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Joiner, J.

Publications and source records attributed to Joiner, J..

At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

Link Between Arctic Tropospheric BrO Explosion Observed from Space and Sea-Salt Aerosols from Blowing Snow Investigated Using Ozone Monitoring Instrument BrO Data and GEOS-5 Data Assimilation System

Bromine radicals (Br + BrO) are important atmospheric species owing to their ability to catalytically destroy ozone as well as their potential impacts on the oxidative pathways of many trace gases, including dimethylsulfide and mercury. Using space-based observations of BrO, recent studies have reported rapid enhancements of tropospheric BrO over large areas (so called "BrO explosions") connected to near-surface ozone depletion occurring in polar spring. However, the source(s) of reactive bromine and mechanism(s) that initiate these BrO explosions are uncertain. In this study, we investigate the relationships between Arctic BrO explosions and two of the proposed sources of reactive bromine: sea-salt aerosol (SSA) generated from blowing snow and first-year (seasonal) sea ice. We use tropospheric column BrO derived from the Ozone Monitoring Instrument (OMI) in conjunction with the Goddard Earth Observing System Version 5 (GEOS-5) data assimilation system provided by National Aeronautics and Space Administration Global Modeling and Assimilation Office. Case studies demonstrate a strong association between the temporal and spatial extent of OMI-observed BrO explosions and the GEOS-5 simulated blowing snow-generated SSA during Arctic spring. Furthermore, the frequency of BrO explosion events observed over the 11-year record of OMI exhibits significant correlation with a time series of the simulated SSA emission flux in the Arctic and little to no correlation with a time series of satellite-based first-year sea ice area. Therefore, we conclude that SSA generated by blowing snow is an important factor in the formation of the BrO explosion observed from space during Arctic spring.

blowing snow↗
NASA NTRS2017

High Sensitivity of Gross Primary Production in the Rocky Mountains to Summer Rain

n the catchments of the Rocky Mountains, peak snowpack is declining in response to warmer spring temperatures. To understand how this will influence terrestrial gross primary production (GPP), we compared precipitation data across the intermountain west with satellite retrievals of solar-induced fluorescence (SIF), a proxy for GPP. Annual precipitation patterns explained most of the spatial and temporal variability of SIF, but the slope of the response was dependent on site to site differences in the proportion of snowpack to summer rain. We separated the response of SIF to different seasonal precipitation amounts and found that SIF was approximately twice as sensitive to variations in summer rain than snowpack. The response of peak GPP to a secular decline in snowpack will likely be subtle, whereas a change in summer rain amount will have precipitous effects on GPP. The study suggests that the rain use efficiency of Rocky Mountain ecosystems is strongly dependent on precipitation form and timing.

solar-induced 15 Fuorescence (SIF)↗
NASA NTRS2014

Global Free-tropospheric NO2 Abundances Derived Using a Cloud Slicing Technique from AURA OMI

We derive free-tropospheric NO2 volume mixing ratios (VMRs) by applying a cloud-slicing technique to data from the Ozone Monitoring Instrument (OMI) on the Aura satellite. In the cloud-slicing approach, the slope of the above-cloud NO2 column versus the cloud scene pressure is proportional to the NO2 VMR. In this work, we use a sample of nearby OMI pixel data from a single orbit for the linear fit. The OMI data include cloud scene pressures from the rotational-Raman algorithm and above-cloud NO2 vertical column density (VCD) (defined as the NO2 column from the cloud scene pressure to the top of the atmosphere) from a differential optical absorption spectroscopy (DOAS) algorithm. We compare OMI-derived NO2 VMRs with in situ aircraft profiles measured during the NASA Intercontinental Chemical Transport Experiment Phase B (INTEX-B) campaign in 2006. The agreement is generally within the estimated uncertainties when appropriate data screening is applied. We then derive a global seasonal climatology of free-tropospheric NO2 VMR in cloudy conditions. Enhanced NO2 in the free troposphere commonly appears near polluted urban locations where NO2 produced in the boundary layer may be transported vertically out of the boundary layer and then horizontally away from the source. Signatures of lightning NO2 are also shown throughout low and middle latitude regions in summer months. A profile analysis of our cloud-slicing data indicates signatures of lightning-generated NO2 in the upper troposphere. Comparison of the climatology with simulations from the global modeling initiative (GMI) for cloudy conditions (cloud optical depth less than10) shows similarities in the spatial patterns of continental pollution outflow. However, there are also some differences in the seasonal variation of free-tropospheric NO2 VMRs near highly populated regions and in areas affected by lightning-generated NOx.

NO2↗
NASA NTRS2014

The Seasonal Cycle of Satellite Chlorophyll Fluorescence Observations and its Relationship to Vegetation Phenology and Ecosystem Atmosphere Carbon Exchange

Mapping of terrestrial chlorophyll uorescence from space has shown potentialfor providing global measurements related to gross primary productivity(GPP). In particular, space-based fluorescence may provide information onthe length of the carbon uptake period that can be of use for global carboncycle modeling. Here, we examine the seasonal cycle of photosynthesis asestimated from satellite fluorescence retrievals at wavelengths surroundingthe 740nm emission feature. These retrievals are from the Global OzoneMonitoring Experiment 2 (GOME-2) flying on the MetOp A satellite. Wecompare the fluorescence seasonal cycle with that of GPP as estimated froma diverse set of North American tower gas exchange measurements. Because the GOME-2 has a large ground footprint (40 x 80km2) as compared with that of the flux towers and requires averaging to reduce random errors, we additionally compare with seasonal cycles of upscaled GPP in the satellite averaging area surrounding the tower locations estimated from the Max Planck Institute for Biogeochemistry (MPI-BGC) machine learning algorithm. We also examine the seasonality of absorbed photosynthetically-active radiation(APAR) derived with reflectances from the MODerate-resolution Imaging Spectroradiometer (MODIS). Finally, we examine seasonal cycles of GPP as produced from an ensemble of vegetation models. Several of the data-driven models rely on satellite reflectance-based vegetation parameters to derive estimates of APAR that are used to compute GPP. For forested sites(particularly deciduous broadleaf and mixed forests), the GOME-2 fluorescence captures the spring onset and autumn shutoff of photosynthesis as delineated by the tower-based GPP estimates. In contrast, the reflectance-based indicators and many of the models tend to overestimate the length of the photosynthetically-active period for these and other biomes as has been noted previously in the literature. Satellite fluorescence measurements therefore show potential for improving model GPP estimates.

Joiner, J.↗
NASA NTRS2014

Global Free Tropospheric NO2 Abundances Derived Using a Cloud Slicing Technique Applied to Satellite Observations from the Aura Ozone Monitoring Instrument (OMI)

We derive free-tropospheric NO2 volume mixing ratios (VMRs) and stratospheric column amounts of NO2 by applying a cloud slicing technique to data from the Ozone Monitoring Instrument (OMI) on the Aura satellite. In the cloud-slicing approach, the slope of the above-cloud NO2 column versus the cloud scene pressure is proportional to the NO2 VMR. In this work, we use a sample of nearby OMI pixel data from a single orbit for the linear fit. The OMI data include cloud scene pressures from the rotational-Raman algorithm and above-cloud NO2 vertical column density (VCD) (defined as the NO2 column from the cloud scene pressure to the top-of-the-atmosphere) from a differential optical absorption spectroscopy (DOAS) algorithm. Estimates of stratospheric column NO2 are obtained by extrapolating the linear fits to the tropopause. We compare OMI-derived NO2 VMRs with in situ aircraft profiles measured during the NASA Intercontinental Chemical Transport Experiment Phase B (INTEX-B) campaign in 2006. The agreement is generally within the estimated uncertainties when appropriate data screening is applied. We then derive a global seasonal climatology of free-tropospheric NO2 VMR in cloudy conditions. Enhanced NO2 in the free troposphere commonly appears near polluted urban locations where NO2 produced in the boundary layer may be transported vertically out of the boundary layer and then horizontally away from the source. Signatures of lightning NO2 are also shown throughout low and middle latitude regions in summer months. A profile analysis of our cloud slicing data indicates signatures of uplifted and transported anthropogenic NO2 in the middle troposphere as well as lightning-generated NO2 in the upper troposphere. Comparison of the climatology with simulations from the Global Modeling Initiative (GMI) for cloudy conditions (cloud optical thicknesses > 10) shows similarities in the spatial patterns of continental pollution outflow. However, there are also some differences in the seasonal variation of free-tropospheric NO2 VMRs near highly populated regions and in areas affected by lightning-generated NOx. Stratospheric column NO2 obtained from cloud slicing agrees well with other independently-generated estimates, providing further confidence in the free-tropospheric results.

NO2↗
NASA NTRS2013

Global Monitoring of Terrestrial Chlorophyll Fluorescence from Moderate-Spectral-Resolution Near-Infrared Satellite Measurements: Methodology, Simulations, and Application to GOME-2

Globally mapped terrestrial chlorophyll fluorescence retrievals are of high interest because they can provide information on the functional status of vegetation including light-use efficiency and global primary productivity that can be used for global carbon cycle modeling and agricultural applications. Previous satellite retrievals of fluorescence have relied solely upon the filling-in of solar Fraunhofer lines that are not significantly affected by atmospheric absorption. Although these measurements provide near-global coverage on a monthly basis, they suffer from relatively low precision and sparse spatial sampling. Here, we describe a new methodology to retrieve global far-red fluorescence information; we use hyperspectral data with a simplified radiative transfer model to disentangle the spectral signatures of three basic components: atmospheric absorption, surface reflectance, and fluorescence radiance. An empirically based principal component analysis approach is employed, primarily using cloudy data over ocean, to model and solve for the atmospheric absorption. Through detailed simulations, we demonstrate the feasibility of the approach and show that moderate-spectral-resolution measurements with a relatively high signal-to-noise ratio can be used to retrieve far-red fluorescence information with good precision and accuracy. The method is then applied to data from the Global Ozone Monitoring Instrument 2 (GOME-2). The GOME-2 fluorescence retrievals display similar spatial structure as compared with those from a simpler technique applied to the Greenhouse gases Observing SATellite (GOSAT). GOME-2 enables global mapping of far-red fluorescence with higher precision over smaller spatial and temporal scales than is possible with GOSAT. Near-global coverage is provided within a few days. We are able to show clearly for the first time physically plausible variations in fluorescence over the course of a single month at a spatial resolution of 0.5 0.5. We also show some significant differences between fluorescence and coincident normalized difference vegetation indices (NDVI) retrievals.

Fluorescence↗
NASA NTRS2013

Global Monitoring of Terrestrial Chlorophyll Fluorescence from Moderate-spectral-resolution Near-infrared Satellite Measurements: Methodology, Simulations, and Application to GOME-2

Globally mapped terrestrial chlorophyll fluorescence retrievals are of high interest because they can provide information on the functional status of vegetation including light-use efficiency and global primary productivity that can be used for global carbon cycle modeling and agricultural applications. Previous satellite retrievals of fluorescence have relied solely upon the filling-in of solar Fraunhofer lines that are not significantly affected by atmospheric absorption. Although these measurements provide near-global coverage on a monthly basis, they suffer from relatively low precision and sparse spatial sampling. Here, we describe a new methodology to retrieve global far-red fluorescence information; we use hyperspectral data with a simplified radiative transfer model to disentangle the spectral signatures of three basic components: atmospheric absorption, surface reflectance, and fluorescence radiance. An empirically based principal component analysis approach is employed, primarily using cloudy data over ocean, to model and solve for the atmospheric absorption. Through detailed simulations, we demonstrate the feasibility of the approach and show that moderate-spectral-resolution measurements with a relatively high signal-to-noise ratio can be used to retrieve far-red fluorescence information with good precision and accuracy. The method is then applied to data from the Global Ozone Monitoring Instrument 2 (GOME-2). The GOME-2 fluorescence retrievals display similar spatial structure as compared with those from a simpler technique applied to the Greenhouse gases Observing SATellite (GOSAT). GOME-2 enables global mapping of far-red fluorescence with higher precision over smaller spatial and temporal scales than is possible with GOSAT. Near-global coverage is provided within a few days. We are able to show clearly for the first time physically plausible variations in fluorescence over the course of a single month at a spatial resolution of 0.5 deg × 0.5 deg. We also show some significant differences between fluorescence and coincident normalized difference vegetation indices (NDVI) retrievals.

remote sensing↗
NASA NTRS2012

Filling-in of Far-Red and Near-Infrared Solar Lines by Terrestrial and Atmospheric Effects: Simulations and Space-Based Observations from SCIAMACHY and GOSAT

Mapping of terrestrial vegetation fluorescence from space is of interest because it can potentially provide global information on the functional status of vegetation including light use efficiency and global primary productivity that can be used for global carbon cycle modeling. Space-based measurement of solar-induced chlorophyll fluorescence is challenging, because its signal is small as compared with the much larger reflectance signal. Ground- and aircraft-based approaches have made use of the dark and spectrally-wide O2-A ( approx 760 nm) and O2-B (approx 690 nm) atmospheric features to detect the weak fluorescence signal. More recently, Joiner et al. and Frankenberg et al. focused on longer-wavelength solar Fraunhofer lines that can be observed with space-based instruments such as the currently operational GOSAT. They showed that fluorescence can be detected using Fraunhofer lines away from the far-red chlorophyll-a fluorescence peak even when the surface is relatively bright. Here, we build on that work by developing methodology to correct for instrumental artifacts that produce false filling-in signals that can bias fluorescence retrievals. We also examine other potential sources of filling-in at far-red and NIR wavelengths. Another objective is to explore the possibility of making fluorescence measurements from space with lower spectral resolution instrumentation than the GOSAT interferometer. We focus on the 866nm Ca II solar Fraunhofer line. Very few laboratory and ground-based measurements of vegetation fluorescence have been reported at wavelengths longer than 800 nm. Some results of fluorescence measurements of corn leaves acquired in the laboratory using polychromatic excitation at wavelengths shorter than 665nm show that at 866 nm, the measured signal is of the order of 0.1-0.2 mW/sq m/nm/sr. In this work, we use the following satellite observations: We use SCIAMACHY channel 5 in nadir mode that covers wavelengths between 773 and 1063nm at a spectral resolution of 0.54 nm. GOSAT has two instrument packages: the Thermal And Near-infrared Sensor for carbon Observation-Fourier Transform Spectrometer (TANSO-FTS) and the Cloud and Aerosol Imager (CAI). We use TANSO-FTS band 1, which extends from approximately 758 to 775nm and we use cloud fraction derived from the CAI. We compare satellite-derived fluorescence with the Enhanced Vegetation Index (EVI), an Aqua/MODIS-derived vegetation reflectance-based index that indicates relative greenness and is used to infer photosynthetic function.

Joiner, J.↗
NASA NTRS2012

Recent Advances in Ozone Data Assimilation at the GMAO - Towards a New Reanalysis

This presentation summarized ongoing work on improving the representation of ozone in the GEOS Data Assimilation Systems. Data from two EOS Aura sensors was used: the total column ozone from the Ozone Monitoring Instrument (OMI) and high vertical resolution stratospheric profiles from Microwave Limb Sounder (MLS, version 3.3). As several previous studies have demonstrated, assimilation of this data can constrain the stratospheric and tropospheric ozone columns with relatively good accuracy. However, the representation of the vertical structures in the troposphere and near tropopause region is often deficient. Since both these layers of the atmosphere are critical to the understanding of the radiative forcing as well as the ozone budget in the troposphere, current work will focus on improving the assimilated product between the surface and the 50 hPa pressure level. The discussion included recent steps that have been taken towards refining the treatment of ozone in GEOS-5. Impacts of improved tropospheric chemistry model were discussed including the introduction of efficiency factors ("averaging kernels") for OMI total ozone, and direct assimilation of radiances from the MLS instrument. In particular, advantages and challenges involved in assimilating limb radiances rather than retrieved product were discussed. This work is, in part, a preparation for a planned reanalysis of the EOS Aura data from 2005 to present.

Krzysztof, Wargan↗
NASA NTRS2012

Analysis of Satellite-Derived Arctic Tropospheric BrO Columns in Conjunction with Aircraft Measurements During ARCTAS and ARCPAC

We derive tropospheric column BrO during the ARCTAS and ARCPAC field campaigns in spring 2008 using retrievals of total column BrO from the satellite UV nadir sensors OMI and GOME-2 using a radiative transfer model and stratospheric column BrO from a photochemical simulation. We conduct a comprehensive comparison of satellite-derived tropospheric BrO column to aircraft in-situ observations ofBrO and related species. The aircraft profiles reveal that tropospheric BrO, when present during April 2008, was distributed over a broad range of altitudes rather than being confined to the planetary boundary layer (PBL). Perturbations to the total column resulting from tropospheric BrO are the same magnitude as perturbations due to longitudinal variations in the stratospheric component, so proper accounting of the stratospheric signal is essential for accurate determination of satellite-derived tropospheric BrO. We find reasonably good agreement between satellite-derived tropospheric BrO and columns found using aircraft in-situ BrO profiles, particularly when satellite radiances were obtained over bright surfaces (albedo> 0.7), for solar zenith angle < 80 and clear sky conditions. The rapid activation of BrO due to surface processes (the bromine explosion) is apparent in both the OMI and GOME-2 based tropospheric columns. The wide orbital swath of OMI allows examination of the evolution of tropospheric BrO on about hourly time intervals near the pole. Low surface pressure, strong wind, and high PBL height are associated with an observed BrO activation event, supporting the notion of bromine activation by high winds over snow.

Choi, S.↗
NASA NTRS2012

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

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.

Joiner, J.↗
NASA NTRS2012

Filling-in of Far-Red and Near-Infrared Solar Lines by Terrestrial and Atmospheric Effects: Simulations and Space-Based Observations from SCHIAMACHY and GOSAT

Mapping of terrestrial vegetation fluorescence from space is of interest because it can potentially provide global information on the functional status of vegetation including light use efficiency and global primary productivity that can be used for global carbon cycle modeling. Space-based measurement of solar-induced chlorophyll fluorescence is challenging, because its signal is small as compared with the much larger reflectance signal. Ground- and aircraft-based approaches have made use of the dark and spectrally-wide 02-A (approx 760 nm) and O2-B (approx 690 nm) atmospheric features to detect the weak fluorescence signal. More recently, Joiner et a1. and Frankenberg et a1. focused on longer-wavelength solar Fraunhofer lines that can be observed with space-based instruments such as the currently operational GOSAT. They showed that fluorescence can be detected using Fraunhofer lines away from the far-red chlorophyll-a fluorescence peak even when the surface is relatively bright. Here, we build on that work by developing methodology to correct for instrumental artifacts that produce false filling-in signals that can bias fluorescence retrievals. We also examine other potential sources of filling-in at far-red and NIR wavelengths. Another objective is to explore the possibility of making fluorescence measurements from space with lower spectral resolution instrumentation than the GOSAT interferometer. We focus on the 866 nm Ca II solar Fraunhofer line. Very few laboratory and ground-based measurements of vegetation fluorescence have been reported at wavelengths longer than 800 mn. Some results of fluorescence measurements of corn leaves acquired in the laboratory using polychromatic excitation at wavelengths shorter than 665 nm show that at 866 nm, the measured signal is of the order of 0.1-0.2 mw/sq m/nm/sr. In this work we use the following satellite observations: We use SCIAMACHY channel 5 in nadir mode that covers wavelengths between 773 and 1063 nm at a spectral resolution of 0.54 nm. GOSAT has two instrument packages: the Thermal And Near-infrared Sensor for carbon Observation-Fourier Transform Spectrometer (TANSO-FTS) and the Cloud and Aerosol Imager (CAI). We use TANSO-FTS band 1, which extends from approximately 758 to 775 mn and we use cloud fraction derived from the CAL We compare satellite-derived fluorescence with the Enhanced Vegetation Index (EVI), an Aqua/MODIS-derived vegetation reflectance-based index that indicates relative greenness and is used to infer photosynthetic function.

Joiner, J.↗
NASA NTRS2011

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

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.

Joiner, J.↗
NASA NTRS2011

Filling-In of Broad Far-Red Solar Lines by Terrestrial Fluorescence and Atmospheric Raman Scattering as Detected by SCIAMACHY Satellite Measurements

Global mapping of terrestrial vegetation fluorescence from space has recently been accomplished with high spectral resolution measurements from the Japanese Greenhouse gases Observing SATellite (GOSAT). These data are of interest because they can potentially provide global information on the functional status of vegetation including light use efficiency and global primary productivity that can be used for global carbon cycle modeling. Quantifying the impact of fluorescence on the O2-A band is important as this band is used for cloud- and aerosol-characterization for other trace-gas retrievals including CO2. Here, we demonstrate that fluorescence information can be derived from space using potentially lower-cost hyperspectral instrumentation, i.e., more than an order of magnitude less spectral resolution than GOSAT, with a relatively simple algorithm. As a demonstration, we use the filling-in of one of the few wide and deep solar Fraunhofer lines in the red and far-red chlorophylla fluorescence bands, the calcium II line near 866 nm, to retrieve fluorescence with the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) satellite instrument. Although the signal from vegetation fluorescence is extremely weak at 866 nm, our results suggest that useful information may be obtained after adjustments are made to the observed spectra to correct for instrumental artifacts. We compare fluorescence from SCIAMACHY with that retrieved at 758 and 770 nm from similarly-corrected GOSAT data as well with the Enhanced Vegetation Index (EVI) from the MODerate-resolution Imaging Spectroradiometer (MODIS). We also show that filling-in occurs at 866 nm over barren areas, possibly originating from luminescent minerals in rock and soil.

Joiner, J.↗
NASA NTRS2010

Detection of Multi-Layer and Vertically-Extended Clouds Using A-Train Sensors

The detection of mUltiple cloud layers using satellite observations is important for retrieval algorithms as well as climate applications. In this paper, we describe a relatively simple algorithm to detect multiple cloud layers and distinguish them from vertically-extended clouds. The algorithm can be applied to coincident passive sensors that derive both cloud-top pressure from the thermal infrared observations and an estimate of solar photon pathlength from UV, visible, or near-IR measurements. Here, we use data from the A-train afternoon constellation of satellites: cloud-top pressure, cloud optical thickness, the multi-layer flag from the Aqua MODerate-resolution Imaging Spectroradiometer (MODIS) and the optical centroid cloud pressure from the Aura Ozone Monitoring Instrument (OMI). For the first time, we use data from the CloudSat radar to evaluate the results of a multi-layer cloud detection scheme. The cloud classification algorithms applied with different passive sensor configurations compare well with each other as well as with data from CloudSat. We compute monthly mean fractions of pixels containing multi-layer and vertically-extended clouds for January and July 2007 at the OMI spatial resolution (l2kmx24km at nadir) and at the 5kmx5km MODIS resolution used for infrared cloud retrievals. There are seasonal variations in the spatial distribution of the different cloud types. The fraction of cloudy pixels containing distinct multi-layer cloud is a strong function of the pixel size. Globally averaged, these fractions are approximately 20% and 10% for OMI and MODIS, respectively. These fractions may be significantly higher or lower depending upon location. There is a much smaller resolution dependence for fractions of pixels containing vertically-extended clouds (approx.20% for OMI and slightly less for MODIS globally), suggesting larger spatial scales for these clouds. We also find higher fractions of vertically-extended clouds over land as compared with ocean, particularly in the tropics and summer hemisphere.

Joiner, J.↗
NASA NTRS2008

The Cloud Slicing Technique-Measuring the Unmeasureable

In satellite remote sensing clouds are usually considered an annoying interference. Satellite investigators go to unusual lengths to try to avoid clouds or to correct for their effects, and satellite data users routinely exclude cloudy data from analysis. Yet it was shown about a decade ago using TOMS data that for the study of tropospheric constituents, such as ozone, clouds can play a very beneficial role by allowing one to measure what otherwise cannot be directly measured from space. We call this technique "cloud Slicing". The so-called Convective Cloud Differential (CCD) method is one particular application of cloud slicing that has been applied successfully to data from TOMS and other similar satellite instruments to study the behavior of tropical tropospheric ozone at variety of spatial and temporal scales. However, there has been considerable confusion in the literature as to what exactly one measures from reflected sunlight instruments such as TOMS in cloudy atmospheres. We will discuss recently completed analysis of data taken by the Ozone Monitoring Instrument (OMI) on the Aura satellite in conjunction with several other instruments on the A-train satellite constellation to present new insight on how clouds affect absorption by aerosols and trace gases at reflected wavelengths (UV-SWIR). We will show several examples to illustrate how this insight is helping us to study the behavior of trace gases and aerosols in the atmosphere that cannot be studied by focusing only on cloud-free scenes.

Bhartia, P.↗
NASA NTRS2007

Three Way Comparison between Two OMI/Aura and One POLDER/PARASOL Cloud Pressure Products

The cloud pressures determined by three different algorithms, operating on reflectances measured by two space-borne instruments in the "A" train, are compared with each other. The retrieval algorithms are based on absorption in the oxygen A-band near 760 nm, absorption by a collision induced absorption in oxygen near 477nm, and the filling in of Fraunhofer lines by rotational Raman scattering. The first algorithm operates on data collected by the POLDER instrument on board PARASOL, while the latter two operate on data from the OMI instrument on board Aura. The satellites sample the same air mass within about 15 minutes. Using one month of data, the cloud pressures from the three algorithms are found to show a similar behavior, with correlation coefficients larger than 0.85 between the data sets for thick clouds. The average differences in the cloud pressure are also small, between 2 and 45 hPa, for the whole data set. For optically thin to medium thick clouds, the cloud pressure the distribution found by POLDER is very similar to that found by OMI using the O2 - O2 absorption. Somewhat larger differences are found for very thick clouds, and we hypothesise that the strong absorption in the oxygen A-band causes the POLDER instrument to retrieve lower pressures for those scenes.

Sneep, M.↗