase in global biomass burning or biogenic emissions of CO or volatile organic compounds (VOCs) is not able to reduce the annual course of the model bias and yields concentrations over the Southern Hemisphere which are too high. Raising global annual anthropogenic emissions with a simple scaling factor results in overestimations of surface mixing ratios in most regions all year round. Instead, our results indicate that anthropogenic CO and, possibly, VOC emissions in the MACCity inventory are too low for the industrialized countries only during winter and spring. Reasonable agreement with observations can only be achieved if the CO emissions are adjusted seasonally with regionally varying scaling factors. A part of the model bias could also be eliminated by exchanging the original resistance-type dry deposition scheme with a parameterization for CO uptake by oxidation from soil bacteria and microbes, which reduces the boreal winter dry deposition fluxes. The best match to surface observations, satellite retrievals, and aircraft observations was achieved when the modified dry deposition scheme was combined with increased wintertime road traffic emissions over Europe and North America (factors up to 4.5 and 2, respectively). One reason for the apparent underestimation of emissions may be an exaggerated downward trend in the Representative Concentration Pathway (RCP) 8.5 scenario in these regions between 2000 and 2010, as this scenario was used to extrapolate the MACCity emissions from their base year 2000. This factor is potentially amplified by a lack of knowledge about the seasonality of emissions. A methane lifetime of 9.7 yr for our basic model and 9.8 yr for the optimized simulation agrees well with current estimates of global OH, but we cannot fully exclude a potential effect from errors in the geographical and seasonal distribution of OH concentrations on the modelled CO.

New capabilities for characterizing smoke and dust aerosol over land using MODIS

NASA Astrophysics Data System (ADS)

Levy, R. C.; Remer, L. A.

2006-12-01

Smoke and dust aerosol have different chemical, optical and physical properties and both types affect many processes within the climate system. As earth's surface and atmosphere are continuously altered by natural and anthropogenic processes, the emission and presumably the effects of these aerosols are also changing. Thus it is necessary to observe and characterize aerosols on a global and climatic scale. While MODIS has been reporting characteristics of smoke and dust aerosol over land and ocean since shortly after Terra launch, the uncertainties in the over-land retrieval have been larger than expected. To better characterize different aerosol types closer to their source regions with greater accuracy, we have developed a new operational algorithm for retrieving aerosol properties over dark land surfaces from MODIS-observed visible (VIS) and infrared (IR) reflectance. Like earlier versions, this algorithm estimates the total loading (aerosol optical depth-τ) and relative weighting of fine (non-dust) and coarse (dust) -dominated aerosol to the total τ (fine weighting-η) over dark land surfaces. However, the fundamental mathematics and major assumptions have been overhauled. The new algorithm performs simultaneous multi-channel inversion that includes information about coarse aerosol in the IR channels, while assuming a fine-tuned relationship between VIS and IR surface reflectances, that is itself a function of scattering angle and vegetation condition. Finally, the suite of expected aerosol optical models described by the lookup table have been revised to closer resemble the AERONET climatology, including for smoke and dust aerosol. Beginning in April 2006, this algorithm has been used for forward processing and backward re- processing of the entire MODIS dataset observed from both Terra and Aqua. "Collection 5" products were completed for Aqua reprocessing by July 2006 and should be complete for Terra by December 2006. In this study, we used the complete Aqua dataset (July 2002-Aug 2006) and two years of Terra (2005-Aug 2006) data to evaluate the products in regions known to be dominated by smoke and/or dust. We compared with sunphotometer data at selected AERONET sites and found improved τ retrievals,within prescribed accuracy.

Retrieving optical constants of glasses with variable iron abundance

NASA Astrophysics Data System (ADS)

Carli, C.; Roush, T. L.; Capaccioni, F.; Baraldi, A.

2013-12-01

Visible and Near Infrared (VNIR, ~0.4-2.5 μm) spectroscopy is an important tool to explore the surface composition of objects in our Solar System. Using this technique different minerals have been recognized on the surfaces of solar system bodies. One of the principal products of extrusive volcanism and impact cratering is a glassy component, that can be abundant and thus significantly influence the spectral signature of the region investigated. Different types of glasses have been proposed and identified on the lunar surface and in star forming regions near young stellar objects. Here we report an initial effort of retrieving the optical constants of volcanic glasses formed in oxidizing terrestrial-like conditions. We also investigated how those calculations are affected by the grain size distribution. Bidirectional reflectance spectra, obtained with incidence and emission angles of 30° and 0°, respectively, were measured on powders of different grain sizes for four different glassy compositions in the VNIR. Hapke's model of the interaction of light with particulate surfaces was used to determine the imaginary index, k, at each wavelength by iteratively minimizing the difference between measured and calculated reflectance The basic approach to retrieving the optical constants was to use multiple grain sizes of the same sample and assume all grain sizes are compositionally equivalent. Unless independently known as a function of wavelength, an additional assumption must be made regarding the real index of refraction, n. The median size for each particle size separate was adopted for initially estimating k. Then, iterating the Hapke analysis results with a subtractive Kramers-Kronig analysis we were able to determine the wavelength dependence of n. For each composition we used the k-values estimated for all the grain sizes to calculate a mean k-value representing that composition. These values were then used to fit the original spectra by only varying the grain sizes. As a separate estimate of the k-values, we will use transmission measurements in the VNIR. Two slabs, with different thicknesses, will be measured for each composition. These data will be used to determine a k value and a comparison between k values obtained from the two different techniques will be discussed.

Retrieval and Validation of aerosol optical properties from AHI measurements: impact of surface reflectance assumption

NASA Astrophysics Data System (ADS)

Lim, H.; Choi, M.; Kim, J.; Go, S.; Chan, P.; Kasai, Y.

2017-12-01

This study attempts to retrieve the aerosol optical properties (AOPs) based on the spectral matching method, with using three visible and one near infrared channels (470, 510, 640, 860nm). This method requires the preparation of look-up table (LUT) approach based on the radiative transfer modeling. Cloud detection is one of the most important processes for guaranteed quality of AOPs. Since the AHI has several infrared channels, which are very advantageous for cloud detection, clouds can be removed by using brightness temperature difference (BTD) and spatial variability test. The Yonsei Aerosol Retrieval (YAER) algorithm is basically utilized on a dark surface, therefore a bright surface (e.g., desert, snow) should be removed first. Then we consider the characteristics of the reflectance of land and ocean surface using three visible channels. The known surface reflectivity problem in high latitude area can be solved in this algorithm by selecting appropriate channels through improving tests. On the other hand, we retrieved the AOPs by obtaining the visible surface reflectance using NIR to normalized difference vegetation index short wave infrared (NDVIswir) relationship. ESR tends to underestimate urban and cropland area, we improved the visible surface reflectance considering urban effect. In this version, ocean surface reflectance is using the new cox and munk method which considers ocean bidirectional reflectance distribution function (BRDF). Input of this method has wind speed, chlorophyll, salinity and so on. Based on validation results with the sun-photometer measurement in AErosol Robotic NETwork (AERONET), we confirm that the quality of Aerosol Optical Depth (AOD) from the YAER algorithm is comparable to the product from the Japan Aerospace Exploration Agency (JAXA) retrieval algorithm. Our future update includes a consideration of improvement land surface reflectance by hybrid approach, and non-spherical aerosols. This will improve the quality of YAER algorithm more, particularly retrieval for the dust particle over the bright surface in East Asia.

Background concentrations for high resolution satellite observing systems of methane

NASA Astrophysics Data System (ADS)

Benmergui, J. S.; Propp, A. M.; Turner, A. J.; Wofsy, S. C.

2017-12-01

Emerging satellite technologies promise to measure total column dry-air mole fractions of methane (XCH4) at resolutions on the order of a kilometer. XCH4 is linearly related to regional methane emissions through enhancements in the mixed layer, giving these satellites the ability to constrain emissions at unprecedented resolution. However, XCH4 is also sensitive to variability in transport of upwind concentrations (the "background concentration"). Variations in the background concentration are caused by synoptic scale transport in both the free troposphere and the stratosphere, as well as the rate of methane oxidation. Misspecification of the background concentration is aliased onto retrieved emissions as bias. This work explores several methods of specifying the background concentration for high resolution satellite observations of XCH4. We conduct observing system simulation experiments (OSSEs) that simulate the retrieval of emissions in the Barnett Shale using observations from a 1.33 km resolution XCH4 imaging satellite. We test background concentrations defined (1) from an external continental-scale model, (2) using pixels along the edge of the image as a boundary value, (3) using differences between adjacent pixels, and (4) using differences between the same pixel separated by one hour in time. We measure success using the accuracy of the retrieval, the potential for bias induced by misspecification of the background, and the computational expedience of the method. Pathological scenarios are given to each method.

Influence of Solar-Geomagnetic Disturbances on SABER Measurements of 4.3 Micrometer Emission and the Retrieval of Kinetic Temperature and Carbon Dioxide

NASA Technical Reports Server (NTRS)

Mertens, Christopher J.; Winick, Jeremy R.; Picard, Richard H.; Evans, David S.; Lopez-Puertas, Manuel; Wintersteiner, Peter P.; Xu, Xiaojing; Mlynczak, Martin G.; Russell, James M., III

2008-01-01

Thermospheric infrared radiance at 4.3 micrometers is susceptible to the influence of solar-geomagnetic disturbances. Ionization processes followed by ion-neutral chemical reactions lead to vibrationally excited NO(+) (i.e., NO(+)(v)) and subsequent 4.3 micrometer emission in the ionospheric E-region. Large enhancements of nighttime 4.3 m emission were observed by the TIMED/SABER instrument during the April 2002 and October-November 2003 solar storms. Global measurements of infrared 4.3 micrometer emission provide an excellent proxy to observe the nighttime E-region response to auroral dosing and to conduct a detailed study of E-region ion-neutral chemistry and energy transfer mechanisms. Furthermore, we find that photoionization processes followed by ion-neutral reactions during quiescent, daytime conditions increase the NO(+) concentration enough to introduce biases in the TIMED/SABER operational processing of kinetic temperature and CO2 data, with the largest effect at summer solstice. In this paper, we discuss solar storm enhancements of 4.3 micrometer emission observed from SABER and assess the impact of NO(+)(v) 4.3 micrometer emission on quiescent, daytime retrievals of Tk/CO2 from the SABER instrument.

Below the Surface: Analogical Similarity and Retrieval Competition in Reminding.

ERIC Educational Resources Information Center

Wharton, Charles M.; And Others

1994-01-01

Three experiments involving 222 undergraduates investigated whether and when human memory retrieval is influenced by structural consistency. In all experiments, retrieval competition was manipulated. Results indicate that both retrieval competition and structural consistency influence reminding. Implications for psychological and artificial…

Evaluating the Effects of Surface Properties on Methane Detection with the Airborne Visible/Infrared Imaging Spectrometer Next Generation (AVIRIS-NG)

NASA Astrophysics Data System (ADS)

Ayasse, A.; Thorpe, A. K.; Roberts, D. A.; Aubrey, A. D.; Dennison, P. E.; Thompson, D. R.; Frankenberg, C.

2016-12-01

Atmospheric methane has been increasing since the industrial revolution and is thought to be responsible for about 25% of global radiative forcing (Hofman et al., 2006; Montzka et al., 2011). Given the importance of methane to global climate, it is essential that we identify methane sources to better understand the proportion of emissions coming from various sectors. Recently the Airborne Visible-Infrared Imaging Spectrometer Next Generation (AVIRIS-NG) has proven to be a valuable instrument for mapping methane plumes (Frankenberg et al., 2016; Thorpe et al., 2016; Thompson et al., 2015). However, it is important to determine how land cover and albedo affect the ability of AVIRIS-NG to detect methane. This study aims to quantify the effect these surface properties have on detection. To do so we are using a synthetic AVIRIS-NG image that has multiple land cover types, albedos, and methane concentrations and applying the Cluster Tunes Matched Filter (CTMF) algorithm (Funk et al. 2001, Thorpe et al., 2013) to detect methane enhancements within the image. CTMF results are compared to the surface properties to characterize how different surface properties affect detection. We will also evaluate the effect of surface properties with examples of methane plumes observed from oil fields and manure ponds in the San Joaquin Valley of California, two important methane sources (Figure 1). Initial results suggest that darker surfaces, such as water absent sun glint, will make detecting the methane signal challenging, while bright surfaces such as dry soils produce a much clearer signal. Characterizing the effect of surface properties on methane detection is of increasing importance given the application of this technology will likely expand to map methane across a diverse range of emission sources. Figure 1. AVIRIS-NG image acquired Apr. 29, 2015. True color image with a superimposed methane plume from a manure pond. Bright surfaces, such as the dirt road, provide a better surface for retrievals than dark surfaces, such as the vegetation.

The Imaging Spectrometric Observatory for the ATLAS 1 mission

NASA Technical Reports Server (NTRS)

Torr, Douglas G.

1995-01-01

The Imaging Spectrometric Observatory (ISO) was flown on the ATLAS 1 mission and was enormously successful, providing a baseline database on the coupled stratospheric, mesospheric, thermospheric, and ionospheric regions. Specific ISO accomplishments include measurements of the hydroxyl radical, studies of the global ionosphere, retrieval of the concentrations of neutral species from the ISO data, studies of mesospheric oxygen emissions, retrieval of mesospheric O from oxygen emissions, studies of the OH Meinel bands and the search for the Herzberg III bands, search for metallic species, studies of thermospheric nitric oxide, auroral study of molecular nitrogen emissions, and studies of thermospheric species. Apart from participation in the data analysis, the primary post-flight responsibility of Marshall Space Flight Center was the delivery of the final post mission dataset. Support provided by the University of Alabama in Huntsville is described.

SEM and EDS investigation of a pyrolytic carbon covered C/C composite maxillofacial implant retrieved from the human body after 8 years.

PubMed

Sebők, Béla; Kiss, Gábor; Szabó, Péter J; Rigler, Dániel; Molnár, Milán L; Dobos, Gábor; Réti, Ferenc; Szőcs, Hajnal; Joób, Arpád F; Bogdán, Sándor; Szabó, György

2013-03-01

The long term effect of the human body on a pyrolytic carbon covered C/C composite maxillofacial implant (CarBulat(Tm)) was investigated by comparing the structure, the surface morphology and composition of an implant retrieved after 8 years to a sterilized, but not implanted one. Although the thickness of the carbon fibres constituting the implants did not change during the 8 year period, the surface of the implant retrieved was covered with a thin surface layer not present on the unimplanted implant. The composition of this layer is identical to the composition of the underlying carbon fibres. Calcium can only be detected on the surface as a trace element implying that the new layer is not formed by bone tissue. Residual soft tissue penetrating the bulk material between the carbon fibre bunches was found on the retrieved implant indicating the importance of the surface morphology in tissue growth and adhering to implants.

A triggered mechanism retrieves membrane in seconds after Ca(2+)- stimulated exocytosis in single pituitary cells

PubMed Central

1994-01-01

In neuroendocrine cells, cytosolic Ca2+ triggers exocytosis in tens of milliseconds, yet known pathways of endocytic membrane retrieval take minutes. To test for faster retrieval mechanisms, we have triggered short bursts of exocytosis by flash photolysis of caged Ca2+, and have tracked subsequent retrieval by measuring the plasma membrane capacitance. We find that a limited amount of membrane can be retrieved with a time constant of 4 s at 21-26 degrees C, and that this occurs partially via structures larger than coated vesicles. This novel mechanism may be arrested at a late step. Incomplete retrieval structures then remain on the cell surface for minutes until the consequences of a renewed increase in cytosolic [Ca2+] disconnect them from the cell surface in < 1 s. Our results provide evidence for a rapid, triggered membrane retrieval pathway in excitable cells. PMID:8120090

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.

AIRS Data Service at NASA Goddard Earth Sciences Data and Information Services (GES DISC) and Its Application to Climate Change Study

NASA Technical Reports Server (NTRS)

Won, Young-In; Vollimer, Bruce; Theobald, Mike; Hua, Xin-Min

2008-01-01

The Atmospheric Infrared Sounder (AIRS) instrument suite is designed to observe and characterize the entire atmospheric column from the surface to the top of the atmosphere in terms of surface emissivity and temperature, atmospheric temperature and humidity profiles, cloud amount and height, and the spectral outgoing infrared radiation on a global scale. The AIRS Data Support Team at the GES DISC provides data support to assist others in understanding, retrieving and extracting information from the AIRS/AMSU/HSB data products. Because a number of years has passed since its operation started, the amount of data has reached a certain level of maturity where we can address the climate change study utilizing AIRS data, In this presentation we will list various service we provide and to demonstrate how to utilize/apply the existing service to long-term and short-term variability study.

MAPIR: An Airborne Polarmetric Imaging Radiometer in Support of Hydrologic Satellite Observations

NASA Technical Reports Server (NTRS)

Laymon, C.; Al-Hamdan, M.; Crosson, W.; Limaye, A.; McCracken, J.; Meyer, P.; Richeson, J.; Sims, W.; Srinivasan, K.; Varnevas, K.

2010-01-01

In this age of dwindling water resources and increasing demands, accurate estimation of water balance components at every scale is more critical to end users than ever before. Several near-term Earth science satellite missions are aimed at global hydrologic observations. The Marshall Airborne Polarimetric Imaging Radiometer (MAPIR) is a dual beam, dual angle polarimetric, scanning L band passive microwave radiometer system developed by the Observing Microwave Emissions for Geophysical Applications (OMEGA) team at MSFC to support algorithm development and validation efforts in support of these missions. MAPIR observes naturally-emitted radiation from the ground primarily for remote sensing of land surface brightness temperature from which we can retrieve soil moisture and possibly surface or water temperature and ocean salinity. MAPIR has achieved Technical Readiness Level 6 with flight heritage on two very different aircraft, the NASA P-3B, and a Piper Navajo.

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.

Global Precipitation Measurement (GPM) Mission: Precipitation Processing System (PPS) GPM Mission Gridded Text Products Provide Surface Precipitation Retrievals

NASA Technical Reports Server (NTRS)

Stocker, Erich Franz; Kelley, O.; Kummerow, C.; Huffman, G.; Olson, W.; Kwiatkowski, J.

2015-01-01

In February 2015, the Global Precipitation Measurement (GPM) mission core satellite will complete its first year in space. The core satellite carries a conically scanning microwave imager called the GPM Microwave Imager (GMI), which also has 166 GHz and 183 GHz frequency channels. The GPM core satellite also carries a dual frequency radar (DPR) which operates at Ku frequency, similar to the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar, and a new Ka frequency. The precipitation processing system (PPS) is producing swath-based instantaneous precipitation retrievals from GMI, both radars including a dual-frequency product, and a combined GMIDPR precipitation retrieval. These level 2 products are written in the HDF5 format and have many additional parameters beyond surface precipitation that are organized into appropriate groups. While these retrieval algorithms were developed prior to launch and are not optimal, these algorithms are producing very creditable retrievals. It is appropriate for a wide group of users to have access to the GPM retrievals. However, for researchers requiring only surface precipitation, these L2 swath products can appear to be very intimidating and they certainly do contain many more variables than the average researcher needs. Some researchers desire only surface retrievals stored in a simple easily accessible format. In response, PPS has begun to produce gridded text based products that contain just the most widely used variables for each instrument (surface rainfall rate, fraction liquid, fraction convective) in a single line for each grid box that contains one or more observations.This paper will describe the gridded data products that are being produced and provide an overview of their content. Currently two types of gridded products are being produced: (1) surface precipitation retrievals from the core satellite instruments GMI, DPR, and combined GMIDPR (2) surface precipitation retrievals for the partner constellation satellites. Both of these gridded products are generated for a.25 degree x.25 degree hourly grid, which are packaged into daily ASCII (American Standard Code for Information Interchange) files that can downloaded from the PPS FTP (File Transfer Protocol) site. To reduce the download size, the files are compressed using the gzip utility.This paper will focus on presenting high-level details about the gridded text product being generated from the instruments on the GPM core satellite. But summary information will also be presented about the partner radiometer gridded product. All retrievals for the partner radiometer are done using the GPROF2014 algorithmusing as input the PPS generated inter-calibrated 1C product for the radiometer.

GPM Mission Gridded Text Products Providing Surface Precipitation Retrievals

NASA Astrophysics Data System (ADS)

Stocker, Erich Franz; Kelley, Owen; Huffman, George; Kummerow, Christian

2015-04-01

In February 2015, the Global Precipitation Measurement (GPM) mission core satellite will complete its first year in space. The core satellite carries a conically scanning microwave imager called the GPM Microwave Imager (GMI), which also has 166 GHz and 183 GHz frequency channels. The GPM core satellite also carries a dual frequency radar (DPR) which operates at Ku frequency, similar to the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar), and a new Ka frequency. The precipitation processing system (PPS) is producing swath-based instantaneous precipitation retrievals from GMI, both radars including a dual-frequency product, and a combined GMI/DPR precipitation retrieval. These level 2 products are written in the HDF5 format and have many additional parameters beyond surface precipitation that are organized into appropriate groups. While these retrieval algorithms were developed prior to launch and are not optimal, these algorithms are producing very creditable retrievals. It is appropriate for a wide group of users to have access to the GPM retrievals. However, for reseachers requiring only surface precipitation, these L2 swath products can appear to be very intimidating and they certainly do contain many more variables than the average researcher needs. Some researchers desire only surface retrievals stored in a simple easily accessible format. In response, PPS has begun to produce gridded text based products that contain just the most widely used variables for each instrument (surface rainfall rate, fraction liquid, fraction convective) in a single line for each grid box that contains one or more observations. This paper will describe the gridded data products that are being produced and provide an overview of their content. Currently two types of gridded products are being produced: (1) surface precipitation retrievals from the core satellite instruments - GMI, DPR, and combined GMI/DPR (2) surface precipitation retrievals for the partner constellation satellites. Both of these gridded products are generated for a .25 degree x .25 degree hourly grid, which are packaged into daily ASCII files that can downloaded from the PPS FTP site. To reduce the download size, the files are compressed using the gzip utility. This paper will focus on presenting high-level details about the gridded text product being generated from the instruments on the GPM core satellite. But summary information will also be presented about the partner radiometer gridded product. All retrievals for the partner radiometer are done using the GPROF2014 algorithm using as input the PPS generated inter-calibrated 1C product for the radiometer.

Error sources in the retrieval of aerosol information over bright surfaces from satellite measurements in the oxygen A band

NASA Astrophysics Data System (ADS)

Nanda, Swadhin; de Graaf, Martin; Sneep, Maarten; de Haan, Johan F.; Stammes, Piet; Sanders, Abram F. J.; Tuinder, Olaf; Pepijn Veefkind, J.; Levelt, Pieternel F.

2018-01-01

Retrieving aerosol optical thickness and aerosol layer height over a bright surface from measured top-of-atmosphere reflectance spectrum in the oxygen A band is known to be challenging, often resulting in large errors. In certain atmospheric conditions and viewing geometries, a loss of sensitivity to aerosol optical thickness has been reported in the literature. This loss of sensitivity has been attributed to a phenomenon known as critical surface albedo regime, which is a range of surface albedos for which the top-of-atmosphere reflectance has minimal sensitivity to aerosol optical thickness. This paper extends the concept of critical surface albedo for aerosol layer height retrievals in the oxygen A band, and discusses its implications. The underlying physics are introduced by analysing the top-of-atmosphere reflectance spectrum as a sum of atmospheric path contribution and surface contribution, obtained using a radiative transfer model. Furthermore, error analysis of an aerosol layer height retrieval algorithm is conducted over dark and bright surfaces to show the dependence on surface reflectance. The analysis shows that the derivative with respect to aerosol layer height of the atmospheric path contribution to the top-of-atmosphere reflectance is opposite in sign to that of the surface contribution - an increase in surface brightness results in a decrease in information content. In the case of aerosol optical thickness, these derivatives are anti-correlated, leading to large retrieval errors in high surface albedo regimes. The consequence of this anti-correlation is demonstrated with measured spectra in the oxygen A band from the GOME-2 instrument on board the Metop-A satellite over the 2010 Russian wildfires incident.

Light scatter on the surface of AcrySof intraocular lenses: part I. Analysis of lenses retrieved from pseudophakic postmortem human eyes.

PubMed

Yaguchi, Shigeo; Nishihara, Hitoshi; Kambhiranond, Waraporn; Stanley, Daniel; Apple, David J

2008-01-01

To investigate the cause of light scatter measured on the surface of AcrySof intraocular lenses (Alcon Laboratories, Inc., Fort Worth, TX) retrieved from pseudophakic postmortem human eyes. Ten intraocular lenses (Alcon AcrySofModel MA60BM) were retrieved postmortem and analyzed for light scatter before and after removal of surface-bound biofilms. Six of the 10 lenses exhibited light scatter that was clearly above baseline levels. In these 6 lenses, both peak and average pixel density were reduced by approximately 80% after surface cleaning. The current study demonstrates that a coating deposited in vivo on the lens surface is responsible for the light scatter observed when incident light is applied.

Experiments on transient melting of tungsten by ELMs in ASDEX Upgrade

NASA Astrophysics Data System (ADS)

Krieger, K.; Balden, M.; Coenen, J. W.; Laggner, F.; Matthews, G. F.; Nille, D.; Rohde, V.; Sieglin, B.; Giannone, L.; Göths, B.; Herrmann, A.; de Marne, P.; Pitts, R. A.; Potzel, S.; Vondracek, P.; ASDEX-Upgrade Team; EUROfusion MST1 Team

2018-02-01

Repetitive melting of tungsten by power transients originating from edge localized modes (ELMs) has been studied in ASDEX Upgrade. Tungsten samples were exposed to H-mode discharges at the outer divertor target plate using the divertor manipulator II (DIM-II) system (Herrmann et al 2015 Fusion Eng. Des. 98-9 1496-9). Designed as near replicas of the geometries used also in separate experiments on the JET tokamak (Coenen et al 2015 J. Nucl. Mater. 463 78-84 Coenen et al 2015 Nucl. Fusion 55 023010; Matthews et al 2016 Phys. Scr. T167 7), the samples featured a misaligned leading edge and a sloped ridge respectively. Both structures protrude above the default target plate surface thus receiving an increased fraction of the parallel power flux. Transient melting by ELMs was induced by moving the outer strike point to the sample location. The temporal evolution of the measured current flow from the samples to vessel potential confirmed transient melting. Current magnitude and dependency from surface temperature provided strong evidence for thermionic electron emission as main origin of the replacement current driving the melt motion. The different melt patterns observed after exposures at the two sample geometries support the thermionic electron emission model used in the MEMOS melt motion code, which assumes a strong decrease of the thermionic net current at shallow magnetic field to surface angles (Pitts et al 2017 Nucl. Mater. Energy 12 60-74). Post exposure ex situ analysis of the retrieved samples show recrystallization of tungsten at the exposed surface areas to a depth of up to several mm. The melt layer transport to less exposed surface areas leads to ratcheting pile up of re-solidified debris with zonal growth extending from the already enlarged grains at the surface.

Is ozone model bias driven by errors in cloud predictions? A quantitative assessment using satellite cloud retrievals in WRF-Chem

NASA Astrophysics Data System (ADS)

Ryu, Y. H.; Hodzic, A.; Barré, J.; Descombes, G.; Minnis, P.

2017-12-01

Clouds play a key role in radiation and hence O3 photochemistry by modulating photolysis rates and light-dependent emissions of biogenic volatile organic compounds (BVOCs). It is not well known, however, how much of the bias in O3 predictions is caused by inaccurate cloud predictions. This study quantifies the errors in surface O3 predictions associated with clouds in summertime over CONUS using the Weather Research and Forecasting with Chemistry (WRF-Chem) model. Cloud fields used for photochemistry are corrected based on satellite cloud retrievals in sensitivity simulations. It is found that the WRF-Chem model is able to detect about 60% of clouds in the right locations and generally underpredicts cloud optical depths. The errors in hourly O3 due to the errors in cloud predictions can be up to 60 ppb. On average in summertime over CONUS, the errors in 8-h average O3 of 1-6 ppb are found to be attributable to those in cloud predictions under cloudy sky conditions. The contribution of changes in photolysis rates due to clouds is found to be larger ( 80 % on average) than that of light-dependent BVOC emissions. The effects of cloud corrections on O­3 are about 2 times larger in VOC-limited than NOx-limited regimes, suggesting that the benefits of accurate cloud predictions would be greater in VOC-limited than NOx-limited regimes.

Sensitivity study of the inverse problem on retrieval of the altitude profile of ozone from emission intensities of the molecular oxygen in the MLT

NASA Astrophysics Data System (ADS)

Martyshenko, Kseniia; Yankovsky, Valentine

2015-04-01

Retrieval of the ozone density altitude profile is important problem for energetics of the upper atmosphere. For comparison of methods of retrieval of altitude profiles of ozone concentration from emissions of excited oxygen molecule and atom was used a modern model of electronic-vibrational kinetics of the products of O3 and O2 photolysis YM-2011 [1]. This study uses only a part of the complete model YM-2011 related to population of levels O2(b1Σ+g, v=0-2), O2(a1Δg, v=0-5) and metastable atom O(1D). Thereby, we obtained solutions of the inverse problem of [O3] retrieval from five proxies O2(a1Δg, v = 0), O2(b1Σ+g, v = 0, 1, 2) and O (1D). Theoretically, every proposed emission of excited component could be promising sources of information about [O3], because it depends on [O3] both in production and in quenching. Detailed analysis of the solutions of the inverse problem of [O3] retrieval were conducted by the sensitivity study of these levels for variations of all model parameters at altitudes of z=40-105 km. The maximum values of sensitivity coefficient to [O3] variations have the following components: O2(b1Σ+g, v = 1), O2(a1Δg, v = 0) and O(1D). The sensitivity of all excited component to variations of ozone decreases sharply above 105 km due to a drastic fall of ozone concentration. [O2(b1Σ+g, v=2)] does not depend on ozone completely at the proposed altitudes, and [O2(b1Σ+g, v=0)] has the lowest sensitivity to variations of [O3] among rest components. Based on the results of the sensitivity study authors investigated the ozone altitude profiles retrieval accuracy taking into account uncertainties of all input parameters (solar excitation and photodissociation rates, quantum yields of products and rate constants of aeronomical reactions). Uncertainties of retrieval of altitude profiles of [O3] from [O(1D)] don't exceed 10% in the interval 40-85 km were obtained. Profile of [O2(b1Σ+g, v=1] allows us to retrieval of [O3] with 21% uncertainty at z =40-95 km, and [O2(b1Σ+g, v=0] - 29% at altitudes up to 97 km. Uncertainties of retrieval of altitude profiles of ozone from [O2(a1Δg, v=0)] achieved 21% at altitudes of z=40-89 km, but it's not uniform in height and in the 77-85 km don't exceed 10%. Overall, optimal methods of retrieval of altitude profiles of ozone concentration is the observation volume emission rate of the molecule O2(b1Σ+g, v=1) in the MLT region. 1. Yankovsky V. A., Manuilova R. O., Babaev A. S., Feofilov A. G., Kutepov A. A. 2011. Model of electronic-vibrational kinetics of the O3 and O2 photolysis products in the middle atmosphere: applications to water vapor retrievals from SABER/TIMED 6.3 µm radiance measurements. International Journal of Remote Sensing, V. 33, N. 12, P. 3065-3078.

The CAMS interim Reanalysis of Carbon Monoxide, Ozone and Aerosol for 2003-2015

NASA Astrophysics Data System (ADS)

Flemming, Johannes; Benedetti, Angela; Inness, Antje; Engelen, Richard J.; Jones, Luke; Huijnen, Vincent; Remy, Samuel; Parrington, Mark; Suttie, Martin; Bozzo, Alessio; Peuch, Vincent-Henri; Akritidis, Dimitris; Katragkou, Eleni

2017-02-01

A new global reanalysis data set of atmospheric composition (AC) for the period 2003-2015 has been produced by the Copernicus Atmosphere Monitoring Service (CAMS). Satellite observations of total column (TC) carbon monoxide (CO) and aerosol optical depth (AOD), as well as several TC and profile observations of ozone, have been assimilated with the Integrated Forecasting System for Composition (C-IFS) of the European Centre for Medium-Range Weather Forecasting. Compared to the previous Monitoring Atmospheric Composition and Climate (MACC) reanalysis (MACCRA), the new CAMS interim reanalysis (CAMSiRA) is of a coarser horizontal resolution of about 110 km, compared to 80 km, but covers a longer period with the intent to be continued to present day. This paper compares CAMSiRA with MACCRA and a control run experiment (CR) without assimilation of AC retrievals. CAMSiRA has smaller biases than the CR with respect to independent observations of CO, AOD and stratospheric ozone. However, ozone at the surface could not be improved by the assimilation because of the strong impact of surface processes such as dry deposition and titration with nitrogen monoxide (NO), which were both unchanged by the assimilation. The assimilation of AOD led to a global reduction of sea salt and desert dust as well as an exaggerated increase in sulfate. Compared to MACCRA, CAMSiRA had smaller biases for AOD, surface CO and TC ozone as well as for upper stratospheric and tropospheric ozone. Finally, the temporal consistency of CAMSiRA was better than the one of MACCRA. This was achieved by using a revised emission data set as well as by applying careful selection and bias correction to the assimilated retrievals. CAMSiRA is therefore better suited than MACCRA for the study of interannual variability, as demonstrated for trends in surface CO.

Validation of UARS Microwave Limb Sounder ClO Measurements

NASA Technical Reports Server (NTRS)

Waters, J. W.; Read, W. G.; Froidevaux, L.; Lungu, T. A.; Perun, V. S.; Stachnik, R. A.; Jarnot, R. F.; Cofield, R. E.; Fishbein, E. F.; Flower, D. A.;

Ground-Based Lidar for Atmospheric Boundary Layer Ozone Measurements

NASA Technical Reports Server (NTRS)

Kuang, Shi; Newchurch, Michael J.; Burris, John; Liu, Xiong

2013-01-01

Ground-based lidars are suitable for long-term ozone monitoring as a complement to satellite and ozonesonde measurements. However, current ground-based lidars are unable to consistently measure ozone below 500 m above ground level (AGL) due to both engineering issues and high retrieval sensitivity to various measurement errors. In this paper, we present our instrument design, retrieval techniques, and preliminary results that focus on the high-temporal profiling of ozone within the atmospheric boundary layer (ABL) achieved by the addition of an inexpensive and compact mini-receiver to the previous system. For the first time, to the best of our knowledge, the lowest, consistently achievable observation height has been extended down to 125 m AGL for a ground-based ozone lidar system. Both the analysis and preliminary measurements demonstrate that this lidar measures ozone with a precision generally better than 10% at a temporal resolution of 10 min and a vertical resolution from 150 m at the bottom of the ABL to 550 m at the top. A measurement example from summertime shows that inhomogeneous ozone aloft was affected by both surface emissions and the evolution of ABL structures.

Application of Artificial Neural Networks to the Development of Improved Multi-Sensor Retrievals of Near-Surface Air Temperature and Humidity Over Ocean

NASA Technical Reports Server (NTRS)

Roberts, J. Brent; Robertson, Franklin R.; Clayson, Carol Anne

2012-01-01

Improved estimates of near-surface air temperature and air humidity are critical to the development of more accurate turbulent surface heat fluxes over the ocean. Recent progress in retrieving these parameters has been made through the application of artificial neural networks (ANN) and the use of multi-sensor passive microwave observations. Details are provided on the development of an improved retrieval algorithm that applies the nonlinear statistical ANN methodology to a set of observations from the Advanced Microwave Scanning Radiometer (AMSR-E) and the Advanced Microwave Sounding Unit (AMSU-A) that are currently available from the NASA AQUA satellite platform. Statistical inversion techniques require an adequate training dataset to properly capture embedded physical relationships. The development of multiple training datasets containing only in-situ observations, only synthetic observations produced using the Community Radiative Transfer Model (CRTM), or a mixture of each is discussed. An intercomparison of results using each training dataset is provided to highlight the relative advantages and disadvantages of each methodology. Particular emphasis will be placed on the development of retrievals in cloudy versus clear-sky conditions. Near-surface air temperature and humidity retrievals using the multi-sensor ANN algorithms are compared to previous linear and non-linear retrieval schemes.

CO source contribution analysis for California during ARCTAS-CARB

NASA Astrophysics Data System (ADS)

Pfister, G. G.; Avise, J.; Wiedinmyer, C.; Edwards, D. P.; Emmons, L. K.; Diskin, G. D.; Podolske, J.; Wisthaler, A.

2011-08-01

Air pollution is of concern in many parts of California and is impacted by both local emissions and also by pollution inflow from the North Pacific Ocean. In this study, we use the regional chemical transport model WRF-Chem V3.2 together with the global Model for OZone and Related Chemical Tracers to examine the CO budget over California. We include model CO tracers for different emission sources in the models, which allow estimation of the relative importance of local sources versus pollution inflow on the distribution of CO at the surface and in the free troposphere. The focus of our study is on the 15 June-15 July 2008 time period, which coincides with the aircraft deployment of the NASA Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) mission over California. Model simulations are evaluated using these aircraft observations as well as satellite retrievals and surface observations of CO. Evaluation results show that the model overall predicts the observed CO fields well, but points towards an underestimate of CO from the fires in Northern California, which had a strong influence during the study period, and towards a slight overestimate of CO from pollution inflow and local anthropogenic sources. The analysis of the CO budget over California reveals that inflow of CO explains on average 99 ± 11 ppbV of surface CO during the study period, compared to 61 ± 95 ppbV for local anthropogenic direct emissions of CO and 84 ± 194 ppbV for fires. In the free troposphere, the average CO contributions are estimated as 96 ± 7 ppbV for CO inflow, 8 ± 9 ppbV for CO from local anthropogenic sources and 18 ± 13 ppbV for CO from fires. Accounting for the low bias in the CO fire emission inventory, the fire impact during the study period might have been up to a factor 4 higher than the given estimates.

Inverse Modeling of Surface CH4 and δ13C-CH4 Measurements to Understand Recent Trends in Global Methane Emissions

NASA Astrophysics Data System (ADS)

Karmakar, S.; Butenhoff, C. L.; Rice, A. L.; Lofdahl, D. B.; Khalil, A. K.

2016-12-01

Methane (CH4) is the second most important greenhouse gas with a radiative forcing of 0.97 W/m2 including both direct and indirect effects and a global warming potential of 28 over a 100-year time horizon. Unlike CO2 whose rate of growth in the atmosphere has remained positive and increased in recent decades, the behavior of atmospheric methane is considerably more complex and is much less understood on account of the spatiotemporal variability of its emissions which include biogenic (e.g. wetlands, ruminants, rice agriculture), thermogenic (fossil fuels), and pyrogenic (i.e. biomass burning) sources. After sustained growth during most of the 20th century, the CH4 growth rate declined falling from 15 ppbv/yr during the 1980s to 6 ppbv/yr in the 1990s to near-zero and even negative values in the early 2000s. With some surprise however, the growth rate rebounded in 2007 and has been on average 6 ppbv/yr during the past 10 years. During this same period the 13CH4/12CH4 ratio of atmospheric CH4 also declined suggesting the recent CH4 growth was caused by an increase in 13CH4-depleted biogenic emissions. Here, we provide additional insight into the recent behavior of atmospheric methane by performing a global three-dimensional Bayesian inversion of surface CH4 and 13CH4/12CH4 ratios over the period 1985-2015 using NOAA Global Monitoring Division (GMD) CH4 measurements and the GEOS-Chem chemical-transport model (CTM) at a horizontal grid resolution of 2ox2.5o. The use of the 3-D model allows us to exploit spatial patterns in the global CH4 and 13CH4/12CH4 fields that provide additional constraints on the retrieval of the time-dependent CH4 fluxes. This work follows up on our previous CH4 inversion where we used a 4ox5o horizontal grid for GEOS-Chem to retrieve fluxes from 1985 to 2009. At higher resolution more information is extracted from the observations due to improved model skill and a smaller number of stations aggregated within model grid cells. This increases the weights of the measurements relative to the a priori fluxes in the inversion producing stronger observational constraints on the optimized fluxes. This work assesses the contribution of spatial heterogeneities in the observed CH4 record to the retrieval of global CH4 fluxes and provides a new look into the causes of the recent growth in atmospheric methane.

Transcontinental methane measurements: Part 2. Mobile surface investigation of fossil fuel industrial fugitive emissions

NASA Astrophysics Data System (ADS)

Leifer, Ira; Culling, Daniel; Schneising, Oliver; Farrell, Paige; Buchwitz, Michael; Burrows, John P.

2013-08-01

The potent greenhouse gas, methane, CH4, has a wide variety of anthropogenic and natural sources. Fall, continental-scale (Florida to California) surface CH4 data were collected to investigate the importance of fossil fuel industrial (FFI) emissions in the South US. A total of 6600 measurements along 7020-km of roadways were made by flame ion detection gas chromatography onboard a nearly continuously moving recreational vehicle in 2010. A second, winter survey in Southern California measured CH4 at 2 Hz with a cavity ring-down spectrometer in 2012. Data revealed strong and persistent FFI CH4 sources associated with refining, oil/gas production, a presumed major pipeline leak, and a coal loading plant. Nocturnal CH4 mixing ratios tended to be higher than daytime values for similar sources, sometimes significantly, which was attributed to day/night meteorological differences, primarily changes in the boundary layer height. The highest CH4 mixing ratio (39 ppm) was observed near the Kern River Oil Field, California, which uses steam reinjection. FFI CH4 plume signatures were distinguished as stronger than other sources on local scales. On large (4°) scales, the CH4 trend was better matched spatially with FFI activity than wetland spatial patterns. Qualitative comparison of surface data with SCIAMACHY and GOSAT satellite retrievals showed agreement of the large-scale CH4 spatial patterns. Comparison with inventory models and seasonal winds suggests for some seasons and some portions of the Gulf of Mexico a non-negligible underestimation of FFI emissions. For other seasons and locations, qualitative interpretation is not feasible. Unambiguous quantitative source attribution is more complex, requiring transport modeling.

A Bayesian Retrieval of Greenland Ice Sheet Internal Temperature from Ultra-wideband Software-defined Microwave Radiometer (UWBRAD) Measurements

NASA Astrophysics Data System (ADS)

Duan, Y.; Durand, M. T.; Jezek, K. C.; Yardim, C.; Bringer, A.; Aksoy, M.; Johnson, J. T.

2017-12-01

The ultra-wideband software-defined microwave radiometer (UWBRAD) is designed to provide ice sheet internal temperature product via measuring low frequency microwave emission. Twelve channels ranging from 0.5 to 2.0 GHz are covered by the instrument. A Greenland air-borne demonstration was demonstrated in September 2016, provided first demonstration of Ultra-wideband radiometer observations of geophysical scenes, including ice sheets. Another flight is planned for September 2017 for acquiring measurements in central ice sheet. A Bayesian framework is designed to retrieve the ice sheet internal temperature from simulated UWBRAD brightness temperature (Tb) measurements over Greenland flight path with limited prior information of the ground. A 1-D heat-flow model, the Robin Model, was used to model the ice sheet internal temperature profile with ground information. Synthetic UWBRAD Tb observations was generated via the partially coherent radiation transfer model, which utilizes the Robin model temperature profile and an exponential fit of ice density from Borehole measurement as input, and corrupted with noise. The effective surface temperature, geothermal heat flux, the variance of upper layer ice density, and the variance of fine scale density variation at deeper ice sheet were treated as unknown variables within the retrieval framework. Each parameter is defined with its possible range and set to be uniformly distributed. The Markov Chain Monte Carlo (MCMC) approach is applied to make the unknown parameters randomly walk in the parameter space. We investigate whether the variables can be improved over priors using the MCMC approach and contribute to the temperature retrieval theoretically. UWBRAD measurements near camp century from 2016 was also treated with the MCMC to examine the framework with scattering effect. The fine scale density fluctuation is an important parameter. It is the most sensitive yet highly unknown parameter in the estimation framework. Including the fine scale density fluctuation greatly improved the retrieval results. The ice sheet vertical temperature profile, especially the 10m temperature, can be well retrieved via the MCMC process. Future retrieval work will apply the Bayesian approach to UWBRAD airborne measurements.

Measuring SO2 ship emissions with an ultraviolet imaging camera

NASA Astrophysics Data System (ADS)

Prata, A. J.

2014-05-01

Over the last few years fast-sampling ultraviolet (UV) imaging cameras have been developed for use in measuring SO2 emissions from industrial sources (e.g. power plants; typical emission rates ~ 1-10 kg s-1) and natural sources (e.g. volcanoes; typical emission rates ~ 10-100 kg s-1). Generally, measurements have been made from sources rich in SO2 with high concentrations and emission rates. In this work, for the first time, a UV camera has been used to measure the much lower concentrations and emission rates of SO2 (typical emission rates ~ 0.01-0.1 kg s-1) in the plumes from moving and stationary ships. Some innovations and trade-offs have been made so that estimates of the emission rates and path concentrations can be retrieved in real time. Field experiments were conducted at Kongsfjord in Ny Ålesund, Svalbard, where SO2 emissions from cruise ships were made, and at the port of Rotterdam, Netherlands, measuring emissions from more than 10 different container and cargo ships. In all cases SO2 path concentrations could be estimated and emission rates determined by measuring ship plume speeds simultaneously using the camera, or by using surface wind speed data from an independent source. Accuracies were compromised in some cases because of the presence of particulates in some ship emissions and the restriction of single-filter UV imagery, a requirement for fast-sampling (> 10 Hz) from a single camera. Despite the ease of use and ability to determine SO2 emission rates from the UV camera system, the limitation in accuracy and precision suggest that the system may only be used under rather ideal circumstances and that currently the technology needs further development to serve as a method to monitor ship emissions for regulatory purposes. A dual-camera system or a single, dual-filter camera is required in order to properly correct for the effects of particulates in ship plumes.

Aerosol Optical Retrieval and Surface Reflectance from Airborne Remote Sensing Data over Land

PubMed Central

Bassani, Cristiana; Cavalli, Rosa Maria; Pignatti, Stefano

2010-01-01

Quantitative analysis of atmospheric optical properties and surface reflectance can be performed by applying radiative transfer theory in the Atmosphere-Earth coupled system, for the atmospheric correction of hyperspectral remote sensing data. This paper describes a new physically-based algorithm to retrieve the aerosol optical thickness at 550nm (τ550) and the surface reflectance (ρ) from airborne acquired data in the atmospheric window of the Visible and Near-Infrared (VNIR) range. The algorithm is realized in two modules. Module A retrieves τ550 with a minimization algorithm, then Module B retrieves the surface reflectance ρ for each pixel of the image. The method was tested on five remote sensing images acquired by an airborne sensor under different geometric conditions to evaluate the reliability of the method. The results, τ550 and ρ, retrieved from each image were validated with field data contemporaneously acquired by a sun-sky radiometer and a spectroradiometer, respectively. Good correlation index, r, and low root mean square deviations, RMSD, were obtained for the τ550 retrieved by Module A (r2 = 0.75, RMSD = 0.08) and the ρ retrieved by Module B (r2 ≤ 0.9, RMSD ≤ 0.003). Overall, the results are encouraging, indicating that the method is reliable for optical atmospheric studies and the atmospheric correction of airborne hyperspectral images. The method does not require additional at-ground measurements about at-ground reflectance of the reference pixel and aerosol optical thickness. PMID:22163558

Determination of microwave vegetation optical depth and water content in the source region of the Yellow River

NASA Astrophysics Data System (ADS)

Liu, R.; Wen, J.; Wang, X.

2017-12-01

In this study, we use dual polarization brightness temperature observational data at the K frequency band collected by the Micro Wave Radiation Imager (MWRI) on board the Fengyun-3B satellite (FY-3B) to improve the τ-ω model by considering the contribution of water bodies in the pixels to radiation in the wetland area of the Yellow River source region. We define a dual polarization slope parameter and express the surface emissivity in the τ-ω model as the sum of the soil and water body emissivity to retrieve the vegetation optical depth (VOD); however, in regions without water body coverage, we still use the τ-ω model to solve for the VOD. By using the field observation data on the vegetation water content (VWC) in the source region of the Yellow River during the summer of 2012, we establish the regression relationship between the VOD and VWC and retrieve the spatial distribution of the VWC. The results indicate that in the entire source region of the Yellow River in 2012, the VOD was in the range of 0.20-1.20 and the VWC was in the range of 0.20 to 1.40, thereby exhibiting a trend of low values in the west and high values in the east. The area with the largest regional variation is along the Yellow River. We compare the results from remote-sensing estimated and ground-measured vegetation water content, and the root-mean-square error is 0.12. The analysis results indicated that by considering the coverage of seasonal wetlands in the source region of the Yellow River, the microwave remote sensing data collected by the FY-3B MWRI can be used to retrieve the vegetation water content in the source region of the Yellow River.

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.

Optimizing a remote sensing instrument to measure atmospheric surface pressure

NASA Technical Reports Server (NTRS)

Peckham, G. E.; Gatley, C.; Flower, D. A.

1983-01-01

Atmospheric surface pressure can be remotely sensed from a satellite by an active instrument which measures return echoes from the ocean at frequencies near the 60 GHz oxygen absorption band. The instrument is optimized by selecting its frequencies of operation, transmitter powers and antenna size through a new procedure baesd on numerical simulation which maximizes the retrieval accuracy. The predicted standard deviation error in the retrieved surface pressure is 1 mb. In addition the measurements can be used to retrieve water vapor, cloud liquid water and sea state, which is related to wind speed.

Inter-Comparison of SMOS and Aquarius Sea Surface Salinity: Effects of the Dielectric Constant and Vicarious Calibration

NASA Technical Reports Server (NTRS)

Dinnat, Emmanuel P.; Boutin, Jacqueline; Yin, Xiaobin; Le Vine, David M.

2014-01-01

Two spaceborne instruments share the scientific objective of mapping the global Sea Surface Salinity (SSS). ESA's Soil Moisture and Ocean Salinity (SMOS) and NASA's Aquarius use L-band (1.4 GHz) radiometry to retrieve SSS. We find that SSS retrieved by SMOS is generally lower than SSS retrieved by Aquarius, except for very cold waters where SMOS SSS is higher overall. The spatial distribution of the differences in SSS is similar to the distribution of sea surface temperature. There are several differences in the retrieval algorithm that could explain the observed SSS differences. We assess the impact of the dielectric constant model and the ancillary sea surface salinity used by both missions for calibrating the radiometers and retrieving SSS. The differences in dielectric constant model produce differences in SSS of the order of 0.3 psu and exhibit a dependence on latitude and temperature. We use comparisons with the Argo in situ data to assess the performances of the model in various regions of the globe. Finally, the differences in the ancillary sea surface salinity products used to perform the vicarious calibration of both instruments are relatively small (0.1 psu), but not negligible considering the requirements for spaceborne remote sensing of SSS.

Development and validation of satellite-based estimates of surface visibility

NASA Astrophysics Data System (ADS)

Brunner, J.; Pierce, R. B.; Lenzen, A.

2016-02-01

A satellite-based surface visibility retrieval has been developed using Moderate Resolution Imaging Spectroradiometer (MODIS) measurements as a proxy for Advanced Baseline Imager (ABI) data from the next generation of Geostationary Operational Environmental Satellites (GOES-R). The retrieval uses a multiple linear regression approach to relate satellite aerosol optical depth, fog/low cloud probability and thickness retrievals, and meteorological variables from numerical weather prediction forecasts to National Weather Service Automated Surface Observing System (ASOS) surface visibility measurements. Validation using independent ASOS measurements shows that the GOES-R ABI surface visibility retrieval (V) has an overall success rate of 64.5 % for classifying clear (V ≥ 30 km), moderate (10 km ≤ V < 30 km), low (2 km ≤ V < 10 km), and poor (V < 2 km) visibilities and shows the most skill during June through September, when Heidke skill scores are between 0.2 and 0.4. We demonstrate that the aerosol (clear-sky) component of the GOES-R ABI visibility retrieval can be used to augment measurements from the United States Environmental Protection Agency (EPA) and National Park Service (NPS) Interagency Monitoring of Protected Visual Environments (IMPROVE) network and provide useful information to the regional planning offices responsible for developing mitigation strategies required under the EPA's Regional Haze Rule, particularly during regional haze events associated with smoke from wildfires.

Development and validation of satellite based estimates of surface visibility

NASA Astrophysics Data System (ADS)

Brunner, J.; Pierce, R. B.; Lenzen, A.

2015-10-01

A satellite based surface visibility retrieval has been developed using Moderate Resolution Imaging Spectroradiometer (MODIS) measurements as a proxy for Advanced Baseline Imager (ABI) data from the next generation of Geostationary Operational Environmental Satellites (GOES-R). The retrieval uses a multiple linear regression approach to relate satellite aerosol optical depth, fog/low cloud probability and thickness retrievals, and meteorological variables from numerical weather prediction forecasts to National Weather Service Automated Surface Observing System (ASOS) surface visibility measurements. Validation using independent ASOS measurements shows that the GOES-R ABI surface visibility retrieval (V) has an overall success rate of 64.5% for classifying Clear (V ≥ 30 km), Moderate (10 km ≤ V < 30 km), Low (2 km ≤ V < 10 km) and Poor (V < 2 km) visibilities and shows the most skill during June through September, when Heidke skill scores are between 0.2 and 0.4. We demonstrate that the aerosol (clear sky) component of the GOES-R ABI visibility retrieval can be used to augment measurements from the United States Environmental Protection Agency (EPA) and National Park Service (NPS) Interagency Monitoring of Protected Visual Environments (IMPROVE) network, and provide useful information to the regional planning offices responsible for developing mitigation strategies required under the EPA's Regional Haze Rule, particularly during regional haze events associated with smoke from wildfires.

Derivation of an observation-based map of North African dust emission

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

Evan, Amato T.; Fiedler, Stephanie; Zhao, Chun

Changes in the emission, transport and deposition of aeolian dust have profound effects on regional climate, so that characterizing the lifecycle of dust in observations and improving the representation of dust in global climate models is necessary. A fundamental aspect of characterizing the dust cycle is quantifying surface dust fluxes, yet no spatially explicit estimates of this flux exist for the World’s major source regions. Here we present a novel technique for creating a map of the annual mean emitted dust flux for North Africa based on retrievals of dust storm frequency from the Meteosat Second Generation Spinning Enhanced Visiblemore » and InfraRed Imager (SEVIRI) and the relationship between dust storm frequency and emitted mass flux derived from the output of five models that simulate dust. Our results suggest that 64 (±16)% of all dust emitted from North Africa is from the Bodélé depression, and that 13 (±3)% of the North African dust flux is from a depression lying in the lee of the Aïr and Hoggar Mountains, making this area the second most important region of emission within North Africa.« less

Precipitation from the GPM Microwave Imager and Constellation Radiometers

NASA Astrophysics Data System (ADS)

Kummerow, Christian; Randel, David; Kirstetter, Pierre-Emmanuel; Kulie, Mark; Wang, Nai-Yu

2014-05-01

Satellite precipitation retrievals from microwave sensors are fundamentally underconstrained requiring either implicit or explicit a-priori information to constrain solutions. The radiometer algorithm designed for the GPM core and constellation satellites makes this a-priori information explicit in the form of a database of possible rain structures from the GPM core satellite and a Bayesian retrieval scheme. The a-priori database will eventually come from the GPM core satellite's combined radar/radiometer retrieval algorithm. That product is physically constrained to ensure radiometric consistency between the radars and radiometers and is thus ideally suited to create the a-priori databases for all radiometers in the GPM constellation. Until a robust product exists, however, the a-priori databases are being generated from the combination of existing sources over land and oceans. Over oceans, the Day-1 GPM radiometer algorithm uses the TRMM PR/TMI physically derived hydrometer profiles that are available from the tropics through sea surface temperatures of approximately 285K. For colder sea surface temperatures, the existing profiles are used with lower hydrometeor layers removed to correspond to colder conditions. While not ideal, the results appear to be reasonable placeholders until the full GPM database can be constructed. It is more difficult to construct physically consistent profiles over land due to ambiguities in surface emissivities as well as details of the ice scattering that dominates brightness temperature signatures over land. Over land, the a-priori databases have therefore been constructed by matching satellite overpasses to surface radar data derived from the WSR-88 network over the continental United States through the National Mosaic and Multi-Sensor QPE (NMQ) initiative. Databases are generated as a function of land type (4 categories of increasing vegetation cover as well as 4 categories of increasing snow depth), land surface temperature and total precipitable water. One year of coincident observations, generating 20 and 80 million database entries, depending upon the sensor, are used in the retrieval algorithm. The remaining areas such as sea ice and high latitude coastal zones are filled with a combination of CloudSat and AMSR-E plus MHS observations together with a model to create the equivalent databases for other radiometers in the constellation. The most noteworthy result from the Day-1 algorithm is the quality of the land products when compared to existing products. Unlike previous versions of land algorithms that depended upon complex screening routines to decide if pixels were precipitating or not, the current scheme is free of conditional rain statements and appears to produce rain rate with much greater fidelity than previous schemes. There results will be shown.

Hurricane Imaging Radiometer (HIRAD) Observations of Brightness Temperatures and Ocean Surface Wind Speed and Rain Rate During NASA's GRIP and HS3 Campaigns

NASA Technical Reports Server (NTRS)

Miller, Timothy L.; James, M. W.; Roberts, J. B.; Jones, W. L.; Biswas, S.; Ruf, C. S.; Uhlhorn, E. W.; Atlas, R.; Black, P.; Albers, C.

2012-01-01

HIRAD flew on high-altitude aircraft over Earl and Karl during NASA s GRIP (Genesis and Rapid Intensification Processes) campaign in August - September of 2010, and plans to fly over Atlantic tropical cyclones in September of 2012 as part of the Hurricane and Severe Storm Sentinel (HS3) mission. HIRAD is a new C-band radiometer using a synthetic thinned array radiometer (STAR) technology to obtain spatial resolution of approximately 2 km, out to roughly 30 km each side of nadir. By obtaining measurements of emissions at 4, 5, 6, and 6.6 GHz, observations of ocean surface wind speed and rain rate can be retrieved. The physical retrieval technique has been used for many years by precursor instruments, including the Stepped Frequency Microwave Radiometer (SFMR), which has been flying on the NOAA and USAF hurricane reconnaissance aircraft for several years to obtain observations within a single footprint at nadir angle. Results from the flights during the GRIP and HS3 campaigns will be shown, including images of brightness temperatures, wind speed, and rain rate. Comparisons will be made with observations from other instruments on the campaigns, for which HIRAD observations are either directly comparable or are complementary. Features such as storm eye and eye-wall, location of storm wind and rain maxima, and indications of dynamical features such as the merging of a weaker outer wind/rain maximum with the main vortex may be seen in the data. Potential impacts on operational ocean surface wind analyses and on numerical weather forecasts will also be discussed.

A Bispectral Composite Threshold Approach for Automatic Cloud Detection in VIIRS Imagery

NASA Technical Reports Server (NTRS)

LaFontaine Frank J.; Jedlovec, Gary J.

2015-01-01

The detection of clouds in satellite imagery has a number of important applications in weather and climate studies. The presence of clouds can alter the energy budget of the Earth-atmosphere system through scattering and absorption of shortwave radiation and the absorption and re-emission of infrared radiation at longer wavelengths. The scattering and absorption characteristics of clouds vary with the microphysical properties of clouds, hence the cloud type. Thus, detecting the presence of clouds over a region in satellite imagery is important in order to derive atmospheric or surface parameters that give insight into weather and climate processes. For many applications however, clouds are a contaminant whose presence interferes with retrieving atmosphere or surface information. In these cases, is important to isolate cloud-free pixels, used to retrieve atmospheric thermodynamic information or surface geophysical parameters, from cloudy ones. This abstract describes an application of a two-channel bispectral composite threshold (BCT) approach applied to VIIRS imagery. The simplified BCT approach uses only the 10.76 and 3.75 micrometer spectral channels from VIIRS in two spectral tests; a straight-forward infrared threshold test with the longwave channel and a shortwave - longwave channel difference test. The key to the success of this approach as demonstrated in past applications to GOES and MODIS data is the generation of temporally and spatially dependent thresholds used in the tests from a previous number of days at similar observations to the current data. The paper and subsequent presentation will present an overview of the approach and intercomparison results with other satellites, methods, and against verification data.

METHODOLOGIES FOR ESTIMATING AIR EMISSIONS FROM THREE NON-TRADITIONAL SOURCE CATEGORIES: OIL SPILLS, PETROLEUM VESSEL LOADING & UNLOADING, AND COOLING TOWERS

EPA Science Inventory

The report discusses part of EPA's program to identify and characterize emissions sources not currently accounted for by either the existing Aerometric Information Retrieval System (AIRS) or State Implementation Plan (sip) area source methodologies and to develop appropriate emis...

Mineral dust emission from the Bodélé Depression, northern Chad, during BoDEx 2005

NASA Astrophysics Data System (ADS)

Todd, Martin C.; Washington, Richard; Martins, José Vanderlei; Dubovik, Oleg; Lizcano, Gil; M'bainayel, Samuel; Engelstaedter, Sebastian

2007-03-01

Mineral dust in the atmosphere is an important component of the climate system but is poorly quantified. The Bodélé Depression of northern Chad stands out as the world's greatest source region of mineral dust into the atmosphere. Frequent dust plumes are a distinguishing feature of the region's climate. There is a need for more detailed information on processes of dust emission/transport and dust optical properties to inform model simulations of this source. During the Bodélé Dust Experiment (BoDEx) in 2005, instrumentation was deployed to measure dust properties and boundary layer meteorology. Observations indicate that dust emission events are triggered when near-surface wind speeds exceed 10 ms-1, associated with synoptic-scale variability in the large-scale atmospheric circulation. Dust emission pulses in phase with the diurnal cycle of near-surface winds. Analysis of dust samples shows that the dust consists predominantly of fragments of diatomite sediment. The particle size distribution of this diatomite dust estimated from sun photometer data, using a modified Aeronet retrieval algorithm, indicates a dominant coarse mode (radius centered on 1-2 μm) similar to other Saharan dust observations. Single-scattering albedo values are high, broadly in line with other Saharan dust even though the diatomite composition of dust from the Bodélé is likely to be unusual. The radiative impact of high dust loadings results in a reduction in surface daytime maximum temperature of around 7°C in the Bodélé region. Using optical and physical properties of dust obtained in the field, we estimate the total dust flux emitted from the Bodélé to be 1.18 ± 0.45 Tg per day during a substantial dust event. We speculate that the Bodélé Depression (˜10,800 km2) may be responsible for between 6-18% of global dust emissions, although the uncertainty in both the Bodélé and global estimates remains high.

Worldwide biogenic soil NOx emission estimates from OMI NO2 observations and the GEOS-Chem model

NASA Astrophysics Data System (ADS)

Vinken, Geert; Boersma, Folkert; Maasakkers, Bram; Martin, Randall

2014-05-01

Bacteria in soils are an important source of biogenic nitrogen oxides (NOx = NO + NO2), which are important precursors for ozone (O3) formation. Furthermore NOx emissions contribute to increased nitrogen deposition and particulate matter formation. Bottom-up estimates of global soil NOx emissions range from 4 to 27 Tg N / yr, reflecting our incomplete knowledge of emission factors and processes driving these emissions. In this study we used, for the first time, OMI NO2 columns on all continents to reduce the uncertainty in soil NOx emissions. Regions and months dominated by soil NOx emissions were identified using a filtering scheme in the GEOS-Chem chemistry transport model. Consequently, we compared OMI observed NO2 observed columns to GEOS-Chem simulated columns and provide constraints for these months in 11 regions. This allows us to provide a top-down emission inventory for 2005 for soil NOx emissions from all continents. Our total global soil NOx emission inventory amounts to 10 Tg N / yr. Our estimate is 4% higher than the GEOS-Chem a priori (Hudman et al., 2012), but substantial regional differences exist (e.g. +20% for Sahel and India; and -40% for mid-USA). We furthermore observed a stronger seasonal cycle in the Sahel region, indicating directions for possible future improvements to the parameterization currently used in GEOS-Chem. We validated NO2 concentrations simulated with this new top-down inventory against surface NO2 measurements from monitoring stations in Africa, the USA and Europe. On the whole, we conclude that simulations with our new top-down inventory better agree with measurements. Our work shows that satellite retrieved NO2 columns can improve estimates of soil NOx emissions over sparsely monitored remote rural areas. We show that the range in previous estimates of soil NOx emissions is too large, and global emissions are most likely around 10 Tg N/yr, in agreement with the most recent parameterizations.

Cloud Masking and Surface Temperature Distribution in the Polar Regions Using AVHRR and other Satellite Data

NASA Technical Reports Server (NTRS)

Comiso, Joey C.

1995-01-01

Surface temperature is one of the key variables associated with weather and climate. Accurate measurements of surface air temperatures are routinely made in meteorological stations around the world. Also, satellite data have been used to produce synoptic global temperature distributions. However, not much attention has been paid on temperature distributions in the polar regions. In the polar regions, the number of stations is very sparse. Because of adverse weather conditions and general inaccessibility, surface field measurements are also limited. Furthermore, accurate retrievals from satellite data in the region have been difficult to make because of persistent cloudiness and ambiguities in the discrimination of clouds from snow or ice. Surface temperature observations are required in the polar regions for air-sea-ice interaction studies, especially in the calculation of heat, salinity, and humidity fluxes. They are also useful in identifying areas of melt or meltponding within the sea ice pack and the ice sheets and in the calculation of emissivities of these surfaces. Moreover, the polar regions are unique in that they are the sites of temperature extremes, the location of which is difficult to identify without a global monitoring system. Furthermore, the regions may provide an early signal to a potential climate change because such signal is expected to be amplified in the region due to feedback effects. In cloud free areas, the thermal channels from infrared systems provide surface temperatures at relatively good accuracies. Previous capabilities include the use of the Temperature Humidity Infrared Radiometer (THIR) onboard the Nimbus-7 satellite which was launched in 1978. Current capabilities include the use of the Advance Very High Resolution Radiometer (AVHRR) aboard NOAA satellites. Together, these two systems cover a span of 16 years of thermal infrared data. Techniques for retrieving surface temperatures with these sensors in the polar regions have been developed. Errors have been estimated to range from 1K to 5K mainly due to cloud masking problems. With many additional channels available, it is expected that the EOS-Moderate Resolution Imaging Spectroradiometer (MODIS) will provide an improved characterization of clouds and a good discrimination of clouds from snow or ice surfaces.

Impact of surface roughness on L-band emissivity of the sea ice

NASA Astrophysics Data System (ADS)

Miernecki, M.; Kaleschke, L.; Hendricks, S.; Søbjærg, S. S.

2015-12-01

In March 2014 a joint experiment IRO2/SMOSice was carried out in the Barents Sea. R/V Lance equipped with meteorological instruments, electromagnetic sea ice thickness probe and engine monitoring instruments, was performing a series of tests in different ice conditions in order to validate the ice route optimization (IRO) system, advising on his route through pack ice. In parallel cal/val activities for sea ice thickness product obtained from SMOS (Soil Moisture and Ocean Salinity mission) L-band radiometer were carried out. Apart from helicopter towing the EMbird thickness probe, Polar 5 aircraft was serving the area during the experiment with L-band radiometer EMIRAD2 and Airborne Laser Scanner (ALS) as primary instruments. Sea ice Thickness algorithm using SMOS brightness temperature developed at University of Hamburg, provides daily maps of thin sea ice (up to 0.5-1 m) in polar regions with resolution of 35-50 km. So far the retrieval method was not taking into account surface roughness, assuming that sea ice is a specular surface. Roughness is a stochastic process that can be characterized by standard deviation of surface height σ and by shape of the autocorrelation function R to estimate it's vertical and horizontal scales respectively. Interactions of electromagnetic radiation with the surface of the medium are dependent on R and σ and they scales with respect to the incident wavelength. During SMOSice the radiometer was observing sea ice surface at two incidence angles 0 and 40 degrees and simultaneously the surface elevation was scanned with ALS with ground resolution of ~ 0.25 m. This configuration allowed us to calculate σ and R from power spectral densities of surface elevation profiles and quantify the effect of surface roughness on the emissivity of the sea ice. First results indicate that Gaussian autocorrelation function is suitable for deformed ice, for other ice types exponential function is the best fit.

Advances in the Validation of Satellite-Based Maps of Volcanic Sulfur Dioxide Plumes

NASA Astrophysics Data System (ADS)

Realmuto, V. J.; Berk, A.; Acharya, P. K.; Kennett, R.

2013-12-01

The monitoring of volcanic gas emissions with gas cameras, spectrometer arrays, tethersondes, and UAVs presents new opportunities for the validation of satellite-based retrievals of gas concentrations. Gas cameras and spectrometer arrays provide instantaneous observations of the gas burden, or concentration along an optical path, over broad sections of a plume, similar to the observations acquired by nadir-viewing satellites. Tethersondes and UAVs provide us with direct measurements of the vertical profiles of gas concentrations within plumes. This presentation will focus on our current efforts to validate ASTER-based maps of sulfur dioxide plumes at Turrialba and Kilauea Volcanoes (located in Costa Rica and Hawaii, respectively). These volcanoes, which are the subjects of comprehensive monitoring programs, are challenging targets for thermal infrared (TIR) remote sensing due the warm and humid atmospheric conditions. The high spatial resolution of ASTER in the TIR (90 meters) allows us to map the plumes back to their source vents, but also requires us to pay close attention to the temperature and emissivity of the surfaces beneath the plumes. Our knowledge of the surface and atmospheric conditions is never perfect, and we employ interactive mapping techniques that allow us to evaluate the impact of these uncertainties on our estimates of plume composition. To accomplish this interactive mapping we have developed the Plume Tracker tool kit, which integrates retrieval procedures, visualization tools, and a customized version of the MODTRAN radiative transfer (RT) model under a single graphics user interface (GUI). We are in the process of porting the RT calculations to graphics processing units (GPUs) with the goal of achieving a 100-fold increase in the speed of computation relative to conventional CPU-based processing. We will report on our progress with this evolution of Plume Tracker. Portions of this research were conducted at the Jet Propulsion Laboratory, California Institute of Technology, under contract to the National Aeronautics and Space Administration.

A Satellite-Based Imaging Instrumentation Concept for Hyperspectral Thermal Remote Sensing

PubMed Central

Udelhoven, Thomas; Schlerf, Martin; Segl, Karl; Mallick, Kaniska; Bossung, Christian; Rock, Gilles; Fischer, Peter; Müller, Andreas; Storch, Tobias; Eisele, Andreas; Weise, Dennis; Hupfer, Werner; Knigge, Thiemo

2017-01-01

This paper describes the concept of the hyperspectral Earth-observing thermal infrared (TIR) satellite mission HiTeSEM (High-resolution Temperature and Spectral Emissivity Mapping). The scientific goal is to measure specific key variables from the biosphere, hydrosphere, pedosphere, and geosphere related to two global problems of significant societal relevance: food security and human health. The key variables comprise land and sea surface radiation temperature and emissivity, surface moisture, thermal inertia, evapotranspiration, soil minerals and grain size components, soil organic carbon, plant physiological variables, and heat fluxes. The retrieval of this information requires a TIR imaging system with adequate spatial and spectral resolutions and with day-night following observation capability. Another challenge is the monitoring of temporally high dynamic features like energy fluxes, which require adequate revisit time. The suggested solution is a sensor pointing concept to allow high revisit times for selected target regions (1–5 days at off-nadir). At the same time, global observations in the nadir direction are guaranteed with a lower temporal repeat cycle (>1 month). To account for the demand of a high spatial resolution for complex targets, it is suggested to combine in one optic (1) a hyperspectral TIR system with ~75 bands at 7.2–12.5 µm (instrument NEDT 0.05 K–0.1 K) and a ground sampling distance (GSD) of 60 m, and (2) a panchromatic high-resolution TIR-imager with two channels (8.0–10.25 µm and 10.25–12.5 µm) and a GSD of 20 m. The identified science case requires a good correlation of the instrument orbit with Sentinel-2 (maximum delay of 1–3 days) to combine data from the visible and near infrared (VNIR), the shortwave infrared (SWIR) and TIR spectral regions and to refine parameter retrieval. PMID:28671575

Retrievals of Surface Air Temperature Using Multiple Satellite Data Combinations over Complex Terrain in the Korean Peninsula

NASA Astrophysics Data System (ADS)

Jang, K.; Won, M.; Yoon, S.; Lim, J.

2016-12-01

Surface air temperature (Tair) is a fundamental factor for terrestrial environments and plays a major role in the fields of applied meteorology, climatology, and ecology. The satellite remotely sensed data offers the opportunity to estimate Tair on the earth's surface with high spatial and temporal resolutions. The Moderate Resolution Imaging Spectroradiometer (MODIS) provides effective Tair retrievals although restricted to clear sky condition. MODIS Tair over complex terrain can result in significant retrieval errors due to the retrieval height mismatch to the elevation of local weather stations. In this study, we propose the methodology to estimate Tair over complex terrain for all sky conditions using multiple satellite data fusion based on the pixel-wise regression method. The combination of synergistic information from MODIS Tair and the brightness temperature (Tb) retrievals at 37 GHz frequency from the satellite microwave sensor were used for analysis. The air temperature lapse rate was applied to estimate the near-surface Tair considering the complex terrain such as mountainous regions. The retrieval results produced from this study showed a good agreement (RMSE < 2.5 K) with weather measurements from the Korea Forest Service (KFS) for mountain regions and the Korea Meteorology Administration (KMA). The gaps in the MODIS Tair data due to cloud contamination were successfully filled using the proposed method which yielded similar accuracy as retrievals of clear sky. The results of this study indicate that the satellite data fusion can continuously produce Tair retrievals with reasonable accuracy and that the application of the temperature lapse rate can lead to improvement of the reliability over complex terrains such as the Korean Peninsula.

Coupled retrieval of aerosol properties and land surface reflection using the Airborne Multiangle SpectroPolarimetric Imager

NASA Astrophysics Data System (ADS)

Xu, Feng; van Harten, Gerard; Diner, David J.; Kalashnikova, Olga V.; Seidel, Felix C.; Bruegge, Carol J.; Dubovik, Oleg

2017-07-01

The Airborne Multiangle SpectroPolarimetric Imager (AirMSPI) has been flying aboard the NASA ER-2 high-altitude aircraft since October 2010. In step-and-stare operation mode, AirMSPI acquires radiance and polarization data in bands centered at 355, 380, 445, 470*, 555, 660*, 865*, and 935 nm (* denotes polarimetric bands). The imaged area covers about 10 km by 11 km and is typically observed from nine viewing angles between ±66° off nadir. For a simultaneous retrieval of aerosol properties and surface reflection using AirMSPI, an efficient and flexible retrieval algorithm has been developed. It imposes multiple types of physical constraints on spectral and spatial variations of aerosol properties as well as spectral and temporal variations of surface reflection. Retrieval uncertainty is formulated by accounting for both instrumental errors and physical constraints. A hybrid Markov-chain/adding-doubling radiative transfer (RT) model is developed to combine the computational strengths of these two methods in modeling polarized RT in vertically inhomogeneous and homogeneous media, respectively. Our retrieval approach is tested using 27 AirMSPI data sets with low to moderately high aerosol loadings, acquired during four NASA field campaigns plus one AirMSPI preengineering test flight. The retrieval results including aerosol optical depth, single-scattering albedo, aerosol size and refractive index are compared with Aerosol Robotic Network reference data. We identify the best angular combinations for 2, 3, 5, and 7 angle observations from the retrieval quality assessment of various angular combinations. We also explore the benefits of polarimetric and multiangular measurements and target revisits in constraining aerosol property and surface reflection retrieval.

Retrieval of thermospheric atomic oxygen, nitrogen and temperature from the 732 NM emission measured by the ISO on ATLAS 1

NASA Technical Reports Server (NTRS)

Fennelly, Judy A.; Torr, Douglas G.; Torr, Marsha R.; Richards, Phillip G.; Yung, Sopo

1993-01-01

The Imaging Spectrometric Observatory (ISO) was a part of the ATLAS 1 Mission flown on the shuttle Atlantis from March 24 to April 2, 1992. During limb scanning operations, the ISO measured the O+(2P) ion emission at 732 nm. We have used a numerical inversion technique to retrieve thermospheric atomic oxygen, molecular nitrogen and temperature profiles. These preliminary results indicate a lower thermospheric temperature cooler than that predicted by MSIS for the solar conditions during the mission. Although the densities agree at low altitudes, the reduced scale height produces O and N2 densities 25 percent lower than the MSIS at 300 km.

The EUSTACE project: delivering global, daily information on surface air temperature

NASA Astrophysics Data System (ADS)

Ghent, D.; Rayner, N. A.

2017-12-01

Day-to-day variations in surface air temperature affect society in many ways; however, daily surface air temperature measurements are not available everywhere. A global daily analysis cannot be achieved with measurements made in situ alone, so incorporation of satellite retrievals is needed. To achieve this, in the EUSTACE project (2015-2018, https://www.eustaceproject.eu) we have developed an understanding of the relationships between traditional (land and marine) surface air temperature measurements and retrievals of surface skin temperature from satellite measurements, i.e. Land Surface Temperature, Ice Surface Temperature, Sea Surface Temperature and Lake Surface Water Temperature. Here we discuss the science needed to produce a fully-global daily analysis (or ensemble of analyses) of surface air temperature on the centennial scale, integrating different ground-based and satellite-borne data types. Information contained in the satellite retrievals is used to create globally-complete fields in the past, using statistical models of how surface air temperature varies in a connected way from place to place. This includes developing new "Big Data" analysis methods as the data volumes involved are considerable. We will present recent progress along this road in the EUSTACE project, i.e.: • identifying inhomogeneities in daily surface air temperature measurement series from weather stations and correcting for these over Europe; • estimating surface air temperature over all surfaces of Earth from surface skin temperature retrievals; • using new statistical techniques to provide information on higher spatial and temporal scales than currently available, making optimum use of information in data-rich eras. Information will also be given on how interested users can become involved.

Phase Retrieval for Radio Telescope and Antenna Control

NASA Technical Reports Server (NTRS)

Dean, Bruce

2011-01-01

Phase-retrieval is a general term used in optics to describe the estimation of optical imperfections or "aberrations." The purpose of this innovation is to develop the application of phase retrieval to radio telescope and antenna control in the millimeter wave band. Earlier techniques do not approximate the incoherent subtraction process as a coherent propagation. This approximation reduces the noise in the data and allows a straightforward application of conventional phase retrieval techniques for radio telescope and antenna control. The application of iterative-transform phase retrieval to radio telescope and antenna control is made by approximating the incoherent subtraction process as a coherent propagation. Thus, for systems utilizing both positive and negative polarity feeds, this approximation allows both surface and alignment errors to be assessed without the use of additional hardware or laser metrology. Knowledge of the antenna surface profile allows errors to be corrected at a given surface temperature and observing angle. In addition to imperfections of the antenna surface figure, the misalignment of multiple antennas operating in unison can reduce or degrade the signal-to-noise ratio of the received or broadcast signals. This technique also has application to the alignment of antenna array configurations.

Factor information retrieval system version 2. 0 (fire) (for microcomputers). Software

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

Not Available

FIRE Version 2.0 contains EPA's unique recommended criteria and toxic air emission estimation factors. FIRE consists of: (1) an EPA internal repository system that contains emission factor data identified and collected, and (2) an external distribution system that contains only EPA's recommended factors. The emission factors, compiled from a review of the literature, are identified by pollutant name, CAS number, process and emission source descriptions, SIC code, SCC, and control status. The factors are rated for quality using AP-42 rating criteria.

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.

Using input feature information to improve ultraviolet retrieval in neural networks

NASA Astrophysics Data System (ADS)

Sun, Zhibin; Chang, Ni-Bin; Gao, Wei; Chen, Maosi; Zempila, Melina

2017-09-01

In neural networks, the training/predicting accuracy and algorithm efficiency can be improved significantly via accurate input feature extraction. In this study, some spatial features of several important factors in retrieving surface ultraviolet (UV) are extracted. An extreme learning machine (ELM) is used to retrieve the surface UV of 2014 in the continental United States, using the extracted features. The results conclude that more input weights can improve the learning capacities of neural networks.

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.

Multiplatform observations enabling albedo retrievals with high temporal resolution

NASA Astrophysics Data System (ADS)

Riihelä, Aku; Manninen, Terhikki; Key, Jeffrey; Sun, Qingsong; Sütterlin, Melanie; Lattanzio, Alessio; Schaaf, Crystal

2017-04-01

In this paper we show that combining observations from different polar orbiting satellite families (such as AVHRR and MODIS) is physically justifiable and technically feasible. Our proposed approach will lead to surface albedo retrievals at higher temporal resolution than the state of the art, with comparable or better accuracy. This study is carried out in the World Meteorological Organization (WMO) Sustained and coordinated processing of Environmental Satellite data for Climate Monitoring (SCOPE-CM) project SCM-02 (http://www.scope-cm.org/projects/scm-02/). Following a spectral homogenization of the Top-of-Atmosphere reflectances of bands 1 & 2 from AVHRR and MODIS, both observation datasets are atmospherically corrected with a coherent atmospheric profile and algorithm. The resulting surface reflectances are then fed into an inversion of the RossThick-LiSparse-Reciprocal surface bidirectional reflectance distribution function (BRDF) model. The results of the inversion (BRDF kernels) may then be integrated to estimate various surface albedo quantities. A key principle here is that the larger number of valid surface observations with multiple satellites allows us to invert the BRDF coefficients within a shorter time span, enabling the monitoring of relatively rapid surface phenomena such as snowmelt. The proposed multiplatform approach is expected to bring benefits in particular to the observation of the albedo of the polar regions, where persistent cloudiness and long atmospheric path lengths present challenges to satellite-based retrievals. Following a similar logic, the retrievals over tropical regions with high cloudiness should also benefit from the method. We present results from a demonstrator dataset of a global combined AVHRR-GAC and MODIS dataset covering the year 2010. The retrieved surface albedo is compared against quality-monitored in situ albedo observations from the Baseline Surface Radiation Network (BSRN). Additionally, the combined retrieval dataset is compared against MODIS C6 albedo/BRDF datasets to assess the quality of the multiplatform approach against current state of the art. This approach is not limited to AHVRR and MODIS observations. Provided that the spectral homogenization produces an acceptably good match, any instrument observing the Earth's surface in the visible and near-infrared wavelengths could, in principal, be included to further enhance the temporal resolution and accuracy of the retrievals. The SCOPE-CM initiative provides a potential framework for such expansion in the future.

Microwave-derived soil moisture over Mediterranean land uses: from ground-based radiometry to SMOS first observations

NASA Astrophysics Data System (ADS)

Saleh, Kauzar; Antolín, Carmen; Juglea, Silvia; Kerr, Yann; Millán-Scheiding, Cristina; Novello, Nathalie; Pardé, Mickael; Wigneron, Jean-Pierre; Zribi, Mehrez; López-Baeza, Ernesto

2010-05-01

This communication will present the main results of a series of airborne and ground-based experiments conducted at the Valencia Anchor Station (VAS) site for the implementation of the SMOS emission model L-MEB (L-band Microwave Emission model of the Biosphere, Wigneron et al., 2007), and will evaluate the performance of L-MEB against SMOS measurements. The L-MEB model has been implemented in the context of the SMOS mission and through numerous radiometry experiments over different land uses. Within L-MEB, each land use is characterised by model parameterisations that are used to describe the radiative transfer at L-band. They describe, for instance, the attenuation properties of different canopies, or the effect of soil roughness on the surface emission. In recent years, the Valencia Anchor Station site (VAS) has hosted various radiometry experiments. These were performed at different scales, from the plot scale to the regional scale (up to 50 km), using ground-based and airborne-based radiometry. The main results are discussed in this communication, and some preliminary comparisons with SMOS measurements are presented. 1) Ground-based experiments. MELBEX-I was a ground-radiometry experiment run in 2005 using the L-band radiometer EMIRAD over a plot of shrub land. We will present results from this experiment (Cano et al., 2009), that highlighted a constant (and small) contribution of Mediterranean shrub land to the overall emission, and investigated the role of exposed rocks in the surface emission. MELBEX-II was a ground-radiometry experiment run in 2007 using the EMIRAD L-band radiometer over a plot of vineyards throughout the whole vegetation cycle. Vineyards are the main land use at the VAS site, therefore parameterisations for vineyards are key for the validation of SMOS data at VAS. This communication will discuss, in particular, estimates of microwave surface roughness throughout the crop year, and changes in the canopy microwave properties throughout the plant growing cycle. 2) Airborne-based experiments. 2.1) ESA's SMOS Rehearsal 2008. For this campaign an area of 100 km2 of vineyards in winter-like conditions was flown on four days using the EMIRAD radiometer. Soil moisture could be retrieved with good accuracy but only after surface roughness was determined. In fact, the campaign highlighted that close to specular modelling of the surface reflectivity using 0-6 cm measurements of soil moisture underestimated the surface emission. This was observed also in other airborne data sets (Saleh et al. 2009). 2.2) CNES CAROLS campaigns. In 2009, the L-band CAROLS radiometer was flown on three occasions over an area of 1500 km2 covering vineyards, shrub land and Mediterranean pine forest. Main results of CAROLS 2009 will be presented in this communication, and the emphasis will be on comparing local to regional scale results given that CAROLS flights were performed at ~4000 m above the surface. For soil moisture, SVAT-derived, field soil moisture, and surface-type derived soil moisture will be used as ground truth. 3) SMOS data Finally, the results of the above mentioned experiments concerning L-MEB parameterisations will be the basis for comparisons between simulated brightness temperatures (TB) and measured TBs from SMOS at the VAS site. These exercises will be conducted in order to have an assessment of the L-MEB performance in a highly studied and monitored area, and to help pinpointing future areas of investigation in microwave radiometry. References Cano A., Saleh K., Wigneron J.P., Antolín C., Balling J., Kerr Y.H., Kruszewski A., Millán-Scheiding C., Søbjaerg S.S., Skou N., López-Baeza E. (2009), The SMOS Medierranean Ecosystem L-band experiment (MELBEX-I) over natural shrubs, Remote Sensing of Environment, in press. Saleh K., Kerr Y.H., Richaume P., Escorihuela, M.J., Panciera R., Delwart S., Walker J., Boulet G., Maisongrande P., Wursteisen P., Wigneron, J.P. (2009), Soil moisture retrievals at L-band using a two-step inversion approach (COSMOS/NAFE'05), Remote Sensing of Environment, vol. 113, 6, 1304-1312. Wigneron, J.-P., Kerr, Y., Waldteufel, P., Saleh, K., Escorihuela, M.-J., Richaume, P., Ferrazzoli, P., Grant, J. P., Hornbuckle, B., de Rosnay, P., Calvet, J.-C., Pellarin, T., Gurney, R., Mätzler, C. (2007), L-band Microwave Emission of the Biosphere (L-MEB) Model: description and calibration against experimental data sets over crop fields, Remote Sensing of Environment, vol (107), 639-655.

Retrieval of haze properties and HCN concentrations from the three-micron spectrum of Titan

NASA Astrophysics Data System (ADS)

Kim, Sang J.; Lee, D. W.; Sim, C. K.; Seon, K. I.; Courtin, R.; Geballe, T. R.

2018-05-01

The 3 μm spectrum of Titan contains line emission and absorption as well as a significant haze continuum. The line emission has been previously analyzed in the literature, but that analysis has not properly included the influence of haze on the line emission. We report a new analysis of the 3 μm HCN emission spectrum using radiative transfer equations that include scattering and absorption by molecules and haze particles at altitudes lower than 500 km, where the influence of haze on the emergent spectrum becomes significant. Taking advantage of the dominance of resonant single scattering in the HCN ν3 fundamental and of the moderate haze optical thickness of the atmosphere around 3 μm, we adopt single dust and molecular scattering and present a formulation for the radiative transfer process. We evaluate the quantitative influence of haze scattering on the emission line intensities, and derive vertically-resolved single scattering albedos of the haze from model fits. We also present the resulting concentrations of HCN for altitudes below 500 km, where we find that the haze scattering significantly influences the retrieval of the concentrations of HCN. We conclude that the formulation we present is useful for the analysis of the HCN line emission from Titan and other similar hazy planetary or celestial objects.

Evaluation of NOx emissions from U.S. wildfires occurring during August-October 2006 using WRF-Chem model simulations and satellite observations

NASA Astrophysics Data System (ADS)

Kim, S.; Brioude, J.; Hilboll, A.; Richter, A.; Gleason, J. F.; Burrows, J. P.; Ryerson, T. B.; Peischl, J. W.; Holloway, J.; Lee, S.; Frost, G. J.; McKeen, S. A.; Trainer, M.

2009-12-01

During August-October 2006, there were many fire events in the U.S., including a month-long fire in Los Padres National Forest in California and numerous fires in the southeastern U.S. The OMI instrument onboard NASA's Aura satellite, the MODIS instrument on NASA's Terra satellite, and instruments on the NOAA GOES satellites clearly detected fire plumes during this period, opening the possibility of using trace gas and aerosol measurements from satellites to improve bottom-up emission estimates from wildfires. WRF-Chem model simulations of U.S. air quality without bottom-up fire emissions underestimated satellite-observed nitrogen dioxide columns substantially over fire-impacted regions during this time period. In this presentation, nitrogen dioxide columns simulated from the model including the wildfire emissions will be compared with the satellite retrievals and uncertainties in the bottom-up fire NOx emissions will be discussed. In addition, the sensitivities of satellite retrievals to aerosols resulting from these fires will be shown. The satellite NO2 columns will also be tested with aircraft observations made over the Texas region during September-October 2006 as part of the TexAQS/GoMACCS field campaign.

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.

Using TES retrievals to investigate PAN in North American biomass burning plumes

NASA Astrophysics Data System (ADS)

Fischer, Emily V.; Zhu, Liye; Payne, Vivienne H.; Worden, John R.; Jiang, Zhe; Kulawik, Susan S.; Brey, Steven; Hecobian, Arsineh; Gombos, Daniel; Cady-Pereira, Karen; Flocke, Frank

2018-04-01

Peroxyacyl nitrate (PAN) is a critical atmospheric reservoir for nitrogen oxide radicals, and plays a lead role in their redistribution in the troposphere. We analyze new Tropospheric Emission Spectrometer (TES) PAN observations over North America from July 2006 to July 2009. Using aircraft observations from the Colorado Front Range, we demonstrate that TES can be sensitive to elevated PAN in the boundary layer (˜ 750 hPa) even in the presence of clouds. In situ observations have shown that wildfire emissions can rapidly produce PAN, and PAN decomposition is an important component of ozone production in smoke plumes. We identify smoke-impacted TES PAN retrievals by co-location with NOAA Hazard Mapping System (HMS) smoke plumes. Depending on the year, 15-32 % of cases where elevated PAN is identified in TES observations (retrievals with degrees of freedom (DOF) > 0.6) overlap smoke plumes during July. Of all the retrievals attempted in the July 2006 to July 2009 study period, 18 % is associated with smoke . A case study of smoke transport in July 2007 illustrates that PAN enhancements associated with HMS smoke plumes can be connected to fire complexes, providing evidence that TES is sufficiently sensitive to measure elevated PAN several days downwind of major fires. Using a subset of retrievals with TES 510 hPa carbon monoxide (CO) > 150 ppbv, and multiple estimates of background PAN, we calculate enhancement ratios for tropospheric average PAN relative to CO in smoke-impacted retrievals. Most of the TES-based enhancement ratios fall within the range calculated from in situ measurements.

Improved Prediction of Quasi-Global Vegetation Conditions Using Remotely-Sensed Surface Soil Moisture

NASA Technical Reports Server (NTRS)

Bolten, John; Crow, Wade

2012-01-01

The added value of satellite-based surface soil moisture retrievals for agricultural drought monitoring is assessed by calculating the lagged rank correlation between remotely-sensed vegetation indices (VI) and soil moisture estimates obtained both before and after the assimilation of surface soil moisture retrievals derived from the Advanced Microwave Scanning Radiometer-EOS (AMSR-E) into a soil water balance model. Higher soil moisture/VI lag correlations imply an enhanced ability to predict future vegetation conditions using estimates of current soil moisture. Results demonstrate that the assimilation of AMSR-E surface soil moisture retrievals substantially improve the performance of a global drought monitoring system - particularly in sparsely-instrumented areas of the world where high-quality rainfall observations are unavailable.

A new calibration of the effective scattering albedo and soil roughness parameters in the SMOS SM retrieval algorithm

NASA Astrophysics Data System (ADS)

Fernandez-Moran, R.; Wigneron, J.-P.; De Lannoy, G.; Lopez-Baeza, E.; Parrens, M.; Mialon, A.; Mahmoodi, A.; Al-Yaari, A.; Bircher, S.; Al Bitar, A.; Richaume, P.; Kerr, Y.

2017-10-01

This study focuses on the calibration of the effective vegetation scattering albedo (ω) and surface soil roughness parameters (HR, and NRp, p = H,V) in the Soil Moisture (SM) retrieval from L-band passive microwave observations using the L-band Microwave Emission of the Biosphere (L-MEB) model. In the current Soil Moisture and Ocean Salinity (SMOS) Level 2 (L2), v620, and Level 3 (L3), v300, SM retrieval algorithms, low vegetated areas are parameterized by ω = 0 and HR = 0.1, whereas values of ω = 0.06 - 0.08 and HR = 0.3 are used for forests. Several parameterizations of the vegetation and soil roughness parameters (ω, HR and NRp, p = H,V) were tested in this study, treating SMOS SM retrievals as homogeneous over each pixel instead of retrieving SM over a representative fraction of the pixel, as implemented in the operational SMOS L2 and L3 algorithms. Globally-constant values of ω = 0.10, HR = 0.4 and NRp = -1 (p = H,V) were found to yield SM retrievals that compared best with in situ SM data measured at many sites worldwide from the International Soil Moisture Network (ISMN). The calibration was repeated for collections of in situ sites classified in different land cover categories based on the International Geosphere-Biosphere Programme (IGBP) scheme. Depending on the IGBP land cover class, values of ω and HR varied, respectively, in the range 0.08-0.12 and 0.1-0.5. A validation exercise based on in situ measurements confirmed that using either a global or an IGBP-based calibration, there was an improvement in the accuracy of the SM retrievals compared to the SMOS L3 SM product considering all statistical metrics (R = 0.61, bias = -0.019 m3 m-3, ubRMSE = 0.062 m3 m-3 for the IGBP-based calibration; against R = 0.54, bias = -0.034 m3 m-3 and ubRMSE = 0.070 m3 m-3 for the SMOS L3 SM product). This result is a key step in the calibration of the roughness and vegetation parameters in the operational SMOS retrieval algorithm. The approach presented here is the core of a new forthcoming SMOS optimized SM product.

Hyperspectral retrieval of surface reflectances: A new scheme

NASA Astrophysics Data System (ADS)

Thelen, Jean-Claude; Havemann, Stephan

2013-05-01

Here, we present a new prototype algorithm for the simultaneous retrieval of the atmospheric profiles (temperature, humidity, ozone and aerosol) and the surface reflectance from hyperspectral radiance measurements obtained from air/space borne, hyperspectral imagers. The new scheme, proposed here, consists of a fast radiative transfer code, based on empirical orthogonal functions (EOFs), in conjunction with a 1D-Var retrieval scheme. The inclusion of an 'exact' scattering code based on spherical harmonics, allows for an accurate treatment of Rayleigh scattering and scattering by aerosols, water droplets and ice-crystals, thus making it possible to also retrieve cloud and aerosol optical properties, although here we will concentrate on non-cloudy scenes.

Snow water equivalent monitoring retrieved by assimilating passive microwave observations in a coupled snowpack evolution and microwave emission models over North-Eastern Canada

NASA Astrophysics Data System (ADS)

Royer, A.; Larue, F.; De Sève, D.; Roy, A.; Vionnet, V.; Picard, G.; Cosme, E.

2017-12-01

Over northern snow-dominated basins, the snow water equivalent (SWE) is of primary interest for spring streamflow forecasting. SWE retrievals from satellite data are still not well resolved, in particular from microwave (MW) measurements, the only type of data sensible to snow mass. Also, the use of snowpack models is challenging due to the large uncertainties in meteorological input forcings. This project aims to improve SWE prediction by assimilation of satellite brightness temperature (TB), without any ground-based observations. The proposed approach is the coupling of a detailed multilayer snowpack model (Crocus) with a MW snow emission model (DMRT-ML). The assimilation scheme is a Sequential Importance Resampling Particle filter, through ensembles of perturbed meteorological forcings according to their respective uncertainties. Crocus simulations driven by operational meteorological forecasts from the Canadian Global Environmental Multiscale model at 10 km spatial resolution were compared to continuous daily SWE measurements over Québec, North-Eastern Canada (56° - 45°N). The results show a mean bias of the maximum SWE overestimated by 16% with variations up to +32%. This observed large variability could lead to dramatic consequences on spring flood forecasts. Results of Crocus-DMRT-ML coupling compared to surface-based TB measurements (at 11, 19 and 37 GHz) show that the Crocus snowpack microstructure described by sticky hard spheres within DMRT has to be scaled by a snow stickiness of 0.18, significantly reducing the overall RMSE of simulated TBs. The ability of assimilation of daily TBs to correct the simulated SWE is first presented through twin experiments with synthetic data, and then with AMSR-2 satellite time series of TBs along the winter taking into account atmospheric and forest canopy interferences (absorption and emission). The differences between TBs at 19-37 GHz and at 11-19 GHz, in vertical polarization, were assimilated. This assimilation test with synthetic data gives a SWE RMSE reduced by a factor of 2 after assimilation. Assimilation of AMSR-2 TBs shows improvement in SWE retrievals compared to continuous in-situ SWE measurements. The accuracy is discussed as a function of boreal forest density and LAI (MODIS-based data), having significant effects.

Improving land surface parameter retrieval by integrating plant traits priors in the MULTIPLY data assimilation platform

NASA Astrophysics Data System (ADS)

Corbin, A. E.; Timmermans, J.; Hauser, L.; Bodegom, P. V.; Soudzilovskaia, N. A.

2017-12-01

There is a growing demand for accurate land surface parameterization from remote sensing (RS) observations. This demand has not been satisfied, because most estimation schemes apply 1) a single-sensor single-scale approach, and 2) require specific key-variables to be `guessed'. This is because of the relevant observational information required to accurately retrieve parameters of interest. Consequently, many schemes assume specific variables to be constant or not present; subsequently leading to more uncertainty. In this aspect, the MULTIscale SENTINEL land surface information retrieval Platform (MULTIPLY) was created. MULTIPLY couples a variety of RS sources with Radiative Transfer Models (RTM) over varying spectral ranges using data-assimilation to estimate geophysical parameters. In addition, MULTIPLY also uses prior information about the land surface to constrain the retrieval problem. This research aims to improve the retrieval of plant biophysical parameters through the use of priors of biophysical parameters/plant traits. Of particular interest are traits (physical, morphological or chemical trait) affecting individual performance and fitness of species. Plant traits that are able to be retrieved via RS and with RTMs include traits such as leaf-pigments, leaf water, LAI, phenols, C/N, etc. In-situ data for plant traits that are retrievable via RS techniques were collected for a meta-analysis from databases such as TRY, Ecosis, and individual collaborators. Of particular interest are the following traits: chlorophyll, carotenoids, anthocyanins, phenols, leaf water, and LAI. ANOVA statistics were generated for each traits according to species, plant functional groups (such as evergreens, grasses, etc.), and the trait itself. Afterwards, traits were also compared using covariance matrices. Using these as priors, MULTIPLY was is used to retrieve several plant traits in two validation sites in the Netherlands (Speulderbos) and in Finland (Sodankylä). Initial comparisons show significant improved results over non-a priori based retrievals.

A demonstration of adjoint methods for multi-dimensional remote sensing of the atmosphere and surface

NASA Astrophysics Data System (ADS)

Martin, William G. K.; Hasekamp, Otto P.

2018-01-01

In previous work, we derived the adjoint method as a computationally efficient path to three-dimensional (3D) retrievals of clouds and aerosols. In this paper we will demonstrate the use of adjoint methods for retrieving two-dimensional (2D) fields of cloud extinction. The demonstration uses a new 2D radiative transfer solver (FSDOM). This radiation code was augmented with adjoint methods to allow efficient derivative calculations needed to retrieve cloud and surface properties from multi-angle reflectance measurements. The code was then used in three synthetic retrieval studies. Our retrieval algorithm adjusts the cloud extinction field and surface albedo to minimize the measurement misfit function with a gradient-based, quasi-Newton approach. At each step we compute the value of the misfit function and its gradient with two calls to the solver FSDOM. First we solve the forward radiative transfer equation to compute the residual misfit with measurements, and second we solve the adjoint radiative transfer equation to compute the gradient of the misfit function with respect to all unknowns. The synthetic retrieval studies verify that adjoint methods are scalable to retrieval problems with many measurements and unknowns. We can retrieve the vertically-integrated optical depth of moderately thick clouds as a function of the horizontal coordinate. It is also possible to retrieve the vertical profile of clouds that are separated by clear regions. The vertical profile retrievals improve for smaller cloud fractions. This leads to the conclusion that cloud edges actually increase the amount of information that is available for retrieving the vertical profile of clouds. However, to exploit this information one must retrieve the horizontally heterogeneous cloud properties with a 2D (or 3D) model. This prototype shows that adjoint methods can efficiently compute the gradient of the misfit function. This work paves the way for the application of similar methods to 3D remote sensing problems.

Validation of high-resolution MAIAC aerosol product over South America

NASA Astrophysics Data System (ADS)

Martins, V. S.; Lyapustin, A.; de Carvalho, L. A. S.; Barbosa, C. C. F.; Novo, E. M. L. M.

2017-07-01

Multiangle Implementation of Atmospheric Correction (MAIAC) is a new Moderate Resolution Imaging Spectroradiometer (MODIS) algorithm that combines time series approach and image processing to derive surface reflectance and atmosphere products, such as aerosol optical depth (AOD) and columnar water vapor (CWV). The quality assessment of MAIAC AOD at 1 km resolution is still lacking across South America. In the present study, critical assessment of MAIAC AOD550 was performed using ground-truth data from 19 Aerosol Robotic Network (AERONET) sites over South America. Additionally, we validated the MAIAC CWV retrievals using the same AERONET sites. In general, MAIAC AOD Terra/Aqua retrievals show high agreement with ground-based measurements, with a correlation coefficient (R) close to unity (RTerra:0.956 and RAqua: 0.949). MAIAC accuracy depends on the surface properties and comparisons revealed high confidence retrievals over cropland, forest, savanna, and grassland covers, where more than 2/3 ( 66%) of retrievals are within the expected error (EE = ±(0.05 + 0.05 × AOD)) and R exceeding 0.86. However, AOD retrievals over bright surfaces show lower correlation than those over vegetated areas. Both MAIAC Terra and Aqua retrievals are similarly comparable to AERONET AOD over the MODIS lifetime (small bias offset 0.006). Additionally, MAIAC CWV presents quantitative information with R 0.97 and more than 70% of retrievals within error (±15%). Nonetheless, the time series validation shows an upward bias trend in CWV Terra retrievals and systematic negative bias for CWV Aqua. These results contribute to a comprehensive evaluation of MAIAC AOD retrievals as a new atmospheric product for future aerosol studies over South America.

Derivation of a New Smoke Emissions Inventory using Remote Sensing, and Its Implications for Near Real-Time Air Quality Applications

NASA Technical Reports Server (NTRS)

Ellison, Luke; Ichoku, Charles

2012-01-01

A new emissions inventory of particulate matter (PM) is being derived mainly from remote sensing data using fire radiative power (FRP) and aerosol optical depth (AOD) retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument, as well as wind data from the Modern Era Retrospective-Analysis for Research and Applications (MERRA) reanalysis dataset, which spans the satellite era. This product is generated using a coefficient of emission, C(sub e), that has been produced on a 1x1 degree global grid such that, when it is multiplied with satellite measurements of FRP or its time-integrated equivalent fire radiative energy (FRE) retrieved over a given area and time period, the corresponding PM emissions are estimated. This methodology of using C(sub e) to derive PM emissions is relatively new and advantageous for near real-time air quality applications compared to current methods based on post-fire burned area that may not provide emissions in a timely manner. Furthermore, by using FRP to characterize a fire s output, it will represent better accuracy than the use of raw fire pixel counts, since fires in individual pixels can differ in size and strength by orders of magnitude, resulting in similar differences in emission rates. Here we will show examples of this effect and how this new emission inventory can properly account for the differing emission rates from fires of varying strengths. We also describe the characteristics of the new emissions inventory, and propose the process chain of incorporating it into models for air quality applications.

Airborne characterization of aerosols over the contiguous United States during the SEAC4RS and DC3 campaigns: an in situ light scattering perspective

NASA Astrophysics Data System (ADS)

Espinosa, R.; Remer, L.; Puthukkudy, A.; Orozco, D.; Dubovik, O.; Martins, J. V.

2017-12-01

Models used to estimate climate change and interpret remote sensing observations must make assumptions regarding aerosol radiation interactions. This presentation will summarize aerosol light scattering measurements made by the Polarized Imaging Nephelometer (PI-Neph) during the Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS) and Deep Convective Clouds and Chemistry (DC3) experiments. The data presented includes direct measurements of phase function (P11) and polarized phase function (-P12/P11) as well as retrievals of size distribution, sphericity and complex refractive index made using the Generalized Retrieval of Aerosol and Surface Properties (GRASP). An aerosol classification scheme is developed to identify different aerosol types measured during the deployments, making use of ancillary data that includes gas tracers, chemical composition, aerodynamic particle size and geographic location. Principal component analysis (PCA) is then used to reduce the dimensionality of the multi-angle PI-Neph scattering data and a strong link between the PCA scores and the ancillary classification results is observed. The scattering differences that reliable distinguish the different aerosol types are found to be quite subtle and often rely on the relationships between many scattering angles simultaneously. This fact emphasis the value of multi-angle scattering measurements, as well as principal component analysis's ability to reveal the underlying patterns in these datasets. The parameters retrieved from the DC3 scattering data suggest the presence of a significant amount of dust in aerosols influenced by convective systems, with the quantity of dust correlating strongly with sampling location and the underlying surface features. All fine mode dominated aerosol types from SEAC4RS had remarkably similar retrieved properties, except for the real refractive index of the biomass burning cases, which was consistently elevated (n532=1.54) when compared to the other types (n532=1.50). This result suggests that climate and remote sensing models may often be able to capture the differences in optical properties between biomass burning and other fine mode aerosols by only adjusting the real refractive index of the particles.