The effect of spatial resolution upon cloud optical property retrievals. I - Optical thickness

NASA Technical Reports Server (NTRS)

Feind, Rand E.; Christopher, Sundar A.; Welch, Ronald M.

1992-01-01

High spectral and spatial resolution Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) imagery is used to study the effects of spatial resolution upon fair weather cumulus cloud optical thickness retrievals. As a preprocessing step, a variation of the Gao and Goetz three-band ratio technique is used to discriminate clouds from the background. The combination of the elimination of cloud shadow pixels and using the first derivative of the histogram allows for accurate cloud edge discrimination. The data are progressively degraded from 20 m to 960 m spatial resolution. The results show that retrieved cloud area increases with decreasing spatial resolution. The results also show that there is a monotonic decrease in retrieved cloud optical thickness with decreasing spatial resolution. It is also demonstrated that the use of a single, monospectral reflectance threshold is inadequate for identifying cloud pixels in fair weather cumulus scenes and presumably in any inhomogeneous cloud field. Cloud edges have a distribution of reflectance thresholds. The incorrect identification of cloud edges significantly impacts the accurate retrieval of cloud optical thickness values.

Retrieval of Ice Cloud Properties Using Variable Phase Functions

NASA Astrophysics Data System (ADS)

Heck, Patrick W.; Minnis, Patrick; Yang, Ping; Chang, Fu-Lung; Palikonda, Rabindra; Arduini, Robert F.; Sun-Mack, Sunny

2009-03-01

An enhancement to NASA Langley's Visible Infrared Solar-infrared Split-window Technique (VISST) is developed to identify and account for situations when errors are induced by using smooth ice crystals. The retrieval scheme incorporates new ice cloud phase functions that utilize hexagonal crystals with roughened surfaces. In some situations, cloud optical depths are reduced, hence, cloud height is increased. Cloud effective particle size also changes with the roughened ice crystal models which results in varied effects on the calculation of ice water path. Once validated and expanded, the new approach will be integrated in the CERES MODIS algorithm and real-time retrievals at Langley.

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.

An imager-based multispectral retrieval of above-cloud absorbing aerosol optical depth and the optical and microphysical properties of underlying marine stratocumulus clouds

NASA Astrophysics Data System (ADS)

Meyer, K.; Platnick, S. E.; Zhang, Z.

2014-12-01

Clouds, aerosols, and their interactions are widely considered to be key uncertainty components in our current understanding of the Earth's atmosphere and radiation budget. The work presented here is focused on the quasi-permanent marine boundary layer (MBL) clouds over the southeastern Atlantic Ocean, which underlie a near-persistent smoke layer produced from extensive biomass burning throughout the southern African savanna during austral winter. The absorption of the above-cloud smoke layer, which increases with decreasing wavelength, can introduce biases into imager-based cloud optical and microphysical property retrievals of the underlying MBL clouds. This effect is more pronounced for cloud optical thickness retrievals, which are typically derived from the visible or near-IR wavelength channels (effective particle size retrievals are derived from short and mid-wave IR channels that are less affected by aerosol absorption). Here, a new method is introduced to simultaneously retrieve the above-cloud smoke aerosol optical depth (AOD) and the unbiased cloud optical thickness (COT) and effective radius (CER) using multiple spectral channels in the visible and near- and shortwave-IR. The technique has been applied to MODIS, and retrieval results and statistics, as well as comparisons with other A-Train sensors, are shown.

Cloud Properties and Radiative Heating Rates for TWP

DOE Data Explorer

Comstock, Jennifer

2013-11-07

A cloud properties and radiative heating rates dataset is presented where cloud properties retrieved using lidar and radar observations are input into a radiative transfer model to compute radiative fluxes and heating rates at three ARM sites located in the Tropical Western Pacific (TWP) region. The cloud properties retrieval is a conditional retrieval that applies various retrieval techniques depending on the available data, that is if lidar, radar or both instruments detect cloud. This Combined Remote Sensor Retrieval Algorithm (CombRet) produces vertical profiles of liquid or ice water content (LWC or IWC), droplet effective radius (re), ice crystal generalized effective size (Dge), cloud phase, and cloud boundaries. The algorithm was compared with 3 other independent algorithms to help estimate the uncertainty in the cloud properties, fluxes, and heating rates (Comstock et al. 2013). The dataset is provided at 2 min temporal and 90 m vertical resolution. The current dataset is applied to time periods when the MMCR (Millimeter Cloud Radar) version of the ARSCL (Active Remotely-Sensed Cloud Locations) Value Added Product (VAP) is available. The MERGESONDE VAP is utilized where temperature and humidity profiles are required. Future additions to this dataset will utilize the new KAZR instrument and its associated VAPs.

Cloud, Aerosol, and Volcanic Ash Retrievals Using ASTR and SLSTR with ORAC

NASA Astrophysics Data System (ADS)

McGarragh, Gregory; Poulsen, Caroline; Povey, Adam; Thomas, Gareth; Christensen, Matt; Sus, Oliver; Schlundt, Cornelia; Stapelberg, Stefan; Stengel, Martin; Grainger, Don

2015-12-01

The Optimal Retrieval of Aerosol and Cloud (ORAC) is a generalized optimal estimation system that retrieves cloud, aerosol and volcanic ash parameters using satellite imager measurements in the visible to infrared. Use of the same algorithm for different sensors and parameters leads to consistency that facilitates inter-comparison and interaction studies. ORAC currently supports ATSR, AVHRR, MODIS and SEVIRI. In this proceeding we discuss the ORAC retrieval algorithm applied to ATSR data including the retrieval methodology, the forward model, uncertainty characterization and discrimination/classification techniques. Application of ORAC to SLSTR data is discussed including the additional features that SLSTR provides relative to the ATSR heritage. The ORAC level 2 and level 3 results are discussed and an application of level 3 results to the study of cloud/aerosol interactions is presented.

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

NASA Technical Reports Server (NTRS)

Meyer, Kerry; Yang, Yuekui; Platnick, Steven

2016-01-01

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

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

PubMed Central

Meyer, Kerry; Yang, Yuekui; Platnick, Steven

2018-01-01

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

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

PubMed

Meyer, Kerry; Yang, Yuekui; Platnick, Steven

2016-01-01

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

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

NASA Astrophysics Data System (ADS)

Meyer, Kerry; Yang, Yuekui; Platnick, Steven

2016-04-01

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

Remote Sensing of Multiple Cloud Layer Heights Using Multi-Angular Measurements

NASA Technical Reports Server (NTRS)

Sinclair, Kenneth; Van Diedenhoven, Bastiaan; Cairns, Brian; Yorks, John; Wasilewski, Andrzej; Mcgill, Matthew

2017-01-01

Cloud top height (CTH) affects the radiative properties of clouds. Improved CTH observations will allow for improved parameterizations in large-scale models and accurate information on CTH is also important when studying variations in freezing point and cloud microphysics. NASAs airborne Research Scanning Polarimeter (RSP) is able to measure cloud top height using a novel multi-angular contrast approach. For the determination of CTH, a set of consecutive nadir reflectances is selected and the cross-correlations between this set and co-located sets at other viewing angles are calculated for a range of assumed cloud top heights, yielding a correlation profile. Under the assumption that cloud reflectances are isotropic, local peaks in the correlation profile indicate cloud layers. This technique can be applied to every RSP footprint and we demonstrate that detection of multiple peaks in the correlation profile allow retrieval of heights of multiple cloud layers within single RSP footprints. This paper provides an in-depth description of the architecture and performance of the RSPs CTH retrieval technique using data obtained during the Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC(exp. 4)RS) campaign. RSP retrieved cloud heights are evaluated using collocated data from the Cloud Physics Lidar (CPL). The method's accuracy associated with the magnitude of correlation, optical thickness, cloud thickness and cloud height are explored. The technique is applied to measurements at a wavelength of 670 nm and 1880 nm and their combination. The 1880-nm band is virtually insensitive to the lower troposphere due to strong water vapor absorption.

Thin ice clouds in the Arctic: cloud optical depth and particle size retrieved from ground-based thermal infrared radiometry

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

Blanchard, Yann; Royer, Alain; O'Neill, Norman T.

Multiband downwelling thermal measurements of zenith sky radiance, along with cloud boundary heights, were used in a retrieval algorithm to estimate cloud optical depth and effective particle diameter of thin ice clouds in the Canadian High Arctic. Ground-based thermal infrared (IR) radiances for 150 semitransparent ice clouds cases were acquired at the Polar Environment Atmospheric Research Laboratory (PEARL) in Eureka, Nunavut, Canada (80° N, 86° W). We analyzed and quantified the sensitivity of downwelling thermal radiance to several cloud parameters including optical depth, effective particle diameter and shape, water vapor content, cloud geometric thickness and cloud base altitude. A lookupmore » table retrieval method was used to successfully extract, through an optimal estimation method, cloud optical depth up to a maximum value of 2.6 and to separate thin ice clouds into two classes: (1) TIC1 clouds characterized by small crystals (effective particle diameter ≤ 30 µm), and (2) TIC2 clouds characterized by large ice crystals (effective particle diameter > 30 µm). The retrieval technique was validated using data from the Arctic High Spectral Resolution Lidar (AHSRL) and Millimeter Wave Cloud Radar (MMCR). Inversions were performed over three polar winters and results showed a significant correlation ( R 2 = 0.95) for cloud optical depth retrievals and an overall accuracy of 83 % for the classification of TIC1 and TIC2 clouds. A partial validation relative to an algorithm based on high spectral resolution downwelling IR radiance measurements between 8 and 21µm was also performed. It confirms the robustness of the optical depth retrieval and the fact that the broadband thermal radiometer retrieval was sensitive to small particle (TIC1) sizes.« less

Thin ice clouds in the Arctic: cloud optical depth and particle size retrieved from ground-based thermal infrared radiometry

NASA Astrophysics Data System (ADS)

Blanchard, Yann; Royer, Alain; O'Neill, Norman T.; Turner, David D.; Eloranta, Edwin W.

2017-06-01

Multiband downwelling thermal measurements of zenith sky radiance, along with cloud boundary heights, were used in a retrieval algorithm to estimate cloud optical depth and effective particle diameter of thin ice clouds in the Canadian High Arctic. Ground-based thermal infrared (IR) radiances for 150 semitransparent ice clouds cases were acquired at the Polar Environment Atmospheric Research Laboratory (PEARL) in Eureka, Nunavut, Canada (80° N, 86° W). We analyzed and quantified the sensitivity of downwelling thermal radiance to several cloud parameters including optical depth, effective particle diameter and shape, water vapor content, cloud geometric thickness and cloud base altitude. A lookup table retrieval method was used to successfully extract, through an optimal estimation method, cloud optical depth up to a maximum value of 2.6 and to separate thin ice clouds into two classes: (1) TIC1 clouds characterized by small crystals (effective particle diameter ≤ 30 µm), and (2) TIC2 clouds characterized by large ice crystals (effective particle diameter > 30 µm). The retrieval technique was validated using data from the Arctic High Spectral Resolution Lidar (AHSRL) and Millimeter Wave Cloud Radar (MMCR). Inversions were performed over three polar winters and results showed a significant correlation (R2 = 0.95) for cloud optical depth retrievals and an overall accuracy of 83 % for the classification of TIC1 and TIC2 clouds. A partial validation relative to an algorithm based on high spectral resolution downwelling IR radiance measurements between 8 and 21 µm was also performed. It confirms the robustness of the optical depth retrieval and the fact that the broadband thermal radiometer retrieval was sensitive to small particle (TIC1) sizes.

Thin ice clouds in the Arctic: cloud optical depth and particle size retrieved from ground-based thermal infrared radiometry

DOE PAGES

Blanchard, Yann; Royer, Alain; O'Neill, Norman T.; ...

2017-06-09

Multiband downwelling thermal measurements of zenith sky radiance, along with cloud boundary heights, were used in a retrieval algorithm to estimate cloud optical depth and effective particle diameter of thin ice clouds in the Canadian High Arctic. Ground-based thermal infrared (IR) radiances for 150 semitransparent ice clouds cases were acquired at the Polar Environment Atmospheric Research Laboratory (PEARL) in Eureka, Nunavut, Canada (80° N, 86° W). We analyzed and quantified the sensitivity of downwelling thermal radiance to several cloud parameters including optical depth, effective particle diameter and shape, water vapor content, cloud geometric thickness and cloud base altitude. A lookupmore » table retrieval method was used to successfully extract, through an optimal estimation method, cloud optical depth up to a maximum value of 2.6 and to separate thin ice clouds into two classes: (1) TIC1 clouds characterized by small crystals (effective particle diameter ≤ 30 µm), and (2) TIC2 clouds characterized by large ice crystals (effective particle diameter > 30 µm). The retrieval technique was validated using data from the Arctic High Spectral Resolution Lidar (AHSRL) and Millimeter Wave Cloud Radar (MMCR). Inversions were performed over three polar winters and results showed a significant correlation ( R 2 = 0.95) for cloud optical depth retrievals and an overall accuracy of 83 % for the classification of TIC1 and TIC2 clouds. A partial validation relative to an algorithm based on high spectral resolution downwelling IR radiance measurements between 8 and 21µm was also performed. It confirms the robustness of the optical depth retrieval and the fact that the broadband thermal radiometer retrieval was sensitive to small particle (TIC1) sizes.« less

Feasibility study of multi-pixel retrieval of optical thickness and droplet effective radius of inhomogeneous clouds using deep learning

NASA Astrophysics Data System (ADS)

Okamura, Rintaro; Iwabuchi, Hironobu; Schmidt, K. Sebastian

2017-12-01

Three-dimensional (3-D) radiative-transfer effects are a major source of retrieval errors in satellite-based optical remote sensing of clouds. The challenge is that 3-D effects manifest themselves across multiple satellite pixels, which traditional single-pixel approaches cannot capture. In this study, we present two multi-pixel retrieval approaches based on deep learning, a technique that is becoming increasingly successful for complex problems in engineering and other areas. Specifically, we use deep neural networks (DNNs) to obtain multi-pixel estimates of cloud optical thickness and column-mean cloud droplet effective radius from multispectral, multi-pixel radiances. The first DNN method corrects traditional bispectral retrievals based on the plane-parallel homogeneous cloud assumption using the reflectances at the same two wavelengths. The other DNN method uses so-called convolutional layers and retrieves cloud properties directly from the reflectances at four wavelengths. The DNN methods are trained and tested on cloud fields from large-eddy simulations used as input to a 3-D radiative-transfer model to simulate upward radiances. The second DNN-based retrieval, sidestepping the bispectral retrieval step through convolutional layers, is shown to be more accurate. It reduces 3-D radiative-transfer effects that would otherwise affect the radiance values and estimates cloud properties robustly even for optically thick clouds.

Synergy of stereo cloud top height and ORAC optimal estimation cloud retrieval: evaluation and application to AATSR

NASA Astrophysics Data System (ADS)

Fisher, Daniel; Poulsen, Caroline A.; Thomas, Gareth E.; Muller, Jan-Peter

2016-03-01

In this paper we evaluate the impact on the cloud parameter retrievals of the ORAC (Optimal Retrieval of Aerosol and Cloud) algorithm following the inclusion of stereo-derived cloud top heights as a priori information. This is performed in a mathematically rigorous way using the ORAC optimal estimation retrieval framework, which includes the facility to use such independent a priori information. Key to the use of a priori information is a characterisation of their associated uncertainty. This paper demonstrates the improvements that are possible using this approach and also considers their impact on the microphysical cloud parameters retrieved. The Along-Track Scanning Radiometer (AATSR) instrument has two views and three thermal channels, so it is well placed to demonstrate the synergy of the two techniques. The stereo retrieval is able to improve the accuracy of the retrieved cloud top height when compared to collocated Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), particularly in the presence of boundary layer inversions and high clouds. The impact of the stereo a priori information on the microphysical cloud properties of cloud optical thickness (COT) and effective radius (RE) was evaluated and generally found to be very small for single-layer clouds conditions over open water (mean RE differences of 2.2 (±5.9) microns and mean COD differences of 0.5 (±1.8) for single-layer ice clouds over open water at elevations of above 9 km, which are most strongly affected by the inclusion of the a priori).

Cloud-property retrieval using merged HIRS and AVHRR data

NASA Technical Reports Server (NTRS)

Baum, Bryan A.; Wielicki, Bruce A.; Minnis, Patrick; Parker, Lindsay

1992-01-01

A technique is developed that uses a multispectral, multiresolution method to improve the overall retrieval of mid- to high-level cloud properties by combining HIRS sounding channel data with higher spatial resolution AVHRR radiometric data collocated with the HIRS footprint. Cirrus cloud radiative and physical properties are determined using satellite data, surface-based measurements provided by rawinsondes and lidar, and aircraft-based lidar data collected during the First International Satellite Cloud Climatology Program Regional Experiment in Wisconsin during the months of October and November 1986. HIRS cloud-height retrievals are compared to ground-based lidar and aircraft lidar when possible. Retrieved cloud heights are found to have close agreement with lidar for thin cloud, but are higher than lidar for optically thick cloud. The results of the reflectance-emittance relationships derived are compared to theoretical scattering model results for both water-droplet spheres and randomly oriented hexagonal ice crystals. It is found that the assumption of 10-micron water droplets is inadequate to describe the reflectance-emittance relationship for the ice clouds seen here. Use of this assumption would lead to lower cloud heights using the ISCCP approach. The theoretical results show that use of hexagonal ice crystal phase functions could lead to much improved results for cloud retrieval algorithms using a bispectral approach.

Retrieval of cloud properties from POLDER-3 data using the neural network approach

NASA Astrophysics Data System (ADS)

Di Noia, A.; Hasekamp, O. P.

2017-12-01

Satellite multi-angle spectroplarimetry is a useful technique for observing the microphysical properties of clouds and aerosols. Most of the algorithms for the retrieval of cloud and aerosol properties from satellite measurements require multiple calls to radiative transfer models, which make the retrieval computationally expensive. A traditional alternative to these schemes is represented by lookup-tables (LUTs), where the retrieval is performed by choosing, within a predefined database of combinations of clouds or aerosol properties, the combination that best fits the measurements. LUT retrievals are quicker than full-physics, iterative retrievals, but their accuracy is limited by the number of entries stored in the LUT. Another retrieval method capable of producing very quick retrievals without a big sacrifice in accuracy is the neural network method. Neural network methods are routinely applied to several types of satellite measurements, but their application to multi-angle spectropolarimetric data is still in its early stage, because of the difficulty of accounting for the angular variability of the measurements in the training process. We have recently developed a neural network scheme for the retrieval of cloud properties from POLDER-3 data. The neural network retrieval is trained using synthetic measurements performed for realistic combinations of cloud properties and measurement angles, and is able to process an entire orbit in about 20 seconds. Comparisons of the retrieved cloud properties with Moderate Resolution Imaging Spectroradiometer (MODIS) gridded products during one year show encouraging retrieval performance for cloud optical thickness and effective radius. A discussion of the setup of the neural network and of the validation results will be the main topic of our presentation.

Improved Cloud and Snow Screening in MAIAC Aerosol Retrievals Using Spectral and Spatial Analysis

NASA Technical Reports Server (NTRS)

Lyapustin, A.; Wang, Y.; Laszlo, I.; Kokrkin, S.

2012-01-01

An improved cloud/snow screening technique in the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm is described. It is implemented as part of MAIAC aerosol retrievals based on analysis of spectral residuals and spatial variability. Comparisons with AERONET aerosol observations and a large-scale MODIS data analysis show strong suppression of aerosol optical thickness outliers due to unresolved clouds and snow. At the same time, the developed filter does not reduce the aerosol retrieval capability at high 1 km resolution in strongly inhomogeneous environments, such as near centers of the active fires. Despite significant improvement, the optical depth outliers in high spatial resolution data are and will remain the problem to be addressed by the application-dependent specialized filtering techniques.

Absorbing Aerosols Above Cloud: Detection, Quantitative Retrieval, and Radiative Forcing from Satellite-based Passive Sensors

NASA Astrophysics Data System (ADS)

Jethva, H.; Torres, O.; Remer, L. A.; Bhartia, P. K.

2012-12-01

Light absorbing particles such as carbonaceous aerosols generated from biomass burning activities and windblown dust particles can exert a net warming effect on climate; the strength of which depends on the absorption capacity of the particles and brightness of the underlying reflecting background. When advected over low-level bright clouds, these aerosols absorb the cloud reflected radiation from ultra-violet (UV) to shortwave-IR (SWIR) and makes cloud scene darker-a phenomenon commonly known as "cloud darkening". The apparent "darkening" effect can be seen by eyes in satellite images as well as quantitatively in the spectral reflectance measurements made by space borne sensors over regions where light absorbing carbonaceous and dust aerosols overlay low-level cloud decks. Theoretical radiative transfer simulations support the observational evidence, and further reveal that the strength of the cloud darkening and its spectral signature (or color ratio) between measurements at two wavelengths are a bi-function of aerosol and cloud optical thickness (AOT and COT); both are measures of the total amount of light extinction caused by aerosols and cloud, respectively. Here, we developed a retrieval technique, named as the "color ratio method" that uses the satellite measurements at two channels, one at shorter wavelength in the visible and one at longer wavelength in the shortwave-IR for the simultaneous retrieval of AOT and COT. The present technique requires assumptions on the aerosol single-scattering albedo and aerosol-cloud separation which are supplemented by the Aerosol Robotic Network (AERONET) and space borne CALIOP lidar measurements. The retrieval technique has been tested making use of the near-UV and visible reflectance observations made by the Ozone Monitoring Instrument (OMI) and Moderate Resolution Imaging Spectroradiometer (MODIS) for distinct above-cloud smoke and dust aerosol events observed seasonally over the southeast and tropical Atlantic Ocean, respectively. This study constitutes the first attempt to use non-polarized and non-lidar reflectance observations-both of them shown to have above-cloud aerosols retrieval capability, to retrieve above-cloud AOT by a passive non-polarized sensor. The uncertainty analysis suggests that the present method should retrieve above-cloud AOT within -10% to 50% which mainly arises due to uncertainty associated with the single-scattering albedo assumption. Although, currently tested by making use of OMI and MODIS measurements, the present color ratio method can be equally applied to the other satellite measurements that carry similar or near-by channels in VIS region of the spectrum such as MISR and NPP/VIIRS. The capability of quantifying the above-cloud aerosol load will facilitate several aspects of cloud-aerosol interaction research such as estimation of the direct radiative forcing of aerosols above clouds; the sign of which can be opposite (warming) to cloud-free aerosol forcing (cooling), aerosol transport, indirect effects of aerosols on clouds, and hydrological cycle.

Development of GK-2A cloud optical and microphysical properties retrieval algorithm

NASA Astrophysics Data System (ADS)

Yang, Y.; Yum, S. S.; Um, J.

2017-12-01

Cloud and aerosol radiative forcing is known to be one of the the largest uncertainties in climate change prediction. To reduce this uncertainty, remote sensing observation of cloud radiative and microphysical properties have been used since 1970s and the corresponding remote sensing techniques and instruments have been developed. As a part of such effort, Geo-KOMPSAT-2A (Geostationary Korea Multi-Purpose Satellite-2A, GK-2A) will be launched in 2018. On the GK-2A, the Advanced Meteorological Imager (AMI) is primary instrument which have 3 visible, 3 near-infrared, and 10 infrared channels. To retrieve optical and microphysical properties of clouds using AMI measurements, the preliminary version of new cloud retrieval algorithm for GK-2A was developed and several validation tests were conducted. This algorithm retrieves cloud optical thickness (COT), cloud effective radius (CER), liquid water path (LWP), and ice water path (IWP), so we named this algorithm as Daytime Cloud Optical thickness, Effective radius and liquid and ice Water path (DCOEW). The DCOEW uses cloud reflectance at visible and near-infrared channels as input data. An optimal estimation (OE) approach that requires appropriate a-priori values and measurement error information is used to retrieve COT and CER. LWP and IWP are calculated using empirical relationships between COT/CER and cloud water path that were determined previously. To validate retrieved cloud properties, we compared DCOEW output data with other operational satellite data. For COT and CER validation, we used two different data sets. To compare algorithms that use cloud reflectance at visible and near-IR channels as input data, MODIS MYD06 cloud product was selected. For the validation with cloud products that are based on microwave measurements, COT(2B-TAU)/CER(2C-ICE) data retrieved from CloudSat cloud profiling radar (W-band, 94 GHz) was used. For cloud water path validation, AMSR-2 Level-3 Cloud liquid water data was used. Detailed results will be shown at the conference.

Vertical Photon Transport in Cloud Remote Sensing Problems

NASA Technical Reports Server (NTRS)

Platnick, S.

1999-01-01

Photon transport in plane-parallel, vertically inhomogeneous clouds is investigated and applied to cloud remote sensing techniques that use solar reflectance or transmittance measurements for retrieving droplet effective radius. Transport is couched in terms of weighting functions which approximate the relative contribution of individual layers to the overall retrieval. Two vertical weightings are investigated, including one based on the average number of scatterings encountered by reflected and transmitted photons in any given layer. A simpler vertical weighting based on the maximum penetration of reflected photons proves useful for solar reflectance measurements. These weighting functions are highly dependent on droplet absorption and solar/viewing geometry. A superposition technique, using adding/doubling radiative transfer procedures, is derived to accurately determine both weightings, avoiding time consuming Monte Carlo methods. Superposition calculations are made for a variety of geometries and cloud models, and selected results are compared with Monte Carlo calculations. Effective radius retrievals from modeled vertically inhomogeneous liquid water clouds are then made using the standard near-infrared bands, and compared with size estimates based on the proposed weighting functions. Agreement between the two methods is generally within several tenths of a micrometer, much better than expected retrieval accuracy. Though the emphasis is on photon transport in clouds, the derived weightings can be applied to any multiple scattering plane-parallel radiative transfer problem, including arbitrary combinations of cloud, aerosol, and gas layers.

Seasonal Bias of Retrieved Ice Cloud Optical Properties Based on MISR and MODIS Measurements

NASA Astrophysics Data System (ADS)

Wang, Y.; Hioki, S.; Yang, P.; Di Girolamo, L.; Fu, D.

2017-12-01

The precise estimation of two important cloud optical and microphysical properties, cloud particle optical thickness and cloud particle effective radius, is fundamental in the study of radiative energy budget and hydrological cycle. In retrieving these two properties, an appropriate selection of ice particle surface roughness is important because it substantially affects the single-scattering properties. At present, using a predetermined ice particle shape without spatial and temporal variations is a common practice in satellite-based retrieval. This approach leads to substantial uncertainties in retrievals. The cloud radiances measured by each of the cameras of the Multi-angle Imaging SpectroRadiometer (MISR) instrument are used to estimate spherical albedo values at different scattering angles. By analyzing the directional distribution of estimated spherical albedo values, the degree of ice particle surface roughness is estimated. With an optimal degree of ice particle roughness, cloud optical thickness and effective radius are retrieved based on a bi-spectral shortwave technique in conjunction with two Moderate Resolution Imaging Spectroradiometer (MODIS) bands centered at 0.86 and 2.13 μm. The seasonal biases of retrieved cloud optical and microphysical properties, caused by the uncertainties in ice particle roughness, are investigated by using one year of MISR-MODIS fused data.

Estimation of Cirrus and Stratus Cloud Heights Using Landsat Imagery

NASA Technical Reports Server (NTRS)

Inomata, Yasushi; Feind, R. E.; Welch, R. M.

1996-01-01

A new method based upon high-spatial-resolution imagery is presented that matches cloud and shadow regions to estimate cirrus and stratus cloud heights. The distance between the cloud and the matching shadow pattern is accomplished using the 2D cross-correlation function from which the cloud height is derived. The distance between the matching cloud-shadow patterns is verified manually. The derived heights also are validated through comparison with a temperature-based retrieval of cloud height. It is also demonstrated that an estimate of cloud thickness can be retrieved if both the sunside and anti-sunside of the cloud-shadow pair are apparent. The technique requires some intepretation to determine the cloud height level retrieved (i.e., the top, base, or mid-level). It is concluded that the method is accurate to within several pixels, equivalent to cloud height variations of about +/- 250 m. The results show that precise placement of the templates is unnecessary, so that the development of a semi-automated procedure is possible. Cloud templates of about 64 pixels on a side or larger produce consistent results. The procedure was repeated for imagery degraded to simulate lower spatial resolutions. The results suggest that spatial resolution of 150-200 m or better is necessary in order to obtain stable cloud height retrievals.

Liquid Water Cloud Properties During the Polarimeter Definition Experiment (PODEX)

NASA Technical Reports Server (NTRS)

Alexandrov, Mikhail D.; Cairns, Brian; Wasilewski, Andrzei P.; Ackerman, Andrew S.; McGill, Matthew J.; Yorks, John E.; Hlavka, Dennis L.; Platnick, Steven; Arnold, George; Van Diedenhoven, Bastiaan;

The Observed Behavior of the Bias in MODIS-retrieved Cloud Droplet Effective Radius through MISR-MODIS Data Fusion

NASA Astrophysics Data System (ADS)

Fu, D.; Di Girolamo, L.; Liang, L.; Zhao, G.

2017-12-01

Listed as one of the Essential Climate Variables by the Global Climate Observing System, the effective radius (Re) of the cloud drop size distribution plays an important role in the energy and water cycles of the Earth system. Re is retrieved from several passive sensors, such as the Moderate Resolution Imaging Spectroradiometer (MODIS), based on a visible and near-infrared bi-spectral technique that had its foundation more than a quarter century ago. This technique makes a wide range of assumptions, including 1-D radiative transfer, assumed single-mode drop size distribution, and cloud horizontal and vertical homogeneity. It is well known that deviations from these assumptions lead to bias in the retrieved Re. Recently, an effort to characterize the bias in MODIS-retrieved Re through MISR-MODIS data fusion revealed biases in the zonal-mean values of MODIS-retrieved Re that varied from 2 to 11 µm, depending on latitude (Liang et al., 2015). Here, in a push towards bias-correction of MODIS-retrieved Re, we further examine the bias with MISR-MODIS data fusion as it relates to other observed cloud properties, such as cloud-top height and the spatial variability of the radiance field, sun-view geometry, and the driving meteorology had from reanalysis data. Our results show interesting relationships in Re bias behavior with these observed properties, revealing that while Re bias do show a certain degree of dependence on some properties, no single property dominates the behavior in MODIS-retrieved Re bias.

Optical Thickness and Effective Radius Retrievals of Liquid Water Clouds over Ice and Snow Surface

NASA Technical Reports Server (NTRS)

Platnick, S.; King, M. D.; Tsay, S.-C.; Arnold, G. T.; Gerber, H.; Hobbs, P. V.; Rangno, A.

1999-01-01

Cloud optical thickness and effective radius retrievals from solar reflectance measurements traditionally depend on a combination of spectral channels that are absorbing and non-absorbing for liquid water droplets. Reflectances in non-absorbing channels (e.g., 0.67, 0.86 micrometer bands) are largely dependent on cloud optical thickness, while longer wavelength absorbing channels (1.6, 2.1, and 3.7 micrometer window bands) provide cloud particle size information. Retrievals are complicated by the presence of an underlying ice/snow surface. At the shorter wavelengths, sea ice is both bright and highly variable, significantly increasing cloud retrieval uncertainty. However, reflectances at the longer wavelengths are relatively small and may be comparable to that of dark open water. Sea ice spectral albedos derived from Cloud Absorption Radiometer (CAR) measurements during April 1992 and June 1995 Arctic field deployments are used to illustrate these statements. A modification to the traditional retrieval technique is devised. The new algorithm uses a combination of absorbing spectral channels for which the snow/ice albedo is relatively small. Using this approach, preliminary retrievals have been made with the MODIS Airborne Simulator (MAS) imager flown aboard the NASA ER-2 during FIRE-ACE. Data from coordinated ER-2 and University of Washington CV-580 aircraft observations of liquid water stratus clouds on June 3 and June 6, 1998 have been examined. Size retrievals are compared with in situ cloud profile measurements of effective radius made with the CV-580 PMS FSSP probe, and optical thickness retrievals are compared with extinction profiles derived from the Gerber Scientific "g-meter" probe. MAS retrievals are shown to be in good agreement with the in situ measurements.

Automated Detection of Clouds in Satellite Imagery

NASA Technical Reports Server (NTRS)

Jedlovec, Gary

2010-01-01

Many different approaches have been used to automatically detect clouds in satellite imagery. Most approaches are deterministic and provide a binary cloud - no cloud product used in a variety of applications. Some of these applications require the identification of cloudy pixels for cloud parameter retrieval, while others require only an ability to mask out clouds for the retrieval of surface or atmospheric parameters in the absence of clouds. A few approaches estimate a probability of the presence of a cloud at each point in an image. These probabilities allow a user to select cloud information based on the tolerance of the application to uncertainty in the estimate. Many automated cloud detection techniques develop sophisticated tests using a combination of visible and infrared channels to determine the presence of clouds in both day and night imagery. Visible channels are quite effective in detecting clouds during the day, as long as test thresholds properly account for variations in surface features and atmospheric scattering. Cloud detection at night is more challenging, since only courser resolution infrared measurements are available. A few schemes use just two infrared channels for day and night cloud detection. The most influential factor in the success of a particular technique is the determination of the thresholds for each cloud test. The techniques which perform the best usually have thresholds that are varied based on the geographic region, time of year, time of day and solar angle.

Combined retrieval of Arctic liquid water cloud and surface snow properties using airborne spectral solar remote sensing

NASA Astrophysics Data System (ADS)

Ehrlich, André; Bierwirth, Eike; Istomina, Larysa; Wendisch, Manfred

2017-09-01

The passive solar remote sensing of cloud properties over highly reflecting ground is challenging, mostly due to the low contrast between the cloud reflectivity and that of the underlying surfaces (sea ice and snow). Uncertainties in the retrieved cloud optical thickness τ and cloud droplet effective radius reff, C may arise from uncertainties in the assumed spectral surface albedo, which is mainly determined by the generally unknown effective snow grain size reff, S. Therefore, in a first step the effects of the assumed snow grain size are systematically quantified for the conventional bispectral retrieval technique of τ and reff, C for liquid water clouds. In general, the impact of uncertainties of reff, S is largest for small snow grain sizes. While the uncertainties of retrieved τ are independent of the cloud optical thickness and solar zenith angle, the bias of retrieved reff, C increases for optically thin clouds and high Sun. The largest deviations between the retrieved and true original values are found with 83 % for τ and 62 % for reff, C. In the second part of the paper a retrieval method is presented that simultaneously derives all three parameters (τ, reff, C, reff, S) and therefore accounts for changes in the snow grain size. Ratios of spectral cloud reflectivity measurements at the three wavelengths λ1 = 1040 nm (sensitive to reff, S), λ2 = 1650 nm (sensitive to τ), and λ3 = 2100 nm (sensitive to reff, C) are combined in a trispectral retrieval algorithm. In a feasibility study, spectral cloud reflectivity measurements collected by the Spectral Modular Airborne Radiation measurement sysTem (SMART) during the research campaign Vertical Distribution of Ice in Arctic Mixed-Phase Clouds (VERDI, April/May 2012) were used to test the retrieval procedure. Two cases of observations above the Canadian Beaufort Sea, one with dense snow-covered sea ice and another with a distinct snow-covered sea ice edge are analysed. The retrieved values of τ, reff, C, and reff, S show a continuous transition of cloud properties across snow-covered sea ice and open water and are consistent with estimates based on satellite data. It is shown that the uncertainties of the trispectral retrieval increase for high values of τ, and low reff, S but nevertheless allow the effective snow grain size in cloud-covered areas to be estimated.

A New Normalized Difference Cloud Retrieval Technique Applied to Landsat Radiances Over the Oklahoma ARM Site

NASA Technical Reports Server (NTRS)

Orepoulos, Lazaros; Cahalan, Robert; Marshak, Alexander; Wen, Guoyong

1999-01-01

We suggest a new approach to cloud retrieval, using a normalized difference of nadir reflectivities (NDNR) constructed from a non-absorbing and absorbing (with respect to liquid water) wavelength. Using Monte Carlo simulations we show that this quantity has the potential of removing first order scattering effects caused by cloud side illumination and shadowing at oblique Sun angles. Application of the technique to TM (Thematic Mapper) radiance observations from Landsat-5 over the Southern Great Plains site of the ARM (Atmospheric Radiation Measurement) program gives very similar regional statistics and histograms, but significant differences at the pixel level. NDNR can be also combined with the inverse NIPA (Nonlocal Independent Pixel Approximation) of Marshak (1998) which is applied for the first time on overcast Landsat scene subscenes. We demonstrate the sensitivity of the NIPA-retrieved cloud fields on the parameters of the method and discuss practical issues related to the optimal choice of these parameters.

Cloud cover over the equatorial eastern Pacific derived from July 1983 International Satellite Cloud Climatology Project data using a hybrid bispectral threshold method

NASA Technical Reports Server (NTRS)

Minnis, Patrick; Harrison, Edwin F.; Gibson, Gary G.

1987-01-01

A set of visible and IR data obtained with GOES from July 17-31, 1983 is analyzed using a modified version of the hybrid bispectral threshold method developed by Minnis and Harrison (1984). This methodology can be divided into a set of procedures or optional techniques to determine the proper contaminate clear-sky temperature or IR threshold. The various optional techniques are described; the options are: standard, low-temperature limit, high-reflectance limit, low-reflectance limit, coldest pixel and thermal adjustment limit, IR-only low-cloud temperature limit, IR clear-sky limit, and IR overcast limit. Variations in the cloud parameters and the characteristics and diurnal cycles of trade cumulus and stratocumulus clouds over the eastern equatorial Pacific are examined. It is noted that the new method produces substantial changes in about one third of the cloud amount retrieval; and low cloud retrievals are affected most by the new constraints.

Orbiting lidar simulations. I - Aerosol and cloud measurements by an independent-wavelength technique

NASA Technical Reports Server (NTRS)

Russell, P. B.; Morley, B. M.; Livingston, J. M.; Grams, G. W.; Patterson, E. M.

1982-01-01

Aerosol and cloud measurements have been simulated for a Space Shuttle lidar. Expected errors - in signal, transmission, density, and calibration - are calculated algebraically and checked by simulating measurements and retrievals using random-number generators. By day, vertical structure is retrieved for tenuous clouds, Saharan aerosols, and boundary layer aerosols (at 0.53 and 1.06 micron) as well as strong volcanic stratospheric aerosols (at 0.53 micron). By night, all these constituents are retrieved plus upper tropospheric and stratospheric aerosols (at 1.06 micron), mesospheric aerosols (at 0.53 micron), and noctilucent clouds (at 1.06 and 0.53 micron). The vertical resolution was 0.1-0.5 km in the troposphere, 0.5-2.0 km above, except 0.25-1.0 km in the mesospheric cloud and aerosol layers; horizontal resolution was 100-2000 km.

Retrieval of nonprecipitating liquid water cloud parameters from microwave data - A simulation study

NASA Technical Reports Server (NTRS)

Huang, Hung-Lung; Diak, George R.

1992-01-01

A new microwave algorithm, analogous to the IR 'radiance-ratioing' method of Eyre and Menzel (1989) is developed to retrieve the height and 'effective' fraction (defined as the product of the emissivity times the actual physical fractional coverage) of nonprecipitating water clouds using various pairs of the 20 microwave channels planned for the Advanced Microwave Sounding Unit (AMSU), an instrument slated to fly on polar-orbiting satellites beginning in 1994. The results of a simulation study are presented to provide some insights into the potentials of this technique using different AMSU channel combinations. This study suggests that the use of the oxygen channels 3 and 5 and water vapor channels 19 and 20 will produce the most accurate retrievals of liquid water cloud parameters and the highest percentage of good-quality retrievals over a range of meteorological and cloud conditions.

Ice Cloud Properties in Ice-Over-Water Cloud Systems Using TRMM VIRS and TMI Data

NASA Technical Reports Server (NTRS)

Minnis, Patrick; Huang, Jianping; Lin, Bing; Yi, Yuhong; Arduini, Robert F.; Fan, Tai-Fang; Ayers, J. Kirk; Mace, Gerald G.

2007-01-01

A multi-layered cloud retrieval system (MCRS) is updated and used to estimate ice water path in maritime ice-over-water clouds using Visible and Infrared Scanner (VIRS) and TRMM Microwave Imager (TMI) measurements from the Tropical Rainfall Measuring Mission spacecraft between January and August 1998. Lookup tables of top-of-atmosphere 0.65- m reflectance are developed for ice-over-water cloud systems using radiative transfer calculations with various combinations of ice-over-water cloud layers. The liquid and ice water paths, LWP and IWP, respectively, are determined with the MCRS using these lookup tables with a combination of microwave (MW), visible (VIS), and infrared (IR) data. LWP, determined directly from the TMI MW data, is used to define the lower-level cloud properties to select the proper lookup table. The properties of the upper-level ice clouds, such as optical depth and effective size, are then derived using the Visible Infrared Solar-infrared Split-window Technique (VISST), which matches the VIRS IR, 3.9- m, and VIS data to the multilayer-cloud lookup table reflectances and a set of emittance parameterizations. Initial comparisons with surface-based radar retrievals suggest that this enhanced MCRS can significantly improve the accuracy and decrease the IWP in overlapped clouds by 42% and 13% compared to using the single-layer VISST and an earlier simplified MW-VIS-IR (MVI) differencing method, respectively, for ice-over-water cloud systems. The tropical distribution of ice-over-water clouds is the same as derived earlier from combined TMI and VIRS data, but the new values of IWP and optical depth are slightly larger than the older MVI values, and exceed those of single-layered layered clouds by 7% and 11%, respectively. The mean IWP from the MCRS is 8-14% greater than that retrieved from radar retrievals of overlapped clouds over two surface sites and the standard deviations of the differences are similar to those for single-layered clouds. Examples of a method for applying the MCRS over land without microwave data yield similar differences with the surface retrievals. By combining the MCRS with other techniques that focus primarily on optically thin cirrus over low water clouds, it will be possible to more fully assess the IWP in all conditions over ocean except for precipitating systems.

New Satellite Estimates of Mixed-Phase Cloud Properties: A Synergistic Approach for Application to Global Satellite Imager Data

NASA Astrophysics Data System (ADS)

Smith, W. L., Jr.; Spangenberg, D.; Fleeger, C.; Sun-Mack, S.; Chen, Y.; Minnis, P.

2016-12-01

Determining accurate cloud properties horizontally and vertically over a full range of time and space scales is currently next to impossible using data from either active or passive remote sensors or from modeling systems. Passive satellite imagers provide horizontal and temporal resolution of clouds, but little direct information on vertical structure. Active sensors provide vertical resolution but limited spatial and temporal coverage. Cloud models embedded in NWP can produce realistic clouds but often not at the right time or location. Thus, empirical techniques that integrate information from multiple observing and modeling systems are needed to more accurately characterize clouds and their impacts. Such a strategy is employed here in a new cloud water content profiling technique developed for application to satellite imager cloud retrievals based on VIS, IR and NIR radiances. Parameterizations are developed to relate imager retrievals of cloud top phase, optical depth, effective radius and temperature to ice and liquid water content profiles. The vertical structure information contained in the parameterizations is characterized climatologically from cloud model analyses, aircraft observations, ground-based remote sensing data, and from CloudSat and CALIPSO. Thus, realistic cloud-type dependent vertical structure information (including guidance on cloud phase partitioning) circumvents poor assumptions regarding vertical homogeneity that plague current passive satellite retrievals. This paper addresses mixed phase cloud conditions for clouds with glaciated tops including those associated with convection and mid-latitude storm systems. Novel outcomes of our approach include (1) simultaneous retrievals of ice and liquid water content and path, which are validated with active sensor, microwave and in-situ data, and yield improved global cloud climatologies, and (2) new estimates of super-cooled LWC, which are demonstrated in aviation safety applications and validated with icing PIREPS. The initial validation is encouraging for single-layer cloud conditions. More work is needed to test and refine the method for global application in a wider range of cloud conditions. A brief overview of our current method, applications, verification, and plans for future work will be presented.

MWR3C physical retrievals of precipitable water vapor and cloud liquid water path

DOE Data Explorer

Cadeddu, Maria

2016-10-12

The data set contains physical retrievals of PWV and cloud LWP retrieved from MWR3C measurements during the MAGIC campaign. Additional data used in the retrieval process include radiosondes and ceilometer. The retrieval is based on an optimal estimation technique that starts from a first guess and iteratively repeats the forward model calculations until a predefined convergence criterion is satisfied. The first guess is a vector of [PWV,LWP] from the neural network retrieval fields in the netcdf file. When convergence is achieved the 'a posteriori' covariance is computed and its square root is expressed in the file as the retrieval 1-sigma uncertainty. The closest radiosonde profile is used for the radiative transfer calculations and ceilometer data are used to constrain the cloud base height. The RMS error between the brightness temperatures is computed at the last iterations as a consistency check and is written in the last column of the output file.

Comparing airborne and satellite retrievals of cloud optical thickness and particle effective radius using a spectral radiance ratio technique: two case studies for cirrus and deep convective clouds

NASA Astrophysics Data System (ADS)

Krisna, Trismono C.; Wendisch, Manfred; Ehrlich, André; Jäkel, Evelyn; Werner, Frank; Weigel, Ralf; Borrmann, Stephan; Mahnke, Christoph; Pöschl, Ulrich; Andreae, Meinrat O.; Voigt, Christiane; Machado, Luiz A. T.

2018-04-01

Solar radiation reflected by cirrus and deep convective clouds (DCCs) was measured by the Spectral Modular Airborne Radiation Measurement System (SMART) installed on the German High Altitude and Long Range Research Aircraft (HALO) during the Mid-Latitude Cirrus (ML-CIRRUS) and the Aerosol, Cloud, Precipitation, and Radiation Interaction and Dynamic of Convective Clouds System - Cloud Processes of the Main Precipitation Systems in Brazil: A Contribution to Cloud Resolving Modelling and to the Global Precipitation Measurement (ACRIDICON-CHUVA) campaigns. On particular flights, HALO performed measurements closely collocated with overpasses of the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Aqua satellite. A cirrus cloud located above liquid water clouds and a DCC topped by an anvil cirrus are analyzed in this paper. Based on the nadir spectral upward radiance measured above the two clouds, the optical thickness τ and particle effective radius reff of the cirrus and DCC are retrieved using a radiance ratio technique, which considers the cloud thermodynamic phase, the vertical profile of cloud microphysical properties, the presence of multilayer clouds, and the heterogeneity of the surface albedo. For the cirrus case, the comparison of τ and reff retrieved on the basis of SMART and MODIS measurements yields a normalized mean absolute deviation of up to 1.2 % for τ and 2.1 % for reff. For the DCC case, deviations of up to 3.6 % for τ and 6.2 % for reff are obtained. The larger deviations in the DCC case are mainly attributed to the fast cloud evolution and three-dimensional (3-D) radiative effects. Measurements of spectral upward radiance at near-infrared wavelengths are employed to investigate the vertical profile of reff in the cirrus. The retrieved values of reff are compared with corresponding in situ measurements using a vertical weighting method. Compared to the MODIS observations, measurements of SMART provide more information on the vertical distribution of particle sizes, which allow reconstructing the profile of reff close to the cloud top. The comparison between retrieved and in situ reff yields a normalized mean absolute deviation, which ranges between 1.5 and 10.3 %, and a robust correlation coefficient of 0.82.

Global cloud top height retrieval using SCIAMACHY limb spectra: model studies and first results

NASA Astrophysics Data System (ADS)

Eichmann, Kai-Uwe; Lelli, Luca; von Savigny, Christian; Sembhi, Harjinder; Burrows, John P.

2016-03-01

Cloud top heights (CTHs) are retrieved for the period 1 January 2003 to 7 April 2012 using height-resolved limb spectra measured with the SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY (SCIAMACHY) on board ENVISAT (ENVIronmental SATellite). In this study, we present the retrieval code SCODA (SCIAMACHY cloud detection algorithm) based on a colour index method and test the accuracy of the retrieved CTHs in comparison to other methods. Sensitivity studies using the radiative transfer model SCIATRAN show that the method is capable of detecting cloud tops down to about 5 km and very thin cirrus clouds up to the tropopause. Volcanic particles can be detected that occasionally reach the lower stratosphere. Upper tropospheric ice clouds are observable for a nadir cloud optical thickness (COT) ≥ 0.01, which is in the subvisual range. This detection sensitivity decreases towards the lowermost troposphere. The COT detection limit for a water cloud top height of 5 km is roughly 0.1. This value is much lower than thresholds reported for passive cloud detection methods in nadir-viewing direction. Low clouds at 2 to 3 km can only be retrieved under very clean atmospheric conditions, as light scattering of aerosol particles interferes with the cloud particle scattering. We compare co-located SCIAMACHY limb and nadir cloud parameters that are retrieved with the Semi-Analytical CloUd Retrieval Algorithm (SACURA). Only opaque clouds (τN,c > 5) are detected with the nadir passive retrieval technique in the UV-visible and infrared wavelength ranges. Thus, due to the frequent occurrence of thin clouds and subvisual cirrus clouds in the tropics, larger CTH deviations are detected between both viewing geometries. Zonal mean CTH differences can be as high as 4 km in the tropics. The agreement in global cloud fields is sufficiently good. However, the land-sea contrast, as seen in nadir cloud occurrence frequency distributions, is not observed in limb geometry. Co-located cloud top height measurements of the limb-viewing Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) on ENVISAT are compared for the period from January 2008 to March 2012. The global CTH agreement of about 1 km is observed, which is smaller than the vertical field of view of both instruments. Lower stratospheric aerosols from volcanic eruptions occasionally interfere with the cloud retrieval and inhibit the detection of tropospheric clouds. The aerosol impact on cloud retrievals was studied for the volcanoes Kasatochi (August 2008), Sarychev Peak (June 2009), and Nabro (June 2011). Long-lasting aerosol scattering is detected after these events in the Northern Hemisphere for heights above 12.5 km in tropical and polar latitudes. Aerosol top heights up to about 22 km are found in 2009 and the enhanced lower stratospheric aerosol layer persisted for about 7 months. In August 2009 about 82 % of the lower stratosphere between 30 and 70° N was filled with scattering particles and nearly 50 % in October 2008.

Detection and Retrieval of Multi-Layered Cloud Properties Using Satellite Data

NASA Technical Reports Server (NTRS)

Minnis, Patrick; Sun-Mack, Sunny; Chen, Yan; Yi, Helen; Huang, Jian-Ping; Nguyen, Louis; Khaiyer, Mandana M.

2005-01-01

Four techniques for detecting multilayered clouds and retrieving the cloud properties using satellite data are explored to help address the need for better quantification of cloud vertical structure. A new technique was developed using multispectral imager data with secondary imager products (infrared brightness temperature differences, BTD). The other methods examined here use atmospheric sounding data (CO2-slicing, CO2), BTD, or microwave data. The CO2 and BTD methods are limited to optically thin cirrus over low clouds, while the MWR methods are limited to ocean areas only. This paper explores the use of the BTD and CO2 methods as applied to Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Microwave Scanning Radiometer EOS (AMSR-E) data taken from the Aqua satellite over ocean surfaces. Cloud properties derived from MODIS data for the Clouds and the Earth's Radiant Energy System (CERES) Project are used to classify cloud phase and optical properties. The preliminary results focus on a MODIS image taken off the Uruguayan coast. The combined MW visible infrared (MVI) method is assumed to be the reference for detecting multilayered ice-over-water clouds. The BTD and CO2 techniques accurately match the MVI classifications in only 51 and 41% of the cases, respectively. Much additional study is need to determine the uncertainties in the MVI method and to analyze many more overlapped cloud scenes.

Detection and retrieval of multi-layered cloud properties using satellite data

NASA Astrophysics Data System (ADS)

Minnis, Patrick; Sun-Mack, Sunny; Chen, Yan; Yi, Helen; Huang, Jianping; Nguyen, Louis; Khaiyer, Mandana M.

2005-10-01

Four techniques for detecting multilayered clouds and retrieving the cloud properties using satellite data are explored to help address the need for better quantification of cloud vertical structure. A new technique was developed using multispectral imager data with secondary imager products (infrared brightness temperature differences, BTD). The other methods examined here use atmospheric sounding data (CO2-slicing, CO2), BTD, or microwave data. The CO2 and BTD methods are limited to optically thin cirrus over low clouds, while the MWR methods are limited to ocean areas only. This paper explores the use of the BTD and CO2 methods as applied to Moderate Resolution Imaging Spectroradiometer (MODIS) and Advanced Microwave Scanning Radiometer EOS (AMSR-E) data taken from the Aqua satellite over ocean surfaces. Cloud properties derived from MODIS data for the Clouds and the Earth's Radiant Energy System (CERES) Project are used to classify cloud phase and optical properties. The preliminary results focus on a MODIS image taken off the Uruguayan coast. The combined MW visible infrared (MVI) method is assumed to be the reference for detecting multilayered ice-over-water clouds. The BTD and CO2 techniques accurately match the MVI classifications in only 51 and 41% of the cases, respectively. Much additional study is need to determine the uncertainties in the MVI method and to analyze many more overlapped cloud scenes.

Improved simulation of aerosol, cloud, and density measurements by shuttle lidar

NASA Technical Reports Server (NTRS)

Russell, P. B.; Morley, B. M.; Livingston, J. M.; Grams, G. W.; Patterson, E. W.

1981-01-01

Data retrievals are simulated for a Nd:YAG lidar suitable for early flight on the space shuttle. Maximum assumed vertical and horizontal resolutions are 0.1 and 100 km, respectively, in the boundary layer, increasing to 2 and 2000 km in the mesosphere. Aerosol and cloud retrievals are simulated using 1.06 and 0.53 microns wavelengths independently. Error sources include signal measurement, conventional density information, atmospheric transmission, and lidar calibration. By day, tenuous clouds and Saharan and boundary layer aerosols are retrieved at both wavelengths. By night, these constituents are retrieved, plus upper tropospheric, stratospheric, and mesospheric aerosols and noctilucent clouds. Density, temperature, and improved aerosol and cloud retrievals are simulated by combining signals at 0.35, 1.06, and 0.53 microns. Particlate contamination limits the technique to the cloud free upper troposphere and above. Error bars automatically show effect of this contamination, as well as errors in absolute density nonmalization, reference temperature or pressure, and the sources listed above. For nonvolcanic conditions, relative density profiles have rms errors of 0.54 to 2% in the upper troposphere and stratosphere. Temperature profiles have rms errors of 1.2 to 2.5 K and can define the tropopause to 0.5 km and higher wave structures to 1 or 2 km.

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

NASA Technical Reports Server (NTRS)

Titlow, James; Baum, Bryan A.

1993-01-01

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

Land, Ocean and Ice sheet surface elevation retrieval from CALIPSO lidar measurements

NASA Astrophysics Data System (ADS)

Lu, X.; Hu, Y.

2013-12-01

Since launching in April 2006 the main objective of the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission has been studying the climate impact of clouds and aerosols in the atmosphere. However, CALIPSO also collects information about other components of the Earth's ecosystem, such as lands, oceans and polar ice sheets. The objective of this study is to propose a Super-Resolution Altimetry (SRA) technique to provide high resolution of land, ocean and polar ice sheet surface elevation from CALIPSO single shot lidar measurements (70 m spot size). The land surface results by the new technique agree with the United States Geological Survey (USGS) National Elevation Database (NED) high-resolution elevation maps, and the ice sheet surface results in the region of Greenland and Antarctic compare very well with the Ice, Cloud and land Elevation Satellite (ICESat) laser altimetry measurements. The comparisons suggest that the obtained CALIPSO surface elevation information by the new technique is accurate to within 1 m. The effects of error sources on the retrieved surface elevation are discussed. Based on the new technique, the preliminary data products of along-track topography retrieved from the CALIPSO lidar measurements is available to the altimetry community for evaluation.

Characterizing the information content of cloud thermodynamic phase retrievals from the notional PACE OCI shortwave reflectance measurements

NASA Astrophysics Data System (ADS)

Coddington, O. M.; Vukicevic, T.; Schmidt, K. S.; Platnick, S.

2017-08-01

We rigorously quantify the probability of liquid or ice thermodynamic phase using only shortwave spectral channels specific to the National Aeronautics and Space Administration's Moderate Resolution Imaging Spectroradiometer, Visible Infrared Imaging Radiometer Suite, and the notional future Plankton, Aerosol, Cloud, ocean Ecosystem imager. The results show that two shortwave-infrared channels (2135 and 2250 nm) provide more information on cloud thermodynamic phase than either channel alone; in one case, the probability of ice phase retrieval increases from 65 to 82% by combining 2135 and 2250 nm channels. The analysis is performed with a nonlinear statistical estimation approach, the GEneralized Nonlinear Retrieval Analysis (GENRA). The GENRA technique has previously been used to quantify the retrieval of cloud optical properties from passive shortwave observations, for an assumed thermodynamic phase. Here we present the methodology needed to extend the utility of GENRA to a binary thermodynamic phase space (i.e., liquid or ice). We apply formal information content metrics to quantify our results; two of these (mutual and conditional information) have not previously been used in the field of cloud studies.

Cloud Overlapping Detection Algorithm Using Solar and IR Wavelengths With GOSE Data Over ARM/SGP Site

NASA Technical Reports Server (NTRS)

Kawamoto, Kazuaki; Minnis, Patrick; Smith, William L., Jr.

2001-01-01

One of the most perplexing problems in satellite cloud remote sensing is the overlapping of cloud layers. Although most techniques assume a 1-layer cloud system in a given retrieval of cloud properties, many observations are affected by radiation from more than one cloud layer. As such, cloud overlap can cause errors in the retrieval of many properties including cloud height, optical depth, phase, and particle size. A variety of methods have been developed to identify overlapped clouds in a given satellite imager pixel. Baum el al. (1995) used CO2 slicing and a spatial coherence method to demonstrate a possible analysis method for nighttime detection of multilayered clouds. Jin and Rossow (1997) also used a multispectral CO2 slicing technique for a global analysis of overlapped cloud amount. Lin et al. (1999) used a combination infrared, visible, and microwave data to detect overlapped clouds over water. Recently, Baum and Spinhirne (2000) proposed 1.6 and 11 microns. bispectral threshold method. While all of these methods have made progress in solving this stubborn problem, none have yet proven satisfactory for continuous and consistent monitoring of multilayer cloud systems. It is clear that detection of overlapping clouds from passive instruments such as satellite radiometers is in an immature stage of development and requires additional research. Overlapped cloud systems also affect the retrievals of cloud properties over the ARM domains (e.g., Minnis et al 1998) and hence should identified as accurately as possible. To reach this goal, it is necessary to determine which information can be exploited for detecting multilayered clouds from operational meteorological satellite data used by ARM. This paper examines the potential information available in spectral data available on the Geostationary Operational Environmental Satellite (GOES) imager and the NOAA Advanced Very High Resolution Radiometer (AVHRR) used over the ARM SGP and NSA sites to study the capability of detecting overlapping clouds

Cloud Overlapping Detection Algorithm Using Solar and IR Wavelengths with GOES Data Over ARM/SGP Site

NASA Technical Reports Server (NTRS)

Kawamoto, K.; Minnis, P.; Smith, W. L., Jr.

2001-01-01

One of the most perplexing problems in satellite cloud remote sensing is the overlapping of cloud layers. Although most techniques assume a one layer cloud system in a given retrieval of cloud properties, many observations are affected by radiation from more than one cloud layer. As such, cloud overlap can cause errors in the retrieval of many properties including cloud height, optical depth, phase, and particle size. A variety of methods have been developed to identify overlapped clouds in a given satellite imager pixel. Baum et al used CO2 slicing and a spatial coherence method to demonstrate a possible analysis method for nighttime detection of multilayered clouds. Jin and Rossow also used a multispectral CO2 slicing technique for a global analysis of overlapped cloud amount. Lin et al. used a combination infrared (IR), visible (VIS), and microwave data to detect overlapped clouds over water. Recently, Baum and Spinhirne proposed a 1.6 and 11 micron bispectral threshold method. While all of these methods have made progress in solving this stubborn problem none have yet proven satisfactory for continuous and consistent monitoring of multilayer cloud systems. It is clear that detection of overlapping clouds from passive instruments such as satellite radiometers is in an immature stage of development and requires additional research. Overlapped cloud systems also affect the retrievals of cloud properties over the Atmospheric Radiation Measurement (ARM) domains and hence should be identified as accurately as possible. To reach this goal, it is necessary to determine which information can be exploited for detecting multilayered clouds from operational meteorological satellite data used by ARM. This paper examines the potential information available in spectral data available on the Geostationary Operational Environmental Satellite (GOES) imager and the National Oceanic Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) used over the ARM Program's Southern Great Plains (SGP), and North Slope of Alaska (NSA) sites to study the capability of detecting overlapping clouds.

Retrievals of Cloud Droplet Size from the RSP Data: Validation Using in Situ Measurements

NASA Technical Reports Server (NTRS)

Alexandrov, Mikhail D.; Cairns, Brian; Sinclair, Kenneth; Wasilewski, Andrzej P.; Ziemba, Luke; Crosbie, Ewan; Hair, John; Hu, Yongxiang; Hostetler, Chris; Stamnes, Snorre

2016-01-01

We present comparisons of cloud droplet size distributions retrieved from the Research Scanning Polarimeter (RSP) data with correlative in situ measurements made during the North Atlantic Aerosols and Marine Ecosystems Study (NAAMES). This field experiment was based at St. Johns airport, Newfoundland, Canada with the latest deployment in May - June 2016. RSP was onboard the NASA C-130 aircraft together with an array of in situ and other remote sensing instrumentation. The RSP is an along-track scanner measuring polarized and total reflectances in9 spectral channels. Its unique high angular resolution allows for characterization of liquid water droplet size using the rainbow structure observed in the polarized reflectances in the scattering angle range between 135 and 165 degrees. A parametric fitting algorithm applied to the polarized reflectances provides retrievals of the droplet effective radius and variance assuming a prescribed size distribution shape (gamma distribution). In addition to this, we use a non-parametric method, Rainbow Fourier Transform (RFT), which allows us to retrieve the droplet size distribution (DSD) itself. The latter is important in the case of clouds with complex structure, which results in multi-modal DSDs. During NAAMES the aircraft performed a number of flight patterns specifically designed for comparison of remote sensing retrievals and in situ measurements. These patterns consisted of two flight segments above the same straight ground track. One of these segments was flown above clouds allowing for remote sensing measurements, while the other was at the cloud top where cloud droplets were sampled. We compare the DSDs retrieved from the RSP data with in situ measurements made by the Cloud Droplet Probe (CDP). The comparisons show generally good agreement with deviations explainable by the position of the aircraft within cloud and by presence of additional cloud layers in RSP view that do not contribute to the in situ DSDs. In the latter case the distributions retrieved from the RSP data were consistent with the multi-layer cloud structures observed in the correlative High Spectral Resolution Lidar (HSRL) profiles. The comparison results provide a rare validation of polarimetric droplet size retrieval techniques, which can be used for analysis of satellite data on global scale.

Cloud property datasets retrieved from AVHRR, MODIS, AATSR and MERIS in the framework of the Cloud_cci project

NASA Astrophysics Data System (ADS)

Stengel, Martin; Stapelberg, Stefan; Sus, Oliver; Schlundt, Cornelia; Poulsen, Caroline; Thomas, Gareth; Christensen, Matthew; Carbajal Henken, Cintia; Preusker, Rene; Fischer, Jürgen; Devasthale, Abhay; Willén, Ulrika; Karlsson, Karl-Göran; McGarragh, Gregory R.; Proud, Simon; Povey, Adam C.; Grainger, Roy G.; Fokke Meirink, Jan; Feofilov, Artem; Bennartz, Ralf; Bojanowski, Jedrzej S.; Hollmann, Rainer

2017-11-01

New cloud property datasets based on measurements from the passive imaging satellite sensors AVHRR, MODIS, ATSR2, AATSR and MERIS are presented. Two retrieval systems were developed that include components for cloud detection and cloud typing followed by cloud property retrievals based on the optimal estimation (OE) technique. The OE-based retrievals are applied to simultaneously retrieve cloud-top pressure, cloud particle effective radius and cloud optical thickness using measurements at visible, near-infrared and thermal infrared wavelengths, which ensures spectral consistency. The retrieved cloud properties are further processed to derive cloud-top height, cloud-top temperature, cloud liquid water path, cloud ice water path and spectral cloud albedo. The Cloud_cci products are pixel-based retrievals, daily composites of those on a global equal-angle latitude-longitude grid, and monthly cloud properties such as averages, standard deviations and histograms, also on a global grid. All products include rigorous propagation of the retrieval and sampling uncertainties. Grouping the orbital properties of the sensor families, six datasets have been defined, which are named AVHRR-AM, AVHRR-PM, MODIS-Terra, MODIS-Aqua, ATSR2-AATSR and MERIS+AATSR, each comprising a specific subset of all available sensors. The individual characteristics of the datasets are presented together with a summary of the retrieval systems and measurement records on which the dataset generation were based. Example validation results are given, based on comparisons to well-established reference observations, which demonstrate the good quality of the data. In particular the ensured spectral consistency and the rigorous uncertainty propagation through all processing levels can be considered as new features of the Cloud_cci datasets compared to existing datasets. In addition, the consistency among the individual datasets allows for a potential combination of them as well as facilitates studies on the impact of temporal sampling and spatial resolution on cloud climatologies.

For each dataset a digital object identifier has been issued:

Cloud_cci AVHRR-AM: https://doi.org/10.5676/DWD/ESA_Cloud_cci/AVHRR-AM/V002

Cloud_cci AVHRR-PM: https://doi.org/10.5676/DWD/ESA_Cloud_cci/AVHRR-PM/V002

Cloud_cci MODIS-Terra: https://doi.org/10.5676/DWD/ESA_Cloud_cci/MODIS-Terra/V002

Cloud_cci MODIS-Aqua: https://doi.org/10.5676/DWD/ESA_Cloud_cci/MODIS-Aqua/V002

Cloud_cci ATSR2-AATSR: https://doi.org/10.5676/DWD/ESA_Cloud_cci/ATSR2-AATSR/V002

Cloud_cci MERIS+AATSR: https://doi.org/10.5676/DWD/ESA_Cloud_cci/MERIS+AATSR/V002

Estimating the Direct Radiative Effect of Absorbing Aerosols Overlying Marine Boundary Layer Clouds in the Southeast Atlantic Using MODIS and CALIOP

NASA Technical Reports Server (NTRS)

Meyer, Kerry; Platnick, Steven; Oreopoulos, Lazaros; Lee, Dongmin

2013-01-01

Absorbing aerosols such as smoke strongly absorb solar radiation, particularly at ultraviolet and visible/near-infrared (VIS/NIR) wavelengths, and their presence above clouds can have considerable implications. It has been previously shown that they have a positive (i.e., warming) direct aerosol radiative effect (DARE) when overlying bright clouds. Additionally, they can cause biased passive instrument satellite retrievals in techniques that rely on VIS/NIR wavelengths for inferring the cloud optical thickness (COT) and effective radius (re) of underlying clouds, which can in turn yield biased above-cloud DARE estimates. Here we investigate Moderate Resolution Imaging Spectroradiometer (MODIS) cloud optical property retrieval biases due to overlying absorbing aerosols observed by Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and examine the impact of these biases on above-cloud DARE estimates. The investigation focuses on a region in the southeast Atlantic Ocean during August and September (2006-2011), where smoke from biomass burning in southern Africa overlies persistent marine boundary layer stratocumulus clouds. Adjusting for above-cloud aerosol attenuation yields increases in the regional mean liquid COT (averaged over all ocean-only liquid clouds) by roughly 6%; mean re increases by roughly 2.6%, almost exclusively due to the COT adjustment in the non-orthogonal retrieval space. It is found that these two biases lead to an underestimate of DARE. For liquid cloud Aqua MODIS pixels with CALIOP-observed above-cloud smoke, the regional mean above-cloud radiative forcing efficiency (DARE per unit aerosol optical depth (AOD)) at time of observation (near local noon for Aqua overpass) increases from 50.9Wm(sup-2)AOD(sup-1) to 65.1Wm(sup-2)AOD(sup -1) when using bias-adjusted instead of nonadjusted MODIS cloud retrievals.

Retrieval of cloud cover parameters from multispectral satellite images

NASA Technical Reports Server (NTRS)

Arking, A.; Childs, J. D.

1985-01-01

A technique is described for extracting cloud cover parameters from multispectral satellite radiometric measurements. Utilizing three channels from the AVHRR (Advanced Very High Resolution Radiometer) on NOAA polar orbiting satellites, it is shown that one can retrieve four parameters for each pixel: cloud fraction within the FOV, optical thickness, cloud-top temperature and a microphysical model parameter. The last parameter is an index representing the properties of the cloud particle and is determined primarily by the radiance at 3.7 microns. The other three parameters are extracted from the visible and 11 micron infrared radiances, utilizing the information contained in the two-dimensional scatter plot of the measured radiances. The solution is essentially one in which the distributions of optical thickness and cloud-top temperature are maximally clustered for each region, with cloud fraction for each pixel adjusted to achieve maximal clustering.

Extending "Deep Blue" aerosol retrieval coverage to cases of absorbing aerosols above clouds: Sensitivity analysis and first case studies

NASA Astrophysics Data System (ADS)

Sayer, A. M.; Hsu, N. C.; Bettenhausen, C.; Lee, J.; Redemann, J.; Schmid, B.; Shinozuka, Y.

2016-05-01

Cases of absorbing aerosols above clouds (AACs), such as smoke or mineral dust, are omitted from most routinely processed space-based aerosol optical depth (AOD) data products, including those from the Moderate Resolution Imaging Spectroradiometer (MODIS). This study presents a sensitivity analysis and preliminary algorithm to retrieve above-cloud AOD and liquid cloud optical depth (COD) for AAC cases from MODIS or similar sensors, for incorporation into a future version of the "Deep Blue" AOD data product. Detailed retrieval simulations suggest that these sensors should be able to determine AAC AOD with a typical level of uncertainty ˜25-50% (with lower uncertainties for more strongly absorbing aerosol types) and COD with an uncertainty ˜10-20%, if an appropriate aerosol optical model is known beforehand. Errors are larger, particularly if the aerosols are only weakly absorbing, if the aerosol optical properties are not known, and the appropriate model to use must also be retrieved. Actual retrieval errors are also compared to uncertainty envelopes obtained through the optimal estimation (OE) technique; OE-based uncertainties are found to be generally reasonable for COD but larger than actual retrieval errors for AOD, due in part to difficulties in quantifying the degree of spectral correlation of forward model error. The algorithm is also applied to two MODIS scenes (one smoke and one dust) for which near-coincident NASA Ames Airborne Tracking Sun photometer (AATS) data were available to use as a ground truth AOD data source, and found to be in good agreement, demonstrating the validity of the technique with real observations.

Retrieval of Aerosol Optical Depth Above Clouds from OMI Observations: Sensitivity Analysis, Case Studies

NASA Technical Reports Server (NTRS)

Torres, O.; Jethva, H.; Bhartia, P. K.

2012-01-01

A large fraction of the atmospheric aerosol load reaching the free troposphere is frequently located above low clouds. Most commonly observed aerosols above clouds are carbonaceous particles generally associated with biomass burning and boreal forest fires, and mineral aerosols originated in arid and semi-arid regions and transported across large distances, often above clouds. Because these aerosols absorb solar radiation, their role in the radiative transfer balance of the earth atmosphere system is especially important. The generally negative (cooling) top of the atmosphere direct effect of absorbing aerosols, may turn into warming when the light-absorbing particles are located above clouds. The actual effect depends on the aerosol load and the single scattering albedo, and on the geometric cloud fraction. In spite of its potential significance, the role of aerosols above clouds is not adequately accounted for in the assessment of aerosol radiative forcing effects due to the lack of measurements. In this paper we discuss the basis of a simple technique that uses near-UV observations to simultaneously derive the optical depth of both the aerosol layer and the underlying cloud for overcast conditions. The two-parameter retrieval method described here makes use of the UV aerosol index and reflectance measurements at 388 nm. A detailed sensitivity analysis indicates that the measured radiances depend mainly on the aerosol absorption exponent and aerosol-cloud separation. The technique was applied to above-cloud aerosol events over the Southern Atlantic Ocean yielding realistic results as indicated by indirect evaluation methods. An error analysis indicates that for typical overcast cloudy conditions and aerosol loads, the aerosol optical depth can be retrieved with an accuracy of approximately 54% whereas the cloud optical depth can be derived within 17% of the true value.

Use of MISR measurements to study the radiative transfer of an isolated convective cloud: Implications for cloud optical thickness retrieval

NASA Astrophysics Data System (ADS)

Cornet, C.; Davies, R.

2008-02-01

Radiative transfer simulations of an isolated deep convective cloud reconstructed with stereo-techniques from the Multiangle Imaging Spectroradiometer (MISR) are compared with the reflectances measured at the nine MISR viewing angles. The simulations were done using a three dimensional Monte Carlo model, in which ocean reflectance, aerosol and Rayleigh scattering were prescribed to match the surrounding clear-sky MISR measurements. Making reasonable assumptions regarding the vertical and horizontal distribution of the volume extinction coefficient, we were able to reproduce the MISR measurements with the 3D radiative calculations. While the uniqueness of the these distributions cannot be proven, they all lead to retrievals of much larger cloud optical thickness and cloud water content than for a 1D retrieval. Averaged over the cloud, the difference was a factor of about 3, rising to 9 locally. This is a consequence of horizontal photon transport that serves to highlight the inadequacy of 1D retrievals for the case of deep convective cloud. Concerning the internal cloud properties, we noticed the angular distribution of modeled radiances did not match the measured radiances when an ice crystal phase function was applied. Better estimates of the optical depths and water contents of deep convective clouds appear to be obtainable by integrating an estimate of the extinction coefficient over the vertical cloud extent (when this can assessed) than by attempting to invert the radiance measured from a single-angle view using 1D theory.

Using Radar, Lidar, and Radiometer measurements to Classify Cloud Type and Study Middle-Level Cloud Properties

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

Wang, Zhien

2010-06-29

The project is mainly focused on the characterization of cloud macrophysical and microphysical properties, especially for mixed-phased clouds and middle level ice clouds by combining radar, lidar, and radiometer measurements available from the ACRF sites. First, an advanced mixed-phase cloud retrieval algorithm will be developed to cover all mixed-phase clouds observed at the ACRF NSA site. The algorithm will be applied to the ACRF NSA observations to generate a long-term arctic mixed-phase cloud product for model validations and arctic mixed-phase cloud processes studies. To improve the representation of arctic mixed-phase clouds in GCMs, an advanced understanding of mixed-phase cloud processesmore » is needed. By combining retrieved mixed-phase cloud microphysical properties with in situ data and large-scale meteorological data, the project aim to better understand the generations of ice crystals in supercooled water clouds, the maintenance mechanisms of the arctic mixed-phase clouds, and their connections with large-scale dynamics. The project will try to develop a new retrieval algorithm to study more complex mixed-phase clouds observed at the ACRF SGP site. Compared with optically thin ice clouds, optically thick middle level ice clouds are less studied because of limited available tools. The project will develop a new two wavelength radar technique for optically thick ice cloud study at SGP site by combining the MMCR with the W-band radar measurements. With this new algorithm, the SGP site will have a better capability to study all ice clouds. Another area of the proposal is to generate long-term cloud type classification product for the multiple ACRF sites. The cloud type classification product will not only facilitates the generation of the integrated cloud product by applying different retrieval algorithms to different types of clouds operationally, but will also support other research to better understand cloud properties and to validate model simulations. The ultimate goal is to improve our cloud classification algorithm into a VAP.« less

Retrievals of cloud microphysical properties from the Research Scanning Polarimeter measurements made during PODEX field campaign

NASA Astrophysics Data System (ADS)

Alexandrov, M. D.; Cairns, B.; Sinclair, K.

2013-12-01

We present the retrievals of cloud droplet size distribution parameters (effective radius and variance) from the Research Scanning Polarimeter (RSP) measurements made during NASA's POlarimeter Definition EXperiment (PODEX), which was based in Palmdale, California in January - February 2013. The RSP is an airborne prototype for the Aerosol Polarimetery Sensor (APS), which was built for the NASA Glory Mission project. This instrument measures both polarized and total reflectances in 9 spectral channels with center wavelengths of 410, 470, 555, 670, 865, 960, 1590, 1880 and 2250 nm. The RSP is a push broom scanner making samples at 0.8 degree intervals within 60 degrees from nadir in both forward and backward directions. The data from actual RSP scans is aggregated into "virtual" scans, each consisting of all reflectances (at a variety of scattering angles) from a single point on the ground or at the cloud top. In the case of water clouds the rainbow is observed in the polarized reflectances in the scattering angle range between 135 and 170 degrees. It has a unique signature that is being used to accurately determine the droplet size and is not affected by cloud morphology. Simple parametric fitting algorithm applied to these polarized reflectances provides retrievals of the droplet effective radius and variance assuming a prescribed size distribution shape (gamma distribution). In addition to this, we use a non-parametric method, Rainbow Fourier Transform (RFT), which allows to retrieve the droplet size distribution a parametric model. Of particular interest is the information contained in droplet size distribution width, which is indicative of cloud life cycle. The absorbing band method is also applied to RSP total reflectance observations. The difference in the retrieved droplet size between polarized and absorbing band techniques is expected to reflect the strength of the vertical gradient in cloud liquid water content. In addition to established retrieval techniques, we will use the campaign data to evaluate a new theoretical concept allowing to estimate cloud physical thickness and droplet number concentration using both polarized and total reflectances. During the PODEX campaign the RSP was onboard the NASA's long-range high-altitude ER-2 aircraft together with an array of other remote sensing instrumentation. Correlative sampling measurements from another aircraft were also available. The data obtained during the campaign provides a good opportunity to study cloud properties and to test retrieval algorithms in a variety of locations and atmospheric conditions.

Estimating nocturnal opaque ice cloud optical depth from MODIS multispectral infrared radiances using a neural network method

NASA Astrophysics Data System (ADS)

Minnis, Patrick; Hong, Gang; Sun-Mack, Szedung; Smith, William L.; Chen, Yan; Miller, Steven D.

2016-05-01

Retrieval of ice cloud properties using IR measurements has a distinct advantage over the visible and near-IR techniques by providing consistent monitoring regardless of solar illumination conditions. Historically, the IR bands at 3.7, 6.7, 11.0, and 12.0 µm have been used to infer ice cloud parameters by various methods, but the reliable retrieval of ice cloud optical depth τ is limited to nonopaque cirrus with τ < 8. The Ice Cloud Optical Depth from Infrared using a Neural network (ICODIN) method is developed in this paper by training Moderate Resolution Imaging Spectroradiometer (MODIS) radiances at 3.7, 6.7, 11.0, and 12.0 µm against CloudSat-estimated τ during the nighttime using 2 months of matched global data from 2007. An independent data set comprising observations from the same 2 months of 2008 was used to validate the ICODIN. One 4-channel and three 3-channel versions of the ICODIN were tested. The training and validation results show that IR channels can be used to estimate ice cloud τ up to 150 with correlations above 78% and 69% for all clouds and only opaque ice clouds, respectively. However, τ for the deepest clouds is still underestimated in many instances. The corresponding RMS differences relative to CloudSat are ~100 and ~72%. If the opaque clouds are properly identified with the IR methods, the RMS differences in the retrieved optical depths are ~62%. The 3.7 µm channel appears to be most sensitive to optical depth changes but is constrained by poor precision at low temperatures. A method for estimating total optical depth is explored for estimation of cloud water path in the future. Factors affecting the uncertainties and potential improvements are discussed. With improved techniques for discriminating between opaque and semitransparent ice clouds, the method can ultimately improve cloud property monitoring over the entire diurnal cycle.

The DC-8 Submillimeter-Wave Cloud Ice Radiometer

NASA Technical Reports Server (NTRS)

Walter, Steven J.; Batelaan, Paul; Siegel, Peter; Evans, K. Franklin; Evans, Aaron; Balachandra, Balu; Gannon, Jade; Guldalian, John; Raz, Guy; Shea, James

2000-01-01

An airborne radiometer is being developed to demonstrate the capability of radiometry at submillimeter-wavelengths to characterize cirrus clouds. At these wavelengths, cirrus clouds scatter upwelling radiation from water vapor in the lower troposphere. Radiometric measurements made at multiple widely spaced frequencies permit flux variations caused by changes in scattering due to crystal size to be distinguished from changes in cloud ice content. Measurements at dual polarizations can also be used to constrain the mean crystal shape. An airborne radiometer measuring the upwelling submillimeter-wave flux should then able to retrieve both bulk and microphysical cloud properties. The radiometer is being designed to make measurements at four frequencies (183 GHz, 325 GHz, 448 GHz, and 643 GHz) with dual-polarization capability at 643 GHz. The instrument is being developed for flight on NASA's DC-8 and will scan cross-track through an aircraft window. Measurements with this radiometer in combination with independent ground-based and airborne measurements will validate the submillimeter-wave radiometer retrieval techniques. The goal of this effort is to develop a technique to enable spaceborne characterization of cirrus, which will meet a key climate measurement need. The development of an airborne radiometer to validate cirrus retrieval techniques is a critical step toward development of spaced-based radiometers to investigate and monitor cirrus on a global scale. The radiometer development is a cooperative effort of the University of Colorado, Colorado State University, Swales Aerospace, and Jet Propulsion Laboratory and is funded by the NASA Instrument Incubator Program.

A novel technique for evaluating the volcanic cloud top altitude using GPS Radio Occultation data

NASA Astrophysics Data System (ADS)

Biondi, Riccardo; Corradini, Stefano; Guerrieri, Lorenzo; Merucci, Luca; Stelitano, Dario; Pugnaghi, Sergio

2017-04-01

Volcanic ash and sulfuric gases are a major hazards to aviation since they damage the aircraft engines also at large distance from the eruption. Many challenges given by volcanic explosive eruptions are still discussed and several issues are far from being solved. The cloud top altitude can be detected with different techniques, but the accuracy is still quite coarse. This parameter is important for the air traffic to know what altitude can be ash free, and it assumes a key role for the contribution of the eruption to the climate change. Moreover, the cloud top altitude is also strictly related to the mass ejected by the eruption and represent a key parameter for the ash and SO2 retrievals by using several techniques. The Global Positioning System (GPS) Radio Occultation (RO) technique enables real time measurement of atmospheric density structure in any meteorological condition, in remote areas and during extreme atmospheric events with high vertical resolution and accuracy and this makes the RO an interesting tool for this kind of studies. In this study we have tracked the Eyjafjöll 2010 eruption by using MODIS satellite measurements and retrieved the volcanic cloud top altitudes by using two different procedures exploiting the thermal infrared CO2 absorption bands around 13.4 micrometers. The first approach is a modification of the standard CO2 slicing method while the second is based on look up tables computations. We have then selected all the RO profiles co-located with the volcanic cloud and implemented an algorithm based on the variation of the bending angle for detecting the cloud top altitude with high accuracy. The results of the comparison between the MODIS and RO volcanic height retrievals are encouraging and suggesting that, due to their independence from weather conditions and due to their high vertical resolution, the RO observations can contribute to improved detection and monitoring of volcanic clouds and to support warning systems.

Ultraviolet Satellite Measurements of Volcanic Ash. Chapter 12

NASA Technical Reports Server (NTRS)

Carn, S. A.; Krotkov, N. A.

2016-01-01

Ultraviolet (UV) remote sensing of volcanic ash and other absorbing aerosols from space began with the launch of the first Total Ozone Mapping Spectrometer (TOMS) instrument in 1978. Subsequent UV satellite missions (TOMS, GOME, SCIAMACHY, OMI, GOME-2, OMPS) have extended UV ash measurements to the present, generating a unique multidecadal record. A UV Aerosol Index (UVAI) based on two near-UV wavelengths, equally applicable to multispectral (TOMS, DSCOVR) or hyperspectral (GOME, SCIAMACHY, OMI, GOME-2, OMPS) instruments, has been used to derive a unique absorbing aerosol climatology across multiple UV satellite missions. Advantages of UV ash measurements relative to infrared (IR) techniques include the ability to detect ash at any altitude (assuming no clouds), above clouds, and over bright surfaces, where visible and IR techniques may fail. Disadvantages include the daytime-only restriction and nonspecificity to silicate ash, since UV measurements are sensitive to any UV-absorbing aerosol, including smoke, desert dust, and pollution. However, simultaneous retrieval of sulfur dioxide (SO2) abundance and UVAI provides robust discrimination of volcanic clouds. Although the UVAI is only semiquantitative, it has proved successful at detecting and tracking volcanic ash clouds from many volcanic eruptions since 1978. NASA A-Train measurements since 2006 (eg, CALIOP) have provided much improved constraints on volcanic ash altitude, and also permit identification of aerosol type through sensor synergy. Quantitative UV retrievals of ash optical depth, effective particle size, and ash column mass are possible and require assumptions of ash refractive index, particle size distribution, and ash layer altitude. The lack of extensive ash refractive index data in the UV-visible and the effects of ash particle shape on retrievals introduce significant uncertainty in the retrieved parameters, although limited validation against IR ash retrievals has been successful. In this contribution, we review UV ash detection and retrieval techniques and provide examples of volcanic eruptions detected in the approx. 37 year data record.

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.

Hyperspectrally-Resolved Surface Emissivity Derived Under Optically Thin 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

Surface spectral emissivity derived from current and future satellites can and will reveal critical information about the Earth s ecosystem and land surface type properties, which can be utilized as a means of long-term monitoring of global environment and climate change. Hyperspectrally-resolved surface emissivities are derived with an algorithm utilizes a combined fast radiative transfer model (RTM) with a molecular RTM and a cloud RTM accounting for both atmospheric absorption and cloud absorption/scattering. Clouds are automatically detected and cloud microphysical parameters are retrieved; and emissivity is retrieved under clear and optically thin cloud conditions. This technique separates surface emissivity from skin temperature by representing the emissivity spectrum with eigenvectors derived from a laboratory measured emissivity database; in other words, using the constraint as a means for the emissivity to vary smoothly across atmospheric absorption lines. Here we present the emissivity derived under optically thin clouds in comparison with that under clear conditions.

Satellite-derived vertical profiles of temperature and dew point for mesoscale weather forecast

NASA Astrophysics Data System (ADS)

Masselink, Thomas; Schluessel, P.

1995-12-01

Weather forecast-models need spatially high resolutioned vertical profiles of temperature and dewpoint for their initialisation. These profiles can be supplied by a combination of data from the Tiros-N Operational Vertical Sounder (TOVS) and the imaging Advanced Very High Resolution Radiometer (AVHRR) on board the NOAA polar orbiting sate!- lites. In cloudy cases the profiles derived from TOVS data only are of insufficient accuracy. The stanthrd deviations from radiosonde ascents or numerical weather analyses likely exceed 2 K in temperature and 5Kin dewpoint profiles. It will be shown that additional cloud information as retrieved from AVHIRR allows a significant improvement in theaccuracy of vertical profiles. The International TOVS Processing Package (ITPP) is coupled to an algorithm package called AVHRR Processing scheme Over cLouds, Land and Ocean (APOLLO) where parameters like cloud fraction and cloud-top temperature are determined with higher accuracy than obtained from TOVS retrieval alone. Furthermore, a split-window technique is applied to the cloud-free AVHRR imagery in order to derive more accurate surface temperatures than can be obtained from the pure TOVS retrieval. First results of the impact of AVHRR cloud detection on the quality of the profiles are presented. The temperature and humidity profiles of different retrieval approaches are validated against analyses of the European Centre for Medium-Range Weatherforecasts.

Remote Sensing of Cloud Top Height from SEVIRI: Analysis of Eleven Current Retrieval Algorithms

NASA Technical Reports Server (NTRS)

Hamann, U.; Walther, A.; Baum, B.; Bennartz, R.; Bugliaro, L.; Derrien, M.; Francis, P. N.; Heidinger, A.; Joro, S.; Kniffka, A.;

A browser-based 3D Visualization Tool designed for comparing CERES/CALIOP/CloudSAT level-2 data sets.

NASA Astrophysics Data System (ADS)

Chu, C.; Sun-Mack, S.; Chen, Y.; Heckert, E.; Doelling, D. R.

2017-12-01

In Langley NASA, Clouds and the Earth's Radiant Energy System (CERES) and Moderate Resolution Imaging Spectroradiometer (MODIS) are merged with Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) on the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) and CloudSat Cloud Profiling Radar (CPR). The CERES merged product (C3M) matches up to three CALIPSO footprints with each MODIS pixel along its ground track. It then assigns the nearest CloudSat footprint to each of those MODIS pixels. The cloud properties from MODIS, retrieved using the CERES algorithms, are included in C3M with the matched CALIPSO and CloudSat products along with radiances from 18 MODIS channels. The dataset is used to validate the CERES retrieved MODIS cloud properties and the computed TOA and surface flux difference using MODIS or CALIOP/CloudSAT retrieved clouds. This information is then used to tune the computed fluxes to match the CERES observed TOA flux. A visualization tool will be invaluable to determine the cause of these large cloud and flux differences in order to improve the methodology. This effort is part of larger effort to allow users to order the CERES C3M product sub-setted by time and parameter as well as the previously mentioned visualization capabilities. This presentation will show a new graphical 3D-interface, 3D-CERESVis, that allows users to view both passive remote sensing satellites (MODIS and CERES) and active satellites (CALIPSO and CloudSat), such that the detailed vertical structures of cloud properties from CALIPSO and CloudSat are displayed side by side with horizontally retrieved cloud properties from MODIS and CERES. Similarly, the CERES computed profile fluxes whether using MODIS or CALIPSO and CloudSat clouds can also be compared. 3D-CERESVis is a browser-based visualization tool that makes uses of techniques such as multiple synchronized cursors, COLLADA format data and Cesium.

Extending "Deep Blue" Aerosol Retrieval Coverage to Cases of Absorbing Aerosols Above Clouds: Sensitivity Analysis and First Case Studies

NASA Technical Reports Server (NTRS)

Sayer, A. M.; Hsu, N. C.; Bettenhausen, C.; Lee, J.; Redemann, J.; Schmid, B.; Shinozuka, Y.

2016-01-01

Cases of absorbing aerosols above clouds (AACs), such as smoke or mineral dust, are omitted from most routinely processed space-based aerosol optical depth (AOD) data products, including those from the Moderate Resolution Imaging Spectroradiometer (MODIS). This study presents a sensitivity analysis and preliminary algorithm to retrieve above-cloud AOD and liquid cloud optical depth (COD) for AAC cases from MODIS or similar sensors, for incorporation into a future version of the "Deep Blue" AOD data product. Detailed retrieval simulations suggest that these sensors should be able to determine AAC AOD with a typical level of uncertainty approximately 25-50 percent (with lower uncertainties for more strongly absorbing aerosol types) and COD with an uncertainty approximately10-20 percent, if an appropriate aerosol optical model is known beforehand. Errors are larger, particularly if the aerosols are only weakly absorbing, if the aerosol optical properties are not known, and the appropriate model to use must also be retrieved. Actual retrieval errors are also compared to uncertainty envelopes obtained through the optimal estimation (OE) technique; OE-based uncertainties are found to be generally reasonable for COD but larger than actual retrieval errors for AOD, due in part to difficulties in quantifying the degree of spectral correlation of forward model error. The algorithm is also applied to two MODIS scenes (one smoke and one dust) for which near-coincident NASA Ames Airborne Tracking Sun photometer (AATS) data were available to use as a ground truth AOD data source, and found to be in good agreement, demonstrating the validity of the technique with real observations.

Fog and Cloud Induced Aerosol Modification Observed by AERONET

NASA Technical Reports Server (NTRS)

Eck, T. F.; Holben, B. N.; Reid, J. S.; Giles, D. M.; Rivas, M. A.; Singh, R. P.; Tripathi, S. N.; Bruegge, C. J.; Platnick, S. E.; Arnold, G. T.;

Cirrus Horizontal Heterogeneity Effects on Cloud Optical Properties Retrieved from MODIS VNIR to TIR Channels as a Function of the Spatial Resolution

NASA Astrophysics Data System (ADS)

Fauchez, T.; Platnick, S. E.; Sourdeval, O.; Wang, C.; Meyer, K.; Cornet, C.; Szczap, F.

2017-12-01

Cirrus are an important part of the Earth radiation budget but an assessment of their role yet remains highly uncertain. Cirrus optical properties such as Cloud Optical Thickness (COT) and ice crystal effective particle size (Re) are often retrieved with a combination of Visible/Near InfraRed (VNIR) and ShortWave-InfraRed (SWIR) reflectance channels. Alternatively, Thermal InfraRed (TIR) techniques, such as the Split Window Technique (SWT), have demonstrated better sensitivity to thin cirrus. However, current satellite operational products for both retrieval methods assume that cloudy pixels are horizontally homogeneous (Plane Parallel and Homogeneous Approximation (PPHA)) and independent (Independent Pixel Approximation (IPA)). The impact of these approximations on cirrus retrievals needs to be understood and, as far as possible, corrected. Horizontal heterogeneity effects can be more easily estimated and corrected in the TIR range because they are mainly dominated by the PPA bias, which primarily depends on the COT subpixel heterogeneity. For solar reflectance channels, in addition to the PPHA bias, the IPA can lead to significant retrieval errors if there is large photon transport between cloudy columns in addition to brightening and shadowing effects that are more difficult to quantify.The effects of cirrus horizontal heterogeneity are here studied on COT and Re retrievals obtained using simulated MODIS reflectances at 0.86 and 2.11 μm and radiances at 8.5, 11.0 and 12.0 μm, for spatial resolutions ranging from 50 m to 10 km. For each spatial resolution, simulated TOA reflectances and radiances are combined for cloud optical property retrievals with a research-level optimal estimation retrieval method (OEM). The impact of horizontal heterogeneity on the retrieved products is assessed for different solar geometries and various combinations of the five channels.

Retrieval, Inter-Comparison, and Validation of Above-Cloud Aerosol Optical Depth from A-train Sensors

NASA Technical Reports Server (NTRS)

Jethva, Hiren; Torres, Omar; Bhartia, Pawan K.; Remer, Lorraine; Redemann, Jens; Dunagan, Stephen E.; Livingston, John; Shinozuka, Yohei; Kacenelenbogen, Meloe; Segal-Rosenbeimer, Michal;

Constraining Methane Abundance and Cloud Properties from the Reflected Light Spectra of Directly Imaged Exoplanets

NASA Astrophysics Data System (ADS)

Lupu, R.; Marley, M. S.; Lewis, N. K.

2015-12-01

We have assembled an atmospheric retrieval package for the reflected light spectra of gas- and ice- giants in order to inform the design and estimate the scientific return of future space-based coronagraph instruments. Such instruments will have a working bandpass of ~0.4-1 μm and a resolving power R~70, and will enable the characterization of tens of exoplanets in the Solar neighborhood. The targets will be chosen form known RV giants, with estimated effective temperatures of ~100-600 K and masses between 0.3 and 20 MJupiter. In this regime, both methane and clouds will have the largest effects on the observed spectra. Our retrieval code is the first to include cloud properties in the core set of parameters, along with methane abundance and surface gravity. We consider three possible cloud structure scenarios, with 0, 1 or 2 cloud layers, respectively. The best-fit parameters for a given model are determined using a Monte Carlo Markov Chain ensemble sampler, and the most favored cloud structure is chosen by calculating the Bayes factors between different models. We present the performance of our retrieval technique applied to a set of representative model spectra, covering a SNR range form 5 to 20 and including possible noise correlations over a 25 or 100 nanometer scale. Further, we apply the technique to more realistic cases, namely simulated observations of Jupiter, Saturn, Uranus, and the gas-giant HD99492c. In each case, we determine the confidence levels associated with the methane and cloud detections, as a function of SNR and noise properties.

Cloud Optical Depth Retrievals from Solar Background "signal" of Micropulse Lidars

NASA Technical Reports Server (NTRS)

Chiu, J. Christine; Marshak, A.; Wiscombe, W.; Valencia, S.; Welton, E. J.

2007-01-01

Pulsed lidars are commonly used to retrieve vertical distributions of cloud and aerosol layers. It is widely believed that lidar cloud retrievals (other than cloud base altitude) are limited to optically thin clouds. Here we demonstrate that lidars can retrieve optical depths of thick clouds using solar background light as a signal, rather than (as now) merely a noise to be subtracted. Validations against other instruments show that retrieved cloud optical depths agree within 10-15% for overcast stratus and broken clouds. In fact, for broken cloud situations one can retrieve not only the aerosol properties in clear-sky periods using lidar signals, but also the optical depth of thick clouds in cloudy periods using solar background signals. This indicates that, in general, it may be possible to retrieve both aerosol and cloud properties using a single lidar. Thus, lidar observations have great untapped potential to study interactions between clouds and aerosols.

Simulating return signals of a spaceborne high-spectral resolution lidar channel at 532 nm

NASA Astrophysics Data System (ADS)

Xiao, Yu; Binglong, Chen; Min, Min; Xingying, Zhang; Lilin, Yao; Yiming, Zhao; Lidong, Wang; Fu, Wang; Xiaobo, Deng

2018-06-01

High spectral resolution lidar (HSRL) system employs a narrow spectral filter to separate the particulate (cloud/aerosol) and molecular scattering components in lidar return signals, which improves the quality of the retrieved cloud/aerosol optical properties. To better develop a future spaceborne HSRL system, a novel simulation technique was developed to simulate spaceborne HSRL return signals at 532 nm using the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) cloud/aerosol extinction coefficients product and numerical weather prediction data. For validating simulated data, a mathematical particulate extinction coefficient retrieval method for spaceborne HSRL return signals is described here. We compare particulate extinction coefficient profiles from the CALIPSO operational product with simulated spaceborne HSRL data. Further uncertainty analysis shows that relative uncertainties are acceptable for retrieving the optical properties of cloud and aerosol. The final results demonstrate that they agree well with each other. It indicates that the return signals of the spaceborne HSRL molecular channel at 532 nm will be suitable for developing operational algorithms supporting a future spaceborne HSRL system.

Retrieval of Precipitation Profiles from Multiresolution, Multifrequency, Active and Passive Microwave Observations

NASA Technical Reports Server (NTRS)

Grecu, Mircea; Anagnostou, Emmanouil N.; Olson, William S.; Starr, David OC. (Technical Monitor)

2002-01-01

In this study, a technique for estimating vertical profiles of precipitation from multifrequency, multiresolution active and passive microwave observations is investigated using both simulated and airborne data. The technique is applicable to the Tropical Rainfall Measuring Mission (TRMM) satellite multi-frequency active and passive observations. These observations are characterized by various spatial and sampling resolutions. This makes the retrieval problem mathematically more difficult and ill-determined because the quality of information decreases with decreasing resolution. A model that, given reflectivity profiles and a small set of parameters (including the cloud water content, the intercept drop size distribution, and a variable describing the frozen hydrometeor properties), simulates high-resolution brightness temperatures is used. The high-resolution simulated brightness temperatures are convolved at the real sensor resolution. An optimal estimation procedure is used to minimize the differences between simulated and observed brightness temperatures. The retrieval technique is investigated using cloud model synthetic and airborne data from the Fourth Convection And Moisture Experiment. Simulated high-resolution brightness temperatures and reflectivities and airborne observation strong are convolved at the resolution of the TRMM instruments and retrievals are performed and analyzed relative to the reference data used in observations synthesis. An illustration of the possible use of the technique in satellite rainfall estimation is presented through an application to TRMM data. The study suggests improvements in combined active and passive retrievals even when the instruments resolutions are significantly different. Future work needs to better quantify the retrievals performance, especially in connection with satellite applications, and the uncertainty of the models used in retrieval.

A self-consistency approach to improve microwave rainfall rate estimation from space

NASA Technical Reports Server (NTRS)

Kummerow, Christian; Mack, Robert A.; Hakkarinen, Ida M.

1989-01-01

A multichannel statistical approach is used to retrieve rainfall rates from the brightness temperature T(B) observed by passive microwave radiometers flown on a high-altitude NASA aircraft. T(B) statistics are based upon data generated by a cloud radiative model. This model simulates variabilities in the underlying geophysical parameters of interest, and computes their associated T(B) in each of the available channels. By further imposing the requirement that the observed T(B) agree with the T(B) values corresponding to the retrieved parameters through the cloud radiative transfer model, the results can be made to agree quite well with coincident radar-derived rainfall rates. Some information regarding the cloud vertical structure is also obtained by such an added requirement. The applicability of this technique to satellite retrievals is also investigated. Data which might be observed by satellite-borne radiometers, including the effects of nonuniformly filled footprints, are simulated by the cloud radiative model for this purpose.

Deriving Cloud Droplet Number Concentration from Combined Airborne Lidar and Polarimeter Measurements from the NAAMES Mission

NASA Astrophysics Data System (ADS)

Hair, J. W.; Hostetler, C. A.; Brian, C.; Ziemba, L. D.; Alexandrov, M. D.; Hu, Y.; Crosbie, E.; Scarino, A. J.; Butler, C. F.; Moore, R.; Berkoff, T.; Harper, D. B.; Cook, A. L.; Hare, R. J.; Lee, J.; Anderson, B. E.

2017-12-01

The NASA Langley High Spectral Resolution lidar (HSRL) and the NASA GISS Research Scanning Polarimeter (RSP) were deployed onboard the NASA C-130 during two field campaigns as part of the NASA's Earth Venture-Suborbital (EVS) North Atlantic Aerosol and Marine Ecosystems Study (NAAMES) during November 2015 and May 2016. The main objectives of NAAMES are to study the phases of the North Atlantic annual plankton cycle and to investigate remote marine aerosols and their impact on boundary layer clouds. Lidar retrievals of the cloud-top extinction and lidar ratio (extinction/backscatter ratio) of boundary layer clouds are presented. These retrievals are unique and are enabled by two characteristics of the lidar: employment of the high-spectral-resolution lidar technique and the high-vertical-resolution (1.25 m) the Langley HSRL instrument. The HSRL lidar ratio retrievals are compared to estimates derived from Research Scanning Polarimeter data to assess consistency between the two remote sensors. The measurements of effective size and variance from RSP are combined with the HSRL cloud top extinction to retrieve the cloud droplet number concentrations (CDNC). The lidar+polarimeter CDNC estimates are compared to those from the Cloud Droplet Probe (CDP) that is part of the NASA Langley Aerosol Research Group Experiment (LARGE) instrument suite. Histograms of the CNDC measurements from remote sensors are shown to highlight the observed differences in CDNC between the November and May deployments.

Thermodynamic and cloud parameter retrieval using infrared spectral data

NASA Technical Reports Server (NTRS)

Zhou, Daniel K.; Smith, William L., Sr.; Liu, Xu; Larar, Allen M.; Huang, Hung-Lung A.; Li, Jun; McGill, Matthew J.; Mango, Stephen A.

2005-01-01

High-resolution infrared radiance spectra obtained from near nadir observations provide atmospheric, surface, and cloud property information. A fast radiative transfer model, including cloud effects, is used for atmospheric profile and cloud parameter retrieval. The retrieval algorithm is presented along with its application to recent field experiment data from the NPOESS Airborne Sounding Testbed - Interferometer (NAST-I). The retrieval accuracy dependence on cloud properties is discussed. It is shown that relatively accurate temperature and moisture retrievals can be 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 an accuracy of approximately 1.0 km. Preliminary NAST-I retrieval results from the recent Atlantic-THORPEX Regional Campaign (ATReC) are presented and compared with coincident observations obtained from dropsondes and the nadir-pointing Cloud Physics Lidar (CPL).

Clouds over the summertime Sahara: an evaluation of Met Office retrievals from Meteosat Second Generation using airborne remote sensing

NASA Astrophysics Data System (ADS)

Kealy, John C.; Marenco, Franco; Marsham, John H.; Garcia-Carreras, Luis; Francis, Pete N.; Cooke, Michael C.; Hocking, James

2017-05-01

Novel methods of cloud detection are applied to airborne remote sensing observations from the unique Fennec aircraft dataset, to evaluate the Met Office-derived products on cloud properties over the Sahara based on the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) on-board the Meteosat Second Generation (MSG) satellite. Two cloud mask configurations are considered, as well as the retrievals of cloud-top height (CTH), and these products are compared to airborne cloud remote sensing products acquired during the Fennec campaign in June 2011 and June 2012. Most detected clouds (67 % of the total) have a horizontal extent that is smaller than a SEVIRI pixel (3 km × 3 km). We show that, when partially cloud-contaminated pixels are included, a match between the SEVIRI and aircraft datasets is found in 80 ± 8 % of the pixels. Moreover, under clear skies the datasets are shown to agree for more than 90 % of the pixels. The mean cloud field, derived from the satellite cloud mask acquired during the Fennec flights, shows that areas of high surface albedo and orography are preferred sites for Saharan cloud cover, consistent with published theories. Cloud-top height retrievals however show large discrepancies over the region, which are ascribed to limiting factors such as the cloud horizontal extent, the derived effective cloud amount, and the absorption by mineral dust. The results of the CTH analysis presented here may also have further-reaching implications for the techniques employed by other satellite applications facilities across the world.

A Case for More Multiple Scattering Lidar from Space: Analysis of Four LITE Pulses Returned from a Marine Stratocumulus Deck

NASA Technical Reports Server (NTRS)

Davis, Anthony B.; Winker, David M.

2011-01-01

Outline: (1) Signal Physics for Multiple-Scattering Cloud Lidar, (2) SNR Estimation (3) Cloud Property Retrievals (3a) several techniques (3b) application to Lidar-In-space Technology Experiment (LITE) data (3c) relation to O2 A-band

Optically Thin Liquid Water Clouds: Their Importance and Our Challenge

NASA Technical Reports Server (NTRS)

Turner, D. D.; Vogelmann, A. M.; Austin, R. T.; Barnard, J. C.; Cady-Pereira, K.; Chiu, J. C.; Clough, S. A.; Flynn, C.; Khaiyer, M. M.; Liljegren, J.;

Retrieval and Validation of Cirrus Cloud Properties with the Far-Infrared Sensor for Cirrus (FIRSC) During CRYSTAL-FACE

NASA Technical Reports Server (NTRS)

Evans, K. Franklin

2004-01-01

This grant supported the principal investigator's analysis of data obtained during CRYSTAL-FACE by two submillimeter-wave radiometers: the Far-Infrared Sensor for Cirrus (FIRSC) and the Conical Scanning Submillimeter-wave Imaging Radiometer (CoSSIR). The PI led the overall FIRSC investigation, though Co-I Michael Vanek led the instrument component at NASA Langley. The overall CoSSIR investigation was led by James Wang at NASA Goddard, but the cirrus retrieval and validation was performed at the University of Colorado. The goal of this research was to demonstrate the submillimeter-wave cirrus cloud remote sensing technique, provide retrievals of ice water path (IWP) and median mass particle diameter (D(sub me)), and perform validation of the cirrus retrievals using other CRYSTAL-FACE datasets.

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.

Assessing the accuracy of MISR and MISR-simulated cloud top heights using CloudSat- and CALIPSO-retrieved hydrometeor profiles

NASA Astrophysics Data System (ADS)

Hillman, Benjamin R.; Marchand, Roger T.; Ackerman, Thomas P.; Mace, Gerald G.; Benson, Sally

2017-03-01

Satellite retrievals of cloud properties are often used in the evaluation of global climate models, and in recent years satellite instrument simulators have been used to account for known retrieval biases in order to make more consistent comparisons between models and retrievals. Many of these simulators have seen little critical evaluation. Here we evaluate the Multiangle Imaging Spectroradiometer (MISR) simulator by using visible extinction profiles retrieved from a combination of CloudSat, CALIPSO, MODIS, and AMSR-E observations as inputs to the MISR simulator and comparing cloud top height statistics from the MISR simulator with those retrieved by MISR. Overall, we find that the occurrence of middle- and high-altitude topped clouds agrees well between MISR retrievals and the MISR-simulated output, with distributions of middle- and high-topped cloud cover typically agreeing to better than 5% in both zonal and regional averages. However, there are significant differences in the occurrence of low-topped clouds between MISR retrievals and MISR-simulated output that are due to differences in the detection of low-level clouds between MISR and the combined retrievals used to drive the MISR simulator, rather than due to errors in the MISR simulator cloud top height adjustment. This difference highlights the importance of sensor resolution and boundary layer cloud spatial structure in determining low-altitude cloud cover. The MISR-simulated and MISR-retrieved cloud optical depth also show systematic differences, which are also likely due in part to cloud spatial structure.

4-D cloud properties from passive satellite data and applications to resolve the flight icing threat to aircraft

NASA Astrophysics Data System (ADS)

Smith, William L., Jr.

The threat for aircraft icing in clouds is a significant hazard that routinely impacts aviation operations. Accurate diagnoses and forecasts of aircraft icing conditions requires identifying the location and vertical distribution of clouds with super-cooled liquid water (SLW) droplets, as well as the characteristics of the droplet size distribution. Traditional forecasting methods rely on guidance from numerical models and conventional observations, neither of which currently resolve cloud properties adequately on the optimal scales needed for aviation. Satellite imagers provide measurements over large areas with high spatial resolution that can be interpreted to identify the locations and characteristics of clouds, including features associated with adverse weather and storms. This thesis develops new techniques for interpreting cloud products derived from satellite data to infer the flight icing threat to aircraft in a wide range of cloud conditions. For unobscured low clouds, the icing threat is determined using empirical relationships developed from correlations between satellite imager retrievals of liquid water path and droplet size with icing conditions reported by pilots (PIREPS). For deep ice over water cloud systems, ice and liquid water content profiles are derived by using the imager cloud properties to constrain climatological information on cloud vertical structure and water phase obtained apriori from radar and lidar observations, and from cloud model analyses. Retrievals of the SLW content embedded within overlapping clouds are mapped to the icing threat using guidance from an airfoil modeling study. Compared to PIREPS, the satellite icing detection and intensity accuracies are found to be about 90% and 70%, respectively. Mean differences between the imager IWC retrievals with those from CloudSat and Calipso are less than 30%. This level of closure in the cloud water budget can only be achieved by correcting for errors in the imager retrievals due to the simplifying but poor assumption that deep optically thick clouds are single-phase and vertically homogeneous. When applied to geostationary satellite data, the profiling method provides a real-time characterization of clouds in 4-D. This research should improve the utility of satellite imager data for quantitatively diagnosing and predicting clouds and their effects in weather and climate applications.

The CREW intercomparison of SEVIRI cloud retrievals

NASA Astrophysics Data System (ADS)

Hamann, U.; Walther, A.; Bennartz, R.; Thoss, A.; Meirink, J. M.; Roebeling, R.

2012-12-01

About 70% of the earth's surface is covered with clouds. They strongly influence the radiation balance and the water cycle of the earth. Hence the detailed monitoring of cloud properties - such as cloud fraction, cloud top temperature, cloud particle size, and cloud water path - is important to understand the role of clouds in the weather and the climate system. The remote sensing with passive sensors is an essential mean for the global observation of the cloud parameters, but is nevertheless challenging. This presentation focuses on the inter-comparison and validation of cloud physical properties retrievals from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) onboard METEOSAT. For this study we use retrievals from 12 state-of-art algorithms (Eumetsat, KNMI, NASA Langley, NASA Goddard, University Madison/Wisconsin, DWD, DLR, Meteo-France, KMI, FU Berlin, UK MetOffice) that are made available through the common database of the CREW (Cloud Retrieval Evaluation Working) group. Cloud detection, cloud top phase, height, and temperature, as well as optical properties and water path are validated with CLOUDSAT, CALIPSO, MISR, and AMSR-E measurements. Special emphasis is given to challenging retrieval conditions. Semi-transparent clouds over the earth's surface or another cloud layer modify the measured brightness temperature and increase the retrieval uncertainty. The consideration of the three-dimensional radiative effects is especially important for large viewing angles and broken cloud fields. Aerosols might be misclassified as cloud and may increase the retrieval uncertainty, too. Due to the availability of the high number of sophisticated retrieval datasets, the advantages of different retrieval approaches can be examined and suggestions for future retrieval developments can be made. We like to thank Eumetsat for sponsoring the CREW project including this work.nstitutes that participate in the CREW project.

Volcanic Ash Cloud Altitude retrievals from passive satellite sensors: the 03-09 December 2015 Etna eruption.

NASA Astrophysics Data System (ADS)

corradini, stefano; merucci, luca; guerrieri, lorenzo; pugnaghi, sergio; mcgarragh, greg; carboni, elisa; ventress, lucy; grainger, roy; scollo, simona; pardini, federica; zaksek, klemen; langmann, baerbel; bancalá, severin; stelitano, dario

2016-04-01

The volcanic ash cloud altitude is one of the most important parameter needed for the volcanic ash cloud estimations (mass, effective radius and optical depth). It is essential by modelers to initialize the ash cloud transportation models, and by volcanologists to give insights into eruption dynamics. Moreover, it is extremely important in order to reduce the disruption to flights as a result of volcanic activity whilst still ensuring safe travel. In this work, the volcanic ash cloud altitude is computed from remote sensing passive satellite data (SEVIRI, MODIS, IASI and MISR) by using the most of the existing retrieval techniques. A novel approach, based on the CO2 slicing procedure, is also shown. The comparisons among different techniques are presented and advantages and drawbacks emphasized. As test cases Etna eruptions in the period between 03 and 09 December 2015 are considered. During this time four lava fountain events occurred at the Voragine crater, forming eruption columns higher than 12 km asl and producing copious tephra fallout on volcano flanks. These events, among the biggest of the last 20 years, produced emissions that reached the stratosphere and produced a circum-global transport throughout the northern hemisphere.

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.

A physical retrieval of cloud liquid water over the global oceans using special sensor microwave/imager (SSM/I) observations

NASA Astrophysics Data System (ADS)

Greenwald, Thomas J.; Stephens, Graeme L.; Vonder Haar, Thomas H.; Jackson, Darren L.

1993-10-01

A method of remotely sensing integrated cloud liquid water over the oceans using spaceborne passive measurements from the special sensor microwave/imager (SSM/I) is described. The technique is comprised of a simple physical model that uses the 19.35- and 37-GHz channels of the SSM/I. The most comprehensive validation to date of cloud liquid water estimated from satellites is presented. This is accomplished through a comparison to independent ground-based microwave radiometer measurements of liquid water on San Nicolas Island, over the North Sea, and on Kwajalein and Saipan Islands in the western Pacific. In areas of marine stratocumulus clouds off the coast of California a further comparison is made to liquid water inferred from advanced very high resolution radiometer (AVHRR) visible reflectance measurements. The results are also compared qualitatively with near-coincident satellite imagery and with other existing microwave methods in selected regions. These comparisons indicate that the liquid water amounts derived from the simple scheme are consistent with the ground-based measurements for nonprecipitating cloud systems in the subtropics and middle to high latitudes. The comparison in the tropics, however, was less conclusive. Nevertheless, the retrieval method appears to have general applicability over most areas of the global oceans. An observational measure of the minimum uncertainty in the retrievals is determined in a limited number of known cloud-free areas, where the liquid water amounts are found to have a low variability of 0.016 kg m-2. A simple sensitivity and error analysis suggests that the liquid water estimates have a theoretical relative error typically ranging from about 25% to near 40% depending on the atmospheric/surface conditions and on the amount of liquid water present in the cloud. For the global oceans as a whole the average cloud liquid water is determined to be about 0.08 kg m-2. The major conclusion of this paper is that reasonably accurate amounts of cloud liquid water can be retrieved from SSM/I observations for nonprecipitating cloud systems, particularly in areas of persistent stratocumulus clouds, with less accurate retrievals in tropical regions.

Exploring the Effects of Cloud Vertical Structure on Cloud Microphysical Retrievals based on Polarized Reflectances

NASA Astrophysics Data System (ADS)

Miller, D. J.; Zhang, Z.; Platnick, S. E.; Ackerman, A. S.; Cornet, C.; Baum, B. A.

2013-12-01

A polarized cloud reflectance simulator was developed by coupling an LES cloud model with a polarized radiative transfer model to assess the capabilities of polarimetric cloud retrievals. With future remote sensing campaigns like NASA's Aerosols/Clouds/Ecosystems (ACE) planning to feature advanced polarimetric instruments it is important for the cloud remote sensing community to understand the retrievable information available and the related systematic/methodical limitations. The cloud retrieval simulator we have developed allows us to probe these important questions in a realistically relevant test bed. Our simulator utilizes a polarized adding-doubling radiative transfer model and an LES cloud field from a DHARMA simulation (Ackerman et al. 2004) with cloud properties based on the stratocumulus clouds observed during the DYCOMS-II field campaign. In this study we will focus on how the vertical structure of cloud microphysics can influence polarized cloud effective radius retrievals. Numerous previous studies have explored how retrievals based on total reflectance are affected by cloud vertical structure (Platnick 2000, Chang and Li 2002) but no such studies about the effects of vertical structure on polarized retrievals exist. Unlike the total cloud reflectance, which is predominantly multiply scattered light, the polarized reflectance is primarily the result of singly scattered photons. Thus the polarized reflectance is sensitive to only the uppermost region of the cloud (tau~<1) where photons can scatter once and still escape before being scattered again. This means that retrievals based on polarized reflectance have the potential to reveal behaviors specific to the cloud top. For example cloud top entrainment of dry air, a major influencer on the microphysical development of cloud droplets, can be potentially studied with polarimetric retrievals.

Cirrus Cloud Retrieval Using Infrared Sounding Data: Multilevel Cloud Errors.

NASA Astrophysics Data System (ADS)

Baum, Bryan A.; Wielicki, Bruce A.

1994-01-01

In this study we perform an error analysis for cloud-top pressure retrieval using the High-Resolution Infrared Radiometric Sounder (HIRS/2) 15-µm CO2 channels for the two-layer case of transmissive cirrus overlying an overcast, opaque stratiform cloud. This analysis includes standard deviation and bias error due to instrument noise and the presence of two cloud layers, the lower of which is opaque. Instantaneous cloud pressure retrieval errors are determined for a range of cloud amounts (0.1 1.0) and cloud-top pressures (850250 mb). Large cloud-top pressure retrieval errors are found to occur when a lower opaque layer is present underneath an upper transmissive cloud layer in the satellite field of view (FOV). Errors tend to increase with decreasing upper-cloud elective cloud amount and with decreasing cloud height (increasing pressure). Errors in retrieved upper-cloud pressure result in corresponding errors in derived effective cloud amount. For the case in which a HIRS FOV has two distinct cloud layers, the difference between the retrieved and actual cloud-top pressure is positive in all casts, meaning that the retrieved upper-cloud height is lower than the actual upper-cloud height. In addition, errors in retrieved cloud pressure are found to depend upon the lapse rate between the low-level cloud top and the surface. We examined which sounder channel combinations would minimize the total errors in derived cirrus cloud height caused by instrument noise and by the presence of a lower-level cloud. We find that while the sounding channels that peak between 700 and 1000 mb minimize random errors, the sounding channels that peak at 300—500 mb minimize bias errors. For a cloud climatology, the bias errors are most critical.

Comparison of CALIPSO-Like, LaRC, and MODIS Retrievals of Ice Cloud Properties over SIRTA in France and Florida during CRYSTAL-FACE

NASA Technical Reports Server (NTRS)

Chiriaco, M.; Chepfer, H.; Haeffelin, M.; Minnis, P.; Noel, V.; Platnick, S.; McGill, M.; Baumgardner, D.; Dubuisson, P.; Pelon, J.;

Final Report of Research Conducted For DE-AI02-08ER64546

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

Patrick Minnis

2012-03-28

Research was conducted for 3-4 years to use ARM data to validate satellite cloud retrievals and help the development of improved techniques for remotely sensing clouds and radiative fluxes from space to complement the ARM surface measurement program. This final report summarizes the results and publications during the last 2 years of the studies. Since our last report covering the 2009 period, we published four papers that were accepted during the previous reporting period and revised and published a fifth one. Our efforts to intercalibrate selected channels on several polar orbiting and geostationary satellite imagers, which are funded in partmore » by ASR, resulted in methods that were accepted as part of the international Global Space-based Intercalibration System (GSICS) calibration algorithms. We developed a new empirical method for correcting the spectral differences between comparable channels on various imagers that will be used to correct the calibrations of the satellite data used for ARM. We documented our cloud retrievals for the VAMOS Ocean-Cloud-Atmosphere-Land Study Regional Experiment (VOCALS-Rex; ARM participated with an AAF contribution) in context of the entire experiment. We used our VOCALS satellite data along with the aircraft measurements to better understand the relationships between aerosols and liquid water path in marine stratus clouds. We continued or efforts to validate and improve the satellite cloud retrievals for ARM and using ARM data to validate retrievals for other purposes.« less

Simultaneously inferring above-cloud absorbing aerosol optical thickness and underlying liquid phase cloud optical and microphysical properties using MODIS

NASA Astrophysics Data System (ADS)

Meyer, Kerry; Platnick, Steven; Zhang, Zhibo

2015-06-01

The regional haze over the southeast (SE) Atlantic Ocean induced by biomass burning in southern Africa can be problematic for passive imager-based retrievals of the underlying quasi-permanent marine boundary layer (MBL) clouds and for estimates of top-of-atmosphere (TOA) aerosol direct radiative effect (DRE). Here an algorithm is introduced to simultaneously retrieve above-cloud aerosol optical thickness (AOT), the cloud optical thickness (COT), and cloud effective particle radius (CER) of the underlying MBL clouds while also providing pixel-level estimates of retrieval uncertainty. This approach utilizes reflectance measurements at six Moderate Resolution Imaging Spectroradiometer (MODIS) channels from the visible to the shortwave infrared. Retrievals are run under two aerosol model assumptions on 8 years (2006-2013) of June-October Aqua MODIS data over the SE Atlantic, from which a regional cloud and above-cloud aerosol climatology is produced. The cloud retrieval methodology is shown to yield COT and CER consistent with those from the MODIS operational cloud product (MOD06) when forcing AOT to zero, while the full COT-CER-AOT retrievals that account for the above-cloud aerosol attenuation increase regional monthly mean COT and CER by up to 9% and 2%, respectively. Retrieved AOT is roughly 3 to 5 times larger than the collocated 532 nm Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) retrievals, though closer agreement is observed with the CALIOP 1064 nm retrievals, a result consistent with previous case study analyses. Regional cloudy-sky above-cloud aerosol DRE calculations are also performed that illustrate the importance of the aerosol model assumption and underlying cloud retrievals.

Comparison of Ice Cloud Particle Sizes Retrieved From Satellite Data Derived From In Situ Measurements

NASA Technical Reports Server (NTRS)

Han, Qingyuan; Rossow, William B.; Chou, Joyce; Welch, Ronald M.

1997-01-01

Cloud microphysical parameterizations have attracted a great deal of attention in recent years due to their effect on cloud radiative properties and cloud-related hydrological processes in large-scale models. The parameterization of cirrus particle size has been demonstrated as an indispensable component in the climate feedback analysis. Therefore, global-scale, long-term observations of cirrus particle sizes are required both as a basis of and as a validation of parameterizations for climate models. While there is a global scale, long-term survey of water cloud droplet sizes (Han et al. 1994), there is no comparable study for cirrus ice crystals. In this paper a near-global survey of cirrus ice crystal sizes is conducted using ISCCP satellite data analysis. The retrieval scheme uses phase functions based upon hexagonal crystals calculated by a ray tracing technique. The results show that global mean values of D(e) are about 60 micro-m. This study also investigates the possible reasons for the significant difference between satellite retrieved effective radii (approx. 60 micro-m) and aircraft measured particle sizes (approx. 200 micro-m) during the FIRE I IFO experiment. They are (1) vertical inhomogeneity of cirrus particle sizes; (2) lower limit of the instrument used in aircraft measurements; (3) different definitions of effective particle sizes; and (4) possible inappropriate phase functions used in satellite retrieval.

Effect of the Inhomogeneity of Ice Crystals on Retrieving Ice Cloud Optical Thickness and Effective Particle Size

NASA Technical Reports Server (NTRS)

Xie, Yu; Minnis, Patrick; Hu, Yong X.; Kattawar, George W.; Yang, Ping

2008-01-01

Spherical or spheroidal air bubbles are generally trapped in the formation of rapidly growing ice crystals. In this study the single-scattering properties of inhomogeneous ice crystals containing air bubbles are investigated. Specifically, a computational model based on an improved geometric-optics method (IGOM) has been developed to simulate the scattering of light by randomly oriented hexagonal ice crystals containing spherical or spheroidal air bubbles. A combination of the ray-tracing technique and the Monte Carlo method is used. The effect of the air bubbles within ice crystals is to smooth the phase functions, diminish the 22deg and 46deg halo peaks, and substantially reduce the backscatter relative to bubble-free particles. These features vary with the number, sizes, locations and shapes of the air bubbles within ice crystals. Moreover, the asymmetry factors of inhomogeneous ice crystals decrease as the volume of air bubbles increases. Cloud reflectance lookup tables were generated at wavelengths 0.65 m and 2.13 m with different air-bubble conditions to examine the impact of the bubbles on retrieving ice cloud optical thickness and effective particle size. The reflectances simulated for inhomogeneous ice crystals are slightly larger than those computed for homogenous ice crystals at a wavelength of 0.65 microns. Thus, the retrieved cloud optical thicknesses are reduced by employing inhomogeneous ice cloud models. At a wavelength of 2.13 microns, including air bubbles in ice cloud models may also increase the reflectance. This effect implies that the retrieved effective particle sizes for inhomogeneous ice crystals are larger than those retrieved for homogeneous ice crystals, particularly, in the case of large air bubbles.

Validation of Cloud Properties From Multiple Satellites Using CALIOP Data

NASA Technical Reports Server (NTRS)

Yost, Christopher R.; Minnis, Patrick; Bedka, Kristopher M.; Heck, Patrick W.; Palikonda, Rabindra; Sun-Mack, Sunny; Trepte, Qing

2016-01-01

The NASA Langley Satellite ClOud and Radiative Property retrieval System (SatCORPS) is routinely applied to multispectral imagery from several geostationary and polar-orbiting imagers to retrieve cloud properties for weather and climate applications. Validation of the retrievals with independent datasets is continuously ongoing in order to understand differences caused by calibration, spatial resolution, viewing geometry, and other factors. The CALIOP instrument provides a decade of detailed cloud observations which can be used to evaluate passive imager retrievals of cloud boundaries, thermodynamic phase, cloud optical depth, and water path on a global scale. This paper focuses on comparisons of CALIOP retrievals to retrievals from MODIS, VIIRS, AVHRR, GOES, SEVIRI, and MTSAT. CALIOP is particularly skilled at detecting weakly-scattering cirrus clouds with optical depths less than approx. 0.5. These clouds are often undetected by passive imagers and the effect this has on the property retrievals is discussed.

Progress in Understanding the Impacts of 3-D Cloud Structure on MODIS Cloud Property Retrievals for Marine Boundary Layer Clouds

NASA Technical Reports Server (NTRS)

Zhang, Zhibo; Werner, Frank; Miller, Daniel; Platnick, Steven; Ackerman, Andrew; DiGirolamo, Larry; Meyer, Kerry; Marshak, Alexander; Wind, Galina; Zhao, Guangyu

2016-01-01

Theory: A novel framework based on 2-D Tayler expansion for quantifying the uncertainty in MODIS retrievals caused by sub-pixel reflectance inhomogeneity. (Zhang et al. 2016). How cloud vertical structure influences MODIS LWP retrievals. (Miller et al. 2016). Observation: Analysis of failed MODIS cloud property retrievals. (Cho et al. 2015). Cloud property retrievals from 15m resolution ASTER observations. (Werner et al. 2016). Modeling: LES-Satellite observation simulator (Zhang et al. 2012, Miller et al. 2016).

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

NASA Technical Reports Server (NTRS)

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

2014-01-01

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

Liquid Water Cloud Measurements Using the Raman Lidar Technique: Current Understanding and Future Research Needs

NASA Technical Reports Server (NTRS)

Tetsu, Sakai; Whiteman, David N.; Russo, Felicita; Turner, David D.; Veselovskii, Igor; Melfi, S. Harvey; Nagai, Tomohiro; Mano, Yuzo

2013-01-01

This paper describes recent work in the Raman lidar liquid water cloud measurement technique. The range-resolved spectral measurements at the National Aeronautics and Space Administration Goddard Space Flight Center indicate that the Raman backscattering spectra measured in and below low clouds agree well with theoretical spectra for vapor and liquid water. The calibration coefficients of the liquid water measurement for the Raman lidar at the Atmospheric Radiation Measurement Program Southern Great Plains site of the U.S. Department of Energy were determined by comparison with the liquid water path (LWP) obtained with Atmospheric Emitted Radiance Interferometer (AERI) and the liquid water content (LWC) obtained with the millimeter wavelength cloud radar and water vapor radiometer (MMCR-WVR) together. These comparisons were used to estimate the Raman liquid water cross-sectional value. The results indicate a bias consistent with an effective liquid water Raman cross-sectional value that is 28%-46% lower than published, which may be explained by the fact that the difference in the detectors' sensitivity has not been accounted for. The LWP of a thin altostratus cloud showed good qualitative agreement between lidar retrievals and AERI. However, the overall ensemble of comparisons of LWP showed considerable scatter, possibly because of the different fields of view of the instruments, the 350-m distance between the instruments, and the horizontal inhomogeneity of the clouds. The LWC profiles for a thick stratus cloud showed agreement between lidar retrievals andMMCR-WVR between the cloud base and 150m above that where the optical depth was less than 3. Areas requiring further research in this technique are discussed.

[Retrieval of the Optical Thickness and Cloud Top Height of Cirrus Clouds Based on AIRS IR High Spectral Resolution Data].

PubMed

Cao, Ya-nan; Wei, He-li; Dai, Cong-ming; Zhang, Xue-hai

2015-05-01

A study was carried out to retrieve optical thickness and cloud top height of cirrus clouds from the Atmospheric Infrared Sounder (AIRS) high spectral resolution data in 1070~1135 cm-1 IR band using a Combined Atmospheric Radiative Transfer model (CART) by brightness temperature difference between model simulation and AIRS observation. The research is based on AIRS LIB high spectral infrared observation data combined with Moderate Resolution Imaging Spectroradiometer (MODIS) cloud product data. Brightness temperature spectra based, on the retrieved cirrus optical thickness and cloud top height were simulated and compared with brightness temperature spectra of AIRS observation in the 650~1150 cm-1 band. The cirrus optical thickness and cloud top height retrieved were compared with brightness temperature of AIRS for channel 760 (900.56 cm-1, 11. 1 µm) and cirrus reflectance of MODIS cloud product. And cloud top height retrieved was compared with cloud top height from MODIS. Results show that the brightness temperature spectra simulated were basically consistent with AIRS observation under the condition of retrieval in the 650~1150 cm-1 band. It means that CART can be used to simulate AIRS brightness temperature spectra. The retrieved cirrus parameters are consistent with brightness temperature of AIRS for channel 11. 1 µm with low brightness temperature corresponding to large cirrus optical thickness and high cloud top height. And the retrieved cirrus parameters are consistent with cirrus reflectance of MODIS cloud product with high cirrus reflectance corresponding to large cirrus optical thickness and high cloud top height. Correlation coefficient of brightness temperature between retrieved cloud top height and MODIS cloud top height was relatively high. They are mostly located in the range of 8. 5~11.5 km, and their probability distribution trend is approximately identical. CART model is feasible to retrieve cirrus properties, and the retrieval is reliable.

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.

Examining the Impact of Overlying Aerosols on the Retrieval of Cloud Optical Properties from Passive Remote Sensing

NASA Technical Reports Server (NTRS)

Coddington, O. M.; Pilewskie, P.; Redemann, J.; Platnick, S.; Russell, P. B.; Schmidt, K. S.; Gore, W. J.; Livingston, J.; Wind, G.; Vukicevic, T.

2010-01-01

Haywood et al. (2004) show that an aerosol layer above a cloud can cause a bias in the retrieved cloud optical thickness and effective radius. Monitoring for this potential bias is difficult because space ]based passive remote sensing cannot unambiguously detect or characterize aerosol above cloud. We show that cloud retrievals from aircraft measurements above cloud and below an overlying aerosol layer are a means to test this bias. The data were collected during the Intercontinental Chemical Transport Experiment (INTEX-A) study based out of Portsmouth, New Hampshire, United States, above extensive, marine stratus cloud banks affected by industrial outflow. Solar Spectral Flux Radiometer (SSFR) irradiance measurements taken along a lower level flight leg above cloud and below aerosol were unaffected by the overlying aerosol. Along upper level flight legs, the irradiance reflected from cloud top was transmitted through an aerosol layer. We compare SSFR cloud retrievals from below ]aerosol legs to satellite retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) in order to detect an aerosol ]induced bias. In regions of small variation in cloud properties, we find that SSFR and MODIS-retrieved cloud optical thickness compares within the uncertainty range for each instrument while SSFR effective radius tend to be smaller than MODIS values (by 1-2 microns) and at the low end of MODIS uncertainty estimates. In regions of large variation in cloud properties, differences in SSFR and MODIS ]retrieved cloud optical thickness and effective radius can reach values of 10 and 10 microns, respectively. We include aerosols in forward modeling to test the sensitivity of SSFR cloud retrievals to overlying aerosol layers. We find an overlying absorbing aerosol layer biases SSFR cloud retrievals to smaller effective radii and optical thickness while nonabsorbing aerosols had no impact.

How Often and Why MODIS Cloud Property Retrievals Fail for Liquid-Phase Clouds over Ocean? a Comprehensive Analysis Based on a-Train Observations

NASA Astrophysics Data System (ADS)

Zhang, Z.; Cho, H. M.; Platnick, S. E.; Meyer, K.; Lebsock, M. D.

2014-12-01

The cloud optical thickness (τ) and droplet effective radius (re) are two key cloud parameters retrieved by MODIS (Moderate Resolution Imaging Spectroradiometer). These MODIS cloud products are widely used in a broad range of earth system science applications. In this paper, we present a comprehensive analysis of the failed cloud τ and/or re retrievals for liquid-phase clouds over ocean in the Collection 6 MODIS cloud product. The main findings from this study are summarized as follows: MODIS retrieval failure rates for marine boundary layer (MBL) clouds have a strong dependence on the spectral combination used for retrieval (e.g., 0.86 + 2.1 µm vs. 0.8 + 3.7 µm) and the cloud morphology (i.e., "good" pixels vs. partly cloudy (PCL) pixels). Combining all clear-sky-restoral (CSR) categories (CSR=0,1 and 3), the 0.86 + 2.1 µm and 0.86 + 3.7 µm spectral combinations have an overall failure rate of about 20% and 12%, respectively (See figure below). The PCL pixels (CSR=1 & 3) have significantly higher failure rates and contribute more to the total failure population than the "good" (CSR=0) pixels. The majority of the failed retrievals are caused by the re too large failure, which explains about 85% and 70% of the failed 0.86 + 2.1 µm and 0.86 + 3.7 µm retrievals, respectively. The remaining failures are either due to the re too small failure or τ retrieval failure. The geographical distribution of failure rates has a significant dependence on cloud regime, lower over the coastal stratocumulus cloud regime and higher over the broken trade-wind cumulus cloud regime over open oceans. Enhanced retrieval failure rates are found when MBL clouds have high sub-pixel inhomogeneity , or are located at special Sun-satellite viewing geometries, such as sunglint, large viewing or solar zenith angle, or cloudbow and glory angles, or subject to cloud masking, cloud overlapping and/or cloud phase retrieval issues. About 80% of the failure retrievals can be attributed to at least one or more potential reasons mentioned above. Collocated radar reflectivity observations from CloudSat suggest that the remaining 20% are unlikely to be retrieval artifacts, but reflection of true cloud microphysics, i.e., the true is either truly very small or very large.

How do A-train Sensors Inter-Compare in the Retrieval of Above-Cloud Aerosol Optical Depth? A Case Study based Assessment

NASA Astrophysics Data System (ADS)

Jethva, H. T.; Torres, O.; Waquet, F.; Chand, D.

2013-12-01

Atmospheric aerosols are known to produce a net cooling effect in the cloud-free conditions. However, when present over the reflective cloud decks, absorbing aerosols such as biomass burning generated smoke and wind-blown dust can potentially exert a large positive forcing through enhanced atmospheric heating resulting from cloud-aerosol radiative interactions. The interest on this aspect of aerosol science has grown significantly in the recent years. Particularly, development of the satellite-based retrieval techniques and unprecedented knowledge on the above-cloud aerosol optical depth (ACAOD) is of great relevance. A direct validation of satellite ACAOD is a difficult task primarily due to lack of ample in situ and/or remote sensing measurements of aerosols above cloud. In these circumstances, a comparative analysis on the inter-satellite ACAOD retrievals can be performed for the sack of consistency check. Here, we inter-compare the ACAOD of biomass burning plumes observed from different A-train sensors, i.e., MODIS [Jethva et al., 2013], CALIOP [Chand et al., 2008], POLDER [Waquet et al., 2009], and OMI [Torres et al., 2012]. These sensors have been shown to acquire sensitivity and independent capabilities to detect and retrieve aerosol loading above marine stratocumulus clouds--a kind of situation often found over the southeastern Atlantic Ocean during dry burning season. A systematic one-to-one comparison reveals that, in general, all passive sensors and CALIOP-based research methods retrieve comparable ACAOD over homogeneous cloud fields. The high-resolution sensors (MODIS and CALIOP) are able to retrieve aerosols over thin clouds but with larger discrepancies. Given the different types of sensor measurements processed with different algorithms, a reasonable agreement between them is encouraging. A direct validation of satellite-based ACAOD remains an open challenge for which dedicated field measurements over the region of frequent aerosol/cloud overlap are a prime requirement. Jethva, H., O. Torres, L. A. Remer, P. K. Bhartia (2013), A Color Ratio Method for Simultaneous Retrieval of Aerosol and Cloud Optical Thickness of Above-Cloud Absorbing Aerosols From Passive Sensors: Application to MODIS Measurements, Geoscience and Remote Sensing, IEEE Transactions on, 51(7), pp. 3862-3870, doi: 10.1109/TGRS.2012.2230008. Chand, D., T. L. Anderson, R. Wood, R. J. Charlson, Y. Hu, Z. Liu, and M. Vaughan (2008), Quantifying above-cloud aerosol using spaceborne lidar for improved understanding of cloudy-sky direct climate forcing, J. Geophys. Res., 113, D13206, doi:10.1029/2007JD009433. Waquet, F., J. Riedi, L. C. Labonnote, P. Goloub, B. Cairns, J.-L. Deuzeand, and D. Tanre (2009), Aerosol remote sensing over clouds using a-train observations, J. Atmos. Sci., 66(8), 2468-2480, doi: http://dx.doi.org/10.1175/2009JAS3026.1 Torres, O., H. Jethva, and P. K. Bhartia (2012), Retrieval of aerosol optical depth above clouds from OMI observations: Sensitivity analysis and case studies, J. Atmos. Sci., 69(3), 1037-1053, doi: http://dx.doi.org/10.1175/JAS-D-11-0130.

Evaluation of the OMI Cloud Pressures Derived from Rotational Raman Scattering by Comparisons with other Satellite Data and Radiative Transfer Simulations

NASA Technical Reports Server (NTRS)

Vasilkov, Alexander; Joiner, Joanna; Spurr, Robert; Bhartia, Pawan K.; Levelt, Pieternel; Stephens, Graeme

2009-01-01

In this paper we examine differences between cloud pressures retrieved from the Ozone Monitoring Instrument (OMI) using the ultraviolet rotational Raman scattering (RRS) algorithm and those from the thermal infrared (IR) Aqua/MODIS. Several cloud data sets are currently being used in OMI trace gas retrieval algorithms including climatologies based on IR measurements and simultaneous cloud parameters derived from OMI. From a validation perspective, it is important to understand the OMI retrieved cloud parameters and how they differ with those derived from the IR. To this end, we perform radiative transfer calculations to simulate the effects of different geophysical conditions on the OMI RRS cloud pressure retrievals. We also quantify errors related to the use of the Mixed Lambert-Equivalent Reflectivity (MLER) concept as currently implemented of the OMI algorithms. Using properties from the Cloudsat radar and MODIS, we show that radiative transfer calculations support the following: (1) The MLER model is adequate for single-layer optically thick, geometrically thin clouds, but can produce significant errors in estimated cloud pressure for optically thin clouds. (2) In a two-layer cloud, the RRS algorithm may retrieve a cloud pressure that is either between the two cloud decks or even beneath the top of the lower cloud deck because of scattering between the cloud layers; the retrieved pressure depends upon the viewing geometry and the optical depth of the upper cloud deck. (3) Absorbing aerosol in and above a cloud can produce significant errors in the retrieved cloud pressure. (4) The retrieved RRS effective pressure for a deep convective cloud will be significantly higher than the physical cloud top pressure derived with thermal IR.

A Comparison of High Spectral Resolution Infrared Cloud-Top Pressure Altitude Algorithms Using S-HIS Measurements

NASA Technical Reports Server (NTRS)

Holz, Robert E.; Ackerman, Steve; Antonelli, Paolo; Nagle, Fred; McGill, Matthew; Hlavka, Dennis L.; Hart, William D.

2005-01-01

This paper presents a comparison of cloud-top altitude retrieval methods applied to S-HIS (Scanning High Resolution Interferometer Sounder) measurements. Included in this comparison is an improvement to the traditional CO2 Slicing method. The new method, CO2 Sorting, determines optimal channel pairs to apply the CO2 Slicing. Measurements from collocated samples of the Cloud Physics Lidar (CPL) and Modis Airborne Simulator (MAS) instruments assist in the comparison. For optically thick clouds good correlation between the S-HIS and lidar cloud-top retrievals are found. For tenuous ice clouds there can be large differences between lidar (CPL) and S-HIS retrieved cloud-tops. It is found that CO2 Sorting significantly reduces the cloud height biases for the optically thin cloud (total optical depths less then 1.0). For geometrically thick but optically thin cirrus clouds large differences between the S-HIS infrared cloud top retrievals and the CPL detected cloud top where found. For these cases the cloud height retrieved by the S-HIS cloud retrievals correlated closely with the level the CPL integrated cloud optical depth was approximately 1.0.

Analyse du potentiel de la radiometrie infrarouge thermique pour la caracterisation des nuages de glace en Arctique

NASA Astrophysics Data System (ADS)

Blanchard, Yann

An important goal, within the context of improving climate change modelling, is to enhance our understanding of aerosols and their radiative effects (notably their indirect impact as cloud condensation nuclei). The cloud optical depth (COD) and average ice particle size of thin ice clouds (TICs) are two key parameters whose variations could strongly influence radiative effects and climate in the Arctic environment. Our objective was to assess the potential of using multi-band thermal radiance measurements of zenith sky radiance for retrieving COD and effective particle diameter (Deff) of TICs in the Arctic. We analyzed and quantified the sensitivity of thermal radiance on many parameters, such as COD, Deff, water vapor content, cloud bottom altitude and thickness, size distribution and shape. Using the sensitivity of IRT to COD and Deff, the developed retrieval technique is validated in comparison with retrievals from LIDAR and RADAR. Retrievals were applied to ground-based thermal infrared data acquired for 100 TICs at the high-Arctic PEARL observatory in Eureka, Nunavut, Canada and were validated using AHSRL LIDAR and MMCR RADAR data. The results of the retrieval method were used to successfully extract COD up to values of 3 and to separate TICs into two types : TIC1 characterized by small crystals (Deff < 30 mum) and TIC2 by large ice crystals (Deff > 30 mum, up to 300 mum). Inversions were performed across two polar winters. At the end of this research, we proposed different alternatives to apply our methodology in the Arctic. Keywords : Remote sensing ; ice clouds ; thermal infrared multi-band radiometry ; Arctic.

Impact of varying lidar measurement and data processing techniques in evaluating cirrus cloud and aerosol direct radiative effects

NASA Astrophysics Data System (ADS)

Lolli, Simone; Madonna, Fabio; Rosoldi, Marco; Campbell, James R.; Welton, Ellsworth J.; Lewis, Jasper R.; Gu, Yu; Pappalardo, Gelsomina

2018-03-01

In the past 2 decades, ground-based lidar networks have drastically increased in scope and relevance, thanks primarily to the advent of lidar observations from space and their need for validation. Lidar observations of aerosol and cloud geometrical, optical and microphysical atmospheric properties are subsequently used to evaluate their direct radiative effects on climate. However, the retrievals are strongly dependent on the lidar instrument measurement technique and subsequent data processing methodologies. In this paper, we evaluate the discrepancies between the use of Raman and elastic lidar measurement techniques and corresponding data processing methods for two aerosol layers in the free troposphere and for two cirrus clouds with different optical depths. Results show that the different lidar techniques are responsible for discrepancies in the model-derived direct radiative effects for biomass burning (0.05 W m-2 at surface and 0.007 W m-2 at top of the atmosphere) and dust aerosol layers (0.7 W m-2 at surface and 0.85 W m-2 at top of the atmosphere). Data processing is further responsible for discrepancies in both thin (0.55 W m-2 at surface and 2.7 W m-2 at top of the atmosphere) and opaque (7.7 W m-2 at surface and 11.8 W m-2 at top of the atmosphere) cirrus clouds. Direct radiative effect discrepancies can be attributed to the larger variability of the lidar ratio for aerosols (20-150 sr) than for clouds (20-35 sr). For this reason, the influence of the applied lidar technique plays a more fundamental role in aerosol monitoring because the lidar ratio must be retrieved with relatively high accuracy. In contrast, for cirrus clouds, with the lidar ratio being much less variable, the data processing is critical because smoothing it modifies the aerosol and cloud vertically resolved extinction profile that is used as input to compute direct radiative effect calculations.

The Community Cloud retrieval for CLimate (CC4CL) - Part 2: The optimal estimation approach

NASA Astrophysics Data System (ADS)

McGarragh, Gregory R.; Poulsen, Caroline A.; Thomas, Gareth E.; Povey, Adam C.; Sus, Oliver; Stapelberg, Stefan; Schlundt, Cornelia; Proud, Simon; Christensen, Matthew W.; Stengel, Martin; Hollmann, Rainer; Grainger, Roy G.

2018-06-01

The Community Cloud retrieval for Climate (CC4CL) is a cloud property retrieval system for satellite-based multispectral imagers and is an important component of the Cloud Climate Change Initiative (Cloud_cci) project. In this paper we discuss the optimal estimation retrieval of cloud optical thickness, effective radius and cloud top pressure based on the Optimal Retrieval of Aerosol and Cloud (ORAC) algorithm. Key to this method is the forward model, which includes the clear-sky model, the liquid water and ice cloud models, the surface model including a bidirectional reflectance distribution function (BRDF), and the "fast" radiative transfer solution (which includes a multiple scattering treatment). All of these components and their assumptions and limitations will be discussed in detail. The forward model provides the accuracy appropriate for our retrieval method. The errors are comparable to the instrument noise for cloud optical thicknesses greater than 10. At optical thicknesses less than 10 modeling errors become more significant. The retrieval method is then presented describing optimal estimation in general, the nonlinear inversion method employed, measurement and a priori inputs, the propagation of input uncertainties and the calculation of subsidiary quantities that are derived from the retrieval results. An evaluation of the retrieval was performed using measurements simulated with noise levels appropriate for the MODIS instrument. Results show errors less than 10 % for cloud optical thicknesses greater than 10. Results for clouds of optical thicknesses less than 10 have errors up to 20 %.

Cloud Property Retrieval Products for Graciosa Island, Azores

DOE Data Explorer

Dong, Xiquan

2014-05-05

The motivation for developing this product was to use the Dong et al. 1998 method to retrieve cloud microphysical properties, such as cloud droplet effective radius, cloud droplets number concentration, and optical thickness. These retrieved properties have been used to validate the satellite retrieval, and evaluate the climate simulations and reanalyses. We had been using this method to retrieve cloud microphysical properties over ARM SGP and NSA sites. We also modified the method for the AMF at Shouxian, China and some IOPs, e.g. ARM IOP at SGP in March, 2000. The ARSCL data from ARM data archive over the SGP and NSA have been used to determine the cloud boundary and cloud phase. For these ARM permanent sites, the ARSCL data was developed based on MMCR measurements, however, there were no data available at the Azores field campaign. We followed the steps to generate this derived product and also include the MPLCMASK cloud retrievals to determine the most accurate cloud boundaries, including the thin cirrus clouds that WACR may under-detect. We use these as input to retrieve the cloud microphysical properties. Due to the different temporal resolutions of the derived cloud boundary heights product and the cloud properties product, we submit them as two separate netcdf files.

Frequency and causes of failed MODIS cloud property retrievals for liquid phase clouds over global oceans.

PubMed

Cho, Hyoun-Myoung; Zhang, Zhibo; Meyer, Kerry; Lebsock, Matthew; Platnick, Steven; Ackerman, Andrew S; Di Girolamo, Larry; C-Labonnote, Laurent; Cornet, Céline; Riedi, Jerome; Holz, Robert E

2015-05-16

Moderate Resolution Imaging Spectroradiometer (MODIS) retrieves cloud droplet effective radius ( r e ) and optical thickness ( τ ) by projecting observed cloud reflectances onto a precomputed look-up table (LUT). When observations fall outside of the LUT, the retrieval is considered "failed" because no combination of τ and r e within the LUT can explain the observed cloud reflectances. In this study, the frequency and potential causes of failed MODIS retrievals for marine liquid phase (MLP) clouds are analyzed based on 1 year of Aqua MODIS Collection 6 products and collocated CALIOP and CloudSat observations. The retrieval based on the 0.86 µm and 2.1 µm MODIS channel combination has an overall failure rate of about 16% (10% for the 0.86 µm and 3.7 µm combination). The failure rates are lower over stratocumulus regimes and higher over the broken trade wind cumulus regimes. The leading type of failure is the " r e too large" failure accounting for 60%-85% of all failed retrievals. The rest is mostly due to the " r e too small" or τ retrieval failures. Enhanced retrieval failure rates are found when MLP cloud pixels are partially cloudy or have high subpixel inhomogeneity, are located at special Sun-satellite viewing geometries such as sunglint, large viewing or solar zenith angles, or cloudbow and glory angles, or are subject to cloud masking, cloud overlapping, and/or cloud phase retrieval issues. The majority (more than 84%) of failed retrievals along the CALIPSO track can be attributed to at least one or more of these potential reasons. The collocated CloudSat radar reflectivity observations reveal that the remaining failed retrievals are often precipitating. It remains an open question whether the extremely large r e values observed in these clouds are the consequence of true cloud microphysics or still due to artifacts not included in this study.

Frequency and causes of failed MODIS cloud property retrievals for liquid phase clouds over global oceans

PubMed Central

Cho, Hyoun‐Myoung; Meyer, Kerry; Lebsock, Matthew; Platnick, Steven; Ackerman, Andrew S.; Di Girolamo, Larry; C.‐Labonnote, Laurent; Cornet, Céline; Riedi, Jerome; Holz, Robert E.

2015-01-01

Abstract Moderate Resolution Imaging Spectroradiometer (MODIS) retrieves cloud droplet effective radius (r e) and optical thickness (τ) by projecting observed cloud reflectances onto a precomputed look‐up table (LUT). When observations fall outside of the LUT, the retrieval is considered “failed” because no combination of τ and r e within the LUT can explain the observed cloud reflectances. In this study, the frequency and potential causes of failed MODIS retrievals for marine liquid phase (MLP) clouds are analyzed based on 1 year of Aqua MODIS Collection 6 products and collocated CALIOP and CloudSat observations. The retrieval based on the 0.86 µm and 2.1 µm MODIS channel combination has an overall failure rate of about 16% (10% for the 0.86 µm and 3.7 µm combination). The failure rates are lower over stratocumulus regimes and higher over the broken trade wind cumulus regimes. The leading type of failure is the “r e too large” failure accounting for 60%–85% of all failed retrievals. The rest is mostly due to the “r e too small” or τ retrieval failures. Enhanced retrieval failure rates are found when MLP cloud pixels are partially cloudy or have high subpixel inhomogeneity, are located at special Sun‐satellite viewing geometries such as sunglint, large viewing or solar zenith angles, or cloudbow and glory angles, or are subject to cloud masking, cloud overlapping, and/or cloud phase retrieval issues. The majority (more than 84%) of failed retrievals along the CALIPSO track can be attributed to at least one or more of these potential reasons. The collocated CloudSat radar reflectivity observations reveal that the remaining failed retrievals are often precipitating. It remains an open question whether the extremely large r e values observed in these clouds are the consequence of true cloud microphysics or still due to artifacts not included in this study. PMID:27656330

Consistency of aerosols above clouds characterization from A-Train active and passive measurements

NASA Astrophysics Data System (ADS)

Deaconu, Lucia T.; Waquet, Fabien; Josset, Damien; Ferlay, Nicolas; Peers, Fanny; Thieuleux, François; Ducos, Fabrice; Pascal, Nicolas; Tanré, Didier; Pelon, Jacques; Goloub, Philippe

2017-09-01

This study presents a comparison between the retrieval of optical properties of aerosol above clouds (AAC) from different techniques developed for the A-Train sensors CALIOP/CALIPSO and POLDER/PARASOL. The main objective is to analyse the consistency between the results derived from the active and the passive measurements. We compare the aerosol optical thickness (AOT) above optically thick clouds (cloud optical thickness (COT) larger than 3) and their Ångström exponent (AE). These parameters are retrieved with the CALIOP operational method, the POLDER operational polarization method and the CALIOP-based depolarization ratio method (DRM) - for which we also propose a calibrated version (denominated DRMSODA, where SODA is the Synergized Optical Depth of Aerosols). We analyse 6 months of data over three distinctive regions characterized by different types of aerosols and clouds. Additionally, for these regions, we select three case studies: a biomass-burning event over the South Atlantic Ocean, a Saharan dust case over the North Atlantic Ocean and a Siberian biomass-burning event over the North Pacific Ocean. Four and a half years of data are studied over the entire globe for distinct situations where aerosol and cloud layers are in contact or vertically separated. Overall, the regional analysis shows a good correlation between the POLDER and the DRMSODA AOTs when the microphysics of aerosols is dominated by fine-mode particles of biomass-burning aerosols from southern Africa (correlation coefficient (R2) of 0.83) or coarse-mode aerosols of Saharan dust (R2 of 0.82). A good correlation between these methods (R2 of 0.68) is also observed in the global treatment, when the aerosol and cloud layers are separated well. The analysis of detached layers also shows a mean difference in AOT of 0.07 at 532 nm between POLDER and DRMSODA at a global scale. The correlation between the retrievals decreases when a complex mixture of aerosols is expected (R2 of 0.37) - as in the East Asia region - and when the aerosol-cloud layers are in contact (R2 of 0.36). The correlation coefficient between the CALIOP operational method and POLDER is found to be low, as the CALIOP method largely underestimates the aerosol loading above clouds by a factor that ranges from 2 to 4. Potential biases on the retrieved AOT as a function of cloud properties are also investigated. For different types of scenes, the retrieval of above-cloud AOT from POLDER and from DRM are compared for different underlying cloud properties (droplet effective radius (reff) and COT retrieved with MODIS). The results reveal that DRM AOT vary with reff. When accounting for reff in the DRM algorithm, the consistency between the methods increases. The sensitivity study shows that an additional polarized signal coming from aerosols located within the cloud could affect the polarization method, which leads to an overestimation of the AOT retrieved with POLDER algorithm. In addition, the aerosols attached to or within the cloud can potentially impact the DRM retrievals through the modification of the cloud droplet chemical composition and its ability to backscatter light. The next step of this work is to combine POLDER and CALIOP to investigate the impacts of aerosols on clouds and climate when these particles are transported above or within clouds.

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.

Statistics Analysis of the Uncertainties in Cloud Optical Depth Retrievals Caused by Three-Dimensional Radiative Effects

NASA Technical Reports Server (NTRS)

Varnai, Tamas; Marshak, Alexander

2000-01-01

This paper presents a simple approach to estimate the uncertainties that arise in satellite retrievals of cloud optical depth when the retrievals use one-dimensional radiative transfer theory for heterogeneous clouds that have variations in all three dimensions. For the first time, preliminary error bounds are set to estimate the uncertainty of cloud optical depth retrievals. These estimates can help us better understand the nature of uncertainties that three-dimensional effects can introduce into retrievals of this important product of the MODIS instrument. The probability distribution of resulting retrieval errors is examined through theoretical simulations of shortwave cloud reflection for a wide variety of cloud fields. The results are used to illustrate how retrieval uncertainties change with observable and known parameters, such as solar elevation or cloud brightness. Furthermore, the results indicate that a tendency observed in an earlier study, clouds appearing thicker for oblique sun, is indeed caused by three-dimensional radiative effects.

A multi-sensor approach to the retrieval and model validation of global cloudiness

NASA Astrophysics Data System (ADS)

Miller, Steven D.

2000-11-01

The ephemeral clouds have represented a daunting challenge to the atmospheric modeling community from the very beginning. Our inability to resolve them by means of traditional passive sensors to the level of detail required for characterizing their complicated role in the climate feedback system has lead us to explore other resources at our disposal. This research seeks to illustrate and, where applicable, quantify the ways in which active (e.g., radar and lidar) remote sensing devices on existing and proposed platforms can serve to improve our current understanding of cloud and cloud processes in terms of (1)their role in the improvement of cloud property retrievals and (2)their application to the validation/development of clouds in numerical weather prediction models. A new retrieval technique which employs active sensors to constrain cloud boundaries in the vertical is shown to decrease the parameter uncertainties with respect to traditional passive methods in excess of 20% for effective particle radius, and 10-20% for optical depth when considering night-time retrievals of cirrus. These results are brought together with detailed cloud profile sampling from the Lidar In-space Technology Experiment (LITE) to conduct the first global-scale active sensor validation of ECMWF short-range forecasts. The comparisons display remarkable agreement in cloud spatial distribution. A weighted statistical analysis yields hit rates between 75-90%, threat scores 45-75%, probabilities of detection ~80%, and false alarm rates 10-45%. The results suggest that, given the level of realism displayed currently by the ECMWF prognostic cloud scheme forecasts, the reanalysis data may be considered as a new resource for global cloud information. A practical application of these findings has been outlined in the context of defining Cloud-Sat instrument requirements based on virtual orbital observations created from ECMWF global cloud distributions of liquid and ice water contents. This research gives cause for new hope in capturing the complex radiative, convective, and dynamical feedback mechanisms associated with clouds in the climate feedback system. Further, it appeals to the need for an improved collaborative rapport between the now largely disjoint modeling and measurement communities.

Statistical retrieval of thin liquid cloud microphysical properties using ground-based infrared and microwave observations

NASA Astrophysics Data System (ADS)

Marke, Tobias; Ebell, Kerstin; Löhnert, Ulrich; Turner, David D.

2016-12-01

In this article, liquid water cloud microphysical properties are retrieved by a combination of microwave and infrared ground-based observations. Clouds containing liquid water are frequently occurring in most climate regimes and play a significant role in terms of interaction with radiation. Small perturbations in the amount of liquid water contained in the cloud can cause large variations in the radiative fluxes. This effect is enhanced for thin clouds (liquid water path, LWP <100 g/m2), which makes accurate retrieval information of the cloud properties crucial. Due to large relative errors in retrieving low LWP values from observations in the microwave domain and a high sensitivity for infrared methods when the LWP is low, a synergistic retrieval based on a neural network approach is built to estimate both LWP and cloud effective radius (reff). These statistical retrievals can be applied without high computational demand but imply constraints like prior information on cloud phase and cloud layering. The neural network retrievals are able to retrieve LWP and reff for thin clouds with a mean relative error of 9% and 17%, respectively. This is demonstrated using synthetic observations of a microwave radiometer (MWR) and a spectrally highly resolved infrared interferometer. The accuracy and robustness of the synergistic retrievals is confirmed by a low bias in a radiative closure study for the downwelling shortwave flux, even for marginally invalid scenes. Also, broadband infrared radiance observations, in combination with the MWR, have the potential to retrieve LWP with a higher accuracy than a MWR-only retrieval.

Retrieval of atmospheric properties of cloudy L dwarfs

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

Burningham, Ben; Marley, Mark S.; Line, Michael R.

Here, we present the first results from applying the spectral inversion technique in the cloudy L dwarf regime. This new framework provides a flexible approach to modelling cloud opacity which can be built incrementally as the data require and improves upon previous retrieval experiments in the brown dwarf regime by allowing for scattering in two-stream radiative transfer. Our first application of the tool to two mid-L dwarfs is able to reproduce their near-infrared spectra far more closely than grid models. Our retrieved thermal, chemical and cloud profiles allow us to estimate Teff = 1796more » $$+23\\atop{-25}$$ K and logg = 5.21$$+0.05\\atop{-0.08}$$ for 2MASS J05002100+0330501, and for 2MASSW J2224438-015852 we find Teff = 1723 $$+18\\atop{-19}$$ K and log g = 5.31 $$+0.04\\atop{-0.08}$$, in close agreement with previous empirical estimates. Our best model for both objects includes an optically thick cloud deck which passes τcloud ≥ 1 (looking down) at a pressure of around 5 bar. The temperature at this pressure is too high for silicate species to condense, and we argue that corundum and/or iron clouds are responsible for this cloud opacity. Our retrieved profiles are cooler at depth and warmer at altitude than the forward grid models that we compare, and we argue that some form of heating mechanism may be at work in the upper atmospheres of these L dwarfs. We also identify anomalously high CO abundance in both targets, which does not correlate with the warmth of our upper atmospheres or our choice of cloud model, and find similarly anomalous alkali abundance for one of our targets. For these anomalies they may reflect unrecognized shortcomings in our retrieval model or inaccuracies in our gas phase opacities.« less

Retrieval of atmospheric properties of cloudy L dwarfs

DOE PAGES

Burningham, Ben; Marley, Mark S.; Line, Michael R.; ...

2017-05-20

Here, we present the first results from applying the spectral inversion technique in the cloudy L dwarf regime. This new framework provides a flexible approach to modelling cloud opacity which can be built incrementally as the data require and improves upon previous retrieval experiments in the brown dwarf regime by allowing for scattering in two-stream radiative transfer. Our first application of the tool to two mid-L dwarfs is able to reproduce their near-infrared spectra far more closely than grid models. Our retrieved thermal, chemical and cloud profiles allow us to estimate Teff = 1796more » $$+23\\atop{-25}$$ K and logg = 5.21$$+0.05\\atop{-0.08}$$ for 2MASS J05002100+0330501, and for 2MASSW J2224438-015852 we find Teff = 1723 $$+18\\atop{-19}$$ K and log g = 5.31 $$+0.04\\atop{-0.08}$$, in close agreement with previous empirical estimates. Our best model for both objects includes an optically thick cloud deck which passes τcloud ≥ 1 (looking down) at a pressure of around 5 bar. The temperature at this pressure is too high for silicate species to condense, and we argue that corundum and/or iron clouds are responsible for this cloud opacity. Our retrieved profiles are cooler at depth and warmer at altitude than the forward grid models that we compare, and we argue that some form of heating mechanism may be at work in the upper atmospheres of these L dwarfs. We also identify anomalously high CO abundance in both targets, which does not correlate with the warmth of our upper atmospheres or our choice of cloud model, and find similarly anomalous alkali abundance for one of our targets. For these anomalies they may reflect unrecognized shortcomings in our retrieval model or inaccuracies in our gas phase opacities.« less

Infrared Retrievals of Ice Cloud Properties and Uncertainties with an Optimal Estimation Retrieval Method

NASA Astrophysics Data System (ADS)

Wang, C.; Platnick, S. E.; Meyer, K.; Zhang, Z.

2014-12-01

We developed an optimal estimation (OE)-based method using infrared (IR) observations to retrieve ice cloud optical thickness (COT), cloud effective radius (CER), and cloud top height (CTH) simultaneously. The OE-based retrieval is coupled with a fast IR radiative transfer model (RTM) that simulates observations of different sensors, and corresponding Jacobians in cloudy atmospheres. Ice cloud optical properties are calculated using the MODIS Collection 6 (C6) ice crystal habit (severely roughened hexagonal column aggregates). The OE-based method can be applied to various IR space-borne and airborne sensors, such as the Moderate Resolution Imaging Spectroradiometer (MODIS) and the enhanced MODIS Airborne Simulator (eMAS), by optimally selecting IR bands with high information content. Four major error sources (i.e., the measurement error, fast RTM error, model input error, and pre-assumed ice crystal habit error) are taken into account in our OE retrieval method. We show that measurement error and fast RTM error have little impact on cloud retrievals, whereas errors from the model input and pre-assumed ice crystal habit significantly increase retrieval uncertainties when the cloud is optically thin. Comparisons between the OE-retrieved ice cloud properties and other operational cloud products (e.g., the MODIS C6 and CALIOP cloud products) are shown.

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.

Towards a true aerosol-and-cloud retrieval scheme

NASA Astrophysics Data System (ADS)

Thomas, Gareth; Poulsen, Caroline; Povey, Adam; McGarragh, Greg; Jerg, Matthias; Siddans, Richard; Grainger, Don

2014-05-01

The Optimal Retrieval of Aerosol and Cloud (ORAC) - formally the Oxford-RAL Aerosol and Cloud retrieval - offers a framework that can provide consistent and well characterised properties of both aerosols and clouds from a range of imaging satellite instruments. Several practical issues stand in the way of achieving the potential of this combined scheme however; in particular the sometimes conflicting priorities and requirements of aerosol and cloud retrieval problems, and the question of the unambiguous identification of aerosol and cloud pixels. This presentation will present recent developments made to the ORAC scheme for both aerosol and cloud, and detail how these are being integrated into a single retrieval framework. The implementation of a probabilistic method for pixel identification will also be presented, for both cloud detection and aerosol/cloud type selection. The method is based on Bayesian methods applied the optimal estimation retrieval output of ORAC and is particularly aimed at providing additional information in the so-called "twilight zone", where pixels can't be unambiguously identified as either aerosol or cloud and traditional cloud or aerosol products do not provide results.

Airborne Polarimeter Intercomparison for the NASA Aerosols-Clouds-Ecosystems (ACE) Mission

NASA Technical Reports Server (NTRS)

Knobelspiesse, Kirk; Redemann, Jens

2014-01-01

The Aerosols-Clouds-Ecosystems (ACE) mission, recommended by the National Research Council's Decadal Survey, calls for a multi-angle, multi-spectral polarimeter devoted to observations of atmospheric aerosols and clouds. In preparation for ACE, NASA funds the deployment of airborne polarimeters, including the Airborne Multi-angle SpectroPolarimeter Imager (AirMSPI), the Passive Aerosol and Cloud Suite (PACS) and the Research Scanning Polarimeter (RSP). These instruments have been operated together on NASA's ER-2 high altitude aircraft as part of field campaigns such as the POlarimeter DEfinition EXperiment (PODEX) (California, early 2013) and Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS, California and Texas, summer 2013). Our role in these efforts has been to serve as an assessment team performing level 1 (calibrated radiance, polarization) and level 2 (retrieved geophysical parameter) instrument intercomparisons, and to promote unified and generalized calibration, uncertainty assessment and retrieval techniques. We will present our progress in this endeavor thus far and describe upcoming research in 2015.

Progress in Airborne Polarimeter Inter Comparison for the NASA Aerosols-Clouds-Ecosystems (ACE) Mission

NASA Technical Reports Server (NTRS)

Knobelspiesse, Kirk; Redemann, Jens

2014-01-01

The Aerosols-Clouds-Ecosystems (ACE) mission, recommended by the National Research Council's Decadal Survey, calls for a multi-angle, multi-spectral polarimeter devoted to observations of atmospheric aerosols and clouds. In preparation for ACE, NASA funds the deployment of airborne polarimeters, including the Airborne Multiangle SpectroPolarimeter Imager (AirMSPI), the Passive Aerosol and Cloud Suite (PACS) and the Research Scanning Polarimeter (RSP). These instruments have been operated together on NASA's ER-2 high altitude aircraft as part of field campaigns such as the POlarimeter DEfinition EXperiment (PODEX) (California, early 2013) and Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS, California and Texas, summer 2013). Our role in these efforts has been to serve as an assessment team performing level 1 (calibrated radiance, polarization) and level 2 (retrieved geophysical parameter) instrument intercomparisons, and to promote unified and generalized calibration, uncertainty assessment and retrieval techniques. We will present our progress in this endeavor thus far and describe upcoming research in 2015.

Observations of Three-Dimensional Radiative Effects that Influence Satellite Retrievals of Cloud Properties

NASA Technical Reports Server (NTRS)

Varnai, Tamas; Marshak, Alexander; Lau, William K. M. (Technical Monitor)

2001-01-01

This paper examines three-dimensional (3D) radiative effects, which arise from horizontal radiative interactions between areas that have different cloud properties. Earlier studies have argued that these effects can cause significant uncertainties in current satellite retrievals of cloud properties, because the retrievals rely on one-dimensional (1D) theory and do not consider the effects of horizontal changes in cloud properties. This study addresses two questions: which retrieved cloud properties are influenced by 3D radiative effects, and where 3D effects tend to occur? The influence of 3D effects is detected from the wayside illumination and shadowing make clouds appear asymmetric: Areas appear brighter if the cloud top surface is tilted toward, rather than away from, the Sun. The analysis of 30 images by the Moderate Resolution Imaging Spectroradiometer (MODIS) reveals that retrievals of cloud optical thickness and cloud water content are most influenced by 3D effects, whereas retrievals of cloud particle size are much less affected. The results also indicate that while 3D effects are strongest at cloud edges, cloud top variability in cloud interiors, even in overcast regions, also produces considerable 3D effects. Finally, significant 3D effects are found in a wide variety of situations, ranging from thin clouds to thick ones and from low clouds to high ones.

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

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

An Extension of the Split Window Technique for the Retrieval of Precipitable Water: Experimental Verification

DTIC Science & Technology

1988-09-23

DOWNGRADING SCHEDULE D~istribution Unlimited 4. PERFORMING ORGANIZATiON REPORT NUMVBER(S) 5. MONITORiG ORGANIZATION REPORT NUMBER(S) AFGL-TR-88-0237...Collocations were performed on launch sites of the cloud contamination, aerosol problems, collocation 1200 UT radiosondes on 25 Aug 1987. Statistics were...al (1987) and Thomason, 1987). In this imagery opaque clouds to this problem appear white, low clouds and fog appear bright red against a brown

Trace gas retrieval for limb DOAS under changing atmospheric conditions: The X-gas scaling method vs optimal estimation

NASA Astrophysics Data System (ADS)

Hueneke, Tilman; Grossmann, Katja; Knecht, Matthias; Raecke, Rasmus; Stutz, Jochen; Werner, Bodo; Pfeilsticker, Klaus

2016-04-01

Changing atmospheric conditions during DOAS measurements from fast moving aircraft platforms pose a challenge for trace gas retrievals. Traditional inversion techniques to retrieve trace gas concentrations from limb scattered UV/vis spectroscopy, like optimal estimation, require a-priori information on Mie extinction (e.g., aerosol concentration and cloud cover) and albedo, which determine the atmospheric radiative transfer. In contrast to satellite applications, cloud filters can not be applied because they would strongly reduce the usable amount of expensively gathered measurement data. In contrast to ground-based MAX-DOAS applications, an aerosol retrieval based on O4 is not able to constrain the radiative transfer in air-borne applications due to the rapidly decreasing amount of O4 with altitude. Furthermore, the assumption of a constant cloud cover is not valid for fast moving aircrafts, thus requiring 2D or even 3D treatment of the radiative transfer. Therefore, traditional techniques are not applicable for most of the data gathered by fast moving aircraft platforms. In order to circumvent these limitations, we have been developing the so-called X-gas scaling method. By utilising a proxy gas X (e.g. O3, O4, …), whose concentration is either a priori known or simultaneously in-situ measured as well as remotely measured, an effective absorption length for the target gas is inferred. In this presentation, we discuss the strengths and weaknesses of the novel approach along with some sample cases. A particular strength of the X-gas scaling method is its insensitivity towards the aerosol abundance and cloud cover as well as wavelength dependent effects, whereas its sensitivity towards the profiles of both gases requires a priori information on their shapes.

Different Applications of FORTRACC: From Convective Clouds to thunderstorms and radar fields

NASA Astrophysics Data System (ADS)

Morales, C.; Machado, L. A.

2009-09-01

The algorithm Forecasting and Tracking the Evolution of Cloud Clusters (ForTraCC), Vila et al. (2008), has been employed operationally in Brazil since 2005 to track and forecast the development of convective clouds. This technique depicts the main morphological features of the cloud systems and most importantly it reconstructs its entire life cycle. Based on this information, several relationships that use the area expansion and convective and stratiform fraction are employed to predict the life time duration and cloud area. Because of these features, the civil defense and power companies are using this information to mitigate the damages in the population. Further developments in FORTRACC included the integration of satellite rainfall retrievals, radar fields and thunderstorm initiation. These improvements try to address the following problems: a) most of the satellite rainfall retrievals do not take into account the life cycle stage that it is a key element on defining the rain area and rain intensity; b) by using the life cycle information it is possible to better predict the precipitation pattern observed in the radar fields; c) cloud signatures are associated to the development of systems that have lightning and no lightning activity. During the presentation, an overview of the different applications of FORTRACC will be presented including case studies and evaluation of the technique. Finally, the presentation will address how the users can have access to the algorithm to implement in their institute.

Cloud retrievals from satellite data using optimal estimation: evaluation and application to ATSR

NASA Astrophysics Data System (ADS)

Poulsen, C. A.; Siddans, R.; Thomas, G. E.; Sayer, A. M.; Grainger, R. G.; Campmany, E.; Dean, S. M.; Arnold, C.; Watts, P. D.

2012-08-01

Clouds play an important role in balancing the Earth's radiation budget. Hence, it is vital that cloud climatologies are produced that quantify cloud macro and micro physical parameters and the associated uncertainty. In this paper, we present an algorithm ORAC (Oxford-RAL retrieval of Aerosol and Cloud) which is based on fitting a physically consistent cloud model to satellite observations simultaneously from the visible to the mid-infrared, thereby ensuring that the resulting cloud properties provide both a good representation of the short-wave and long-wave radiative effects of the observed cloud. The advantages of the optimal estimation method are that it enables rigorous error propagation and the inclusion of all measurements and any a priori information and associated errors in a rigorous mathematical framework. The algorithm provides a measure of the consistency between retrieval representation of cloud and satellite radiances. The cloud parameters retrieved are the cloud top pressure, cloud optical depth, cloud effective radius, cloud fraction and cloud phase. The algorithm can be applied to most visible/infrared satellite instruments. In this paper, we demonstrate the applicability to the Along-Track Scanning Radiometers ATSR-2 and AATSR. Examples of applying the algorithm to ATSR-2 flight data are presented and the sensitivity of the retrievals assessed, in particular the algorithm is evaluated for a number of simulated single-layer and multi-layer conditions. The algorithm was found to perform well for single-layer cloud except when the cloud was very thin; i.e., less than 1 optical depths. For the multi-layer cloud, the algorithm was robust except when the upper ice cloud layer is less than five optical depths. In these cases the retrieved cloud top pressure and cloud effective radius become a weighted average of the 2 layers. The sum of optical depth of multi-layer cloud is retrieved well until the cloud becomes thick, greater than 50 optical depths, where the cloud begins to saturate. The cost proved a good indicator of multi-layer scenarios. Both the retrieval cost and the error need to be considered together in order to evaluate the quality of the retrieval. This algorithm in the configuration described here has been applied to both ATSR-2 and AATSR visible and infrared measurements in the context of the GRAPE (Global Retrieval and cloud Product Evaluation) project to produce a 14 yr consistent record for climate research.

Quantifying the Climate-Scale Accuracy of Satellite Cloud Retrievals

NASA Astrophysics Data System (ADS)

Roberts, Y.; Wielicki, B. A.; Sun-Mack, S.; Minnis, P.; Liang, L.; Di Girolamo, L.

2014-12-01

Instrument calibration and cloud retrieval algorithms have been developed to minimize retrieval errors on small scales. However, measurement uncertainties and assumptions within retrieval algorithms at the pixel level may alias into decadal-scale trends of cloud properties. We first, therefore, quantify how instrument calibration changes could alias into cloud property trends. For a perfect observing system the climate trend accuracy is limited only by the natural variability of the climate variable. Alternatively, for an actual observing system, the climate trend accuracy is additionally limited by the measurement uncertainty. Drifts in calibration over time may therefore be disguised as a true climate trend. We impose absolute calibration changes to MODIS spectral reflectance used as input to the CERES Cloud Property Retrieval System (CPRS) and run the modified MODIS reflectance through the CPRS to determine the sensitivity of cloud properties to calibration changes. We then use these changes to determine the impact of instrument calibration changes on trend uncertainty in reflected solar cloud properties. Secondly, we quantify how much cloud retrieval algorithm assumptions alias into cloud optical retrieval trends by starting with the largest of these biases: the plane-parallel assumption in cloud optical thickness (τC) retrievals. First, we collect liquid water cloud fields obtained from Multi-angle Imaging Spectroradiometer (MISR) measurements to construct realistic probability distribution functions (PDFs) of 3D cloud anisotropy (a measure of the degree to which clouds depart from plane-parallel) for different ISCCP cloud types. Next, we will conduct a theoretical study with dynamically simulated cloud fields and a 3D radiative transfer model to determine the relationship between 3D cloud anisotropy and 3D τC bias for each cloud type. Combining these results provides distributions of 3D τC bias by cloud type. Finally, we will estimate the change in frequency of occurrence of cloud types between two decades and will have the information needed to calculate the total change in 3D optical thickness bias between two decades. If we uncover aliases in this study, the results will motivate the development and rigorous testing of climate specific cloud retrieval algorithms.

Sensitivity of Marine Warm Cloud Retrieval Statistics to Algorithm Choices: Examples from MODIS Collection 6

NASA Technical Reports Server (NTRS)

Platnick, Steven; Wind, Galina; Zhang, Zhibo; Ackerman, Steven A.; Maddux, Brent

2012-01-01

The optical and microphysical structure of warm boundary layer marine clouds is of fundamental importance for understanding a variety of cloud radiation and precipitation processes. With the advent of MODIS (Moderate Resolution Imaging Spectroradiometer) on the NASA EOS Terra and Aqua platforms, simultaneous global/daily 1km retrievals of cloud optical thickness and effective particle size are provided, as well as the derived water path. In addition, the cloud product (MOD06/MYD06 for MODIS Terra and Aqua, respectively) provides separate effective radii results using the l.6, 2.1, and 3.7 m spectral channels. Cloud retrieval statistics are highly sensitive to how a pixel identified as being "notclear" by a cloud mask (e.g., the MOD35/MYD35 product) is determined to be useful for an optical retrieval based on a 1-D cloud model. The Collection 5 MODIS retrieval algorithm removed pixels associated with cloud'edges as well as ocean pixels with partly cloudy elements in the 250m MODIS cloud mask - part of the so-called Clear Sky Restoral (CSR) algorithm. Collection 6 attempts retrievals for those two pixel populations, but allows a user to isolate or filter out the populations via CSR pixel-level Quality Assessment (QA) assignments. In this paper, using the preliminary Collection 6 MOD06 product, we present global and regional statistical results of marine warm cloud retrieval sensitivities to the cloud edge and 250m partly cloudy pixel populations. As expected, retrievals for these pixels are generally consistent with a breakdown of the ID cloud model. While optical thickness for these suspect pixel populations may have some utility for radiative studies, the retrievals should be used with extreme caution for process and microphysical studies.

CloudSat-Constrained Cloud Ice Water Path and Cloud Top Height Retrievals from MHS 157 and 183.3 GHz Radiances

NASA Technical Reports Server (NTRS)

Gong, J.; Wu, D. L.

2014-01-01

Ice water path (IWP) and cloud top height (ht) are two of the key variables in determining cloud radiative and thermodynamical properties in climate models. Large uncertainty remains among IWP measurements from satellite sensors, in large part due to the assumptions made for cloud microphysics in these retrievals. In this study, we develop a fast algorithm to retrieve IWP from the 157, 183.3+/-3 and 190.3 GHz radiances of the Microwave Humidity Sounder (MHS) such that the MHS cloud ice retrieval is consistent with CloudSat IWP measurements. This retrieval is obtained by constraining the empirical forward models between collocated and coincident measurements of CloudSat IWP and MHS cloud-induced radiance depression (Tcir) at these channels. The empirical forward model is represented by a lookup table (LUT) of Tcir-IWP relationships as a function of ht and the frequency channel.With ht simultaneously retrieved, the IWP is found to be more accurate. The useful range of the MHS IWP retrieval is between 0.5 and 10 kg/sq m, and agrees well with CloudSat in terms of the normalized probability density function (PDF). Compared to the empirical model, current operational radiative transfer models (RTMs) still have significant uncertainties in characterizing the observed Tcir-IWP relationships. Therefore, the empirical LUT method developed here remains an effective approach to retrieving ice cloud properties from the MHS-like microwave channels.

Monitoring Snow Using Geostationary Satellite Retrievals During the SAAWSO Project

NASA Astrophysics Data System (ADS)

Rabin, Robert M.; Gultepe, Ismail; Kuligowski, Robert J.; Heidinger, Andrew K.

2016-09-01

The SAAWSO (Satellite Applications for Arctic Weather and SAR (Search And Rescue) Operations) field programs were conducted by Environment Canada near St. Johns, NL and Goose Bay, NL in the winters of 2012-13 and 2013-14, respectively. The goals of these programs were to validate satellite-based nowcasting products, including snow amount, wind intensity, and cloud physical parameters (e.g., cloud cover), over northern latitudes with potential applications to Search And Rescue (SAR) operations. Ground-based in situ sensors and remote sensing platforms were used to measure microphysical properties of precipitation, clouds and fog, radiation, temperature, moisture and wind profiles. Multi-spectral infrared observations obtained from Geostationary Operational Environmental Satellite (GOES)-13 provided estimates of cloud top temperature and height, phase (water, ice), hydrometer size, extinction, optical depth, and horizontal wind patterns at 15 min intervals. In this work, a technique developed for identifying clouds capable of producing high snowfall rates and incorporating wind information from the satellite observations is described. The cloud top physical properties retrieved from operational satellite observations are validated using measurements obtained from the ground-based in situ and remote sensing platforms collected during two precipitation events: a blizzard heavy snow storm case and a moderate snow event. The retrieved snow precipitation rates are found to be comparable to those of ground-based platform measurements in the heavy snow event.

Validation of GOES-10 Satellite-derived Cloud and Radiative Properties for the MASRAD ARM Mobile Facility Deployment

NASA Technical Reports Server (NTRS)

Khaiyer, M. M.; Doelling, D. R.; Palikonda, R.; Mordeen, M. L.; Minnis, P.

2007-01-01

This poster presentation reviews the process used to validate the GOES-10 satellite derived cloud and radiative properties. The ARM Mobile Facility (AMF) deployment at Pt Reyes, CA as part of the Marine Stratus Radiation Aerosol and Drizzle experiment (MASRAD), 14 March - 14 September 2005 provided an excellent chance to validate satellite cloud-property retrievals with the AMF's flexible suite of ground-based remote sensing instruments. For this comparison, NASA LaRC GOES10 satellite retrievals covering this region and period were re-processed using an updated version of the Visible Infrared Solar-Infrared Split-Window Technique (VISST), which uses data taken at 4 wavelengths (0.65, 3.9,11 and 12 m resolution), and computes broadband fluxes using improved CERES (Clouds and Earth's Radiant Energy System)-GOES-10 narrowband-to-broadband flux conversion coefficients. To validate MASRAD GOES-10 satellite-derived cloud property data, VISST-derived cloud amounts, heights, liquid water paths are compared with similar quantities derived from available ARM ground-based instrumentation and with CERES fluxes from Terra.

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.

Improvements for retrieval of cloud droplet size by the POLDER instrument

NASA Astrophysics Data System (ADS)

Shang, H.; Husi, L.; Bréon, F. M.; Ma, R.; Chen, L.; Wang, Z.

2017-12-01

The principles of cloud droplet size retrieval via Polarization and Directionality of the Earth's Reflectance (POLDER) requires that clouds be horizontally homogeneous. The retrieval is performed by combining all measurements from an area of 150 km × 150 km to compensate for POLDER's insufficient directional sampling. Using POLDER-like data simulated with the RT3 model, we investigate the impact of cloud horizontal inhomogeneity and directional sampling on the retrieval and analyze which spatial resolution is potentially accessible from the measurements. Case studies show that the sub-grid-scale variability in droplet effective radius (CDR) can significantly reduce valid retrievals and introduce small biases to the CDR ( 1.5µm) and effective variance (EV) estimates. Nevertheless, the sub-grid-scale variations in EV and cloud optical thickness (COT) only influence the EV retrievals and not the CDR estimate. In the directional sampling cases studied, the retrieval using limited observations is accurate and is largely free of random noise. Several improvements have been made to the original POLDER droplet size retrieval. For example, measurements in the primary rainbow region (137-145°) are used to ensure retrievals of large droplet (>15 µm) and to reduce the uncertainties caused by cloud heterogeneity. A premium resoltion of 0.8° is determined by considering successful retrievals and cloud horizontal homogeneity. The improved algorithm is applied to measurements of POLDER in 2008, and we further compared our retrievals with cloud effective radii estimations of Moderate Resolution Imaging Spectroradiometer (MODIS). The results indicate that in global scale, the cloud effective radii and effective variance is larger in the central ocean than inland and coast areas. Over heavy polluted regions, the cloud droplets has small effective radii and narraw distribution due to the influence of aerosol particles.

Radiative Transfer Model for Operational Retrieval of Cloud Parameters from DSCOVR-EPIC Measurements

NASA Astrophysics Data System (ADS)

Yang, Y.; Molina Garcia, V.; Doicu, A.; Loyola, D. G.

2016-12-01

The Earth Polychromatic Imaging Camera (EPIC) onboard the Deep Space Climate Observatory (DSCOVR) measures the radiance in the backscattering region. To make sure that all details in the backward glory are covered, a large number of streams is required by a standard radiative transfer model based on the discrete ordinates method. Even the use of the delta-M scaling and the TMS correction do not substantially reduce the number of streams. The aim of this work is to analyze the capability of a fast radiative transfer model to retrieve operationally cloud parameters from EPIC measurements. The radiative transfer model combines the discrete ordinates method with matrix exponential for the computation of radiances and the matrix operator method for the calculation of the reflection and transmission matrices. Standard acceleration techniques as, for instance, the use of the normalized right and left eigenvectors, telescoping technique, Pade approximation and successive-order-of-scattering approximation are implemented. In addition, the model may compute the reflection matrix of the cloud by means of the asymptotic theory, and may use the equivalent Lambertian cloud model. The various approximations are analyzed from the point of view of efficiency and accuracy.

The US-DOE ARM/ASR Effort in Quantifying Uncertainty in Ground-Based Cloud Property Retrievals (Invited)

NASA Astrophysics Data System (ADS)

Xie, S.; Protat, A.; Zhao, C.

2013-12-01

One primary goal of the US Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program is to obtain and retrieve cloud microphysical properties from detailed cloud observations using ground-based active and passive remote sensors. However, there is large uncertainty in the retrieved cloud property products. Studies have shown that the uncertainty could arise from instrument limitations, measurement errors, sampling errors, retrieval algorithm deficiencies in assumptions, as well as inconsistent input data and constraints used by different algorithms. To quantify the uncertainty in cloud retrievals, a scientific focus group, Quantification of Uncertainties In Cloud Retrievals (QUICR), was recently created by the DOE Atmospheric System Research (ASR) program. This talk will provide an overview of the recent research activities conducted within QUICR and discuss its current collaborations with the European cloud retrieval community and future plans. The goal of QUICR is to develop a methodology for characterizing and quantifying uncertainties in current and future ARM cloud retrievals. The Work at LLNL was performed under the auspices of the U. S. Department of Energy (DOE), Office of Science, Office of Biological and Environmental Research by Lawrence Livermore National Laboratory under contract No. DE-AC52-07NA27344. LLNL-ABS-641258.

Validating Satellite-Retrieved Cloud Properties for Weather and Climate Applications

NASA Astrophysics Data System (ADS)

Minnis, P.; Bedka, K. M.; Smith, W., Jr.; Yost, C. R.; Bedka, S. T.; Palikonda, R.; Spangenberg, D.; Sun-Mack, S.; Trepte, Q.; Dong, X.; Xi, B.

2014-12-01

Cloud properties determined from satellite imager radiances are increasingly used in weather and climate applications, particularly in nowcasting, model assimilation and validation, trend monitoring, and precipitation and radiation analyses. The value of using the satellite-derived cloud parameters is determined by the accuracy of the particular parameter for a given set of conditions, such as viewing and illumination angles, surface background, and cloud type and structure. Because of the great variety of those conditions and of the sensors used to monitor clouds, determining the accuracy or uncertainties in the retrieved cloud parameters is a daunting task. Sensitivity studies of the retrieved parameters to the various inputs for a particular cloud type are helpful for understanding the errors associated with the retrieval algorithm relative to the plane-parallel world assumed in most of the model clouds that serve as the basis for the retrievals. Real world clouds, however, rarely fit the plane-parallel mold and generate radiances that likely produce much greater errors in the retrieved parameter than can be inferred from sensitivity analyses. Thus, independent, empirical methods are used to provide a more reliable uncertainty analysis. At NASA Langley, cloud properties are being retrieved from both geostationary (GEO) and low-earth orbiting (LEO) satellite imagers for climate monitoring and model validation as part of the NASA CERES project since 2000 and from AVHRR data since 1978 as part of the NOAA CDR program. Cloud properties are also being retrieved in near-real time globally from both GEO and LEO satellites for weather model assimilation and nowcasting for hazards such as aircraft icing. This paper discusses the various independent datasets and approaches that are used to assessing the imager-based satellite cloud retrievals. These include, but are not limited to data from ARM sites, CloudSat, and CALIPSO. This paper discusses the use of the various datasets available, the methods employed to utilize them in the cloud property retrieval validation process, and the results and how they aid future development of the retrieval algorithms. Future needs are also discussed.

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

NASA Technical Reports Server (NTRS)

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

Evaluation of AIRS cloud properties using MPACE data

NASA Astrophysics Data System (ADS)

Wu, Xuebao; Li, Jun; Menzel, W. Paul; Huang, Allen; Baggett, Kevin; Revercomb, Henry

2005-12-01

Retrieval of cloud properties from the Atmospheric Infrared Sounder (AIRS) aboard the NASA Aqua satellite has been investigated. The cloud products from the collocated MODerate resolution Imaging Spectroradiometer (MODIS) data are used to characterize the AIRS sub-pixel cloud information such as cloud phase, cloud coverage, and cloud layer information. A Minimum Residual (MR) approach is used to retrieve cloud microphysical properties once the cloud top pressure (CTP) and effective cloud amount (ECA) are determined from AIRS CO2 absorption channels between 720 and 790 cm-1. The cloud microphysical properties can be retrieved by minimizing the differences between the observations and the calculations using AIRS longwave window channels between 790 and 1130 cm-1. AIRS is used to derive cloud properties during the Mixed Phase Arctic Cloud Experiment (MPACE) field campaign. Comparison with measurements obtained from lidar data is made for a test day, showing that AIRS cloud property retrievals agree with in situ lidar observations. Due to the large solar zenith angle, the MODIS operational retrieval approach is not able to provide cloud microphysics north of Barrow, Alaska; however, AIRS provides cloud microphysical properties with its high spectral resolution IR measurements.

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.

Fast Simulators for Satellite Cloud Optical Centroid Pressure Retrievals, 1. Evaluation of OMI Cloud Retrievals

NASA Technical Reports Server (NTRS)

Joiner, J.; Vasilkov, A.; Gupta, P.; Bhartia, P. K.; Veefkind, P.; Sneep, M.; de Haan, J.; Polonsky, I.; Spurr, R.

2012-01-01

The cloud Optical Centroid Pressure (OCP), also known as the effective cloud pressure, is a satellite-derived parameter that is commonly used in trace-gas retrievals to account for the effects of clouds on near-infrared through ultraviolet radiance measurements. Fast simulators are desirable to further expand the use of cloud OCP retrievals into the operational and climate communities for applications such as data assimilation and evaluation of cloud vertical structure in general circulation models. In this paper, we develop and validate fast simulators that provide estimates of the cloud OCP given a vertical profile of optical extinction. We use a pressure-weighting scheme where the weights depend upon optical parameters of clouds and/or aerosol. A cloud weighting function is easily extracted using this formulation. We then use fast simulators to compare two different satellite cloud OCP retrievals from the Ozone Monitoring Instrument (OMI) with estimates based on collocated cloud extinction profiles from a combination of CloudS at radar and MODIS visible radiance data. These comparisons are made over a wide range of conditions to provide a comprehensive validation of the OMI cloud OCP retrievals. We find generally good agreement between OMI cloud OCPs and those predicted by CloudSat. However, the OMI cloud OCPs from the two independent algorithms agree better with each other than either does with the estimates from CloudSat/MODIS. Differences between OMI cloud OCPs and those based on CloudSat/MODIS may result from undetected snow/ice at the surface, cloud 3-D effects, low altitude clouds missed by CloudSat, and the fact that CloudSat only observes a relatively small fraction of an OMI field-of-view.

Extraction of Profile Information from Cloud Contaminated Radiances. Appendixes 2

NASA Technical Reports Server (NTRS)

Smith, W. L.; Zhou, D. K.; Huang, H.-L.; Li, Jun; Liu, X.; Larar, A. M.

2003-01-01

Clouds act to reduce the signal level and may produce noise dependence on the complexity of the cloud properties and the manner in which they are treated in the profile retrieval process. There are essentially three ways to extract profile information from cloud contaminated radiances: (1) cloud-clearing using spatially adjacent cloud contaminated radiance measurements, (2) retrieval based upon the assumption of opaque cloud conditions, and (3) retrieval or radiance assimilation using a physically correct cloud radiative transfer model which accounts for the absorption and scattering of the radiance observed. Cloud clearing extracts the radiance arising from the clear air portion of partly clouded fields of view permitting soundings to the surface or the assimilation of radiances as in the clear field of view case. However, the accuracy of the clear air radiance signal depends upon the cloud height and optical property uniformity across the two fields of view used in the cloud clearing process. The assumption of opaque clouds within the field of view permits relatively accurate profiles to be retrieved down to near cloud top levels, the accuracy near the cloud top level being dependent upon the actual microphysical properties of the cloud. The use of a physically correct cloud radiative transfer model enables accurate retrievals down to cloud top levels and below semi-transparent cloud layers (e.g., cirrus). It should also be possible to assimilate cloudy radiances directly into the model given a physically correct cloud radiative transfer model using geometric and microphysical cloud parameters retrieved from the radiance spectra as initial cloud variables in the radiance assimilation process. This presentation reviews the above three ways to extract profile information from cloud contaminated radiances. NPOESS Airborne Sounder Testbed-Interferometer radiance spectra and Aqua satellite AIRS radiance spectra are used to illustrate how cloudy radiances can be used in the profile retrieval process.

Joint retrievals of cloud and drizzle in marine boundary layer clouds using ground-based radar, lidar and zenith radiances

DOE PAGES

Fielding, M. D.; Chiu, J. C.; Hogan, R. J.; ...

2015-02-16

Active remote sensing of marine boundary-layer clouds is challenging as drizzle drops often dominate the observed radar reflectivity. We present a new method to simultaneously retrieve cloud and drizzle vertical profiles in drizzling boundary-layer cloud using surface-based observations of radar reflectivity, lidar attenuated backscatter, and zenith radiances. Specifically, the vertical structure of droplet size and water content of both cloud and drizzle is characterised throughout the cloud. An ensemble optimal estimation approach provides full error statistics given the uncertainty in the observations. To evaluate the new method, we first perform retrievals using synthetic measurements from large-eddy simulation snapshots of cumulusmore » under stratocumulus, where cloud water path is retrieved with an error of 31 g m −2. The method also performs well in non-drizzling clouds where no assumption of the cloud profile is required. We then apply the method to observations of marine stratocumulus obtained during the Atmospheric Radiation Measurement MAGIC deployment in the northeast Pacific. Here, retrieved cloud water path agrees well with independent 3-channel microwave radiometer retrievals, with a root mean square difference of 10–20 g m −2.« less

Single-footprint retrievals of temperature, water vapor and cloud properties from AIRS

NASA Astrophysics Data System (ADS)

Irion, Fredrick W.; Kahn, Brian H.; Schreier, Mathias M.; Fetzer, Eric J.; Fishbein, Evan; Fu, Dejian; Kalmus, Peter; Wilson, R. Chris; Wong, Sun; Yue, Qing

2018-02-01

Single-footprint Atmospheric Infrared Sounder spectra are used in an optimal estimation-based algorithm (AIRS-OE) for simultaneous retrieval of atmospheric temperature, water vapor, surface temperature, cloud-top temperature, effective cloud optical depth and effective cloud particle radius. In a departure from currently operational AIRS retrievals (AIRS V6), cloud scattering and absorption are in the radiative transfer forward model and AIRS single-footprint thermal infrared data are used directly rather than cloud-cleared spectra (which are calculated using nine adjacent AIRS infrared footprints). Coincident MODIS cloud data are used for cloud a priori data. Using single-footprint spectra improves the horizontal resolution of the AIRS retrieval from ˜ 45 to ˜ 13.5 km at nadir, but as microwave data are not used, the retrieval is not made at altitudes below thick clouds. An outline of the AIRS-OE retrieval procedure and information content analysis is presented. Initial comparisons of AIRS-OE to AIRS V6 results show increased horizontal detail in the water vapor and relative humidity fields in the free troposphere above the clouds. Initial comparisons of temperature, water vapor and relative humidity profiles with coincident radiosondes show good agreement. Future improvements to the retrieval algorithm, and to the forward model in particular, are discussed.

Correction of Rayleigh Scattering Effects in Cloud Optical Thickness Retrievals

NASA Technical Reports Server (NTRS)

Wang, Meng-Hua; King, Michael D.

1997-01-01

We present results that demonstrate the effects of Rayleigh scattering on the 9 retrieval of cloud optical thickness at a visible wavelength (0.66 Am). The sensor-measured radiance at a visible wavelength (0.66 Am) is usually used to infer remotely the cloud optical thickness from aircraft or satellite instruments. For example, we find that without removing Rayleigh scattering effects, errors in the retrieved cloud optical thickness for a thin water cloud layer (T = 2.0) range from 15 to 60%, depending on solar zenith angle and viewing geometry. For an optically thick cloud (T = 10), on the other hand, errors can range from 10 to 60% for large solar zenith angles (0-60 deg) because of enhanced Rayleigh scattering. It is therefore particularly important to correct for Rayleigh scattering contributions to the reflected signal from a cloud layer both (1) for the case of thin clouds and (2) for large solar zenith angles and all clouds. On the basis of the single scattering approximation, we propose an iterative method for effectively removing Rayleigh scattering contributions from the measured radiance signal in cloud optical thickness retrievals. The proposed correction algorithm works very well and can easily be incorporated into any cloud retrieval algorithm. The Rayleigh correction method is applicable to cloud at any pressure, providing that the cloud top pressure is known to within +/- 100 bPa. With the Rayleigh correction the errors in retrieved cloud optical thickness are usually reduced to within 3%. In cases of both thin cloud layers and thick ,clouds with large solar zenith angles, the errors are usually reduced by a factor of about 2 to over 10. The Rayleigh correction algorithm has been tested with simulations for realistic cloud optical and microphysical properties with different solar and viewing geometries. We apply the Rayleigh correction algorithm to the cloud optical thickness retrievals from experimental data obtained during the Atlantic Stratocumulus Transition Experiment (ASTEX) conducted near the Azores in June 1992 and compare these results to corresponding retrievals obtained using 0.88 Am. These results provide an example of the Rayleigh scattering effects on thin clouds and further test the Rayleigh correction scheme. Using a nonabsorbing near-infrared wavelength lambda (0.88 Am) in retrieving cloud optical thickness is only applicable over oceans, however, since most land surfaces are highly reflective at 0.88 Am. Hence successful global retrievals of cloud optical thickness should remove Rayleigh scattering effects when using reflectance measurements at 0.66 Am.

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.

A New Methodology for Simultaneous Multi-layer Retrievals of Ice and Liquid Water Cloud Properties

NASA Astrophysics Data System (ADS)

Sourdeval, O.; Labonnote, L.; Baran, A. J.; Brogniez, G.

2014-12-01

It is widely recognized that the study of clouds has nowadays become one of the major concern of the climate research community. Consequently, a multitude of retrieval methodologies have been developed during the last decades in order to obtain accurate retrievals of cloud properties that can be supplied to climate models. Most of the current methodologies have proven to be satisfactory for separately retrieving ice or liquid cloud properties, but very few of them have attempted simultaneous retrievals of these two cloud types. Recent studies nevertheless show that the omission of one of these layers can have strong consequences on the retrievals and their accuracy. In this study, a new methodology that simultaneously retrieves the properties of ice and liquid clouds is presented. The optical thickness and the effective radius of up to two liquid cloud layers and the ice water path of one ice cloud layer are simultaneously retrieved, along with an accurate estimation of their uncertainties. Radiometric measurements ranging from the visible to the thermal infrared are used for performing the retrievals. In order to quantify the capabilities and limitations of our methodology, the results of a theoretical information content analysis are first presented. This analysis allows obtaining an a priori understanding of how much information should be expected on each of the retrieval parameters in different atmospheric conditions, and which set of channels is likely to provide this information. After such theoretical considerations, global retrievals corresponding to several months of A-Train data are presented. Comparisons of our retrievals with operational products from active and passive instruments are effectuated and show good global agreements. These comparisons are useful for validating our retrievals but also for testing how operational products can be influenced by multi-layer configurations.

Observing ice particle growth along fall streaks in mixed-phase clouds using spectral polarimetric radar data

NASA Astrophysics Data System (ADS)

Pfitzenmaier, Lukas; Unal, Christine M. H.; Dufournet, Yann; Russchenberg, Herman W. J.

2018-06-01

The growth of ice crystals in presence of supercooled liquid droplets represents the most important process for precipitation formation in the mid-latitudes. However, such mixed-phase interaction processes remain relatively unknown, as capturing the complexity in cloud dynamics and microphysical variabilities turns to be a real observational challenge. Ground-based radar systems equipped with fully polarimetric and Doppler capabilities in high temporal and spatial resolutions such as the S-band transportable atmospheric radar (TARA) are best suited to observe mixed-phase growth processes. In this paper, measurements are taken with the TARA radar during the ACCEPT campaign (analysis of the composition of clouds with extended polarization techniques). Besides the common radar observables, the 3-D wind field is also retrieved due to TARA unique three beam configuration. The novelty of this paper is to combine all these observations with a particle evolution detection algorithm based on a new fall streak retrieval technique in order to study ice particle growth within complex precipitating mixed-phased cloud systems. In the presented cases, three different growth processes of ice crystals, plate-like crystals, and needles are detected and related to the presence of supercooled liquid water. Moreover, TARA observed signatures are assessed with co-located measurements obtained from a cloud radar and radiosondes. This paper shows that it is possible to observe ice particle growth processes within complex systems taking advantage of adequate technology and state of the art retrieval algorithms. A significant improvement is made towards a conclusive interpretation of ice particle growth processes and their contribution to rain production using fall streak rearranged radar data.

Outcome of the third cloud retrieval evaluation workshop

NASA Astrophysics Data System (ADS)

Roebeling, Rob; Baum, Bryan; Bennartz, Ralf; Hamann, Ulrich; Heidinger, Andy; Thoss, Anke; Walther, Andi

2013-05-01

Accurate measurements of global distributions of cloud parameters and their diurnal, seasonal, and interannual variations are needed to improve understanding of the role of clouds in the weather and climate system, and to monitor their time-space variations. Cloud properties retrieved from satellite observations, such as cloud vertical placement, cloud water path and cloud particle size, play an important role for such studies. In order to give climate and weather researchers more confidence in the quality of these retrievals their validity needs to be determined and their error characteristics must be quantified. The purpose of the Cloud Retrieval Evaluation Workshop (CREW), held from 15-18 Nov. 2011 in Madison, Wisconsin, USA, is to enhance knowledge on state-of-art cloud properties retrievals from passive imaging satellites, and pave the path towards optimizing these retrievals for climate monitoring as well as for the analysis of cloud parameterizations in climate and weather models. CREW also seeks to observe and understand methods used to prepare daily and monthly cloud parameter climatologies. An important workshop component is discussion on results of the algorithm and sensor comparisons and validation studies. Hereto a common database with about 12 different cloud properties retrievals from passive imagers (MSG, MODIS, AVHRR, POLDER and/or AIRS), complemented with cloud measurements that serve as a reference (CLOUDSAT, CALIPSO, AMSU, MISR), was prepared for a number of "golden days". The passive imager cloud property retrievals were inter-compared and validated against Cloudsat, Calipso and AMSU observations. In our presentation we summarize the outcome of the inter-comparison and validation work done in the framework of CREW, and elaborate on reasons for observed differences. More in depth discussions were held on retrieval principles and validation, and utilization of cloud parameters for climate research. This was done in parallel breakout sessions on cloud vertical placement, cloud physical properties, and cloud climatologies. We present the recommendations of these sessions, propose a way forward to establish international partnerships on cloud research, and summarize actions defined to tailor CREW activities to missions of international programs, such as the Global Energy and Water Cycle Experiment (GEWEX) and Sustained, Co-Ordinated Processing of Environmental Satellite Data for Climate Monitoring (SCOPE-CM). Finally, attention is given to increase the traceability and uniformity of different longterm and homogeneous records of cloud parameters.

Retrievals and Comparisons of Various MODIS-Spectrum Inferred Water Cloud Droplet Effective Radii

NASA Technical Reports Server (NTRS)

Fu-Lung, Chang; Minnis, Patrick; Lin, Bin; Sunny, Sun-Mack; Khaiyer, Mandana M.

2007-01-01

Cloud droplet effective radius retrievals from different Aqua MODIS nearinfrared channels (2.1- micrometer, 3.7- micrometer, and 1.6- micrometer) show considerable differences even among most confident QC pixels. Both Collection 004 and Collection 005 MOD06 show smaller mean effective radii at 3.7- micrometer wavelength than at 2.1- micrometer and 1.6- micrometer wavelengths. Differences in effective radius retrievals between Collection 004 and Collection 005 may be affected by cloud top height/temperature differences, which mainly occur for optically thin clouds. Changes in cloud top height and temperature for thin clouds have different impacts on the effective radius retrievals from 2.1- micrometer, 3.7- micrometer, and 1.6- micrometer channels. Independent retrievals (this study) show, on average, more consistency in the three effective radius retrievals. This study is for Aqua MODIS only.

Retrieval of Ice Cloud Properties Using an Optimal Estimation Algorithm and MODIS Infrared Observations: 2. Retrieval Evaluation

NASA Technical Reports Server (NTRS)

Wang, Chenxi; Platnick, Steven; Zhang, Zhibo; Meyer, Kerry; Wind, Galina; Yang, Ping

2016-01-01

An infrared-based optimal estimation (OE-IR) algorithm for retrieving ice cloud properties is evaluated. Specifically, the implementation of the algorithm with MODerate resolution Imaging Spectroradiometer (MODIS) observations is assessed in comparison with the operational retrieval products from MODIS on the Aqua satellite (MYD06), Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), and the Imaging Infrared Radiometer (IIR); the latter two instruments fly on the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite in the Afternoon Constellation (A-Train) with Aqua. The results show that OE-IR cloud optical thickness (tau) and effective radius (r(sub eff)) retrievals perform best for ice clouds having 0.5 < tau< 7 and r(sub eff) < 50microns. For global ice clouds, the averaged retrieval uncertainties of tau and r(sub eff) are 19% and 33%, respectively. For optically thick ice clouds with tau larger than 10, however, the tau and r(sub eff) retrieval uncertainties can exceed 30% and 50%, respectively. For ice cloud top height (h), the averaged global uncertainty is 0.48km. Relatively large h uncertainty (e.g., > 1km) occurs for tau < 0.5. Analysis of 1month of the OE-IR retrievals shows large tau and r(sub eff) uncertainties in storm track regions and the southern oceans where convective clouds are frequently observed, as well as in high-latitude regions where temperature differences between the surface and cloud top are more ambiguous. Generally, comparisons between the OE-IR and the operational products show consistent tau and h retrievals. However, obvious differences between the OE-IR and the MODIS Collection 6 r(sub eff) are found.

Neural network cloud top pressure and height for MODIS

NASA Astrophysics Data System (ADS)

Håkansson, Nina; Adok, Claudia; Thoss, Anke; Scheirer, Ronald; Hörnquist, Sara

2018-06-01

Cloud top height retrieval from imager instruments is important for nowcasting and for satellite climate data records. A neural network approach for cloud top height retrieval from the imager instrument MODIS (Moderate Resolution Imaging Spectroradiometer) is presented. The neural networks are trained using cloud top layer pressure data from the CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) dataset. Results are compared with two operational reference algorithms for cloud top height: the MODIS Collection 6 Level 2 height product and the cloud top temperature and height algorithm in the 2014 version of the NWC SAF (EUMETSAT (European Organization for the Exploitation of Meteorological Satellites) Satellite Application Facility on Support to Nowcasting and Very Short Range Forecasting) PPS (Polar Platform System). All three techniques are evaluated using both CALIOP and CPR (Cloud Profiling Radar for CloudSat (CLOUD SATellite)) height. Instruments like AVHRR (Advanced Very High Resolution Radiometer) and VIIRS (Visible Infrared Imaging Radiometer Suite) contain fewer channels useful for cloud top height retrievals than MODIS, therefore several different neural networks are investigated to test how infrared channel selection influences retrieval performance. Also a network with only channels available for the AVHRR1 instrument is trained and evaluated. To examine the contribution of different variables, networks with fewer variables are trained. It is shown that variables containing imager information for neighboring pixels are very important. The error distributions of the involved cloud top height algorithms are found to be non-Gaussian. Different descriptive statistic measures are presented and it is exemplified that bias and SD (standard deviation) can be misleading for non-Gaussian distributions. The median and mode are found to better describe the tendency of the error distributions and IQR (interquartile range) and MAE (mean absolute error) are found to give the most useful information of the spread of the errors. For all descriptive statistics presented MAE, IQR, RMSE (root mean square error), SD, mode, median, bias and percentage of absolute errors above 0.25, 0.5, 1 and 2 km the neural network perform better than the reference algorithms both validated with CALIOP and CPR (CloudSat). The neural networks using the brightness temperatures at 11 and 12 µm show at least 32 % (or 623 m) lower MAE compared to the two operational reference algorithms when validating with CALIOP height. Validation with CPR (CloudSat) height gives at least 25 % (or 430 m) reduction of MAE.

Estimating Cloud optical thickness from SEVIRI, for air quality research, by implementing a semi-analytical cloud retrieval algorithm

NASA Astrophysics Data System (ADS)

Pandey, Praveen; De Ridder, Koen; van Looy, Stijn; van Lipzig, Nicole

2010-05-01

Clouds play an important role in Earth's climate system. As they affect radiation hence photolysis rate coefficients (ozone formation),they also affect the air quality at the surface of the earth. Thus, a satellite remote sensing technique is used to retrieve the cloud properties for air quality research. The geostationary satellite, Meteosat Second Generation (MSG) has onboard, the Spinning Enhanced Visible and Infrared Imager (SEVIRI). The channels in the wavelength 0.6 µm and 1.64 µm are used to retrieve cloud optical thickness (COT). The study domain is over Europe covering a region between 35°N-70°N and 5°W-30°E, centred over Belgium. The steps involved in pre-processing the EUMETSAT level 1.5 images are described, which includes, acquisition of digital count number, radiometric conversion using offsets and slopes, estimation of radiance and calculation of reflectance. The Sun-earth-satellite geometry also plays an important role. A semi-analytical cloud retrieval algorithm (Kokhanovsky et al., 2003) is implemented for the estimation of COT. This approach doesn't involve the conventional look-up table approach, hence it makes the retrieval independent of numerical radiative transfer solutions. The semi-analytical algorithm is implemented on a monthly dataset of SEVIRI level 1.5 images. Minimum reflectance in the visible channel, at each pixel, during the month is accounted as the surface albedo of the pixel. Thus, monthly variation of COT over the study domain is prepared. The result so obtained, is compared with the COT products of Satellite Application Facility on Climate Monitoring (CM SAF). Henceforth, an approach to assimilate the COT for air quality research is presented. Address of corresponding author: Praveen Pandey, VITO- Flemish Institute for Technological Research, Boeretang 200, B 2400, Mol, Belgium E-mail: praveen.pandey@vito.be

Extending 3D Near-Cloud Corrections from Shorter to Longer Wavelengths

NASA Technical Reports Server (NTRS)

Marshak, Alexander; Evans, K. Frank; Varnai, Tamas; Guoyong, Wen

2014-01-01

Satellite observations have shown a positive correlation between cloud amount and aerosol optical thickness (AOT) that can be explained by the humidification of aerosols near clouds, and/or by cloud contamination by sub-pixel size clouds and the cloud adjacency effect. The last effect may substantially increase reflected radiation in cloud-free columns, leading to overestimates in the retrieved AOT. For clear-sky areas near boundary layer clouds the main contribution to the enhancement of clear sky reflectance at shorter wavelengths comes from the radiation scattered into clear areas by clouds and then scattered to the sensor by air molecules. Because of the wavelength dependence of air molecule scattering, this process leads to a larger reflectance increase at shorter wavelengths, and can be corrected using a simple two-layer model. However, correcting only for molecular scattering skews spectral properties of the retrieved AOT. Kassianov and Ovtchinnikov proposed a technique that uses spectral reflectance ratios to retrieve AOT in the vicinity of clouds; they assumed that the cloud adjacency effect influences the spectral ratio between reflectances at two wavelengths less than it influences the reflectances themselves. This paper combines the two approaches: It assumes that the 3D correction for the shortest wavelength is known with some uncertainties, and then it estimates the 3D correction for longer wavelengths using a modified ratio method. The new approach is tested with 3D radiances simulated for 26 cumulus fields from Large-Eddy Simulations, supplemented with 40 aerosol profiles. The results showed that (i) for a variety of cumulus cloud scenes and aerosol profiles over ocean the 3D correction due to cloud adjacency effect can be extended from shorter to longer wavelengths and (ii) the 3D corrections for longer wavelengths are not very sensitive to unbiased random uncertainties in the 3D corrections at shorter wavelengths.

Sensitivity of Marine Warm Cloud Retrieval Statistics to Algorithm Choices: Examples from MODIS Collection 6

NASA Astrophysics Data System (ADS)

Platnick, S.; Wind, G.; Zhang, Z.; Ackerman, S. A.; Maddux, B. C.

2012-12-01

The optical and microphysical structure of warm boundary layer marine clouds is of fundamental importance for understanding a variety of cloud radiation and precipitation processes. With the advent of MODIS (Moderate Resolution Imaging Spectroradiometer) on the NASA EOS Terra and Aqua platforms, simultaneous global/daily 1km retrievals of cloud optical thickness and effective particle size are provided, as well as the derived water path. In addition, the cloud product (MOD06/MYD06 for MODIS Terra and Aqua, respectively) provides separate effective radii results using the 1.6, 2.1, and 3.7 μm spectral channels. Cloud retrieval statistics are highly sensitive to how a pixel identified as being "not-clear" by a cloud mask (e.g., the MOD35/MYD35 product) is determined to be useful for an optical retrieval based on a 1-D cloud model. The Collection 5 MODIS retrieval algorithm removed pixels associated with cloud edges (defined by immediate adjacency to "clear" MOD/MYD35 pixels) as well as ocean pixels with partly cloudy elements in the 250m MODIS cloud mask - part of the so-called Clear Sky Restoral (CSR) algorithm. Collection 6 attempts retrievals for those two pixel populations, but allows a user to isolate or filter out the populations via CSR pixel-level Quality Assessment (QA) assignments. In this paper, using the preliminary Collection 6 MOD06 product, we present global and regional statistical results of marine warm cloud retrieval sensitivities to the cloud edge and 250m partly cloudy pixel populations. As expected, retrievals for these pixels are generally consistent with a breakdown of the 1D cloud model. While optical thickness for these suspect pixel populations may have some utility for radiative studies, the retrievals should be used with extreme caution for process and microphysical studies.

Estimate of the Impact of Absorbing Aerosol Over Cloud on the MODIS Retrievals of Cloud Optical Thickness and Effective Radius Using Two Independent Retrievals of Liquid Water Path

NASA Technical Reports Server (NTRS)

Wilcox, Eric M.; Harshvardhan; Platnick, Steven

2009-01-01

Two independent satellite retrievals of cloud liquid water path (LWP) from the NASA Aqua satellite are used to diagnose the impact of absorbing biomass burning aerosol overlaying boundary-layer marine water clouds on the Moderate Resolution Imaging Spectrometer (MODIS) retrievals of cloud optical thickness (tau) and cloud droplet effective radius (r(sub e)). In the MODIS retrieval over oceans, cloud reflectance in the 0.86-micrometer and 2.13-micrometer bands is used to simultaneously retrieve tau and r(sub e). A low bias in the MODIS tau retrieval may result from reductions in the 0.86-micrometer reflectance, which is only very weakly absorbed by clouds, owing to absorption by aerosols in cases where biomass burning aerosols occur above water clouds. MODIS LWP, derived from the product of the retrieved tau and r(sub e), is compared with LWP ocean retrievals from the Advanced Microwave Scanning Radiometer-EOS (AMSR-E), determined from cloud microwave emission that is transparent to aerosols. For the coastal Atlantic southern African region investigated in this study, a systematic difference between AMSR-E and MODIS LWP retrievals is found for stratocumulus clouds over three biomass burning months in 2005 and 2006 that is consistent with above-cloud absorbing aerosols. Biomass burning aerosol is detected using the ultraviolet aerosol index from the Ozone Monitoring Instrument (OMI) on the Aura satellite. The LWP difference (AMSR-E minus MODIS) increases both with increasing tau and increasing OMI aerosol index. During the biomass burning season the mean LWP difference is 14 g per square meters, which is within the 15-20 g per square meter range of estimated uncertainties in instantaneous LWP retrievals. For samples with only low amounts of overlaying smoke (OMI AI less than or equal to 1) the difference is 9.4, suggesting that the impact of smoke aerosols on the mean MODIS LWP is 5.6 g per square meter. Only for scenes with OMI aerosol index greater than 2 does the average LWP difference and the estimated bias in MODIS cloud optical thickness attributable to the impact of overlaying biomass burning aerosol exceed the instantaneous uncertainty in the retrievals.

Remote sensing of cirrus cloud vertical size profile using MODIS data

NASA Astrophysics Data System (ADS)

Wang, Xingjuan; Liou, K. N.; Ou, Steve S. C.; Mace, G. G.; Deng, M.

2009-05-01

This paper describes an algorithm for inferring cirrus cloud top and cloud base effective particle sizes and cloud optical thickness from the Moderate Resolution Imaging Spectroradiometer (MODIS) 0.645, 1.64 and 2.13, and 3.75 μm band reflectances/radiances. This approach uses a successive minimization method based on a look-up library of precomputed reflectances/radiances from an adding-doubling radiative transfer program, subject to corrections for Rayleigh scattering at the 0.645 μm band, above-cloud water vapor absorption, and 3.75 μm thermal emission. The algorithmic accuracy and limitation of the retrieval method were investigated by synthetic retrievals subject to the instrument noise and the perturbation of input parameters. The retrieval algorithm was applied to three MODIS cirrus scenes over the Atmospheric Radiation Measurement Program's southern Great Plain site, north central China, and northeast Asia. The reliability of retrieved cloud optical thicknesses and mean effective particle sizes was evaluated by comparison with MODIS cloud products and qualitatively good correlations were obtained for all three cases, indicating that the performance of the vertical sizing algorithm is comparable with the MODIS retrieval program. Retrieved cloud top and cloud base ice crystal effective sizes were also compared with those derived from the collocated ground-based millimeter wavelength cloud radar for the first case and from the Cloud Profiling Radar onboard CloudSat for the other two cases. Differences between retrieved and radar-derived cloud properties are discussed in light of assumptions made in the collocation process and limitations in radar remote sensing characteristics.

Physically-Retrieving Cloud and Thermodynamic Parameters from Ultraspectral IR Measurements

NASA Technical Reports Server (NTRS)

Zhou, Daniel K.; Smith, William L., Sr.; Liu, Xu; Larar, Allen M.; Mango, Stephen A.; Huang, Hung-Lung

2007-01-01

A 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 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 can be 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). NPOESS Airborne Sounder Testbed Interferometer (NAST-I) retrievals from the Atlantic-THORPEX Regional Campaign are compared with coincident observations obtained from dropsondes and the nadir-pointing Cloud Physics Lidar (CPL). This work was motivated by the need to obtain solutions for atmospheric soundings from infrared radiances observed for every individual field of view, regardless of cloud cover, from future ultraspectral geostationary satellite sounding instruments, such as the Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS) and the Hyperspectral Environmental Suite (HES). However, this retrieval approach can also be applied to the ultraspectral sounding instruments to fly on Polar satellites, such as the Infrared Atmospheric Sounding Interferometer (IASI) on the European MetOp satellite, the Cross-track Infrared Sounder (CrIS) on the NPOESS Preparatory Project and the following NPOESS series of satellites.

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.

Sensor Calibration and Ocean Products for TRMM Microwave Radiometer

NASA Technical Reports Server (NTRS)

Wentz, Frank J.; Lawrence, Richard J. (Technical Monitor)

2003-01-01

During the three years of finding, we have carefully corrected for two sensor/platform problems, developed a physically based retrieval algorithm to calculate SST, wind speed, water vapor, cloud liquid water and rain rates, validated these variables, and demonstrated that satellite microwave radiometers can provide very accurate SST retrievals through clouds. Prior to this, there was doubt by some scientists that the technique of microwave SST retrieval from satellites is a viable option. We think we have put these concerns to rest, and look forward to making microwave SSTs a standard component of the Earth science data sets. Our TMI SSTs were featured on several network news broadcasts and were reported in Science magazine. Additionally, we have developed a SST algorithm for VIRS to facilitate IR/MW inter-comparisons and completed research into diurnal cycles and air-sea interactions.

Sensor Calibration and Ocean Products for TRMM Microwave Radiometer

NASA Technical Reports Server (NTRS)

Lawrence, Richard J. (Technical Monitor); Wentz, Frank J.

2003-01-01

During the three years of fundin& we have carefully corrected for two sensor/platform problems, developed a physically based retrieval algorithm to calculate SST, wind speed, water vapor, cloud liquid water and rain rates, validated these variables, and demonstrated that satellite microwave radiometers can provide very accurate SST retrievals through clouds. Prior to this, there was doubt by some scientists that the technique of microwave SST retrieval from satellites is a viable option. We think we have put these concerns to rest, and look forward to making microwave SSTs a standard component of the Earth science data sets. Our TMI SSTs were featured on several network news broadcasts and were reported in Science magazine. Additionally, we have developed a SST algorithm for VIRS to facilitate IR/MW inter-comparisons and completed research into diurnal cycles and air-sea interactions.

Retrievals of Thick Cloud Optical Depth from the Geoscience Laser Altimeter System (GLAS) by Calibration of Solar Background Signal

NASA Technical Reports Server (NTRS)

Yang, Yuekui; Marshak, Alexander; Chiu, J. Christine; Wiscombe, Warren J.; Palm, Stephen P.; Davis, Anthony B.; Spangenberg, Douglas A.; Nguyen, Louis; Spinhirne, James D.; Minnis, Patrick

2008-01-01

Laser beams emitted from the Geoscience Laser Altimeter System (GLAS), as well as other space-borne laser instruments, can only penetrate clouds to a limit of a few optical depths. As a result, only optical depths of thinner clouds (< about 3 for GLAS) are retrieved from the reflected lidar signal. This paper presents a comprehensive study of possible retrievals of optical depth of thick clouds using solar background light and treating GLAS as a solar radiometer. To do so we first calibrate the reflected solar radiation received by the photon-counting detectors of GLAS' 532 nm channel, which is the primary channel for atmospheric products. The solar background radiation is regarded as a noise to be subtracted in the retrieval process of the lidar products. However, once calibrated, it becomes a signal that can be used in studying the properties of optically thick clouds. In this paper, three calibration methods are presented: (I) calibration with coincident airborne and GLAS observations; (2) calibration with coincident Geostationary Operational Environmental Satellite (GOES) and GLAS observations of deep convective clouds; (3) calibration from the first principles using optical depth of thin water clouds over ocean retrieved by GLAS active remote sensing. Results from the three methods agree well with each other. Cloud optical depth (COD) is retrieved from the calibrated solar background signal using a one-channel retrieval. Comparison with COD retrieved from GOES during GLAS overpasses shows that the average difference between the two retrievals is 24%. As an example, the COD values retrieved from GLAS solar background are illustrated for a marine stratocumulus cloud field that is too thick to be penetrated by the GLAS laser. Based on this study, optical depths for thick clouds will be provided as a supplementary product to the existing operational GLAS cloud products in future GLAS data releases.

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.

Assimilation of all-weather GMI and ATMS observations into HWRF

NASA Astrophysics Data System (ADS)

Moradi, I.; Evans, F.; McCarty, W.; Marks, F.; Eriksson, P.

2017-12-01

We propose a novel Bayesian Monte Carlo Integration (BMCI) technique to retrieve the profiles of temperature, water vapor, and cloud liquid/ice water content from microwave cloudy measurements in the presence of TCs. These retrievals then can either be directly used by meteorologists to analyze the structure of TCs or be assimilated to provide accurate initial conditions for the NWP models. The technique is applied to the data from the Advanced Technology Microwave Sounder (ATMS) onboard Suomi National Polar-orbiting Partnership (NPP) and Global Precipitation Measurement (GPM) Microwave Imager (GMI).

A better understanding of POLDER's cloud droplet size retrieval: impact of cloud horizontal inhomogeneity and directional sampling

NASA Astrophysics Data System (ADS)

Shang, H.; Chen, L.; Bréon, F.-M.; Letu, H.; Li, S.; Wang, Z.; Su, L.

2015-07-01

The principles of the Polarization and Directionality of the Earth's Reflectance (POLDER) cloud droplet size retrieval requires that clouds are horizontally homogeneous. Nevertheless, the retrieval is applied by combining all measurements from an area of 150 km × 150 km to compensate for POLDER's insufficient directional sampling. Using the POLDER-like data simulated with the RT3 model, we investigate the impact of cloud horizontal inhomogeneity and directional sampling on the retrieval, and then analyze which spatial resolution is potentially accessible from the measurements. Case studies show that the sub-scale variability in droplet effective radius (CDR) can mislead both the CDR and effective variance (EV) retrievals. Nevertheless, the sub-scale variations in EV and cloud optical thickness (COT) only influence the EV retrievals and not the CDR estimate. In the directional sampling cases studied, the retrieval is accurate using limited observations and is largely independent of random noise. Several improvements have been made to the original POLDER droplet size retrieval. For example, the measurements in the primary rainbow region (137-145°) are used to ensure accurate large droplet (> 15 μm) retrievals and reduce the uncertainties caused by cloud heterogeneity. We apply the improved method using the POLDER global L1B data for June 2008, the new CDR results are compared with the operational CDRs. The comparison show that the operational CDRs tend to be underestimated for large droplets. The reason is that the cloudbow oscillations in the scattering angle region of 145-165° are weak for cloud fields with CDR > 15 μm. Lastly, a sub-scale retrieval case is analyzed, illustrating that a higher resolution, e.g., 42 km × 42 km, can be used when inverting cloud droplet size parameters from POLDER measurements.

Coupled Retrieval of Liquid Water Cloud and Above-Cloud Aerosol Properties Using the Airborne Multiangle SpectroPolarimetric Imager (AirMSPI)

NASA Astrophysics Data System (ADS)

Xu, Feng; van Harten, Gerard; Diner, David J.; Davis, Anthony B.; Seidel, Felix C.; Rheingans, Brian; Tosca, Mika; Alexandrov, Mikhail D.; Cairns, Brian; Ferrare, Richard A.; Burton, Sharon P.; Fenn, Marta A.; Hostetler, Chris A.; Wood, Robert; Redemann, Jens

2018-03-01

An optimization algorithm is developed to retrieve liquid water cloud properties including cloud optical depth (COD), droplet size distribution and cloud top height (CTH), and above-cloud aerosol properties including aerosol optical depth (AOD), single-scattering albedo, and microphysical properties from sweep-mode observations by Jet Propulsion Laboratory's Airborne Multiangle SpectroPolarimetric Imager (AirMSPI) instrument. The retrieval is composed of three major steps: (1) initial estimate of the mean droplet size distribution across the entire image of 80-100 km along track by 10-25 km across track from polarimetric cloudbow observations, (2) coupled retrieval of image-scale cloud and above-cloud aerosol properties by fitting the polarimetric data at all observation angles, and (3) iterative retrieval of 1-D radiative transfer-based COD and droplet size distribution at pixel scale (25 m) by establishing relationships between COD and droplet size and fitting the total radiance measurements. Our retrieval is tested using 134 AirMSPI data sets acquired during the National Aeronautics and Space Administration (NASA) field campaign ObseRvations of Aerosols above CLouds and their intEractionS. The retrieved above-cloud AOD and CTH are compared to coincident HSRL-2 (HSRL-2, NASA Langley Research Center) data, and COD and droplet size distribution parameters (effective radius reff and effective variance veff) are compared to coincident Research Scanning Polarimeter (RSP) (NASA Goddard Institute for Space Studies) data. Mean absolute differences between AirMSPI and HSRL-2 retrievals of above-cloud AOD at 532 nm and CTH are 0.03 and <0.5 km, respectively. At RSP's footprint scale ( 323 m), mean absolute differences between RSP and AirMSPI retrievals of COD, reff, and veff in the cloudbow area are 2.33, 0.69 μm, and 0.020, respectively. Neglect of smoke aerosols above cloud leads to an underestimate of image-averaged COD by 15%.

Intercomparisons of marine boundary layer cloud properties from the ARM CAP-MBL campaign and two MODIS cloud products

NASA Astrophysics Data System (ADS)

Zhang, Zhibo; Dong, Xiquan; Xi, Baike; Song, Hua; Ma, Po-Lun; Ghan, Steven J.; Platnick, Steven; Minnis, Patrick

2017-02-01

From April 2009 to December 2010, the Department of Energy Atmospheric Radiation Measurement (ARM) program carried out an observational field campaign on Graciosa Island, targeting the marine boundary layer (MBL) clouds over the Azores region. In this paper, we present an intercomparison of the MBL cloud properties, namely, cloud liquid water path (LWP), cloud optical thickness (COT), and cloud-droplet effective radius (CER), among retrievals from the ARM mobile facility and two Moderate Resolution Imaging Spectroradiometer (MODIS) cloud products (Goddard Space Flight Center (GSFC)-MODIS and Clouds and Earth's Radiant Energy System-MODIS). A total of 63 daytime single-layer MBL cloud cases are selected for intercomparison. Comparison of collocated retrievals indicates that the two MODIS cloud products agree well on both COT and CER retrievals, with the correlation coefficient R > 0.95, despite their significant difference in spatial sampling. In both MODIS products, the CER retrievals based on the 2.1 µm band (CER2.1) are significantly larger than those based on the 3.7 µm band (CER3.7). The GSFC-MODIS cloud product is collocated and compared with ground-based ARM observations at several temporal-spatial scales. In general, the correlation increases with more precise collocation. For the 63 selected MBL cloud cases, the GSFC-MODIS LWP and COT retrievals agree reasonably well with the ground-based observations with no apparent bias and correlation coefficient R around 0.85 and 0.70, respectively. However, GSFC-MODIS CER3.7 and CER2.1 retrievals have a lower correlation (R 0.5) with the ground-based retrievals. For the 63 selected cases, they are on average larger than ground observations by about 1.5 µm and 3.0 µm, respectively. Taking into account that the MODIS CER retrievals are only sensitive to cloud top reduces the bias only by 0.5 µm.

Investigation of passive atmospheric sounding using millimeter and submillimeter wavelength channels

NASA Technical Reports Server (NTRS)

Gasiewski, A. J.; Adelberg, L. K.; Kunkee, D. B.; Jackson, D. M.

1993-01-01

Progress by investigators at the Georgia Institute of Technology in the development of techniques for passive microwave retrieval of water vapor, cloud, and precipitation parameters using millimeter- and sub-millimeter wavelength channels is reviewed. Channels of particular interest are in the tropospheric transmission windows at 90, 166, 220, 340, and 410 GHz and centered around the water vapor lines at 183 and 325 GHz. Collectively, these channels have potential application in high-resolution mapping (e.g., from geosynchronous orbit), remote sensing of cloud and precipitation parameters, and retrieval of water vapor profiles. During the period from 1 Jan. 1993 through 30 Jun. 1993 the Millimeter-wave Imaging Radiometer (MIR) completed data flights during a two-month long deployment in conjunction with TOGA/COARE. Coincident data was collected from several other ground-based, airborne, and satellite sensors, including the NASA/MSFC AMPR, MIT MTS, DMSP SSM/T-2 satellite, collocated radiosondes, ground- and aircraft-based radiometers and cloud lidars, airborne infrared imagers, solar flux probes, and airborne cloud particle sampling probes.

Linearized radiative transfer models for retrieval of cloud parameters from EPIC/DSCOVR measurements

NASA Astrophysics Data System (ADS)

Molina García, Víctor; Sasi, Sruthy; Efremenko, Dmitry S.; Doicu, Adrian; Loyola, Diego

2018-07-01

In this paper, we describe several linearized radiative transfer models which can be used for the retrieval of cloud parameters from EPIC (Earth Polychromatic Imaging Camera) measurements. The approaches under examination are (1) the linearized forward approach, represented in this paper by the linearized discrete ordinate and matrix operator methods with matrix exponential, and (2) the forward-adjoint approach based on the discrete ordinate method with matrix exponential. To enhance the performance of the radiative transfer computations, the correlated k-distribution method and the Principal Component Analysis (PCA) technique are used. We provide a compact description of the proposed methods, as well as a numerical analysis of their accuracy and efficiency when simulating EPIC measurements in the oxygen A-band channel at 764 nm. We found that the computation time of the forward-adjoint approach using the correlated k-distribution method in conjunction with PCA is approximately 13 s for simultaneously computing the derivatives with respect to cloud optical thickness and cloud top height.

Multi-sensor measurements of mixed-phase clouds above Greenland

NASA Astrophysics Data System (ADS)

Stillwell, Robert A.; Shupe, Matthew D.; Thayer, Jeffrey P.; Neely, Ryan R.; Turner, David D.

2018-04-01

Liquid-only and mixed-phase clouds in the Arctic strongly affect the regional surface energy and ice mass budgets, yet much remains unknown about the nature of these clouds due to the lack of intensive measurements. Lidar measurements of these clouds are challenged by very large signal dynamic range, which makes even seemingly simple tasks, such as thermodynamic phase classification, difficult. This work focuses on a set of measurements made by the Clouds Aerosol Polarization and Backscatter Lidar at Summit, Greenland and its retrieval algorithms, which use both analog and photon counting as well as orthogonal and non-orthogonal polarization retrievals to extend dynamic range and improve overall measurement quality and quantity. Presented here is an algorithm for cloud parameter retrievals that leverages enhanced dynamic range retrievals to classify mixed-phase clouds. This best guess retrieval is compared to co-located instruments for validation.

A multi-spectral approach to simultaneously retrieve above-cloud smoke optical depth and the optical and microphysical properties of underlying marine stratocumulus clouds using MODIS

NASA Astrophysics Data System (ADS)

Meyer, K.; Platnick, S. E.; Zhang, Z.

2013-12-01

Clouds, aerosols, and their interactions are widely considered to be key uncertainty components in our current understanding of the Earth's atmosphere and radiation budget. The work presented here is focused on the quasi-permanent marine boundary layer (MBL) clouds over the southeastern Atlantic Ocean, which underlie a near-persistent smoke layer produced from extensive biomass burning throughout the southern African savanna during austral winter. The absorption of the above-cloud smoke layer, which increases with decreasing wavelength, can introduce biases into the standard MODIS cloud optical and microphysical property retrievals of the underlying MBL clouds. This effect is more pronounced in the cloud optical thickness retrievals, which over ocean are derived from the wavelength channel centered near 0.86 μm (effective particle size retrievals are derived from the short and mid-wave IR channels at 1.6, 2.1, and 3.7 μm). Here, a new method is introduced to simultaneously retrieve the above-cloud smoke aerosol optical depth (AOD) and the unbiased cloud optical thickness (COT) and effective radius (CER) using multiple MODIS spectral channels in the visible and near- and shortwave-infrared. Preliminary retrieval results are shown, as are comparisons with other A-Train sensors.

Derivation of cloud-free-region atmospheric motion vectors from FY-2E thermal infrared imagery

NASA Astrophysics Data System (ADS)

Wang, Zhenhui; Sui, Xinxiu; Zhang, Qing; Yang, Lu; Zhao, Hang; Tang, Min; Zhan, Yizhe; Zhang, Zhiguo

2017-02-01

The operational cloud-motion tracking technique fails to retrieve atmospheric motion vectors (AMVs) in areas lacking cloud; and while water vapor shown in water vapor imagery can be used, the heights assigned to the retrieved AMVs are mostly in the upper troposphere. As the noise-equivalent temperature difference (NEdT) performance of FY-2E split window (10.3-11.5 μm, 11.6-12.8 μm) channels has been improved, the weak signals representing the spatial texture of water vapor and aerosols in cloud-free areas can be strengthened with algorithms based on the difference principle, and applied in calculating AMVs in the lower troposphere. This paper is a preliminary summary for this purpose, in which the principles and algorithm schemes for the temporal difference, split window difference and second-order difference (SD) methods are introduced. Results from simulation and cases experiments are reported in order to verify and evaluate the methods, based on comparison among retrievals and the "truth". The results show that all three algorithms, though not perfect in some cases, generally work well. Moreover, the SD method appears to be the best in suppressing the surface temperature influence and clarifying the spatial texture of water vapor and aerosols. The accuracy with respect to NCEP 800 hPa reanalysis data was found to be acceptable, as compared with the accuracy of the cloud motion vectors.

The Effects of an Absorbing Smoke Layer on MODIS Marine Boundary Layer Cloud Optical Property Retrievals and Radiative Forcing

NASA Technical Reports Server (NTRS)

Meyer, Kerry; Platnick, Steven

2012-01-01

Clouds, aerosols, and their interactions are widely considered to be key uncertainty components in our current understanding of the Earth's atmosphere and radiation budget. The work presented here is focused on the quasi-permanent marine boundary layer . (MBL) clouds off the southern Atlantic coast of Africa and the effects on MODIS cloud optical property retrievals (MOD06) of an overlying absorbing smoke layer. During much of August and September, a persistent smoke layer resides over this region, produced from extensive biomass burning throughout the southern African savanna. The resulting absorption, which increases with decreasing wavelength, potentially introduces biases into the MODIS cloud optical property retrievals of the underlying MBL clouds. This effect is more pronounced in the cloud optical thickness retrievals, which over ocean are derived from the wavelength channel centered near 0.86 micron (effective particle size retrievals are derived from the longer-wavelength near-IR channels at 1.6, 2.1, and 3.7 microns). Here, the spatial distributions of the scalar statistics of both the cloud and aerosol layers are first determined from the CALIOP 5 km layer products. Next, the MOD06 look-up tables (LUTs) are adjusted by inserting an absorbing smoke layer of varying optical thickness over the cloud. Retrievals are subsequently performed for a subset of MODIS pixels collocated with the CALIOP ground track, using smoke optical thickness from the CALIOP 5km aerosol layer product to select the appropriate LUT. The resulting differences in cloud optical property retrievals due to the inclusion of the smoke layer in the LUTs will be examined. In addition, the direct radiative forcing of this smoke layer will be investigated from the perspective of the cloud optical property retrieval differences.

Retrievals of Aerosol and Cloud Particle Microphysics Using Polarization and Depolarization Techniques

NASA Technical Reports Server (NTRS)

Mishchenko, Michael; Hansen, James E. (Technical Monitor)

2001-01-01

The recent availability of theoretical techniques for computing single and multiple scattering of light by realistic polydispersions of spherical and nonspherical particles and the strong dependence of the Stokes scattering matrix on particle size, shape, and refractive index make polarization and depolarization measurements a powerful particle characterization tool. In this presentation I will describe recent applications of photopolarimetric and lidar depolarization measurements to remote sensing characterization of tropospheric aerosols, polar stratospheric clouds (PSCs), and contrails. The talk will include (1) a short theoretical overview of the effects of particle microphysics on particle single-scattering characteristics; (2) the use of multi-angle multi-spectral photopolarimetry to retrieve the optical thickness, size distribution, refractive index, and number concentration of tropospheric aerosols over the ocean surface; and (3) the application of the T-matrix method to constraining the PSC and contrail particle microphysics using multi-spectral measurements of lidar backscatter and depolarization.

Outcome of the Third Cloud Retrieval Evaluation Workshop

NASA Astrophysics Data System (ADS)

Roebeling, R.; Baum, B.; Bennartz, R.; Hamann, U.; Heidinger, A.; Thoss, A.; Walther, A.

2012-04-01

Accurate measurements of global distributions of cloud parameters and their diurnal, seasonal, and inter-annual variations are needed to improve the understanding of the role of clouds in the weather and climate system, and to monitor their time-space variations. Cloud properties retrieved from satellite observations, such as cloud vertical placement, cloud water path and cloud particle size, play an important role such studies. In order to give climate and weather researchers more confidence in the quality of these retrievals their validity needs to be determined and their error characteristics need to be quantified. The purpose of the Cloud Retrieval Evaluation Workshop (CREW), which was held from 15-18 November 2011 in Madison, Wisconsin, USA, is to enhance our knowledge on state-of-art cloud properties retrievals from passive imaging satellites, and pave the path towards optimising these retrievals for climate monitoring as well as for the analysis of cloud parameterizations in climate and weather models. CREW also seeks to observe and understand methods that are used to prepare daily and monthly cloud parameter climatologies. An important component of the workshop is the discussion on the results of the algorithm and sensor comparisons and validation studies. Hereto a common database with about 12 different cloud properties retrievals from passive imagers (MSG, MODIS, AVHRR, POLDER and/or AIRS), complemented with cloud measurements that serve as a reference (CLOUDSAT, CALIPSO, AMSU, MISR), was prepared for a number of "golden days". The passive imager cloud property retrievals were inter-compared and validated against Cloudsat, Calipso and AMSU observations. In our presentation we will summarize the outcome of the inter-comparison and validation work done in the framework of CREW, and elaborate on the reasons for the observed differences. More in depth discussions were held on retrieval principles and validation, and the utilization of cloud parameters for climate research. This was done in parallel breakout sessions on cloud vertical placement; cloud physical properties, and cloud climatologies. We will present the recommendations of these sessions, propose a way forward to establish international partnerships on cloud research, and summarize the actions defined to tailor the CREW activities to missions of international programs, such as the Global Energy and Water Cycle Experiment (GEWEX) and Sustained, Co-Ordinated Processing of Environmental Satellite Data for Climate Monitoring (SCOPE-CM). Finally, attention will be given to increase the traceability and uniformity of different long-term and homogeneous records of cloud parameters.

Surface radiation budget in the Clouds and the Earth's Radiant Energy System (CERES) effort and in the Global Energy and Water Cycle Experiment (GEWEX)

NASA Technical Reports Server (NTRS)

Charlock, Thomas P.; Smith, G. L.; Rose, Fred G.

1990-01-01

The surface radiation budget (SRB) and the atmospheric radiative flux divergence (ARD) are vital components of the weather and climate system. The importance of radiation in a complex international scientific endeavor, the GEWEX of the World Climate Research Programme is explained. The radiative transfer techniques and satellite instrumentation that will be used to retrieve the SRB and ARD later in this decade with the CERES are discussed; CERES is a component of the Earth Observing System satellite program. Examples of consistent SRB and ARD retrievals made with Nimbus-7 and International Satellite Cloud Climatology Project data from July 1983 are presented.

Volcanic Ash Retrievals Using ORAC and Satellite Measurements in the Visible and IR

NASA Astrophysics Data System (ADS)

Mcgarragh, Gregory R.; Thomas, Gareth E.; Povey, Adam C.; Poulsen, Caroline A.; Grainger, Roy G.

2015-11-01

The Optimal Retrieval of Aerosol and Cloud (ORAC) is a generalized optimal estimation system that uses visible to infrared measurements from a wide range of instruments including AATSR, AVHRR, MODIS and SEVIRI. Recently, support to retrieve volcanic ash has been added for which it retrieves optical thickness, effective radius and cloud top pressure. In this proceeding we discuss the implementation of the volcanic ash retrieval in ORAC including the retrieval methodology, forward model, sources of uncertainty and the discrimination of ash from aerosol and cloud. Results are presented that are consistent with a well know eruption from both AATSR and MODIS while results of a full SEVIRI retrieval of ash, aerosol and cloud properties relative to the ash is are discussed.

Atmospheric influences on infrared-laser signals used for occultation measurements between Low Earth Orbit satellites

NASA Astrophysics Data System (ADS)

Schweitzer, S.; Kirchengast, G.; Proschek, V.

2011-10-01

LEO-LEO infrared-laser occultation (LIO) is a new occultation technique between Low Earth Orbit (LEO) satellites, which applies signals in the short wave infrared spectral range (SWIR) within 2 μm to 2.5 μm. It is part of the LEO-LEO microwave and infrared-laser occultation (LMIO) method that enables to retrieve thermodynamic profiles (pressure, temperature, humidity) and altitude levels from microwave signals and profiles of greenhouse gases and further variables such as line-of-sight wind speed from simultaneously measured LIO signals. Due to the novelty of the LMIO method, detailed knowledge of atmospheric influences on LIO signals and of their suitability for accurate trace species retrieval did not yet exist. Here we discuss these influences, assessing effects from refraction, trace species absorption, aerosol extinction and Rayleigh scattering in detail, and addressing clouds, turbulence, wind, scattered solar radiation and terrestrial thermal radiation as well. We show that the influence of refractive defocusing, foreign species absorption, aerosols and turbulence is observable, but can be rendered small to negligible by use of the differential transmission principle with a close frequency spacing of LIO absorption and reference signals within 0.5%. The influences of Rayleigh scattering and terrestrial thermal radiation are found negligible. Cloud-scattered solar radiation can be observable under bright-day conditions, but this influence can be made negligible by a close time spacing (within 5 ms) of interleaved laser-pulse and background signals. Cloud extinction loss generally blocks SWIR signals, except very thin or sub-visible cirrus clouds, which can be addressed by retrieving a cloud layering profile and exploiting it in the trace species retrieval. Wind can have a small influence on the trace species absorption, which can be made negligible by using a simultaneously retrieved or a moderately accurate background wind speed profile. We conclude that the set of SWIR channels proposed for implementing the LMIO method (Kirchengast and Schweitzer, 2011) provides adequate sensitivity to accurately retrieve eight trace species of key importance to climate and atmospheric chemistry (H2O, CO2, 13CO2, C18OO, CH4, N2O, O3, CO) in the upper troposphere/lower stratosphere region outside clouds under all atmospheric conditions. Two further species (HDO, H218O) can be retrieved in the upper troposphere.

Information content of OCO-2 oxygen A-band channels for retrieving marine liquid cloud properties

NASA Astrophysics Data System (ADS)

Richardson, Mark; Stephens, Graeme L.

2018-03-01

Information content analysis is used to select channels for a marine liquid cloud retrieval using the high-spectral-resolution oxygen A-band instrument on NASA's Orbiting Carbon Observatory-2 (OCO-2). Desired retrieval properties are cloud optical depth, cloud-top pressure and cloud pressure thickness, which is the geometric thickness expressed in hectopascals. Based on information content criteria we select a micro-window of 75 of the 853 functioning OCO-2 channels spanning 763.5-764.6 nm and perform a series of synthetic retrievals with perturbed initial conditions. We estimate posterior errors from the sample standard deviations and obtain ±0.75 in optical depth and ±12.9 hPa in both cloud-top pressure and cloud pressure thickness, although removing the 10 % of samples with the highest χ2 reduces posterior error in cloud-top pressure to ±2.9 hPa and cloud pressure thickness to ±2.5 hPa. The application of this retrieval to real OCO-2 measurements is briefly discussed, along with limitations and the greatest caution is urged regarding the assumption of a single homogeneous cloud layer, which is often, but not always, a reasonable approximation for marine boundary layer clouds.

View angle dependence of cloud optical thicknesses retrieved by MODIS

NASA Technical Reports Server (NTRS)

Marshak, Alexander; Varnai, Tamas

2005-01-01

This study examines whether cloud inhomogeneity influences the view angle dependence of MODIS cloud optical thickness (tau) retrieval results. The degree of cloud inhomogeneity is characterized through the local gradient in 11 microns brightness temperature. The analysis of liquid phase clouds in a one year long global dataset of Collection 4 MODIS data reveals that while optical thickness retrievals give remarkably consistent results for all view directions if clouds are homogeneous, they give much higher tau-values for oblique views than for overhead views if clouds are inhomogeneous and the sun is fairly oblique. For solar zenith angles larger than 55deg, the mean optical thickness retrieved for the most inhomogeneous third of cloudy pixels is more than 30% higher for oblique views than for overhead views. After considering a variety of possible scenarios, the paper concludes that the most likely reason for the increase lies in three-dimensional radiative interactions that are not considered in current, one-dimensional retrieval algorithms. Namely, the radiative effect of cloud sides viewed at oblique angles seems to contribute most to the enhanced tau-values. The results presented here will help understand cloud retrieval uncertainties related to cloud inhomogeneity. They complement the uncertainty estimates that will start accompanying MODIS cloud products in Collection 5 and may eventually help correct for the observed view angle dependent biases.

Performance of greenhouse gas profiling by infrared-laser and microwave occultation in cloudy air

NASA Astrophysics Data System (ADS)

Proschek, V.; Kirchengast, G.; Emde, C.; Schweitzer, S.

2012-12-01

ACCURATE is a proposed future satellite mission enabling simultaneous measurements of greenhouse gases (GHGs), wind and thermodynamic variables from Low Earth Orbit (LEO). The measurement principle is a combination of LEO-LEO infrared-laser occultation (LIO) and microwave occultation (LMO), the LMIO method, where the LIO signals are very sensitive to clouds. The GHG retrieval will therefore be strongly influenced by clouds in parts of the troposphere. The IR-laser signals, at wavelengths within 2--2.5μ m, are chosen to measure six GHGs (H2O, CO2, CH4, N2O, O3, CO; incl.~key isotopes 13CO2, C18OO, HDO). The LMO signals enable to co-measure the thermodynamic variables. In this presentation we introduce the algorithm to retrieve GHG profiles under cloudy-air conditions by using quasi-realistic forward simulations, including also influence of Rayleigh scattering, scintillations and aerosols. Data from CALIPSO--Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations--with highest vertical resolution of about 60 m and horizontal resolution of about 330 m were used for simulation of clouds. The IR-laser signals consist for each GHG of a GHG-sensitive and a close-by reference signal. The key process, ``differencing'' of these two signals, removes the atmospheric ``broadband'' effects, resulting in a pure GHG transmission profile. Very thin ice clouds, like sub-visible cirrus, are fairly transparent to the IR-laser signals, thicker and liquid water clouds block the signals. The reference signal is used to produce a cloud layering profile from zero to blocking clouds and is smoothed in a preprocess to suppress scintillations. Sufficiently small gaps, of width <2 km in the cloud layering profile, are found to enable a decent retrieval of entire GHG profiles over the UTLS under broken cloudiness and are therefore bridged by interpolation. Otherwise in case of essentially continuous cloudiness the profiles are found to terminate at cloud top level. The accuracy of retrieved GHG profiles is found better than 1% to 4% for single profiles in the UTLS region outside clouds and through broken cloudiness, and the profiles are essentially unbiased. Cloud gap-interpolation increases the tropospheric penetration of GHG profiles for scientific applications. The associated cloud layering profile provides quality-control information on cloud gap-interpolations, if they occured, and on cloud-top altitude for cloud blocking cases. The LMIO technique shows promising prospects for GHG monitoring even under cloudy-air conditions.

Intercomparisons of Marine Boundary Layer Cloud Properties from the ARM CAP-MBL Campaign and Two MODIS Cloud Products

NASA Technical Reports Server (NTRS)

Zhang, Zhibo; Dong, Xiquan; Xi, Baike; Song, Hua; Ma, Po-Lun; Ghan, Steven J.; Platnick, Steven; Minnis, Patrick

2017-01-01

From April 2009 to December 2010, the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program carried out an observational field campaign on Graciosa Island, targeting the marine boundary layer (MBL) clouds over the Azores region. In this paper, we present an inter-comparison of the MBL cloud properties, namely, cloud liquid water path (LWP), cloud optical thickness (COT) and cloud-droplet effective radius (CER), among retrievals from the ARM mobile facility (AMF) and two Moderate Resolution Spectroradiometer (MODIS) cloud products (GSFC-MODIS and CERES-MODIS). A total of 63 daytime single-layer MBL cloud cases are selected for inter-comparison. Comparison of collocated retrievals indicates that the two MODIS cloud products agree well on both COT and CER retrievals, with the correlation coefficient R greater than 0.95 despite their significant difference in spatial sampling. In both MODIS products, the CER retrievals based on the 2.1 micrometers band (CER(sub 2.1)) is significantly smaller than that based on the 3.7 micrometers band (CER(sub 3.7)). The GSFC-MODIS cloud product is collocated and compared with ground-based ARM observations at several temporal spatial scales. In general, the correlation increases with more precise collocation. For the 63 selected MBL cloud cases, the GSFC-MODIS LWP and COT retrievals agree reasonably well with the ground-based observations with no apparent bias and correlation coefficient R around 0.85 and 0.70, respectively. However, GSFC-MODIS CER(sub 3.7) and CER(sub 2.1) retrievals have a lower correlation (R is approximately 0.5) with the ground-based retrievals. For the 63 selected cases, they are on average larger than ground observations by about 1.5 micrometers and 3.0 micrometers, respectively. Taking into account that the MODIS CER retrievals are only sensitive to cloud top reduces the bias only by 0.5 micrometers.

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.

A framework for quantifying the impacts of sub-pixel reflectance variance and covariance on cloud optical thickness and effective radius retrievals based on the bi-spectral method

NASA Astrophysics Data System (ADS)

Zhang, Z.; Werner, F.; Cho, H.-M.; Wind, G.; Platnick, S.; Ackerman, A. S.; Di Girolamo, L.; Marshak, A.; Meyer, Kerry

2017-02-01

The so-called bi-spectral method retrieves cloud optical thickness (τ) and cloud droplet effective radius (re) simultaneously from a pair of cloud reflectance observations, one in a visible or near infrared (VIS/NIR) band and the other in a shortwave-infrared (SWIR) band. A cloudy pixel is usually assumed to be horizontally homogeneous in the retrieval. Ignoring sub-pixel variations of cloud reflectances can lead to a significant bias in the retrieved τ and re. In this study, we use the Taylor expansion of a two-variable function to understand and quantify the impacts of sub-pixel variances of VIS/NIR and SWIR cloud reflectances and their covariance on the τ and re retrievals. This framework takes into account the fact that the retrievals are determined by both VIS/NIR and SWIR band observations in a mutually dependent way. In comparison with previous studies, it provides a more comprehensive understanding of how sub-pixel cloud reflectance variations impact the τ and re retrievals based on the bi-spectral method. In particular, our framework provides a mathematical explanation of how the sub-pixel variation in VIS/NIR band influences the re retrieval and why it can sometimes outweigh the influence of variations in the SWIR band and dominate the error in re retrievals, leading to a potential contribution of positive bias to the re retrieval.

A Framework for Quantifying the Impacts of Sub-Pixel Reflectance Variance and Covariance on Cloud Optical Thickness and Effective Radius Retrievals Based on the Bi-Spectral Method.

NASA Technical Reports Server (NTRS)

Zhang, Z; Werner, F.; Cho, H. -M.; Wind, Galina; Platnick, S.; Ackerman, A. S.; Di Girolamo, L.; Marshak, A.; Meyer, Kerry

2017-01-01

The so-called bi-spectral method retrieves cloud optical thickness (t) and cloud droplet effective radius (re) simultaneously from a pair of cloud reflectance observations, one in a visible or near infrared (VIS/NIR) band and the other in a shortwave-infrared (SWIR) band. A cloudy pixel is usually assumed to be horizontally homogeneous in the retrieval. Ignoring sub-pixel variations of cloud reflectances can lead to a significant bias in the retrieved t and re. In this study, we use the Taylor expansion of a two-variable function to understand and quantify the impacts of sub-pixel variances of VIS/NIR and SWIR cloud reflectances and their covariance on the t and re retrievals. This framework takes into account the fact that the retrievals are determined by both VIS/NIR and SWIR band observations in a mutually dependent way. In comparison with previous studies, it provides a more comprehensive understanding of how sub-pixel cloud reflectance variations impact the t and re retrievals based on the bi-spectral method. In particular, our framework provides a mathematical explanation of how the sub-pixel variation in VIS/NIR band influences the re retrieval and why it can sometimes outweigh the influence of variations in the SWIR band and dominate the error in re retrievals, leading to a potential contribution of positive bias to the re retrieval.

Cloud-top height retrieval from polarizing remote sensor POLDER

NASA Astrophysics Data System (ADS)

He, Xianqiang; Pan, Delu; Yan, Bai; Mao, Zhihua

2006-10-01

A new cloud-top height retrieval method is proposed by using polarizing remote sensing. In cloudy conditions, it shows that, in purple and blue bands, linear polarizing radiance at the top-of-atmosphere (TOA) is mainly contributed by Rayleigh scattering of the atmosphere's molecules above cloud, and the contribution by cloud reflection and aerosol scattering can be neglected. With such characteristics, the basis principle and method of cloud-top height retrieval using polarizing remote sensing are presented in detail, and tested by the polarizing remote sensing data of POLDER. The satellite-derived cloud-top height product can not only show the distribution of global cloud-top height, but also obtain the cloud-top height distribution of moderate-scale meteorological phenomena like hurricanes and typhoons. This new method is promising to become the operational algorithm for cloud-top height retrieval for POLDER and the future polarizing remote sensing satellites.

Infrared cloud imaging in support of Earth-space optical communication.

PubMed

Nugent, Paul W; Shaw, Joseph A; Piazzolla, Sabino

2009-05-11

The increasing need for high data return from near-Earth and deep-space missions is driving a demand for the establishment of Earth-space optical communication links. These links will require a nearly obstruction-free path to the communication platform, so there is a need to measure spatial and temporal statistics of clouds at potential ground-station sites. A technique is described that uses a ground-based thermal infrared imager to provide continuous day-night cloud detection and classification according to the cloud optical depth and potential communication channel attenuation. The benefit of retrieving cloud optical depth and corresponding attenuation is illustrated through measurements that identify cloudy times when optical communication may still be possible through thin clouds.

EPIC/DSCOVR's Oxygen Absorption Channels: A Cloud Profiling Information Content Analysis

NASA Astrophysics Data System (ADS)

Davis, A. B.; Merlin, G.; Labonnote, L. C.; Cornet, C.; Dubuisson, P.; Ferlay, N.; Parol, F.; Riedi, J.; Yang, Y.

2016-12-01

EPIC/DSCOVR has several spectral channels dedicated to cloud characterization, most notably O2 A- and B-band. Differential optical absorption spectroscopy (DOAS) ratios of in-band and reference channels are less prone to calibration error than the 4 individual signals. Using these ratios, we have replicated for mono-directional (quasi-backscattering) EPIC observations the recent cloud information content analysis by Merlin et al. (AMT-D,8:12709-12758,2015) that was focused on A-band-only but multi-angle observations by POLDER in the past, by AirMSPI in the present, and by 3MI and MAIA in the future. The methodology is based on extensive forward 1D radiative transfer (RT) computations using the ARTDECO model that implements a k-distribution technique for the absorbing (in-band) channels. These synthetic signals are combined into a Bayesian Rodgers-type framework for estimating posterior uncertainty on retrieved quantities. Recall that this formalism calls explicitly for: (1) estimates of instrument error, and (2) prior uncertainty on the retrieved quantities, to which we add (3) reasonable estimates of uncertainty in the non- or otherwise-retrieved properties. Wide ranges of cloud top heights (CTHs) and cloud geometrical thicknesses (CGTs) are examined for a representative selection of cloud optical thicknesses (COTs), solar angles, and surface reflectances. We found that CTH should be reliably retrieved from EPIC data under most circumstances as long as COT can be inferred from non-absorbing channels, and the bias from in-cloud absorption is removed. However, CGT will be hard to determine unless CTH is constrained by independent means. EPIC has several UV channels that could be brought to bear. These findings conflict those of Yang et al. (JQSRT,122:141-149,2013), so we also revisit that more preliminary study that did not account for a realistic level of residual instrument noise in the DOAS ratios. In conclusion, we believe that the present information content analysis will inform the EPIC/DSCOVR Level 2 algorithm development team about what cloud properties to target using the A/B-band channels, depending on the availability of other cloud information.

Coupled retrieval of water cloud and above-cloud aerosol properties using the Airborne Multiangle SpectroPolarimetric Imager (AirMSPI)

NASA Astrophysics Data System (ADS)

Xu, F.; van Harten, G.; Diner, D. J.; Rheingans, B. E.; Tosca, M.; Seidel, F. C.; Bull, M. A.; Tkatcheva, I. N.; McDuffie, J. L.; Garay, M. J.; Davis, A. B.; Jovanovic, V. M.; Brian, C.; Alexandrov, M. D.; Hostetler, C. A.; Ferrare, R. A.; Burton, S. P.

2017-12-01

The Airborne Multiangle SpectroPolarimetric Imager (AirMSPI) has been flying aboard the NASA ER-2 high altitude aircraft since October 2010. AirMSPI acquires radiance and polarization data in bands centered at 355, 380, 445, 470*, 555, 660*, 865*, and 935 nm (*denotes polarimetric bands). In sweep mode, georectified images cover an area of 80-100 km (along track) by 10-25 km (across track) between ±66° off nadir, with a map-projected spatial resolution of 25 meters. An efficient and flexible retrieval algorithm has been developed using AirMSPI polarimetric bands for simultaneous retrieval of cloud and above-cloud aerosol microphysical properties. We design a three-step retrieval approach, namely 1) estimating effective droplet size distribution using polarimetric cloudbow observations and using it as initial guess for Step 2; 2) combining water cloud and aerosol above cloud retrieval by fitting polarimetric signals at all scattering angles (e.g. from 80° to 180°); and 3) constructing a lookup table of radiance for a set of cloud optical depth grids using aerosol and cloud information retrieved from Step 2 and then estimating pixel-scale cloud optical depth based on 1D radiative transfer (RT) theory by fitting the AirMSPI radiance. Retrieval uncertainty is formulated by accounting for instrumental errors and constraints imposed on spectral variations of aerosol and cloud droplet optical properties. As the forward RT model, a hybrid approach is developed to combine the computational strengths of Markov-chain and adding-doubling methods to model polarized RT in a coupled aerosol, Rayleigh and cloud system. Our retrieval approach is tested using 134 AirMSPI datasets acquired during NASA ORACLES field campaign in 09/2016, with low to high aerosol loadings. For validation, the retrieved aerosol optical depths and cloud-top heights are compared to coincident High Spectral Resolution Lidar-2 (HSRL-2) data, and the droplet size parameters including effective radius and effective variance and cloud optical thickness are compared to coincident Research Scanning Polarimeter (RSP) data.

Comparison of Cloud Properties from CALIPSO-CloudSat and Geostationary Satellite Data

NASA Technical Reports Server (NTRS)

Nguyen, L.; Minnis, P.; Chang, F.; Winker, D.; Sun-Mack, S.; Spangenberg, D.; Austin, R.

2007-01-01

Cloud properties are being derived in near-real time from geostationary satellite imager data for a variety of weather and climate applications and research. Assessment of the uncertainties in each of the derived cloud parameters is essential for confident use of the products. Determination of cloud amount, cloud top height, and cloud layering is especially important for using these real -time products for applications such as aircraft icing condition diagnosis and numerical weather prediction model assimilation. Furthermore, the distribution of clouds as a function of altitude has become a central component of efforts to evaluate climate model cloud simulations. Validation of those parameters has been difficult except over limited areas where ground-based active sensors, such as cloud radars or lidars, have been available on a regular basis. Retrievals of cloud properties are sensitive to the surface background, time of day, and the clouds themselves. Thus, it is essential to assess the geostationary satellite retrievals over a variety of locations. The availability of cloud radar data from CloudSat and lidar data from CALIPSO make it possible to perform those assessments over each geostationary domain at 0130 and 1330 LT. In this paper, CloudSat and CALIPSO data are matched with contemporaneous Geostationary Operational Environmental Satellite (GOES), Multi-functional Transport Satellite (MTSAT), and Meteosat-8 data. Unlike comparisons with cloud products derived from A-Train imagers, this study considers comparisons of nadir active sensor data with off-nadir retrievals. These matched data are used to determine the uncertainties in cloud-top heights and cloud amounts derived from the geostationary satellite data using the Clouds and the Earth s Radiant Energy System (CERES) cloud retrieval algorithms. The CERES multi-layer cloud detection method is also evaluated to determine its accuracy and limitations in the off-nadir mode. The results will be useful for constraining the use of the passive retrieval data in models and for improving the accuracy of the retrievals.

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

NASA Technical Reports Server (NTRS)

Platnick, S.; Wind, G.

2004-01-01

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

The Validation of Cloud Retrieval Algorithms Using Synthetic Datasets

NASA Astrophysics Data System (ADS)

Kokhanovsky, Alexander; Fischer, Jurgen; Linstrot, Rasmus; Meirink, Jan Fokke; Poulsen, Caroline; Preusker, Rene; Siddans, Richard; Thomas, Gareth; Arnold, Chris; Grainger, Roy; Lilli, Luca; Rozanov, Vladimir

2012-11-01

We have performed the inter-comparison study of cloud property retrievals using algorithms initially developed for AATSR (ORAC, RAL-Oxford University), AVHRR and SEVIRI (CPP, KNMI), SCIAMACHY/GOME (SACURA, University of Bremen), and MERIS (ANNA, Free University of Berlin). The accuracy of retrievals of cloud optical thickness (COT), effective radius (ER) of droplets, and cloud top height (CTH) is discussed.

Estimating vertical profiles of water-cloud droplet effective radius from SWIR satellite measurements via a statistical model derived from CloudSat observations

NASA Astrophysics Data System (ADS)

Nagao, T. M.; Murakami, H.; Nakajima, T. Y.

2017-12-01

This study proposes an algorithm to estimate vertical profiles of cloud droplet effective radius (CDER-VP) for water clouds from shortwave infrared (SWIR) measurements of Himawari-8/AHI via a statistical model of CDER-VP derived from CloudSat observation. Several similar algorithms in previous studies utilize a spectral radiance matching on the assumption of simultaneous observations of CloudSat and Aqua/MODIS. However, our algorithm does not assume simultaneous observations with CloudSat. First, in advance, a database (DB) of CDER-VP is prepared by the following procedure: TOA radiances at 0.65, 2.3 and 10.4-μm bands of the AHI are simulated using CDER-VP and cloud optical depth vertical profile (COD-VP) contained in the CloudSat 2B-CWC-RVOD and 2B-TAU products. Cloud optical thickness (COT), Column-CDER and cloud top height (CTH) are retrieved from the simulated radiances using a traditional retrieval algorithm with vertically homogeneous cloud model (1-SWIR VHC method). The CDER-VP is added to the DB by using the COT and Column-CDER retrievals as a key of the DB. Then by using principal component (PC) analysis, up to three PC vectors of the CDER-VPs in the DB are extracted. Next, the algorithm retrieves CDER-VP from actual AHI measurements by the following procedure: First, COT, Column-CDER and CTH are retrieved from TOA radiances at 0.65, 2.3 and 10.4-μm bands of the AHI using by 1-SWIR VHC method. Then, the PC vectors of CDER-VP is fetched from the DB using the COT and Column-CDER retrievals as the key of the DB. Finally, using coefficients of the PC vectors of CDER-VP as variables for retrieval, CDER-VP, COT and CTH are retrieved from TOA radiances at 0.65, 1.6, 2.3, 3.9 and 10.4-μm bands of the AHI based on optimal estimation method with iterative radiative transfer calculation. The simulation result showed the CDER-VP retrieval errors were almost smaller than 3 - 4 μm. The CDER retrieval errors at the cloud base were almost larger than the others (e.g. CDER at cloud top), especially when COT and CDER was large. The tendency can be explained by less sensitivities of SWIRs to CDER at cloud base. Additionally, as a case study, this study will attempt to apply the algorithm to the AHI's high-frequency observations, and to interpret the time series of the CDER-VP retrievals in terms of temporal evolution of water clouds.

New approaches to removing cloud shadows and evaluating the 380 nm surface reflectance for improved aerosol optical thickness retrievals from the GOSAT/TANSO-Cloud and Aerosol Imager

NASA Astrophysics Data System (ADS)

Fukuda, Satoru; Nakajima, Teruyuki; Takenaka, Hideaki; Higurashi, Akiko; Kikuchi, Nobuyuki; Nakajima, Takashi Y.; Ishida, Haruma

2013-12-01

satellite aerosol retrieval algorithm was developed to utilize a near-ultraviolet band of the Greenhouse gases Observing SATellite/Thermal And Near infrared Sensor for carbon Observation (GOSAT/TANSO)-Cloud and Aerosol Imager (CAI). At near-ultraviolet wavelengths, the surface reflectance over land is smaller than that at visible wavelengths. Therefore, it is thought possible to reduce retrieval error by using the near-ultraviolet spectral region. In the present study, we first developed a cloud shadow detection algorithm that uses first and second minimum reflectances of 380 nm and 680 nm based on the difference in Rayleigh scattering contribution for these two bands. Then, we developed a new surface reflectance correction algorithm, the modified Kaufman method, which uses minimum reflectance data at 680 nm and the NDVI to estimate the surface reflectance at 380 nm. This algorithm was found to be particularly effective at reducing the aerosol effect remaining in the 380 nm minimum reflectance; this effect has previously proven difficult to remove owing to the infrequent sampling rate associated with the three-day recursion period of GOSAT and the narrow CAI swath of 1000 km. Finally, we applied these two algorithms to retrieve aerosol optical thicknesses over a land area. Our results exhibited better agreement with sun-sky radiometer observations than results obtained using a simple surface reflectance correction technique using minimum radiances.

Inference of Ice Cloud Properties from High-spectral Resolution Infrared Observations. Appendix 4

NASA Technical Reports Server (NTRS)

Huang, Hung-Lung; Yang, Ping; Wei, Heli; Baum, Bryan A.; Hu, Yongxiang; Antonelli, Paolo; Ackerman, Steven A.

2005-01-01

The theoretical basis is explored for inferring the microphysical properties of ice crystal from high-spectral resolution infrared observations. A radiative transfer model is employed to simulate spectral radiances to address relevant issues. The extinction and absorption efficiencies of individual ice crystals, assumed as hexagonal columns for large particles and droxtals for small particles, are computed from a combination of the finite- difference time-domain (FDTD) technique and a composite method. The corresponding phase functions are computed from a combination of FDTD and an improved geometric optics method (IGOM). Bulk scattering properties are derived by averaging the single- scattering properties of individual particles for 30 particle size distributions developed from in situ measurements and for additional four analytical Gamma size distributions for small particles. The non-sphericity of ice crystals is shown to have a significant impact on the radiative signatures in the infrared (IR) spectrum; the spherical particle approximation for inferring ice cloud properties may result in an overest&ation of the optical thickness and an inaccurate retrieval of effective particle size. Furthermore, we show that the error associated with the use of the Henyey-Greenstein phase function can be as larger as 1 K in terms of brightness temperature for larger particle effective size at some strong scattering wavenumbers. For small particles, the difference between the two phase functions is much less, with brightness temperatures generally differing by less than 0.4 K. The simulations undertaken in this study show that the slope of the IR brightness temperature spectrum between 790-960/cm is sensitive to the effective particle size. Furthermore, a strong sensitivity of IR brightness temperature to cloud optical thickness is noted within the l050-1250/cm region. Based on this spectral feature, a technique is presented for the simultaneous retrieval of the visible optical thickness and effective particle size from high spectral resolution infrared data under ice cloudy con&tion. The error analysis shows that the uncertainty of the retrieved optical thickness and effective particle size has a small range of variation. The error for retrieving particle size in conjunction with an uncertainty of 5 K in cloud'temperature, or a surface temperature uncertainty of 2.5 K, is less than 15%. The corresponding e m r in the uncertainty of optical thickness is within 5-2096, depending on the value of cloud optical thickness. The applicability of the technique is demonstrated using the aircraft-based High- resolution Interferometer Sounder (HIS) data from the Subsonic Aircraft: Contrail and Cloud Effects Special Study (SUCCESS) in 1996 and the First ISCCP Regional Experiment - Arctic Clouds Experiment (FIRE-ACE) in 1998.

Fast Simulators for Satellite Cloud Optical Centroid Pressure Retrievals, 1. Evaluation of OMI Cloud Retrievals

NASA Technical Reports Server (NTRS)

Joiner, J.; Vasilkov, A. P.; Gupta, Pawan; Bhartia, P. K.; Veefkind, Pepijn; Sneep, Maarten; deHaan, Johan; Polonsky, Igor; Spurr, Robert

2011-01-01

We have developed a relatively simple scheme for simulating retrieved cloud optical centroid pressures (OCP) from satellite solar backscatter observations. We have compared simulator results with those from more detailed retrieval simulators that more fully account for the complex radiative transfer in a cloudy atmosphere. We used this fast simulator to conduct a comprehensive evaluation of cloud OCPs from the two OMI algorithms using collocated data from CloudSat and Aqua MODIS, a unique situation afforded by the A-train formation of satellites. We find that both OMI algorithms perform reasonably well and that the two algorithms agree better with each other than either does with the collocated CloudSat data. This indicates that patchy snow/ice, cloud 3D, and aerosol effects not simulated with the CloudSat data are affecting both algorithms similarly. We note that the collocation with CloudSat occurs mainly on the East side of OMI's swath. Therefore, we are not able to address cross-track biases in OMI cloud OCP retrievals. Our fast simulator may also be used to simulate cloud OCP from output generated by general circulation models (GCM) with appropriate account of cloud overlap. We have implemented such a scheme and plan to compare OMI data with GCM output in the near future.

Cloud Properties of CERES-MODIS Edition 4 and CERES-VIIRS Edition 1

NASA Technical Reports Server (NTRS)

Sun-Mack, Sunny; Minnis, Patrick; Chang, Fu-Lung; Hong, Gang; Arduini, Robert; Chen, Yan; Trepte, Qing; Yost, Chris; Smith, Rita; Brown, Ricky;

Diabatic forcing and intialization with assimilation of cloud water and rainwater in a forecast model

NASA Technical Reports Server (NTRS)

Raymond, William H.; Olson, William S.; Callan, Geary

1995-01-01

In this study, diabatic forcing, and liquid water assimilation techniques are tested in a semi-implicit hydrostatic regional forecast model containing explicit representations of grid-scale cloud water and rainwater. Diabatic forcing, in conjunction with diabatic contributions in the initialization, is found to help the forecast retain the diabatic signal found in the liquid water or heating rate data, consequently reducing the spinup time associated with grid-scale precipitation processes. Both observational Special Sensor Microwave/Imager (SSM/I) and model-generated data are used. A physical retrieval method incorporating SSM/I radiance data is utilized to estimate the 3D distribution of precipitating storms. In the retrieval method the relationship between precipitation distributions and upwelling microwave radiances is parameterized, based upon cloud ensemble-radiative model simulations. Regression formulae relating vertically integrated liquid and ice-phase precipitation amounts to latent heating rates are also derived from the cloud ensemble simulations. Thus, retrieved SSM/I precipitation structures can be used in conjunction with the regression-formulas to infer the 3D distribution of latent heating rates. These heating rates are used directly in the forecast model to help initiate Tropical Storm Emily (21 September 1987). The 14-h forecast of Emily's development yields atmospheric precipitation water contents that compare favorably with coincident SSM/I estimates.

Cloud Liquid Water Path Comparisons from Passive Microwave and Solar Reflectance Satellite Measurements: Assessment of Sub-Field-of-View Cloud Effects in Microwave Retrievals

NASA Technical Reports Server (NTRS)

Greenwald, Thomas J.; Christopher, Sundar A.; Chou, Joyce

1997-01-01

Satellite observations of the cloud liquid water path (LWP) are compared from special sensor microwave imager (SSM/I) measurements and GOES 8 imager solar reflectance (SR) measurements to ascertain the impact of sub-field-of-view (FOV) cloud effects on SSM/I 37 GHz retrievals. The SR retrievals also incorporate estimates of the cloud droplet effective radius derived from the GOES 8 3.9-micron channel. The comparisons consist of simultaneous collocated and full-resolution measurements and are limited to nonprecipitating marine stratocumulus in the eastern Pacific for two days in October 1995. The retrievals from these independent methods are consistent for overcast SSM/I FOVS, with RMS differences as low as 0.030 kg/sq m, although biases exist for clouds with more open spatial structure, where the RMS differences increase to 0.039 kg/sq m. For broken cloudiness within the SSM/I FOV the average beam-filling error (BFE) in the microwave retrievals is found to be about 22% (average cloud amount of 73%). This systematic error is comparable with the average random errors in the microwave retrievals. However, even larger BFEs can be expected for individual FOVs and for regions with less cloudiness. By scaling the microwave retrievals by the cloud amount within the FOV, the systematic BFE can be significantly reduced but with increased RMS differences of O.046-0.058 kg/sq m when compared to the SR retrievals. The beam-filling effects reported here are significant and are expected to impact directly upon studies that use instantaneous SSM/I measurements of cloud LWP, such as cloud classification studies and validation studies involving surface-based or in situ data.

Microwave Ground-Based Retrievals of Liquid Water Path in Drizzling Clouds: Challenges and Possibilities

NASA Astrophysics Data System (ADS)

Cadeddu, M. P.; Marchand, R.; Orlandi, E.; Turner, D. D.; Mech, M.

2016-12-01

The retrieval of liquid water path (LWP) during drizzle and rain from ground-based microwave radiometers presents several challenges that have not been entirely solved. Ground-based microwave radiometers have been traditionally used to retrieve cloud LWP assuming non-precipitating conditions. Yet retrieval of liquid water path under light rain and possibly the partition of total liquid water path among cloud and rain are very important to study cloud properties because the presence of drizzle affects for example the cloud's lifetime. Improving the LWP retrieval during drizzle and possibly partitioning cloud and rain LWP is therefore highly desirable. In precipitating clouds the raindrop's size is of the same order of magnitude of the wavelength sampled by the instrument and the effects of hydrometeor's scattering can't be neglected. In this paper we model the effect of scattering hydrometeors on radiometric brightness temperatures commonly used in LWP retrievals and develop a physical retrieval to derive precipitable water vapor (PWV), total LWP, and the fraction of cloud and rain liquid water (Cf) from microwave brightness temperatures at three commonly used frequencies. The retrieval is first applied to a set of synthetic measurements and is then used to retrieve PWV, LWP, and Cf in two drizzling cases at the Atmospheric Radiation Measurement (ARM) Program Eastern North Atlantic (ENA) site. Results show that there is useful information in the microwave brightness temperatures that can be used to reduce LWP retrieval uncertainty during light rain and can open the path for a better integration of active and passive sensors. The effect of raindrops on the radiometer's lens is examined with the help of a digital camera and experimental data. A possible way to account for raindrop deposition on the instrument's lens is suggested.

Using Ground-Based Measurements and Retrievals to Validate Satellite Data

NASA Technical Reports Server (NTRS)

Dong, Xiquan

2002-01-01

The proposed research is to use the DOE ARM ground-based measurements and retrievals as the ground-truth references for validating satellite cloud results and retrieving algorithms. This validation effort includes four different ways: (1) cloud properties on different satellites, therefore different sensors, TRMM VIRS and TERRA MODIS; (2) cloud properties at different climatic regions, such as DOE ARM SGP, NSA, and TWP sites; (3) different cloud types, low and high level cloud properties; and (4) day and night retrieving algorithms. Validation of satellite-retrieved cloud properties is very difficult and a long-term effort because of significant spatial and temporal differences between the surface and satellite observing platforms. The ground-based measurements and retrievals, only carefully analyzed and validated, can provide a baseline for estimating errors in the satellite products. Even though the validation effort is so difficult, a significant progress has been made during the proposed study period, and the major accomplishments are summarized in the follow.

Retrieval of Absorbing Aerosols Above Clouds retrieval over the South East Atlantic Ocean from MSG/SEVIRI

NASA Astrophysics Data System (ADS)

Peers, F.; Haywood, J. M.; Francis, P. N.; Meyer, K.; Platnick, S. E.

2017-12-01

Over the South East Atlantic Ocean, biomass burning aerosols from Southern Africa are frequently observed above clouds during fire season. However, the quantification of their interactions with both radiations and clouds remains uncertain because of a lack of information on aerosol properties and on their interaction process. In the last decade, methods have been developed to retrieve aerosol optical properties above clouds from satellite measurements, especially over the South East Atlantic Ocean. Most of these methods have been applied to polar orbiting instruments which prevent the analysis of aerosols and clouds at a sub-daily scale. With its wide spatial coverage and its high temporal resolution, the geostationary instrument SEVIRI, on board the MSG platform, offers a unique opportunity to monitor aerosols in this region and to evaluate their impact on clouds and their radiative effects. In this study, we will investigate the possibility of retrieving simultaneously aerosol and cloud properties (i.e. aerosol and cloud optical thicknesses and cloud droplet effective radius) when aerosols are located above clouds. The retrieved properties will then be compared with the ones obtained from MODIS [Meyer et al., 2015] as well as observations from the CLARIFY-2017 field campaign.

A climate index indicative of cloudiness derived from satellite infrared sounder data

NASA Technical Reports Server (NTRS)

Abel, M. D.; Cox, S. K.

1981-01-01

In many current studies conducted to enhance the usefulness of meteorological satellite radiance data, one common objective is to infer conventional weather variables. The present investigation, on the other hand, is mainly concerned with the efficient retrieval (minimization of errors) of a nonstandard atmospheric descriptor. The atmosphere's Vertical Infrared Radiative Emitting Structure (VIRES) is retrieved. VIRES is described by the broadband infrared weighting function curve. The shapes of these weighting curves are primarily a function of the three-dimensional cloud structure. The weighting curves are retrieved by a method which uses satellite spectral radiance data. The basic theory involved in the VIRES retrieval procedure parallels the technique used to retrieve temperature soundings.

A framework based on 2-D Taylor expansion for quantifying the impacts of subpixel reflectance variance and covariance on cloud optical thickness and effective radius retrievals based on the bispectral method

NASA Astrophysics Data System (ADS)

Zhang, Z.; Werner, F.; Cho, H.-M.; Wind, G.; Platnick, S.; Ackerman, A. S.; Di Girolamo, L.; Marshak, A.; Meyer, K.

2016-06-01

The bispectral method retrieves cloud optical thickness (τ) and cloud droplet effective radius (re) simultaneously from a pair of cloud reflectance observations, one in a visible or near-infrared (VIS/NIR) band and the other in a shortwave infrared (SWIR) band. A cloudy pixel is usually assumed to be horizontally homogeneous in the retrieval. Ignoring subpixel variations of cloud reflectances can lead to a significant bias in the retrieved τ and re. In the literature, the retrievals of τ and re are often assumed to be independent and considered separately when investigating the impact of subpixel cloud reflectance variations on the bispectral method. As a result, the impact on τ is contributed only by the subpixel variation of VIS/NIR band reflectance and the impact on re only by the subpixel variation of SWIR band reflectance. In our new framework, we use the Taylor expansion of a two-variable function to understand and quantify the impacts of subpixel variances of VIS/NIR and SWIR cloud reflectances and their covariance on the τ and re retrievals. This framework takes into account the fact that the retrievals are determined by both VIS/NIR and SWIR band observations in a mutually dependent way. In comparison with previous studies, it provides a more comprehensive understanding of how subpixel cloud reflectance variations impact the τ and re retrievals based on the bispectral method. In particular, our framework provides a mathematical explanation of how the subpixel variation in VIS/NIR band influences the re retrieval and why it can sometimes outweigh the influence of variations in the SWIR band and dominate the error in re retrievals, leading to a potential contribution of positive bias to the re retrieval. We test our framework using synthetic cloud fields from a large-eddy simulation and real observations from Moderate Resolution Imaging Spectroradiometer. The predicted results based on our framework agree very well with the numerical simulations. Our framework can be used to estimate the retrieval uncertainty from subpixel reflectance variations in operational satellite cloud products and to help understand the differences in τ and re retrievals between two instruments.

A Framework Based on 2-D Taylor Expansion for Quantifying the Impacts of Sub-Pixel Reflectance Variance and Covariance on Cloud Optical Thickness and Effective Radius Retrievals Based on the Bi-Spectral Method

NASA Technical Reports Server (NTRS)

Zhang, Z.; Werner, F.; Cho, H. -M.; Wind, G.; Platnick, S.; Ackerman, A. S.; Di Girolamo, L.; Marshak, A.; Meyer, Kerry

2016-01-01

The bi-spectral method retrieves cloud optical thickness and cloud droplet effective radius simultaneously from a pair of cloud reflectance observations, one in a visible or near-infrared (VISNIR) band and the other in a shortwave infrared (SWIR) band. A cloudy pixel is usually assumed to be horizontally homogeneous in the retrieval. Ignoring sub-pixel variations of cloud reflectances can lead to a significant bias in the retrieved and re. In the literature, the retrievals of and re are often assumed to be independent and considered separately when investigating the impact of sub-pixel cloud reflectance variations on the bi-spectral method. As a result, the impact on is contributed only by the sub-pixel variation of VISNIR band reflectance and the impact on re only by the sub-pixel variation of SWIR band reflectance. In our new framework, we use the Taylor expansion of a two-variable function to understand and quantify the impacts of sub-pixel variances of VISNIR and SWIR cloud reflectances and their covariance on the and re retrievals. This framework takes into account the fact that the retrievals are determined by both VISNIR and SWIR band observations in a mutually dependent way. In comparison with previous studies, it provides a more comprehensive understanding of how sub-pixel cloud reflectance variations impact the and re retrievals based on the bi-spectral method. In particular, our framework provides a mathematical explanation of how the sub-pixel variation in VISNIR band influences the re retrieval and why it can sometimes outweigh the influence of variations in the SWIR band and dominate the error in re retrievals, leading to a potential contribution of positive bias to the re retrieval. We test our framework using synthetic cloud fields from a large-eddy simulation and real observations from Moderate Resolution Imaging Spectroradiometer. The predicted results based on our framework agree very well with the numerical simulations. Our framework can be used to estimate the retrieval uncertainty from sub-pixel reflectance variations in operational satellite cloud products and to help understand the differences in and re retrievals between two instruments.

A Framework Based on 2-D Taylor Expansion for Quantifying the Impacts of Subpixel Reflectance Variance and Covariance on Cloud Optical Thickness and Effective Radius Retrievals Based on the Bispectral Method

NASA Technical Reports Server (NTRS)

Zhang, Z.; Werner, F.; Cho, H.-M.; Wind, G.; Platnick, S.; Ackerman, A. S.; Di Girolamo, L.; Marshak, A.; Meyer, K.

2016-01-01

The bispectral method retrieves cloud optical thickness (t) and cloud droplet effective radius (re) simultaneously from a pair of cloud reflectance observations, one in a visible or near-infrared (VIS/NIR) band and the other in a shortwave infrared (SWIR) band. A cloudy pixel is usually assumed to be horizontally homogeneous in the retrieval. Ignoring subpixel variations of cloud reflectances can lead to a significant bias in the retrieved t and re. In the literature, the retrievals of t and re are often assumed to be independent and considered separately when investigating the impact of subpixel cloud reflectance variations on the bispectral method. As a result, the impact on t is contributed only by the subpixel variation of VIS/NIR band reflectance and the impact on re only by the subpixel variation of SWIR band reflectance. In our new framework, we use the Taylor expansion of a two-variable function to understand and quantify the impacts of subpixel variances of VIS/NIR and SWIR cloud reflectances and their covariance on the t and re retrievals. This framework takes into account the fact that the retrievals are determined by both VIS/NIR and SWIR band observations in a mutually dependent way. In comparison with previous studies, it provides a more comprehensive understanding of how subpixel cloud reflectance variations impact the t and re retrievals based on the bispectral method. In particular, our framework provides a mathematical explanation of how the subpixel variation in VIS/NIR band influences the re retrieval and why it can sometimes outweigh the influence of variations in the SWIR band and dominate the error in re retrievals, leading to a potential contribution of positive bias to the re retrieval. We test our framework using synthetic cloud fields from a large-eddy simulation and real observations from Moderate Resolution Imaging Spectroradiometer. The predicted results based on our framework agree very well with the numerical simulations. Our framework can be used to estimate the retrieval uncertainty from subpixel reflectance variations in operational satellite cloud products and to help understand the differences in t and re retrievals between two instruments.

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.

Vertical air motion retrievals in deep convective clouds using the ARM scanning radar network in Oklahoma during MC3E

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

North, Kirk W.; Oue, Mariko; Kollias, Pavlos

The US Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program's Southern Great Plains (SGP) site includes a heterogeneous distributed scanning Doppler radar network suitable for collecting coordinated Doppler velocity measurements in deep convective clouds. The surrounding National Weather Service (NWS) Next Generation Weather Surveillance Radar 1988 Doppler (NEXRAD WSR-88D) further supplements this network. Radar velocity measurements are assimilated in a three-dimensional variational (3DVAR) algorithm that retrieves horizontal and vertical air motions over a large analysis domain (100 km × 100 km) at storm-scale resolutions (250 m). For the first time, direct evaluation of retrieved vertical air velocities with thosemore » from collocated 915 MHz radar wind profilers is performed. Mean absolute and root-mean-square differences between the two sources are of the order of 1 and 2 m s -1, respectively, and time–height correlations are of the order of 0.5. An empirical sensitivity analysis is done to determine a range of 3DVAR constraint weights that adequately satisfy the velocity observations and anelastic mass continuity. It is shown that the vertical velocity spread over this range is of the order of 1 m s -1. The 3DVAR retrievals are also compared to those obtained from an iterative upwards integration technique. Lastly, the results suggest that the 3DVAR technique provides a robust, stable solution for cases in which integration techniques have difficulty satisfying velocity observations and mass continuity simultaneously.« less

Vertical air motion retrievals in deep convective clouds using the ARM scanning radar network in Oklahoma during MC3E

DOE PAGES

North, Kirk W.; Oue, Mariko; Kollias, Pavlos; ...

2017-08-04

The US Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program's Southern Great Plains (SGP) site includes a heterogeneous distributed scanning Doppler radar network suitable for collecting coordinated Doppler velocity measurements in deep convective clouds. The surrounding National Weather Service (NWS) Next Generation Weather Surveillance Radar 1988 Doppler (NEXRAD WSR-88D) further supplements this network. Radar velocity measurements are assimilated in a three-dimensional variational (3DVAR) algorithm that retrieves horizontal and vertical air motions over a large analysis domain (100 km × 100 km) at storm-scale resolutions (250 m). For the first time, direct evaluation of retrieved vertical air velocities with thosemore » from collocated 915 MHz radar wind profilers is performed. Mean absolute and root-mean-square differences between the two sources are of the order of 1 and 2 m s -1, respectively, and time–height correlations are of the order of 0.5. An empirical sensitivity analysis is done to determine a range of 3DVAR constraint weights that adequately satisfy the velocity observations and anelastic mass continuity. It is shown that the vertical velocity spread over this range is of the order of 1 m s -1. The 3DVAR retrievals are also compared to those obtained from an iterative upwards integration technique. Lastly, the results suggest that the 3DVAR technique provides a robust, stable solution for cases in which integration techniques have difficulty satisfying velocity observations and mass continuity simultaneously.« less

Evaluating cloud retrieval algorithms with the ARM BBHRP framework

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

Mlawer,E.; Dunn,M.; Mlawer, E.

2008-03-10

Climate and weather prediction models require accurate calculations of vertical profiles of radiative heating. Although heating rate calculations cannot be directly validated due to the lack of corresponding observations, surface and top-of-atmosphere measurements can indirectly establish the quality of computed heating rates through validation of the calculated irradiances at the atmospheric boundaries. The ARM Broadband Heating Rate Profile (BBHRP) project, a collaboration of all the working groups in the program, was designed with these heating rate validations as a key objective. Given the large dependence of radiative heating rates on cloud properties, a critical component of BBHRP radiative closure analysesmore » has been the evaluation of cloud microphysical retrieval algorithms. This evaluation is an important step in establishing the necessary confidence in the continuous profiles of computed radiative heating rates produced by BBHRP at the ARM Climate Research Facility (ACRF) sites that are needed for modeling studies. This poster details the continued effort to evaluate cloud property retrieval algorithms within the BBHRP framework, a key focus of the project this year. A requirement for the computation of accurate heating rate profiles is a robust cloud microphysical product that captures the occurrence, height, and phase of clouds above each ACRF site. Various approaches to retrieve the microphysical properties of liquid, ice, and mixed-phase clouds have been processed in BBHRP for the ACRF Southern Great Plains (SGP) and the North Slope of Alaska (NSA) sites. These retrieval methods span a range of assumptions concerning the parameterization of cloud location, particle density, size, shape, and involve different measurement sources. We will present the radiative closure results from several different retrieval approaches for the SGP site, including those from Microbase, the current 'reference' retrieval approach in BBHRP. At the NSA, mixed-phase clouds and cloud with a low optical depth are prevalent; the radiative closure studies using Microbase demonstrated significant residuals. As an alternative to Microbase at NSA, the Shupe-Turner cloud property retrieval algorithm, aimed at improving the partitioning of cloud phase and incorporating more constrained, conditional microphysics retrievals, also has been evaluated using the BBHRP data set.« less

Cirrus Cloud Optical and Microphysical Property Retrievals from eMAS During SEAC4RS Using Bi-Spectral Reflectance Measurements Within the 1.88 micron Water Vapor Absorption Band

NASA Technical Reports Server (NTRS)

Meyer, K.; Platnick, S.; Arnold, G. T.; Holz, R. E.; Veglio, P.; Yorks, J.; Wang, C.

2016-01-01

Previous bi-spectral imager retrievals of cloud optical thickness (COT) and effective particle radius (CER) based on the Nakajima and King (1990) approach, such as those of the operational MODIS cloud optical property retrieval product (MOD06), have typically paired a non-absorbing visible or near-infrared wavelength, sensitive to COT, with an absorbing shortwave or midwave infrared wavelength sensitive to CER. However, in practice it is only necessary to select two spectral channels that exhibit a strong contrast in cloud particle absorption. Here it is shown, using eMAS observations obtained during NASAs SEAC4RS field campaign, that selecting two absorbing wavelength channels within the broader 1.88 micron water vapor absorption band, namely the 1.83 and 1.93 micron channels that have sufficient differences in ice crystal single scattering albedo, can yield COT and CER retrievals for thin to moderately thick single-layer cirrus that are reasonably consistent with other solar and IR imager-based and lidar-based retrievals. A distinct advantage of this channel selection for cirrus cloud retrievals is that the below cloud water vapor absorption minimizes the surface contribution to measured cloudy TOA reflectance, in particular compared to the solar window channels used in heritage retrievals such as MOD06. This reduces retrieval uncertainty resulting from errors in the surface reflectance assumption, as well as reduces the frequency of retrieval failures for thin cirrus clouds.

Cirrus cloud optical and microphysical property retrievals from eMAS during SEAC4RS using bi-spectral reflectance measurements within the 1.88 µm water vapor absorption band

NASA Astrophysics Data System (ADS)

Meyer, Kerry; Platnick, Steven; Arnold, G. Thomas; Holz, Robert E.; Veglio, Paolo; Yorks, John; Wang, Chenxi

2016-04-01

Previous bi-spectral imager retrievals of cloud optical thickness (COT) and effective particle radius (CER) based on the Nakajima and King (1990) approach, such as those of the operational MODIS cloud optical property retrieval product (MOD06), have typically paired a non-absorbing visible or near-infrared wavelength, sensitive to COT, with an absorbing shortwave or mid-wave infrared wavelength sensitive to CER. However, in practice it is only necessary to select two spectral channels that exhibit a strong contrast in cloud particle absorption. Here it is shown, using eMAS observations obtained during NASA's SEAC4RS field campaign, that selecting two absorbing wavelength channels within the broader 1.88 µm water vapor absorption band, namely the 1.83 and 1.93 µm channels that have sufficient differences in ice crystal single scattering albedo, can yield COT and CER retrievals for thin to moderately thick single-layer cirrus that are reasonably consistent with other solar and IR imager-based and lidar-based retrievals. A distinct advantage of this channel selection for cirrus cloud retrievals is that the below-cloud water vapor absorption minimizes the surface contribution to measured cloudy top-of-atmosphere reflectance, in particular compared to the solar window channels used in heritage retrievals such as MOD06. This reduces retrieval uncertainty resulting from errors in the surface reflectance assumption and reduces the frequency of retrieval failures for thin cirrus clouds.

Joint retrievals of cloud and drizzle in marine boundary layer clouds using ground-based radar, lidar and zenith radiances

DOE PAGES

Fielding, M. D.; Chiu, J. C.; Hogan, R. J.; ...

2015-07-02

Active remote sensing of marine boundary-layer clouds is challenging as drizzle drops often dominate the observed radar reflectivity. We present a new method to simultaneously retrieve cloud and drizzle vertical profiles in drizzling boundary-layer clouds using surface-based observations of radar reflectivity, lidar attenuated backscatter, and zenith radiances under conditions when precipitation does not reach the surface. Specifically, the vertical structure of droplet size and water content of both cloud and drizzle is characterised throughout the cloud. An ensemble optimal estimation approach provides full error statistics given the uncertainty in the observations. To evaluate the new method, we first perform retrievalsmore » using synthetic measurements from large-eddy simulation snapshots of cumulus under stratocumulus, where cloud water path is retrieved with an error of 31 g m -2. The method also performs well in non-drizzling clouds where no assumption of the cloud profile is required. We then apply the method to observations of marine stratocumulus obtained during the Atmospheric Radiation Measurement MAGIC deployment in the Northeast Pacific. Here, retrieved cloud water path agrees well with independent three-channel microwave radiometer retrievals, with a root mean square difference of 10–20 g m -2.« less

Optical properties of aerosol contaminated cloud derived from MODIS instrument

NASA Astrophysics Data System (ADS)

Mei, Linlu; Rozanov, Vladimir; Lelli, Luca; Vountas, Marco; Burrows, John P.

2016-04-01

The presence of absorbing aerosols above/within cloud can reduce the amount of up-welling radiation in visible (VIS) and short-wave infrared and darken the spectral reflectance when compared with a spectrum of a clean cloud observed by satellite instruments (Jethva et al., 2013). Cloud properties retrieval for aerosol contaminated cases is a great challenge. Even small additional injection of aerosol particles into clouds in the cleanest regions of Earth's atmosphere will cause significant effect on those clouds and on climate forcing (Koren et al., 2014; Rosenfeld et al., 2014) because the micro-physical cloud process are non-linear with respect to the aerosol loading. The current cloud products like Moderate Resolution Imaging Spectroradiometer (MODIS) ignoring the aerosol effect for the retrieval, which may cause significant error in the satellite-derived cloud properties. In this paper, a new cloud properties retrieval method, considering aerosol effect, based on the weighting-function (WF) method, is presented. The retrieval results shows that the WF retrieved cloud properties (e.g COT) agrees quite well with MODIS COT product for relative clear atmosphere (AOT ≤ 0.4) while there is a large difference for large aerosol loading. The MODIS COT product is underestimated for at least 2 - 3 times for AOT>0.4, and this underestimation increases with the increase of AOT.

Determination of Ice Water Path in Ice-over-Water Cloud Systems Using Combined MODIS and AMSR-E Measurements

NASA Technical Reports Server (NTRS)

Huang, Jianping; Minnis, Patrick; Lin, Bing; Yi, Yuhong; Fan, T.-F.; Sun-Mack, Sunny; Ayers, J. K.

2006-01-01

To provide more accurate ice cloud properties for evaluating climate models, the updated version of multi-layered cloud retrieval system (MCRS) is used to retrieve ice water path (IWP) in ice-over-water cloud systems over global ocean using combined instrument data from the Aqua satellite. The liquid water path (LWP) of lower layer water clouds is estimated from the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) measurements. With the lower layer LWP known, the properties of the upper-level ice clouds are then derived from Moderate Resolution Imaging Spectroradiometer measurements by matching simulated radiances from a two-cloud layer radiative transfer model. Comparisons with single-layer cirrus systems and surface-based radar retrievals show that the MCRS can significantly improve the accuracy and reduce the over-estimation of optical depth and ice water path retrievals for ice over-water cloud systems. During the period from December 2004 through February 2005, the mean daytime ice cloud optical depth and IWP for overlapped ice-over-water clouds over ocean from Aqua are 7.6 and 146.4 gm(sup -2), respectively, significantly less than the initial single layer retrievals of 17.3 and 322.3 gm(sup -2). The mean IWP for actual single-layer clouds was 128.2 gm(sup -2).

Impact of cloud horizontal inhomogeneity and directional sampling on the retrieval of cloud droplet size by the POLDER instrument

NASA Astrophysics Data System (ADS)

Shang, H.; Chen, L.; Bréon, F. M.; Letu, H.; Li, S.; Wang, Z.; Su, L.

2015-11-01

The principles of cloud droplet size retrieval via Polarization and Directionality of the Earth's Reflectance (POLDER) requires that clouds be horizontally homogeneous. The retrieval is performed by combining all measurements from an area of 150 km × 150 km to compensate for POLDER's insufficient directional sampling. Using POLDER-like data simulated with the RT3 model, we investigate the impact of cloud horizontal inhomogeneity and directional sampling on the retrieval and analyze which spatial resolution is potentially accessible from the measurements. Case studies show that the sub-grid-scale variability in droplet effective radius (CDR) can significantly reduce valid retrievals and introduce small biases to the CDR (~ 1.5 μm) and effective variance (EV) estimates. Nevertheless, the sub-grid-scale variations in EV and cloud optical thickness (COT) only influence the EV retrievals and not the CDR estimate. In the directional sampling cases studied, the retrieval using limited observations is accurate and is largely free of random noise. Several improvements have been made to the original POLDER droplet size retrieval. For example, measurements in the primary rainbow region (137-145°) are used to ensure retrievals of large droplet (> 15 μm) and to reduce the uncertainties caused by cloud heterogeneity. We apply the improved method using the POLDER global L1B data from June 2008, and the new CDR results are compared with the operational CDRs. The comparison shows that the operational CDRs tend to be underestimated for large droplets because the cloudbow oscillations in the scattering angle region of 145-165° are weak for cloud fields with CDR > 15 μm. Finally, a sub-grid-scale retrieval case demonstrates that a higher resolution, e.g., 42 km × 42 km, can be used when inverting cloud droplet size distribution parameters from POLDER measurements.

Cirrus cloud retrieval with MSG/SEVIRI using artificial neural networks

NASA Astrophysics Data System (ADS)

Strandgren, Johan; Bugliaro, Luca; Sehnke, Frank; Schröder, Leon

2017-09-01

Cirrus clouds play an important role in climate as they tend to warm the Earth-atmosphere system. Nevertheless their physical properties remain one of the largest sources of uncertainty in atmospheric research. To better understand the physical processes of cirrus clouds and their climate impact, enhanced satellite observations are necessary. In this paper we present a new algorithm, CiPS (Cirrus Properties from SEVIRI), that detects cirrus clouds and retrieves the corresponding cloud top height, ice optical thickness and ice water path using the SEVIRI imager aboard the geostationary Meteosat Second Generation satellites. CiPS utilises a set of artificial neural networks trained with SEVIRI thermal observations, CALIOP backscatter products, the ECMWF surface temperature and auxiliary data. CiPS detects 71 and 95 % of all cirrus clouds with an optical thickness of 0.1 and 1.0, respectively, that are retrieved by CALIOP. Among the cirrus-free pixels, CiPS classifies 96 % correctly. With respect to CALIOP, the cloud top height retrieved by CiPS has a mean absolute percentage error of 10 % or less for cirrus clouds with a top height greater than 8 km. For the ice optical thickness, CiPS has a mean absolute percentage error of 50 % or less for cirrus clouds with an optical thickness between 0.35 and 1.8 and of 100 % or less for cirrus clouds with an optical thickness down to 0.07 with respect to the optical thickness retrieved by CALIOP. The ice water path retrieved by CiPS shows a similar performance, with mean absolute percentage errors of 100 % or less for cirrus clouds with an ice water path down to 1.7 g m-2. Since the training reference data from CALIOP only include ice water path and optical thickness for comparably thin clouds, CiPS also retrieves an opacity flag, which tells us whether a retrieved cirrus is likely to be too thick for CiPS to accurately derive the ice water path and optical thickness. By retrieving CALIOP-like cirrus properties with the large spatial coverage and high temporal resolution of SEVIRI during both day and night, CiPS is a powerful tool for analysing the temporal evolution of cirrus clouds including their optical and physical properties. To demonstrate this, the life cycle of a thin cirrus cloud is analysed.

Cloud Droplet Size and Liquid Water Path Retrievals From Zenith Radiance Measurements: Examples From the Atmospheric Radiation Measurement Program and the Aerosol Robotic Network

NASA Technical Reports Server (NTRS)

Chiu, J. C.; Marshak, A.; Huang, C.-H.; Varnai, T.; Hogan, R. J.; Giles, D. M.; Holben, B. N.; Knyazikhin, Y.; O'Connor, E. J.; Wiscombe, W. J.

2012-01-01

The ground-based Atmospheric Radiation Measurement Program (ARM) and NASA Aerosol Robotic Network (AERONET) routinely monitor clouds using zenith radiances at visible and near-infrared wavelengths. Using the transmittance calculated from such measurements, we have developed a new retrieval method for cloud effective droplet size and conducted extensive tests for non-precipitating liquid water clouds. The underlying principle is to combine a water-absorbing wavelength (i.e. 1640 nm) with a nonwater-absorbing wavelength for acquiring information on cloud droplet size and optical depth. For simulated stratocumulus clouds with liquid water path less than 300 g/sq m and horizontal resolution of 201m, the retrieval method underestimates the mean effective radius by 0.8 m, with a root-mean-squared error of 1.7 m and a relative deviation of 13 %. For actual observations with a liquid water path less than 450 gm.2 at the ARM Oklahoma site during 2007-2008, our 1.5 min-averaged retrievals are generally larger by around 1 m than those from combined ground-based cloud radar and microwave radiometer at a 5min temporal resolution. We also compared our retrievals to those from combined shortwave flux and microwave observations for relatively homogeneous clouds, showing that the bias between these two retrieval sets is negligible, but the error of 2.6 m and the relative deviation of 22% are larger than those found in our simulation case. Finally, the transmittance-based cloud effective droplet radii agree to better than 11% with satellite observations and have a negative bias of 1 m. Overall, the retrieval method provides reasonable cloud effective radius estimates, which can enhance the cloud products of both ARM and AERONET.

Results of a joint NOAA/NASA sounder simulation study

NASA Technical Reports Server (NTRS)

Phillips, N.; Susskind, Joel; Mcmillin, L.

1988-01-01

This paper presents the results of a joint NOAA and NASA sounder simulation study in which the accuracies of atmospheric temperature profiles and surface skin temperature measuremnents retrieved from two sounders were compared: (1) the currently used IR temperature sounder HIRS2 (High-resolution Infrared Radiation Sounder 2); and (2) the recently proposed high-spectral-resolution IR sounder AMTS (Advanced Moisture and Temperature Sounder). Simulations were conducted for both clear and partial cloud conditions. Data were analyzed at NASA using a physical inversion technique and at NOAA using a statistical technique. Results show significant improvement of AMTS compared to HIRS2 for both clear and cloudy conditions. The improvements are indicated by both methods of data analysis, but the physical retrievals outperform the statistical retrievals.

Cloud-Scale Vertical Velocity and Turbulent Dissipation Rate Retrievals

DOE Data Explorer

Shupe, Matthew

2013-05-22

Time-height fields of retrieved in-cloud vertical wind velocity and turbulent dissipation rate, both retrieved primarily from vertically-pointing, Ka-band cloud radar measurements. Files are available for manually-selected, stratiform, mixed-phase cloud cases observed at the North Slope of Alaska (NSA) site during periods covering the Mixed-Phase Arctic Cloud Experiment (MPACE, late September through early November 2004) and the Indirect and Semi-Direct Aerosol Campaign (ISDAC, April-early May 2008). These time periods will be expanded in a future submission.

Determination of ice water path in ice-over-water cloud systems using combined MODIS and AMSR-E measurements

NASA Astrophysics Data System (ADS)

Huang, Jianping; Minnis, Patrick; Lin, Bing; Yi, Yuhong; Fan, T.-F.; Sun-Mack, Sunny; Ayers, J. K.

2006-11-01

To provide more accurate ice cloud microphysical properties, the multi-layered cloud retrieval system (MCRS) is used to retrieve ice water path (IWP) in ice-over-water cloud systems globally over oceans using combined instrument data from Aqua. The liquid water path (LWP) of lower-layer water clouds is estimated from the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) measurements. The properties of the upper-level ice clouds are then derived from Moderate Resolution Imaging Spectroradiometer (MODIS) measurements by matching simulated radiances from a two-cloud-layer radiative transfer model. The results show that the MCRS can significantly improve the accuracy and reduce the over-estimation of optical depth and IWP retrievals for ice-over-water cloud systems. The mean daytime ice cloud optical depth and IWP for overlapped ice-over-water clouds over oceans from Aqua are 7.6 and 146.4 gm-2, respectively, down from the initial single-layer retrievals of 17.3 and 322.3 gm-2. The mean IWP for actual single-layer clouds is 128.2 gm-2.

A single field of view method for retrieving tropospheric temperature profiles from cloud-contaminated radiance data

NASA Technical Reports Server (NTRS)

Hodges, D. B.

1976-01-01

An iterative method is presented to retrieve single field of view (FOV) tropospheric temperature profiles directly from cloud-contaminated radiance data. A well-defined temperature profile may be calculated from the radiative transfer equation (RTE) for a partly cloudy atmosphere when the average fractional cloud amount and cloud-top height for the FOV are known. A cloud model is formulated to calculate the fractional cloud amount from an estimated cloud-top height. The method is then examined through use of simulated radiance data calculated through vertical integration of the RTE for a partly cloudy atmosphere using known values of cloud-top height(s) and fractional cloud amount(s). Temperature profiles are retrieved from the simulated data assuming various errors in the cloud parameters. Temperature profiles are retrieved from NOAA-4 satellite-measured radiance data obtained over an area dominated by an active cold front and with considerable cloud cover and compared with radiosonde data. The effects of using various guessed profiles and the number of iterations are considered.

Ten Years of Cloud Optical and Microphysical Retrievals from MODIS

NASA Technical Reports Server (NTRS)

Platnick, Steven; King, Michael D.; Wind, Galina; Hubanks, Paul; Arnold, G. Thomas; Amarasinghe, Nandana

2010-01-01

The MODIS cloud optical properties algorithm (MOD06/MYD06 for Terra and Aqua MODIS, respectively) has undergone extensive improvements and enhancements since the launch of Terra. These changes have included: improvements in the cloud thermodynamic phase algorithm; substantial changes in the ice cloud light scattering look up tables (LUTs); a clear-sky restoral algorithm for flagging heavy aerosol and sunglint; greatly improved spectral surface albedo maps, including the spectral albedo of snow by ecosystem; inclusion of pixel-level uncertainty estimates for cloud optical thickness, effective radius, and water path derived for three error sources that includes the sensitivity of the retrievals to solar and viewing geometries. To improve overall retrieval quality, we have also implemented cloud edge removal and partly cloudy detection (using MOD35 cloud mask 250m tests), added a supplementary cloud optical thickness and effective radius algorithm over snow and sea ice surfaces and over the ocean, which enables comparison with the "standard" 2.1 11m effective radius retrieval, and added a multi-layer cloud detection algorithm. We will discuss the status of the MOD06 algorithm and show examples of pixellevel (Level-2) cloud retrievals for selected data granules, as well as gridded (Level-3) statistics, notably monthly means and histograms (lD and 2D, with the latter giving correlations between cloud optical thickness and effective radius, and other cloud product pairs).

Estimation of liquid water cloud height and fraction using simulated AMSU-A and MHS data. [Advanced Microwave Sounding Unit and Microwave Humidity Sounder

NASA Technical Reports Server (NTRS)

Huang, Hung-Lung; Diak, George R.

1992-01-01

The rms retrieval errors in cloud top pressure for fully overcast conditions over both land and water surfaces are shown for AMSU-A oxygen channel pair 3 and 5 and MHS water vapor channel pair 4 and 5. For both pairs, the decrease of retrieval skill from high cloud is evident for almost all liquid water contents. For high cloud and medium cloud, the water vapor pair outperforms the oxygen pair. Retrieval accuracy is the best for high and middle clouds and degrades as the cloud top is lower in the atmosphere.

Retrieving Aerosol in a Cloudy Environment: Aerosol Availability as a Function of Spatial and Temporal Resolution

NASA Technical Reports Server (NTRS)

Remer, Lorraine A.; Mattoo, Shana; Levy, Robert C.; Heidinger, Andrew; Pierce, R. Bradley; Chin, Mian

2011-01-01

The challenge of using satellite observations to retrieve aerosol properties in a cloudy environment is to prevent contamination of the aerosol signal from clouds, while maintaining sufficient aerosol product yield to satisfy specific applications. We investigate aerosol retrieval availability at different instrument pixel resolutions, using the standard MODIS aerosol cloud mask applied to MODIS data and a new GOES-R cloud mask applied to GOES data for a domain covering North America and surrounding oceans. Aerosol availability is not the same as the cloud free fraction and takes into account the technqiues used in the MODIS algorithm to avoid clouds, reduce noise and maintain sufficient numbers of aerosol retrievals. The inherent spatial resolution of each instrument, 0.5x0.5 km for MODIS and 1x1 km for GOES, is systematically degraded to 1x1 km, 2x2 km, 4x4 km and 8x8 km resolutions and then analyzed as to how that degradation would affect the availability of an aerosol retrieval, assuming an aerosol product resolution at 8x8 km. The results show that as pixel size increases, availability decreases until at 8x8 km 70% to 85% of the retrievals available at 0.5 km have been lost. The diurnal pattern of aerosol retrieval availability examined for one day in the summer suggests that coarse resolution sensors (i.e., 4x4 km or 8x8 km) may be able to retrieve aerosol early in the morning that would otherwise be missed at the time of current polar orbiting satellites, but not the diurnal aerosol properties due to cloud cover developed during the day. In contrast finer resolution sensors (i.e., 1x1 km or 2x2 km) have much better opportunity to retrieve aerosols in the partly cloudy scenes and better chance of returning the diurnal aerosol properties. Large differences in the results of the two cloud masks designed for MODIS aerosol and GOES cloud products strongly reinforce that cloud masks must be developed with specific purposes in mind and that a generic cloud mask applied to an independent aerosol retrieval will likely fail.

Evaluation of long-term surface-retrieved cloud droplet number concentration with in situ aircraft observations: ARM Cloud Droplet Number Concentration

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

Lim, Kyo-Sun Sunny; Riihimaki, Laura; Comstock, Jennifer M.

A new cloud-droplet number concentration (NDROP) value added product (VAP) has been produced at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site for the 13 years from January 1998 to January 2011. The retrieval is based on surface radiometer measurements of cloud optical depth from the multi-filter rotating shadow-band radiometer (MFRSR) and liquid water path from the microwave radiometer (MWR). It is only applicable for single-layered warm clouds. Validation with in situ aircraft measurements during the extended-term aircraft field campaign, Routine ARM Aerial Facility (AAF) CLOWD Optical Radiative Observations (RACORO), shows that the NDROP VAP robustly reproduces themore » primary mode of the in situ measured probability density function (PDF), but produces a too wide distribution, primarily caused by frequent high cloud-droplet number concentration. Our analysis shows that the error in the MWR retrievals at low liquid water paths is one possible reason for this deficiency. Modification through the diagnosed liquid water path from the coordinate solution improves not only the PDF of the NDROP VAP but also the relationship between the cloud-droplet number concentration and cloud-droplet effective radius. Consideration of entrainment effects rather than assuming an adiabatic cloud improves the values of the NDROP retrieval by reducing the magnitude of cloud-droplet number concentration. Aircraft measurements and retrieval comparisons suggest that retrieving the vertical distribution of cloud-droplet number concentration and effective radius is feasible with an improvement of the parameter representing the mixing effects between environment and clouds and with a better understanding of the effect of mixing degree on cloud properties.« less

Ozone profiles retrieval from SCIAMACHY Chappuis-Wulf limb scattered spectra using MART

NASA Astrophysics Data System (ADS)

Wang, ZiJun; Chen, ShengBo; Jin, LiHua; Yang, ChunYan

2011-02-01

The Scanning Imaging Absorption spectroMeter for Atmospheric ChartographY (SCIAMACHY) instrument, launched on the Envisat satellite in March 2002, measures the earthshine radiance, simultaneously from the ultraviolet (UV) to the near infrared (NIR), in the three viewing geometries: nadir, limb, and occultation. These measurements are used to retrieve both the total amount and vertical profiles of a large number of atmospheric constituents. In this paper, stratospheric ozone profiles between 15 and 40 km altitude are retrieved on 3 km grids from SCIAMACHY limb scattered radiance in the Chappuis-Wulf band. The study employs a new multiplicative algebraic reconstruction technique (MART) coupled with the radiative transfer model SCIATRAN. This technique is outstanding in that more than one measurement vector element can be used to retrieve the ozone density at any altitude. Furthermore, it is straightforward to understand, easy to implement and likely to produce stable results. Radiance normalization and wavelength pairing is applied to radiance as an intermediate step, using the wavelengths 525 nm, 600 nm and 675 nm. The sensitivity of ozone retrieval by this method to tangent altitude pointing, surface albedo, aerosol and cloud parameters is studied, and the results show that the retrieval impact due to tangent altitude pointing bias is the biggest up to 75% with 1 km shift, and the impact of albedo is limited within 5%. The effect of boundary visibility and cloud parameters can be ignored since their impact is too small. The effectiveness of the retrieval is demonstrated using a set of coincident SCIAMACHY products at Hefei that shows a mean bias of less than 12% between 15 and 40 km, and with a better accuracy of 5% from 16 to 36 km.

A New Neural Network Approach Including First-Guess for Retrieval of Atmospheric Water Vapor, Cloud Liquid Water Path, Surface Temperature and Emissivities Over Land From Satellite Microwave Observations

NASA Technical Reports Server (NTRS)

Aires, F.; Prigent, C.; Rossow, W. B.; Rothstein, M.; Hansen, James E. (Technical Monitor)

2000-01-01

The analysis of microwave observations over land to determine atmospheric and surface parameters is still limited due to the complexity of the inverse problem. Neural network techniques have already proved successful as the basis of efficient retrieval methods for non-linear cases, however, first-guess estimates, which are used in variational methods to avoid problems of solution non-uniqueness or other forms of solution irregularity, have up to now not been used with neural network methods. In this study, a neural network approach is developed that uses a first-guess. Conceptual bridges are established between the neural network and variational methods. The new neural method retrieves the surface skin temperature, the integrated water vapor content, the cloud liquid water path and the microwave surface emissivities between 19 and 85 GHz over land from SSM/I observations. The retrieval, in parallel, of all these quantities improves the results for consistency reasons. A data base to train the neural network is calculated with a radiative transfer model and a a global collection of coincident surface and atmospheric parameters extracted from the National Center for Environmental Prediction reanalysis, from the International Satellite Cloud Climatology Project data and from microwave emissivity atlases previously calculated. The results of the neural network inversion are very encouraging. The r.m.s. error of the surface temperature retrieval over the globe is 1.3 K in clear sky conditions and 1.6 K in cloudy scenes. Water vapor is retrieved with a r.m.s. error of 3.8 kg/sq m in clear conditions and 4.9 kg/sq m in cloudy situations. The r.m.s. error in cloud liquid water path is 0.08 kg/sq m . The surface emissivities are retrieved with an accuracy of better than 0.008 in clear conditions and 0.010 in cloudy conditions. Microwave land surface temperature retrieval presents a very attractive complement to the infrared estimates in cloudy areas: time record of land surface temperature will be produced.

An Airborne A-Band Spectrometer for Remote Sensing Of Aerosol and Cloud Optical Properties

NASA Technical Reports Server (NTRS)

Pitts, Michael; Hostetler, Chris; Poole, Lamont; Holden, Carl; Rault, Didier

2000-01-01

Atmospheric remote sensing with the O2 A-band has a relatively long history, but most of these studies were attempting to estimate surface pressure or cloud-top pressure. Recent conceptual studies have demonstrated the potential of spaceborne high spectral resolution O2 A-band spectrometers for retrieval of aerosol and cloud optical properties. The physical rationale of this new approach is that information on the scattering properties of the atmosphere is embedded in the detailed line structure of the O2 A-band reflected radiance spectrum. The key to extracting this information is to measure the radiance spectrum at very high spectral resolution. Instrument performance requirement studies indicate that, in addition to high spectral resolution, the successful retrieval of aerosol and cloud properties from A-band radiance spectra will also require high radiometric accuracy, instrument stability, and high signal-to-noise measurements. To experimentally assess the capabilities of this promising new remote sensing application, the NASA Langley Research Center is developing an airborne high spectral resolution A-band spectrometer. The spectrometer uses a plane holographic grating with a folded Littrow geometry to achieve high spectral resolution (0.5 cm-1) and low stray light in a compact package. This instrument will be flown in a series of field campaigns beginning in 2001 to evaluate the overall feasibility of this new technique. Results from these campaigns should be particularly valuable for future spaceborne applications of A-band spectrometers for aerosol and cloud retrievals.

Retrieval Of Cloud Pressure And Chlorophyll Content Using Raman Scattering In GOME Ultraviolet Spectra

NASA Technical Reports Server (NTRS)

Atlas, Robert (Technical Monitor); Joiner, Joanna; Vasikov, Alexander; Flittner, David; Gleason, James; Bhartia, P. K.

2002-01-01

Reliable cloud pressure estimates are needed for accurate retrieval of ozone and other trace gases using satellite-borne backscatter ultraviolet (buv) instruments such as the global ozone monitoring experiment (GOME). Cloud pressure can be derived from buv instruments by utilizing the properties of rotational-Raman scattering (RRS) and absorption by O2-O2. In this paper we estimate cloud pressure from GOME observations in the 355-400 nm spectral range using the concept of a Lambertian-equivalent reflectivity (LER) surface. GOME has full spectral coverage in this range at relatively high spectral resolution with a very high signal-to-noise ratio. This allows for much more accurate estimates of cloud pressure than were possible with its predecessors SBUV and TOMS. We also demonstrate the potential capability to retrieve chlorophyll content with full-spectral buv instruments. We compare our retrieved LER cloud pressure with cloud top pressures derived from the infrared ATSR instrument on the same satellite. The findings confirm results from previous studies that showed retrieved LER cloud pressures from buv observations are systematically higher than IR-derived cloud-top pressure. Simulations using Mie-scattering radiative transfer algorithms that include O2-O2 absorption and RRS show that these differences can be explained by increased photon path length within and below cloud.

A method for retrieving vertical ozone profiles from limb scattered measurements

NASA Astrophysics Data System (ADS)

Wang, Zijun; Chen, Shengbo; Yang, Chunyan; Jin, Lihua

2011-10-01

A two-step method is employed in this study to retrieve vertical ozone profiles using scattered measurements from the limb of the atmosphere. The combination of the Differential Optical Absorption Spectroscopy (DOAS) and the Multiplicative Algebraic Reconstruction Technique (MART) is proposed. First, the limb radiance, measured over a range of tangent heights, is processed using the DOAS technique to recover the effective column densities of atmospheric ozone. Second, these effective column densities along the lines of sight (LOSs) are inverted using the MART coupled with a forward model SCIATRAN (radiative transfer model for SCIAMACHY) to derive the ozone profiles. This method is applied to Optical Spectrograph and Infra Red Imager System (OSIRIS) radiance, using the wavelength windows 571-617 nm. Vertical ozone profiles between 10 and 48 km are derived with a vertical resolution of 1 km. The results illustrate a good agreement with the cloud-free coincident SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) ozone measurements, with deviations less than ±10% (±5% for altitudes from 17 to 47 km). Furthermore, sensitivities of retrieved ozone to aerosol, cloud parameters and NO2 concentration are also investigated.

Surface Emissivity Retrieved with Satellite Ultraspectral IR Measurements for Monitoring Global Change

NASA Technical Reports Server (NTRS)

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

2009-01-01

Surface and atmospheric thermodynamic parameters retrieved with advanced ultraspectral remote sensors aboard Earth observing satellites are critical to general atmospheric and Earth science research, climate monitoring, and weather prediction. Ultraspectral resolution infrared radiance obtained from nadir observations provide atmospheric, surface, and cloud information. Presented here is the global surface IR emissivity retrieved from Infrared Atmospheric Sounding Interferometer (IASI) measurements under "clear-sky" conditions. Fast radiative transfer models, applied to the cloud-free (or clouded) atmosphere, are used for atmospheric profile and surface parameter (or cloud parameter) retrieval. The inversion scheme, dealing with cloudy as well as cloud-free radiances observed with ultraspectral infrared sounders, has been developed to simultaneously retrieve atmospheric thermodynamic and surface (or cloud microphysical) parameters. Rapidly produced surface emissivity is initially evaluated through quality control checks on the retrievals of other impacted atmospheric and surface parameters. Surface emissivity and surface skin temperature from the current and future operational satellites can and will reveal critical information on the Earth s ecosystem and land surface type properties, which can be utilized as part of long-term monitoring for the Earth s environment and global climate change.

Current Sounding Capability From Satellite Meteorological Observation With Ultraspectral Infrared Instruments

NASA Technical Reports Server (NTRS)

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

2008-01-01

Ultraspectral resolution infrared spectral radiance obtained from near nadir observations provide atmospheric, surface, and cloud property information. The intent of the measurement of tropospheric thermodynamic state and trace abundances is the initialization of climate models and the monitoring of air quality. The NPOESS Airborne Sounder Testbed-Interferometer (NAST-I), designed to support the development of future satellite temperature and moisture sounders, aboard high altitude aircraft has been collecting data throughout many field campaigns. An advanced retrieval algorithm developed with NAST-I is now applied to satellite data collected with the Atmospheric InfraRed Sounder (AIRS) on the Aqua satellite launched on 4 May 2002 and the Infrared Atmospheric Sounding Interferometer (IASI) on the MetOp satellite launched on October 19, 2006. These instruments possess an ultra-spectral resolution, for example, both IASI and NAST-I have 0.25 cm-1 and a spectral coverage from 645 to 2760 cm-1. The retrieval algorithm with a fast radiative transfer model, including cloud effects, is used for atmospheric profile and cloud parameter retrieval. The 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 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 can be 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 less than 1 km). Retrievals of atmospheric soundings, surface properties, and cloud microphysical properties with the AIRS and IASI observations are obtained and presented. These retrievals are 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 AIRS and IASI are investigated. These advanced satellite ultraspectral infrared instruments are now playing an important role in satellite meteorological observation for numerical weather prediction.

First Transmitted Hyperspectral Light Measurements and Cloud Properties from Recent Field Campaign Sampling Clouds Under Biomass Burning Aerosol

NASA Technical Reports Server (NTRS)

Leblanc, S.; Redemann, Jens; Shinozuka, Yohei; Flynn, Connor J.; Segal Rozenhaimer, Michal; Kacenelenbogen, Meloe Shenandoah; Pistone, Kristina Marie Myers; Schmidt, Sebastian; Cochrane, Sabrina

2016-01-01

We present a first view of data collected during a recent field campaign aimed at measuring biomass burning aerosol above clouds from airborne platforms. The NASA ObseRvations of CLouds above Aerosols and their intEractionS (ORACLES) field campaign recently concluded its first deployment sampling clouds and overlying aerosol layer from the airborne platform NASA P3. We present results from the Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research (4STAR), in conjunction with the Solar Spectral Flux Radiometers (SSFR). During this deployment, 4STAR sampled transmitted solar light either via direct solar beam measurements and scattered light measurements, enabling the measurement of aerosol optical thickness and the retrieval of information on aerosol particles in addition to overlying cloud properties. We focus on the zenith-viewing scattered light measurements, which are used to retrieve cloud optical thickness, effective radius, and thermodynamic phase of clouds under a biomass burning layer. The biomass burning aerosol layer present above the clouds is the cause of potential bias in retrieved cloud optical depth and effective radius from satellites. We contrast the typical reflection based approach used by satellites to the transmission based approach used by 4STAR during ORACLES for retrieving cloud properties. It is suspected that these differing approaches will yield a change in retrieved properties since light transmitted through clouds is sensitive to a different cloud volume than reflected light at cloud top. We offer a preliminary view of the implications of these differences in sampling volumes to the calculation of cloud radiative effects (CRE).

Fast radiative transfer models for retrieval of cloud properties in the back-scattering region: application to DSCOVR-EPIC sensor

NASA Astrophysics Data System (ADS)

Molina Garcia, Victor; Sasi, Sruthy; Efremenko, Dmitry; Doicu, Adrian; Loyola, Diego

2017-04-01

In this work, the requirements for the retrieval of cloud properties in the back-scattering region are described, and their application to the measurements taken by the Earth Polychromatic Imaging Camera (EPIC) on board the Deep Space Climate Observatory (DSCOVR) is shown. Various radiative transfer models and their linearizations are implemented, and their advantages and issues are analyzed. As radiative transfer calculations in the back-scattering region are computationally time-consuming, several acceleration techniques are also studied. The radiative transfer models analyzed include the exact Discrete Ordinate method with Matrix Exponential (DOME), the Matrix Operator method with Matrix Exponential (MOME), and the approximate asymptotic and equivalent Lambertian cloud models. To reduce the computational cost of the line-by-line (LBL) calculations, the k-distribution method, the Principal Component Analysis (PCA) and a combination of the k-distribution method plus PCA are used. The linearized radiative transfer models for retrieval of cloud properties include the Linearized Discrete Ordinate method with Matrix Exponential (LDOME), the Linearized Matrix Operator method with Matrix Exponential (LMOME) and the Forward-Adjoint Discrete Ordinate method with Matrix Exponential (FADOME). These models were applied to the EPIC oxygen-A band absorption channel at 764 nm. It is shown that the approximate asymptotic and equivalent Lambertian cloud models give inaccurate results, so an offline processor for the retrieval of cloud properties in the back-scattering region requires the use of exact models such as DOME and MOME, which behave similarly. The combination of the k-distribution method plus PCA presents similar accuracy to the LBL calculations, but it is up to 360 times faster, and the relative errors for the computed radiances are less than 1.5% compared to the results when the exact phase function is used. Finally, the linearized models studied show similar behavior, with relative errors less than 1% for the radiance derivatives, but FADOME is 2 times faster than LDOME and 2.5 times faster than LMOME.

Rainbow Fourier Transform

NASA Technical Reports Server (NTRS)

Alexandrov, Mikhail D.; Cairns, Brian; Mishchenko, Michael I.

2012-01-01

We present a novel technique for remote sensing of cloud droplet size distributions. Polarized reflectances in the scattering angle range between 135deg and 165deg exhibit a sharply defined rainbow structure, the shape of which is determined mostly by single scattering properties of cloud particles, and therefore, can be modeled using the Mie theory. Fitting the observed rainbow with such a model (computed for a parameterized family of particle size distributions) has been used for cloud droplet size retrievals. We discovered that the relationship between the rainbow structures and the corresponding particle size distributions is deeper than it had been commonly understood. In fact, the Mie theory-derived polarized reflectance as a function of reduced scattering angle (in the rainbow angular range) and the (monodisperse) particle radius appears to be a proxy to a kernel of an integral transform (similar to the sine Fourier transform on the positive semi-axis). This approach, called the rainbow Fourier transform (RFT), allows us to accurately retrieve the shape of the droplet size distribution by the application of the corresponding inverse transform to the observed polarized rainbow. While the basis functions of the proxy-transform are not exactly orthogonal in the finite angular range, this procedure needs to be complemented by a simple regression technique, which removes the retrieval artifacts. This non-parametric approach does not require any a priori knowledge of the droplet size distribution functional shape and is computationally fast (no look-up tables, no fitting, computations are the same as for the forward modeling).

Extinction coefficients from lidar observations in ice clouds compared to in-situ measurements from the Cloud Integrating Nephelometer during CRYSTAL-FACE

NASA Technical Reports Server (NTRS)

Noel, Vincent; Winker, D. M.; Garrett, T. J.; McGill, M.

2005-01-01

This paper presents a comparison of volume extinction coefficients in tropical ice clouds retrieved from two instruments : the 532-nm Cloud Physics Lidar (CPL), and the in-situ probe Cloud Integrating Nephelometer (CIN). Both instruments were mounted on airborne platforms during the CRYSTAL-FACE campaign and took measurements in ice clouds up to 17km. Coincident observations from three cloud cases are compared : one synoptically-generated cirrus cloud of low optical depth, and two ice clouds located on top of convective systems. Emphasis is put on the vertical variability of the extinction coefficient. Results show small differences on small spatial scales (approx. 100m) in retrievals from both instruments. Lidar retrievals also show higher extinction coefficients in the synoptic cirrus case, while the opposite tendency is observed in convective cloud systems. These differences are generally variations around the average profile given by the CPL though, and general trends on larger spatial scales are usually well reproduced. A good agreement exists between the two instruments, with an average difference of less than 16% on optical depth retrievals.

Satellite retrieval of cloud condensation nuclei concentrations by using clouds as CCN chambers

PubMed Central

Rosenfeld, Daniel; Zheng, Youtong; Hashimshoni, Eyal; Pöhlker, Mira L.; Jefferson, Anne; Pöhlker, Christopher; Yu, Xing; Zhu, Yannian; Liu, Guihua; Yue, Zhiguo; Fischman, Baruch; Li, Zhanqing; Giguzin, David; Goren, Tom; Artaxo, Paulo; Pöschl, Ulrich

2016-01-01

Quantifying the aerosol/cloud-mediated radiative effect at a global scale requires simultaneous satellite retrievals of cloud condensation nuclei (CCN) concentrations and cloud base updraft velocities (Wb). Hitherto, the inability to do so has been a major cause of high uncertainty regarding anthropogenic aerosol/cloud-mediated radiative forcing. This can be addressed by the emerging capability of estimating CCN and Wb of boundary layer convective clouds from an operational polar orbiting weather satellite. Our methodology uses such clouds as an effective analog for CCN chambers. The cloud base supersaturation (S) is determined by Wb and the satellite-retrieved cloud base drop concentrations (Ndb), which is the same as CCN(S). Validation against ground-based CCN instruments at Oklahoma, at Manaus, and onboard a ship in the northeast Pacific showed a retrieval accuracy of ±25% to ±30% for individual satellite overpasses. The methodology is presently limited to boundary layer not raining convective clouds of at least 1 km depth that are not obscured by upper layer clouds, including semitransparent cirrus. The limitation for small solar backscattering angles of <25° restricts the satellite coverage to ∼25% of the world area in a single day. PMID:26944081

Satellite retrieval of cloud condensation nuclei concentrations by using clouds as CCN chambers.

PubMed

Rosenfeld, Daniel; Zheng, Youtong; Hashimshoni, Eyal; Pöhlker, Mira L; Jefferson, Anne; Pöhlker, Christopher; Yu, Xing; Zhu, Yannian; Liu, Guihua; Yue, Zhiguo; Fischman, Baruch; Li, Zhanqing; Giguzin, David; Goren, Tom; Artaxo, Paulo; Barbosa, Henrique M J; Pöschl, Ulrich; Andreae, Meinrat O

2016-05-24

Quantifying the aerosol/cloud-mediated radiative effect at a global scale requires simultaneous satellite retrievals of cloud condensation nuclei (CCN) concentrations and cloud base updraft velocities (Wb). Hitherto, the inability to do so has been a major cause of high uncertainty regarding anthropogenic aerosol/cloud-mediated radiative forcing. This can be addressed by the emerging capability of estimating CCN and Wb of boundary layer convective clouds from an operational polar orbiting weather satellite. Our methodology uses such clouds as an effective analog for CCN chambers. The cloud base supersaturation (S) is determined by Wb and the satellite-retrieved cloud base drop concentrations (Ndb), which is the same as CCN(S). Validation against ground-based CCN instruments at Oklahoma, at Manaus, and onboard a ship in the northeast Pacific showed a retrieval accuracy of ±25% to ±30% for individual satellite overpasses. The methodology is presently limited to boundary layer not raining convective clouds of at least 1 km depth that are not obscured by upper layer clouds, including semitransparent cirrus. The limitation for small solar backscattering angles of <25° restricts the satellite coverage to ∼25% of the world area in a single day.

Cirrus and Polar Stratospheric Cloud Studies using CLAES Data

NASA Technical Reports Server (NTRS)

Mergenthaler, John L.; Douglass, A. (Technical Monitor)

2001-01-01

We've concluded a 3 year (Period of Performance- January 21, 1998 to February 28, 2001) study of cirrus and polar stratospheric clouds using CLAES (Cryogenic Limb Array Etalon Spectrometer) data. We have described the progress of this study in monthly reports, UARS (Upper Atmosphere Research Satellite) science team meetings, American Geophysical Society Meetings, refereed publications and collaborative publications. Work undertaken includes the establishment of CLAES cloud detection criteria, the refinement of CLAES temperature retrieval techniques, compare the findings of CLAES with those of other instruments, and present findings to the larger community. This report describes the progress made in these 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.

Neural Network (NN) retrievals of Stratocumulus cloud properties using multi-angle polarimetric observations during ORACLES

NASA Astrophysics Data System (ADS)

Segal-Rosenhaimer, M.; Knobelspiesse, K. D.; Redemann, J.; Cairns, B.; Alexandrov, M. D.

2016-12-01

The ORACLES (ObseRvations of Aerosols above CLouds and their intEractionS) campaign is taking place in the South-East Atlantic during the Austral Spring for three consecutive years from 2016-2018. The study area encompasses one of the Earth's three semi-permanent subtropical Stratocumulus (Sc) cloud decks, and experiences very large aerosol optical depths, mainly biomass burning, originating from Africa. Over time, cloud optical depth (COD), lifetime and cloud microphysics (number concentration, effective radii Reff and precipitation) are expected to be influenced by indirect aerosol effects. These changes play a key role in the energetic balance of the region, and are part of the core investigation objectives of the ORACLES campaign, which acquires measurements of clean and polluted scenes of above cloud aerosols (ACA). Simultaneous retrievals of aerosol and cloud optical properties are being developed (e.g. MODIS, OMI), but still challenging, especially for passive, single viewing angle instruments. By comparison, multiangle polarimetric instruments like RSP (Research Scanning Polarimeter) show promise for detection and quantification of ACA, however, there are no operational retrieval algorithms available yet. Here we describe a new algorithm to retrieve cloud and aerosol optical properties from observations by RSP flown on the ER-2 and P-3 during the 2016 ORACLES campaign. The algorithm is based on training a NN, and is intended to retrieve aerosol and cloud properties simultaneously. However, the first step was to establish the retrieval scheme for low level Sc cloud optical properties. The NN training was based on simulated RSP total and polarized radiances for a range of COD, Reff, and effective variances, spanning 7 wavelength bands and 152 viewing zenith angles. Random and correlated noise were added to the simulations to achieve a more realistic representation of the signals. Before introducing the input variables to the network, the signals are projected on a principle component plane that retains the maximal signal information but minimizes the noise contribution. We will discuss parameter choices for the network and present preliminary results of cloud retrievals from ORACLES, compared with standard RSP low-level cloud retrieval method that has been validated against in situ observations.

A New Technique for the Retrieval of Near Surface Water Vapor Using DIAL Measurements

NASA Technical Reports Server (NTRS)

Ismail, Syed; Kooi, Susan; Ferrare, Richard; Winker, David; Hair, Johnathan; Nehrir, Amin; Notari, Anthony; Hostetler, Chris

2015-01-01

Water vapor is one of the most important atmospheric trace gas species and influences radiation, climate, cloud formation, surface evaporation, precipitation, storm development, transport, dynamics, and chemistry. For improvements in NWP (numerical weather prediction) and climate studies, global water vapor measurements with higher accuracy and vertical resolution are needed than are currently available. Current satellite sensors are challenged to characterize the content and distribution of water vapor in the Boundary Layer (BL) and particularly near the first few hundred meters above the surface within the BL. These measurements are critically needed to infer surface evaporation rates in cloud formation and climate studies. The NASA Langley Research Center Lidar Atmospheric Sensing Experiment (LASE) system, which uses the Differential Absorption Lidar (DIAL) technique, has demonstrated the capability to provide high quality water vapor measurements in the BL and across the troposphere. A new retrieval technique is investigated to extend these DIAL water vapor measurements to the surface. This method uses signals from both atmospheric backscattering and the strong surface returns (even over low reflectivity oceanic surfaces) using multiple gain channels to cover the large signal dynamic range. Measurements can be made between broken clouds and in presence of optically thin cirrus. Examples of LASE measurements from a variety of conditions encountered during NASA hurricane field experiments over the Atlantic Ocean are presented. Comparisons of retrieved water vapor profiles from LASE near the surface with dropsonde measurements show very good agreement. This presentation also includes a discussion of the feasibility of developing space-based DIAL capability for high resolution water vapor measurements in the BL and above and an assessment of the technology needed for developing this capability.

Architectures for Rainfall Property Estimation From Polarimetric Radar

NASA Astrophysics Data System (ADS)

Collis, S. M.; Giangrande, S. E.; Helmus, J.; Troemel, S.

2014-12-01

Radars that transmit and receive signals in polarizations aligned both horizontal and vertical to the horizon collect a number of measurements. The relation both between these measurements and between measurements and desired microphysical quantities (such as rainfall rate) is complicated due to a number of scattering mechanisms. The result is that there ends up being an intractable number of often incompatible techniques for extracting geophysical insight. This presentation will discuss methods developed by the Atmospheric Measurement Climate (ARM) Research Facility to streamline the creation of application chains for retrieving rainfall properties for the purposes of fine scale model evaluation. By using a Common Data Model (CDM) approach and working in the popular open source Python scientific environment analysis techniques such as Linear Programming (LP) can be bought to bear on the task of retrieving insight from radar signals. This presentation will outline how we have used these techniques to detangle polarimetric phase signals, estimate a three-dimensional precipitation field and then objectively compare to cloud resolving model derived rainfall fields from the NASA/DoE Mid-Latitude Continental Convective Clouds Experiment (MC3E). All techniques show will be available, open source, in the Python-ARM Radar Toolkit (Py-ART).

Simulation of particle size distributions in Polar Mesospheric Clouds from Microphysical Models

NASA Astrophysics Data System (ADS)

Thomas, G. E.; Merkel, A.; Bardeen, C.; Rusch, D. W.; Lumpe, J. D.

2009-12-01

The size distribution of ice particles is perhaps the most important observable aspect of microphysical processes in Polar Mesospheric Cloud (PMC) formation and evolution. A conventional technique to derive such information is from optical observation of scattering, either passive solar scattering from photometric or spectrometric techniques, or active backscattering by lidar. We present simulated size distributions from two state-of-the-art models using CARMA sectional microphysics: WACCM/CARMA, in which CARMA is interactively coupled with WACCM3 (Bardeen et al, 2009), and stand-alone CARMA forced by WACCM3 meteorology (Merkel et al, this meeting). Both models provide well-resolved size distributions of ice particles as a function of height, location and time for realistic high-latitude summertime conditions. In this paper we present calculations of the UV scattered brightness at multiple scattering angles as viewed by the AIM Cloud Imaging and Particle Size (CIPS) satellite experiment. These simulations are then considered discretely-sampled “data” for the scattering phase function, which are inverted using a technique (Lumpe et al, this meeting) to retrieve particle size information. We employ a T-matrix scattering code which applies to a wide range of non-sphericity of the ice particles, using the conventional idealized prolate/oblate spheroidal shape. This end-to-end test of the relatively new scattering phase function technique provides insight into both the retrieval accuracy and the information content in passive remote sensing of PMC.

Remote Sensing of Cloud Properties using Ground-based Measurements of Zenith Radiance

NASA Technical Reports Server (NTRS)

Chiu, J. Christine; Marshak, Alexander; Knyazikhin, Yuri; Wiscombe, Warren J.; Barker, Howard W.; Barnard, James C.; Luo, Yi

2006-01-01

An extensive verification of cloud property retrievals has been conducted for two algorithms using zenith radiances measured by the Atmospheric Radiation Measurement (ARM) Program ground-based passive two-channel (673 and 870 nm) Narrow Field-Of-View Radiometer. The underlying principle of these algorithms is that clouds have nearly identical optical properties at these wavelengths, but corresponding spectral surface reflectances (for vegetated surfaces) differ significantly. The first algorithm, the RED vs. NIR, works for a fully three-dimensional cloud situation. It retrieves not only cloud optical depth, but also an effective radiative cloud fraction. Importantly, due to one-second time resolution of radiance measurements, we are able, for the first time, to capture detailed changes in cloud structure at the natural time scale of cloud evolution. The cloud optical depths tau retrieved by this algorithm are comparable to those inferred from both downward fluxes in overcast situations and microwave brightness temperatures for broken clouds. Moreover, it can retrieve tau for thin patchy clouds, where flux and microwave observations fail to detect them. The second algorithm, referred to as COUPLED, couples zenith radiances with simultaneous fluxes to infer 2. In general, the COUPLED and RED vs. NIR algorithms retrieve consistent values of tau. However, the COUPLED algorithm is more sensitive to the accuracies of measured radiance, flux, and surface reflectance than the RED vs. NIR algorithm. This is especially true for thick overcast clouds where it may substantially overestimate z.

MODIS Collection 6 Clear Sky Restoral (CSR): Filtering Cloud Mast 'Not Clear' Pixels

NASA Technical Reports Server (NTRS)

Meyer, Kerry G.; Platnick, Steven Edward; Wind, Galina; Riedi, Jerome

2014-01-01

Correctly identifying cloudy pixels appropriate for the MOD06 cloud optical and microphysical property retrievals is accomplished in large part using results from the MOD35 1km cloud mask tests (note there are also two 250m subpixel cloud mask tests that can convert the 1km cloudy designations to clear sky). However, because MOD35 is by design clear sky conservative (i.e., it identifies "not clear" pixels), certain situations exist in which pixels identified by MOD35 as "cloudy" are nevertheless likely to be poor retrieval candidates. For instance, near the edge of clouds or within broken cloud fields, a given 1km MODIS field of view (FOV) may in fact only be partially cloudy. This can be problematic for the MOD06 retrievals because in these cases the assumptions of a completely overcast homogenous cloudy FOV and 1-dimensional plane-parallel radiative transfer no longer hold, and subsequent retrievals will be of low confidence. Furthermore, some pixels may be identified by MOD35 as "cloudy" for reasons other than the presence of clouds, such as scenes with thick smoke or lofted dust, and should therefore not be retrieved as clouds. With such situations in mind, a Clear Sky Restoral (CSR) algorithm was introduced in C5 that attempts to identify pixels expected to be poor retrieval candidates. Table 1 provides SDS locations for CSR and partly cloudy (PCL) pixels.

Satellite remote sensing of aerosol and cloud properties over Eurasia

NASA Astrophysics Data System (ADS)

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

2015-04-01

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

Exoplanets with JWST: degeneracy, systematics and how to avoid them

NASA Astrophysics Data System (ADS)

Barstow, Joanna K.; Irwin, Patrick G. J.; Kendrew, Sarah; Aigrain, Suzanne

2016-07-01

The high sensitivity and broad wavelength coverage of the James Webb Space Telescope will transform the field of exoplanet transit spectroscopy. Transit spectra are inferred from minute, wavelength-dependent variations in the depth of a transit or eclipse as the planet passes in front of or is obscured by its star, and the spectra contain information about the composition, structure and cloudiness of exoplanet atmospheres. Atmospheric retrieval is the preferred technique for extracting information from these spectra, but the process can be confused by astrophysical and instrumental systematic noise. We present results of retrieval tests based on synthetic, noisy JWST spectra, for clear and cloudy planets and active and inactive stars. We find that the ability to correct for stellar activity is likely to be a limiting factor for cloudy planets, as the effects of unocculted star spots may mimic the presence of a scattering slope due to clouds. We discuss the pros and cons of the available JWST instrument combinations for transit spectroscopy, and consider the effect of clouds and aerosols on the spectra. Aerosol high in a planet's atmosphere obscures molecular absorption features in transmission, reducing the information content of spectra in wavelength regions where the cloud is optically thick. We discuss the usefulness of particular wavelength regions for identifying the presence of cloud, and suggest strategies for solving the highly-degenerate retrieval problem for these objects.

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.;

Improvements in Night-Time Low Cloud Detection and MODIS-Style Cloud Optical Properties from MSG SEVIRI

NASA Technical Reports Server (NTRS)

Wind, Galina (Gala); Platnick, Steven; Riedi, Jerome

2011-01-01

The MODIS cloud optical properties algorithm (MOD06IMYD06 for Terra and Aqua MODIS, respectively) slated for production in Data Collection 6 has been adapted to execute using available channels on MSG SEVIRI. Available MODIS-style retrievals include IR Window-derived cloud top properties, using the new Collection 6 cloud top properties algorithm, cloud optical thickness from VISINIR bands, cloud effective radius from 1.6 and 3.7Jlm and cloud ice/water path. We also provide pixel-level uncertainty estimate for successful retrievals. It was found that at nighttime the SEVIRI cloud mask tends to report unnaturally low cloud fraction for marine stratocumulus clouds. A correction algorithm that improves detection of such clouds has been developed. We will discuss the improvements to nighttime low cloud detection for SEVIRI and show examples and comparisons with MODIS and CALIPSO. We will also show examples of MODIS-style pixel-level (Level-2) cloud retrievals for SEVIRI with comparisons to MODIS.

Differential absorption radar techniques: water vapor retrievals

NASA Astrophysics Data System (ADS)

Millán, Luis; Lebsock, Matthew; Livesey, Nathaniel; Tanelli, Simone

2016-06-01

Two radar pulses sent at different frequencies near the 183 GHz water vapor line can be used to determine total column water vapor and water vapor profiles (within clouds or precipitation) exploiting the differential absorption on and off the line. We assess these water vapor measurements by applying a radar instrument simulator to CloudSat pixels and then running end-to-end retrieval simulations. These end-to-end retrievals enable us to fully characterize not only the expected precision but also their potential biases, allowing us to select radar tones that maximize the water vapor signal minimizing potential errors due to spectral variations in the target extinction properties. A hypothetical CloudSat-like instrument with 500 m by ˜ 1 km vertical and horizontal resolution and a minimum detectable signal and radar precision of -30 and 0.16 dBZ, respectively, can estimate total column water vapor with an expected precision of around 0.03 cm, with potential biases smaller than 0.26 cm most of the time, even under rainy conditions. The expected precision for water vapor profiles was found to be around 89 % on average, with potential biases smaller than 77 % most of the time when the profile is being retrieved close to surface but smaller than 38 % above 3 km. By using either horizontal or vertical averaging, the precision will improve vastly, with the measurements still retaining a considerably high vertical and/or horizontal resolution.

Simultaneous retrieval of water vapour, temperature and cirrus clouds properties from measurements of far infrared spectral radiance over the Antarctic Plateau

NASA Astrophysics Data System (ADS)

Di Natale, Gianluca; Palchetti, Luca; Bianchini, Giovanni; Del Guasta, Massimo

2017-03-01

The possibility separating the contributions of the atmospheric state and ice clouds by using spectral infrared measurements is a fundamental step to quantifying the cloud effect in climate models. A simultaneous retrieval of cloud and atmospheric parameters from infrared wideband spectra will allow the disentanglement of the spectral interference between these variables. In this paper, we describe the development of a code for the simultaneous retrieval of atmospheric state and ice cloud parameters, and its application to the analysis of the spectral measurements acquired by the Radiation Explorer in the Far Infrared - Prototype for Applications and Development (REFIR-PAD) spectroradiometer, which has been in operation at Concordia Station on the Antarctic Plateau since 2012. The code performs the retrieval with a computational time that is comparable with the instrument acquisition time. Water vapour and temperature profiles and the cloud optical and microphysical properties, such as the generalised effective diameter and the ice water path, are retrieved by exploiting the 230-980 cm-1 spectral band. To simulate atmospheric radiative transfer, the Line-By-Line Radiative Transfer Model (LBLRTM) has been integrated with a specifically developed subroutine based on the δ-Eddington two-stream approximation, whereas the single-scattering properties of cirrus clouds have been derived from a database for hexagonal column habits. In order to detect ice clouds, a backscattering and depolarisation lidar, co-located with REFIR-PAD has been used, allowing us to infer the position and the cloud thickness to be used in the retrieval. A climatology of the vertical profiles of water vapour and temperature has been performed by using the daily radiosounding available at the station at 12:00 UTC. The climatology has been used to build an a priori profile correlation to constrain the fitting procedure. An optimal estimation method with the Levenberg-Marquardt approach has been used to perform the retrieval. In most cases, the retrieved humidity and temperature profiles show a good agreement with the radiosoundings, demonstrating that the simultaneous retrieval of the atmospheric state is not biased by the presence of cirrus clouds. Finally, the retrieved cloud parameters allow us to study the relationships between cloud temperature and optical depth and between effective particle diameter and ice water content. These relationships are similar to the statistical correlations measured on the Antarctic coast at Dumont d'Urville and in the Arctic region.

Water vapor profiling using microwave radiometry

NASA Technical Reports Server (NTRS)

Wang, J. R.; Wilheit, T. T.

1988-01-01

Water vapor is one of the most important constituents in the Earth's atmosphere. Its spatial and temporal variations affect a wide spectrum of meteorological phenomena ranging from the formation of clouds to the development of severe storms. The passive microwave technique offers an excellent means for water vapor measurements. It can provide both day and night coverage under most cloud conditions. Two water vapor absorption features, at 22 and 183 GHz, were explored in the past years. The line strengths of these features differ by nearly two orders of magnitude. As a consequence, the techniques and the final products of water vapor measurements are also quite different. The research effort in the past few years was to improve and extend the retrieval algorithm to the measurements of water vapor profiles under cloudy conditions. In addition, the retrieval of total precipitable water using 183 GHz measurements, but in a manner analogous to the use of 22 GHz measurements, to increase measurement sensitivity for atmospheres of very low moisture content was also explored.

MODIS Retrievals of Cloud Optical Thickness and Particle Radius

NASA Technical Reports Server (NTRS)

Platnick, S.; King, M. D.; Ackerman, S. A.; Gray, M.; Moody, E.; Arnold, G. T.; Einaudi, Franco (Technical Monitor)

2000-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) provides an unprecedented opportunity for global cloud studies with 36 spectral bands from the visible through the infrared, and spatial resolution from 250 m to 1 km at nadir. In particular, all solar window bands useful for simultaneous retrievals of cloud optical thickness and particle size (0.67, 0.86, 1.2, 1.6, 2.1, and 3.7 micron bands) are now available on a single satellite instrument/platform for the first time. An operational algorithm for the retrieval of these optical and cloud physical properties (including water path) have been developed for both liquid and ice phase clouds. The product is archived into two categories: pixel-level retrievals at 1 km spatial resolution (referred to as a Level-2 product) and global gridded statistics (Level-3 product). An overview of the MODIS cloud retrieval algorithm and early level-2 and -3 results will be presented. A number of MODIS cloud validation activities are being planned, including the recent Southern Africa Regional Science Initiative 2000 (SAFARI-2000) dry season campaign conducted in August/September 2000. The later part of the experiment concentrated on MODIS validation in the Namibian stratocumulus regime off the southwest coast of Africa. Early retrieval results from this regime will be discussed.

What does reflection from cloud sides tell us about vertical distribution of cloud droplets?

NASA Technical Reports Server (NTRS)

Marshak, A.; Kaufman, Yoram; Martins, V.; Zubko, Victor

2006-01-01

In order to accurately measure the interaction of clouds with aerosols, we have to resolve the vertical distribution of cloud droplet sizes and determine the temperature of glaciation for clean and polluted clouds. Knowledge of the droplet vertical profile is also essential for understanding precipitation. So far, all existing satellites either measure cloud microphysics only at cloud top (e.g., MODIS) or give a vertical profile of precipitation sized droplets (e.g., Cloudsat). What if one measures cloud microphysical properties in the vertical by retrieving them from the solar and infrared radiation reflected or emitted from cloud sides? This was the idea behind CLAIM-3D (A 3D - cloud aerosol interaction mission) recently proposed by NASA GSFC. This presentation will focus on the interpretation of the radiation reflected from cloud sides. In contrast to plane-parallel approximation, a conventional approach to all current operational retrievals, 3D radiative transfer will be used for interpreting the observed reflectances. As a proof of concept, we will show a few examples of radiation reflected from cloud fields generated by a simple stochastic cloud model with prescribed microphysics. Instead of fixed values of the retrieved effective radii, the probability density functions of droplet size distributions will serve as possible retrievals.

The effect of cloud screening on MAX-DOAS aerosol retrievals.

NASA Astrophysics Data System (ADS)

Gielen, Clio; Van Roozendael, Michel; Hendrik, Francois; Fayt, Caroline; Hermans, Christian; Pinardi, Gaia; De Backer, Hugo; De Bock, Veerle; Laffineur, Quentin; Vlemmix, Tim

2014-05-01

In recent years, ground-based multi-axis differential absorption spectroscopy (MAX-DOAS) has shown to be ideally suited for the retrieval of tropospheric trace gases and deriving information on the aerosol properties. These measurements are invaluable to our understanding of the physics and chemistry of the atmospheric system, and the impact on the Earth's climate. Unfortunately, MAX-DOAS measurements are often performed under strong non-clear-sky conditions, causing strong data quality degradation and uncertainties on the retrievals. Here we present the result of our cloud-screening method, using the colour index (CI), on aerosol retrievals from MAX-DOAS measurements (AOD and vertical profiles). We focus on two large data sets, from the Brussels and Beijing area. Using the CI we define 3 different sky conditions: bad (=full thick cloud cover/extreme aerosols), mediocre (=thin clouds/aerosols) and good (=clear sky). We also flag the presence of broken/scattered clouds. We further compare our cloud-screening method with results from cloud-cover fractions derived from thermic infrared measurements. In general, our method shows good results to qualify the sky and cloud conditions of MAX-DOAS measurements, without the need for other external cloud-detection systems. Removing data under bad-sky and broken-cloud conditions results in a strongly improved agreement, in both correlation and slope, between the MAX-DOAS aerosol retrievals and data from other instruments (e.g. AERONET, Brewer). With the improved AOD retrievals, the seasonal and diurnal variations of the aerosol content and vertical distribution at both sites can be investigated in further detail. By combining with additional information derived by other instruments (Brewer, lidar, ...) operated at the stations, we will further study the observed aerosol characteristics, and their influence on and by meteorological conditions such as clouds and/or the boundary layer height.

Sensitivity Study of IROE Cloud Retrievals Using VIIRS M-Bands and Combined VIIRS/CrIS IR Observations

NASA Astrophysics Data System (ADS)

Wang, C.; Platnick, S. E.; Meyer, K.; Ackerman, S. A.; Holz, R.; Heidinger, A.

2017-12-01

The Visible Infrared Imaging Radiometer Suite (VIIRS) on board the Suomi-NPP spacecraft is considered as the next generation of instrument providing operational moderate resolution imaging capabilities after the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. However, cloud-top property (CTP) retrieval algorithms designed for the two instruments cannot be identical because of the absence of CO2 bands on VIIRS. In this study, we conduct a comprehensive sensitivity study of cloud retrievals utilizing a IR-Optimal Estimation (IROE) based algorithm. With a fast IR radiative transfer model, the IROE simultaneously retrieves cloud-top height (CTH), cloud optical thickness (COT), cloud effective radius (CER) and corresponding uncertainties using a set of IR bands. Three retrieval runs are implemented for this sensitivity study: retrievals using 1) three native VIIRS M-Bands at 750m resolution (8.5-, 11-, and 12-μm), 2) three native VIIRS M-Bands with spectrally integrated CO2 bands from the Cross-Track Infrared Sounder (CrIS), and 3) six MODIS IR bands (8.5-, 11-, 12-, 13.3-, 13.6-, and 13.9-μm). We select a few collocated MODIS and VIIRS granules for pixel-level comparison. Furthermore, aggregated daily and monthly cloud properties from the three runs are also compared. It shows that, the combined VIIRS/CrIS run agrees well with the MODIS-only run except for pixels near cloud edges. The VIIRS-only run is close to its counterparts when clouds are optically thick. However, for optically thin clouds, the VIIRS-only run can be readily influenced by the initial guess. Large discrepancies and uncertainties can be found for optically thin clouds from the VIIRS-only run.

A statistical retrieval of cloud parameters for the millimeter wave Ice Cloud Imager on board MetOp-SG

NASA Astrophysics Data System (ADS)

Prigent, Catherine; Wang, Die; Aires, Filipe; Jimenez, Carlos

2017-04-01

The meteorological observations from satellites in the microwave domain are currently limited to below 190 GHz. However, the next generation of European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Polar System-Second Generation-EPS-SG will carry an instrument, the Ice Cloud Imager (ICI), with frequencies up to 664 GHz, to improve the characterization of the cloud frozen phase. In this paper, a statistical retrieval of cloud parameters for ICI is developed, trained on a synthetic database derived from the coupling of a mesoscale cloud model and radiative transfer calculations. The hydrometeor profiles simulated with the Weather Research and Forecasting model (WRF) for twelve diverse European mid-latitude situations are used to simulate the brightness temperatures with the Atmospheric Radiative Transfer Simulator (ARTS) to prepare the retrieval database. The WRF+ARTS simulations have been compared to the Special Sensor Microwave Imager/Sounder (SSMIS) observations up to 190 GHz: this successful evaluation gives us confidence in the simulations at the ICI channels from 183 to 664 GHz. Statistical analyses have been performed on this simulated retrieval database, showing that it is not only physically realistic but also statistically satisfactory for retrieval purposes. A first Neural Network (NN) classifier is used to detect the cloud presence. A second NN is developed to retrieve the liquid and ice integrated cloud quantities over sea and land separately. The detection and retrieval of the hydrometeor quantities (i.e., ice, snow, graupel, rain, and liquid cloud) are performed with ICI-only, and with ICI combined with observations from the MicroWave Imager (MWI, with frequencies from 19 to 190 GHz, also on board MetOp-SG). The ICI channels have been optimized for the detection and quantification of the cloud frozen phases: adding the MWI channels improves the performance of the vertically integrated hydrometeor contents, especially for the cloud liquid phases. The relative error for the retrieved integrated frozen water content (FWP, i.e., ice+snow+graupel) is below 40% for 0.1kg/m2 < FWP < 0.5kg/m2 and below 20% for FWP > 0.5 kg/m2.

Final Technical Report

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

de Szoeke, Simon P.

The investigator and DOE-supported student [1] retrieved vertical air velocity and microphysical fall velocity retrieval for VOCALS and CAP-MBL homogeneous clouds. [2] Calculated in-cloud and cloud top dissipation calculation and diurnal cycle computed for VOCALS. [3] Compared CAP-MBL Doppler cloud radar scenes with (Remillard et al. 2012) automated classification.

Characterizing the Retrieval of Cloud Optical Thickness and Droplet Effective Radius to Overlying Aerosols Using a General Inverse Theory Approach

NASA Astrophysics Data System (ADS)

Coddington, O.; Pilewskie, P.; Schmidt, S.

2013-12-01

The upwelling shortwave irradiance measured by the airborne Solar Spectral Flux Radiometer (SSFR) flying above a cloud and aerosol layer is influenced by the properties of the cloud and aerosol particles below, just as would the radiance measured from satellite. Unlike satellite measurements, those from aircraft provide the unique capability to fly a lower-level leg above the cloud, yet below the aerosol layer, to characterize the extinction of the aerosol layer and account for its impact on the measured cloud albedo. Previous work [Coddington et al., 2010] capitalized on this opportunity to test the effects of aerosol particles (or more appropriately, the effects of neglecting aerosols in forward modeling calculations) on cloud retrievals using data obtained during the Intercontinental Chemical Transport Experiment/Intercontinental Transport and Chemical Transformation of anthropogenic pollution (INTEX-A/ITCT) study. This work showed aerosols can cause a systematic bias in the cloud retrieval and that such a bias would need to be distinguished from a true aerosol indirect effect (i.e. the brightening of a cloud due to aerosol effects on cloud microphysics) as theorized by Haywood et al., [2004]. The effects of aerosols on clouds are typically neglected in forward modeling calculations because their pervasiveness, variable microphysical properties, loading, and lifetimes makes forward modeling calculations under all possible combinations completely impractical. Using a general inverse theory technique, which propagates separate contributions from measurement and forward modeling errors into probability distributions of retrieved cloud optical thickness and droplet effective radius, we have demonstrated how the aerosol presence can be introduced as a spectral systematic error in the distributions of the forward modeling solutions. The resultant uncertainty and bias in cloud properties induced by the aerosols is identified by the shape and peak of the posteriori retrieval distributions. In this work, we apply this general inverse theory approach to extend our analysis of the spectrally-dependent impacts of overlying aerosols on cloud properties over a broad range in cloud optical thickness and droplet effective radius. We investigate the relative impacts of this error source and compare and contrast results to biases and uncertainties in cloud properties induced by varying surface conditions (ocean, land, snow). We perform the analysis for two different measurement accuracies (3% and 0.3%) that are typical of current passive imagers, such as the Moderate Resolution Imaging Spectroradiometer (MODIS) [Platnick et al., 2003], and that are expected for future passive imagers, such as the HyperSpectral Imager for Climate Science (HySICS) [Kopp et al., 2010]. Coddington, O., P. Pilewskie, et al., 2010, J. Geophys. Res., 115, doi: 10.1029/2009JD012829. Haywood, J. M., S. R. Osborne, and S. J. Abel, 2004, Q. J. R. Meteorol. Soc., 130, 779-800. Kopp, G., et al., 2010, Hyperspectral Imagery Radiometry Improvements for Visible and Near-Infrared Climate Studies, paper presented at 2010 Earth Science Technology Forum, Arlington, VA, USA. Platnick, S., et al., 2003, IEEE Trans. Geosci. Remote Sens., 41(2), 459- 473.

Global Single and Multiple Cloud Classification with a Fuzzy Logic Expert System

NASA Technical Reports Server (NTRS)

Welch, Ronald M.; Tovinkere, Vasanth; Titlow, James; Baum, Bryan A.

1996-01-01

An unresolved problem in remote sensing concerns the analysis of satellite imagery containing both single and multiple cloud layers. While cloud parameterizations are very important both in global climate models and in studies of the Earth's radiation budget, most cloud retrieval schemes, such as the bispectral method used by the International Satellite Cloud Climatology Project (ISCCP), have no way of determining whether overlapping cloud layers exist in any group of satellite pixels. Coakley (1983) used a spatial coherence method to determine whether a region contained more than one cloud layer. Baum et al. (1995) developed a scheme for detection and analysis of daytime multiple cloud layers using merged AVHRR (Advanced Very High Resolution Radiometer) and HIRS (High-resolution Infrared Radiometer Sounder) data collected during the First ISCCP Regional Experiment (FIRE) Cirrus 2 field campaign. Baum et al. (1995) explored the use of a cloud classification technique based on AVHRR data. This study examines the feasibility of applying the cloud classifier to global satellite imagery.

Satellite retrieval of cloud condensation nuclei concentrations by using clouds as CCN chambers

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

Rosenfeld, Daniel; Zheng, Youtong; Hashimshoni, Eyal

Quantifying the aerosol/cloud-mediated radiative effect at a global scale requires simultaneous satellite retrievals of cloud condensation nuclei (CCN) concentrations and cloud base updraft velocities ( Wb). Hitherto, the inability to do so has been a major cause of high uncertainty regarding anthropogenic aerosol/cloud-mediated radiative forcing. This can be addressed by the emerging capability of estimating CCN and Wb of boundary layer convective clouds from an operational polar orbiting weather satellite. In this paper, our methodology uses such clouds as an effective analog for CCN chambers. The cloud base supersaturation ( S) is determined by Wb and the satellite-retrieved cloud basemore » drop concentrations ( Ndb), which is the same as CCN(S). Validation against ground-based CCN instruments at Oklahoma, at Manaus, and onboard a ship in the northeast Pacific showed a retrieval accuracy of ±25% to ±30% for individual satellite overpasses. The methodology is presently limited to boundary layer not raining convective clouds of at least 1 km depth that are not obscured by upper layer clouds, including semitransparent cirrus. Finally, the limitation for small solar backscattering angles of <25° restricts the satellite coverage to ~25% of the world area in a single day.« less

Satellite retrieval of cloud condensation nuclei concentrations by using clouds as CCN chambers

DOE PAGES

Rosenfeld, Daniel; Zheng, Youtong; Hashimshoni, Eyal; ...

2016-03-04

Quantifying the aerosol/cloud-mediated radiative effect at a global scale requires simultaneous satellite retrievals of cloud condensation nuclei (CCN) concentrations and cloud base updraft velocities ( Wb). Hitherto, the inability to do so has been a major cause of high uncertainty regarding anthropogenic aerosol/cloud-mediated radiative forcing. This can be addressed by the emerging capability of estimating CCN and Wb of boundary layer convective clouds from an operational polar orbiting weather satellite. In this paper, our methodology uses such clouds as an effective analog for CCN chambers. The cloud base supersaturation ( S) is determined by Wb and the satellite-retrieved cloud basemore » drop concentrations ( Ndb), which is the same as CCN(S). Validation against ground-based CCN instruments at Oklahoma, at Manaus, and onboard a ship in the northeast Pacific showed a retrieval accuracy of ±25% to ±30% for individual satellite overpasses. The methodology is presently limited to boundary layer not raining convective clouds of at least 1 km depth that are not obscured by upper layer clouds, including semitransparent cirrus. Finally, the limitation for small solar backscattering angles of <25° restricts the satellite coverage to ~25% of the world area in a single day.« less

Statistical Evaluation of CRM-Simulated Cloud and Precipitation Structures Using Multi- sensor TRMM Measurements and Retrievals

NASA Astrophysics Data System (ADS)

Posselt, D.; L'Ecuyer, T.; Matsui, T.

2009-05-01

Cloud resolving models are typically used to examine the characteristics of clouds and precipitation and their relationship to radiation and the large-scale circulation. As such, they are not required to reproduce the exact location of each observed convective system, much less each individual cloud. Some of the most relevant information about clouds and precipitation is provided by instruments located on polar-orbiting satellite platforms, but these observations are intermittent "snapshots" in time, making assessment of model performance challenging. In contrast to direct comparison, model results can be evaluated statistically. This avoids the requirement for the model to reproduce the observed systems, while returning valuable information on the performance of the model in a climate-relevant sense. The focus of this talk is a model evaluation study, in which updates to the microphysics scheme used in a three-dimensional version of the Goddard Cumulus Ensemble (GCE) model are evaluated using statistics of observed clouds, precipitation, and radiation. We present the results of multiday (non-equilibrium) simulations of organized deep convection using single- and double-moment versions of a the model's cloud microphysical scheme. Statistics of TRMM multi-sensor derived clouds, precipitation, and radiative fluxes are used to evaluate the GCE results, as are simulated TRMM measurements obtained using a sophisticated instrument simulator suite. We present advantages and disadvantages of performing model comparisons in retrieval and measurement space and conclude by motivating the use of data assimilation techniques for analyzing and improving model parameterizations.

Active sensor synergy for arctic cloud microphysics

NASA Astrophysics Data System (ADS)

Sato, Kaori; Okamoto, Hajime; Katagiri, Shuichiro; Shiobara, Masataka; Yabuki, Masanori; Takano, Toshiaki

2018-04-01

In this study, we focus on the retrieval of liquid and ice-phase cloud microphysics from spaceborne and ground-based lidar-cloud radar synergy. As an application of the cloud retrieval algorithm developed for the EarthCARE satellite mission (JAXA-ESA) [1], the derived statistics of cloud microphysical properties in high latitudes and their relation to the Arctic climate are investigated.

Retrieval of Boundary Layer 3D Cloud Properties Using Scanning Cloud Radar and 3D Radiative Transfer

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

Marchand, Roger

Retrievals of cloud optical and microphysical properties for boundary layer clouds, including those widely used by ASR investigators, frequently assume that clouds are sufficiently horizontally homogeneous that scattering and absorption (at all wavelengths) can be treated using one dimensional (1D) radiative transfer, and that differences in the field-of-view of different sensors are unimportant. Unfortunately, most boundary layer clouds are far from horizontally homogeneous, and numerous theoretical and observational studies show that the assumption of horizontal homogeneity leads to significant errors. The introduction of scanning cloud and precipitation radars at the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) programmore » sites presents opportunities to move beyond the horizontally homogeneous assumption. The primary objective of this project was to develop a 3D retrieval for warm-phase (liquid only) boundary layer cloud microphysical properties, and to assess errors in current 1D (non-scanning) approaches. Specific research activities also involved examination of the diurnal cycle of hydrometeors as viewed by ARM cloud radar, and continued assessment of precipitation impacts on retrievals of cloud liquid water path using passive microwaves.« less

Unveiling aerosol-cloud interactions - Part 1: Cloud contamination in satellite products enhances the aerosol indirect forcing estimate

NASA Astrophysics Data System (ADS)

Christensen, Matthew W.; Neubauer, David; Poulsen, Caroline A.; Thomas, Gareth E.; McGarragh, Gregory R.; Povey, Adam C.; Proud, Simon R.; Grainger, Roy G.

2017-11-01

Increased concentrations of aerosol can enhance the albedo of warm low-level cloud. Accurately quantifying this relationship from space is challenging due in part to contamination of aerosol statistics near clouds. Aerosol retrievals near clouds can be influenced by stray cloud particles in areas assumed to be cloud-free, particle swelling by humidification, shadows and enhanced scattering into the aerosol field from (3-D radiative transfer) clouds. To screen for this contamination we have developed a new cloud-aerosol pairing algorithm (CAPA) to link cloud observations to the nearest aerosol retrieval within the satellite image. The distance between each aerosol retrieval and nearest cloud is also computed in CAPA. Results from two independent satellite imagers, the Advanced Along-Track Scanning Radiometer (AATSR) and Moderate Resolution Imaging Spectroradiometer (MODIS), show a marked reduction in the strength of the intrinsic aerosol indirect radiative forcing when selecting aerosol pairs that are located farther away from the clouds (-0.28±0.26 W m-2) compared to those including pairs that are within 15 km of the nearest cloud (-0.49±0.18 W m-2). The larger aerosol optical depths in closer proximity to cloud artificially enhance the relationship between aerosol-loading, cloud albedo, and cloud fraction. These results suggest that previous satellite-based radiative forcing estimates represented in key climate reports may be exaggerated due to the inclusion of retrieval artefacts in the aerosol located near clouds.

Microwave Passive Ground-Based Retrievals of Cloud and Rain Liquid Water Path in Drizzling Clouds: Challenges and Possibilities

DOE PAGES

Cadeddu, Maria P.; Marchand, Roger; Orlandi, Emiliano; ...

2017-08-11

Satellite and ground-based microwave radiometers are routinely used for the retrieval of liquid water path (LWP) under all atmospheric conditions. The retrieval of water vapor and LWP from ground-based radiometers during rain has proved to be a difficult challenge for two principal reasons: the inadequacy of the nonscattering approximation in precipitating clouds and the deposition of rain drops on the instrument's radome. In this paper, we combine model computations and real ground-based, zenith-viewing passive microwave radiometer brightness temperature measurements to investigate how total, cloud, and rain LWP retrievals are affected by assumptions on the cloud drop size distribution (DSD) andmore » under which conditions a nonscattering approximation can be considered reasonably accurate. Results show that until the drop effective diameter is larger than similar to 200 mu m, a nonscattering approximation yields results that are still accurate at frequencies less than 90 GHz. For larger drop sizes, it is shown that higher microwave frequencies contain useful information that can be used to separate cloud and rain LWP provided that the vertical distribution of hydrometeors, as well as the DSD, is reasonably known. The choice of the DSD parameters becomes important to ensure retrievals that are consistent with the measurements. A physical retrieval is tested on a synthetic data set and is then used to retrieve total, cloud, and rain LWP from radiometric measurements during two drizzling cases at the atmospheric radiation measurement Eastern North Atlantic site.« less

Microwave Passive Ground-Based Retrievals of Cloud and Rain Liquid Water Path in Drizzling Clouds: Challenges and Possibilities

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

Cadeddu, Maria P.; Marchand, Roger; Orlandi, Emiliano

Satellite and ground-based microwave radiometers are routinely used for the retrieval of liquid water path (LWP) under all atmospheric conditions. The retrieval of water vapor and LWP from ground-based radiometers during rain has proved to be a difficult challenge for two principal reasons: the inadequacy of the nonscattering approximation in precipitating clouds and the deposition of rain drops on the instrument's radome. In this paper, we combine model computations and real ground-based, zenith-viewing passive microwave radiometer brightness temperature measurements to investigate how total, cloud, and rain LWP retrievals are affected by assumptions on the cloud drop size distribution (DSD) andmore » under which conditions a nonscattering approximation can be considered reasonably accurate. Results show that until the drop effective diameter is larger than similar to 200 mu m, a nonscattering approximation yields results that are still accurate at frequencies less than 90 GHz. For larger drop sizes, it is shown that higher microwave frequencies contain useful information that can be used to separate cloud and rain LWP provided that the vertical distribution of hydrometeors, as well as the DSD, is reasonably known. The choice of the DSD parameters becomes important to ensure retrievals that are consistent with the measurements. A physical retrieval is tested on a synthetic data set and is then used to retrieve total, cloud, and rain LWP from radiometric measurements during two drizzling cases at the atmospheric radiation measurement Eastern North Atlantic site.« less

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.

An Algorithm for the Retrieval of Droplet Number Concentration and Geometrical Thickness of Stratiform Marine Boundary Layer Clouds Applied to MODIS Radiometric Observations.

NASA Astrophysics Data System (ADS)

Schüller, Lothar; Bennartz, Ralf; Fischer, Jürgen; Brenguier, Jean-Louis

2005-01-01

Algorithms are now currently used for the retrieval of cloud optical thickness and droplet effective radius from multispectral radiance measurements. This paper extends their application to the retrieval of cloud droplet number concentration, cloud geometrical thickness, and liquid water path in shallow convective clouds, using an algorithm that was previously tested with airborne measurements of cloud radiances and validated against in situ measurements of the same clouds. The retrieval is based on a stratified cloud model of liquid water content and droplet spectrum. Radiance measurements in visible and near-infrared channels of the Moderate Resolution Imaging Spectroradiometer (MODIS), which is operated from the NASA platforms Terra and Aqua, are analyzed. Because of uncertainties in the simulation of the continental surface reflectance, the algorithm is presently limited to the monitoring of the microphysical structure of boundary layer clouds over the ocean. Two MODIS scenes of extended cloud fields over the North Atlantic Ocean trade wind region are processed. A transport and dispersion model (the Hybrid Single-Particle Lagrangian Integrated Trajectory Model, HYSPLIT4) is also used to characterize the origin of the air masses and hence their aerosol regimes. One cloud field formed in an air mass that was advected from southern Europe and North Africa. It shows high values of the droplet concentration when compared with the second cloud system, which developed in a more pristine environment. The more pristine case also exhibits a higher geometrical thickness and, thus, liquid water path, which counterbalances the expected cloud albedo increase of the polluted case. Estimates of cloud liquid water path are then compared with retrievals from the Special Sensor Microwave Imager (SSM/I). SSM/I-derived liquid water paths are in good agreement with the MODIS-derived values.

Interpretation of multi-wavelength-retrieved cloud droplet effective radii in terms of cloud vertical inhomogeneity based on water cloud simulations using a spectral-bin microphysics cloud model

NASA Astrophysics Data System (ADS)

Matsui, T. N.; Suzuki, K.; Nakajima, T. Y.; Matsumae, Y.

2011-12-01

Clouds play an import role in energy balance and climate changes of the Earth. IPCC AR4, however, pointed out that cloud feedback is still the large source of uncertainty in climate estimates. In the recent decade, the new satellites with the active instruments (e.g. Cloudsat) represented a new epoch in earth observations. The active remote sensing is powerful for illustrating the vertical structures of clouds, but the passive remote sensing from satellite images also contribute to better understating of cloud system. For instance, Nakajima et al. (2010a) and Suzuki et al. (2010) illustrated transition of cloud growth, from cloud droplet to drizzle to rain, using the combine analysis of the cloud droplet size retrieved from passive images (MODIS) and the reflectivity profiles from Cloudsat. Furthermore, EarthCARE that is a new satellite launched years later is composed of not only the active but also passive instruments for the combined analysis. On the other hands, the methods to retrieve the advanced information of cloud properties are also required because many imagers have been operated and are now planned (e.g. GCOM-C/SGLI), and have the advantages such as wide observation width and more observation channels. Cloud droplet effective radius (CDR) and cloud optical thickness (COT) can be retrieved using a non-water-absorbing band (e.g. 0.86μm) and a water-absorbing band (1.6, 2.1, 3.7μm) of imagers under the assumptions such as the log-normal droplet size distribution and the plane-parallel cloud structure. However, the differences between three retrieved CDRs using 1.6, 2.1 or 3.7μm (R16, R21 and R37) are found in the satellite observations. Several studies pointed out that vertical/horizontal inhomogeneity of cloud structure, difference of penetration depth of water-absorbing bands, multi-modal droplet distribution and/or 3-D radiative transfer effect cause the CDR differences. In other words, the advanced information of clouds may lie hidden in the differences. Nakajima et al. (2010b) investigated the impact of the differences sensitivities to particle size and the penetration depth in an attempt to explain the CDR differences found in by using a simple two-layer cloud model with the bi-modal size distribution functions. Their results showed the sensitivity differences between 1.6, 2.1 and 3.7μm bands to droplet sizes and their vertical stratification. In this study, we further investigate the impact of the vertical inhomogeneity structure including the drizzle by using a spectral-bin microphysics cloud model. We apply the 1-D radiative transfer computation to the numerical cloud fields generated by the cloud model, and retrieve the CDRs from the reflectances thus simulated at each band. We then compare the statistics of these retrieved CDRs with the CDRs obtained from MODIS observations and derive the sensitivity functions of the retrieved CDRs to the particle size and the optical depth from the sets of the droplet distribution functions predicted by the model and the retrieved CDRs. This study is an attempt to interpret the CDR differences in terms of the cloud vertical structure and the cloud particle growth processes.

Retrieval of Cloud Properties for Partially Cloud-Filled Pixels During CRYSTAL-FACE

NASA Astrophysics Data System (ADS)

Nguyen, L.; Minnis, P.; Smith, W. L.; Khaiyer, M. M.; Heck, P. W.; Sun-Mack, S.; Uttal, T.; Comstock, J.

2003-12-01

Partially cloud-filled pixels can be a significant problem for remote sensing of cloud properties. Generally, the optical depth and effective particle sizes are often too small or too large, respectively, when derived from radiances that are assumed to be overcast but contain radiation from both clear and cloud areas within the satellite imager field of view. This study presents a method for reducing the impact of such partially cloud field pixels by estimating the cloud fraction within each pixel using higher resolution visible (VIS, 0.65mm) imager data. Although the nominal resolution for most channels on the Geostationary Operational Environmental Satellite (GOES) imager and the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra are 4 and 1 km, respectively, both instruments also take VIS channel data at 1 km and 0.25 km, respectively. Thus, it may be possible to obtain an improved estimate of cloud fraction within the lower resolution pixels by using the information contained in the higher resolution VIS data. GOES and MODIS multi-spectral data, taken during the Cirrus Regional Study of Tropical Anvils and Cirrus Layers - Florida Area Cirrus Experiment (CRYSTAL-FACE), are analyzed with the algorithm used for the Atmospheric Radiation Measurement Program (ARM) and the Clouds and Earth's Radiant Energy System (CERES) to derive cloud amount, temperature, height, phase, effective particle size, optical depth, and water path. Normally, the algorithm assumes that each pixel is either entirely clear or cloudy. In this study, a threshold method is applied to the higher resolution VIS data to estimate the partial cloud fraction within each low-resolution pixel. The cloud properties are then derived from the observed low-resolution radiances using the cloud cover estimate to properly extract the radiances due only to the cloudy part of the scene. This approach is applied to both GOES and MODIS data to estimate the improvement in the retrievals for each resolution. Results are compared with the radar reflectivity techniques employed by the NOAA ETL MMCR and the PARSL 94 GHz radars located at the CRYSTAL-FACE Eastern & Western Ground Sites, respectively. This technique is most likely to yield improvements for low and midlevel layer clouds that have little thermal variability in cloud height.

Combined Ozone Retrieval From METOP Sensors Using META-Training Of Deep Neural Networks

NASA Astrophysics Data System (ADS)

Felder, Martin; Sehnke, Frank; Kaifel, Anton

2013-12-01

The newest installment of our well-proven Neural Net- work Ozone Retrieval System (NNORSY) combines the METOP sensors GOME-2 and IASI with cloud information from AVHRR. Through the use of advanced meta- learning techniques like automatic feature selection and automatic architecture search applied to a set of deep neural networks, having at least two or three hidden layers, we have been able to avoid many technical issues normally encountered during the construction of such a joint retrieval system. This has been made possible by harnessing the processing power of modern consumer graphics cards with high performance graphic processors (GPU), which decreases training times by about two orders of magnitude. The system was trained on data from 2009 and 2010, including target ozone profiles from ozone sondes, ACE- FTS and MLS-AURA. To make maximum use of tropospheric information in the spectra, the data were partitioned into several sets of different cloud fraction ranges with the GOME-2 FOV, on which specialized retrieval networks are being trained. For the final ozone retrieval processing the different specialized networks are combined. The resulting retrieval system is very stable and does not show any systematic dependence on solar zenith angle, scan angle or sensor degradation. We present several sensitivity studies with regard to cloud fraction and target sensor type, as well as the performance in several latitude bands and with respect to independent validation stations. A visual cross-comparison against high-resolution ozone profiles from the KNMI EUMETSAT Ozone SAF product has also been performed and shows some distinctive features which we will briefly discuss. Overall, we demonstrate that a complex retrieval system can now be constructed with a minimum of ma- chine learning knowledge, using automated algorithms for many design decisions previously requiring expert knowledge. Provided sufficient training data and computation power of GPUs is available, the method can be applied to almost any kind of retrieval or, more generally, regression problem.

Design of a Shadowband Spectral Radiometer for the Retrieval of Thin Cloud Optical Depth, Liquid Water Path, and the Effective Radius

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

Bartholomew M. J.; Reynolds, R. M.; Vogelmann, A. M.

2011-11-01

The design and operation of a Thin-Cloud Rotating Shadowband Radiometer (TCRSR) described here was used to measure the radiative intensity of the solar aureole and enable the simultaneous retrieval of cloud optical depth, drop effective radius, and liquid water path. The instrument consists of photodiode sensors positioned beneath two narrow metal bands that occult the sun by moving alternately from horizon to horizon. Measurements from the narrowband 415-nm channel were used to demonstrate a retrieval of the cloud properties of interest. With the proven operation of the relatively inexpensive TCRSR instrument, its usefulness for retrieving aerosol properties under cloud-free skiesmore » and for ship-based observations is discussed.« less

Retrieval of Aerosol Absorption Properties from Satellite Observations

NASA Technical Reports Server (NTRS)

Torres, Omar; Bhartia, Pawan K.; Jethva, H.; Ahn, Chang-Woo

2012-01-01

The Angstrom Absorption Exponent (AAE) is a parameter commonly used to characterize the wavelength-dependence of aerosol absorption optical depth (AAOD). It is closely related to aerosol composition. Black carbon (BC) containing aerosols yield AAE values near unity whereas Organic carbon (OC) aerosol particles are associated with values larger than 2. Even larger AAE values have been reported for desert dust aerosol particles. Knowledge of spectral AAOD is necessary for the calculation of direct radiative forcing effect of aerosols and for inferring aerosol composition. We have developed a satellitebased method of determining the spectral AAOD of absorbing aerosols. The technique uses multi-spectral measurements of upwelling radiation from scenes where absorbing aerosols lie above clouds as indicated by the UV Aerosol Index. For those conditions, the satellite measurement can be explained, using an approximations of Beer's Law (BL), as the upwelling reflectance at the cloud top attenuated by the absorption effects of the overlying aerosol layer. The upwelling reflectance at the cloud-top in an aerosol-free atmospheric column is mainly a function of cloud optical depth (COD). In the proposed method of AAE derivation, the first step is determining COD which is retrieved using a previously developed color-ratio based approach. In the second step, corrections for molecular scattering effects are applied to both the observed ad the calculated cloud reflectance terms, and the spectral AAOD is then derived by an inversion of the BL approximation. The proposed technique will be discussed in detail and application results making use of OMI multi-spectral measurements in the UV-Vis. will be presented.

Cloudy Sounding and Cloud-Top Height Retrieval From AIRS Alone Single Field-of-View Radiance Measurements

NASA Technical Reports Server (NTRS)

Weisz, Elisabeth; Li, Jun; Li, Jinlong; Zhou, Daniel K.; Huang, Hung-Lung; Goldberg, Mitchell D.; Yang, Ping

2007-01-01

High-spectral resolution measurements from the Atmospheric Infrared Sounder (AIRS) onboard the EOS (Earth Observing System) Aqua satellite provide unique information about atmospheric state, surface and cloud properties. This paper presents an AIRS alone single field-of-view (SFOV) retrieval algorithm to simultaneously retrieve temperature, humidity and ozone profiles under all weather conditions, as well as cloud top pressure (CTP) and cloud optical thickness (COT) under cloudy skies. For optically thick cloud conditions the above-cloud soundings are derived, whereas for clear skies and optically thin cloud conditions the profiles are retrieved from 0.005 hPa down to the earth's surface. Initial validation has been conducted by using the operational MODIS (Moderate Resolution Imaging Spectroradiometer) product, ECMWF (European Center of Medium range Weather Forecasts) analysis fields and radiosonde observations (RAOBs). These inter-comparisons clearly demonstrate the potential of this algorithm to process data from 38 high-spectral infrared (IR) sounder instruments.

Retrieve Optically Thick Ice Cloud Microphysical Properties by Using Airborne Dual-Wavelength Radar Measurements

NASA Technical Reports Server (NTRS)

Wang, Zhien; Heymsfield, Gerald M.; Li, Lihua; Heymsfield, Andrew J.

2005-01-01

An algorithm to retrieve optically thick ice cloud microphysical property profiles is developed by using the GSFC 9.6 GHz ER-2 Doppler Radar (EDOP) and the 94 GHz Cloud Radar System (CRS) measurements aboard the high-altitude ER-2 aircraft. In situ size distribution and total water content data from the CRYSTAL-FACE field campaign are used for the algorithm development. To reduce uncertainty in calculated radar reflectivity factors (Ze) at these wavelengths, coincident radar measurements and size distribution data are used to guide the selection of mass-length relationships and to deal with the density and non-spherical effects of ice crystals on the Ze calculations. The algorithm is able to retrieve microphysical property profiles of optically thick ice clouds, such as, deep convective and anvil clouds, which are very challenging for single frequency radar and lidar. Examples of retrieved microphysical properties for a deep convective clouds are presented, which show that EDOP and CRS measurements provide rich information to study cloud structure and evolution. Good agreement between IWPs derived from an independent submillimeter-wave radiometer, CoSSIR, and dual-wavelength radar measurements indicates accuracy of the IWC retrieved from the two-frequency radar algorithm.

The "RED Versa NIR" Plane to Retrieve Broken-Cloud Optical Depth from Ground-Based Measurements"

NASA Technical Reports Server (NTRS)

Marshak, A.; Knyazikhin, Y.; Evans, K.; Wiscombe, W.

2003-01-01

A new method for retrieving cloud optical depth from ground-based measurements of zenith radiance in the RED and near infrared (MR) spectral regions is introduced. Because zenith radiance does not have a one-to-one relationship with optical depth, it is absolutely impossible to use a monochromatic retrieval. On the other side, algebraic combinations of spectral radiances such as NDCI while largely removing nouniquiness and the radiative effects of cloud inhomogeneity, can result in poor retrievals due to its insensitivity to cloud fraction. Instead, both RED and NIR radiances as points on the 'RED vs. NIR' plane are proposed to be used for retrieval. The proposed retrieval method is applied to Cimel measurements at the Atmospheric Radiation Measurements (ARM) site in Oklahoma. Cimel, a multi-channel sunphotometer, is a part of AERONET - a ground-based network for monitoring aerosol optical properties. The results of retrieval are compared with the ones from Microwave Radiometer (MWR) and Multi-Filter Rotating Shadowband Radiometers (MFRSR) located next to Cimel at the ARM site. In addition, the performance of the retrieval method is assessed using a fractal model of cloud inhomogeneity and broken cloudiness. The preliminary results look very promising both theoretically and from measurements.

Information content of visible and midinfrared radiances for retrieving tropical ice cloud properties

NASA Astrophysics Data System (ADS)

Chang, Kai-Wei; L'Ecuyer, Tristan S.; Kahn, Brian H.; Natraj, Vijay

2017-05-01

Hyperspectral instruments such as Atmospheric Infrared Sounder (AIRS) have spectrally dense observations effective for ice cloud retrievals. However, due to the large number of channels, only a small subset is typically used. It is crucial that this subset of channels be chosen to contain the maximum possible information about the retrieved variables. This study describes an information content analysis designed to select optimal channels for ice cloud retrievals. To account for variations in ice cloud properties, we perform channel selection over an ensemble of cloud regimes, extracted with a clustering algorithm, from a multiyear database at a tropical Atmospheric Radiation Measurement site. Multiple satellite viewing angles over land and ocean surfaces are considered to simulate the variations in observation scenarios. The results suggest that AIRS channels near wavelengths of 14, 10.4, 4.2, and 3.8 μm contain the most information. With an eye toward developing a joint AIRS-MODIS (Moderate Resolution Imaging Spectroradiometer) retrieval, the analysis is also applied to combined measurements from both instruments. While application of this method to MODIS yields results consistent with previous channel sensitivity studies, the analysis shows that this combination may yield substantial improvement in cloud retrievals. MODIS provides most information on optical thickness and particle size, aided by a better constraint on cloud vertical placement from AIRS. An alternate scenario where cloud top boundaries are supplied by the active sensors in the A-train is also explored. The more robust cloud placement afforded by active sensors shifts the optimal channels toward the window region and shortwave infrared, further constraining optical thickness and particle size.

Estimating optically-thin cirrus cloud induced cold bias on infrared radiometric satellite sea surface temperature retrieval in the tropics

NASA Astrophysics Data System (ADS)

Marquis, Jared Wayne

Passive longwave infrared radiometric satellite-based retrievals of sea surface temperature (SST) at instrument nadir are investigated for cold bias caused by unscreened optically-thin cirrus (OTC) clouds (cloud optical depth ≤ 0.3; COD). Level 2 split-window SST retrievals over tropical oceans (30° S - 30° N) from Moderate Resolution Imaging Spectroradiometer (MODIS) radiances collected aboard the NASA Aqua satellite (Aqua-MODIS) are collocated with cloud profiles from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument, mounted on the independent NASA CALIPSO satellite. OTC are present in approximately 25% of tropical quality-assured (QA) Aqua-MODIS Level-2 data, representing over 99% of all contaminating cirrus found. This results in cold-biased SST retrievals using either split- (MODIS, AVHRR and VIIRS) or triple-window (AVHRR and VIIRS only) retrieval methods. SST retrievals are modeled based on operational algorithms using radiative transfer model simulations conducted with a hypothetical 1.5 km thick OTC cloud placed incrementally from 10.0 - 18.0 km above mean sea level for cloud optical depths (COD) between 0.0 - 0.3. Corresponding cold bias estimates for each sensor are estimated using relative Aqua-MODIS cloud contamination frequencies as a function of cloud top height and COD (assuming them consistent across each platform) integrated within each corresponding modeled cold bias matrix. Split-window relative OTC cold biases, for any single observation, range from 0.40° - 0.49° C for the three sensors, with an absolute (bulk mean) bias between 0.10° - 0.13° C. Triple-window retrievals are more resilient, ranging from 0.03° - 0.04° C relative and 0.11° - 0.16° C absolute. Cold biases are constant across the Pacific and Indian Ocean domains. Absolute bias is smaller over the Atlantic, but relative bias is larger due to different cloud properties indicating that this issue persists globally.

How Do A-train Sensors Intercompare in the Retrieval of Above-cloud Aerosol Optical Depth? A Case Study-based Assessment

NASA Technical Reports Server (NTRS)

Jethva, Hiren; Torres, Omar; Waquet, Fabien; Chand, Duli; Hu, Yongxiang

2014-01-01

We intercompare the above-cloud aerosol optical depth (ACAOD) of biomass burning plumes retrieved from A-train sensors, i.e., Moderate Resolution Imaging Spectroradiometer (MODIS), Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), Polarization and Directionality of Earth Reflectances (POLDER), and Ozone Monitoring Instrument (OMI). These sensors have shown independent capabilities to retrieve aerosol loading above marine boundary layer clouds-a kind of situation often found over the southeast Atlantic Ocean during dry burning season. A systematic comparison reveals that all passive sensors and CALIOP-based research methods derive comparable ACAOD with differences mostly within 0.2 over homogeneous cloud fields. The 532 nm ACAOD retrieved by CALIOP operational algorithm is underestimated. The retrieved 1064 nm AOD however shows closer agreement with passive sensors. Given the different types of measurements processed with different algorithms, the reported close agreement between them is encouraging. Due to unavailability of direct measurements above cloud, the validation of satellite-based ACAOD remains an open challenge. The intersatellite comparison however can be useful for the relative evaluation and consistency check

Validation of CERES-MODIS Arctic cloud properties using CloudSat/CALIPSO and ARM NSA observations

NASA Astrophysics Data System (ADS)

Giannecchini, K.; Dong, X.; Xi, B.; Minnis, P.; Kato, S.

2011-12-01

The traditional passive satellite studies of cloud properties in the Arctic are often affected by the complex surface features present across the region. Nominal visual and thermal contrast exists between Arctic clouds and the snow- and ice-covered surfaces beneath them, which can lead to difficulties in satellite retrievals of cloud properties. However, the addition of active sensors to the A-Train constellation of satellites has increased the availability of validation sources for cloud properties derived from passive sensors in the data-sparse high-latitude regions. In this study, Arctic cloud fraction and cloud heights derived from the NASA CERES team (CERES-MODIS) have been compared with CloudSat/CALIPSO and DOE ARM NSA radar-lidar observations over Barrow, AK, for the two-year period from 2007 to 2008. An Arctic-wide comparison of cloud fraction and height between CERES-MODIS and CloudSat/CALIPSO was then conducted for the same time period. The CERES-MODIS cloud properties, which include cloud fraction and cloud effective heights, were retrieved using the 4-channel VISST (Visible Infrared Solar-Infrared Split-window Technique) [Minnis et al.,1995]. CloudSat/CALIPSO cloud fraction and cloud-base and -top heights were from version RelB1 data products determined by both the 94 GHz radar onboard CloudSat and the lidar on CALIPSO with a vertical resolution of 30 m below 8.2 km and 60 m above. To match the surface and satellite observations/retrievals, the ARM surface observations were averaged into 3-hour intervals centered at the time of the satellite overpass, while satellite observations were averaged within a 3°x3° grid box centered on the Barrow site. The preliminary results have shown that all observed CFs have peaks during April-May and September-October, and dips during winter months (January-February) and summer months (June-July) during the study period of 2007-2008. ARM radar-lidar and CloudSat/CALIPSO show generally good agreement in CF (0.79 vs. 0.74), while CERES-MODIS derived values are much lower (0.60). CERES-MODIS derived cloud effective height (2.7 km) falls between the CloudSat/CALIPSO derived cloud base (0.6 km) and top (6.4 km) and the ARM ceilometers and MMCR derived cloud base (0.9 km) and radar derived cloud top (5.8 km). When extended to the entire Arctic, although the CERES-MODIS and Cloudsat/CALIPSO derived annual mean CFs agree within a few percents, there are significant differences over several regions, and the maximum cloud heights derived from CloudSat/CALIPSO (13.4 km) and CERES-MODIS (10.7 km) show the largest disagreement during early spring.

Satellite and Surface Data Synergy for Developing a 3D Cloud Structure and Properties Characterization Over the ARM SGP. Stage 1: Cloud Amounts, Optical Depths, and Cloud Heights Reconciliation

NASA Technical Reports Server (NTRS)

Genkova, I.; Long, C. N.; Heck, P. W.; Minnis, P.

2003-01-01

One of the primary Atmospheric Radiation Measurement (ARM) Program objectives is to obtain measurements applicable to the development of models for better understanding of radiative processes in the atmosphere. We address this goal by building a three-dimensional (3D) characterization of the cloud structure and properties over the ARM Southern Great Plains (SGP). We take the approach of juxtaposing the cloud properties as retrieved from independent satellite and ground-based retrievals, and looking at the statistics of the cloud field properties. Once these retrievals are well understood, they will be used to populate the 3D characterization database. As a first step we determine the relationship between surface fractional sky cover and satellite viewing angle dependent cloud fraction (CF). We elaborate on the agreement intercomparing optical depth (OD) datasets from satellite and ground using available retrieval algorithms with relation to the CF, cloud height, multi-layer cloud presence, and solar zenith angle (SZA). For the SGP Central Facility, where output from the active remote sensing cloud layer (ARSCL) valueadded product (VAP) is available, we study the uncertainty of satellite estimated cloud heights and evaluate the impact of this uncertainty for radiative studies.

The MODIS Cloud Optical and Microphysical Products: Collection 6 Up-dates and Examples From Terra and Aqua

NASA Technical Reports Server (NTRS)

Platnick, Steven; Meyer, Kerry G.; King, Michael D.; Wind, Galina; Amarasinghe, Nandana; Marchant, Benjamin G.; Arnold, G. Thomas; Zhang, Zhibo; Hubanks, Paul A.; Holz, Robert E.;

The MODIS cloud optical and microphysical products: Collection 6 updates and examples from Terra and Aqua.

PubMed

Platnick, Steven; Meyer, Kerry G; King, Michael D; Wind, Galina; Amarasinghe, Nandana; Marchant, Benjamin; Arnold, G Thomas; Zhang, Zhibo; Hubanks, Paul A; Holz, Robert E; Yang, Ping; Ridgway, William L; Riedi, Jérôme

2017-01-01

The MODIS Level-2 cloud product (Earth Science Data Set names MOD06 and MYD06 for Terra and Aqua MODIS, respectively) provides pixel-level retrievals of cloud-top properties (day and night pressure, temperature, and height) and cloud optical properties (optical thickness, effective particle radius, and water path for both liquid water and ice cloud thermodynamic phases-daytime only). Collection 6 (C6) reprocessing of the product was completed in May 2014 and March 2015 for MODIS Aqua and Terra, respectively. Here we provide an overview of major C6 optical property algorithm changes relative to the previous Collection 5 (C5) product. Notable C6 optical and microphysical algorithm changes include: (i) new ice cloud optical property models and a more extensive cloud radiative transfer code lookup table (LUT) approach, (ii) improvement in the skill of the shortwave-derived cloud thermodynamic phase, (iii) separate cloud effective radius retrieval datasets for each spectral combination used in previous collections, (iv) separate retrievals for partly cloudy pixels and those associated with cloud edges, (v) failure metrics that provide diagnostic information for pixels having observations that fall outside the LUT solution space, and (vi) enhanced pixel-level retrieval uncertainty calculations. The C6 algorithm changes collectively can result in significant changes relative to C5, though the magnitude depends on the dataset and the pixel's retrieval location in the cloud parameter space. Example Level-2 granule and Level-3 gridded dataset differences between the two collections are shown. While the emphasis is on the suite of cloud optical property datasets, other MODIS cloud datasets are discussed when relevant.

The MODIS cloud optical and microphysical products: Collection 6 updates and examples from Terra and Aqua

PubMed Central

Platnick, Steven; Meyer, Kerry G.; King, Michael D.; Wind, Galina; Amarasinghe, Nandana; Marchant, Benjamin; Arnold, G. Thomas; Zhang, Zhibo; Hubanks, Paul A.; Holz, Robert E.; Yang, Ping; Ridgway, William L.; Riedi, Jérôme

2018-01-01

The MODIS Level-2 cloud product (Earth Science Data Set names MOD06 and MYD06 for Terra and Aqua MODIS, respectively) provides pixel-level retrievals of cloud-top properties (day and night pressure, temperature, and height) and cloud optical properties (optical thickness, effective particle radius, and water path for both liquid water and ice cloud thermodynamic phases–daytime only). Collection 6 (C6) reprocessing of the product was completed in May 2014 and March 2015 for MODIS Aqua and Terra, respectively. Here we provide an overview of major C6 optical property algorithm changes relative to the previous Collection 5 (C5) product. Notable C6 optical and microphysical algorithm changes include: (i) new ice cloud optical property models and a more extensive cloud radiative transfer code lookup table (LUT) approach, (ii) improvement in the skill of the shortwave-derived cloud thermodynamic phase, (iii) separate cloud effective radius retrieval datasets for each spectral combination used in previous collections, (iv) separate retrievals for partly cloudy pixels and those associated with cloud edges, (v) failure metrics that provide diagnostic information for pixels having observations that fall outside the LUT solution space, and (vi) enhanced pixel-level retrieval uncertainty calculations. The C6 algorithm changes collectively can result in significant changes relative to C5, though the magnitude depends on the dataset and the pixel’s retrieval location in the cloud parameter space. Example Level-2 granule and Level-3 gridded dataset differences between the two collections are shown. While the emphasis is on the suite of cloud optical property datasets, other MODIS cloud datasets are discussed when relevant. PMID:29657349

Cloud Coverage and Height Distribution from the GLAS Polar Orbiting Lidar: Comparison to Passive Cloud Retrievals

NASA Technical Reports Server (NTRS)

Spinhime, J. D.; Palm, S. P.; Hlavka, D. L.; Hart, W. D.; Mahesh, A.

2004-01-01

The Geoscience Laser Altimeter System (GLAS) began full on orbit operations in September 2003. A main application of the two-wavelength GLAS lidar is highly accurate detection and profiling of global cloud cover. Initial analysis indicates that cloud and aerosol layers are consistently detected on a global basis to cross-sections down to 10(exp -6) per meter. Images of the lidar data dramatically and accurately show the vertical structure of cloud and aerosol to the limit of signal attenuation. The GLAS lidar has made the most accurate measurement of global cloud coverage and height to date. In addition to the calibrated lidar signal, GLAS data products include multi level boundaries and optical depth of all transmissive layers. Processing includes a multi-variable separation of cloud and aerosol layers. An initial application of the data results is to compare monthly cloud means from several months of GLAS observations in 2003 to existing cloud climatologies from other satellite measurement. In some cases direct comparison to passive cloud retrievals is possible. A limitation of the lidar measurements is nadir only sampling. However monthly means exhibit reasonably good global statistics and coverage results, at other than polar regions, compare well with other measurements but show significant differences in height distribution. For polar regions where passive cloud retrievals are problematic and where orbit track density is greatest, the GLAS results are particularly an advance in cloud cover information. Direct comparison to MODIS retrievals show a better than 90% agreement in cloud detection for daytime, but less than 60% at night. Height retrievals are in much less agreement. GLAS is a part of the NASA EOS project and data products are thus openly available to the science community (see http://glo.gsfc.nasa.gov).

Effect of Thin Cirrus Clouds on Dust Optical Depth Retrievals From MODIS Observations

NASA Technical Reports Server (NTRS)

Feng, Qian; Hsu, N. Christina; Yang, Ping; Tsay, Si-Chee

2011-01-01

The effect of thin cirrus clouds in retrieving the dust optical depth from MODIS observations is investigated by using a simplified aerosol retrieval algorithm based on the principles of the Deep Blue aerosol property retrieval method. Specifically, the errors of the retrieved dust optical depth due to thin cirrus contamination are quantified through the comparison of two retrievals by assuming dust-only atmospheres and the counterparts with overlapping mineral dust and thin cirrus clouds. To account for the effect of the polarization state of radiation field on radiance simulation, a vector radiative transfer model is used to generate the lookup tables. In the forward radiative transfer simulations involved in generating the lookup tables, the Rayleigh scattering by atmospheric gaseous molecules and the reflection of the surface assumed to be Lambertian are fully taken into account. Additionally, the spheroid model is utilized to account for the nonsphericity of dust particles In computing their optical properties. For simplicity, the single-scattering albedo, scattering phase matrix, and optical depth are specified a priori for thin cirrus clouds assumed to consist of droxtal ice crystals. The present results indicate that the errors in the retrieved dust optical depths due to the contamination of thin cirrus clouds depend on the scattering angle, underlying surface reflectance, and dust optical depth. Under heavy dusty conditions, the absolute errors are comparable to the predescribed optical depths of thin cirrus clouds.

Vertical variation of ice particle size in convective cloud tops.

PubMed

van Diedenhoven, Bastiaan; Fridlind, Ann M; Cairns, Brian; Ackerman, Andrew S; Yorks, John E

2016-05-16

A novel technique is used to estimate derivatives of ice effective radius with respect to height near convective cloud tops ( dr e / dz ) from airborne shortwave reflectance measurements and lidar. Values of dr e / dz are about -6 μ m/km for cloud tops below the homogeneous freezing level, increasing to near 0 μ m/km above the estimated level of neutral buoyancy. Retrieved dr e / dz compares well with previously documented remote sensing and in situ estimates. Effective radii decrease with increasing cloud top height, while cloud top extinction increases. This is consistent with weaker size sorting in high, dense cloud tops above the level of neutral buoyancy where fewer large particles are present, and with stronger size sorting in lower cloud tops that are less dense. The results also confirm that cloud-top trends of effective radius can generally be used as surrogates for trends with height within convective cloud tops. These results provide valuable observational targets for model evaluation.

Vertical Variation of Ice Particle Size in Convective Cloud Tops

NASA Technical Reports Server (NTRS)

Van Diedenhoven, Bastiaan; Fridlind, Ann M.; Cairns, Brian; Ackerman, Andrew S.; Yorks, John E.

2016-01-01

A novel technique is used to estimate derivatives of ice effective radius with respect to height near convective cloud tops (dr(sub e)/dz) from airborne shortwave reflectance measurements and lidar. Values of dr(sub e)/dz are about -6 micrometer/km for cloud tops below the homogeneous freezing level, increasing to near 0 micrometer/km above the estimated level of neutral buoyancy. Retrieved dr(sub e)/dz compares well with previously documented remote sensing and in situ estimates. Effective radii decrease with increasing cloud top height, while cloud top extinction increases. This is consistent with weaker size sorting in high, dense cloud tops above the level of neutral buoyancy where fewer large particles are present and with stronger size sorting in lower cloud tops that are less dense. The results also confirm that cloud top trends of effective radius can generally be used as surrogates for trends with height within convective cloud tops. These results provide valuable observational targets for model evaluation.

3D Radiative Aspects of the Increased Aerosol Optical Depth Near Clouds

NASA Technical Reports Server (NTRS)

Marshak, Alexander; Wen, Guoyong; Remer, Lorraine; Cahalan, Robert; Coakley, Jim

2007-01-01

To characterize aerosol-cloud interactions it is important to correctly retrieve aerosol optical depth in the vicinity of clouds. It is well reported in the literature that aerosol optical depth increases with cloud cover. Part of the increase comes from real physics as humidification; another part, however, comes from 3D cloud effects in the remote sensing retrievals. In many cases it is hard to say whether the retrieved increased values of aerosol optical depth are remote sensing artifacts or real. In the presentation, we will discuss how the 3D cloud affects can be mitigated. We will demonstrate a simple model that can assess the enhanced illumination of cloud-free columns in the vicinity of clouds. This model is based on the assumption that the enhancement in the cloud-free column radiance comes from the enhanced Rayleigh scattering due to presence of surrounding clouds. A stochastic cloud model of broken cloudiness is used to simulate the upward flux.

Marine Boundary Layer Cloud Property Retrievals from High-Resolution ASTER Observations: Case Studies and Comparison with Terra MODIS

NASA Technical Reports Server (NTRS)

Werner, Frank; Wind, Galina; Zhang, Zhibo; Platnick, Steven; Di Girolamo, Larry; Zhao, Guangyu; Amarasinghe, Nandana; Meyer, Kerry

2016-01-01

A research-level retrieval algorithm for cloud optical and microphysical properties is developed for the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) aboard the Terra satellite. It is based on the operational MODIS algorithm. This paper documents the technical details of this algorithm and evaluates the retrievals for selected marine boundary layer cloud scenes through comparisons with the operational MODIS Data Collection 6 (C6) cloud product. The newly developed, ASTERspecific cloud masking algorithm is evaluated through comparison with an independent algorithm reported in Zhao and Di Girolamo (2006). To validate and evaluate the cloud optical thickness (tau) and cloud effective radius (r(sub eff)) from ASTER, the high-spatial-resolution ASTER observations are first aggregated to the same 1000m resolution as MODIS. Subsequently, tau(sub aA) and r(sub eff, aA) retrieved from the aggregated ASTER radiances are compared with the collocated MODIS retrievals. For overcast pixels, the two data sets agree very well with Pearson's product-moment correlation coefficients of R greater than 0.970. However, for partially cloudy pixels there are significant differences between r(sub eff, aA) and the MODIS results which can exceed 10 micrometers. Moreover, it is shown that the numerous delicate cloud structures in the example marine boundary layer scenes, resolved by the high-resolution ASTER retrievals, are smoothed by the MODIS observations. The overall good agreement between the research-level ASTER results and the operational MODIS C6 products proves the feasibility of MODIS-like retrievals from ASTER reflectance measurements and provides the basis for future studies concerning the scale dependency of satellite observations and three-dimensional radiative effects.

Marine boundary layer cloud property retrievals from high-resolution ASTER observations: case studies and comparison with Terra MODIS

NASA Astrophysics Data System (ADS)

Werner, Frank; Wind, Galina; Zhang, Zhibo; Platnick, Steven; Di Girolamo, Larry; Zhao, Guangyu; Amarasinghe, Nandana; Meyer, Kerry

2016-12-01

A research-level retrieval algorithm for cloud optical and microphysical properties is developed for the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) aboard the Terra satellite. It is based on the operational MODIS algorithm. This paper documents the technical details of this algorithm and evaluates the retrievals for selected marine boundary layer cloud scenes through comparisons with the operational MODIS Data Collection 6 (C6) cloud product. The newly developed, ASTER-specific cloud masking algorithm is evaluated through comparison with an independent algorithm reported in [Zhao and Di Girolamo(2006)]. To validate and evaluate the cloud optical thickness (τ) and cloud effective radius (reff) from ASTER, the high-spatial-resolution ASTER observations are first aggregated to the same 1000 m resolution as MODIS. Subsequently, τaA and reff, aA retrieved from the aggregated ASTER radiances are compared with the collocated MODIS retrievals. For overcast pixels, the two data sets agree very well with Pearson's product-moment correlation coefficients of R > 0.970. However, for partially cloudy pixels there are significant differences between reff, aA and the MODIS results which can exceed 10 µm. Moreover, it is shown that the numerous delicate cloud structures in the example marine boundary layer scenes, resolved by the high-resolution ASTER retrievals, are smoothed by the MODIS observations. The overall good agreement between the research-level ASTER results and the operational MODIS C6 products proves the feasibility of MODIS-like retrievals from ASTER reflectance measurements and provides the basis for future studies concerning the scale dependency of satellite observations and three-dimensional radiative effects.

Radiative transfer to space through a precipitating cloud at multiple microwave frequencies. I - Model description. II - Results and analysis

NASA Technical Reports Server (NTRS)

Mugnai, Alberto; Smith, Eric A.

1988-01-01

The impact of time-dependent cloud microphysical structure on the transfer to space of passive microwave radiation is studied at several frequencies across the EHF and lower SHF portions of the microwave spectrum. The feasibility of using multichannel passive-microwave retrieval techniques to estimate precipitation from space-based platforms is examined. The model is described, and the results are assessed in conjunction with a Nimbus-7 SMMR case study of precipitation in an intense tropical Pacific storm. It is concluded that the effects of cloud liquid water content must be considered to obtain a realistic estimation and distribution of rainrates.

Comparison of Monthly Mean Cloud Fraction and Cloud Optical depth Determined from Surface Cloud Radar, TOVS, AVHRR, and MODIS over Barrow, Alaska

NASA Technical Reports Server (NTRS)

Uttal, Taneil; Frisch, Shelby; Wang, Xuan-Ji; Key, Jeff; Schweiger, Axel; Sun-Mack, Sunny; Minnis, Patrick

2005-01-01

A one year comparison is made of mean monthly values of cloud fraction and cloud optical depth over Barrow, Alaska (71 deg 19.378 min North, 156 deg 36.934 min West) between 35 GHz radar-based retrievals, the TOVS Pathfinder Path-P product, the AVHRR APP-X product, and a MODIS based cloud retrieval product from the CERES-Team. The data sets represent largely disparate spatial and temporal scales, however, in this paper, the focus is to provide a preliminary analysis of how the mean monthly values derived from these different data sets compare, and determine how they can best be used separately, and in combination to provide reliable estimates of long-term trends of changing cloud properties. The radar and satellite data sets described here incorporate Arctic specific modifications that account for cloud detection challenges specific to the Arctic environment. The year 2000 was chosen for this initial comparison because the cloud radar data was particularly continuous and reliable that year, and all of the satellite retrievals of interest were also available for the year 2000. Cloud fraction was chosen as a comparison variable as accurate detection of cloud is the primary product that is necessary for any other cloud property retrievals. Cloud optical depth was additionally selected as it is likely the single cloud property that is most closely correlated to cloud influences on surface radiation budgets.

Study on ice cloud optical thickness retrieval with MODIS IR spectral bands

NASA Astrophysics Data System (ADS)

Zhang, Hong; Li, Jun

2005-01-01

The operational Moderate-Resolution Imaging Spectroradiometer (MODIS) products for cloud properties such as cloud-top pressure (CTP), effective cloud amount (ECA), cloud particle size (CPS), cloud optical thickness (COT), and cloud phase (CP) have been available for users globally. An approach to retrieve COT is investigated using MODIS infrared (IR) window spectral bands (8.5 mm, 11mm, and 12 mm). The COT retrieval from MODIS IR bands has the potential to provide microphysical properties with high spatial resolution during night. The results are compared with those from operational MODIS products derived from the visible (VIS) and near-infrared (NIR) bands during day. Sensitivity of COT to MODIS spectral brightness temperature (BT) and BT difference (BTD) values is studied. A look-up table is created from the cloudy radiative transfer model accounting for the cloud absorption and scattering for the cloud microphysical property retrieval. The potential applications and limitations are also discussed. This algorithm can be applied to the future imager systems such as Visible/Infrared Imager/Radiometer Suite (VIIRS) on the National Polar-orbiting Operational Environmental Satellite System (NPOESS) and Advanced Baseline Imager (ABI) on the Geostationary Operational Environmental Satellite (GOES)-R.

What is the Uncertainty in MODIS Aerosol Optical Depth in the Vicinity of Clouds?

NASA Technical Reports Server (NTRS)

Patadia, Falguni; Levy, Rob; Mattoo, Shana

2017-01-01

MODIS dark-target (DT) algorithm retrieves aerosol optical depth (AOD) using a Look Up Table (LUT) approach. Global comparison of AOD (Collection 6 ) with ground-based sun photometer gives an Estimated Error (EE) of +/-(0.04 + 10%) over ocean. However, EE does not represent per-retrieval uncertainty. For retrievals that are biased high compared to AERONET, here we aim to closely examine the contribution of biases due to presence of clouds and per-pixel retrieval uncertainty. We have characterized AOD uncertainty at 550 nm, due to standard deviation of reflectance in 10 km retrieval region, uncertainty related to gas (H2O, O3) absorption, surface albedo, and aerosol models. The uncertainty in retrieved AOD seems to lie within the estimated over ocean error envelope of +/-(0.03+10%). Regions between broken clouds tend to have higher uncertainty. Compared to C6 AOD, a retrieval omitting observations in the vicinity of clouds (< or = 1 km) is biased by about +/- 0.05. For homogeneous aerosol distribution, clear sky retrievals show near zero bias. Close look at per-pixel reflectance histograms suggests retrieval possibility using median reflectance values.

APOLLO_NG - a probabilistic interpretation of the APOLLO legacy for AVHRR heritage channels

NASA Astrophysics Data System (ADS)

Klüser, L.; Killius, N.; Gesell, G.

2015-04-01

The cloud processing scheme APOLLO (Avhrr Processing scheme Over cLouds, Land and Ocean) has been in use for cloud detection and cloud property retrieval since the late 1980s. The physics of the APOLLO scheme still build the backbone of a range of cloud detection algorithms for AVHRR (Advanced Very High Resolution Radiometer) heritage instruments. The APOLLO_NG (APOLLO_NextGeneration) cloud processing scheme is a probabilistic interpretation of the original APOLLO method. While building upon the physical principles having served well in the original APOLLO a couple of additional variables have been introduced in APOLLO_NG. Cloud detection is not performed as a binary yes/no decision based on these physical principals but is expressed as cloud probability for each satellite pixel. Consequently the outcome of the algorithm can be tuned from clear confident to cloud confident depending on the purpose. The probabilistic approach allows to retrieving not only the cloud properties (optical depth, effective radius, cloud top temperature and cloud water path) but also their uncertainties. APOLLO_NG is designed as a standalone cloud retrieval method robust enough for operational near-realtime use and for the application with large amounts of historical satellite data. Thus the radiative transfer solution is approximated by the same two stream approach which also had been used for the original APOLLO. This allows the algorithm to be robust enough for being applied to a wide range of sensors without the necessity of sensor-specific tuning. Moreover it allows for online calculation of the radiative transfer (i.e. within the retrieval algorithm) giving rise to a detailed probabilistic treatment of cloud variables. This study presents the algorithm for cloud detection and cloud property retrieval together with the physical principles from the APOLLO legacy it is based on. Furthermore a couple of example results from on NOAA-18 are presented.

Retrieval of radiative and microphysical properties of clouds from multispectral infrared measurements

NASA Astrophysics Data System (ADS)

Iwabuchi, Hironobu; Saito, Masanori; Tokoro, Yuka; Putri, Nurfiena Sagita; Sekiguchi, Miho

2016-12-01

Satellite remote sensing of the macroscopic, microphysical, and optical properties of clouds are useful for studying spatial and temporal variations of clouds at various scales and constraining cloud physical processes in climate and weather prediction models. Instead of using separate independent algorithms for different cloud properties, a unified, optimal estimation-based cloud retrieval algorithm is developed and applied to moderate resolution imaging spectroradiometer (MODIS) observations using ten thermal infrared bands. The model considers sensor configurations, background surface and atmospheric profile, and microphysical and optical models of ice and liquid cloud particles and radiative transfer in a plane-parallel, multilayered atmosphere. Measurement and model errors are thoroughly quantified from direct comparisons of clear-sky observations over the ocean with model calculations. Performance tests by retrieval simulations show that ice cloud properties are retrieved with high accuracy when cloud optical thickness (COT) is between 0.1 and 10. Cloud-top pressure is inferred with uncertainty lower than 10 % when COT is larger than 0.3. Applying the method to a tropical cloud system and comparing the results with the MODIS Collection 6 cloud product shows good agreement for ice cloud optical thickness when COT is less than about 5. Cloud-top height agrees well with estimates obtained by the CO2 slicing method used in the MODIS product. The present algorithm can detect optically thin parts at the edges of high clouds well in comparison with the MODIS product, in which these parts are recognized as low clouds by the infrared window method. The cloud thermodynamic phase in the present algorithm is constrained by cloud-top temperature, which tends not to produce results with an ice cloud that is too warm and liquid cloud that is too cold.

An Assessment of Differences Between Cloud Effective Particle Radius Retrievals for Marine Water Clouds from Three MODIS Spectral Bands

NASA Technical Reports Server (NTRS)

Platnick, Steven; Zhang, Zhibo

2011-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) cloud product provides three separate 1 km resolution retrievals of cloud particle effective radii (r (sub e)), derived from 1.6, 2.1 and 3.7 micron band observations. In this study, differences among the three size retrievals for maritime water clouds (designated as r (sub e), 1.6 r (sub e), 2.1 and r (sub e),3.7) were systematically investigated through a series of case studies and global analyses. Substantial differences are found between r (sub e),3.7 and r (sub e),2.1 retrievals (delta r (sub e),3.7-2.l), with a strong dependence on cloud regime. The differences are typically small, within +/- 2 micron, over relatively spatially homogeneous coastal stratocumulus cloud regions. However, for trade wind cumulus regimes, r (sub e),3.7 was found to be substantially smaller than r (sub e),2.1, sometimes by more than 10 micron. The correlation of delta r(sub e),3.7-2.1 with key cloud parameters, including the cloud optical thickness (tau), r (sub e) and a cloud horizontal heterogeneity index (H-sigma) derived from 250 m resolution MODIS 0.86 micron band observations, were investigated using one month of MODIS Terra data. It was found that differences among the three r (sub e) retrievals for optically thin clouds (tau <5) are highly variable, ranging from - 15 micron to 10 micron, likely due to the large MODIS retrieval uncertainties when the cloud is thin. The delta r (sub e),3.7-2.1 exhibited a threshold-like dependence on both r (sub e),2.l and H-sigma. The re,3.7 is found to agree reasonably well with re,2.! when re,2.l is smaller than about 15J-Lm, but becomes increasingly smaller than re,2.1 once re,2.! exceeds this size. All three re retrievals showed little dependence when H-sigma < 0.3 (defined as standard deviation divided by the mean for the 250 m pixels within a 1 km pixel retrieval). However, for H-=sigma >0.3, both r (sub e),1.6 and r (sub e),2.1 were seen to increase quickly with H-sigma. On the other hand, r (sub e),3.7 statistics showed little dependence on H-sigma and remained relatively stable over the whole range of H-sigma values. Potential contributing causes to the substantial r (sub e),3.7 and r (sub e),2.1 differences are discussed. In particular, based on both 1-D and 3-D radiative transfer simulations, we have elucidated mechanisms by which cloud heterogeneity and 3-D radiative effects can cause large differences between r (sub e),3.7 and r (sub e),2.l retrievals for highly inhomogeneous clouds. Our results suggest that the contrast in observed delta r (sub e)3.7-2.1 between cloud regimes is correlated with increases in both cloud r (sub e) and H-sigma. We also speculate that in some highly inhomogeneous drizzling clouds, vertical structure induced by drizzle and 3-D radiative effects might operate together to cause dramatic differences between r (sub e),3.7 and r (sub e),2.1 retrievals.

Study of wind retrieval from space-borne infrared coherent lidar in cloudy atmosphere.

NASA Astrophysics Data System (ADS)

Baron, Philippe; Ishii, Shoken; Mizutani, Kohei; Okamoto, Kozo; Ochiai, Satoshi

2015-04-01

Future spaceborne tropospheric wind missions using infrared coherent lidar are currently being studied in Japan and in the United States [1,2]. The line-of-sight wind velocity is retrieved from the Doppler shift frequency of the signal returned by aerosol particles. However a large percentage (70-80%) of the measured single-shot intensity profiles are expected to be contaminated by clouds [3]. A large number of cloud contaminated profiles (>40%) will be characterized by a cloud-top signal intensity stronger than the aerosol signal by a factor of one order of magnitude, and by a strong attenuation of the signal backscattered from below the clouds. Profiles including more than one cloud layer are also expected. This work is a simulation study dealing with the impacts of clouds on wind retrieval. We focus on the three following points: 1) definition of an algorithm for optimizing the wind retrieval from the cloud-top signal, 2) assessment of the clouds impact on the measurement performance and, 3) definition of a method for averaging the measurements before the retrieval. The retrieval simulations are conducted considering the instrumental characteristics selected for the Japanese study: wavelength at 2 µm, PRF of 30 Hz, pulse power of 0.125 mJ and platform altitude between 200-400 km. Liquid and ice clouds are considered. The analysis uses data from atmospheric models and statistics of cloud effects derived from CALIPSO measurements such as in [3]. A special focus is put on the average method of the measurements before retrieval. Good retrievals in the mid-upper troposphere implie the average of measured single-range power spectra over large horizontal (100 km) and vertical (1 km) ranges. Large differences of signal intensities due to the presence of clouds and the clouds non-uniform distribution have to be taken into account when averaging the data to optimize the measurement performances. References: [1] S. Ishii, T. Iwasaki, M. Sato, R. Oki, K. Okamoto, T. Ishibashi, P. Baron, and T. Nishizawa: Future Doppler lidar wind measurement from space in Japan, Proc. of SPIE Vol. 8529, 2012 [2] D. Wu, J. Tang, Z. Liu, and Y. Hu: Simulation of coherent doppler wind lidar measurement from space based on CALIPSO lidar global aerosol observations. Journal of Quantitative Spectroscopy and Radiative Transfer, 122(0), 79-86, 2013 [3] G.D Emmitt: CFLOS and cloud statistics from satellite and their impact on future space-based Doppler Wind Lidar development. Symposium on Recent Developments in Atmospheric Applications of Radar and Lidar, 2008

On Cirrus Cloud Fields Measured by the Atmospheric Infrared Sounder

NASA Technical Reports Server (NTRS)

Kahn, Brian H.; Eldering, Annmarie; Liou, Kuo Nan

2006-01-01

A viewgraph presentation showing trends in clouds measured by the Atmospheric Infrared Sounder (AIRS) is given. The topics include: 1) Trends in clouds measured by AIRS: Are they reasonable? 2) Single and multilayered cloud trends; 3) Retrievals of thin cirrus D(sub e) and tau: Single-layered cloud only; 4) Relationships between ECF, D(sub e), tau, and T(sub CLD); and 5) MODIS vs. AIRS retrievals.

Retrievals of ice cloud microphysical properties of deep convective systems using radar measurements: Convective Cloud Microphysical Retrieval

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

Tian, Jingjing; Dong, Xiquan; Xi, Baike

This study presents new algorithms for retrieving ice cloud microphysical properties (ice water content (IWC) and median mass diameter (Dm)) for the stratiform and thick anvil regions of Deep Convective Systems (DCSs) using Next-Generation Radar (NEXRAD) reflectivity and recently developed empirical relationships from aircraft in situ measurements during the Midlatitude Continental Convective Clouds Experiment (MC3E). A classic DCS case on 20 May 2011 is used to compare the retrieved IWC profiles with other retrieval and cloud-resolving model simulations. The mean values of each retrieved and simulated IWC fall within one standard derivation of the other two. The statistical results frommore » six selected cases during MC3E show that the aircraft in situ derived IWC and Dm are 0.47 ± 0.29 g m-3 and 2.02 ± 1.3 mm, while the mean values of retrievals have a positive bias of 0.16 g m-3 (34%) and a negative bias of 0.39 mm (19%). To validate the newly developed retrieval algorithms from this study, IWC and Dm are performed with other DCS cases during Bow Echo and Mesoscale Convective Vortex Experiment (BAMEX) field campaign using composite gridded NEXRAD reflectivity and compared with in situ IWC and Dm from aircraft. A total of 64 1-min collocated aircraft and radar samples are available for comparisons, and the averages of radar retrieved and aircraft in situ measured IWCs are 1.22 g m-3 and 1.26 g m-3 with a correlation of 0.5, and their averaged Dm values are 2.15 and 1.80 mm. These comparisons have shown that the retrieval algorithms 45 developed during MC3E can retrieve similar ice cloud microphysical properties of DCS to aircraft in situ measurements during BAMEX with median errors of ~40% and ~25% for IWC and Dm retrievals, respectively. This is indicating our retrieval algorithms are suitable for other midlatitude continental DCS ice clouds, especially at stratiform rain and thick anvil regions. In addition, based on the averaged IWC and Dm values during MC3E and BAMEX, the DCS IWC values over midlatitude are significantly different, while their Dm values are close to each other. On the other hand, these DCS IWC and Dm values are 1-2 orders of magnitude larger than those of single-layered cirrus clouds over midlatitudes.« less

Cirrus cloud retrieval from MSG/SEVIRI during day and night using artificial neural networks

NASA Astrophysics Data System (ADS)

Strandgren, Johan; Bugliaro, Luca

2017-04-01

By covering a large part of the Earth, cirrus clouds play an important role in climate as they reflect incoming solar radiation and absorb outgoing thermal radiation. Nevertheless, the cirrus clouds remain one of the largest uncertainties in atmospheric research and the understanding of the physical processes that govern their life cycle is still poorly understood, as is their representation in climate models. To monitor and better understand the properties and physical processes of cirrus clouds, it's essential that those tenuous clouds can be observed from geostationary spaceborne imagers like SEVIRI (Spinning Enhanced Visible and InfraRed Imager), that possess a high temporal resolution together with a large field of view and play an important role besides in-situ observations for the investigation of cirrus cloud processes. CiPS (Cirrus Properties from Seviri) is a new algorithm targeting thin cirrus clouds. CiPS is an artificial neural network trained with coincident SEVIRI and CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) observations in order to retrieve a cirrus cloud mask along with the cloud top height (CTH), ice optical thickness (IOT) and ice water path (IWP) from SEVIRI. By utilizing only the thermal/IR channels of SEVIRI, CiPS can be used during day and night making it a powerful tool for the cirrus life cycle analysis. Despite the great challenge of detecting thin cirrus clouds and retrieving their properties from a geostationary imager using only the thermal/IR wavelengths, CiPS performs well. Among the cirrus clouds detected by CALIOP, CiPS detects 70 and 95 % of the clouds with an optical thickness of 0.1 and 1.0 respectively. Among the cirrus free pixels, CiPS classify 96 % correctly. For the CTH retrieval, CiPS has a mean absolute percentage error of 10 % or less with respect to CALIOP for cirrus clouds with a CTH greater than 8 km. For the IOT retrieval, CiPS has a mean absolute percentage error of 100 % or less with respect to CALIOP for cirrus clouds with an optical thickness down to 0.07. For such thin cirrus clouds an error of 100 % should be regarded as low from a geostationary imager like SEVIRI. The IWP retrieved by CiPS shows a similar performance, but has larger deviations for the thinner cirrus clouds.

The ESA Cloud CCI project: Generation of Multi Sensor consistent Cloud Properties with an Optimal Estimation Based Retrieval Algorithm

NASA Astrophysics Data System (ADS)

Jerg, M.; Stengel, M.; Hollmann, R.; Poulsen, C.

2012-04-01

The ultimate objective of the ESA Climate Change Initiative (CCI) Cloud project is to provide long-term coherent cloud property data sets exploiting and improving on the synergetic capabilities of past, existing, and upcoming European and American satellite missions. The synergetic approach allows not only for improved accuracy and extended temporal and spatial sampling of retrieved cloud properties better than those provided by single instruments alone but potentially also for improved (inter-)calibration and enhanced homogeneity and stability of the derived time series. Such advances are required by the scientific community to facilitate further progress in satellite-based climate monitoring, which leads to a better understanding of climate. Some of the primary objectives of ESA Cloud CCI Cloud are (1) the development of inter-calibrated radiance data sets, so called Fundamental Climate Data Records - for ESA and non ESA instruments through an international collaboration, (2) the development of an optimal estimation based retrieval framework for cloud related essential climate variables like cloud cover, cloud top height and temperature, liquid and ice water path, and (3) the development of two multi-annual global data sets for the mentioned cloud properties including uncertainty estimates. These two data sets are characterized by different combinations of satellite systems: the AVHRR heritage product comprising (A)ATSR, AVHRR and MODIS and the novel (A)ATSR - MERIS product which is based on a synergetic retrieval using both instruments. Both datasets cover the years 2007-2009 in the first project phase. ESA Cloud CCI will also carry out a comprehensive validation of the cloud property products and provide a common data base as in the framework of the Global Energy and Water Cycle Experiment (GEWEX). The presentation will give an overview of the ESA Cloud CCI project and its goals and approaches and then continue with results from the Round Robin algorithm comparison exercise carried out at the beginning of the project which included three algorithms. The purpose of the exercise was to assess and compare existing cloud retrieval algorithms in order to chose one of them as backbone of the retrieval system and also identify areas of potential improvement and general strengths and weaknesses of the algorithm. Furthermore the presentation will elaborate on the optimal estimation algorithm subsequently chosen to derive the heritage product and which is presently further developed and will be employed for the AVHRR heritage product. The algorithm's capabilities to coherently and simultaneously process all radiative input and yield retrieval parameters together with associated uncertainty estimates will be presented together with first results for the heritage product. In the course of the project the algorithm is being developed into a freely and publicly available community retrieval system for interested scientists.

What does Reflection from Cloud Sides tell us about Vertical Distribution of Cloud Droplet Sizes?

NASA Technical Reports Server (NTRS)

Marshak, A.; Martins, J. V.; Zubko, V.; Kaufman, Y. J.

2006-01-01

Cloud development, the onset of precipitation and the effect of aerosol on clouds depend on the structure of the cloud profiles of droplet size and phase. Aircraft measurements of cloud profiles are limited in their temporal and spatial extent. Satellites were used to observe cloud tops not cloud profiles with vertical profiles of precipitation-sized droplets anticipated from CloudSat. The recently proposed CLAIM-3D satellite mission (cloud aerosol interaction mission in 3-D) suggests to measure profiles of cloud microphysical properties by retrieving them from the solar and infrared radiation reflected or emitted from cloud sides. Inversion of measurements from the cloud sides requires rigorous understanding of the 3-dimentional(3-D) properties of clouds. Here we discuss the reflected sunlight from the cloud sides and top at two wavelengths: one nonabsorbing to solar radiation (0.67 microns) and one with liquid water efficient absorption of solar radiation (2.1 microns). In contrast to the plane-parallel approximation, a conventional approach to all current operational retrievals, 3-D radiative transfer is used for interpreting the observed reflectances. General properties of the radiation reflected from the sides of an isolated cloud are discussed. As a proof of concept, the paper shows a few examples of radiation reflected from cloud fields generated by a simple stochastic cloud model with the prescribed vertically resolved microphysics. To retrieve the information about droplet sizes, we propose to use the probability density function of the droplet size distribution and its first two moments instead of the assumption about fixed values of the droplet effective radius. The retrieval algorithm is based on the Bayesian theorem that combines prior information about cloud structure and microphysics with radiative transfer calculations.

Reducing Errors in Satellite Simulated Views of Clouds with an Improved Parameterization of Unresolved Scales

NASA Astrophysics Data System (ADS)

Hillman, B. R.; Marchand, R.; Ackerman, T. P.

2016-12-01

Satellite instrument simulators have emerged as a means to reduce errors in model evaluation by producing simulated or psuedo-retrievals from model fields, which account for limitations in the satellite retrieval process. Because of the mismatch in resolved scales between satellite retrievals and large-scale models, model cloud fields must first be downscaled to scales consistent with satellite retrievals. This downscaling is analogous to that required for model radiative transfer calculations. The assumption is often made in both model radiative transfer codes and satellite simulators that the unresolved clouds follow maximum-random overlap with horizontally homogeneous cloud condensate amounts. We examine errors in simulated MISR and CloudSat retrievals that arise due to these assumptions by applying the MISR and CloudSat simulators to cloud resolving model (CRM) output generated by the Super-parameterized Community Atmosphere Model (SP-CAM). Errors are quantified by comparing simulated retrievals performed directly on the CRM fields with those simulated by first averaging the CRM fields to approximately 2-degree resolution, applying a "subcolumn generator" to regenerate psuedo-resolved cloud and precipitation condensate fields, and then applying the MISR and CloudSat simulators on the regenerated condensate fields. We show that errors due to both assumptions of maximum-random overlap and homogeneous condensate are significant (relative to uncertainties in the observations and other simulator limitations). The treatment of precipitation is particularly problematic for CloudSat-simulated radar reflectivity. We introduce an improved subcolumn generator for use with the simulators, and show that these errors can be greatly reduced by replacing the maximum-random overlap assumption with the more realistic generalized overlap and incorporating a simple parameterization of subgrid-scale cloud and precipitation condensate heterogeneity. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000. SAND NO. SAND2016-7485 A

APOLLO_NG - a probabilistic interpretation of the APOLLO legacy for AVHRR heritage channels

NASA Astrophysics Data System (ADS)

Klüser, L.; Killius, N.; Gesell, G.

2015-10-01

The cloud processing scheme APOLLO (AVHRR Processing scheme Over cLouds, Land and Ocean) has been in use for cloud detection and cloud property retrieval since the late 1980s. The physics of the APOLLO scheme still build the backbone of a range of cloud detection algorithms for AVHRR (Advanced Very High Resolution Radiometer) heritage instruments. The APOLLO_NG (APOLLO_NextGeneration) cloud processing scheme is a probabilistic interpretation of the original APOLLO method. It builds upon the physical principles that have served well in the original APOLLO scheme. Nevertheless, a couple of additional variables have been introduced in APOLLO_NG. Cloud detection is no longer performed as a binary yes/no decision based on these physical principles. It is rather expressed as cloud probability for each satellite pixel. Consequently, the outcome of the algorithm can be tuned from being sure to reliably identify clear pixels to conditions of reliably identifying definitely cloudy pixels, depending on the purpose. The probabilistic approach allows retrieving not only the cloud properties (optical depth, effective radius, cloud top temperature and cloud water path) but also their uncertainties. APOLLO_NG is designed as a standalone cloud retrieval method robust enough for operational near-realtime use and for application to large amounts of historical satellite data. The radiative transfer solution is approximated by the same two-stream approach which also had been used for the original APOLLO. This allows the algorithm to be applied to a wide range of sensors without the necessity of sensor-specific tuning. Moreover it allows for online calculation of the radiative transfer (i.e., within the retrieval algorithm) giving rise to a detailed probabilistic treatment of cloud variables. This study presents the algorithm for cloud detection and cloud property retrieval together with the physical principles from the APOLLO legacy it is based on. Furthermore a couple of example results from NOAA-18 are presented.

Retrieval of ice cloud properties using an optimal estimation algorithm and MODIS infrared observations: 1. Forward model, error analysis, and information content

NASA Astrophysics Data System (ADS)

Wang, Chenxi; Platnick, Steven; Zhang, Zhibo; Meyer, Kerry; Yang, Ping

2016-05-01

An optimal estimation (OE) retrieval method is developed to infer three ice cloud properties simultaneously: optical thickness (τ), effective radius (reff), and cloud top height (h). This method is based on a fast radiative transfer (RT) model and infrared (IR) observations from the MODerate resolution Imaging Spectroradiometer (MODIS). This study conducts thorough error and information content analyses to understand the error propagation and performance of retrievals from various MODIS band combinations under different cloud/atmosphere states. Specifically, the algorithm takes into account four error sources: measurement uncertainty, fast RT model uncertainty, uncertainties in ancillary data sets (e.g., atmospheric state), and assumed ice crystal habit uncertainties. It is found that the ancillary and ice crystal habit error sources dominate the MODIS IR retrieval uncertainty and cannot be ignored. The information content analysis shows that for a given ice cloud, the use of four MODIS IR observations is sufficient to retrieve the three cloud properties. However, the selection of MODIS IR bands that provide the most information and their order of importance varies with both the ice cloud properties and the ambient atmospheric and the surface states. As a result, this study suggests the inclusion of all MODIS IR bands in practice since little a priori information is available.

Retrieval of ice cloud properties using an optimal estimation algorithm and MODIS infrared observations. Part I: Forward model, error analysis, and information content.

PubMed

Wang, Chenxi; Platnick, Steven; Zhang, Zhibo; Meyer, Kerry; Yang, Ping

2016-05-27

An optimal estimation (OE) retrieval method is developed to infer three ice cloud properties simultaneously: optical thickness ( τ ), effective radius ( r eff ), and cloud-top height ( h ). This method is based on a fast radiative transfer (RT) model and infrared (IR) observations from the MODerate resolution Imaging Spectroradiometer (MODIS). This study conducts thorough error and information content analyses to understand the error propagation and performance of retrievals from various MODIS band combinations under different cloud/atmosphere states. Specifically, the algorithm takes into account four error sources: measurement uncertainty, fast RT model uncertainty, uncertainties in ancillary datasets (e.g., atmospheric state), and assumed ice crystal habit uncertainties. It is found that the ancillary and ice crystal habit error sources dominate the MODIS IR retrieval uncertainty and cannot be ignored. The information content analysis shows that, for a given ice cloud, the use of four MODIS IR observations is sufficient to retrieve the three cloud properties. However, the selection of MODIS IR bands that provide the most information and their order of importance varies with both the ice cloud properties and the ambient atmospheric and the surface states. As a result, this study suggests the inclusion of all MODIS IR bands in practice since little a priori information is available.

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

NASA Astrophysics Data System (ADS)

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

2017-08-01

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

An approach for retrieval of atmospheric trace gases CO II, CH 4 and CO from the future Canadian micro earth observation satellite (MEOS)

NASA Astrophysics Data System (ADS)

Trishchenko, Alexander P.; Khlopenkov, Konstantin V.; Wang, Shusen; Luo, Yi; Kruzelecky, Roman V.; Jamroz, Wes; Kroupnik, Guennadi

2007-10-01

Among all trace gases, the carbon dioxide and methane provide the largest contribution to the climate radiative forcing and together with carbon monoxide also to the global atmospheric carbon budget. New Micro Earth Observation Satellite (MEOS) mission is proposed to obtain information about these gases along with some other mission's objectives related to studying cloud and aerosol interactions. The miniature suit of instruments is proposed to make measurements with reduced spectral resolution (1.2nm) over wide NIR range 0.9μm to 2.45μm and with high spectral resolution (0.03nm) for three selected regions: oxygen A-band, 1.5μm-1.7μm band and 2.2μm-2.4μm band. It is also planned to supplement the spectrometer measurements with high spatial resolution imager for detailed characterization of cloud and surface albedo distribution within spectrometer field of view. The approaches for cloud/clear-sky identification and column retrievals of above trace gases are based on differential absorption technique and employ the combination of coarse and high-resolution spectral data. The combination of high and coarse resolution spectral data is beneficial for better characterization of surface spectral albedo and aerosol effects. An additional capability for retrieval of the vertical distribution amounts is obtained from the combination of nadir and limb measurements. Oxygen A-band path length will be used for normalization of trace gas retrievals.

Current Status of Aerosol Retrievals from TOMS

NASA Technical Reports Server (NTRS)

Torres, O.; Herman, J. R.; Bhartia, P. K.; Ginoux, P.

1999-01-01

Properties of atmospheric aerosols over all land and water surfaces are retrieved from TOMS measurements of backscattered radiances. The TOMS technique, uses observations at two wavelengths. In the near ultraviolet (330-380 nm) range, where the effects of gaseous absorption are negligible. The retrieved properties are optical depth and a measure of aerosol absorptivity, generally expressed as single scattering albedo. The main sources of error of the TOMS aerosol products are sub-pixel cloud contamination and uncertainty on the height above the surface of UV-absorbing aerosol layers. The first error source is related to the large footprint (50 x 50 km at nadir) of the sensor, and the lack of detection capability of sub-pixel size clouds. The uncertainty associated with the height of the absorbing aerosol layers, on the other hand, is related to the pressure dependence of the molecular scattering process, which is the basis of the near-UV method of absorbing aerosol detection. The detection of non-absorbing aerosols is not sensitive to aerosol layer height. We will report on the ongoing work to overcome both of these difficulties. Coincident measurements of high spatial resolution thermal infrared radiances are used to address the cloud contamination issue. Mostly clear scenes for aerosol retrieval are selected by examining the spatial homogeneity of the IR radiance measurements within a TOMS pixel. The approach to reduce the uncertainty associated with the height of the aerosol layer by making use of a chemical transport model will also be discussed.

Multi-Spectral Stereo Atmospheric Remote Sensing (STARS) for Retrieval of Cloud Properties and Cloud-Motion Vectors

NASA Astrophysics Data System (ADS)

Kelly, M. A.; Boldt, J.; Wilson, J. P.; Yee, J. H.; Stoffler, R.

2017-12-01

The multi-spectral STereo Atmospheric Remote Sensing (STARS) concept has the objective to provide high-spatial and -temporal-resolution observations of 3D cloud structures related to hurricane development and other severe weather events. The rapid evolution of severe weather demonstrates a critical need for mesoscale observations of severe weather dynamics, but such observations are rare, particularly over the ocean where extratropical and tropical cyclones can undergo explosive development. Coincident space-based measurements of wind velocity and cloud properties at the mesoscale remain a great challenge, but are critically needed to improve the understanding and prediction of severe weather and cyclogenesis. STARS employs a mature stereoscopic imaging technique on two satellites (e.g. two CubeSats, two hosted payloads) to simultaneously retrieve cloud motion vectors (CMVs), cloud-top temperatures (CTTs), and cloud geometric heights (CGHs) from multi-angle, multi-spectral observations of cloud features. STARS is a pushbroom system based on separate wide-field-of-view co-boresighted multi-spectral cameras in the visible, midwave infrared (MWIR), and longwave infrared (LWIR) with high spatial resolution (better than 1 km). The visible system is based on a pan-chromatic, low-light imager to resolve cloud structures under nighttime illumination down to ¼ moon. The MWIR instrument, which is being developed as a NASA ESTO Instrument Incubator Program (IIP) project, is based on recent advances in MWIR detector technology that requires only modest cooling. The STARS payload provides flexible options for spaceflight due to its low size, weight, power (SWaP) and very modest cooling requirements. STARS also meets AF operational requirements for cloud characterization and theater weather imagery. In this paper, an overview of the STARS concept, including the high-level sensor design, the concept of operations, and measurement capability will be presented.

Measurement of Atmospheric CO2 Column Concentrations to Cloud Tops With a Pulsed Multi-Wavelength Airborne Lidar

NASA Technical Reports Server (NTRS)

Mao, Jianping; Ramanathan, Anand; Abshire, James B.; Kawa, Stephan R.; Riris, Haris; Allan, Graham R.; Rodriguez, Michael R.; Hasselbrack, William E.; Sun, Xiaoli; Numata, Kenji;

Measurement of atmospheric CO2 column concentrations to cloud tops with a pulsed multi-wavelength airborne lidar

NASA Astrophysics Data System (ADS)

Mao, Jianping; Ramanathan, Anand; Abshire, James B.; Kawa, Stephan R.; Riris, Haris; Allan, Graham R.; Rodriguez, Michael; Hasselbrack, William E.; Sun, Xiaoli; Numata, Kenji; Chen, Jeff; Choi, Yonghoon; Yang, Mei Ying Melissa

2018-01-01

We have measured the column-averaged atmospheric CO2 mixing ratio to a variety of cloud tops by using an airborne pulsed multi-wavelength integrated-path differential absorption (IPDA) lidar. Airborne measurements were made at altitudes up to 13 km during the 2011, 2013 and 2014 NASA Active Sensing of CO2 Emissions over Nights, Days, and Seasons (ASCENDS) science campaigns flown in the United States West and Midwest and were compared to those from an in situ sensor. Analysis of the lidar backscatter profiles shows the average cloud top reflectance was ˜ 5 % for the CO2 measurement at 1572.335 nm except to cirrus clouds, which had lower reflectance. The energies for 1 µs wide laser pulses reflected from cloud tops were sufficient to allow clear identification of CO2 absorption line shape and then to allow retrievals of atmospheric column CO2 from the aircraft to cloud tops more than 90 % of the time. Retrievals from the CO2 measurements to cloud tops had minimal bias but larger standard deviations when compared to those made to the ground, depending on cloud top roughness and reflectance. The measurements show this new capability helps resolve CO2 horizontal and vertical gradients in the atmosphere. When used with nearby full-column measurements to ground, the CO2 measurements to cloud tops can be used to estimate the partial-column CO2 concentration below clouds, which should lead to better estimates of surface carbon sources and sinks. This additional capability of the range-resolved CO2 IPDA lidar technique provides a new benefit for studying the carbon cycle in future airborne and space-based CO2 missions.

Probabilistic verification of cloud fraction from three different products with CALIPSO

NASA Astrophysics Data System (ADS)

Jung, B. J.; Descombes, G.; Snyder, C.

2017-12-01

In this study, we present how Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) can be used for probabilistic verification of cloud fraction, and apply this probabilistic approach to three cloud fraction products: a) The Air Force Weather (AFW) World Wide Merged Cloud Analysis (WWMCA), b) Satellite Cloud Observations and Radiative Property retrieval Systems (SatCORPS) from NASA Langley Research Center, and c) Multi-sensor Advection Diffusion nowCast (MADCast) from NCAR. Although they differ in their details, both WWMCA and SatCORPS retrieve cloud fraction from satellite observations, mainly of infrared radiances. MADCast utilizes in addition a short-range forecast of cloud fraction (provided by the Model for Prediction Across Scales, assuming cloud fraction is advected as a tracer) and a column-by-column particle filter implemented within the Gridpoint Statistical Interpolation (GSI) data-assimilation system. The probabilistic verification considers the retrieved or analyzed cloud fractions as predicting the probability of cloud at any location within a grid cell and the 5-km vertical feature mask (VFM) from CALIPSO level-2 products as a point observation of cloud.

Use of the ARM Measurement of Spectral Zenith Radiance For Better Understanding Of 3D Cloud-Radiation Processes and Aerosol-Cloud Interaction

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

Chiu, Jui-Yuan

2010-10-19

Our proposal focuses on cloud-radiation processes in a general 3D cloud situation, with particular emphasis on cloud optical depth and effective particle size. We also focus on zenith radiance measurements, both active and passive. The proposal has three main parts. Part One exploits the "solar-background" mode of ARM lidars to allow them to retrieve cloud optical depth not just for thin clouds but for all clouds. This also enables the study of aerosol cloud interactions with a single instrument. Part Two exploits the large number of new wavelengths offered by ARM's zenith-pointing ShortWave Spectrometer (SWS), especially during CLASIC, to developmore » better retrievals not only of cloud optical depth but also of cloud particle size. We also propose to take advantage of the SWS's 1 Hz sampling to study the "twilight zone" around clouds where strong aerosol-cloud interactions are taking place. Part Three involves continuing our cloud optical depth and cloud fraction retrieval research with ARM's 2NFOV instrument by, first, analyzing its data from the AMF-COPS/CLOWD deployment, and second, making our algorithms part of ARM's operational data processing.« less

Simulations of Infrared Radiances Over a Deep Convective Cloud System Observed During TC4: Potential for Enhancing Nocturnal Ice Cloud Retrievals

NASA Technical Reports Server (NTRS)

Minnis, Patrick; Hong, Gang; Ayers, Kirk; Smith, William L., Jr.; Yost, Christopher R.; Heymsfield, Andrew J.; Heymsfield, Gerald M.; Hlavka, Dennis L.; King, Michael D.; Korn, Errol;

Simulations of Infrared Radiances Over a Deep Convective Cloud System Observed During TC4- Potential for Enhancing Nocturnal Ice Cloud Retrievals

NASA Technical Reports Server (NTRS)

Minnis, Patrick; Hong, Gang; Ayers, Jeffrey Kirk; Smith, William L.; Yost, Christopher R.; Heymsfield, Andrew J.; Heymsfield, Gerald M.; Hlavka, Dennis L.; King, Michael D.; Korn, Errol M.;

What Does Reflection from Cloud Sides Tell Us About Vertical Distribution of Cloud Droplet Sizes?

NASA Technical Reports Server (NTRS)

Marshak, Alexander; Martins, J. Vanderlei; Zubko, Victor; Kaufman, Yoram, J.

2005-01-01

Cloud development, the onset of precipitation and the effect of aerosol on clouds depend on the structure of the cloud profiles of droplet size and phase. Aircraft measurements of cloud profiles are limited in their temporal and spatial extent. Satellites were used to observe cloud tops not cloud profiles with vertical profiles of precipitation-sized droplets anticipated from Cloudsat. The recently proposed CLAIM-3D satellite mission (cloud aerosol interaction mission in 3D) suggests to measure profiles of cloud microphysical properties by retrieving them from the solar and infrared radiation reflected or emitted from cloud sides. Inversion of measurements from the cloud sides requires rigorous understanding of the 3-dimensional (3D) properties of clouds. Here we discuss the reflected sunlight from the cloud sides and top at two wavelengths: one nonabsorbing to solar radiation (0.67 micrometers) and one with liquid water efficient absorption of solar radiation (2.1 micrometers). In contrast to the plane-parallel approximation, a conventional approach to all current operational retrievals, 3D radiative transfer is used for interpreting the observed reflectances. General properties of the radiation reflected from the sides of an isolated cloud are discussed. As a proof of concept, the paper shows a few examples of radiation reflected from cloud fields generated by a simple stochastic cloud model with the prescribed vertically resolved microphysics. To retrieve the information about droplet sizes, we propose to use the probability density function of the droplet size distribution and its first two moments instead of the assumption about fixed values of the droplet effective radius. The retrieval algorithm is based on the Bayesian theorem that combines prior information about cloud structure and microphysics with radiative transfer calculations.

XBAER-derived aerosol optical thickness from OLCI/Sentinel-3 observation

NASA Astrophysics Data System (ADS)

Mei, Linlu; Rozanov, Vladimir; Vountas, Marco; Burrows, John P.; Richter, Andreas

2018-02-01

A cloud identification algorithm used for cloud masking, which is based on the spatial variability of reflectances at the top of the atmosphere in visible wavelengths, has been developed for the retrieval of aerosol properties by MODIS. It is shown that the spatial pattern of cloud reflectance, as observed from space, is very different from that of aerosols. Clouds show a high spatial variability in the scale of a hundred metres to a few kilometres, whereas aerosols in general are homogeneous. The concept of spatial variability of reflectances at the top of the atmosphere is mainly applicable over the ocean, where the surface background is sufficiently homogeneous for the separation between aerosols and clouds. Aerosol retrievals require a sufficiently accurate cloud identification to be able to mask these ground scenes. However, a conservative mask will exclude strong aerosol episodes and a less conservative mask could introduce cloud contamination that biases the retrieved aerosol optical properties (e.g. aerosol optical depth and effective radii). A detailed study on the effect of cloud contamination on aerosol retrievals has been performed and parameters are established determining the threshold value for the MODIS aerosol cloud mask (3×3-STD) over the ocean. The 3×3-STD algorithm discussed in this paper is the operational cloud mask used for MODIS aerosol retrievals over the ocean.A prolonged pollution haze event occurred in the northeast part of China during the period 16-21 December 2016. To assess the impact of such events, the amounts and distribution of aerosol particles, formed in such events, need to be quantified. The newly launched Ocean Land Colour Instrument (OLCI) onboard Sentinel-3 is the successor of the MEdium Resolution Imaging Spectrometer (MERIS). It provides measurements of the radiance and reflectance at the top of the atmosphere, which can be used to retrieve the aerosol optical thickness (AOT) from synoptic to global scales. In this study, the recently developed AOT retrieval algorithm eXtensible Bremen AErosol Retrieval (XBAER) has been applied to data from the OLCI instrument for the first time to illustrate the feasibility of applying XBAER to the data from this new instrument. The first global retrieval results show similar patterns of aerosol optical thickness, AOT, to those from MODIS and MISR aerosol products. The AOT retrieved from OLCI is validated by comparison with AERONET observations and a correlation coefficient of 0.819 and bias (root mean square) of 0.115 is obtained. The haze episode is well captured by the OLCI-derived AOT product. XBAER is shown to retrieve AOT well from the observations of MERIS and OLCI.

Partitioning CloudSat Ice Water Content for Comparison with Upper-Tropospheric Ice in Global Atmospheric Models

NASA Astrophysics Data System (ADS)

Chen, W. A.; Woods, C. P.; Li, J. F.; Waliser, D. E.; Chern, J.; Tao, W.; Jiang, J. H.; Tompkins, A. M.

2010-12-01

CloudSat provides important estimates of vertically resolved ice water content (IWC) on a global scale based on radar reflectivity. These estimates of IWC have proven beneficial in evaluating the representations of ice clouds in global models. An issue when performing model-data comparisons of IWC particularly germane to this investigation, is the question of which component(s) of the frozen water mass are represented by retrieval estimates and how they relate to what is represented in models. The present study developed and applied a new technique to partition CloudSat total IWC into small and large ice hydrometeors, based on the CloudSat-retrieved ice particle size distribution (PSD) parameters. The new method allows one to make relevant model-data comparisons and provides new insights into the model’s representation of atmospheric IWC. The partitioned CloudSat IWC suggests that the small ice particles contribute to 20-30% of the total IWC in the upper troposphere when a threshold size of 100 μm is used. Sensitivity measures with respect to the threshold size, the PSD parameters, and the retrieval algorithms are presented. The new dataset is compared to model estimates, pointing to areas for model improvement. Cloud ice analyses from the European Centre for Medium-Range Weather Forecasts model agree well with the small IWC from CloudSat. The finite-volume multi-scale modeling framework model underestimates total IWC at 147 and 215 hPa, while overestimating the fractional contribution from the small ice species. These results are discussed in terms of their applications to, and implications for, the evaluation of global atmospheric models, providing constraints on the representations of cloud feedback and precipitation in global models, which in turn can help reduce uncertainties associated with climate change projections. Figure 1. A sample lognormal ice number distribution (red curve), and the corresponding mass distribution (black curve). The dotted line represents the cutoff size for IWC partitioning (Dc = 100 µm as an example). The partial integrals of the mass distribution for particles smaller and larger than Dc correspond to IWC<100 (green area) and IWC>100 (blue area), respectively.

Combining In-situ Measurements, Passive Satellite Imagery, and Active Radar Retrievals for the Detection of High Ice Water Content

NASA Astrophysics Data System (ADS)

Yost, C. R.; Minnis, P.; Bedka, K. M.; Nguyen, L.; Palikonda, R.; Spangenberg, D.; Strapp, J. W.; Delanoë, J.; Protat, A.

2016-12-01

At least one hundred jet engine power loss events since the 1990s have been attributed to the phenomenon known as ice crystal icing (ICI). Ingestion of high concentrations of ice particles into aircraft engines is thought to cause these events, but it is clear that the use of current on-board weather radar systems alone is insufficient for detecting conditions that might cause ICI. Passive radiometers in geostationary orbit are valuable for monitoring systems that produce high ice water content (HIWC) and will play an important role in nowcasting, but are incapable of making vertically resolved measurements of ice particle concentration, i.e., ice water content (IWC). Combined radar, lidar, and in-situ measurements are essential for developing a skilled satellite-based HIWC nowcasting technique. The High Altitude Ice Crystals - High Ice Water Content (HAIC-HIWC) field campaigns in Darwin, Australia, and Cayenne, French Guiana, have produced a valuable dataset of in-situ total water content (TWC) measurements with which to study conditions that produce HIWC. The NASA Langley Satellite ClOud and Radiative Property retrieval System (SatCORPS) was used to derive cloud physical and optical properties such cloud top height, temperature, optical depth, and ice water path from multi-spectral satellite imagery acquired throughout the HAIC-HIWC campaigns. These cloud properties were collocated with the in-situ TWC measurements in order to characterize cloud properties in the vicinity of HIWC. Additionally, a database of satellite-derived overshooting cloud top (OT) detections was used to identify TWC measurements in close proximity to convective cores likely producing large concentrations of ice crystals. Certain cloud properties show some sensitivity to increasing TWC and a multivariate probabilistic indicator of HIWC was developed from these datasets. This paper describes the algorithm development and demonstrates the HIWC indicator with imagery from the HAIC-HIWC campaigns. Vertically resolved IWC retrievals from active sensors such as the Cloud Profiling Radar (CPR) on CloudSat and the Doppler Radar System Airborne (RASTA) provide IWC profiles with which to validate and potentially enhance the satellite-based HIWC indicator.

Modeling of Convective-Stratiform Precipitation Processes: Sensitivity to Partitioning Methods

NASA Technical Reports Server (NTRS)

Lang, S. E.; Tao, W.-K.; Simpson, J.; Ferrier, B.; Starr, David OC. (Technical Monitor)

2001-01-01

Six different convective-stratiform separation techniques, including a new technique that utilizes the ratio of vertical and terminal velocities, are compared and evaluated using two-dimensional numerical simulations of a tropical [Tropical Ocean Global Atmosphere Coupled Ocean Atmosphere Response Experiment (TOGA COARE)] and midlatitude continental [Preliminary Regional Experiment for STORM-Central (PRESTORM)] squall line. Comparisons are made in terms of rainfall, cloud coverage, mass fluxes, apparent heating and moistening, mean hydrometeor profiles, CFADs (Contoured Frequency with Altitude Diagrams), microphysics, and latent heating retrieval. Overall, it was found that the different separation techniques produced results that qualitatively agreed. However, the quantitative differences were significant. Observational comparisons were unable to conclusively evaluate the performance of the techniques. Latent heating retrieval was shown to be sensitive to the use of separation technique mainly due to the stratiform region for methods that found very little stratiform rain.

Image-Based Airborne LiDAR Point Cloud Encoding for 3d Building Model Retrieval

NASA Astrophysics Data System (ADS)

Chen, Yi-Chen; Lin, Chao-Hung

2016-06-01

With the development of Web 2.0 and cyber city modeling, an increasing number of 3D models have been available on web-based model-sharing platforms with many applications such as navigation, urban planning, and virtual reality. Based on the concept of data reuse, a 3D model retrieval system is proposed to retrieve building models similar to a user-specified query. The basic idea behind this system is to reuse these existing 3D building models instead of reconstruction from point clouds. To efficiently retrieve models, the models in databases are compactly encoded by using a shape descriptor generally. However, most of the geometric descriptors in related works are applied to polygonal models. In this study, the input query of the model retrieval system is a point cloud acquired by Light Detection and Ranging (LiDAR) systems because of the efficient scene scanning and spatial information collection. Using Point clouds with sparse, noisy, and incomplete sampling as input queries is more difficult than that by using 3D models. Because that the building roof is more informative than other parts in the airborne LiDAR point cloud, an image-based approach is proposed to encode both point clouds from input queries and 3D models in databases. The main goal of data encoding is that the models in the database and input point clouds can be consistently encoded. Firstly, top-view depth images of buildings are generated to represent the geometry surface of a building roof. Secondly, geometric features are extracted from depth images based on height, edge and plane of building. Finally, descriptors can be extracted by spatial histograms and used in 3D model retrieval system. For data retrieval, the models are retrieved by matching the encoding coefficients of point clouds and building models. In experiments, a database including about 900,000 3D models collected from the Internet is used for evaluation of data retrieval. The results of the proposed method show a clear superiority over related methods.

Retrieval of ice cloud properties from Himawari-8 satellite measurements by Voronoi ice particle model

NASA Astrophysics Data System (ADS)

Letu, H.; Nagao, T. M.; Nakajima, T. Y.; Ishimoto, H.; Riedi, J.; Shang, H.

2017-12-01

Ice cloud property product from satellite measurements is applicable in climate change study, numerical weather prediction, as well as atmospheric study. Ishimoto et al., (2010) and Letu et al., (2016) developed a single scattering property of the highly irregular ice particle model, called the Voronoi model for developing ice cloud product of the GCOM-C satellite program. It is investigated that Voronoi model has a good performance on retrieval of the ice cloud properties by comparing it with other well-known scattering models. Cloud property algorithm (Nakajima et al., 1995, Ishida and Nakajima., 2009, Ishimoto et al., 2009, Letu et al., 2012, 2014, 2016) of the GCOM-C satellite program is improved to produce the Himawari-8/AHI cloud products based on the variation of the solar zenith angle. Himawari-8 is the new-generational geostationary meteorological satellite, which is successfully launched by the Japan Meteorological Agency (JMA) on 7 October 2014. In this study, ice cloud optical and microphysical properties are simulated from RSTAR radiative transfer code by using various model. Scattering property of the Voronoi model is investigated for developing the AHI ice cloud products. Furthermore, optical and microphysical properties of the ice clouds are retrieved from Himawari-8/AHI satellite measurements. Finally, retrieval results from Himawari-8/AHI are compared to MODIS-C6 cloud property products for validation of the AHI cloud products.

The Community Cloud retrieval for CLimate (CC4CL) - Part 1: A framework applied to multiple satellite imaging sensors

NASA Astrophysics Data System (ADS)

Sus, Oliver; Stengel, Martin; Stapelberg, Stefan; McGarragh, Gregory; Poulsen, Caroline; Povey, Adam C.; Schlundt, Cornelia; Thomas, Gareth; Christensen, Matthew; Proud, Simon; Jerg, Matthias; Grainger, Roy; Hollmann, Rainer

2018-06-01

We present here the key features of the Community Cloud retrieval for CLimate (CC4CL) processing algorithm. We focus on the novel features of the framework: the optimal estimation approach in general, explicit uncertainty quantification through rigorous propagation of all known error sources into the final product, and the consistency of our long-term, multi-platform time series provided at various resolutions, from 0.5 to 0.02°. By describing all key input data and processing steps, we aim to inform the user about important features of this new retrieval framework and its potential applicability to climate studies. We provide an overview of the retrieved and derived output variables. These are analysed for four, partly very challenging, scenes collocated with CALIOP (Cloud-Aerosol lidar with Orthogonal Polarization) observations in the high latitudes and over the Gulf of Guinea-West Africa. The results show that CC4CL provides very realistic estimates of cloud top height and cover for optically thick clouds but, where optically thin clouds overlap, returns a height between the two layers. CC4CL is a unique, coherent, multi-instrument cloud property retrieval framework applicable to passive sensor data of several EO missions. Through its flexibility, CC4CL offers the opportunity for combining a variety of historic and current EO missions into one dataset, which, compared to single sensor retrievals, is improved in terms of accuracy and temporal sampling.

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

NASA Astrophysics Data System (ADS)

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

2016-07-01

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

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

NASA Technical Reports Server (NTRS)

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

2016-01-01

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

Atmospheric particles retrieval using satellite remote sensing: Applications for sandstorms and volcanic clouds

NASA Astrophysics Data System (ADS)

Gu, Yingxin

This thesis is concerned with atmospheric particles produced by sandstorms and volcanic eruptions. Three studies were conducted in order to examine particle retrieval methodology, and apply these towards an improved understanding of large-scale sandstorms. A thermal infrared remote sensing retrieval method developed by Wen and Rose [1994], which retrieves particle sizes, optical depth, and total masses of silicate particles in the volcanic cloud, was applied to an April 07, 2001 sandstorm over northern China, using MODIS. Results indicate that the area of the dust cloud observed was 1.34 million km2, the mean particle radius of the dust was 1.44 mum, and the mean optical depth at 11 mum was 0.79. The mean burden of dust was approximately 4.8 tons/km2 and the main portion of the dust storm on April 07, 2001 contained 6.5 million tons of dust. The results are supported by both independent remote sensing data (TOMS) and in-situ data for a similar event in 1998, therefore suggesting that the technique is appropriate for quantitative analysis of silicate dust clouds. This is the first quantitative evaluation of annual and seasonal dust loading in 2003 produced by Saharan dust storms by satellite remote sensing analysis. The retrieved mean particle effective radii of 2003 dust events are between 1.7--2.6 mum which is small enough to be inhaled and is hazardous to human health. The retrieved yearly dust mass load is 658--690 Tg, which is ˜45% of the annual global mineral dust production. Winter is the heaviest dust loading season in the year 2003, which is more than 5 times larger than that in the summer season in 2003.The mean optical depths at 11 mum in the winter season (around 0.7) are higher than those in the summer season (around 0.5). The results could help both meteorologists and environmental scientists to evaluate and predict the hazard degree caused by Saharan dust storms. (Abstract shortened by UMI.)

Evaluating the impact of above-cloud aerosols on cloud optical depth retrievals from MODIS

NASA Astrophysics Data System (ADS)

Alfaro, Ricardo

Using two different operational Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) cloud optical depth (COD) retrievals (visible and shortwave infrared), the impacts of above-cloud absorbing aerosols on the standard COD retrievals are evaluated. For fine-mode aerosol particles, aerosol optical depth (AOD) values diminish sharply from the visible to the shortwave infrared channels. Thus, a suppressed above-cloud particle radiance aliasing effect occurs for COD retrievals using shortwave infrared channels. Aerosol Index (AI) from the spatially and temporally collocated Ozone Monitoring Instrument (OMI) are used to identify above-cloud aerosol particle loading over the southern Atlantic Ocean, including both smoke and dust from the African sub-continent. MODIS and OMI Collocated Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) data are used to constrain cloud phase and provide contextual above-cloud AOD values. The frequency of occurrence of above-cloud aerosols is depicted on a global scale for the spring and summer seasons from OMI and CALIOP, thus indicating the significance of the problem. Seasonal frequencies for smoke-over-cloud off the southwestern Africa coastline reach 20--50% in boreal summer. We find a corresponding low COD bias of 10--20% for standard MODIS COD retrievals when averaged OMI AI are larger than 1.0. No such bias is found over the Saharan dust outflow region off northern Africa, since both MODIS visible and shortwave in channels are vulnerable to dust particle aliasing, and thus a COD impact cannot be isolated with this method. A similar result is found for a smaller domain, in the Gulf of Tonkin region, from smoke advection over marine stratocumulus clouds and outflow into the northern South China Sea in spring. This study shows the necessity of accounting for the above-cloud aerosol events for future studies using standard MODIS cloud products in biomass burning outflow regions, through the use of collocated OMI AI and supplementary MODIS shortwave infrared COD products.

Multi-wavelength dual polarisation lidar for monitoring precipitation process in the cloud seeding technique

NASA Astrophysics Data System (ADS)

Sudhakar, P.; Sheela, K. Anitha; Ramakrishna Rao, D.; Malladi, Satyanarayana

2016-05-01

In recent years weather modification activities are being pursued in many countries through cloud seeding techniques to facilitate the increased and timely precipitation from the clouds. In order to induce and accelerate the precipitation process clouds are artificially seeded with suitable materials like silver iodide, sodium chloride or other hygroscopic materials. The success of cloud seeding can be predicted with confidence if the precipitation process involving aerosol, the ice water balance, water vapor content and size of the seeding material in relation to aerosol in the cloud is monitored in real time and optimized. A project on the enhancement of rain fall through cloud seeding is being implemented jointly with Kerala State Electricity Board Ltd. Trivandrum, Kerala, India at the catchment areas of the reservoir of one of the Hydro electric projects. The dual polarization lidar is being used to monitor and measure the microphysical properties, the extinction coefficient, size distribution and related parameters of the clouds. The lidar makes use of the Mie, Rayleigh and Raman scattering techniques for the various measurement proposed. The measurements with the dual polarization lidar as above are being carried out in real time to obtain the various parameters during cloud seeding operations. In this paper we present the details of the multi-wavelength dual polarization lidar being used and the methodology to monitor the various cloud parameters involved in the precipitation process. The necessary retrieval algorithms for deriving the microphysical properties of clouds, aerosols characteristics and water vapor profiles are incorporated as a software package working under Lab-view for online and off line analysis. Details on the simulation studies and the theoretical model developed in this regard for the optimization of various parameters are discussed.

A potential regulation of jet stream behavior by changes in Arctic cirrus cloud formation mechanism and coverage

NASA Astrophysics Data System (ADS)

Mejia, J.; Mitchell, D. L.; Garnier, A.; Hosseinpour, F.; Avery, M. A.

2017-12-01

Global retrievals of cirrus cloud effective diameter De and mid-cloud temperature T were used to make the cirrus clouds simulated in CAM5 conform with the retrieved De, with the ice fall speeds in CAM5 calculated from the retrieved De. This was done by developing De-T relationships for six latitude zones. Within each latitude zone, seasonal De-T relationships were developed for cirrus over land and for cirrus over ocean (making 48 De-T relationships in total). The recently developed CALIPSO retrieval algorithm is sensitive to the ice crystal number concentration N, which is also retrieved, and it utilizes radiances from the infrared imaging radiometer and backscatter from the CALIPSO lidar. Retrieved De (N) is largest (lowest) between 30S and 30N latitude; a region dominated by anvil cirrus where pre-existing ice strongly favors heterogeneous ice nucleation (henceforth het). Therefore, the De-T relations for this region are considered representative for cirrus formed via het. Outside this region, retrieved De (N) tended to be considerably smaller (higher), presumably due to homogeneous ice nucleation (henceforth hom). Two CAM5 simulations were performed; one where cirrus cloud De is based on the CALIPSO retrievals and one where De-T for het cirrus is applied globally. Differences in net cloud radiative forcing between runs are believed due to differences in cirrus formation mechanism (hom vs. het). Such differences are typically 1.3 W m-2 in the mid-to-high latitudes in the N. Hemisphere excepting summer. These differences imply differences in cirrus cloud heating rates that affect temperatures in the underlying troposphere, which in turn affect the wind fields. The natural cirrus (mixture of hom and het) tend to trap more heat than the het cirrus. Changes in zonal wind fields between simulations suggest that heating by polar cirrus clouds have modifed meridional temperature gradients and thus zonal winds through the thermal wind balance. These changes in heating by polar cirrus clouds can modify the amplitude and meridional position of the midlatitude jet streams, which can lead to more extreme weather. Moreover, the retrievals indicate a doubling of Arctic cirrus coverage during winter, which will also result in increased heating of the underlying troposphere, likely contributing to this same phenomenon.

A physically-based retrieval of cloud liquid water from SSM/I measurements

NASA Technical Reports Server (NTRS)

Greenwald, Thomas J.; Stephens, Graeme L.; Vonder Haar, Thomas H.

1992-01-01

A simple physical scheme is proposed for retrieving cloud liquid water over the ice-free global oceans from Special Sensor Microwave/Imager (SSM/I) observations. Details of the microwave retrieval scheme are discussed, and the microwave-derived liquid water amounts are compared with the ground radiometer and AVHRR-derived liquid water for stratocumulus clouds off the coast of California. Global distributions of the liquid water path derived by the method proposed here are presented.

Aircraft millimeter-wave passive sensing of cloud liquid water and water vapor during VOCALS-REx

DOE PAGES

Zuidema, P.; Leon, D.; Pazmany, A.; ...

2012-01-05

Routine liquid water path measurements and water vapor path are valuable for process studies of the cloudy marine boundary layer and for the assessment of large-scale models. The VOCALS Regional Experiment respected this goal by including a small, inexpensive, upwardpointing millimeter-wavelength passive radiometer on the fourteen research flights of the NCAR C-130 plane, the Gband (183 GHz) Vapor Radiometer (GVR). The radiometer permitted above-cloud retrievals of the free-tropospheric water vapor path (WVP). Retrieved free-tropospheric (abovecloud) water vapor paths possessed a strong longitudinal gradient, with off-shore values of one to twomm and nearcoastal values reaching tenmm. The VOCALS-REx free troposphere wasmore » drier than that of previous years. Cloud liquid water paths (LWPs) were retrieved from the sub-cloud and cloudbase aircraft legs through a combination of the GVR, remotely-sensed cloud boundary information, and insitu thermodynamic data. The absolute (between-leg) and relative (within-leg) accuracy of the LWP retrievals at 1 Hz (≈100 m) resolution was estimated at 20 gm -2 and 3 gm -2 respectively for well-mixed conditions, and 25 gm -2 absolute uncertainty for decoupled conditions where the input WVP specification was more uncertain. Retrieved liquid water paths matched adiabatic values derived from coincident cloud thickness measurements exceedingly well. A significant contribution of the GVR dataset was the extended information on the thin clouds, with 62% (28 %) of the retrieved LWPs <100 (40) gm -2. Coastal LWPs values were lower than those offshore. For the four dedicated 20° S flights, the mean (median) coastal LWP was 67 (61) gm -2, increasing to 166 (120) gm -2 1500 km offshore. Finally, the overall LWP cloud fraction from thirteen research flights was 63 %, higher than that of adiabatic LWPs at 40 %, but lower than the lidar-determined cloud cover of 85 %, further testifying to the frequent occurrence of thin clouds.« less

Radiative transfer models for retrieval of cloud parameters from EPIC/DSCOVR measurements

NASA Astrophysics Data System (ADS)

Molina García, Víctor; Sasi, Sruthy; Efremenko, Dmitry S.; Doicu, Adrian; Loyola, Diego

2018-07-01

In this paper we analyze the accuracy and efficiency of several radiative transfer models for inferring cloud parameters from radiances measured by the Earth Polychromatic Imaging Camera (EPIC) on board the Deep Space Climate Observatory (DSCOVR). The radiative transfer models are the exact discrete ordinate and matrix operator methods with matrix exponential, and the approximate asymptotic and equivalent Lambertian cloud models. To deal with the computationally expensive radiative transfer calculations, several acceleration techniques such as, for example, the telescoping technique, the method of false discrete ordinate, the correlated k-distribution method and the principal component analysis (PCA) are used. We found that, for the EPIC oxygen A-band absorption channel at 764 nm, the exact models using the correlated k-distribution in conjunction with PCA yield an accuracy better than 1.5% and a computation time of 18 s for radiance calculations at 5 viewing zenith angles.

Sensitivities of simulated satellite views of clouds to subgrid-scale overlap and condensate heterogeneity

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

Hillman, Benjamin R.; Marchand, Roger T.; Ackerman, Thomas P.

Satellite simulators are often used to account for limitations in satellite retrievals of cloud properties in comparisons between models and satellite observations. The purpose of the simulator framework is to enable more robust evaluation of model cloud properties, so that di erences between models and observations can more con dently be attributed to model errors. However, these simulators are subject to uncertainties themselves. A fundamental uncertainty exists in connecting the spatial scales at which cloud properties are retrieved with those at which clouds are simulated in global models. In this study, we create a series of sensitivity tests using 4more » km global model output from the Multiscale Modeling Framework to evaluate the sensitivity of simulated satellite retrievals when applied to climate models whose grid spacing is many tens to hundreds of kilometers. In particular, we examine the impact of cloud and precipitation overlap and of condensate spatial variability. We find the simulated retrievals are sensitive to these assumptions. Specifically, using maximum-random overlap with homogeneous cloud and precipitation condensate, which is often used in global climate models, leads to large errors in MISR and ISCCP-simulated cloud cover and in CloudSat-simulated radar reflectivity. To correct for these errors, an improved treatment of unresolved clouds and precipitation is implemented for use with the simulator framework and is shown to substantially reduce the identified errors.« less

Observational evidence of fire-driven changes to tropical cloudiness

NASA Astrophysics Data System (ADS)

Tosca, Michael; Diner, David; Garay, Michael; Kalashnikova, Olga

2014-05-01

Anthropogenic fires in the tropics emit smoke aerosols that affect cloud dynamics, meteorology and climate (Tosca et al., 2013). We developed a new technique to observationally quantify the cloud response to biomass burning aerosols using aerosol retrievals from the Multi-angle Imaging SpectroRadiometer (MISR) and non-coincident cloud retrievals from the MODerate resolution Imaging Spectroradiometer (MODIS) from collocated morning and afternoon overpasses. The Global Fire Emissions Database, version 3 and Level 2 data from scenes acquired between 2006 and 2010 were used to quantify changes in cloud fraction from morning (10:30am local time) to afternoon (1:30pm local time) in the presence of varying fire-aerosol burdens. This temporal offset allowed for analysis of the evolution of clouds in the presence of aerosols, something that previous methods using coincident observations could not produce. We controlled for large-scale meteorological differences between scenes using reanalysis data from the ERA-interim product and matching scenes with fire smoke to those with no smoke and similar initial (morning) meteorological conditions. Elevated aerosol optical depths (AODs) reduced cloud fraction from morning to afternoon in the Southeast Asia, Central America and northern Africa burning regions. In mostly cloudy conditions, aerosols significantly reduced cloud fraction, but in clear skies, cloud fraction increased. These results support the general hypothesis of a positive feedback loop between anthropogenic burning and cloudiness in tropical regions, and are consistent with previous studies linking smoke aerosols to convective cloud reduction. Tosca, M.G., J.T. Randerson and C.S. Zender (2013), Global impact of smoke aerosols from landscape fires on climate and the Hadley circulation, Atmos. Chem. Phys., 13, 5227-5241, doi: 10.5194/acp-13-5227-2013.

Retrieving the Polar Mixed-Phase Cloud Liquid Water Path by Combining CALIOP and IIR Measurements

NASA Astrophysics Data System (ADS)

Luo, Tao; Wang, Zhien; Li, Xuebin; Deng, Shumei; Huang, Yong; Wang, Yingjian

2018-02-01

Mixed-phase cloud (MC) is the dominant cloud type over the polar region, and there are challenging conditions for remote sensing and in situ measurements. In this study, a new methodology of retrieving the stratiform MC liquid water path (LWP) by combining Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and infrared imaging radiometer (IIR) measurements was developed and evaluated. This new methodology takes the advantage of reliable cloud-phase discrimination by combining lidar and radar measurements. An improved multiple-scattering effect correction method for lidar signals was implemented to provide reliable cloud extinction near cloud top. Then with the adiabatic cloud assumption, the MC LWP can be retrieved by a lookup-table-based method. Simulations with error-free inputs showed that the mean bias and the root mean squared error of the LWP derived from the new method are -0.23 ± 2.63 g/m2, with the mean absolute relative error of 4%. Simulations with erroneous inputs suggested that the new methodology could provide reliable retrieval of LWP to support the statistical or climatology analysis. Two-month A-train satellite retrievals over Arctic region showed that the new method can produce very similar cloud top temperature (CTT) dependence of LWP to the ground-based microwave radiometer measurements, with a bias of -0.78 g/m2 and a correlation coefficient of 0.95 between the two mean CTT-LWP relationships. The new approach can also produce reasonable pattern and value of LWP in spatial distribution over the Arctic region.

The Effect of Clouds on Water Vapor Profiling from the Millimeter-Wave Radiometric Measurements

NASA Technical Reports Server (NTRS)

Wang, J. R.; Spinhirne, J. D.; Racette, P.; Chang, L. A.; Hart, W.

1997-01-01

Simultaneous measurements with the millimeter-wave imaging radiometer (MIR), cloud lidar system (CLS), and the MODIS airborne simulator (MAS) were made aboard the NASA ER-2 aircraft over the western Pacific Ocean on 17-18 January 1993. These measurements were used to study the effects of clouds on water vapor profile retrievals based on millimeter-wave radiometer measurements. The CLS backscatter measurements (at 0.532 and 1.064 am) provided information on the heights and a detailed structure of cloud layers; the types of clouds could be positively identified. All 12 MAS channels (0.6-13 Am) essentially respond to all types of clouds, while the six MIR channels (89-220 GHz) show little sensitivity to cirrus clouds. The radiances from the 12-/Am and 0.875-gm channels of the MAS and the 89-GHz channel of the MIR were used to gauge the performance of the retrieval of water vapor profiles from the MIR observations under cloudy conditions. It was found that, for cirrus and absorptive (liquid) clouds, better than 80% of the retrieval was convergent when one of the three criteria was satisfied; that is, the radiance at 0.875 Am is less than 100 W/cm.sr, or the brightness at 12 Am is greater than 260 K, or brightness at 89 GHz is less than 270 K (equivalent to cloud liquid water of less than 0.04 g/cm). The range of these radiances for convergent retrieval increases markedly when the condition for convergent retrieval was somewhat relaxed. The algorithm of water vapor profiling from the MIR measurements could not perform adequately over the areas of storm-related clouds that scatter radiation at millimeter wavelengths.

Modeling Lidar Multiple Scattering

NASA Astrophysics Data System (ADS)

Sato, Kaori; Okamoto, Hajime; Ishimoto, Hiroshi

2016-06-01

A practical model to simulate multiply scattered lidar returns from inhomogeneous cloud layers are developed based on Backward Monte Carlo (BMC) simulations. The estimated time delay of the backscattered intensities returning from different vertical grids by the developed model agreed well with that directly obtained from BMC calculations. The method was applied to the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite data to improve the synergetic retrieval of cloud microphysics with CloudSat radar data at optically thick cloud grids. Preliminary results for retrieving mass fraction of co-existing cloud particles and drizzle size particles within lowlevel clouds are demonstrated.

Retrieval of ice cloud properties using an optimal estimation algorithm and MODIS infrared observations. Part I: Forward model, error analysis, and information content

PubMed Central

Wang, Chenxi; Platnick, Steven; Zhang, Zhibo; Meyer, Kerry; Yang, Ping

2018-01-01

An optimal estimation (OE) retrieval method is developed to infer three ice cloud properties simultaneously: optical thickness (τ), effective radius (reff), and cloud-top height (h). This method is based on a fast radiative transfer (RT) model and infrared (IR) observations from the MODerate resolution Imaging Spectroradiometer (MODIS). This study conducts thorough error and information content analyses to understand the error propagation and performance of retrievals from various MODIS band combinations under different cloud/atmosphere states. Specifically, the algorithm takes into account four error sources: measurement uncertainty, fast RT model uncertainty, uncertainties in ancillary datasets (e.g., atmospheric state), and assumed ice crystal habit uncertainties. It is found that the ancillary and ice crystal habit error sources dominate the MODIS IR retrieval uncertainty and cannot be ignored. The information content analysis shows that, for a given ice cloud, the use of four MODIS IR observations is sufficient to retrieve the three cloud properties. However, the selection of MODIS IR bands that provide the most information and their order of importance varies with both the ice cloud properties and the ambient atmospheric and the surface states. As a result, this study suggests the inclusion of all MODIS IR bands in practice since little a priori information is available. PMID:29707470

Retrieval of Ice Cloud Properties Using an Optimal Estimation Algorithm and MODIS Infrared Observations. Part I: Forward Model, Error Analysis, and Information Content

NASA Technical Reports Server (NTRS)

Wang, Chenxi; Platnick, Steven; Zhang, Zhibo; Meyer, Kerry; Yang, Ping

2016-01-01

An optimal estimation (OE) retrieval method is developed to infer three ice cloud properties simultaneously: optical thickness (tau), effective radius (r(sub eff)), and cloud-top height (h). This method is based on a fast radiative transfer (RT) model and infrared (IR) observations from the MODerate resolution Imaging Spectroradiometer (MODIS). This study conducts thorough error and information content analyses to understand the error propagation and performance of retrievals from various MODIS band combinations under different cloud/atmosphere states. Specifically, the algorithm takes into account four error sources: measurement uncertainty, fast RT model uncertainty, uncertainties in ancillary datasets (e.g., atmospheric state), and assumed ice crystal habit uncertainties. It is found that the ancillary and ice crystal habit error sources dominate the MODIS IR retrieval uncertainty and cannot be ignored. The information content analysis shows that, for a given ice cloud, the use of four MODIS IR observations is sufficient to retrieve the three cloud properties. However, the selection of MODIS IR bands that provide the most information and their order of importance varies with both the ice cloud properties and the ambient atmospheric and the surface states. As a result, this study suggests the inclusion of all MODIS IR bands in practice since little a priori information is available.

Retrieval of Ice Cloud Properties Using an Optimal Estimation Algorithm and MODIS Infrared Observations. Part I: Forward Model, Error Analysis, and Information Content

NASA Technical Reports Server (NTRS)

Wang, Chenxi; Platnick, Steven; Zhang, Zhibo; Meyer, Kerry; Yang, Ping

2016-01-01

An optimal estimation (OE) retrieval method is developed to infer three ice cloud properties simultaneously: optical thickness (tau), effective radius (r(sub eff)), and cloud top height (h). This method is based on a fast radiative transfer (RT) model and infrared (IR) observations from the MODerate resolution Imaging Spectroradiometer (MODIS). This study conducts thorough error and information content analyses to understand the error propagation and performance of retrievals from various MODIS band combinations under different cloud/atmosphere states. Specifically, the algorithm takes into account four error sources: measurement uncertainty, fast RT model uncertainty, uncertainties in ancillary data sets (e.g., atmospheric state), and assumed ice crystal habit uncertainties. It is found that the ancillary and ice crystal habit error sources dominate the MODIS IR retrieval uncertainty and cannot be ignored. The information content analysis shows that for a given ice cloud, the use of four MODIS IR observations is sufficient to retrieve the three cloud properties. However, the selection of MODIS IR bands that provide the most information and their order of importance varies with both the ice cloud properties and the ambient atmospheric and the surface states. As a result, this study suggests the inclusion of all MODIS IR bands in practice since little a priori information is available.

Near-Real Time Satellite-Retrieved Cloud and Surface Properties for Weather and Aviation Safety Applications

NASA Technical Reports Server (NTRS)

Minnis, Patrick; Smith, William L., Jr.; Bedka, Kristopher M.; Nguyen, Louis; Palikonda, Rabindra; Hong, Gang; Trepte, Qing Z.; Chee, Thad; Scarino, Benjamin; Spangenberg, Douglas A.;

Near-Real Time Satellite-Retrieved Cloud and Surface Properties for Weather and Aviation Safety Applications

NASA Astrophysics Data System (ADS)

Minnis, P.; Smith, W., Jr.; Bedka, K. M.; Nguyen, L.; Palikonda, R.; Hong, G.; Trepte, Q.; Chee, T.; Scarino, B. R.; Spangenberg, D.; Sun-Mack, S.; Fleeger, C.; Ayers, J. K.; Chang, F. L.; Heck, P. W.

2014-12-01

Cloud properties determined from satellite imager radiances provide a valuable source of information for nowcasting and weather forecasting. In recent years, it has been shown that assimilation of cloud top temperature, optical depth, and total water path can increase the accuracies of weather analyses and forecasts. Aircraft icing conditions can be accurately diagnosed in near-real time (NRT) retrievals of cloud effective particle size, phase, and water path, providing valuable data for pilots. NRT retrievals of surface skin temperature can also be assimilated in numerical weather prediction models to provide more accurate representations of solar heating and longwave cooling at the surface, where convective initiation. These and other applications are being exploited more frequently as the value of NRT cloud data become recognized. At NASA Langley, cloud properties and surface skin temperature are being retrieved in near-real time globally from both geostationary (GEO) and low-earth orbiting (LEO) satellite imagers for weather model assimilation and nowcasting for hazards such as aircraft icing. Cloud data from GEO satellites over North America are disseminated through NCEP, while those data and global LEO and GEO retrievals are disseminated from a Langley website. This paper presents an overview of the various available datasets, provides examples of their application, and discusses the use of the various datasets downstream. Future challenges and areas of improvement are also presented.

Observations of cloud liquid water path over oceans: Optical and microwave remote sensing methods

NASA Technical Reports Server (NTRS)

Lin, Bing; Rossow, William B.

1994-01-01

Published estimates of cloud liquid water path (LWP) from satellite-measured microwave radiation show little agreement, even about the relative magnitudes of LWP in the tropics and midlatitudes. To understand these differences and to obtain more reliable estimate, optical and microwave LWP retrieval methods are compared using the International Satellite Cloud Climatology Project (ISCCP) and special sensor microwave/imager (SSM/I) data. Errors in microwave LWP retrieval associated with uncertainties in surface, atmosphere, and cloud properties are assessed. Sea surface temperature may not produce great LWP errors, if accurate contemporaneous measurements are used in the retrieval. An uncertainty of estimated near-surface wind speed as high as 2 m/s produces uncertainty in LWP of about 5 mg/sq cm. Cloud liquid water temperature has only a small effect on LWP retrievals (rms errors less than 2 mg/sq cm), if errors in the temperature are less than 5 C; however, such errors can produce spurious variations of LWP with latitude and season. Errors in atmospheric column water vapor (CWV) are strongly coupled with errors in LWP (for some retrieval methods) causing errors as large as 30 mg/sq cm. Because microwave radiation is much less sensitive to clouds with small LWP (less than 7 mg/sq cm) than visible wavelength radiation, the microwave results are very sensitive to the process used to separate clear and cloudy conditions. Different cloud detection sensitivities in different microwave retrieval methods bias estimated LWP values. Comparing ISCCP and SSM/I LWPs, we find that the two estimated values are consistent in global, zonal, and regional means for warm, nonprecipitating clouds, which have average LWP values of about 5 mg/sq cm and occur much more frequently than precipitating clouds. Ice water path (IWP) can be roughly estimated from the differences between ISCCP total water path and SSM/I LWP for cold, nonprecipitating clouds. IWP in the winter hemisphere is about 3 times the LWP but only half the LWP in the summer hemisphere. Precipitating clouds contribute significantly to monthly, zonal mean LWP values determined from microwave, especially in the intertropical convergence zone (ITCZ), because they have almost 10 times the liquid water (cloud plus precipitation) of nonprecipitating clouds on average. There are significant differences among microwave LWP estimates associated with the treatment of precipitating clouds.

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

NASA Technical Reports Server (NTRS)

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

1977-01-01

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

Solar energy estimated from geostationary satellites and its application on the energy management system

NASA Astrophysics Data System (ADS)

Nakajima, T. Y.; Takamatsu, T.; Funayama, T.; Yamamoto, Y.; Takenaka, H.; Nakajima, T.; Irie, H.; Higuchi, A.

2017-12-01

Recently, estimating and forecasting the solar radiation in terms of the electric power generation by photovoltaic (PV) systems is needed for the energy management system (EMS). The estimation technique depends on the latest atmospheric sciences. For instance, when one like to estimate solar radiation reached to ground surface, one will focus on the existence of clouds and their properties, because clouds exert an important influence to the radiative transfer. Visible-to-infared imaging radiometer aboard the geostationary satellites, Himawari, GOES, and Meteosat are useful for such objective, since they observe clouds for full disk of the Earth with high temporal frequency and moderately spatial resolution. Estimation of solar radiation at the ground surface from satellite imagery consists of two steps. The first step is retrieval of cloud optical and microphysical properties by use of the multispectral imaging data. Indeed, we retrieve cloud optical thickness, cloud particle sizes, and cloud top height from visible, near-infrared, and thermal infrared wavelength of the satellite imageries, respectively. The second step is the radiative transfer calculation. We will obtain solar radiation reached to the ground surface, using cloud properties retrieved from the first step, and radiative transfer calculations. We have built a system for near-real time estimation of solar radiation for global scale, named the AMATERASS system, under the support of JST (Japan Science and Technology Agency), CREST/EMS (Energy Management System). The AMATERASS dataset has been used for several researches. For example, Waseda University group applied the AMATERASS data in the electric power system, considering accidental blackout in the electric system for local scale. They made it clear that when AMATERASS data exists the chance of electric voltage deviancy is mitigated when the blackout is over. We have supported a solar car race in Australia, named World Solar Challenge (WSC) 2013, 2015, and 2017, by suppling the AMATERASS solar radiation and some meteorological data along the race track, dynamically following the location of the solar car. This experience is important because the era of electric vehicles equippe with PV panels will come soon.

A cloud and radiation model-based algorithm for rainfall retrieval from SSM/I multispectral microwave measurements

NASA Technical Reports Server (NTRS)

Xiang, Xuwu; Smith, Eric A.; Tripoli, Gregory J.

1992-01-01

A hybrid statistical-physical retrieval scheme is explored which combines a statistical approach with an approach based on the development of cloud-radiation models designed to simulate precipitating atmospheres. The algorithm employs the detailed microphysical information from a cloud model as input to a radiative transfer model which generates a cloud-radiation model database. Statistical procedures are then invoked to objectively generate an initial guess composite profile data set from the database. The retrieval algorithm has been tested for a tropical typhoon case using Special Sensor Microwave/Imager (SSM/I) data and has shown satisfactory results.

Coupling of the microphysical and optical properties of an Arctic nimbostratus cloud during the ASTAR 2004 experiment: Implications for light-scattering modeling

NASA Astrophysics Data System (ADS)

Jourdan, Olivier; Mioche, Guillaume; Garrett, Timothy J.; SchwarzenböCk, Alfons; Vidot, JéRôMe; Xie, Yu; Shcherbakov, Valery; Yang, Ping; Gayet, Jean-FrançOis

2010-12-01

Airborne measurements in an Arctic mixed-phase nimbostratus cloud were conducted in Spitsbergen on 21 May 2004 during the international Arctic Study of Tropospheric Aerosol, Clouds and Radiation (ASTAR) campaign. The in situ instrument suite aboard the Alfred Wegener Institute Polar 2 aircraft included a polar nephelometer (PN), a cloud particle imager (CPI), a Nevzorov probe, and a standard PMS 2DC probe to measure the cloud particle single-scattering properties (at a wavelength of 0.8 μm), and the particle morphology and size, as well as the in-cloud partitioning of ice/water content. The main objective of this work is to present a technique based on principal component analysis and light-scattering modeling to link the microphysical properties of cloud particles to their optical characteristics. The technique is applied to the data collected during the 21 May case study where a wide variety of ice crystal shapes and liquid water fractions were observed at temperatures ranging from -1°C to -12°C. CPI measurements highlight the presence of large supercooled water droplets with diameters close to 500 μm. Although the majority of ice particles were found to have irregular shapes, columns and needles were the prevailing regular habits between -3°C and -6°C while stellars and plates were observed at temperatures below -8°C. The implementation of the principal component analysis of the PN scattering phase function measurements revealed representative optical patterns that were consistent with the particle habit classification derived from the CPI. This indicates that the synergy between the CPI and the PN can be exploited to link the microphysical and shape properties of cloud particles to their single-scattering characteristics. Using light-scattering modeling, we have established equivalent microphysical models based on a limited set of free parameters (roughness, mixture of idealized particle habits, and aspect ratio of ice crystals) that reproduce the main optical features assessed for cloud regions with different particle geometries and liquid water fractions. However, the retrieved bulk microphysical parameters can substantially differ from the measurements (by several times for the effective size and up to 3 orders of magnitude for the number concentration). Several possible explanations for these discrepancies are discussed. The retrievals show that the optical contribution of small particles with sizes lower than 50 μm (droplets and ice crystals) is significant, always exceeding 50% of the total scattering signal, and thus needs to be more accurately quantified. The shattering of large ice crystals on the shrouded inlet of the PN could also strongly affect the retrieved microphysical parameters.

Assessment of Uncertainty in Cloud Radiative Effects and Heating Rates through Retrieval Algorithm Differences: Analysis using 3-years of ARM data at Darwin, Australia

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

Comstock, Jennifer M.; Protat, Alain; McFarlane, Sally A.

2013-05-22

Ground-based radar and lidar observations obtained at the Department of Energy’s Atmospheric Radiation Measurement Program’s Tropical Western Pacific site located in Darwin, Australia are used to retrieve ice cloud properties in anvil and cirrus clouds. Cloud microphysical properties derived from four different retrieval algorithms (two radar-lidar and two radar only algorithms) are compared by examining mean profiles and probability density functions of effective radius (Re), ice water content (IWC), extinction, ice number concentration, ice crystal fall speed, and vertical air velocity. Retrieval algorithm uncertainty is quantified using radiative flux closure exercises. The effect of uncertainty in retrieved quantities on themore » cloud radiative effect and radiative heating rates are presented. Our analysis shows that IWC compares well among algorithms, but Re shows significant discrepancies, which is attributed primarily to assumptions of particle shape. Uncertainty in Re and IWC translates into sometimes-large differences in cloud radiative effect (CRE) though the majority of cases have a CRE difference of roughly 10 W m-2 on average. These differences, which we believe are primarily driven by the uncertainty in Re, can cause up to 2 K/day difference in the radiative heating rates between algorithms.« less

Characterizing the Trade Space Between Capability and Complexity in Next Generation Cloud and Precipitation Observing Systems Using Markov Chain Monte Carlos Techniques

NASA Astrophysics Data System (ADS)

Xu, Z.; Mace, G. G.; Posselt, D. J.

2017-12-01

As we begin to contemplate the next generation atmospheric observing systems, it will be critically important that we are able to make informed decisions regarding the trade space between scientific capability and the need to keep complexity and cost within definable limits. To explore this trade space as it pertains to understanding key cloud and precipitation processes, we are developing a Markov Chain Monte Carlo (MCMC) algorithm suite that allows us to arbitrarily define the specifications of candidate observing systems and then explore how the uncertainties in key retrieved geophysical parameters respond to that observing system. MCMC algorithms produce a more complete posterior solution space, and allow for an objective examination of information contained in measurements. In our initial implementation, MCMC experiments are performed to retrieve vertical profiles of cloud and precipitation properties from a spectrum of active and passive measurements collected by aircraft during the ACE Radiation Definition Experiments (RADEX). Focusing on shallow cumulus clouds observed during the Integrated Precipitation and Hydrology EXperiment (IPHEX), observing systems in this study we consider W and Ka-band radar reflectivity, path-integrated attenuation at those frequencies, 31 and 94 GHz brightness temperatures as well as visible and near-infrared reflectance. By varying the sensitivity and uncertainty of these measurements, we quantify the capacity of various combinations of observations to characterize the physical properties of clouds and precipitation.

CERES ISCCP-D2like Data Products

Atmospheric Science Data Center

2014-07-24

... D2 format.  Merged : Terra + Aqua MODIS and 3-hourly geostationary cloud retrievals for daytime only.  GEO : 3-hourly geostationary-only cloud retrievals for daytime only.  Day/Nit : Single ...

Evaluating the impact of aerosol particles above cloud on cloud optical depth retrievals from MODIS

NASA Astrophysics Data System (ADS)

Alfaro-Contreras, Ricardo; Zhang, Jianglong; Campbell, James R.; Holz, Robert E.; Reid, Jeffrey S.

2014-05-01

Using two different operational Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) cloud optical depth (COD) retrievals (0.86 versus 1.6 µm), we evaluate the impact of above-cloud smoke aerosol particles on near-IR (0.86 µm) COD retrievals. Aerosol Index (AI) from the collocated Ozone Monitoring Instrument (OMI) are used to identify above-cloud aerosol particle loading over the southern Atlantic Ocean, including both smoke and dust from the African subcontinent. Collocated Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation data constrain cloud phase and provide contextual above-cloud aerosol optical depth. The frequency of occurrence of above-cloud aerosol events is depicted on a global scale for the spring and summer seasons from OMI and Cloud Aerosol Lidar with Orthogonal Polarization. Seasonal frequencies for smoke-over-cloud off the southwestern Africa coastline reach 20-50% in boreal summer. We find a corresponding low COD bias of 10-20% for standard MODIS COD retrievals when averaged OMI AI are larger than 1. No such bias is found over the Saharan dust outflow region off northern Africa, since both MODIS 0.86 and 1.6 µm channels are vulnerable to radiance attenuation due to dust particles. A similar result is found for a smaller domain, in the Gulf of Tonkin region, from smoke advection over marine stratocumulus clouds and outflow into the northern South China Sea in spring. This study shows the necessity of accounting for the above-cloud aerosol events for future studies using standard MODIS cloud products in biomass burning outflow regions, through the use of collocated OMI AI and supplementary MODIS 1.6 µm COD products.

The Dependence of Cloud Property Trend Detection on Absolute Calibration Accuracy of Passive Satellite Sensors

NASA Astrophysics Data System (ADS)

Shea, Y.; Wielicki, B. A.; Sun-Mack, S.; Minnis, P.; Zelinka, M. D.

2016-12-01

Detecting trends in climate variables on global, decadal scales requires highly accurate, stable measurements and retrieval algorithms. Trend uncertainty depends on its magnitude, natural variability, and instrument and retrieval algorithm accuracy and stability. We applied a climate accuracy framework to quantify the impact of absolute calibration on cloud property trend uncertainty. The cloud properties studied were cloud fraction, effective temperature, optical thickness, and effective radius retrieved using the Clouds and the Earth's Radiant Energy System (CERES) Cloud Property Retrieval System, which uses Moderate-resolution Imaging Spectroradiometer measurements (MODIS). Modeling experiments from the fifth phase of the Climate Model Intercomparison Project (CMIP5) agree that net cloud feedback is likely positive but disagree regarding its magnitude, mainly due to uncertainty in shortwave cloud feedback. With the climate accuracy framework we determined the time to detect trends for instruments with various calibration accuracies. We estimated a relationship between cloud property trend uncertainty, cloud feedback, and Equilibrium Climate Sensitivity and also between effective radius trend uncertainty and aerosol indirect effect trends. The direct relationship between instrument accuracy requirements and climate model output provides the level of instrument absolute accuracy needed to reduce climate model projection uncertainty. Different cloud types have varied radiative impacts on the climate system depending on several attributes, such as their thermodynamic phase, altitude, and optical thickness. Therefore, we also conducted these studies by cloud types for a clearer understanding of instrument accuracy requirements needed to detect changes in their cloud properties. Combining this information with the radiative impact of different cloud types helps to prioritize among requirements for future satellite sensors and understanding the climate detection capabilities of existing sensors.

Atmospheric CO2 Concentration Measurements with Clouds from an Airborne Lidar

NASA Astrophysics Data System (ADS)

Mao, J.; Abshire, J. B.; Kawa, S. R.; Riris, H.; Allan, G. R.; Hasselbrack, W. E.; Numata, K.; Chen, J. R.; Sun, X.; DiGangi, J. P.; Choi, Y.

2017-12-01

Globally distributed atmospheric CO2 concentration measurements with high precision, low bias and full seasonal sampling are crucial to advance carbon cycle sciences. However, two thirds of the Earth's surface is typically covered by clouds, and passive remote sensing approaches from space are limited to cloud-free scenes. NASA Goddard is developing a pulsed, integrated-path differential absorption (IPDA) lidar approach to measure atmospheric column CO2 concentrations, XCO2, from space as a candidate for NASA's ASCENDS mission. Measurements of time-resolved laser backscatter profiles from the atmosphere also allow this technique to estimate XCO2 and range to cloud tops in addition to those to the ground with precise knowledge of the photon path-length. We demonstrate this measurement capability using airborne lidar measurements from summer 2017 ASCENDS airborne science campaign in Alaska. We show retrievals of XCO2 to ground and to a variety of cloud tops. We will also demonstrate how the partial column XCO2 to cloud tops and cloud slicing approach help resolving vertical and horizontal gradient of CO2 in cloudy conditions. The XCO2 retrievals from the lidar are validated against in situ measurements and compared to the Goddard Parameterized Chemistry Transport Model (PCTM) simulations. Adding this measurement capability to the future lidar mission for XCO2 will provide full global and seasonal data coverage and some information about vertical structure of CO2. This unique facility is expected to benefit atmospheric transport process studies, carbon data assimilation in models, and global and regional carbon flux estimation.

Arctic PBL Cloud Height and Motion Retrievals from MISR and MINX

NASA Technical Reports Server (NTRS)

Wu, Dong L.

2012-01-01

How Arctic clouds respond and feedback to sea ice loss is key to understanding of the rapid climate change seen in the polar region. As more open water becomes available in the Arctic Ocean, cold air outbreaks (aka. off-ice flow from polar lows) produce a vast sheet of roll clouds in the planetary boundary layer (PBl). The cold air temperature and wind velocity are the critical parameters to determine and understand the PBl structure formed under these roll clouds. It has been challenging for nadir visible/IR sensors to detect Arctic clouds due to lack of contrast between clouds and snowy/icy surfaces. In addition) PBl temperature inversion creates a further problem for IR sensors to relate cloud top temperature to cloud top height. Here we explore a new method with the Multiangle Imaging Spectro-Radiometer (MISR) instrument to measure cloud height and motion over the Arctic Ocean. Employing a stereoscopic-technique, MISR is able to measure cloud top height accurately and distinguish between clouds and snowy/icy surfaces with the measured height. We will use the MISR INteractive eXplorer (MINX) to quantify roll cloud dynamics during cold-air outbreak events and characterize PBl structures over water and over sea ice.

Retrievals of Ice Cloud Microphysical Properties of Deep Convective Systems using Radar Measurements

NASA Astrophysics Data System (ADS)

Tian, J.; Dong, X.; Xi, B.; Wang, J.; Homeyer, C. R.

2015-12-01

This study presents innovative algorithms for retrieving ice cloud microphysical properties of Deep Convective Systems (DCSs) using Next-Generation Radar (NEXRAD) reflectivity and newly derived empirical relationships from aircraft in situ measurements in Wang et al. (2015) during the Midlatitude Continental Convective Clouds Experiment (MC3E). With composite gridded NEXRAD radar reflectivity, four-dimensional (space-time) ice cloud microphysical properties of DCSs are retrieved, which is not possible from either in situ sampling at a single altitude or from vertical pointing radar measurements. For this study, aircraft in situ measurements provide the best-estimated ice cloud microphysical properties for validating the radar retrievals. Two statistical comparisons between retrieved and aircraft in situ measured ice microphysical properties are conducted from six selected cases during MC3E. For the temporal-averaged method, the averaged ice water content (IWC) and median mass diameter (Dm) from aircraft in situ measurements are 0.50 g m-3 and 1.51 mm, while the retrievals from radar reflectivity have negative biases of 0.12 g m-3 (24%) and 0.02 mm (1.3%) with correlations of 0.71 and 0.48, respectively. For the spatial-averaged method, the IWC retrievals are closer to the aircraft results (0.51 vs. 0.47 g m-3) with a positive bias of 8.5%, whereas the Dm retrievals are larger than the aircraft results (1.65 mm vs. 1.51 mm) with a positive bias of 9.3%. The retrieved IWCs decrease from ~0.6 g m-3 at 5 km to ~0.15 g m-3 at 13 km, and Dm values decrease from ~2 mm to ~0.7 mm at the same levels. In general, the aircraft in situ measured IWC and Dm values at each level are within one standard derivation of retrieved properties. Good agreements between microphysical properties measured from aircraft and retrieved from radar reflectivity measurements indicate the reasonable accuracy of our retrievals.

Added Value of Far-Infrared Radiometry for Ice Cloud Remote Sensing

NASA Astrophysics Data System (ADS)

Libois, Q.; Blanchet, J. P.; Ivanescu, L.; S Pelletier, L.; Laurence, C.

2017-12-01

Several cloud retrieval algorithms based on satellite observations in the infrared have been developed in the last decades. However, most of these observations only cover the midinfrared (MIR, λ < 15 μm) part of the spectrum, and none are available in the far-infrared (FIR, λ ≥ 15 μm). Recent developments in FIR sensors technology, though, now make it possible to consider spaceborne remote sensing in the FIR. Here we show that adding a few FIR channels with realistic radiometric performances to existing spaceborne narrowband radiometers would significantly improve their ability to retrieve ice cloud radiative properties. For clouds encountered in the polar regions and the upper troposphere, where the atmosphere above clouds is sufficiently transparent in the FIR, using FIR channels would reduce by more than 50% the uncertainties on retrieved values of optical thickness, effective particle diameter, and cloud top altitude. This would somehow extend the range of applicability of current infrared retrieval methods to the polar regions and to clouds with large optical thickness, where MIR algorithms perform poorly. The high performance of solar reflection-based algorithms would thus be reached in nighttime conditions. Using FIR observations is a promising venue for studying ice cloud microphysics and precipitation processes, which is highly relevant for cirrus clouds and convective towers, and for investigating the water cycle in the driest regions of the atmosphere.

The Clouds of Isidore

NASA Technical Reports Server (NTRS)

2002-01-01

These views of Hurricane Isidore were acquired by the Multi-angle Imaging SpectroRadiometer (MISR) on September 20, 2002. After bringing large-scale flooding to western Cuba, Isidore was upgraded (on September 21) from a tropical storm to a category 3hurricane. Sweeping westward to Mexico's Yucatan Peninsula, the hurricane caused major destruction and left hundreds of thousands of people homeless. Although weakened after passing over the Yucatan landmass, Isidore regained strength as it moved northward over the Gulf of Mexico.

At left is a colorful visualization of cloud extent that superimposes MISR's radiometric camera-by-camera cloud mask (RCCM) over natural-color radiance imagery, both derived from data acquired with the instrument's vertical-viewing (nadir) camera. Using brightness and statistical metrics, the RCCM is one of several techniques MISR uses to determine whether an area is clear or cloudy. In this rendition, the RCCM has been color-coded, and purple = cloudy with high confidence, blue = cloudy with low confidence, green = clear with low confidence, and red = clear with high confidence.

In addition to providing information on meteorological events, MISR's data products are designed to help improve our understanding of the influences of clouds on climate. Cloud heights and albedos are among the variables that govern these influences. (Albedo is the amount of sunlight reflected back to space divided by the amount of incident sunlight.) The center panel is the cloud-top height field retrieved using automated stereoscopic processing of data from multiple MISR cameras. Areas where heights could not be retrieved are shown in dark gray. In some areas, such as the southern portion of the image, the stereo retrieval was able to detect thin, high clouds that were not picked up by the RCCM's nadir view. Retrieved local albedo values for Isidore are shown at right. Generation of the albedo product is dependent upon observed cloud radiances as a function of viewing angle as well as the height field. Note that over the short distances (2.2 kilometers) that the local albedo product is generated, values can be greater than 1.0 due to contributions from cloud sides. Areas where albedo could not be retrieved are shown in dark gray.

The Multi-angle Imaging SpectroRadiometer observes the daylit Earth continuously from pole to pole, and every 9 days views the entire globe between 82 degrees north and 82 degrees south latitude. These data products were generated from a portion of the imagery acquired during Terra orbit 14669. The panels cover an area of about 380 kilometers x 704 kilometers, and utilize data from blocks 70 to 79within World Reference System-2 path 17.

MISR was built and is managed by NASA's Jet Propulsion Laboratory, Pasadena, CA, for NASA's Office of Earth Science, Washington, DC. The Terra satellite is managed by NASA's Goddard Space Flight Center, Greenbelt, MD. JPL is a division of the California Institute of Technology.

3D Cloud Radiative Effects on Aerosol Optical Thickness Retrievals in Cumulus Cloud Fields in the Biomass Burning Region in Brazil

NASA Technical Reports Server (NTRS)

Wen, Guo-Yong; Marshak, Alexander; Cahalan, Robert F.

2004-01-01

Aerosol amount in clear regions of a cloudy atmosphere is a critical parameter in studying the interaction between aerosols and clouds. Since the global cloud cover is about 50%, cloudy scenes are often encountered in any satellite images. Aerosols are more or less transparent, while clouds are extremely reflective in the visible spectrum of solar radiation. The radiative transfer in clear-cloudy condition is highly three- dimensional (3D). This paper focuses on estimating the 3D effects on aerosol optical thickness retrievals using Monte Carlo simulations. An ASTER image of cumulus cloud fields in the biomass burning region in Brazil is simulated in this study. The MODIS products (i-e., cloud optical thickness, particle effective radius, cloud top pressure, surface reflectance, etc.) are used to construct the cloud property and surface reflectance fields. To estimate the cloud 3-D effects, we assume a plane-parallel stratification of aerosol properties in the 60 km x 60 km ASTER image. The simulated solar radiation at the top of the atmosphere is compared with plane-parallel calculations. Furthermore, the 3D cloud radiative effects on aerosol optical thickness retrieval are estimated.

Validating MODIS above-cloud aerosol optical depth retrieved from "color ratio" algorithm using direct measurements made by NASA's airborne AATS and 4STAR sensors

NASA Astrophysics Data System (ADS)

Jethva, Hiren; Torres, Omar; Remer, Lorraine; Redemann, Jens; Livingston, John; Dunagan, Stephen; Shinozuka, Yohei; Kacenelenbogen, Meloe; Segal Rosenheimer, Michal; Spurr, Rob

2016-10-01

We present the validation analysis of above-cloud aerosol optical depth (ACAOD) retrieved from the "color ratio" method applied to MODIS cloudy-sky reflectance measurements using the limited direct measurements made by NASA's airborne Ames Airborne Tracking Sunphotometer (AATS) and Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research (4STAR) sensors. A thorough search of the airborne database collection revealed a total of five significant events in which an airborne sun photometer, coincident with the MODIS overpass, observed partially absorbing aerosols emitted from agricultural biomass burning, dust, and wildfires over a low-level cloud deck during SAFARI-2000, ACE-ASIA 2001, and SEAC4RS 2013 campaigns, respectively. The co-located satellite-airborne matchups revealed a good agreement (root-mean-square difference < 0.1), with most matchups falling within the estimated uncertainties associated the MODIS retrievals (about -10 to +50 %). The co-retrieved cloud optical depth was comparable to that of the MODIS operational cloud product for ACE-ASIA and SEAC4RS, however, higher by 30-50 % for the SAFARI-2000 case study. The reason for this discrepancy could be attributed to the distinct aerosol optical properties encountered during respective campaigns. A brief discussion on the sources of uncertainty in the satellite-based ACAOD retrieval and co-location procedure is presented. Field experiments dedicated to making direct measurements of aerosols above cloud are needed for the extensive validation of satellite-based retrievals.

Validating MODIS Above-Cloud Aerosol Optical Depth Retrieved from Color Ratio Algorithm Using Direct Measurements Made by NASA's Airborne AATS and 4STAR Sensors

NASA Technical Reports Server (NTRS)

Jethva, Hiren; Torres, Omar; Remer, Lorraine; Redemann, Jens; Livingston, John; Dunagan, Stephen; Shinozuka, Yohei; Kacenelenbogen, Meloe; Segal Rozenhaimer, Michal; Spurr, Rob

2016-01-01

We present the validation analysis of above-cloud aerosol optical depth (ACAOD) retrieved from the color ratio method applied to MODIS cloudy-sky reflectance measurements using the limited direct measurements made by NASAs airborne Ames Airborne Tracking Sunphotometer (AATS) and Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research (4STAR) sensors. A thorough search of the airborne database collection revealed a total of five significant events in which an airborne sun photometer, coincident with the MODIS overpass, observed partially absorbing aerosols emitted from agricultural biomass burning, dust, and wildfires over a low-level cloud deck during SAFARI-2000, ACE-ASIA 2001, and SEAC4RS 2013 campaigns, respectively. The co-located satellite-airborne match ups revealed a good agreement (root-mean-square difference less than 0.1), with most match ups falling within the estimated uncertainties associated with the MODIS retrievals (about -10 to +50 ). The co-retrieved cloud optical depth was comparable to that of the MODIS operational cloud product for ACE-ASIA and SEAC4RS, however, higher by 30-50% for the SAFARI-2000 case study. The reason for this discrepancy could be attributed to the distinct aerosol optical properties encountered during respective campaigns. A brief discussion on the sources of uncertainty in the satellite-based ACAOD retrieval and co-location procedure is presented. Field experiments dedicated to making direct measurements of aerosols above cloud are needed for the extensive validation of satellite based retrievals.

Retrievals with the Infrared Atmospheric Sounding Interferometer

NASA Technical Reports Server (NTRS)

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

2007-01-01

The Infrared Atmospheric Sounding Interferometer (IASI) on the MetOp satellite was launched on October 19, 2006. 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. Ultraspectral 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. Preliminary retrievals of atmospheric soundings, surface properties, and cloud optical/microphysical properties with the IASI observations during the JAIVEx are obtained and presented. These retrievals are 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.

Supervised machine learning for analysing spectra of exoplanetary atmospheres

NASA Astrophysics Data System (ADS)

Márquez-Neila, Pablo; Fisher, Chloe; Sznitman, Raphael; Heng, Kevin

2018-06-01

The use of machine learning is becoming ubiquitous in astronomy1-3, but remains rare in the study of the atmospheres of exoplanets. Given the spectrum of an exoplanetary atmosphere, a multi-parameter space is swept through in real time to find the best-fit model4-6. Known as atmospheric retrieval, this technique originates in the Earth and planetary sciences7. Such methods are very time-consuming, and by necessity there is a compromise between physical and chemical realism and computational feasibility. Machine learning has previously been used to determine which molecules to include in the model, but the retrieval itself was still performed using standard methods8. Here, we report an adaptation of the `random forest' method of supervised machine learning9,10, trained on a precomputed grid of atmospheric models, which retrieves full posterior distributions of the abundances of molecules and the cloud opacity. The use of a precomputed grid allows a large part of the computational burden to be shifted offline. We demonstrate our technique on a transmission spectrum of the hot gas-giant exoplanet WASP-12b using a five-parameter model (temperature, a constant cloud opacity and the volume mixing ratios or relative abundances of molecules of water, ammonia and hydrogen cyanide)11. We obtain results consistent with the standard nested-sampling retrieval method. We also estimate the sensitivity of the measured spectrum to the model parameters, and we are able to quantify the information content of the spectrum. Our method can be straightforwardly applied using more sophisticated atmospheric models to interpret an ensemble of spectra without having to retrain the random forest.

Single-footprint retrievals for AIRS using a fast TwoSlab cloud-representation model and the SARTA all-sky infrared radiative transfer algorithm

NASA Astrophysics Data System (ADS)

DeSouza-Machado, Sergio; Larrabee Strow, L.; Tangborn, Andrew; Huang, Xianglei; Chen, Xiuhong; Liu, Xu; Wu, Wan; Yang, Qiguang

2018-01-01

One-dimensional variational retrievals of temperature and moisture fields from hyperspectral infrared (IR) satellite sounders use cloud-cleared radiances (CCRs) as their observation. These derived observations allow the use of clear-sky-only radiative transfer in the inversion for geophysical variables but at reduced spatial resolution compared to the native sounder observations. Cloud clearing can introduce various errors, although scenes with large errors can be identified and ignored. Information content studies show that, when using multilayer cloud liquid and ice profiles in infrared hyperspectral radiative transfer codes, there are typically only 2-4 degrees of freedom (DOFs) of cloud signal. This implies a simplified cloud representation is sufficient for some applications which need accurate radiative transfer. Here we describe a single-footprint retrieval approach for clear and cloudy conditions, which uses the thermodynamic and cloud fields from numerical weather prediction (NWP) models as a first guess, together with a simple cloud-representation model coupled to a fast scattering radiative transfer algorithm (RTA). The NWP model thermodynamic and cloud profiles are first co-located to the observations, after which the N-level cloud profiles are converted to two slab clouds (TwoSlab; typically one for ice and one for water clouds). From these, one run of our fast cloud-representation model allows an improvement of the a priori cloud state by comparing the observed and model-simulated radiances in the thermal window channels. The retrieval yield is over 90 %, while the degrees of freedom correlate with the observed window channel brightness temperature (BT) which itself depends on the cloud optical depth. The cloud-representation and scattering package is benchmarked against radiances computed using a maximum random overlap (RMO) cloud scheme. All-sky infrared radiances measured by NASA's Atmospheric Infrared Sounder (AIRS) and NWP thermodynamic and cloud profiles from the European Centre for Medium-Range Weather Forecasts (ECMWF) forecast model are used in this paper.

Apperception of Clouds in AIRS Data

NASA Technical Reports Server (NTRS)

Huang, Hung-Lung; Smith, William L.

2005-01-01

Our capacity to simulate the radiative characteristics of the Earth system has advanced greatly over the past decade. However, new space based measurements show that idealized simulations might not adequately represent the complexity of nature. For example, AIRS simulated multi-layer cloud clearing research provides an excellent groundwork for early Atmospheric Infra-Red Sounder (AIRS) operational cloud clearing and atmospheric profile retrieval. However, it doesn't reflect the complicated reality of clouds over land and coastal areas. Thus far, operational AIRS/AMSU (Advanced Microwave Sounding Unit) cloud clearing is not only of low yield but also of unsatisfying quality. This is not an argument for avoiding this challenging task, rather a powerful argument for exploring other synergistic approaches, and for adapting these strategies toward improving both indirect and direct use of cloudy infrared sounding data. Ample evidence is shown in this paper that the indirect use of cloudy sounding data by way of cloud clearing is sub-optimal for data assimilation. Improvements are needed in quality control, retrieval yield, and overall cloud clearing retrieval performance. For example, cloud clearing over land, especially over the desert surface, has led to much degraded retrieval quality and often a very low yield of quality controlled cloud cleared radiances. If these indirect cloud cleared radiances are instead to be directly assimilated into NWP models, great caution must be used. Our limited and preliminary cloud clearing results from AIRS/AMSU (with the use of MODIS data) and an AIRS/MODIS synergistic approach have, however, shown that higher spatial resolution multispectral imagery data can provide much needed quality control of the AIRS/AMSU cloud clearing retrieval. When AIRS and Moderate Resolution Imaging Spectroradiometer (MODIS) are used synergistically, a higher spatial resolution over difficult terrain (especially desert areas) can be achieved and with a much improved accuracy. Preliminary statistical analyses of cloud cleared radiances derived from (1) operational AIRS/AMSU, (2) operational AIRS/AMSU plus the use of MODIS data as quality control, and (3) AIRS/MODIS synergistic single channel and two field of views cloud clearing are Our capacity to simulate the radiative characteristics of the Earth system has

Extending 'Deep Blue' aerosol retrieval coverage to cases of absorbing aerosols above clouds: sensitivity analysis and first case studies

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

Sayer, Andrew M.; Hsu, C.; Bettenhausen, Corey

Cases of absorbing aerosols above clouds (AAC), such as smoke or mineral dust, are omitted from most routinely-processed space-based aerosol optical depth (AOD) data products, including those from the Moderate Resolution Imaging Spectroradiometer (MODIS). This study presents a sensitivity analysis and preliminary algorithm to retrieve above-cloud AOD and liquid cloud optical depth (COD) for AAC cases from MODIS or similar

A New Understanding for the Rain Rate retrieval of Attenuating Radars Measurement

NASA Astrophysics Data System (ADS)

Koner, P.; Battaglia, A.; Simmer, C.

2009-04-01

The retrieval of rain rate from the attenuated radar (e.g. Cloud Profiling Radar on board of CloudSAT in orbit since June 2006) is a challenging problem. ĹEcuyer and Stephens [1] underlined this difficulty (for rain rates larger than 1.5 mm/h) and suggested the need of additional information (like path-integrated attenuations (PIA) derived from surface reference techniques or precipitation water path estimated from co-located passive microwave radiometer) to constrain the retrieval. It is generally discussed based on the optimal estimation theory that there are no solutions without constraining the problem in a case of visible attenuation because there is no enough information content to solve the problem. However, when the problem is constrained by the additional measurement of PIA, there is a reasonable solution. This raises the spontaneous question: Is all information enclosed in this additional measurement? This also contradicts with the information theory because one measurement can introduce only one degree of freedom in the retrieval. Why is one degree of freedom so important in the above problem? This question cannot be explained using the estimation and information theories of OEM. On the other hand, Koner and Drummond [2] argued that the OEM is basically a regularization method, where a-priori covariance is used as a stabilizer and the regularization strength is determined by the choices of the a-priori and error covariance matrices. The regularization is required for the reduction of the condition number of Jacobian, which drives the noise injection from the measurement and inversion spaces to the state space in an ill-posed inversion. In this work, the above mentioned question will be discussed based on the regularization theory, error mitigation and eigenvalue mathematics. References 1. L'Ecuyer TS and Stephens G. An estimation based precipitation retrieval algorithm for attenuating radar. J. Appl. Met., 2002, 41, 272-85. 2. Koner PK, Drummond JR. A comparison of regularization techniques for atmospheric trace gases retrievals. JQSRT 2008; 109:514-26.

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

Riihimaki, L.; McFarlane, S.; Sivaraman, C.

The ndrop_mfrsr value-added product (VAP) provides an estimate of the cloud droplet number concentration of overcast water clouds retrieved from cloud optical depth from the multi-filter rotating shadowband radiometer (MFRSR) instrument and liquid water path (LWP) retrieved from the microwave radiometer (MWR). When cloud layer information is available from vertically pointing lidar and radars in the Active Remote Sensing of Clouds (ARSCL) product, the VAP also provides estimates of the adiabatic LWP and an adiabatic parameter (beta) that indicates how divergent the LWP is from the adiabatic case. quality control (QC) flags (qc_drop_number_conc), an uncertainty estimate (drop_number_conc_toterr), and a cloudmore » layer type flag (cloud_base_type) are useful indicators of the quality and accuracy of any given value of the retrieval. Examples of these major input and output variables are given in sample plots in section 6.0.« less

Near-Real Time Cloud Retrievals from Operational and Research Meteorological Satellites

NASA Technical Reports Server (NTRS)

Minnis, Patrick; Nguyen, Louis; Palilonda, Rabindra; Heck, Patrick W.; Spangenberg, Douglas A.; Doelling, David R.; Ayers, J. Kirk; Smith, William L., Jr.; Khaiyer, Mandana M.; Trepte, Qing Z.;

The Radiative Consistency of Atmospheric Infrared Sounder and Moderate Resolution Imaging Spectroradiometer Cloud Retrievals

NASA Technical Reports Server (NTRS)

Kahn, Brian H.; Fishbein, Evan; Nasiri, Shaima L.; Eldering, Annmarie; Fetzer, Eric J.; Garay, Michael J.; Lee, Sung-Yung

2007-01-01

The consistency of cloud top temperature (Tc) and effective cloud fraction (f) retrieved by the Atmospheric Infrared Sounder (AIRS)/Advanced Microwave Sounding Unit (AMSU) observation suite and the Moderate Resolution Imaging Spectroradiometer (MODIS) on the EOS-Aqua platform are investigated. Collocated AIRS and MODIS TC and f are compared via an 'effective scene brightness temperature' (Tb,e). Tb,e is calculated with partial field of view (FOV) contributions from TC and surface temperature (TS), weighted by f and 1-f, respectively. AIRS reports up to two cloud layers while MODIS reports up to one. However, MODIS reports TC, TS, and f at a higher spatial resolution than AIRS. As a result, pixel-scale comparisons of TC and f are difficult to interpret, demonstrating the need for alternatives such as Tb,e. AIRS-MODIS Tb,e differences ((Delta)Tb,e) for identical observing scenes are useful as a diagnostic for cloud quantity comparisons. The smallest values of DTb,e are for high and opaque clouds, with increasing scatter in (Delta)Tb,e for clouds of smaller opacity and lower altitude. A persistent positive bias in DTb,e is observed in warmer and low-latitude scenes, characterized by a mixture of MODIS CO2 slicing and 11-mm window retrievals. These scenes contain heterogeneous cloud cover, including mixtures of multilayered cloudiness and misplaced MODIS cloud top pressure. The spatial patterns of (Delta)Tb,e are systematic and do not correlate well with collocated AIRS-MODIS radiance differences, which are more random in nature and smaller in magnitude than (Delta)Tb,e. This suggests that the observed inconsistencies in AIRS and MODIS cloud fields are dominated by retrieval algorithm differences, instead of differences in the observed radiances. The results presented here have implications for the validation of cloudy satellite retrieval algorithms, and use of cloud products in quantitative analyses.

Operational Estimation of Accumulated Precipitation using Satellite Observation, by Eumetsat Satellite Application facility in Support to Hydrology (H-SAF Consortium).

NASA Astrophysics Data System (ADS)

di Diodato, A.; de Leonibus, L.; Zauli, F.; Biron, D.; Melfi, D.

2009-04-01

Operational Estimation of Accumulated Precipitation using Satellite Observation, by Eumetsat Satellite Application facility in Support to Hydrology (H-SAF Consortium). Cap. Attilio DI DIODATO(*), T.Col. Luigi DE LEONIBUS(*), T.Col Francesco ZAULI(*), Cap. Daniele BIRON(*), Ten. Davide Melfi(*) Satellite Application Facilities (SAFs) are specialised development and processing centres of the EUMETSAT Distributed Ground Segment. SAFs process level 1b data from meteorological satellites (geostationary and polar ones) in conjunction with all other relevant sources of data and appropriate models to generate services and level 2 products. Each SAF is a consortium of EUMETSAT European partners lead by a host institute responsible for the management of the complete SAF project. The Meteorological Service of Italian Air Force is the host Institute for the Satellite Application Facility on Support to Operational Hydrology and Water Management (H-SAF). HSAF has the commitment to develop and to provide, operationally after 2010, products regarding precipitation, soil moisture and snow. HSAF is going to provide information on error structure of its products and validation of the products via their impacts into Hydrological models. To that purpose it has been structured a specific subgroups. Accumulated precipitation is computed by temporal integration of the instantaneous rain rate achieved by the blended LEO/MW and GEO/IR precipitation rate products generated by Rapid Update method available every 15 minutes. The algorithm provides four outputs, consisting in accumulated precipitation in 3, 6, 12 and 24 hours, delivered every 3 hours at the synoptic hours. These outputs are our precipitation background fields. Satellite estimates can cover most of the globe, however, they suffer from errors due to lack of a direct relationship between observation parameters and precipitation, the poor sampling and algorithm imperfections. For this reason the 3 hours accumulated precipitation is compared by climatic thresholds got, basically, by the project "Climate Atlas of Europe" led by Meteo France inside the project ECSN (European Climate Support Network) of EUMETNET. To reduce the bias errors introduced by satellite estimates the rain gauge data are used to make an intercalibration with the satellite estimates, using information achieved by GTS network. Precipitation increments are estimated at each observation location from the observation and the interpolated background field. A field of the increments is carried out by standard Kriging method. The final precipitation analysis is achieved by the sum of the increments and the precipitation estimation at each grid points. It is also considered that major error sources in retrieval 15 minutes instantaneous precipitation from cloud top temperature comes from high (cold) non precipitating clouds and the use of same regression coefficients both for warm clouds (stratus) and cold clouds (convective). As that error is intrinsic in the blending technique applied, we are going to improve performances making use of cloud type specified retrievals. To apply such scheme on the products, we apply a discrimination from convective and stratified clouds, then we retrieve precipitation in parallel for the two clouds classes; the two outputs are merged again into one products, solving the double retrieval pixels keeping the convection retrieval. Basic tools for that is the computation of two different lookup tables to associate precipitation at a brightness temperature for the two kinds of cloudiness. The clouds discrimination will be done by the NWC-SAF product named "cloud type" for the stratified clouds and with an application, running operationally at Italian Met Service, named NEFODINA for automatic detection of convective phenomena. Results of studies to improve the accumulated precipitation as well are presented. The studies exploit the potential to use other source of information like quantitative precipitation forecast (QPF) got by numerical weather prediction model to improve the algorithm where the density of ground observations is low, or using it as a background field to generate a precipitation analysis by an optimal interpolation technique. (*) Centro Nazionale Meteorologia e Climatologia Aeronautica - CNMCA

Ice Cloud Optical Thickness and Extinction Estimates from Radar Measurements.

NASA Astrophysics Data System (ADS)

Matrosov, Sergey Y.; Shupe, Matthew D.; Heymsfield, Andrew J.; Zuidema, Paquita

2003-11-01

A remote sensing method is proposed to derive vertical profiles of the visible extinction coefficients in ice clouds from measurements of the radar reflectivity and Doppler velocity taken by a vertically pointing 35-GHz cloud radar. The extinction coefficient and its vertical integral, optical thickness τ, are among the fundamental cloud optical parameters that, to a large extent, determine the radiative impact of clouds. The results obtained with this method could be used as input for different climate and radiation models and for comparisons with parameterizations that relate cloud microphysical parameters and optical properties. An important advantage of the proposed method is its potential applicability to multicloud situations and mixed-phase conditions. In the latter case, it might be able to provide the information on the ice component of mixed-phase clouds if the radar moments are dominated by this component. The uncertainties of radar-based retrievals of cloud visible optical thickness are estimated by comparing retrieval results with optical thicknesses obtained independently from radiometric measurements during the yearlong Surface Heat Budget of the Arctic Ocean (SHEBA) field experiment. The radiometric measurements provide a robust way to estimate τ but are applicable only to optically thin ice clouds without intervening liquid layers. The comparisons of cloud optical thicknesses retrieved from radar and from radiometer measurements indicate an uncertainty of about 77% and a bias of about -14% in the radar estimates of τ relative to radiometric retrievals. One possible explanation of the negative bias is an inherently low sensitivity of radar measurements to smaller cloud particles that still contribute noticeably to the cloud extinction. This estimate of the uncertainty is in line with simple theoretical considerations, and the associated retrieval accuracy should be considered good for a nonoptical instrument, such as radar. This paper also presents relations between radar-derived characteristic cloud particle sizes and effective sizes used in models. An average relation among τ, cloud ice water path, and the layer mean value of cloud particle characteristic size is also given. This relation is found to be in good agreement with in situ measurements. Despite a high uncertainty of radar estimates of extinction, this method is useful for many clouds where optical measurements are not available because of cloud multilayering or opaqueness.

Information content of thermal infrared a microwave bands for simultaneous retrieval of cirrus ice water path and particle effective diameter

NASA Astrophysics Data System (ADS)

Bell, A.; Tang, G.; Yang, P.; Wu, D.

2017-12-01

Due to their high spatial and temporal coverage, cirrus clouds have a profound role in regulating the Earth's energy budget. Variability of their radiative, geometric, and microphysical properties can pose significant uncertainties in global climate model simulations if not adequately constrained. Thus, the development of retrieval methodologies able to accurately retrieve ice cloud properties and present associated uncertainties is essential. The effectiveness of cirrus cloud retrievals relies on accurate a priori understanding of ice radiative properties, as well as the current state of the atmosphere. Current studies have implemented information content theory analyses prior to retrievals to quantify the amount of information that should be expected on parameters to be retrieved, as well as the relative contribution of information provided by certain measurement channels. Through this analysis, retrieval algorithms can be designed in a way to maximize the information in measurements, and therefore ensure enough information is present to retrieve ice cloud properties. In this study, we present such an information content analysis to quantify the amount of information to be expected in retrievals of cirrus ice water path and particle effective diameter using sub-millimeter and thermal infrared radiometry. Preliminary results show these bands to be sensitive to changes in ice water path and effective diameter, and thus lend confidence their ability to simultaneously retrieve these parameters. Further quantification of sensitivity and the information provided from these bands can then be used to design and optimal retrieval scheme. While this information content analysis is employed on a theoretical retrieval combining simulated radiance measurements, the methodology could in general be applicable to any instrument or retrieval approach.

Accuracy Assessments of Cloud Droplet Size Retrievals from Polarized Reflectance Measurements by the Research Scanning Polarimeter

NASA Technical Reports Server (NTRS)

Alexandrov, Mikhail Dmitrievic; Cairns, Brian; Emde, Claudia; Ackerman, Andrew S.; vanDiedenhove, Bastiaan

2012-01-01

We present an algorithm for the retrieval of cloud droplet size distribution parameters (effective radius and variance) from the Research Scanning Polarimeter (RSP) measurements. The RSP is an airborne prototype for the Aerosol Polarimetery Sensor (APS), which was on-board of the NASA Glory satellite. This instrument measures both polarized and total reflectance in 9 spectral channels with central wavelengths ranging from 410 to 2260 nm. The cloud droplet size retrievals use the polarized reflectance in the scattering angle range between 135deg and 165deg, where they exhibit the sharply defined structure known as the rain- or cloud-bow. The shape of the rainbow is determined mainly by the single scattering properties of cloud particles. This significantly simplifies both forward modeling and inversions, while also substantially reducing uncertainties caused by the aerosol loading and possible presence of undetected clouds nearby. In this study we present the accuracy evaluation of our algorithm based on the results of sensitivity tests performed using realistic simulated cloud radiation fields.

Comparison of Marine Boundary Layer Cloud Properties from CERES-MODIS Edition 4 and DOE ARM AMF Measurements at the Azores

NASA Technical Reports Server (NTRS)

Xi, Baike; Dong, Xiquan; Minnis, Patrick; Sun-Mack, Sunny

2014-01-01

Marine boundary layer (MBL) cloud properties derived from the NASA Clouds and the Earth's Radiant Energy System (CERES) project using Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) data are compared with observations taken at the Department of Energy Atmospheric Radiation Measurement (ARM) Mobile Facility at the Azores (AMF-Azores) site from June 2009 through December 2010. Cloud properties derived from ARM ground-based observations were averaged over a 1 h interval centered at the satellite overpass time, while the CERES-MODIS (CM) results were averaged within a 30 km×30 km grid box centered over the Azores site. A total of 63 daytime and 92 nighttime single-layered overcast MBL cloud cases were selected from 19 months of ARM radar-lidar and satellite observations. The CM cloud top/base heights (Htop/Hbase) were determined from cloud top/base temperatures (Ttop/Tbase) using a regional boundary layer lapse rate method. For daytime comparisons, the CM-derived Htop (Hbase), on average, is 0.063 km (0.068 km) higher (lower) than its ARM radar-lidar-observed counterpart, and the CM-derived Ttop and Tbase are 0.9 K less and 2.5 K greater than the surface values with high correlations (R(sup 2) = 0.82 and 0.84, respectively). In general, the cloud top comparisons agree better than the cloud base comparisons, because the CM cloud base temperatures and heights are secondary products determined from cloud top temperatures and heights. No significant day-night difference was found in the analyses. The comparisons of MBL cloud microphysical properties reveal that when averaged over a 30 km× 30 km area, the CM-retrieved cloud droplet effective radius (re) at 3.7 micrometers is 1.3 micrometers larger than that from the ARM retrievals (12.8 micrometers), while the CM-retrieved cloud liquid water path (LWP) is 13.5 gm( exp -2) less than its ARM counterpart (114.2 gm( exp-2) due to its small optical depth (9.6 versus 13.7). The differences are reduced by 50% when the CM averages are computed only using the MODIS pixel nearest the AMF site. Using the effective radius retrieved using 2.1 micrometers channel to calculate LWP can reduce the difference between the CM and ARM microwave radiometer retrievals from 13.7 to 2.1 gm2. The 10% differences between the ARM and CERES-MODIS LWP and r(sub e) retrievals are within the uncertainties of the ARM LWP (approximately 20gm( exp -2)) and r(sub e) (approximately 10%) retrievals; however, the 30% difference in optical depth is significant. Possible reasons contributing to this discrepancy are increased sensitivities in optical depth from both surface retrievals when t is approximately 10 and topography. The t differences vary with wind direction and are consistent with the island orography.Much better agreement in t is obtained when using only those data taken when the wind is from the northeast, where topographical effects on the sampled clouds are minimal.

Comparison of marine boundary layer cloud properties from CERES-MODIS Edition 4 and DOE ARM AMF measurements at the Azores

NASA Astrophysics Data System (ADS)

Xi, Baike; Dong, Xiquan; Minnis, Patrick; Sun-Mack, Sunny

2014-08-01

Marine boundary layer (MBL) cloud properties derived from the NASA Clouds and the Earth's Radiant Energy System (CERES) project using Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) data are compared with observations taken at the Department of Energy Atmospheric Radiation Measurement (ARM) Mobile Facility at the Azores (AMF-Azores) site from June 2009 through December 2010. Cloud properties derived from ARM ground-based observations were averaged over a 1 h interval centered at the satellite overpass time, while the CERES-MODIS (CM) results were averaged within a 30 km × 30 km grid box centered over the Azores site. A total of 63 daytime and 92 nighttime single-layered overcast MBL cloud cases were selected from 19 months of ARM radar-lidar and satellite observations. The CM cloud top/base heights (Htop/Hbase) were determined from cloud top/base temperatures (Ttop/Tbase) using a regional boundary layer lapse rate method. For daytime comparisons, the CM-derived Htop (Hbase), on average, is 0.063 km (0.068 km) higher (lower) than its ARM radar-lidar-observed counterpart, and the CM-derived Ttop and Tbase are 0.9 K less and 2.5 K greater than the surface values with high correlations (R2 = 0.82 and 0.84, respectively). In general, the cloud top comparisons agree better than the cloud base comparisons, because the CM cloud base temperatures and heights are secondary products determined from cloud top temperatures and heights. No significant day-night difference was found in the analyses. The comparisons of MBL cloud microphysical properties reveal that when averaged over a 30 km × 30 km area, the CM-retrieved cloud droplet effective radius (re) at 3.7 µm is 1.3 µm larger than that from the ARM retrievals (12.8 µm), while the CM-retrieved cloud liquid water path (LWP) is 13.5 gm-2 less than its ARM counterpart (114.2 gm-2) due to its small optical depth (9.6 versus 13.7). The differences are reduced by 50% when the CM averages are computed only using the MODIS pixel nearest the AMF site. Using the effective radius retrieved using 2.1 µm channel to calculate LWP can reduce the difference between the CM and ARM microwave radiometer retrievals from -13.7 to 2.1 gm-2. The 10% differences between the ARM and CERES-MODIS LWP and re retrievals are within the uncertainties of the ARM LWP ( 20 gm-2) and re ( 10%) retrievals; however, the 30% difference in optical depth is significant. Possible reasons contributing to this discrepancy are increased sensitivities in optical depth from both surface retrievals when τ 10 and topography. The τ differences vary with wind direction and are consistent with the island orography. Much better agreement in τ is obtained when using only those data taken when the wind is from the northeast, where topographical effects on the sampled clouds are minimal.

Determination of Ice Cloud Models Using MODIS and MISR Data

NASA Technical Reports Server (NTRS)

Xie, Yu; Yang, Ping; Kattawar, George W.; Minnis, Patrick; Hu, Yongxiang; Wu, Dong L.

2012-01-01

Representation of ice clouds in radiative transfer simulations is subject to uncertainties associated with the shapes and sizes of ice crystals within cirrus clouds. In this study, we examined several ice cloud models consisting of smooth, roughened, homogeneous and inhomogeneous hexagonal ice crystals with various aspect ratios. The sensitivity of the bulk scattering properties and solar reflectances of cirrus clouds to specific ice cloud models is investigated using the improved geometric optics method (IGOM) and the discrete ordinates radiative transfer (DISORT) model. The ice crystal habit fractions in the ice cloud model may significantly affect the simulations of cloud reflectances. A new algorithm was developed to help determine an appropriate ice cloud model for application to the satellite-based retrieval of ice cloud properties. The ice cloud particle size retrieved from Moderate Resolution Imaging Spectroradiometer (MODIS) data, collocated with Multi-angle Imaging Spectroradiometer (MISR) observations, is used to infer the optical thicknesses of ice clouds for nine MISR viewing angles. The relative differences between view-dependent cloud optical thickness and the averaged value over the nine MISR viewing angles can vary from -0.5 to 0.5 and are used to evaluate the ice cloud models. In the case for 2 July 2009, the ice cloud model with mixed ice crystal habits is the best fit to the observations (the root mean square (RMS) error of cloud optical thickness reaches 0.365). This ice cloud model also produces consistent cloud property retrievals for the nine MISR viewing configurations within the measurement uncertainties.

Validating Above-cloud Aerosol Optical Depth Retrieved from MODIS using NASA Ames Airborne Sun-Tracking Photometric and Spectrometric (AATS and 4STAR) Measurements

NASA Astrophysics Data System (ADS)

Jethva, H. T.; Torres, O.; Remer, L. A.; Redemann, J.; Dunagan, S. E.; Livingston, J. M.; Shinozuka, Y.; Kacenelenbogen, M. S.; Segal-Rosenhaimer, M.

2014-12-01

Absorbing aerosols produced from biomass burning and dust outbreaks are often found to overlay the lower level cloud decks as evident in the satellite images. In contrast to the cloud-free atmosphere, in which aerosols generally tend to cool the atmosphere, the presence of absorbing aerosols above cloud poses greater potential of exerting positive radiative effects (warming) whose magnitude directly depends on the aerosol loading above cloud, optical properties of clouds and aerosols, and cloud fraction. In recent years, development of algorithms that exploit satellite-based passive measurements of ultraviolet (UV), visible, and polarized light as well as lidar-based active measurements constitute a major breakthrough in the field of remote sensing of aerosols. While the unprecedented quantitative information on aerosol loading above cloud is now available from NASA's A-train sensors, a greater question remains ahead: How to validate the satellite retrievals of above-cloud aerosols (ACA)? Direct measurements of ACA such as carried out by the NASA Ames Airborne Tracking Sunphotometer (AATS) and Spectrometer for Sky-Scanning, Sun-Tracking Atmospheric Research (4STAR) can be of immense help in validating ACA retrievals. In this study, we validate the ACA optical depth retrieved using the 'color ratio' (CR) method applied to the MODIS cloudy-sky reflectance by using the airborne AATS and 4STAR measurements. A thorough search of the historic AATS-4STAR database collected during different field campaigns revealed five events where biomass burning, dust, and wildfire-emitted aerosols were found to overlay lower level cloud decks observed during SAFARI-2000, ACE-ASIA 2001, and SEAC4RS-2013, respectively. The co-located satellite-airborne measurements revealed a good agreement (root-mean-square-error<0.1 for Aerosol Optical Depth (AOD) at 500 nm) with most matchups falling within the estimated uncertainties in the MODIS retrievals (-10% to +50%). An extensive validation of satellite-based ACA retrievals requires equivalent field measurements particularly over the regions where ACA are often observed from satellites, i.e., south-eastern Atlantic Ocean, tropical Atlantic Ocean, northern Arabian Sea, South-East and North-East Asia.

Potential of Higher Moments of the Radar Doppler Spectrum for Studying Ice Clouds

NASA Astrophysics Data System (ADS)

Loehnert, U.; Maahn, M.

2015-12-01

More observations of ice clouds are required to fill gaps in understanding of microphysical properties and processes. However, in situ observations by aircraft are costly and cannot provide long term observations which are required for a deeper understanding of the processes. Ground based remote sensing observations have the potential to fill this gap, but their observations do not contain sufficient information to unambiguously constrain ice cloud properties which leads to high uncertainties. For vertically pointing cloud radars, usually only reflectivity and mean Doppler velocity are used for retrievals; some studies proposed also the use of Doppler spectrum width.In this study, it is investigated whether additional information can be obtained by exploiting also higher moments of the Doppler spectrum such as skewness and kurtosis together with the slope of the Doppler peak. For this, observations of pure ice clouds from the Indirect and Semi-Direct Aerosol Campaign (ISDAC) in Alaska 2008 are analyzed. Using the ISDAC data set, an Optimal Estimation based retrieval is set up based on synthetic and real radar observations. The passive and active microwave radiative transfer model (PAMTRA) is used as a forward model together with the Self-Similar Rayleigh-Gans approximation for estimation of the scattering properties. The state vector of the retrieval consists of the parameters required to simulate the radar Doppler spectrum and describes particle mass, cross section area, particle size distribution, and kinematic conditions such as turbulence and vertical air motion. Using the retrieval, the information content (degrees of freedom for signal) is quantified that higher moments and slopes can contribute to an ice cloud retrieval. The impact of multiple frequencies, radar sensitivity and radar calibration is studied. For example, it is found that a single-frequency measurement using all moments and slopes contains already more information content than a dual-frequency measurement using only reflectivity and mean Doppler velocity. Eventually, the errors and uncertainties of the retrieved ice cloud parameters are investigated for the various retrieval configurations.

Potential of Higher Moments of the Radar Doppler Spectrum for Studying Ice Clouds

NASA Astrophysics Data System (ADS)

Lunt, M. F.; Rigby, M. L.; Ganesan, A.; Manning, A.; O'Doherty, S.; Prinn, R. G.; Saito, T.; Harth, C. M.; Muhle, J.; Weiss, R. F.; Salameh, P.; Arnold, T.; Yokouchi, Y.; Krummel, P. B.; Steele, P.; Fraser, P. J.; Li, S.; Park, S.; Kim, J.; Reimann, S.; Vollmer, M. K.; Lunder, C. R.; Hermansen, O.; Schmidbauer, N.; Young, D.; Simmonds, P. G.

2014-12-01

More observations of ice clouds are required to fill gaps in understanding of microphysical properties and processes. However, in situ observations by aircraft are costly and cannot provide long term observations which are required for a deeper understanding of the processes. Ground based remote sensing observations have the potential to fill this gap, but their observations do not contain sufficient information to unambiguously constrain ice cloud properties which leads to high uncertainties. For vertically pointing cloud radars, usually only reflectivity and mean Doppler velocity are used for retrievals; some studies proposed also the use of Doppler spectrum width.In this study, it is investigated whether additional information can be obtained by exploiting also higher moments of the Doppler spectrum such as skewness and kurtosis together with the slope of the Doppler peak. For this, observations of pure ice clouds from the Indirect and Semi-Direct Aerosol Campaign (ISDAC) in Alaska 2008 are analyzed. Using the ISDAC data set, an Optimal Estimation based retrieval is set up based on synthetic and real radar observations. The passive and active microwave radiative transfer model (PAMTRA) is used as a forward model together with the Self-Similar Rayleigh-Gans approximation for estimation of the scattering properties. The state vector of the retrieval consists of the parameters required to simulate the radar Doppler spectrum and describes particle mass, cross section area, particle size distribution, and kinematic conditions such as turbulence and vertical air motion. Using the retrieval, the information content (degrees of freedom for signal) is quantified that higher moments and slopes can contribute to an ice cloud retrieval. The impact of multiple frequencies, radar sensitivity and radar calibration is studied. For example, it is found that a single-frequency measurement using all moments and slopes contains already more information content than a dual-frequency measurement using only reflectivity and mean Doppler velocity. Eventually, the errors and uncertainties of the retrieved ice cloud parameters are investigated for the various retrieval configurations.

Cirrus Heterogeneity Effects on Cloud Optical Properties Retrieved with an Optimal Estimation Method from MODIS VIS to TIR Channels.

NASA Technical Reports Server (NTRS)

Fauchez, T.; Platnick, S.; Meyer, K.; Sourdeval, O.; Cornet, C.; Zhang, Z.; Szczap, F.

2016-01-01

This study presents preliminary results on the effect of cirrus heterogeneities on top-of-atmosphere (TOA) simulated radiances or reflectances for MODIS channels centered at 0.86, 2.21, 8.56, 11.01 and 12.03 micrometers , and on cloud optical properties retrieved with a research-level optimal estimation method (OEM). Synthetic cirrus cloud fields are generated using a 3D cloud generator (3DCLOUD) and radiances/reflectances are simulated using a 3D radiative transfer code (3DMCPOL). We find significant differences between the heterogeneity effects on either visible and near-infrared (VNIR) or thermal infrared (TIR) radiances. However, when both wavelength ranges are combined, heterogeneity effects are dominated by the VNIR horizontal radiative transport effect. As a result, small optical thicknesses are overestimated and large ones are underestimated. Retrieved effective diameter are found to be slightly affected, contrarily to retrievals using TIR channels only.

The determination of surface albedo from meteorological satellites

NASA Technical Reports Server (NTRS)

Johnson, W. T.

1977-01-01

A surface albedo was determined from visible data collected by the NOAA-4 polar orbiting meteorological satellite. To filter out the major cause of atmospheric reflectivity, namely clouds, techniques were developed and applied to the data resulting in a map of global surface albedo. Neglecting spurious surface albedos for regions with persistent cloud cover, sun glint effects, insufficient reflected light and, at this time, some unresolved influences, the surface albedos retrieved from satellite data closely matched those of a global surface albedo map produced from surface and aircraft measurements and from characteristic albedos for land type and land use.

Cloud cover detection combining high dynamic range sky images and ceilometer measurements

NASA Astrophysics Data System (ADS)

Román, R.; Cazorla, A.; Toledano, C.; Olmo, F. J.; Cachorro, V. E.; de Frutos, A.; Alados-Arboledas, L.

2017-11-01

This paper presents a new algorithm for cloud detection based on high dynamic range images from a sky camera and ceilometer measurements. The algorithm is also able to detect the obstruction of the sun. This algorithm, called CPC (Camera Plus Ceilometer), is based on the assumption that under cloud-free conditions the sky field must show symmetry. The symmetry criteria are applied depending on ceilometer measurements of the cloud base height. CPC algorithm is applied in two Spanish locations (Granada and Valladolid). The performance of CPC retrieving the sun conditions (obstructed or unobstructed) is analyzed in detail using as reference pyranometer measurements at Granada. CPC retrievals are in agreement with those derived from the reference pyranometer in 85% of the cases (it seems that this agreement does not depend on aerosol size or optical depth). The agreement percentage goes down to only 48% when another algorithm, based on Red-Blue Ratio (RBR), is applied to the sky camera images. The retrieved cloud cover at Granada and Valladolid is compared with that registered by trained meteorological observers. CPC cloud cover is in agreement with the reference showing a slight overestimation and a mean absolute error around 1 okta. A major advantage of the CPC algorithm with respect to the RBR method is that the determined cloud cover is independent of aerosol properties. The RBR algorithm overestimates cloud cover for coarse aerosols and high loads. Cloud cover obtained only from ceilometer shows similar results than CPC algorithm; but the horizontal distribution cannot be obtained. In addition, it has been observed that under quick and strong changes on cloud cover ceilometers retrieve a cloud cover fitting worse with the real cloud cover.

17 years of aerosol and clouds from the ATSR Series of Instruments

NASA Astrophysics Data System (ADS)

Poulsen, C. A.

2015-12-01

Aerosols play a significant role in Earth's climate by scattering and absorbing incoming sunlight and affecting the formation and radiative properties of clouds. The extent to which aerosols affect cloud remains one of the largest sources of uncertainty amongst all influences on climate change. Now, a new comprehensive datasets has been developed under the ESA Climate Change Initiative (CCI) programme to quantify how changes in aerosol levels affect these clouds. The unique dataset is constructed from the Optimal Retrieval of Aerosol and Cloud (ORAC) algorithm used in (A)ATSR (Along Track Scanning Radiometer) retrievals of aerosols generated in the Aerosol CCI and the CC4CL ( Community Code for CLimate) for cloud retrieval in the Cloud CCI. The ATSR instrument is a dual viewing instrument with on board visible and infra red calibration systems making it an ideal instrument to study trends of Aerosol and Clouds and their interactions. The data set begins in 1995 and ends in 2012. A new instrument in the series SLSTR(Sea and Land Surface Temperature Radiometer) will be launch in 2015. The Aerosol and Clouds are retreived using similar algorithms to maximise the consistency of the results These state-of-the-art retrievals have been merged together to quantify the susceptibility of cloud properties to changes in aerosol concentration. Aerosol-cloud susceptibilities are calculated from several thousand samples in each 1x1 degree globally gridded region. Two-D histograms of the aerosol and cloud properties are also included to facilitate seamless comparisons between other satellite and modelling data sets. The analysis of these two long term records will be discussed individually and the initial comparisons between these new joint products and models will be presented.

Investigation of the effects of the macrophysical and microphysical properties of cirrus clouds on the retrieval of optical properties: Results for FIRE 2

NASA Technical Reports Server (NTRS)

Stackhouse, Paul W., Jr.; Stephens, Graeme L.

1993-01-01

Due to the prevalence and persistence of cirrus cloudiness across the globe, cirrus clouds are believed to have an important effect on the climate. Stephens et al., (1990) among others have shown that the important factor determining how cirrus clouds modulate the climate is the balance between the albedo and emittance effect of the cloud systems. This factor was shown to depend in part upon the effective sizes of the cirrus cloud particles. Since effective sizes of cirrus cloud microphysical distributions are used as a basis of parameterizations in climate models, it is crucial that the relationships between effective sizes and radiative properties be clearly established. In this preliminary study, the retrieval of cirrus cloud effective sizes are examined using a two dimensional radiative transfer model for a cirrus cloud case sampled during FIRE Cirrus 11. The purpose of this paper is to present preliminary results from the SHSG model demonstrating the sensitivity of the bispectral relationships of reflected radiances and thus the retrieval of effective sizes to phase function and dimensionality.

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.

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.

Parameterization of Cirrus Cloud Vertical Profiles and Geometrical Thickness Using CALIPSO and CloudSat Data

NASA Astrophysics Data System (ADS)

Khatri, P.; Iwabuchi, H.; Saito, M.

2017-12-01

High-level cirrus clouds, which normally occur over more than 20% of the globe, are known to have profound impacts on energy budget and climate change. The scientific knowledge regarding the vertical structure of such high-level cirrus clouds and their geometrical thickness are relatively poorer compared to low-level water clouds. Knowledge regarding cloud vertical structure is especially important in passive remote sensing of cloud properties using infrared channels or channels strongly influenced by gaseous absorption when clouds are geometrically thick and optically thin. Such information is also very useful for validating cloud resolving numerical models. This study analyzes global scale data of ice clouds identified by Cloud profiling Radar (CPR) onboard CloudSat and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) onboard CALIPSO to parameterize (i) vertical profiles of ice water content (IWC), cloud-particle effective radius (CER), and ice-particle number concentration for varying ice water path (IWP) values and (ii) the relation of cloud geometrical thickness (CGT) with IWP and CER for varying cloud top temperature (CTT) values. It is found that the maxima in IWC and CER profile shifts towards cloud base with the increase of IWP. Similarly, if the cloud properties remain same, CGT shows an increasing trend with the decrease of CTT. The implementation of such cloud vertical inhomogeneity parameterization in the forward model used in the Integrated Cloud Analysis System ICAS (Iwabuchi et al., 2016) generally shows increase of brightness temperatures in infrared channels compared to vertically homogeneous cloud assumption. The cloud vertical inhomogeneity is found to bring noticeable changes in retrieved cloud properties. Retrieved CER and cloud top height become larger for optically thick cloud. We will show results of comparison of cloud properties retrieved from infrared measurements and active remote sensing.

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.

Comparison between two lidar methods to retrieve microphysical properties of liquid-water clouds

NASA Astrophysics Data System (ADS)

Jimenez, Cristofer; Ansmann, Albert; Donovan, David; Engelmann, Ronny; Schmidt, Jörg; Wandinger, Ulla

2018-04-01

Since 2010, the Raman dual-FOV lidar system permits the retrieval of microphysical properties of liquid-water clouds during nighttime. A new robust lidar depolarization approach was recently introduced, which permits the retrieval of these properties as well, with high temporal resolution and during daytime. To implement this approach, the lidar system was upgraded, by adding a three channel depolarization receiver. The first preliminary retrieval results and a comparison between both methods is presented.

Studying the Relationship between High-Latitude Geomagnetic Activity and Parameters of Interplanetary Magnetic Clouds with the Use of Artificial Neural Networks

NASA Astrophysics Data System (ADS)

Barkhatov, N. A.; Revunov, S. E.; Vorobjev, V. G.; Yagodkina, O. I.

2018-03-01

The cause-and-effect relations of the dynamics of high-latitude geomagnetic activity (in terms of the AL index) and the type of the magnetic cloud of the solar wind are studied with the use of artificial neural networks. A recurrent neural network model has been created based on the search for the optimal physically coupled input and output parameters characterizing the action of a plasma flux belonging to a certain magnetic cloud type on the magnetosphere. It has been shown that, with IMF components as input parameters of neural networks with allowance for a 90-min prehistory, it is possible to retrieve the AL sequence with an accuracy to 80%. The successful retrieval of the AL dynamics by the used data indicates the presence of a close nonlinear connection of the AL index with cloud parameters. The created neural network models can be applied with high efficiency to retrieve the AL index, both in periods of isolated magnetospheric substorms and in periods of the interaction between the Earth's magnetosphere and magnetic clouds of different types. The developed model of AL index retrieval can be used to detect magnetic clouds.

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

Zhang, Damao; Wang, Zhien; Heymsfield, Andrew J.

Measurement of ice number concentration in clouds is important but still challenging. Stratiform mixed-phase clouds (SMCs) provide a simple scenario for retrieving ice number concentration from remote sensing measurements. The simple ice generation and growth pattern in SMCs offers opportunities to use cloud radar reflectivity (Ze) measurements and other cloud properties to infer ice number concentration quantitatively. To understand the strong temperature dependency of ice habit and growth rate quantitatively, we develop a 1-D ice growth model to calculate the ice diffusional growth along its falling trajectory in SMCs. The radar reflectivity and fall velocity profiles of ice crystals calculatedmore » from the 1-D ice growth model are evaluated with the Atmospheric Radiation Measurements (ARM) Climate Research Facility (ACRF) ground-based high vertical resolution radar measurements. Combining Ze measurements and 1-D ice growth model simulations, we develop a method to retrieve the ice number concentrations in SMCs at given cloud top temperature (CTT) and liquid water path (LWP). The retrieved ice concentrations in SMCs are evaluated with in situ measurements and with a three-dimensional cloud-resolving model simulation with a bin microphysical scheme. These comparisons show that the retrieved ice number concentrations are within an uncertainty of a factor of 2, statistically.« less

Clouds and Ice of the Lambert-Amery System, East Antarctica

NASA Technical Reports Server (NTRS)

2002-01-01

These views from the Multi-angle Imaging SpectroRadiometer (MISR) illustrate ice surface textures and cloud-top heights over the Amery Ice Shelf/Lambert Glacier system in East Antarctica on October 25, 2002.

The left-hand panel is a natural-color view from MISR's downward-looking (nadir) camera. The center panel is a multi-angular composite from three MISR cameras, in which color acts as a proxy for angular reflectance variations related to texture. Here, data from the red-band of MISR's 60o forward-viewing, nadir and 60o backward-viewing cameras are displayed as red, green and blue, respectively. With this display technique, surfaces which predominantly exhibit backward-scattering (generally rough surfaces) appear red/orange, while surfaces which predominantly exhibit forward-scattering (generally smooth surfaces) appear blue. Textural variation for both the grounded and sea ice are apparent. The red/orange pixels in the lower portion of the image correspond with a rough and crevassed region near the grounding zone, that is, the area where the Lambert and four other smaller glaciers merge and the ice starts to float as it forms the Amery Ice Shelf. In the natural-color view, this rough ice is spectrally blue in color.

Clouds exhibit both forward and backward-scattering properties in the middle panel and thus appear purple, in distinct contrast with the underlying ice and snow. An additional multi-angular technique for differentiating clouds from ice is shown in the right-hand panel, which is a stereoscopically derived height field retrieved using automated pattern recognition involving data from multiple MISR cameras. Areas exhibiting insufficient spatial contrast for stereoscopic retrieval are shown in dark gray. Clouds are apparent as a result of their heights above the surface terrain. Polar clouds are an important factor in weather and climate. Inadequate characterization of cloud properties is currently responsible for large uncertainties in climate prediction models. Identification of polar clouds, mapping of their distributions, and retrieval of their heights provide information that will help to reduce this uncertainty.

The Multi-angle Imaging SpectroRadiometer observes the daylit Earth continuously and every 9 days views the entire Earth between 82 degrees north and 82 degrees south latitude. These data products were generated from a portion of the imagery acquired during Terra orbit 15171. The panels cover an area of 380 kilometers x 984 kilometers, and utilize data from blocks 145 to 151 within World Reference System-2 path 127.

MISR was built and is managed by NASA's Jet Propulsion Laboratory,Pasadena, CA, for NASA's Office of Earth Science, Washington, DC. The Terra satellite is managed by NASA's Goddard Space Flight Center,Greenbelt, MD. JPL is a division of the California Institute of Technology.

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.

Observations of Aircraft Dissipation Trails from GOES

NASA Technical Reports Server (NTRS)

Duda, David P.; Minnis, Patrick

2002-01-01

Two cases of distrails (aircraft dissipation trails) with associated fall streak clouds were analyzed using multispectral geostationary satellite data. One distrail was observed on 23 July 2000 in a single cloud layer over southeastern Virginia and the Chesapeake Bay. Another set of trails developed on 6 January 2000 at the top of multilayer clouds off the coasts of Georgia and South Carolina. The distrails on both days formed in optically thin, midlevel stratified clouds with cloud-top heights between 7.6 and 9.1 km. The distrail features remained intact and easily visible from satellite images for 1-2 h in spite of winds near 50 km at cloud level. The width of the distrails spread as far as 20 km within 90 min or less. Differences between the optical properties of the clouds surrounding the trails and those of the fall streak particles inside the distrails allowed for easy identification of the fall streak clouds in either the 3.9-micrometer brightness temperature imagery, or the 10.7-micrometer - 12.0-micrometer brightness temperature difference. Although the three-channel infrared retrieval was better at retrieving cloud properties in the multilayer cloud case, two independent remote sensing retrievals of both distrail cases showed that the fall streaks had larger particle sizes than the clouds outside of the trails.

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

NASA Technical Reports Server (NTRS)

1994-01-01

With the growing awareness and debate over the potential changes associated with global climate change, the polar regions are receiving increased attention. Global cloud distributions can be expected to be altered by increased greenhouse forcing. Owing to the similarity of cloud and snow-ice spectral signatures in both the visible and infrared wavelengths, it is difficult to distinguish clouds from surface features in the polar regions. This work is directed towards the development of algorithms for the ASTER and HIRIS science/instrument teams. Special emphasis is placed on a wide variety of cloud optical property retrievals, and especially retrievals of cloud and surface properties in the polar regions.

Aerosol and Cloud Interaction Observed From High Spectral Resolution Lidar Data

NASA Technical Reports Server (NTRS)

Su, Wenying; Schuster, Gregory L.; Loeb, Norman G.; Rogers, Raymond R.; Ferrare, Richard A.; Hostetler, Chris A.; Hair, Johnathan W.; Obland, Michael D.

2008-01-01

Recent studies utilizing satellite retrievals have shown a strong correlation between aerosol optical depth (AOD) and cloud cover. However, these retrievals from passive sensors are subject to many limitations, including cloud adjacency (or 3D) effects, possible cloud contamination, uncertainty in the AOD retrieval. Some of these limitations do not exist in High Spectral Resolution Lidar (HSRL) observations; for instance, HSRL observations are not a ected by cloud adjacency effects, are less prone to cloud contamination, and offer accurate aerosol property measurements (backscatter coefficient, extinction coefficient, lidar ratio, backscatter Angstrom exponent,and aerosol optical depth) at a neospatial resolution (less than 100 m) in the vicinity of clouds. Hence, the HSRL provides an important dataset for studying aerosol and cloud interaction. In this study, we statistically analyze aircraft-based HSRL profiles according to their distance from the nearest cloud, assuring that all profile comparisons are subject to the same large-scale meteorological conditions. Our results indicate that AODs from HSRL are about 17% higher in the proximity of clouds (approximately 100 m) than far away from clouds (4.5 km), which is much smaller than the reported cloud 3D effect on AOD retrievals. The backscatter and extinction coefficients also systematically increase in the vicinity of clouds, which can be explained by aerosol swelling in the high relative humidity (RH) environment and/or aerosol growth through in cloud processing (albeit not conclusively). On the other hand, we do not observe a systematic trend in lidar ratio; we hypothesize that this is caused by the opposite effects of aerosol swelling and aerosol in-cloud processing on the lidar ratio. Finally, the observed backscatter Angstrom exponent (BAE) does not show a consistent trend because of the complicated relationship between BAE and RH. We demonstrate that BAE should not be used as a surrogate for Angstrom exponent, especially at high RH.

Multilayer Cloud Detection with the MODIS Near-Infrared Water Vapor Absorption Band

NASA Technical Reports Server (NTRS)

Wind, Galina; Platnick, Steven; King, Michael D.; Hubanks, Paul A,; Pavolonis, Michael J.; Heidinger, Andrew K.; Yang, Ping; Baum, Bryan A.

2009-01-01

Data Collection 5 processing for the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the NASA Earth Observing System EOS Terra and Aqua spacecraft includes an algorithm for detecting multilayered clouds in daytime. The main objective of this algorithm is to detect multilayered cloud scenes, specifically optically thin ice cloud overlying a lower-level water cloud, that presents difficulties for retrieving cloud effective radius using single layer plane-parallel cloud models. The algorithm uses the MODIS 0.94 micron water vapor band along with CO2 bands to obtain two above-cloud precipitable water retrievals, the difference of which, in conjunction with additional tests, provides a map of where multilayered clouds might potentially exist. The presence of a multilayered cloud results in a large difference in retrievals of above-cloud properties between the CO2 and the 0.94 micron methods. In this paper the MODIS multilayered cloud algorithm is described, results of using the algorithm over example scenes are shown, and global statistics for multilayered clouds as observed by MODIS are discussed. A theoretical study of the algorithm behavior for simulated multilayered clouds is also given. Results are compared to two other comparable passive imager methods. A set of standard cloudy atmospheric profiles developed during the course of this investigation is also presented. The results lead to the conclusion that the MODIS multilayer cloud detection algorithm has some skill in identifying multilayered clouds with different thermodynamic phases

Arctic Stratus Cloud Properties and Their Effect on the Surface Radiation Budget: Selected Cases from FIRE ACE

NASA Technical Reports Server (NTRS)

Doug, Xiquan; Mace, Gerald G.; Minnis, Patrick; Young, David F.

2001-01-01

To study Arctic stratus cloud properties and their effect on the surface radiation balance during the spring transition season, analyses are performed using data taken during three cloudy and two clear days in May 1998 as part of the First ISCCP Regional Experiment (FIRE) Arctic Cloud Experiment (ACE). Radiative transfer models are used in conjunction with surface- and satellite-based measurements to retrieve the layer-averaged microphysical and shortwave radiative properties. The surface-retrieved cloud properties in Cases 1 and 2 agree well with the in situ and satellite retrievals. Discrepancies in Case 3 are due to spatial mismatches between the aircraft and the surface measurements in a highly variable cloud field. Also, the vertical structure in the cloud layer is not fully characterized by the aircraft measurements. Satellite data are critical for understanding some of the observed discrepancies. The satellite-derived particle sizes agree well with the coincident surface retrievals and with the aircraft data when they were collocated. Optical depths derived from visible-channel data over snow backgrounds were overestimated in all three cases, suggesting that methods currently used in satellite cloud climatologies derive optical depths that are too large. Use of a near-infrared channel with a solar infrared channel to simultaneously derive optical depth and particle size appears to alleviate this overestimation problem. Further study of the optical depth retrieval is needed. The surface-based radiometer data reveal that the Arctic stratus clouds produce a net warming of 20 W m(exp -2) in the surface layer during the transition season suggesting that these clouds may accelerate the spring time melting of the ice pack. This surface warming contrasts with the net cooling at the top of the atmosphere (TOA) during the same period. All analysis of the complete FIRE ACE data sets will be valuable for understanding the role of clouds during the entire melting and refreezing process that occurs annually in the Arctic.

An improvement of the retrieval of temperature and relative humidity profiles from a combination of active and passive remote sensing

NASA Astrophysics Data System (ADS)

Che, Yunfei; Ma, Shuqing; Xing, Fenghua; Li, Siteng; Dai, Yaru

2018-03-01

This paper focuses on an improvement of the retrieval of atmospheric temperature and relative humidity profiles through combining active and passive remote sensing. Ground-based microwave radiometer and millimeter-wavelength cloud radar were used to acquire the observations. Cloud base height and cloud thickness determinations from cloud radar were added into the atmospheric profile retrieval process, and a back-propagation neural network method was used as the retrieval tool. Because a substantial amount of data are required to train a neural network, and as microwave radiometer data are insufficient for this purpose, 8 years of radiosonde data from Beijing were used as the database. The monochromatic radiative transfer model was used to calculate the brightness temperatures in the same channels as the microwave radiometer. Parts of the cloud base heights and cloud thicknesses in the training data set were also estimated using the radiosonde data. The accuracy of the results was analyzed through a comparison with L-band sounding radar data and quantified using the mean bias, root-mean-square error (RMSE), and correlation coefficient. The statistical results showed that an inversion with cloud information was the optimal method. Compared with the inversion profiles without cloud information, the RMSE values after adding cloud information reduced to varying degrees for the vast majority of height layers. These reductions were particularly clear in layers with clouds. The maximum reduction in the RMSE for the temperature profile was 2.2 K, while that for the humidity profile was 16%.

Added value of far-infrared radiometry for remote sensing of ice clouds

NASA Astrophysics Data System (ADS)

Libois, Quentin; Blanchet, Jean-Pierre

2017-06-01

Several cloud retrieval algorithms based on satellite observations in the infrared have been developed in the last decades. However, these observations only cover the midinfrared (MIR, λ < 15 μm) part of the spectrum, and none are available in the far-infrared (FIR, λ≥ 15 μm). Using the optimal estimation method, we show that adding a few FIR channels to existing spaceborne radiometers would significantly improve their ability to retrieve ice cloud radiative properties. For clouds encountered in the polar regions and the upper troposphere, where the atmosphere is sufficiently transparent in the FIR, using FIR channels would reduce by more than 50% the uncertainties on retrieved values of optical thickness, effective particle diameter, and cloud top altitude. Notably, this would extend the range of applicability of current retrieval methods to the polar regions and to clouds with large optical thickness, where MIR algorithms perform poorly. The high performance of solar reflection-based algorithms would thus be reached in nighttime conditions. Since the sensitivity of ice cloud thermal emission to effective particle diameter is approximately 5 times larger in the FIR than in the MIR, using FIR observations is a promising venue for studying ice cloud microphysics and precipitation processes. This is highly relevant for cirrus clouds and convective towers. This is also essential to study precipitation in the driest regions of the atmosphere, where strong feedbacks are at play between clouds and water vapor. The deployment in the near future of a FIR spaceborne radiometer is technologically feasible and should be strongly supported.

G-band atmospheric radars: new frontiers in cloud physics

NASA Astrophysics Data System (ADS)

Battaglia, A.; Westbrook, C. D.; Kneifel, S.; Kollias, P.; Humpage, N.; Löhnert, U.; Tyynelä, J.; Petty, G. W.

2014-01-01

Clouds and associated precipitation are the largest source of uncertainty in current weather and future climate simulations. Observations of the microphysical, dynamical and radiative processes that act at cloud-scales are needed to improve our understanding of clouds. The rapid expansion of ground-based super-sites and the availability of continuous profiling and scanning multi-frequency radar observations at 35 and 94 GHz have significantly improved our ability to probe the internal structure of clouds in high temporal-spatial resolution, and to retrieve quantitative cloud and precipitation properties. However, there are still gaps in our ability to probe clouds due to large uncertainties in the retrievals. The present work discusses the potential of G-band (frequency between 110 and 300 GHz) Doppler radars in combination with lower frequencies to further improve the retrievals of microphysical properties. Our results show that, thanks to a larger dynamic range in dual-wavelength reflectivity, dual-wavelength attenuation and dual-wavelength Doppler velocity (with respect to a Rayleigh reference), the inclusion of frequencies in the G-band can significantly improve current profiling capabilities in three key areas: boundary layer clouds, cirrus and mid-level ice clouds, and precipitating snow.

G band atmospheric radars: new frontiers in cloud physics

NASA Astrophysics Data System (ADS)

Battaglia, A.; Westbrook, C. D.; Kneifel, S.; Kollias, P.; Humpage, N.; Löhnert, U.; Tyynelä, J.; Petty, G. W.

2014-06-01

Clouds and associated precipitation are the largest source of uncertainty in current weather and future climate simulations. Observations of the microphysical, dynamical and radiative processes that act at cloud scales are needed to improve our understanding of clouds. The rapid expansion of ground-based super-sites and the availability of continuous profiling and scanning multi-frequency radar observations at 35 and 94 GHz have significantly improved our ability to probe the internal structure of clouds in high temporal-spatial resolution, and to retrieve quantitative cloud and precipitation properties. However, there are still gaps in our ability to probe clouds due to large uncertainties in the retrievals. The present work discusses the potential of G band (frequency between 110 and 300 GHz) Doppler radars in combination with lower frequencies to further improve the retrievals of microphysical properties. Our results show that, thanks to a larger dynamic range in dual-wavelength reflectivity, dual-wavelength attenuation and dual-wavelength Doppler velocity (with respect to a Rayleigh reference), the inclusion of frequencies in the G band can significantly improve current profiling capabilities in three key areas: boundary layer clouds, cirrus and mid-level ice clouds, and precipitating snow.

Retrieval of effective cloud field parameters from radiometric data

NASA Astrophysics Data System (ADS)

Paulescu, Marius; Badescu, Viorel; Brabec, Marek

2017-06-01

Clouds play a key role in establishing the Earth's climate. Real cloud fields are very different and very complex in both morphological and microphysical senses. Consequently, the numerical description of the cloud field is a critical task for accurate climate modeling. This study explores the feasibility of retrieving the effective cloud field parameters (namely the cloud aspect ratio and cloud factor) from systematic radiometric measurements at high frequency (measurement is taken every 15 s). Two different procedures are proposed, evaluated, and discussed with respect to both physical and numerical restrictions. None of the procedures is classified as best; therefore, the specific advantages and weaknesses are discussed. It is shown that the relationship between the cloud shade and point cloudiness computed using the estimated cloud field parameters recovers the typical relationship derived from measurements.

A simple biota removal algorithm for 35 GHz cloud radar measurements

NASA Astrophysics Data System (ADS)

Kalapureddy, Madhu Chandra R.; Sukanya, Patra; Das, Subrata K.; Deshpande, Sachin M.; Pandithurai, Govindan; Pazamany, Andrew L.; Ambuj K., Jha; Chakravarty, Kaustav; Kalekar, Prasad; Krishna Devisetty, Hari; Annam, Sreenivas

2018-03-01

Cloud radar reflectivity profiles can be an important measurement for the investigation of cloud vertical structure (CVS). However, extracting intended meteorological cloud content from the measurement often demands an effective technique or algorithm that can reduce error and observational uncertainties in the recorded data. In this work, a technique is proposed to identify and separate cloud and non-hydrometeor echoes using the radar Doppler spectral moments profile measurements. The point and volume target-based theoretical radar sensitivity curves are used for removing the receiver noise floor and identified radar echoes are scrutinized according to the signal decorrelation period. Here, it is hypothesized that cloud echoes are observed to be temporally more coherent and homogenous and have a longer correlation period than biota. That can be checked statistically using ˜ 4 s sliding mean and standard deviation value of reflectivity profiles. The above step helps in screen out clouds critically by filtering out the biota. The final important step strives for the retrieval of cloud height. The proposed algorithm potentially identifies cloud height solely through the systematic characterization of Z variability using the local atmospheric vertical structure knowledge besides to the theoretical, statistical and echo tracing tools. Thus, characterization of high-resolution cloud radar reflectivity profile measurements has been done with the theoretical echo sensitivity curves and observed echo statistics for the true cloud height tracking (TEST). TEST showed superior performance in screening out clouds and filtering out isolated insects. TEST constrained with polarimetric measurements was found to be more promising under high-density biota whereas TEST combined with linear depolarization ratio and spectral width perform potentially to filter out biota within the highly turbulent shallow cumulus clouds in the convective boundary layer (CBL). This TEST technique is promisingly simple in realization but powerful in performance due to the flexibility in constraining, identifying and filtering out the biota and screening out the true cloud content, especially the CBL clouds. Therefore, the TEST algorithm is superior for screening out the low-level clouds that are strongly linked to the rainmaking mechanism associated with the Indian Summer Monsoon region's CVS.

AMF3 CloudSat Overpasses Field Campaign Report

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

Matrosov, Sergey; Hardin, Joseph; De Boer, Gijs

Synergy between ground-based and satellite radar observations of clouds and precipitation is important for refining the algorithms to retrieve hydrometeor microphysical parameters, improvements in the retrieval accuracy, and better understanding the advantages and limitations of different retrieval approaches. The new dual-frequency (Ka- and W-band, 35 GHz and 94 GHz) fully polarimetric scanning U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Research Facility cloud radars (SACRs-2) are advanced sensors aimed to significantly enhance remote sensing capabilities (Kollias et al. 2016). One of these radars was deployed as part of the third ARM Mobile Facility (AMF3) at Oliktok Point, Alaska (70.495omore » N, 149.886oW). The National Aeronautics and Space Administration (NASA) CloudSat satellite, which is part of the polar-orbiting A-train satellite constellation, passes over the vicinity of the AMF3 location (typically within 0-7 km depending on a particular overpass) on a descending orbit every 16 days at approximately 13:21 UTC. The nadir pointing W-band CloudSat cloud profiling radar (CPR) provides vertical profiles of reflectivity that are then used for retrievals of hydrometeor parameters (Tanelli et al. 2008). The main objective of the AMF3 CloudSat overpasses intensive operating period (IOP) campaign was to collect approximately collocated in space and time radar data from the SACR-2 and the CloudSat CPR measurements for subsequent joint analysis of radar variables and microphysical retrievals of cloud and precipitation parameters. Providing the reference for the SACR-2 absolute calibration from the well-calibrated CloudSat CPR was another objective of this IOP. The IOP objectives were achieved by conducting seven special SACR-2 scans during the 10.5-min period centered at the exact time of the CloudSat overpass over the AMF3 (~1321 UTC) on six dates of the CloudSat overpasses during the three-month period allocated to this IOP. These six days were March 5 and 21, April 6 and 22, and May 8 and 24.« less

Cloud Retrieval Information Content Studies with the Pre-Aerosol, Cloud and ocean Ecosystem (PACE) Ocean Color Imager (OCI)

NASA Astrophysics Data System (ADS)

Coddington, Odele; Platnick, Steven; Pilewskie, Peter; Schmidt, Sebastian

2016-04-01

The NASA Pre-Aerosol, Cloud and ocean Ecosystem (PACE) Science Definition Team (SDT) report released in 2012 defined imager stability requirements for the Ocean Color Instrument (OCI) at the sub-percent level. While the instrument suite and measurement requirements are currently being determined, the PACE SDT report provided details on imager options and spectral specifications. The options for a threshold instrument included a hyperspectral imager from 350-800 nm, two near-infrared (NIR) channels, and three short wave infrared (SWIR) channels at 1240, 1640, and 2130 nm. Other instrument options include a variation of the threshold instrument with 3 additional spectral channels at 940, 1378, and 2250 nm and the inclusion of a spectral polarimeter. In this work, we present cloud retrieval information content studies of optical thickness, droplet effective radius, and thermodynamic phase to quantify the potential for continuing the low cloud climate data record established by the MOderate Resolution and Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) missions with the PACE OCI instrument (i.e., non-polarized cloud reflectances and in the absence of midwave and longwave infrared channels). The information content analysis is performed using the GEneralized Nonlinear Retrieval Analysis (GENRA) methodology and the Collection 6 simulated cloud reflectance data for the common MODIS/VIIRS algorithm (MODAWG) for Cloud Mask, Cloud-Top, and Optical Properties. We show that using both channels near 2 microns improves the probability of cloud phase discrimination with shortwave-only cloud reflectance retrievals. Ongoing work will extend the information content analysis, currently performed for dark ocean surfaces, to different land surface types.

Cloud parameters from zenith transmittances measured by sky radiometer at surface: Method development and satellite product validation

NASA Astrophysics Data System (ADS)

Khatri, Pradeep; Hayasaka, Tadahiro; Iwabuchi, Hironobu; Takamura, Tamio; Irie, Hitoshi; Nakajima, Takashi Y.; Letu, Husi; Kai, Qin

2017-04-01

Clouds are known to have profound impacts on atmospheric radiation and water budget, climate change, atmosphere-surface interaction, and so on. Cloud optical thickness (COT) and effective radius (Re) are two fundamental cloud parameters required to study clouds from climatological and hydrological point of view. Large spatial-temporal coverages of those cloud parameters from space observation have proved to be very useful for cloud research; however, validation of space-based products is still a challenging task due to lack of reliable data. Ground-based remote sensing instruments, such as sky radiometers distributed around the world through international observation networks of SKYNET (http://atmos2.cr.chiba-u.jp/skynet/) and AERONET (https://aeronet.gsfc.nasa.gov/) have a great potential to produce ground-truth cloud parameters at different parts of the globe to validate satellite products. Focusing to the sky radiometers of SKYNET and AERONET, a few cloud retrieval methods exists, but those methods have some difficulties to address the problem when cloud is optically thin. It is because the observed transmittances at two wavelengths can be originated from more than one set of COD and Re, and the choice of the most plausible set is difficult. At the same time, calibration issue, especially for the wavelength of near infrared (NIR) region, which is important to retrieve Re, is also a difficult task at present. As a result, instruments need to be calibrated at a high mountain or calibration terms need to be transferred from a standard instrument. Taking those points on account, we developed a new retrieval method emphasizing to overcome above-mentioned difficulties. We used observed transmittances of multiple wavelengths to overcome the first problem. We further proposed a method to obtain calibration constant of NIR wavelength channel using observation data. Our cloud retrieval method is found to produce relatively accurate COD and Re when validated them using data of a narrow field of view radiometer of collocated observation in one SKYNET site. Though the method is developed for the sky radiometer of SKYNET, it can be still used for the sky radiometer of AERONET and other instruments observing spectral zenith transmittances. The proposed retrieval method is then applied to retrieve cloud parameters at key sites of SKYNET within Japan, which are then used to validate cloud products obtained from space observations by MODIS sensors onboard TERRA/AQUA satellites and Himawari 8, a Japanese geostationary satellite. Our analyses suggest the underestimation (overestimation) of COD (Re) from space observations.

High Vertically Resolved Atmospheric State Revealed with IASI Single FOV Retrievals under All-weather Conditions

NASA Technical Reports Server (NTRS)

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

2008-01-01

The Infrared Atmospheric Sounding Interferometer (IASI) on the MetOp satellite was launched on October 19, 2006. 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(exp -1) and a spectral coverage from 645 to 2760 cm(exp -1). 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. Preliminary retrievals of atmospheric soundings, surface properties, and cloud optical/microphysical properties with the IASI observations are obtained and presented. These retrievals are 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 to benefit future NPOESS operation.

Trade Study: Storing NASA HDF5/netCDF-4 Data in the Amazon Cloud and Retrieving Data via Hyrax Server / THREDDS Data Server

NASA Technical Reports Server (NTRS)

Habermann, Ted; Jelenak, Aleksander; Lee, Joe; Yang, Kent; Gallagher, James; Potter, Nathan

2017-01-01

As part of the overall effort to understand implications of migrating ESDIS data and services to the cloud we are testing several common OPeNDAP and HDF use cases against three architectures for general performance and cost characteristics. The architectures include retrieving entire files, retrieving datasets using HTTP range gets, and retrieving elements of datasets (chunks) with HTTP range gets. We will describe these architectures and discuss our approach to estimating cost.

A General Uncertainty Quantification Methodology for Cloud Microphysical Property Retrievals

NASA Astrophysics Data System (ADS)

Tang, Q.; Xie, S.; Chen, X.; Zhao, C.

2014-12-01

The US Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) program provides long-term (~20 years) ground-based cloud remote sensing observations. However, there are large uncertainties in the retrieval products of cloud microphysical properties based on the active and/or passive remote-sensing measurements. To address this uncertainty issue, a DOE Atmospheric System Research scientific focus study, Quantification of Uncertainties in Cloud Retrievals (QUICR), has been formed. In addition to an overview of recent progress of QUICR, we will demonstrate the capacity of an observation-based general uncertainty quantification (UQ) methodology via the ARM Climate Research Facility baseline cloud microphysical properties (MICROBASE) product. This UQ method utilizes the Karhunen-Loéve expansion (KLE) and Central Limit Theorems (CLT) to quantify the retrieval uncertainties from observations and algorithm parameters. The input perturbations are imposed on major modes to take into account the cross correlations between input data, which greatly reduces the dimension of random variables (up to a factor of 50) and quantifies vertically resolved full probability distribution functions of retrieved quantities. Moreover, this KLE/CLT approach has the capability of attributing the uncertainties in the retrieval output to individual uncertainty source and thus sheds light on improving the retrieval algorithm and observations. We will present the results of a case study for the ice water content at the Southern Great Plains during an intensive observing period on March 9, 2000. This work is performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344.

On the Cloud Observations in JAXA's Next Coming Satellite Missions

NASA Technical Reports Server (NTRS)

Nakajima, Takashi Y.; Nagao, Takashi M.; Letu, Husi; Ishida, Haruma; Suzuki, Kentaroh

2012-01-01

The use of JAXA's next generation satellites, the EarthCARE and the GCOM-C, for observing overall cloud systems on the Earth is discussed. The satellites will be launched in the middle of 2010-era and contribute for observing aerosols and clouds in terms of climate change, environment, weather forecasting, and cloud revolution process study. This paper describes the role of such satellites and how to use the observing data showing concepts and some sample viewgraphs. Synergistic use of sensors is a key of the study. Visible to infrared bands are used for cloudy and clear discriminating from passively obtained satellite images. Cloud properties such as the cloud optical thickness, the effective particle radii, and the cloud top temperature will be retrieved from visible to infrared wavelengths of imagers. Additionally, we are going to combine cloud properties obtained from passive imagers and radar reflectivities obtained from an active radar in order to improve our understanding of cloud evolution process. This is one of the new techniques of satellite data analysis in terms of cloud sciences in the next decade. Since the climate change and cloud process study have mutual beneficial relationship, a multispectral wide-swath imagers like the GCOM-C SGLI and a comprehensive observation package of cloud and aerosol like the EarthCARE are both necessary.

Type-Dependent Responses of Ice Cloud Properties to Aerosols From Satellite Retrievals

NASA Astrophysics Data System (ADS)

Zhao, Bin; Gu, Yu; Liou, Kuo-Nan; Wang, Yuan; Liu, Xiaohong; Huang, Lei; Jiang, Jonathan H.; Su, Hui

2018-04-01

Aerosol-cloud interactions represent one of the largest uncertainties in external forcings on our climate system. Compared with liquid clouds, the observational evidence for the aerosol impact on ice clouds is much more limited and shows conflicting results, partly because the distinct features of different ice cloud and aerosol types were seldom considered. Using 9-year satellite retrievals, we find that, for convection-generated (anvil) ice clouds, cloud optical thickness, cloud thickness, and cloud fraction increase with small-to-moderate aerosol loadings (<0.3 aerosol optical depth) and decrease with further aerosol increase. For in situ formed ice clouds, however, these cloud properties increase monotonically and more sharply with aerosol loadings. An increase in loading of smoke aerosols generally reduces cloud optical thickness of convection-generated ice clouds, while the reverse is true for dust and anthropogenic pollution aerosols. These relationships between different cloud/aerosol types provide valuable constraints on the modeling assessment of aerosol-ice cloud radiative forcing.

Determination of Cloud Base Height, Wind Velocity, and Short-Range Cloud Structure Using Multiple Sky Imagers Field Campaign Report

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

Huang, Dong; Schwartz, Stephen E.; Yu, Dantong

Clouds are a central focus of the U.S. Department of Energy (DOE)’s Atmospheric System Research (ASR) program and Atmospheric Radiation Measurement (ARM) Climate Research Facility, and more broadly are the subject of much investigation because of their important effects on atmospheric radiation and, through feedbacks, on climate sensitivity. Significant progress has been made by moving from a vertically pointing (“soda-straw”) to a three-dimensional (3D) view of clouds by investing in scanning cloud radars through the American Recovery and Reinvestment Act of 2009. Yet, because of the physical nature of radars, there are key gaps in ARM's cloud observational capabilities. Formore » example, cloud radars often fail to detect small shallow cumulus and thin cirrus clouds that are nonetheless radiatively important. Furthermore, it takes five to twenty minutes for a cloud radar to complete a 3D volume scan and clouds can evolve substantially during this period. Ground-based stereo-imaging is a promising technique to complement existing ARM cloud observation capabilities. It enables the estimation of cloud coverage, height, horizontal motion, morphology, and spatial arrangement over an extended area of up to 30 by 30 km at refresh rates greater than 1 Hz (Peng et al. 2015). With fine spatial and temporal resolution of modern sky cameras, the stereo-imaging technique allows for the tracking of a small cumulus cloud or a thin cirrus cloud that cannot be detected by a cloud radar. With support from the DOE SunShot Initiative, the Principal Investigator (PI)’s team at Brookhaven National Laboratory (BNL) has developed some initial capability for cloud tracking using multiple distinctly located hemispheric cameras (Peng et al. 2015). To validate the ground-based cloud stereo-imaging technique, the cloud stereo-imaging field campaign was conducted at the ARM Facility’s Southern Great Plains (SGP) site in Oklahoma from July 15 to December 24. As shown in Figure 1, the cloud stereo-imaging system consisted of two inexpensive high-definition (HD) hemispheric cameras (each cost less than $1,500) and ARM’s Total Sky Imager (TSI). Together with other co-located ARM instrumentation, the campaign provides a promising opportunity to validate stereo-imaging-based cloud base height and, more importantly, to examine the feasibility of cloud thickness retrieval for low-view-angle clouds.« less

Assessment of Cloud Screening with Apparent Surface Reflectance in Support of the ICESat-2 Mission

NASA Technical Reports Server (NTRS)

Yang, Yuekui; Marshak, Alexander; Palm, Stephen P.; Wang, Zhuosen; Schaaf, Crystal

2011-01-01

The separation of cloud and clear scenes is usually one of the first steps in satellite data analysis. Before deriving a geophysical product, almost every satellite mission requires a cloud mask to label a scene as either clear or cloudy through a cloud detection procedure. For clear scenes, products such as surface properties may be retrieved; for cloudy scenes, scientist can focus on studying the cloud properties. Hence the quality of cloud detection directly affects the quality of most satellite operational and research products. This is certainly true for the Ice, Cloud, and land Elevation Satellite-2 (lCESat-2), which is the successor to the ICESat-l. As a top priority mission, ICESat-2 will continue to provide measurements of ice sheets and sea ice elevation on a global scale. Studies have shown that clouds can significantly affect the accuracy of the retrieved results. For example, some of the photons (a photon is a basic unit of light) in the laser beam will be scattered by cloud particles on its way. So instead of traveling in a straight line, these photons are scattered sideways and have traveled a longer path. This will result in biases in ice sheet elevation measurements. Hence cloud screening must be done and be done accurately before the retrievals.

Multispectral Cloud Retrievals from MODIS on Terra and Aqua

NASA Technical Reports Server (NTRS)

King, Michael D.; Platnick, Steven; Ackerman, Steven A.; Menzel, W. Paul; Gray, Mark A.; Moody, Eric G.

2002-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard the Terra spacecraft on December 18, 1999 and the Aqua spacecraft on April 26, 2002. MODIS scans a swath width sufficient to provide nearly complete global coverage every two days from each polar-orbiting, sun-synchronous, platform at an altitude of 705 km, and provides images in 36 spectral bands between 0.415 and 14.235 microns with spatial resolutions of 250 m (2 bands), 500 m (5 bands) and 1000 m (29 bands). In this paper we will describe the various methods being used for the remote sensing of cloud properties using MODIS data, focusing primarily on the MODIS cloud mask used to distinguish clouds, clear sky, heavy aerosol, and shadows on the ground, and on the remote sensing of cloud optical properties, especially cloud optical thickness and effective radius of water drops and ice crystals. Additional properties of clouds derived from multispectral thermal infrared measurements, especially cloud top pressure and emissivity, will also be described. Results will be presented of MODIS cloud properties both over the land and over the ocean, showing the consistency in cloud retrievals over various ecosystems used in the retrievals. The implications of this new observing system on global analysis of the Earth's environment will be discussed.

New Multispectral Cloud Retrievals from MODIS

NASA Technical Reports Server (NTRS)

King, Michael D.; Platnick, Steven; Tsay, Si-Chee; Ackerman, Steven A.; Menzel, W. Paul; Gray, Mark A.; Moody, Eric G.; Li, Jason Y.; Arnold, G. Thomas

2001-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard the Terra spacecraft on December 18, 1999. It achieved its final orbit and began Earth observations on February 24, 2000. MODIS scans a swath width sufficient to provide nearly complete global coverage every two days from a polar-orbiting, sun- synchronous, platform at an altitude of 705 km, and provides images in 36 spectral bands between 0.415 and 14.235 microns with spatial resolutions of 250 m (two bands), 500 m (five bands) and 1000 m (29 bands). In this paper we will describe the various methods being used for the remote sensing of cloud properties using MODIS data, focusing primarily on the MODIS cloud mask used to distinguish clouds, clear sky, heavy aerosol, and shadows on the ground, and on the remote sensing of cloud optical properties, especially cloud optical thickness and effective radius of water drops and ice crystals. Additional properties of clouds derived from multispectral thermal infrared measurements, especially cloud top pressure and emissivity, will also be described. Results will be presented of MODIS cloud properties both over the land and over the ocean, showing the consistency in cloud retrievals over various ecosystems used in the retrievals. The implications of this new observing system on global analysis of the Earth's environment will be discussed.

DEVELOPING ATMOSPHERIC RETRIEVAL METHODS FOR DIRECT IMAGING SPECTROSCOPY OF GAS GIANTS IN REFLECTED LIGHT. I. METHANE ABUNDANCES AND BASIC CLOUD PROPERTIES

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

Lupu, Roxana E.; Marley, Mark S.; Zahnle, Kevin

Upcoming space-based coronagraphic instruments in the next decade will perform reflected light spectroscopy and photometry of cool directly imaged extrasolar giant planets. We are developing a new atmospheric retrieval methodology to help assess the science return and inform the instrument design for such future missions, and ultimately interpret the resulting observations. Our retrieval technique employs a geometric albedo model coupled with both a Markov chain Monte Carlo Ensemble Sampler ( emcee ) and a multimodal nested sampling algorithm ( MultiNest ) to map the posterior distribution. This combination makes the global evidence calculation more robust for any given model andmore » highlights possible discrepancies in the likelihood maps. As a proof of concept, our current atmospheric model contains one or two cloud layers, methane as a major absorber, and a H{sub 2}–He background gas. This 6-to-9 parameter model is appropriate for Jupiter-like planets and can be easily expanded in the future. In addition to deriving the marginal likelihood distribution and confidence intervals for the model parameters, we perform model selection to determine the significance of methane and cloud detection as a function of expected signal-to-noise ratio in the presence of spectral noise correlations. After internal validation, the method is applied to realistic spectra of Jupiter, Saturn, and HD 99492c, a model observing target. We find that the presence or absence of clouds and methane can be determined with high confidence, while parameter uncertainties are model dependent and correlated. Such general methods will also be applicable to the interpretation of direct imaging spectra of cloudy terrestrial planets.« less

Developing Atmospheric Retrieval Methods for Direct Imaging Spectroscopy of Gas Giants in Reflected Light I: Methane Abundances and Basic Cloud Properties

NASA Technical Reports Server (NTRS)

Lupu, R. E.; Marley, M. S.; Lewis, N.; Line, M.; Traub, W.; Zahnle, K.

2016-01-01

Reflected light spectroscopy and photometry of cool, directly imaged extrasolar giant planets are expected to be performed in the next decade by space-based telescopes equipped with optical wavelength coronagraphs and integral field spectrographs, such as the Wide-Field Infrared Survey Telescope (WFIRST). We are developing a new atmospheric retrieval methodology to help assess the science return and inform the instrument design for such future missions, and ultimately interpret the resulting observations. Our retrieval technique employs an albedo model coupled with both a Markov chain Monte Carlo Ensemble Sampler (emcee) and a multimodal nested sampling algorithm (MultiNest) to map the posterior distribution. This combination makes the global evidence calculation more robust for any given model, and highlights possible discrepancies in the likelihood maps. Here we apply this methodology to simulated spectra of cool giant planets. As a proof-of-concept, our current atmospheric model contains 1 or 2 cloud layers, methane as a major absorber, and a H2-He background gas. This 6-to-9 parameter model is appropriate for Jupiter-like planets and can be easily expanded in the future. In addition to deriving the marginal likelihood distribution and confidence intervals for the model parameters, we perform model selection to determine the significance of methane and cloud detection as a function of expected signal-to-noise, in the presence of spectral noise correlations. After internal validation, the method is applied to realistic reflected-light spectra of Jupiter, Saturn, and HD 99492 c, a likely observing target. We find that the presence or absence of clouds and methane can be determined with high accuracy, while parameters uncertainties are model-dependent.

Characterization of cirrus clouds and atmospheric state using a new hyper-spectral optimal estimation retrieval

NASA Astrophysics Data System (ADS)

Veglio, P.; Holz, R.

2016-12-01

The importance of cirrus clouds as regulators of Earth's climate and radiation budget has been widely demonstrated, but still their characterization remains challenging. In order to derive cirrus properties, many retrieval techniques rely on prior assumptions on the atmospheric state or on the ice microphysics, either because the computational cost is too high or because the measurements do not have enough information, as in the case of broadband sensors. In this work we present a novel infrared hyper-spectral optimal estimation retrieval capable of simultaneously deriving cirrus cloud parameters (optical depth, effective radius, cloud top height) and atmospheric state (temperature and water vapor profiles) with their associated uncertainties by using a fast forward radiative transfer code. The use of hyperspectral data help overcoming the problem of the information content while the computational cost can be addressed by using a fast radiative transfer model. The tradeoff of this choice is an increasing in the complexity of the problem. Also, it is important to consider that by using a fast, approximate radiative transfer model, the uncertainties must be carefully evaluated in order to prevent or minimize any biases that could negatively affect the results. For this application data from the HS3 field campaign are used, which provide high quality hyper-spectral measurements from Scanning HIS along with CPL and possibly also dropsonde data and GDAS reanalysis to help validate the results. The future of this work will be to move from aircraft to satellite observations, and the natural choice is AIRS and CALIOP that offer a similar setup to what is currently used for this study.

Using OMI Observations to Measure Aerosol Absorption of Biomass Burning Aerosols Above Clouds

NASA Technical Reports Server (NTRS)

Torres, Omar; Bhartia, P. K.; Jethva, Hiren

2011-01-01

The presence of absorbing aerosol layers above clouds is unambiguously detected by the TOMS/OMI UV Aerosol Index (AI) that uses satellite observations at two near-UV channels. A sensitivity study using radiative transfer calculations shows that the AI signal of resulting from the presence of aerosols above clouds is mainly driven by the aerosol absorption optical depth and the optical depth of the underlying cloud. Based on these results, an inversion algorithm has been developed to retrieve the aerosol optical depth (AOD) of aerosol layers above clouds. In this presentation we will discuss the sensitivity analysis, describe the retrieval approach, and present results of applications of the retrieval method to OMI observations over the South Atlantic Ocean. Preliminary error analyses, to be discussed, indicate that the AOD can be underestimated (up to -30%) or overestimated (up to 60%) depending on algorithmic assumptions.

Large Scale Gaussian Processes for Atmospheric Parameter Retrieval and Cloud Screening

NASA Astrophysics Data System (ADS)

Camps-Valls, G.; Gomez-Chova, L.; Mateo, G.; Laparra, V.; Perez-Suay, A.; Munoz-Mari, J.

2017-12-01

Current Earth-observation (EO) applications for image classification have to deal with an unprecedented big amount of heterogeneous and complex data sources. Spatio-temporally explicit classification methods are a requirement in a variety of Earth system data processing applications. Upcoming missions such as the super-spectral Copernicus Sentinels EnMAP and FLEX will soon provide unprecedented data streams. Very high resolution (VHR) sensors like Worldview-3 also pose big challenges to data processing. The challenge is not only attached to optical sensors but also to infrared sounders and radar images which increased in spectral, spatial and temporal resolution. Besides, we should not forget the availability of the extremely large remote sensing data archives already collected by several past missions, such ENVISAT, Cosmo-SkyMED, Landsat, SPOT, or Seviri/MSG. These large-scale data problems require enhanced processing techniques that should be accurate, robust and fast. Standard parameter retrieval and classification algorithms cannot cope with this new scenario efficiently. In this work, we review the field of large scale kernel methods for both atmospheric parameter retrieval and cloud detection using infrared sounding IASI data and optical Seviri/MSG imagery. We propose novel Gaussian Processes (GPs) to train problems with millions of instances and high number of input features. Algorithms can cope with non-linearities efficiently, accommodate multi-output problems, and provide confidence intervals for the predictions. Several strategies to speed up algorithms are devised: random Fourier features and variational approaches for cloud classification using IASI data and Seviri/MSG, and engineered randomized kernel functions and emulation in temperature, moisture and ozone atmospheric profile retrieval from IASI as a proxy to the upcoming MTG-IRS sensor. Excellent compromise between accuracy and scalability are obtained in all applications.

Improvements in Near-Terminator and Nocturnal Cloud Masks using Satellite Imager Data over the Atmospheric Radiation Measurement Sites

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

Trepte, Q.Z.; Minnis, P.; Heck, P.W.

2005-03-18

Cloud detection using satellite measurements presents a big challenge near the terminator where the visible (VIS; 0.65 {micro}m) channel becomes less reliable and the reflected solar component of the solar infrared 3.9-{micro}m channel reaches very low signal-to-noise ratio levels. As a result, clouds are underestimated near the terminator and at night over land and ocean in previous Atmospheric Radiation Measurement (ARM) Program cloud retrievals using Geostationary Operational Environmental Satellite (GOES) imager data. Cloud detection near the terminator has always been a challenge. For example, comparisons between the CLAVR-x (Clouds from Advanced Very High Resolution Radiometer [AVHRR]) cloud coverage and Geosciencemore » Laser Altimeter System (GLAS) measurements north of 60{sup o}N indicate significant amounts of missing clouds from AVHRR because this part of the world was near the day/night terminator viewed by AVHRR. Comparisons between MODIS cloud products and GLAS at the same regions also shows the same difficulty in the MODIS cloud retrieval (Pavolonis and Heidinger 2005). Consistent detection of clouds at all times of day is needed to provide reliable cloud and radiation products for ARM and other research efforts involving the modeling of clouds and their interaction with the radiation budget. To minimize inconsistencies between daytime and nighttime retrievals, this paper develops an improved twilight and nighttime cloud mask using GOES-9, 10, and 12 imager data over the ARM sites and the continental United States (CONUS).« less

Improvements in Near-Terminator and Nocturnal Cloud Masks using Satellite Image Data over the Atmospheric Radiation Measurement Sites

NASA Technical Reports Server (NTRS)

Trepte, Q. Z.; Minnis, P.; Heck, R. W.; Palikonda, R.

2005-01-01

Cloud detection using satellite measurements presents a big challenge near the terminator where the visible (VIS; 0.65 (micro)m) channel becomes less reliable and the reflected solar component of the solar infrared 3.9-(micro)m channel reaches very low signal-to-noise ratio levels. As a result, clouds are underestimated near the terminator and at night over land and ocean in previous Atmospheric Radiation Measurement (ARM) Program cloud retrievals using Geostationary Operational Environmental Satellite (GOES) imager data. Cloud detection near the terminator has always been a challenge. For example, comparisons between the CLAVR-x (Clouds from Advanced Very High Resolution Radiometer (AVHRR)) cloud coverage and Geoscience Laser Altimeter System (GLAS) measurements north of 60 degrees N indicate significant amounts of missing clouds from AVHRR because this part of the world was near the day/night terminator viewed by AVHRR. Comparisons between MODIS cloud products and GLAS at the same regions also shows the same difficulty in the MODIS cloud retrieval (Pavolonis and Heidinger 2005). Consistent detection of clouds at all times of day is needed to provide reliable cloud and radiation products for ARM and other research efforts involving the modeling of clouds and their interaction with the radiation budget. To minimize inconsistencies between daytime and nighttime retrievals, this paper develops an improved twilight and nighttime cloud mask using GOES-9, 10, and 12 imager data over the ARM sites and the continental United States (CONUS).

Summertime Coincident Observations of Ice Water Path in the Visible/Near-IR, Radar, and Microwave Frequencies

NASA Technical Reports Server (NTRS)

Pittman, Jasna V.; Robertson, Franklin R.; Atkinson, Robert J.

2008-01-01

Accurate representation of the physical and radiative properties of clouds in climate models continues to be a challenge. At present, both remote sensing observations and modeling of microphysical properties of clouds rely heavily on parameterizations or assumptions on particle size distribution (PSD) and cloud phase. In this study, we compare Ice Water Path (IWP), an important physical and radiative property that provides the amount of ice present in a cloud column, using measurements obtained via three different retrieval strategies. The datasets we use in this study include Visible/Near-IR IWP from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument flying aboard the Aqua satellite, Radar-only IWP from the CloudSat instrument operating at 94 GHz, and NOAA/NESDIS operational IWP from the 89 and 157 GHz channels of the Microwave Humidity Sounder (MHS) instrument flying aboard the NOAA-18 satellite. In the Visible/Near-IR, IWP is derived from observations of optical thickness and effective radius. CloudSat IWP is determined from measurements of cloud backscatter and assumed PSD. MHS IWP retrievals depend on scattering measurements at two different, non-water absorbing channels, 89 and 157 GHz. In order to compare IWP obtained from these different techniques and collected at different vertical and horizontal resolutions, we examine summertime cases in the tropics (30S - 30N) when all 3 satellites are within 4 minutes of each other (approximately 1500 km). All measurements are then gridded to a common 15 km x 15 km box determined by MHS. In a grid box comparison, we find CloudSat to report the highest IWP followed by MODIS, followed by MHS. In a statistical comparison, probability density distributions show MHS with the highest frequencies at IWP of 100-1000 g/m(exp 2) and CloudSat with the longest tail reporting IWP of several thousands g/m(exp 2). For IWP greater than 30 g/m(exp 2), MODIS is consistently higher than CloudSat, and it is higher at the lower IWPs but lower at the higher IWPs that overlap with MHS. Some of these differences can be attributed to the limitations of the measuring techniques themselves, but some can result from the assumptions made in the algorithms that generate the IWP product. We investigate this issue by creating categories based on various conditions such as cloud type, precipitation presence, underlying liquid water content, and surface type (land vs. ocean) and by comparing the performance of the IWP products under each condition.

Aerosol Retrievals over the Ocean using Channel 1 and 2 AVHRR Data: A Sensitivity Analysis and Preliminary Results

NASA Technical Reports Server (NTRS)

Mishchenko, Michael I.; Geogdzhayev, Igor V.; Cairns, Brian; Rossow, William B.; Lacis, Andrew A.

1999-01-01

This paper outlines the methodology of interpreting channel 1 and 2 AVHRR radiance data over the oceans and describes a detailed analysis of the sensitivity of monthly averages of retrieved aerosol parameters to the assumptions made in different retrieval algorithms. The analysis is based on using real AVHRR data and exploiting accurate numerical techniques for computing single and multiple scattering and spectral absorption of light in the vertically inhomogeneous atmosphere-ocean system. We show that two-channel algorithms can be expected to provide significantly more accurate and less biased retrievals of the aerosol optical thickness than one-channel algorithms and that imperfect cloud screening and calibration uncertainties are by far the largest sources of errors in the retrieved aerosol parameters. Both underestimating and overestimating aerosol absorption as well as the potentially strong variability of the real part of the aerosol refractive index may lead to regional and/or seasonal biases in optical thickness retrievals. The Angstrom exponent appears to be the most invariant aerosol size characteristic and should be retrieved along with optical thickness as the second aerosol parameter.

Optical and microphysical parameters of dense stratocumulus clouds during mission 206 of EUCREX '94 as retrieved from measurements made with the airborne lidar LEANDRE 1

NASA Astrophysics Data System (ADS)

Pelon, J.; Flamant, C.; Trouillet, V.; Flamant, P. H.

Cloud parameters derived from measurements performed with the airborne backscatter lidar LEANDRE 1 during mission 206 of the EUCREX '94 campaign are reported. A new method has been developed to retrieve the extinction coefficient at the top of the dense stratocumulus deck under scrutiny during this mission. The largest extinction values are found to be related to the highest cloud top altitude revealing the small-scale structure of vertical motions within the stratocumulus field. Cloud optical depth (COD) is estimated from extinction retrievals, as well as cloud top and cloud base altitude using nadir and zenith lidar observations, respectively. Lidar-derived CODs are compared with CODs deduced from radiometric measurements made onboard the French research aircraft Avion de Recherche Atmosphérique et de Télédétection (ARAT/F27). A fair agreement is obtained (within 20%) for COD's larger than 10. Our results show the potential of lidar measurements to analyze cloud properties at optical depths larger than 5.

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.

The Dependence of Homo- and Heterogeneously Formed Cirrus Clouds on Latitude, Season and Surface-type based on a New CALIPSO Remote Sensing Method

NASA Astrophysics Data System (ADS)

Mitchell, D. L.; Garnier, A.; Mejia, J.; Avery, M. A.; Erfani, E.

2016-12-01

A new CALIPSO infrared retrieval method sensitive to small ice crystals has been developed to measure the temperature dependence of the layer-average number concentration N, effective diameter De and ice water content in single-layer cirrus clouds (one cloud layer in the atmospheric column) that have optical depths between 0.3 and 3.0 and cloud base temperature T < 235 K. While retrievals of low N are not accurate, mid-to-high N can be retrieved with much lower uncertainty. This enables the retrieval to estimate the dominant ice nucleation mechanism (homo- or heterogeneous, henceforth hom and het) though which the cirrus formed. Based on N, hom or het cirrus can be estimated as a function of temperature, season, latitude and surface type. The retrieved properties noted above compare favorably with spatial-temporal coincident cirrus cloud in situ measurements from SPARTICUS case studies as well as the extensive in situ cirrus data set of Krämer et al. (2009, ACP). For our cirrus cloud selection, these retrievals show a pronounced seasonal cycle in the N. Hemisphere over land north of 30°N latitude in terms of both cloud amount and microphysics, with greater cloud cover, higher N and smaller De during the winter season. We postulate that this is partially due to the seasonal cycle of deep convection that replenishes the supply of ice nuclei (IN) at cirrus levels, with hom more likely when deep convection is absent. Over oceans, heterogeneous ice nucleation appears to prevail based on the lower N and higher De observed. Due to the relatively smooth ocean surface, lower amplitude atmospheric waves at cirrus cloud levels are expected. Over land outside the tropics during winter, hom cirrus tend to occur over mountainous terrain, possibly due to lower IN concentrations and stronger, more sustained updrafts in mountain-induced waves. Over pristine Antarctica, IN concentrations are minimal and the terrain near the coast is often high and rugged, allowing hom to dominate. Accordingly, over Antarctica cirrus clouds exhibit relatively high N and small De throughout the year. These retrievals allow us to parameterize De and the ice fall speed in CAM5 as a function of T, season, latitude and surface-type. Our goal is to estimate the radiative impact of hom cirrus north of 30°N latitude in winter relative to het cirrus before the AGU Fall Meeting.

Comparison of Marine Boundary Layer Cloud Properties From CERES-MODIS Edition 4 and DOE ARM AMF Measurements at the Azores

NASA Astrophysics Data System (ADS)

Dong, X.; Xi, B.; Minnis, P.; Sun-Mack, S.

2014-12-01

Marine Boundary Layer (MBL) cloud properties derived for the NASA CERES Project using Terra and Aqua MODIS data are compared with observations taken at DOE ARM Mobile Facility at the Azores site from Jun. 2009 to Dec. 2010. Cloud properties derived from ARM ground-based observations were averaged over a 1-hour interval centered at the satellite overpass time, while the CERES-MODIS (CM) results were averaged within a 30×30 km2 grid box centered over the Azores site. A total of 63 daytime and 92 nighttime single-layered overcast MBL cloud cases were selected from 19 months of ARM radar-lidar and satellite observations. The CM cloud-top/base heights (Htop/Hbase) were determined from cloud-top/base temperatures (Ttop/Tbase) using a regional boundary-layer lapse rate method. For daytime comparisons, the CM-derived Htop (Hbase), on average, is 0.063 km (0.068 km) higher (lower) than its ARM radar-lidar observed counterpart, and the CM-derived Ttop and Tbase are 0.9 K less and 2.5 K greater than the surface values with high correlations (R2=0.82 and 0.84, respectively). In general, the cloud-top comparisons agree better than cloud-base comparisons because the CM Tbase and Hbase are secondary product determined from Ttop and Htop. No significant day-night difference was found in the analyses. The comparisons of microphysical properties reveal that, when averaged over a 30x30 km2 area, the CM-retrieved cloud-droplet effective radius (re) is 1.3 µm larger than that from the ARM retrievals (12.8 µm). While the CM-retrieved cloud liquid water path (LWP) is 13.5 gm-2 less than its ARM counterpart (114.2 gm-2) due to its small optical depth (τ, 9.6 vs. 13.7). The differences are reduced by 50% when the CM averages are computed only using the MODIS pixel nearest the AMF site. Using effective radius retrieved at 2.1-µm channel to calculate LWP can reduce the difference between the CM and ARM from -13.7 to 2.1 gm-2. The 10% differences between the ARM and CM LWP and re retrievals are within the uncertainties of the ARM LWP (~ 20 gm-2) and re (~ 10%) retrievals, however, the 30% difference in τ is significant. Possible reasons contributed to this discrepancy increased sensitivities in τ from both surface retrievals when τ ~ 10 and topography. The τ differences vary with wind direction and are consistent with the island orography.

MISR 17.6 KM Gridded Cloud Motion Vectors: Overview and Assessment

NASA Technical Reports Server (NTRS)

Mueller, Kevin; Garay, Michael; Moroney, Catherine; Jovanovic, Veljko

2012-01-01

The MISR (Multi-angle Imaging SpectroRadiometer) instrument on the Terra satellite has been retrieving cloud motion vectors (CMVs) globally and almost continuously since early in 2000. In February 2012 the new MISR Level 2 Cloud product was publicly released, providing cloud motion vectors at 17.6 km resolution with improved accuracy and roughly threefold increased coverage relative to the 70.4 km resolution vectors of the current MISR Level 2 Stereo product (which remains available). MISR retrieves both horizontal cloud motion and height from the apparent displacement due to parallax and movement of cloud features across three visible channel (670nm) camera views over a span of 200 seconds. The retrieval has comparable accuracy to operational atmospheric motion vectors from other current sensors, but holds the additional advantage of global coverage and finer precision height retrieval that is insensitive to radiometric calibration. The MISR mission is expected to continue operation for many more years, possibly until 2019, and Level 2 Cloud has the possibility of being produced with a sensing-to-availability lag of 5 hours. This report compares MISR CMV with collocated motion vectors from arctic rawinsonde sites, and from the GOES and MODISTerra instruments. CMV at heights below 3 km exhibit the smallest differences, as small as 3.3 m/s for MISR and GOES. Clouds above 3 km exhibit larger differences, as large as 8.9 m/s for MISR and MODIS. Typical differences are on the order of 6 m/s.

Evaluation of multi-layer cloud detection based on MODIS CO2-slicing algorithm with CALIPSO-CloudSat measurements.

NASA Astrophysics Data System (ADS)

Viudez-Mora, A.; Kato, S.; Smith, W. L., Jr.; Chang, F. L.

2016-12-01

Knowledge of the vertical cloud distribution is important for a variety of climate and weather applications. The cloud overlapping variations greatly influence the atmospheric heating/cooling rates, with implications for the surface-troposphere radiative balance, global circulation and precipitation. Additionally, an accurate knowledge of the multi-layer cloud distribution in real-time can be used in applications such safety condition for aviation through storms and adverse weather conditions. In this study, we evaluate a multi-layered cloud algorithm (Chang et al. 2005) based on MODIS measurements aboard Aqua satellite (MCF). This algorithm uses the CO2-slicing technique combined with cloud properties determined from VIS, IR and NIR channels to locate high thin clouds over low-level clouds, and retrieve the τ of each layer. We use CALIPSO (Winker et. al, 2010) and CloudSat (Stephens et. al, 2002) (CLCS) derived cloud vertical profiles included in the C3M data product (Kato et al. 2010) to evaluate MCF derived multi-layer cloud properties. We focus on 2 layer overlapping and 1-layer clouds identified by the active sensors and investigate how well these systems are identified by the MODIS multi-layer technique. The results show that for these multi-layered clouds identified by CLCS, the MCF correctly identifies about 83% of the cases as multi-layer. However, it is found that the upper CTH is underestimated by about 2.6±0.4 km, because the CO2-slicing technique is not as sensitive to the cloud physical top as the CLCS. The lower CTH agree better with differences found to be about 1.2±0.5 km. Another outstanding issue for the MCF approach is the large number of multi-layer false alarms that occur in single-layer conditions. References: Chang, F.-L., and Z. Li, 2005: A new method for detection of cirrus overlapping water clouds and determination of their optical properties. J. Atmos. Sci., 62. Kato, S., et al. (2010), Relationships among cloud occurrence frequency, overlap, and effective thickness derived from CALIPSO and CloudSat merged cloud vertical profiles, J. Geophys. Res., 115. Stephens, G. L., et al. (2002), The CloudSat mission and A-Train, Bull. Am. Meteorol. Soc., 83. Winker, D. M., et al., 2010: The CALIPSO Mission: A global 3D view of aerosols and clouds. Bull. Amer. Meteor. Soc., 91.

Cloud Photogrammetry from Space

NASA Astrophysics Data System (ADS)

Zaksek, K.; Gerst, A.; von der Lieth, J.; Ganci, G.; Hort, M.

2015-04-01

The most commonly used method for satellite cloud top height (CTH) compares brightness temperature of the cloud with the atmospheric temperature profile. Because of the uncertainties of this method, we propose a photogrammetric approach. As clouds can move with high velocities, even instruments with multiple cameras are not appropriate for accurate CTH estimation. Here we present two solutions. The first is based on the parallax between data retrieved from geostationary (SEVIRI, HRV band; 1000 m spatial resolution) and polar orbiting satellites (MODIS, band 1; 250 m spatial resolution). The procedure works well if the data from both satellites are retrieved nearly simultaneously. However, MODIS does not retrieve the data at exactly the same time as SEVIRI. To compensate for advection in the atmosphere we use two sequential SEVIRI images (one before and one after the MODIS retrieval) and interpolate the cloud position from SEVIRI data to the time of MODIS retrieval. CTH is then estimated by intersection of corresponding lines-of-view from MODIS and interpolated SEVIRI data. The second method is based on NASA program Crew Earth observations from the International Space Station (ISS). The ISS has a lower orbit than most operational satellites, resulting in a shorter minimal time between two images, which is needed to produce a suitable parallax. In addition, images made by the ISS crew are taken by a full frame sensor and not a push broom scanner that most operational satellites use. Such data make it possible to observe also short time evolution of clouds.

Quantifying Uncertainties in Mass-Dimensional Relationships Through a Comparison Between CloudSat and SPartICus Reflectivity Factors

NASA Astrophysics Data System (ADS)

Mascio, J.; Mace, G. G.

2015-12-01

CloudSat and CALIPSO, two of the satellites in the A-Train constellation, use algorithms to calculate the scattering properties of small cloud particles, such as the T-matrix method. Ice clouds (i.e. cirrus) cause problems with these cloud property retrieval algorithms because of their variability in ice mass as a function of particle size. Assumptions regarding the microphysical properties, such as mass-dimensional (m-D) relationships, are often necessary in retrieval algorithms for simplification, but these assumptions create uncertainties of their own. Therefore, ice cloud property retrieval uncertainties can be substantial and are often not well known. To investigate these uncertainties, reflectivity factors measured by CloudSat are compared to those calculated from particle size distributions (PSDs) to which different m-D relationships are applied. These PSDs are from data collected in situ during three flights of the Small Particles in Cirrus (SPartICus) campaign. We find that no specific habit emerges as preferred and instead we conclude that the microphysical characteristics of ice crystal populations tend to be distributed over a continuum and, therefore, cannot be categorized easily. To quantify the uncertainties in the mass-dimensional relationships, an optimal estimation inversion was run to retrieve the m-D relationship per SPartICus flight, as well as to calculate uncertainties of the m-D power law.

Statistical evaluation of the feasibility of satellite-retrieved cloud parameters as indicators of PM2.5 levels.

PubMed

Yu, Chao; Di Girolamo, Larry; Chen, Liangfu; Zhang, Xueying; Liu, Yang

2015-01-01

The spatial and temporal characteristics of fine particulate matter (PM2.5, particulate matter <2.5 μm in aerodynamic diameter) are increasingly being studied from satellite aerosol remote sensing data. However, cloud cover severely limits the coverage of satellite-driven PM2.5 models, and little research has been conducted on the association between cloud properties and PM2.5 levels. In this study, we analyzed the relationships between ground PM2.5 concentrations and two satellite-retrieved cloud parameters using data from the Southeastern Aerosol Research and Characterization (SEARCH) Network during 2000-2010. We found that both satellite-retrieved cloud fraction (CF) and cloud optical thickness (COT) are negatively associated with PM2.5 levels. PM2.5 speciation and meteorological analysis suggested that the main reason for these negative relationships might be the decreased secondary particle generation. Stratified analyses by season, land use type, and site location showed that seasonal impacts on this relationship are significant. These associations do not vary substantially between urban and rural sites or inland and coastal sites. The statistically significant negative associations of PM2.5 mass concentrations with CF and COT suggest that satellite-retrieved cloud parameters have the potential to serve as predictors to fill the data gap left by satellite aerosol optical depth in satellite-driven PM2.5 models.

Global observations of aerosol-cloud-precipitation-climate interactions

NASA Astrophysics Data System (ADS)

Rosenfeld, Daniel; Andreae, Meinrat O.; Asmi, Ari; Chin, Mian; de Leeuw, Gerrit; Donovan, David P.; Kahn, Ralph; Kinne, Stefan; Kivekäs, Niku; Kulmala, Markku; Lau, William; Schmidt, K. Sebastian; Suni, Tanja; Wagner, Thomas; Wild, Martin; Quaas, Johannes

2014-12-01

Cloud drop condensation nuclei (CCN) and ice nuclei (IN) particles determine to a large extent cloud microstructure and, consequently, cloud albedo and the dynamic response of clouds to aerosol-induced changes to precipitation. This can modify the reflected solar radiation and the thermal radiation emitted to space. Measurements of tropospheric CCN and IN over large areas have not been possible and can be only roughly approximated from satellite-sensor-based estimates of optical properties of aerosols. Our lack of ability to measure both CCN and cloud updrafts precludes disentangling the effects of meteorology from those of aerosols and represents the largest component in our uncertainty in anthropogenic climate forcing. Ways to improve the retrieval accuracy include multiangle and multipolarimetric passive measurements of the optical signal and multispectral lidar polarimetric measurements. Indirect methods include proxies of trace gases, as retrieved by hyperspectral sensors. Perhaps the most promising emerging direction is retrieving the CCN properties by simultaneously retrieving convective cloud drop number concentrations and updraft speeds, which amounts to using clouds as natural CCN chambers. These satellite observations have to be constrained by in situ observations of aerosol-cloud-precipitation-climate (ACPC) interactions, which in turn constrain a hierarchy of model simulations of ACPC. Since the essence of a general circulation model is an accurate quantification of the energy and mass fluxes in all forms between the surface, atmosphere and outer space, a route to progress is proposed here in the form of a series of box flux closure experiments in the various climate regimes. A roadmap is provided for quantifying the ACPC interactions and thereby reducing the uncertainty in anthropogenic climate forcing.

Improving Pixel Level Cloud Optical Property Retrieval using Monte Carlo Simulations

NASA Technical Reports Server (NTRS)

Oreopoulos, Lazaros; Marshak, Alexander; Cahalan, Robert F.

1999-01-01

The accurate pixel-by-pixel retrieval of cloud optical properties from space is influenced by radiative smoothing due to high order photon scattering and radiative roughening due to low order scattering events. Both are caused by cloud heterogeneity and the three-dimensional nature of radiative transfer and can be studied with the aid of computer simulations. We use Monte Carlo simulations on variable 1-D and 2-D model cloud fields to seek for dependencies of smoothing and roughening phenomena on single scattering albedo, solar zenith angle, and cloud characteristics. The results are discussed in the context of high resolution satellite (such as Landsat) retrieval applications. The current work extends the investigation on the inverse NIPA (Non-local Independent Pixel Approximation) as a tool for removing smoothing and improving retrievals of cloud optical depth. This is accomplished by: (1) Delineating the limits of NIPA applicability; (2) Exploring NIPA parameter dependences on cloud macrostructural features, such as mean cloud optical depth and geometrical thickness, degree of extinction and cloud top height variability. We also compare parameter values from empirical and theoretical considerations; (3) Examining the differences between applying NIPA on radiation quantities vs direct application on optical properties; (4) Studying the radiation budget importance of the NIPA corrections as a function of scale. Finally, we discuss fundamental adjustments that need to be considered for successful radiance inversion at non-conservative wavelengths and oblique Sun angles. These adjustments are necessary to remove roughening signatures which become more prominent with increasing absorption and solar zenith angle.

Submillimeter-Wave Cloud Ice Radiometry

NASA Technical Reports Server (NTRS)

Walter, Steven J.

1999-01-01

Submillimeter-wave cloud ice radiometry is a new and innovative technique for characterizing cirrus ice clouds. Cirrus clouds affect Earth's climate and hydrological cycle by reflecting incoming solar energy, trapping outgoing IR radiation, sublimating into vapor, and influencing atmospheric circulation. Since uncertainties in the global distribution of cloud ice restrict the accuracy of both climate and weather models, successful development of this technique could provide a valuable tool for investigating how clouds affect climate and weather. Cloud ice radiometry could fill an important gap in the observational capabilities of existing and planned Earth-observing systems. Using submillimeter-wave radiometry to retrieve properties of ice clouds can be understood with a simple model. There are a number of submillimeter-wavelength spectral regions where the upper troposphere is transparent. At lower tropospheric altitudes water vapor emits a relatively uniform flux of thermal radiation. When cirrus clouds are present, they scatter a portion of the upwelling flux of submillimeter-wavelength radiation back towards the Earth as shown in the diagram, thus reducing the upward flux o f energy. Hence, the power received by a down-looking radiometer decreases when a cirrus cloud passes through the field of view causing the cirrus cloud to appear radiatively cool against the warm lower atmospheric thermal emissions. The reduction in upwelling thermal flux is a function of both the total cloud ice content and mean crystal size. Radiometric measurements made at multiple widely spaced frequencies permit flux variations caused by changes in crystal size to be distinguished from changes in ice content, and polarized measurements can be used to constrain mean crystal shape. The goal of the cloud ice radiometry program is to further develop and validate this technique of characterizing cirrus. A multi-frequency radiometer is being designed to support airborne science and spacecraft validation missions. This program has already extended the initial millimeter-wave modeling studies to submillimeter-wavelengths and has improved the realism of the cloud scattering models. Additionally a proof-of-concept airborne submillimeter-wave radiometer was constructed and fielded. It measured a radiometric signal from cirrus confirming the basic technical feasibility of this technique. This program is a cooperative effort of the University of Colorado, Colorado State University, Swales Aerospace, and Jet Propulsion Laboratory. Additional information is contained in the original.

Stereoscopic Height and Wind Retrievals for Aerosol Plumes with the MISR INteractive eXplorer (MINX)

NASA Technical Reports Server (NTRS)

Nelson, D.L.; Garay, M.J.; Kahn, Ralph A.; Dunst, Ben A.

2013-01-01

The Multi-angle Imaging SpectroRadiometer (MISR) instrument aboard the Terra satellite acquires imagery at 275-m resolution at nine angles ranging from 0deg (nadir) to 70deg off-nadir. This multi-angle capability facilitates the stereoscopic retrieval of heights and motion vectors for clouds and aerosol plumes. MISR's operational stereo product uses this capability to retrieve cloud heights and winds for every satellite orbit, yielding global coverage every nine days. The MISR INteractive eXplorer (MINX) visualization and analysis tool complements the operational stereo product by providing users the ability to retrieve heights and winds locally for detailed studies of smoke, dust and volcanic ash plumes, as well as clouds, at higher spatial resolution and with greater precision than is possible with the operational product or with other space-based, passive, remote sensing instruments. This ability to investigate plume geometry and dynamics is becoming increasingly important as climate and air quality studies require greater knowledge about the injection of aerosols and the location of clouds within the atmosphere. MINX incorporates features that allow users to customize their stereo retrievals for optimum results under varying aerosol and underlying surface conditions. This paper discusses the stereo retrieval algorithms and retrieval options in MINX, and provides appropriate examples to explain how the program can be used to achieve the best results.

Understanding Differences Between Co-Incident CloudSat, Aqua/MODIS and NOAA18 MHS Ice water Path Retrievals Over the Tropical Oceans

NASA Technical Reports Server (NTRS)

Pittman, Jasna; Robertson, Franklin; Blankenship, Clay

2008-01-01

Accurate measurement of the physical and radiative properties of clouds and their representation in climate models continues to be a challe nge. Model parameterizations are still subject to a large number of t unable parameters; furthermore, accurate and representative in situ o bservations are very sparse, and satellite observations historically have significant quantitative uncertainties, particularly with respect to particle size distribution (PSD) and cloud phase. Ice Water Path (IWP), or amount of ice present in a cloud column, is an important cl oud property to accurately quantify, because it is an integral measur e of the microphysical properties of clouds and the cloud feedback pr ocesses in the climate system. This paper investigates near co-incident retrievals of IWP over tropical oceans using three diverse measurem ent systems: radar from CloudSat, Vis/IR from Aqua/MODIS, and microwa ve from NOAA-18IMHS. CloudSat 94 GHz radar measurements provide high resolution vertical and along-orbit structure of cloud reflectivity a nd enable IWP (and IWC) retrievals. Overlapping MODIS measurements of cloud optical thickness and phase allow estimates of IWP when cloud tops are identified as being ice. Periodically, NOAA18 becomes co-inci dent in space I time to enable comparison of A-Train measurements to IWP inferred from the 157 and 89 GHz channel radiances. This latter m easurement is effective only for thick convective anvil systems. We s tratify these co-incident data (less than 4 minutes separation) into cirrus only, cirrus overlying liquid water clouds, and precipitating d eep convective clouds. Substantial biases in IWP and ice effective ra dius are found. Systematic differences in these retrievals are consid ered in light of the uncertainties in a priori assumptions ofPSDs, sp ectral sensitivity and algorithm strategies, which have a direct impact on the IWP product.

Development of a cloud-screening method for MAX-DOAS measurements

NASA Astrophysics Data System (ADS)

Gielen, Clio; Van Roozendael, Michel; Hendrik, Francois; Fayt, Caroline; Hermans, Christian; Pinardi, Gaia; Vlemmix, Tim

2013-04-01

In recent years, ground-based multi-axis differential absorption spectroscopy (MAX-DOAS) has shown to be ideally suited for the retrieval of tropospheric trace gases and deriving information on the aerosol properties. These measurements are invaluable to our understanding of the physics and chemistry of the atmospheric system, and the impact on the Earth's climate. Unfortunately, MAX-DOAS measurements are often performed under (partially) cloudy conditions, causing data quality degradation and higher uncertainties on the retrievals. A high aerosol load and/or a strong cloud cover can introduce additional photon absorption or multiple scattering. The first effect strongly impacts the retrieved differential slant columns (DSCDs) of the trace gases, leading to an underestimation of the atmospheric column density. Multiple scattering, on the other hand, becomes important for low clouds with a high optical depth, and cause a strong increase in the retrieved trace gas DSCDs. The presence of thin clouds can furthermore introduce a degeneracy in the retrieved aerosol optical depth, since they will have similar effect on the MAX-DOAS measurements. In this case, only information on the trace gas DSCDs can be successfully retrieved. If the cloud cover consists of broken or scattered clouds, the MAX-DOAS method becomes very unstable, since the different elevation angels will probe regions of the sky with strongly deviating properties. Here we present a method to qualify the sky and cloud conditions, using the colour index and O4 DSCDs, as derived from the MAX-DOAS measurements. The colour index is defined as the ratio of the intensities at the short- and long-wavelength part of the visible spectral range, typically at 400 nm and 670 nm. For increasing optical thickness due to clouds or aerosols, the colour index values decrease and values for different elevation angles converge. In the case of broken clouds, the colour index shows a strong and rapid temporal variation, which is easily detectable. Additional information is derived from the O4 DSCD measurements, since they are quite sensitive to the change of the light paths due to scattering at different altitudes. For example, thick clouds at low altitude show a very strong increase in the DSCD values due to scattering, combined with a low colour index value due to the intensity screening. In general, our method shows promising results to qualify the sky and cloud conditions of MAX- DOAS measurements, without the need for other external cloud-detection systems such as Brewer instruments or pyrheliometers.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Applications of the Hyper Angular Rainbow Polarimeter (HARP) instrument from aircraft and from space

NASA Astrophysics Data System (ADS)

Martins, J. V.; Fernandez Borda, R. A.; McBride, B.; Remer, L. A.; Barbosa, H. M.; Dubovik, O.

2017-12-01

The remote sensing of aerosol and cloud microphysics is essential for the global assessment of aerosol and cloud properties. Current spectral techniques utilized by MODIS, VIIRS and similar sensors lack details on the retrieval of the cloud and aerosol particle microphysical properties desired by the scientific community. Multi-spectral hyperangular polarization measurements provide enough information for this additional microphysical retrievals. The HARP (HyperAngular Rainbow Polarimeter) is a compact and modular imaging instrument with wide Field Of View (94 deg cross track and up to 114 degrees along track) and up to 60 along track viewing angles. Spectrally, HARP is envisioned to have modules in the UV, VNIR and SWIR ranges. Currently there are two existing HARP VNIR sensors, for airborne (AirHARP) and space-borne applications respectively, both with 4 wavelengths centered at 440, 550, 670, and 865nm. The space-borne HARP sensor has been designed for a 3U CubeSat satellite currently scheduled for launch to the International Space Station in January 2018 and to be released as a free flying satellite shortly after. At this orbit HARP will provide pixel resolution at the ground of about 400m, which will be binned to coarse resolutions (e.g. 2.5 Km) for data rate reduction. The AirHARP instrument has recently flown in the NASA Langley UC12 aircraft during the LMOS (Lake Michigan Ozone Study) collecting a large data set on aerosol, clouds, and surface properties. AirHARP will also fly in the ACEPOL campaign on board the NASA ER2 aircraft in October/November 2017. These campaigns are supporting HARP's algorithm development and validation in preparation to HARP's Cubesat launch and possibly other HARP space-borne missions. This presentation will describe details of the HARP and AirHARP instruments, as well and preliminary results with level 1 and level 2 data collected during the LMOS and the ACEPOL aircraft campaigns showing clouds and aerosol retrieval results.

Vertical profile of cloud optical parameters derived from airborne measurements above, inside and below clouds

NASA Astrophysics Data System (ADS)

Melnikova, Irina; Gatebe, Charles K.

2018-07-01

Past strategies for retrieving cloud optical properties from remote sensing assumed significant limits for desired parameters such as semi-infinite optical thickness, single scattering albedo equaling unity (non-absorbing scattering), absence of spectral dependence of the optical thickness, etc., and only one optical parameter could be retrieved (either optical thickness or single scattering albedo). Here, we demonstrate a new method based on asymptotic theory for thick atmospheres, and the presence of a diffusion domain within the clouds that does not put restrictions and makes it possible to get two or even three optical parameters (optical thickness, single scattering albedo and phase function asymmetry parameter) for every wavelength independently. We applied this method to measurements of angular distribution of solar radiation above, inside and below clouds, obtained with NASA's Cloud Absorption Radiometer (CAR) over two cases of marine stratocumulus clouds; first case, offshore of Namibia and the second case, offshore of California. The observational and retrieval errors are accounted for by regularization, which allows stable and smooth solutions. Results show good potential for parameterization of the shortwave radiative properties (reflection, transmission, radiative divergence and heating rate) of water clouds.

A new retrieval method for the ice water content of cirrus using data from the CloudSat and CALIPSO

NASA Astrophysics Data System (ADS)

Pan, Honglin; Bu, Lingbing; Kumar, K. Raghavendra; Gao, Haiyang; Huang, Xingyou; Zhang, Wentao

2017-08-01

The CloudSat and CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) are the members of satellite observation system of A-train to achieve the quasi-synchronization observation on the same orbit. With the help of active (CALIOP and CPR) and passive payloads from these two satellites, respectively, unprecedented detailed information of microphysical properties of ice cloud can be retrieved. The ice water content (IWC) is regarded as one of the most important microphysical characteristics of cirrus for its prominent role in cloud radiative forcing. In this paper, we proposed a new joint (Combination) retrieval method using the full advantages of different well established retrieval methods, namely the LIDAR method (for the region Lidar-only), the MWCR method (for the region Radar-only), and Wang method (for the region Lidar-Radar) proposed by Wang et al. (2002). In retrieval of cirrus IWC, empirical formulas of the exponential type were used for both thinner cirrus (detected by Lidar-only), thicker cirrus (detected by radar-only), and the part of cirrus detected by both, respectively. In the present study, the comparison of various methods verified that our proposed new joint method is more comprehensive, rational and reliable. Further, the retrieval information of cirrus is complete and accurate for the region that Lidar cannot penetrate and Radar is insensitive. On the whole, the retrieval results of IWC showed certain differences retrieved from the joint method, Ca&Cl, and ICARE which can be interpreted from the different hypothesis of microphysical characteristics and parameters used in the retrieval method. In addition, our joint method only uses the extinction coefficient and the radar reflectivity factor to calculate the IWC, which is simpler and reduces to some extent the accumulative error. In future studies, we will not only compare the value of IWC but also explore the detailed macrophysical and microphysical characteristics of cirrus.

Relationship Between Cirrus Particle Size and Cloud Top Temperature

NASA Technical Reports Server (NTRS)

Han, Qingyuan; Chou, Joyce; Welch, Ronald M.

1997-01-01

The relationship between cirrus particle size and cloud top temperature is surveyed on a near-global scale. The cirrus particle size is retrieved assuming ice crystals are hexagonal columns and the cloud top temperature and the radiances in channel 1 and 3 of AVHRR used to retrieve ice particle sizes are from ISCCP product. The results show that for thick clouds over North America, the relation between particle size and cloud top temperature is consistent with a summary of this relationship based on aircraft measurement over that region for thick clouds. However, this relationship is not universal for other regions especially for for tropical zone, which has been found by other in situ measurements.

Atmospheric State, Cloud Microphysics and Radiative Flux

DOE Data Explorer

Mace, Gerald

2008-01-15

Atmospheric thermodynamics, cloud properties, radiative fluxes and radiative heating rates for the ARM Southern Great Plains (SGP) site. The data represent a characterization of the physical state of the atmospheric column compiled on a five-minute temporal and 90m vertical grid. Sources for this information include raw measurements, cloud property and radiative retrievals, retrievals and derived variables from other third-party sources, and radiative calculations using the derived quantities.

New Cloud and Precipitation Research Avenues Enabled by low-cost Phased-array Radar Technology

NASA Astrophysics Data System (ADS)

Kollias, P.; Oue, M.; Fridlind, A. M.; Matsui, T.; McLaughlin, D. J.

2017-12-01

For over half a century, radars operating in a wide range of frequencies have been the primary source of observational insights of clouds and precipitation microphysics and dynamics and contributed to numerous significant advancements in the field of cloud and precipitation physics. The development of multi-wavelength and polarization diversity techniques has further strengthened the quality of microphysical and dynamical retrievals from radars and has assisted in overcoming some of the limitations imposed by the physics of scattering. Atmospheric radars have historically employed a mechanically-scanning dish antenna and their ability to point to, survey, and revisit specific points or regions in the atmosphere is limited by mechanical inertia. Electronically scanned, or phased-array, radars capable of high-speed, inertialess beam steering, have been available for several decades, but the cost of this technology has limited its use to military applications. During the last 10 years, lower power and lower-cost versions of electronically scanning radars have been developed, and this presents an attractive and affordable new tool for the atmospheric sciences. The operational and research communities are currently exploring phased array advantages in signal processing (i.e. beam multiplexing, improved clutter rejection, cross beam wind estimation, adaptive sensing) and science applications (i.e. tornadic storm morphology studies). Here, we will present some areas of atmospheric research where inertia-less radars with ability to provide rapid volume imaging offers the potential to advance cloud and precipitation research. We will discuss the added value of single phased-array radars as well as networks of these radars for several problems including: multi-Doppler wind retrieval techniques, cloud lifetime studies and aerosol-convection interactions. The performance of current (dish) and future (e-scan) radar systems for these atmospheric studies will be evaluated using numerical model output and a sophisticated radar simulator package.

An integrated multi-sensors approach for volcanic cloud retrievals and source characterization

NASA Astrophysics Data System (ADS)

Corradini, Stefano; Merucci, Luca

2017-04-01

Volcanic eruptions are one the most important sources of natural pollution. In particular the volcanic clouds represent a severe threat for aviation safety. Worldwide the volcanic activity is monitored by using satellite and ground-based instruments working at different spectral ranges, with different spatial resolutions and sensitivities. Here the complementarity between geostationary and polar satellites and ground based measurements is exploited, in order to significantly improve the volcanic cloud detection and retrievals and to fully characterize the eruption source. The integration procedure named MACE (Multi-platform volcanic Ash Cloud Estimation), has been developed during the EU-FP7 APhoRISM project aimed to develop innovative products to support the management and mitigation of the volcanic and the seismic crisis. The proposed method integrates in a novel manner the volcanic ash retrievals at the space-time scale of typical geostationary observations using both the polar satellite estimations and in-situ measurements. On MACE the typical volcanic cloud retrievals in the thermal infrared are integrated by using a wider spectral range from visible to microwave. Moreover the volcanic cloud detection is extended in case of cloudy atmosphere or steam plumes. As example, the integrated approach is tested on different recent eruptions, occurred on Etna (Italy) in 2013 and 2015 and on Calbuco (Chile) in 2015.

The Apparent Bluing of Aerosols Near Clouds

NASA Technical Reports Server (NTRS)

Marshak, Alexander

2008-01-01

Numerous studies based on satellite observations have reported that aerosol optical depths increase with increasing cloud cover. Part of the increase comes from the humidification and consequent growth of aerosol particles in the moist cloud environment, but part comes from 3D cloud-radiative transfer effects on the retrieved aerosol properties. Often, discerning whether the observed increases in aerosol optical depths are artifacts or real proves difficult. I describe a simple model that quantifies the enhanced illumination of cloud-free columns in the vicinity of clouds that are used in the aerosol retrievals. This model is based on the assumption that the enhancement in the cloud-free column radiance comes from enhanced Rayleigh scattering that results from the presence of the nearby clouds. This assumption leads to a larger increase of AOT for shorter wavelengths, or to a "bluing" of aerosols near clouds. Examples from the MODIS observations that illustrate the apparent bluing of aerosols near clouds will be discussed.

Estimating cirrus cloud properties from MIPAS data

NASA Astrophysics Data System (ADS)

Mendrok, J.; Schreier, F.; Höpfner, M.

2007-04-01

High resolution mid-infrared limb emission spectra observed by the spaceborne Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) showing evidence of cloud interference are analyzed. Using the new line-by-line multiple scattering [Approximate] Spherical Atmospheric Radiative Transfer code (SARTre), a sensitivity study with respect to cirrus cloud parameters, e.g., optical thickness and particle size distribution, is performed. Cirrus properties are estimated by fitting spectra in three distinct microwindows between 8 and 12 μm. For a cirrus with extremely low ice water path (IWP = 0.1 g/m2) and small effective particle size (D e = 10 μm) simulated spectra are in close agreement with observations in broadband signal and fine structures. We show that a multi-microwindow technique enhances reliability of MIPAS cirrus retrievals compared to single microwindow methods.

Cloud radiative properties and aerosol - cloud interaction

NASA Astrophysics Data System (ADS)

Viviana Vladutescu, Daniela; Gross, Barry; Li, Clement; Han, Zaw

2015-04-01

The presented research discusses different techniques for improvement of cloud properties measurements and analysis. The need for these measurements and analysis arises from the high errors noticed in existing methods that are currently used in retrieving cloud properties and implicitly cloud radiative forcing. The properties investigated are cloud fraction (cf) and cloud optical thickness (COT) measured with a suite of collocated remote sensing instruments. The novel approach makes use of a ground based "poor man's camera" to detect cloud and sky radiation in red, green, and blue with a high spatial resolution of 30 mm at 1km. The surface-based high resolution photography provides a new and interesting view of clouds. As the cloud fraction cannot be uniquely defined or measured, it depends on threshold and resolution. However as resolution decreases, cloud fraction tends to increase if the threshold is below the mean, and vice versa. Additionally cloud fractal dimension also depends on threshold. Therefore these findings raise concerns over the ability to characterize clouds by cloud fraction or fractal dimension. Our analysis indicate that Principal Component analysis may lead to a robust means of quantifying cloud contribution to radiance. The cloud images are analyzed in conjunction with a collocated CIMEL sky radiometer, Microwave Radiometer and LIDAR to determine homogeneity and heterogeneity. Additionally, MFRSR measurements are used to determine the cloud radiative properties as a validation tool to the results obtained from the other instruments and methods. The cloud properties to be further studied are aerosol- cloud interaction, cloud particle radii, and vertical homogeneity.

Preliminary analysis toward GOSAT-2 new products, proxy-based XCH4 and SIF, using GOSAT data

NASA Astrophysics Data System (ADS)

Oshio, H.; Yoshida, Y.; Matsunaga, T.

2017-12-01

The Greenhouse gases Observing SATellite (GOSAT) has been operating for more than eight years. As a successor mission to the GOSAT, GOSAT-2 is planned to be launched in FY2018. In addition to the full-physics based dry air mole fractions of carbon dioxide, methane, water vapor, and carbon monoxide (XCO2, XCH4, XH2O, and XCO) products, we are planning to provide the proxy-based XCH4 and solar induced chlorophyll fluorescence (SIF) as a new product. XCH4 and XCO2 are retrieved from GOSAT CH4 1.67 μm band and CO2 1.6 μm band, respectively, under the clear-sky assumption, and their ratio is compared with TCCON data. As expected, most of the cloud and aerosol related errors are counteracted. During this retrieval, XH2O is simultaneously retrieved with XCO2. XCO2 and XH2O are also retrieved from CO2 2.08 μm band under the clear-sky assumption. Difference between Xgas retrieved from different wavelength domains is expected to be useful as cloud and aerosol information because the difference reflects the degree of optical path variation caused by clouds and aerosols. XCO2 ratio and XH2O ratio are compared to the cloud and aerosol information derived by Cloud and Aerosol Imager (CAI) onboarded GOSAT. SIF is retrieved using Fraunhofer lines near O2 A-band by the same method as Frankenberg et al. (2011). For GOSAT, correction of artifact signal (zero-level offset caused by non-linearity of the analog circuit in the spectrometer) is required to obtain SIF (retrieved signal = SIF + zero-level offset). The zero-level offset can be evaluated from the retrieved signal over the areas where the value of SIF is expected to be zero. Although it is currently unknown that such correction is required for GOSAT-2 SIF retrieval, SIF was retrieved from GOSAT data and zero-level offset correction was tested. We investigated the zero-level offset for clouds and bare soils and confirmed its applicability to the offset correction. Zero-level offset correction was then conducted while considering its temporal change and dependence on the observed radiance. Validity of the derived SIF was investigated through comparison with SIF derived by numerical model.

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Accuracy of Geophysical Parameters Derived from AIRS/AMSU as a Function of Fractional Cloud Cover

NASA Technical Reports Server (NTRS)

Susskind, Joel; Barnet, Chris; Blaisdell, John; Iredell, Lena; Keita, Fricky; Kouvaris, Lou; Molnar, Gyula; Chahine, Moustafa

2006-01-01

AIRS was launched on EOS Aqua on May 4,2002, together with AMSU A and HSB, to form a next generation polar orbiting infrared and microwave atmospheric sounding system. The primary products of AIRS/AMSU are twice daily global fields of atmospheric temperature-humidity profiles, ozone profiles, sea/land surface skin temperature, and cloud related parameters including OLR. The sounding goals of AIRS are to produce 1 km tropospheric layer mean temperatures with an rms error of lK, and layer precipitable water with an rms error of 20 percent, in cases with up to 80 percent effective cloud cover. The basic theory used to analyze Atmospheric InfraRed Sounder/Advanced Microwave Sounding Unit/Humidity Sounder Brazil (AIRS/AMSU/HSB) data in the presence of clouds, called the at-launch algorithm, was described previously. Pre-launch simulation studies using this algorithm indicated that these results should be achievable. Some modifications have been made to the at-launch retrieval algorithm as described in this paper. Sample fields of parameters retrieved from AIRS/AMSU/HSB data are presented and validated as a function of retrieved fractional cloud cover. As in simulation, the degradation of retrieval accuracy with increasing cloud cover is small and the RMS accuracy of lower tropospheric temperature retrieved with 80 percent cloud cover is about 0.5 K poorer than for clear cases. HSB failed in February 2003, and consequently HSB channel radiances are not used in the results shown in this paper. The AIRS/AMSU retrieval algorithm described in this paper, called Version 4, become operational at the Goddard DAAC (Distributed Active Archive Center) in April 2003 and is being used to analyze near-real time AIRS/AMSU data. Historical AIRS/AMSU data, going backwards from March 2005 through September 2002, is also being analyzed by the DAAC using the Version 4 algorithm.

Short-term solar irradiance forecasting via satellite/model coupling

DOE PAGES

Miller, Steven D.; Rogers, Matthew A.; Haynes, John M.; ...

2017-12-01

The short-term (0-3 h) prediction of solar insolation for renewable energy production is a problem well-suited to satellite-based techniques. The spatial, spectral, temporal and radiometric resolution of instrumentation hosted on the geostationary platform allows these satellites to describe the current cloud spatial distribution and optical properties. These properties relate directly to the transient properties of the downwelling solar irradiance at the surface, which come in the form of 'ramps' that pose a central challenge to energy load balancing in a spatially distributed network of solar farms. The short-term evolution of the cloud field may be approximated to first order simplymore » as translational, but care must be taken in how the advection is handled and where the impacts are assigned. In this research, we describe how geostationary satellite observations are used with operational cloud masking and retrieval algorithms, wind field data from Numerical Weather Prediction (NWP), and radiative transfer calculations to produce short-term forecasts of solar insolation for applications in solar power generation. The scheme utilizes retrieved cloud properties to group pixels into contiguous cloud objects whose future positions are predicted using four-dimensional (space + time) model wind fields, selecting steering levels corresponding to the cloud height properties of each cloud group. The shadows associated with these clouds are adjusted for sensor viewing parallax displacement and combined with solar geometry and terrain height to determine the actual location of cloud shadows. For mid/high-level clouds at mid-latitudes and high solar zenith angles, the combined displacements from these geometric considerations are non-negligible. The cloud information is used to initialize a radiative transfer model that computes the direct and diffuse-sky solar insolation at both shadow locations and intervening clear-sky regions. Here, we describe the formulation of the algorithm and validate its performance against Surface Radiation (SURFRAD; Augustine et al., 2000, 2005) network observations. Typical errors range from 8.5% to 17.2% depending on the complexity of cloud regimes, and an operational demonstration outperformed persistence-based forecasting of Global Horizontal Irradiance (GHI) under all conditions by ~10 W/m2.« less

Short-term solar irradiance forecasting via satellite/model coupling

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

Miller, Steven D.; Rogers, Matthew A.; Haynes, John M.

The short-term (0-3 h) prediction of solar insolation for renewable energy production is a problem well-suited to satellite-based techniques. The spatial, spectral, temporal and radiometric resolution of instrumentation hosted on the geostationary platform allows these satellites to describe the current cloud spatial distribution and optical properties. These properties relate directly to the transient properties of the downwelling solar irradiance at the surface, which come in the form of 'ramps' that pose a central challenge to energy load balancing in a spatially distributed network of solar farms. The short-term evolution of the cloud field may be approximated to first order simplymore » as translational, but care must be taken in how the advection is handled and where the impacts are assigned. In this research, we describe how geostationary satellite observations are used with operational cloud masking and retrieval algorithms, wind field data from Numerical Weather Prediction (NWP), and radiative transfer calculations to produce short-term forecasts of solar insolation for applications in solar power generation. The scheme utilizes retrieved cloud properties to group pixels into contiguous cloud objects whose future positions are predicted using four-dimensional (space + time) model wind fields, selecting steering levels corresponding to the cloud height properties of each cloud group. The shadows associated with these clouds are adjusted for sensor viewing parallax displacement and combined with solar geometry and terrain height to determine the actual location of cloud shadows. For mid/high-level clouds at mid-latitudes and high solar zenith angles, the combined displacements from these geometric considerations are non-negligible. The cloud information is used to initialize a radiative transfer model that computes the direct and diffuse-sky solar insolation at both shadow locations and intervening clear-sky regions. Here, we describe the formulation of the algorithm and validate its performance against Surface Radiation (SURFRAD; Augustine et al., 2000, 2005) network observations. Typical errors range from 8.5% to 17.2% depending on the complexity of cloud regimes, and an operational demonstration outperformed persistence-based forecasting of Global Horizontal Irradiance (GHI) under all conditions by ~10 W/m2.« less

Remote measurement of cloud microphysics and its influence in predicting high impact weather events

NASA Astrophysics Data System (ADS)

Bipasha, Paul S.; Jinya, John

2016-05-01

Understanding the cloud microphysical processes and precise retrieval of parameters governing the same are crucial for weather and climate prediction. Advanced remote sensing sensors and techniques offer an opportunity for monitoring micro-level developments in cloud structure. . Using the observations from a visible and near-infrared lidar onboard CALIPSO satellite (part of A-train) , the spatial variation of cloud structure has been studied over the Tropical monsoon region . It is found that there is large variability in the cloud microphysical parameters manifesting in distinct precipitation regimes. In particular, the severe storms over this region are driven by processes which range from the synoptic to the microphysical scale. Using INSAT-3D data, retrieval of cloud microphysical parameters like effective radius (CER) and optical depth (COD) were carried out for tropical cyclone Phailine. It was observed that there is a general increase of CER in a top-down direction, characterizing the progressively increasing number and size of precipitation hydrometeors while approaching the cloud base. The distribution of CER relative to cloud top temperature for growing convective clouds has been investigated to reveal the evolution of the particles composing the clouds. It is seen that the relatively high concentration of large particles in the downdraft zone is closely related to the precipitation efficiency of the system. Similar study was also carried using MODIS observations for cyclones over Indian Ocean (2010-2013), in which we find that that the mean effective radius is 24 microns with standard deviation 4.56, mean optical depth is 21 with standard deviation 13.98, mean cloud fraction is 0.92 with standard deviation 0.13 and mainly ice phase is dominant. Thus the remote observations of microstructure of convective storms provide very crucial information about the maintenance and potential devastation likely to be associated with it. With the synergistic observations from A-Train , geostationary and futuristic imaging spectroscopic sensors, a multi-dimensional, and multi-scalar exploration of cloud systems is anticipated leading to accurate prediction of high impact weather events.

Estimation of Microphysical and Radiative Parameters of Precipitating Cloud Systems Using mm-Wavelength Radars

NASA Astrophysics Data System (ADS)

Matrosov, Sergey Y.

2009-03-01

A remote sensing approach is described to retrieve cloud and rainfall parameters within the same precipitating system. This approach is based on mm-wavelength radar signal attenuation effects which are observed in a layer of liquid precipitation containing clouds and rainfall. The parameters of ice clouds in the upper part of startiform precipitating systems are then retrieved using the absolute measurements of radar reflectivity. In case of the ground-based radar location, these measurements are corrected for attenuation in the intervening layer of liquid hydrometers.

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

NASA Astrophysics Data System (ADS)

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

2016-03-01

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

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

New Multispectral Cloud Retrievals from MODIS

NASA Technical Reports Server (NTRS)

Platnick, Steven; Tsay, Si-Chee; Ackerman, Steven A.; Gray, Mark A.; Moody, Eric G.; Li, Jason Y.; Arnold, G. T.; King, Michael D. (Technical Monitor)

2000-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) was developed by NASA and launched onboard the Terra spacecraft on December 18, 1999. It achieved its final orbit and began Earth observations on February 24, 2000. MODIS scans a swath width sufficient to provide nearly complete global coverage every two days from a polar-orbiting, sun-synchronous, platform at an altitude of 705 km, and provides images in 36 spectral bands between 0.415 and 14.235 micrometers with spatial resolutions of 250 m (2 bands), 500 m (5 bands) and 1000 m (29 bands). These bands have been carefully selected to enable advanced studies of land, ocean, and atmospheric processes. In this paper I will describe the various methods being used for the remote sensing of cloud properties using MODIS data, focusing primarily on the MODIS cloud mask used to distinguish clouds, clear sky, heavy aerosol, and shadows on the ground, and on the remote sensing of cloud optical properties, especially cloud optical thickness and effective radius of cloud drops and ice crystals. Results will be presented of MODIS cloud properties both over the land and over the ocean, showing the consistency in cloud retrievals over various ecosystems used in the retrievals. The implications of this new observing system on global analysis of the Earth's environment will be discussed.

Modeling the Impact of Drizzle and 3D Cloud Structure on Remote Sensing of Effective Radius

NASA Technical Reports Server (NTRS)

Platnick, Steven; Zinner, Tobias; Ackerman, S.

2008-01-01

Remote sensing of cloud particle size with passive sensors like MODIS is an important tool for cloud microphysical studies. As a measure of the radiatively relevant droplet size, effective radius can be retrieved with different combinations of visible through shortwave infrared channels. MODIS observations sometimes show significantly larger effective radii in marine boundary layer cloud fields derived from the 1.6 and 2.1 pm channel observations than for 3.7 pm retrievals. Possible explanations range from 3D radiative transport effects and sub-pixel cloud inhomogeneity to the impact of drizzle formation on the droplet distribution. To investigate the potential influence of these factors, we use LES boundary layer cloud simulations in combination with 3D Monte Carlo simulations of MODIS observations. LES simulations of warm cloud spectral microphysics for cases of marine stratus and broken stratocumulus, each for two different values of cloud condensation nuclei density, produce cloud structures comprising droplet size distributions with and without drizzle size drops. In this study, synthetic MODIS observations generated from 3D radiative transport simulations that consider the full droplet size distribution will be generated for each scene. The operational MODIS effective radius retrievals will then be applied to the simulated reflectances and the results compared with the LES microphysics.

Uncertainty in cloud optical depth estimates made from satellite radiance measurements

NASA Technical Reports Server (NTRS)

Pincus, Robert; Szczodrak, Malgorzata; Gu, Jiujing; Austin, Philip

1995-01-01

The uncertainty in optical depths retrieved from satellite measurements of visible wavelength radiance at the top of the atmosphere is quantified. Techniques are briefly reviewed for the estimation of optical depth from measurements of radiance, and it is noted that these estimates are always more uncertain at greater optical depths and larger solar zenith angles. The lack of radiometric calibration for visible wavelength imagers on operational satellites dominates the uncertainty retrievals of optical depth. This is true for both single-pixel retrievals and for statistics calculated from a population of individual retrievals. For individual estimates or small samples, sensor discretization can also be significant, but the sensitivity of the retrieval to the specification of the model atmosphere is less important. The relative uncertainty in calibration affects the accuracy with which optical depth distributions measured by different sensors may be quantitatively compared, while the absolute calibration uncertainty, acting through the nonlinear mapping of radiance to optical depth, limits the degree to which distributions measured by the same sensor may be distinguished.

Recent Progress on the Second Generation CMORPH: LEO-IR Based Precipitation Estimates and Cloud Motion Vector

NASA Astrophysics Data System (ADS)

Xie, Pingping; Joyce, Robert; Wu, Shaorong

2015-04-01

As reported at the EGU General Assembly of 2014, a prototype system was developed for the second generation CMORPH to produce global analyses of 30-min precipitation on a 0.05olat/lon grid over the entire globe from pole to pole through integration of information from satellite observations as well as numerical model simulations. The second generation CMORPH is built upon the Kalman Filter based CMORPH algorithm of Joyce and Xie (2011). Inputs to the system include rainfall and snowfall rate retrievals from passive microwave (PMW) measurements aboard all available low earth orbit (LEO) satellites, precipitation estimates derived from infrared (IR) observations of geostationary (GEO) as well as LEO platforms, and precipitation simulations from numerical global models. Key to the success of the 2nd generation CMORPH, among a couple of other elements, are the development of a LEO-IR based precipitation estimation to fill in the polar gaps and objectively analyzed cloud motion vectors to capture the cloud movements of various spatial scales over the entire globe. In this presentation, we report our recent work on the refinement for these two important algorithm components. The prototype algorithm for the LEO IR precipitation estimation is refined to achieve improved quantitative accuracy and consistency with PMW retrievals. AVHRR IR TBB data from all LEO satellites are first remapped to a 0.05olat/lon grid over the entire globe and in a 30-min interval. Temporally and spatially co-located data pairs of the LEO TBB and inter-calibrated combined satellite PMW retrievals (MWCOMB) are then collected to construct tables. Precipitation at a grid box is derived from the TBB through matching the PDF tables for the TBB and the MWCOMB. This procedure is implemented for different season, latitude band and underlying surface types to account for the variations in the cloud - precipitation relationship. At the meantime, a sub-system is developed to construct analyzed fields of cloud motion vectors from the GEO/LEO IR based precipitation estimates and the CFS Reanalysis (CFSR) precipitation fields. Motion vectors are first derived separately from the satellite IR based precipitation estimates and the CFSR precipitation fields. These individually derived motion vectors are then combined through a 2D-VAR technique to form an analyzed field of cloud motion vectors over the entire globe. Error function is experimented to best reflect the performance of the satellite IR based estimates and the CFSR in capturing the movements of precipitating cloud systems over different regions and for different seasons. Quantitative experiments are conducted to optimize the LEO IR based precipitation estimation technique and the 2D-VAR based motion vector analysis system. Detailed results will be reported at the EGU.

Effects of local meteorology and aerosols on ozone and nitrogen dioxide retrievals from OMI and pandora spectrometers in Maryland, USA during DISCOVER-AQ 2011.

PubMed

Reed, Andra J; Thompson, Anne M; Kollonige, Debra E; Martins, Douglas K; Tzortziou, Maria A; Herman, Jay R; Berkoff, Timothy A; Abuhassan, Nader K; Cede, Alexander

An analysis is presented for both ground- and satellite-based retrievals of total column ozone and nitrogen dioxide levels from the Washington, D.C., and Baltimore, Maryland, metropolitan area during the NASA-sponsored July 2011 campaign of D eriving I nformation on S urface CO nditions from Column and VER tically Resolved Observations Relevant to A ir Q uality (DISCOVER-AQ). Satellite retrievals of total column ozone and nitrogen dioxide from the Ozone Monitoring Instrument (OMI) on the Aura satellite are used, while Pandora spectrometers provide total column ozone and nitrogen dioxide amounts from the ground. We found that OMI and Pandora agree well (residuals within ±25 % for nitrogen dioxide, and ±4.5 % for ozone) for a majority of coincident observations during July 2011. Comparisons with surface nitrogen dioxide from a Teledyne API 200 EU NO x Analyzer showed nitrogen dioxide diurnal variability that was consistent with measurements by Pandora. However, the wide OMI field of view, clouds, and aerosols affected retrievals on certain days, resulting in differences between Pandora and OMI of up to ±65 % for total column nitrogen dioxide, and ±23 % for total column ozone. As expected, significant cloud cover (cloud fraction >0.2) was the most important parameter affecting comparisons of ozone retrievals; however, small, passing cumulus clouds that do not coincide with a high (>0.2) cloud fraction, or low aerosol layers which cause significant backscatter near the ground affected the comparisons of total column nitrogen dioxide retrievals. Our results will impact post-processing satellite retrieval algorithms and quality control procedures.

A13K-0336: Airborne Multi-Wavelength High Spectral Resolution Lidar for Process Studies and Assessment of Future Satellite Remote Sensing Concepts

NASA Technical Reports Server (NTRS)

Hostetler, Chris A.; Ferrare, Rich A.; Hair, Johnathan W.; Cook, Anthony L.; Harper, David B.; Mack, Terry L.; Hare, Richard J.; Cleckner, Craig S.; Rogers, Raymond R.; Muller, Detlef;

A Polar Specific 20-year Data Set of Cloud Fraction and Height Derived from Satellite Radiances

NASA Technical Reports Server (NTRS)

Francis, Jennifer; Schweiger, Axel

2004-01-01

This is a final report to fulfill reporting requirements on NASA grant NASA NAG5-11800. Jennifer Francis, PI at Rutgers University is currently continuing work on this project under a no-cost extension. Work at the University of Washington portion of the project is completed and reported here. Major accomplishments and results from this portion of the project include: 1) Extension and reprocessing of TOVS Polar Pathfinder (Path-P) data set; 2) Analysis of Arctic cloud variability; 3) Validation of Southern Hemisphere ocean cloud retrievals; 4) Intercompared cloud height information from AVHRR retrievals and surface-based cloud radar information.

Latent Heating Retrieval from TRMM Observations Using a Simplified Thermodynamic Model

NASA Technical Reports Server (NTRS)

Grecu, Mircea; Olson, William S.

2003-01-01

A procedure for the retrieval of hydrometeor latent heating from TRMM active and passive observations is presented. The procedure is based on current methods for estimating multiple-species hydrometeor profiles from TRMM observations. The species include: cloud water, cloud ice, rain, and graupel (or snow). A three-dimensional wind field is prescribed based on the retrieved hydrometeor profiles, and, assuming a steady-state, the sources and sinks in the hydrometeor conservation equations are determined. Then, the momentum and thermodynamic equations, in which the heating and cooling are derived from the hydrometeor sources and sinks, are integrated one step forward in time. The hydrometeor sources and sinks are reevaluated based on the new wind field, and the momentum and thermodynamic equations are integrated one more step. The reevalution-integration process is repeated until a steady state is reached. The procedure is tested using cloud model simulations. Cloud-model derived fields are used to synthesize TRMM observations, from which hydrometeor profiles are derived. The procedure is applied to the retrieved hydrometeor profiles, and the latent heating estimates are compared to the actual latent heating produced by the cloud model. Examples of procedure's applications to real TRMM data are also provided.

A Cloud Hydrology and Albedo Synthesis Mission (CHASM)

NASA Technical Reports Server (NTRS)

Davies, Roger

2004-01-01

This slide presentation reviews the Cloud Hydrology and Albedo Synthesis Mission (CHASM). The interaction of clouds with radiation and the hydrological cycle represents a huge uncertainty in our understanding of climate science and the modeling of climate system feedbacks. Despite the recognized need for a unified treatment of cloud processes, the present global average values of remotely sensed cloud liquid water and theoretically accepted values used for cloud physics and precipitation modeling differ by an order of magnitude. This is due in part to sampling and saturation effects, as well as to threedimensional cloud structure effects. In recent work with the Multiangle Imaging SpectroRadiometer (MISR) on Terra, we have gained new insights as to how the remote sensing approach could be significantly improved using a new instrument that combines passive optical (visible and near infrared) and microwave measurements, both as pushbroom scanners with multiple viewing angles, to the degree that measurements of liquid water path over deep convective clouds over land also become possible. This instrument would also have the ability of measuring height-resolved cloud-tracked winds using a hyper stereo retrieval technique. Deployment into a precessing low earth orbit would be optimal for measuring diurnal cloud activity. We have explored an instrument design concept for this that looks promising if we can establish partnerships that provide launch and bus capabilities.

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

Sena, Elisa T.; McComiskey, Allison; Feingold, Graham

Empirical estimates of the microphysical response of cloud droplet size distribution to aerosol perturbations are commonly used to constrain aerosol–cloud interactions in climate models. Instead of empirical microphysical estimates, here macroscopic variables are analyzed to address the influence of aerosol particles and meteorological descriptors on instantaneous cloud albedo and the radiative effect of shallow liquid water clouds. Long-term ground-based measurements from the Atmospheric Radiation Measurement (ARM) program over the Southern Great Plains are used. A broad statistical analysis was performed on 14 years of coincident measurements of low clouds, aerosol, and meteorological properties. Here two cases representing conflicting results regardingmore » the relationship between the aerosol and the cloud radiative effect were selected and studied in greater detail. Microphysical estimates are shown to be very uncertain and to depend strongly on the methodology, retrieval technique and averaging scale. For this continental site, the results indicate that the influence of the aerosol on the shallow cloud radiative effect and albedo is weak and that macroscopic cloud properties and dynamics play a much larger role in determining the instantaneous cloud radiative effect compared to microphysical effects. On a daily basis, aerosol shows no correlation with cloud radiative properties (correlation = -0.01 ± 0.03), whereas the liquid water path shows a clear signal (correlation = 0.56 ± 0.02).« less