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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

Comparing the Atmospheres of Mercury and the Earth's Moon

The exospheres of Mercury and the Earth's Moon are fundamentally similar, but the differences that do exist between them can help us to develop a better understanding of the processes at work on the two bodies that produce and remove volatiles. The major differences are derived from (1) the different compositions of the two surfaces, (2) the different particle and field em'ironments above the surface of each body (particularly the presence of intrinsic magnetic field of Mercury), and (3) the larger flux of interplanetary dust incident at the orbit of Mercury. The first difference, surface composition, is the most intractable problem, but the most challenging part of that problem, the composition of the Hermean regolith, may be at least partially addressed as the MESSENGER mission completes work over the next year. Much progress has been made with respect to exploring the second difference above--spacecraft such as Helios, Ulysses, WIND, and ACE have measured the solar wind and its composition both in Earth orbit and at distances encompassing the orbit of Mercury. While our knowledge of the solar wind is incomplete, again it is far more detailed than a simple 1/R(sup 2) law would predict. Another problem is that of the flux of charged particles to the surfaces. While Mercury's magnetosphere is the subject of current study with MESSENGER, the influx of charged particles on the Moon has gone beyond a cos (psi) picture, where psi is the solar zenith angle. We know that the influx of ions at the Moon is affected by magnetic anomalies, by craters, and by surface charging. The third external difference is the differing flux of interplanetary dust incident on the two surfaces. In this talk we will consider: (1) the species that one can compare now for these two exospheres (Na, K, and He); (2) the species that you might be able to compare with future measurements (Ca and Mg); arid (3) how intensive ground-based observations of the easiest lunar species to observe from the ground, Na and K, might help us address source processes at work on both surfaces. We will discuss current and planned modeling efforts for both the lunar and Hermean exospheres, and some current and planned observations, both ground-based and space-based.

Morgan, Thomas H.↗
NASA NTRS2011

Variability of Thermosphere and Ionosphere Responses to Solar Flares

We investigated how the rise rate and decay rate of solar flares affect the thermosphere and ionosphere responses to them. Model simulations and data analysis were conducted for two flares of similar magnitude (X6.2 and X5.4) that had the same location on the solar limb, but the X6.2 flare had longer rise and decay times. Simulated total electron content (TEC) enhancements from the X6.2 and X5.4 flares were 6 total electron content units (TECU) and approximately 2 TECU, and the simulated neutral density enhancements were approximately 15% -20% and approximately 5%, respectively, in reasonable agreement with observations. Additional model simulations showed that for idealized flares with the same magnitude and location, the thermosphere and ionosphere responses changed significantly as a function of rise and decay rates. The Neupert Effect, which predicts that a faster flare rise rate leads to a larger EUV enhancement during the impulsive phase, caused a larger maximum ion production enhancement. In addition, model simulations showed that increased E x B plasma transport due to conductivity increases during the flares caused a significant equatorial anomaly feature in the electron density enhancement in the F region but a relatively weaker equatorial anomaly feature in TEC enhancement, owing to dominant contributions by photochemical production and loss processes. The latitude dependence of the thermosphere response correlated well with the solar zenith angle effect, whereas the latitude dependence of the ionosphere response was more complex, owing to plasma transport and the winter anomaly.

Qian, Liying↗
NASA NTRS2012

Solar Flare Impacts on Ionospheric Electrodynamics

The sudden increase of X-ray and extreme ultra-violet irradiance during flares increases the density of the ionosphere through enhanced photoionization. In this paper, we use model simulations to investigate possible additional contributions from electrodynamics, finding that the vertical E X B drift in the magnetic equatorial region plays a significant role in the ionosphere response to solar flares. During the initial stage of flares, upward E X B drifts weaken in the magnetic equatorial region, causing a weakened equatorial fountain effect, which in turn causes lowering of the peak height of the F2 region and depletion of the peak electron density of the F2 region. In this initial stage, total electron content (TEC) enhancement is predominantly determined by solar zenith angle control of photoionization. As flares decay, upward E X B drifts are enhanced in the magnetic equatorial region, causing increases of the peak height and density of the F2 region. This process lasts for several hours, causing a prolonged F2-region disturbance and TEC enhancement in the magnetic equator region in the aftermath of flares. During this stage, the global morphology of the TEC enhancement becomes predominantly determined by these perturbations to the electrodynamics of the ionosphere.

Qian, Liying↗
NASA NTRS2012

Highlights of TOMS Version 9 Total Ozone Algorithm

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

Bhartia, Pawan↗
NASA NTRS2012

SBUV version 8.6 Retrieval Algorithm: Error Analysis and Validation Technique

SBUV version 8.6 algorithm was used to reprocess data from the Back Scattered Ultra Violet (BUV), the Solar Back Scattered Ultra Violet (SBUV) and a number of SBUV/2 instruments, which 'span a 41-year period from 1970 to 2011 (except a 5-year gap in the 1970s)[see Bhartia et al, 2012]. In the new version Daumont et al. [1992] ozone cross section were used, and new ozone [McPeters et ai, 2007] and cloud climatologies Doiner and Bhartia, 1995] were implemented. The algorithm uses the Optimum Estimation technique [Rodgers, 2000] to retrieve ozone profiles as ozone layer (partial column, DU) on 21 pressure layers. The corresponding total ozone values are calculated by summing ozone columns at individual layers. The algorithm is optimized to accurately retrieve monthly zonal mean (mzm) profiles rather than an individual profile, since it uses monthly zonal mean ozone climatology as the A Priori. Thus, the SBUV version 8.6 ozone dataset is better suited for long-term trend analysis and monitoring ozone changes rather than for studying short-term ozone variability. Here we discuss some characteristics of the SBUV algorithm and sources of error in the SBUV profile and total ozone retrievals. For the first time the Averaging Kernels, smoothing errors and weighting functions (or Jacobians) are included in the SBUV metadata. The Averaging Kernels (AK) represent the sensitivity of the retrieved profile to the true state and contain valuable information about the retrieval algorithm, such as Vertical Resolution, Degrees of Freedom for Signals (DFS) and Retrieval Efficiency [Rodgers, 2000]. Analysis of AK for mzm ozone profiles shows that the total number of DFS for ozone profiles varies from 4.4 to 5.5 out of 6-9 wavelengths used for retrieval. The number of wavelengths in turn depends on solar zenith angles. Between 25 and 0.5 hPa, where SBUV vertical resolution is the highest, DFS for individual layers are about 0.5.

Kramarova, N. A.↗
NASA NTRS2012

Using Information From Prior Satellite Scans to Improve Cloud Detection Near the Day-Night Terminator

With geostationary satellite data it is possible to have a continuous record of diurnal cycles of cloud properties for a large portion of the globe. Daytime cloud property retrieval algorithms are typically superior to nighttime algorithms because daytime methods utilize measurements of reflected solar radiation. However, reflected solar radiation is difficult to accurately model for high solar zenith angles where the amount of incident radiation is small. Clear and cloudy scenes can exhibit very small differences in reflected radiation and threshold-based cloud detection methods have more difficulty setting the proper thresholds for accurate cloud detection. Because top-of-atmosphere radiances are typically more accurately modeled outside the terminator region, information from previous scans can help guide cloud detection near the terminator. This paper presents an algorithm that uses cloud fraction and clear and cloudy infrared brightness temperatures from previous satellite scan times to improve the performance of a threshold-based cloud mask near the terminator. Comparisons of daytime, nighttime, and terminator cloud fraction derived from Geostationary Operational Environmental Satellite (GOES) radiance measurements show that the algorithm greatly reduces the number of false cloud detections and smoothes the transition from the daytime to the nighttime clod detection algorithm. Comparisons with the Geoscience Laser Altimeter System (GLAS) data show that using this algorithm decreases the number of false detections by approximately 20 percentage points.

Yost, Christopher R.↗
NASA NTRS2012

Dynamic Range and Sensitivity Requirements of Satellite Ocean Color Sensors: Learning from the Past

Sensor design and mission planning for satellite ocean color measurements requires careful consideration of the signal dynamic range and sensitivity (specifically here signal-to-noise ratio or SNR) so that small changes of ocean properties (e.g., surface chlorophyll-a concentrations or Chl) can be quantified while most measurements are not saturated. Past and current sensors used different signal levels, formats, and conventions to specify these critical parameters, making it difficult to make cross-sensor comparisons or to establish standards for future sensor design. The goal of this study is to quantify these parameters under uniform conditions for widely used past and current sensors in order to provide a reference for the design of future ocean color radiometers. Using measurements from the Moderate Resolution Imaging Spectroradiometer onboard the Aqua satellite (MODISA) under various solar zenith angles (SZAs), typical (L(sub typical)) and maximum (L(sub max)) at-sensor radiances from the visible to the shortwave IR were determined. The Ltypical values at an SZA of 45 deg were used as constraints to calculate SNRs of 10 multiband sensors at the same L(sub typical) radiance input and 2 hyperspectral sensors at a similar radiance input. The calculations were based on clear-water scenes with an objective method of selecting pixels with minimal cross-pixel variations to assure target homogeneity. Among the widely used ocean color sensors that have routine global coverage, MODISA ocean bands (1 km) showed 2-4 times higher SNRs than the Sea-viewing Wide Field-of-view Sensor (Sea-WiFS) (1 km) and comparable SNRs to the Medium Resolution Imaging Spectrometer (MERIS)-RR (reduced resolution, 1.2 km), leading to different levels of precision in the retrieved Chl data product. MERIS-FR (full resolution, 300 m) showed SNRs lower than MODISA and MERIS-RR with the gain in spatial resolution. SNRs of all MODISA ocean bands and SeaWiFS bands (except the SeaWiFS near-IR bands) exceeded those from prelaunch sensor specifications after adjusting the input radiance to L(sub typical). The tabulated L(sub typical), L(sub max), and SNRs of the various multiband and hyperspectral sensors under the same or similar radiance input provide references to compare sensor performance in product precision and to help design future missions such as the Geostationary Coastal and Air Pollution Events (GEO-CAPE) mission and the Pre-Aerosol-Clouds-Ecosystems (PACE) mission currently being planned by the U.S. National Aeronautics and Space Administration (NASA).

chlorophyll fluorescence↗
NASA NTRS2012

High Precision, Absolute Total Column Ozone Measurements from the Pandora Spectrometer System: Comparisons with Data from a Brewer Double Monochromator and Aura OMI

We present new, high precision, high temporal resolution measurements of total column ozone (TCO) amounts derived from ground-based direct-sun irradiance measurements using our recently deployed Pandora single-grating spectrometers. Pandora's small size and portability allow deployment at multiple sites within an urban air-shed and development of a ground-based monitoring network for studying small-scale atmospheric dynamics, spatial heterogeneities in trace gas distribution, local pollution conditions, photochemical processes and interdependencies of ozone and its major precursors. Results are shown for four mid- to high-latitude sites where different Pandora instruments were used. Comparisons with a well calibrated double-grating Brewer spectrometer over a period of more than a year in Greenbelt MD showed excellent agreement and a small bias of approximately 2 DU (or, 0.6%). This was constant with slant column ozone amount over the full range of observed solar zenith angles (15-80), indicating adequate Pandora stray light correction. A small (1-2%) seasonal difference was found, consistent with sensitivity studies showing that the Pandora spectral fitting TCO retrieval has a temperature dependence of 1% per 3K, with an underestimation in temperature (e.g., during summer) resulting in an underestimation of TCO. Pandora agreed well with Aura-OMI (Ozone Measuring Instrument) satellite data, with average residuals of <1% at the different sites when the OMI view was within 50 km from the Pandora location and OMI-measured cloud fraction was <0.2. The frequent and continuous measurements by Pandora revealed significant short-term (hourly) temporal changes in TCO, not possible to capture by sun-synchronous satellites, such as OMI, alone.

Ozone↗
NASA NTRS2014

OH in the Tropical Upper Troposhere and Its Relationships to Solar Radiation and Reactive Nitrogen

In situ measurements of [OH], [HO2] (square brackets denote species concentrations), and other chemical species were made in the tropical upper troposphere (TUT). [OH] showed a robust correlation with solar zenith angle. Beyond this dependence, however, [HOx] ([OH] + [HO2]) only weakly responds to variations in its source and sink species. For example, at a given SZA, [HOx] was broadly independent of the product of [O3] and [H2O]. This suggests that [OH] is heavily buffered in the TUT. One important exception to this result is found in regions with very low [O3], [NO], and [NOy], where [OH] is highly suppressed, pointing to the critical role of NO in sustaining OH in the TUT.

Tropical upper troposphere↗
NASA NTRS2014

Improvements in Total Column Ozone in GEOSCCM and Comparisons with a New Ozone-Depleting Substances Scenario

The evolution of ozone is examined in the latest version of the Goddard Earth Observing System Chemistry-Climate Model (GEOSCCM) using old and new ozone-depleting substances (ODS) scenarios. This version of GEOSCCM includes a representation of the quasi-biennial oscillation, a more realistic implementation of ozone chemistry at high solar zenith angles, an improved air/sea roughness parameterization, and an extra 5 parts per trillion of CH3Br to account for brominated very short-lived substances. Together these additions improve the representation of ozone compared to observations. This improved version of GEOSCCM was used to simulate the ozone evolution for the A1 2010 and the newStratosphere-troposphere Processes and their Role in Climate (SPARC) 2013 ODS scenario derived using the SPARC Lifetimes Report 2013. This new ODS scenario results in a maximum Cltot increase of 65 parts per trillion by volume (pptv), decreasing slightly to 60 pptv by 2100. Approximately 72% of the increase is due to the longer lifetime of CFC-11. The quasi-global (60degS-60degN) total column ozone difference is relatively small and less than 1Dobson unit on average and consistent with the 3-4% larger 2050-2080 average Cly in the new SPARC 2013 scenario. Over high latitudes, this small change in Cly compared to the relatively large natural variabilitymakes it not possible to discern a significant impact on ozone in the second half of the 21st century in a single set of simulations.

Ozone↗
NASA NTRS2013

The Collection 6 'dark-target' MODIS Aerosol Products

Aerosol retrieval algorithms are applied to Moderate resolution Imaging Spectroradiometer (MODIS) sensors on both Terra and Aqua, creating two streams of decade-plus aerosol information. Products of aerosol optical depth (AOD) and aerosol size are used for many applications, but the primary concern is that these global products are comprehensive and consistent enough for use in climate studies. One of our major customers is the international modeling comparison study known as AEROCOM, which relies on the MODIS data as a benchmark. In order to keep up with the needs of AEROCOM and other MODIS data users, while utilizing new science and tools, we have improved the algorithms and products. The code, and the associated products, will be known as Collection 6 (C6). While not a major overhaul from the previous Collection 5 (C5) version, there are enough changes that there are significant impacts to the products and their interpretation. In its entirety, the C6 algorithm is comprised of three sub-algorithms for retrieving aerosol properties over different surfaces: These include the dark-target DT algorithms to retrieve over (1) ocean and (2) vegetated-dark-soiled land, plus the (3) Deep Blue (DB) algorithm, originally developed to retrieve over desert-arid land. Focusing on the two DT algorithms, we have updated assumptions for central wavelengths, Rayleigh optical depths and gas (H2O, O3, CO2, etc.) absorption corrections, while relaxing the solar zenith angle limit (up to 84) to increase pole-ward coverage. For DT-land, we have updated the cloud mask to allow heavy smoke retrievals, fine-tuned the assignments for aerosol type as function of season location, corrected bugs in the Quality Assurance (QA) logic, and added diagnostic parameters such as topographic altitude. For DT-ocean, improvements include a revised cloud mask for thin-cirrus detection, inclusion of wind speed dependence in the retrieval, updates to logic of QA Confidence flag (QAC) assignment, and additions of important diagnostic information. At the same time as we have introduced algorithm changes, we have also accounted for upstream changes including: new instrument calibration, revised land-sea masking, and changed cloud masking. Upstream changes also impact the coverage and global statistics of the retrieved AOD. Although our responsibility is to the DT code and products, we have also added a product that merges DT and DB product over semi-arid land surfaces to provide a more gap-free dataset, primarily for visualization purposes. Preliminary validation shows that compared to surface-based sunphotometer data, the C6, Level 2 (along swath) DT-products compare at least as well as those from C5. C6 will include new diagnostic information about clouds in the aerosol field, including an aerosol cloud mask at 500 m resolution, and calculations of the distance to the nearest cloud from clear pixels. Finally, we have revised the strategy for aggregating and averaging the Level 2 (swath) data to become Level 3 (gridded) data. All together, the changes to the DT algorithms will result in reduced global AOD (by 0.02) over ocean and increased AOD (by 0.02) over land, along with changes in spatial coverage. Changes in calibration will have more impact to Terras time series, especially over land. This will result in a significant reduction in artificial differences in the Terra and Aqua datasets, and will stabilize the MODIS data as a target for AEROCOM studie

Aerosol retrieval algorithms↗
NASA NTRS2014

Algorithm Development and Validation of CDOM Properties for Estuarine and Continental Shelf Waters Along the Northeastern U.S. Coast

An extensive set of field measurements have been collected throughout the continental margin of the northeastern U.S. from 2004 to 2011 to develop and validate ocean color satellite algorithms for the retrieval of the absorption coefficient of chromophoric dissolved organic matter (aCDOM) and CDOM spectral slopes for the 275:295 nm and 300:600 nm spectral range (S275:295 and S300:600). Remote sensing reflectance (Rrs) measurements computed from in-water radiometry profiles along with aCDOM() data are applied to develop several types of algorithms for the SeaWiFS and MODIS-Aqua ocean color satellite sensors, which involve least squares linear regression of aCDOM() with (1) Rrs band ratios, (2) quasi-analytical algorithm-based (QAA based) products of total absorption coefficients, (3) multiple Rrs bands within a multiple linear regression (MLR) analysis, and (4) diffuse attenuation coefficient (Kd). The relative error (mean absolute percent difference; MAPD) for the MLR retrievals of aCDOM(275), aCDOM(355), aCDOM(380), aCDOM(412) and aCDOM(443) for our study region range from 20.4-23.9 for MODIS-Aqua and 27.3-30 for SeaWiFS. Because of the narrower range of CDOM spectral slope values, the MAPD for the MLR S275:295 and QAA-based S300:600 algorithms are much lower ranging from 9.9 and 8.3 for SeaWiFS, respectively, and 8.7 and 6.3 for MODIS, respectively. Seasonal and spatial MODIS-Aqua and SeaWiFS distributions of aCDOM, S275:295 and S300:600 processed with these algorithms are consistent with field measurements and the processes that impact CDOM levels along the continental shelf of the northeastern U.S. Several satellite data processing factors correlate with higher uncertainty in satellite retrievals of aCDOM, S275:295 and S300:600 within the coastal ocean, including solar zenith angle, sensor viewing angle, and atmospheric products applied for atmospheric corrections. Algorithms that include ultraviolet Rrs bands provide a better fit to field measurements than algorithms without the ultraviolet Rrs bands. This suggests that satellite sensors with ultraviolet capability could provide better retrievals of CDOM. Because of the strong correlations between CDOM parameters and DOM constituents in the coastal ocean, satellite observations of CDOM parameters can be applied to study the distributions, sources and sinks of DOM, which are relevant for understanding the carbon cycle, modeling the Earth system, and to discern how the Earth is changing.

CDOM Properties↗
NASA NTRS2013

Influence of Observed Diurnal Cycles of Aerosol Optical Depth on Aerosol Direct Radiative Effect

The diurnal variability of aerosol optical depth (AOD) can be significant, depending on location and dominant aerosol type. However, these diurnal cycles have rarely been taken into account in measurement-based estimates of aerosol direct radiative forcing (ADRF) or aerosol direct radiative effect (ADRE). The objective of our study was to estimate the influence of diurnal aerosol variability at the top of the atmosphere ADRE estimates. By including all the possible AERONET sites, we wanted to assess the influence on global ADRE estimates. While focusing also in more detail on some selected sites of strongest impact, our goal was to also see the possible impact regionally.We calculated ADRE with different assumptions about the daily AOD variability: taking the observed daily AOD cycle into account and assuming diurnally constant AOD. Moreover, we estimated the corresponding differences in ADREs, if the single AOD value for the daily mean was taken from the the Moderate Resolution Imaging Spectroradiometer (MODIS) Terra or Aqua overpass times, instead of accounting for the true observed daily variability. The mean impact of diurnal AOD variability on 24 h ADRE estimates, averaged over all AERONET sites, was rather small and it was relatively small even for the cases when AOD was chosen to correspond to the Terra or Aqua overpass time. This was true on average over all AERONET sites, while clearly there can be much stronger impact in individual sites. Examples of some selected sites demonstrated that the strongest observed AOD variability (the strongest morning afternoon contrast) does not typically result in a significant impact on 24 h ADRE. In those cases, the morning and afternoon AOD patterns are opposite and thus the impact on 24 h ADRE, when integrated over all solar zenith angles, is reduced. The most significant effect on daily ADRE was induced by AOD cycles with either maximum or minimum AOD close to local noon. In these cases, the impact on 24 h ADRE was typically around 0.1-0.2W/sq m (both positive and negative) in absolute values, 5-10% in relative ones.

optical depth↗
NASA NTRS2015

Evaluating a New Homogeneous Total Ozone Climate Data Record from GOME/ERS-2, SCIAMACHY/Envisat, and GOME-2/MetOp-A

The European Space Agency's Ozone Climate Change Initiative (O3-CCI) project aims at producing and validating a number of high-quality ozone data products generated from different satellite sensors. For total ozone, the O3-CCI approach consists of minimizing sources of bias and systematic uncertainties by applying a common retrieval algorithm to all level 1 data sets, in order to enhance the consistency between the level 2 data sets from individual sensors. Here we present the evaluation of the total ozone products from the European sensors Global Ozone Monitoring Experiment (GOME)/ERS-2, SCIAMACHY/Envisat, and GOME-2/MetOp-A produced with the GOME-type Direct FITting (GODFIT) algorithm v3. Measurements from the three sensors span more than 16 years, from 1996 to 2012. In this work, we present the latest O3-CCI total ozone validation results using as reference ground-based measurements from Brewer and Dobson spectrophotometers archived at the World Ozone and UV Data Centre of the World Meteorological Organization as well as from UV-visible differential optical absorption spectroscopy (DOAS)/Système D′Analyse par Observations Zénithales (SAOZ) instruments from the Network for the Detection of Atmospheric Composition Change. In particular, we investigate possible dependencies in these new GODFIT v3 total ozone data sets with respect to latitude, season, solar zenith angle, and different cloud parameters, using the most adequate type of ground-based instrument. We show that these three O3-CCI total ozone data products behave very similarly and are less sensitive to instrumental degradation, mainly as a result of the new reflectance soft-calibration scheme. The mean bias to the ground-based observations is found to be within the 1 plus or minus 1 percent level for all three sensors while the near-zero decadal stability of the total ozone columns (TOCs) provided by the three European instruments falls well within the 1-3 percent requirement of the European Space Agency's Ozone Climate Change Initiative project.

Satellite sensors↗
NASA NTRS2014

Dependence of Lunar Surface Charging on Solar Wind Plasma Conditions and Solar Irradiation

The surface of the Moon is electrically charged by exposure to solar radiation on its dayside, as well as by the continuous flux of charged particles from the various plasma environments that surround it. An electric potential develops between the lunar surface and ambient plasma, which manifests itself in a near-surface plasma sheath with a scale height of order the Debye length. This study investigates surface charging on the lunar dayside and near-terminator regions in the solar wind, for which the dominant current sources are usually from the pohotoemission of electrons, J(sub p), and the collection of plasma electrons J(sub e) and ions J(sub i). These currents are dependent on the following six parameters: plasma concentration n(sub 0), electron temperature T(sub e), ion temperature T(sub i), bulk flow velocity V, photoemission current at normal incidence J(sub P0), and photo electron temperature T(sub p). Using a numerical model, derived from a set of eleven basic assumptions, the influence of these six parameters on surface charging - characterized by the equilibrium surface potential, Debye length, and surface electric field - is investigated as a function of solar zenith angle. Overall, T(sub e) is the most important parameter, especially near the terminator, while J(sub P0) and T(sub p) dominate over most of the dayside.

Photoemission↗
NASA NTRS2015

Predicting Clear-Sky Reflectance Over Snow/Ice in Polar Regions

Satellite remote sensing of clouds requires an accurate estimate of the clear-sky radiances for a given scene to detect clouds and aerosols and to retrieve their microphysical properties. Knowing the spatial and angular variability of clear-sky albedo is essential for predicting clear-sky radiance at solar wavelengths. The Clouds and the Earth's Radiant Energy System (CERES) Project uses the nearinfrared (NIR; 1.24, 1.6 or 2.13 micrometers), visible (VIS; 0.63 micrometers) and vegetation (VEG; 0.86 micrometers) channels available on the Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) to help identify clouds and retrieve their properties in both snow-free and snow-covered conditions. Thus, it is critical to have reliable distributions of clear-sky albedo for all of these channels. In CERES Edition 4 (Ed4), the 1.24-micrometer channel is used to retrieve cloud optical depth over snow/ice-covered surfaces. Thus, it is especially critical to accurately predict the 1.24-micrometer clear-sky albedo alpha and reflectance rho for a given location and time. Snow albedo and reflectance patterns are very complex due to surface texture, particle shapes and sizes, melt water, and vegetation protrusions from the snow surface. To minimize those effects, this study focuses on the permanent snow cover of Antarctica where vegetation is absent and melt water is minimal. Clear-sky albedos are determined as a function of solar zenith angle (SZA) from observations over all scenes determined to be cloud-free to produce a normalized directional albedo model (DRM). The DRM is used to develop alpha(SZA=0 degrees) on 10 foot grid for each season. These values provide the basis for predicting r at any location and set of viewing & illumination conditions. This paper examines the accuracy of this approach for two theoretical snow surface reflectance models.

Chen, Yan↗
NASA NTRS2013

Geostationary Enhanced Temporal Interpolation for CERES Flux Products

The Clouds and the Earth's Radiant Energy System (CERES) instruments on board the Terra and Aqua spacecraft continue to provide an unprecedented global climate record of the earth's top-of-atmosphere (TOA) energy budget since March 2000. A critical step in determining accurate daily averaged flux involves estimating the flux between CERES Terra or Aqua overpass times. CERES employs the CERES-only (CO) and the CERES geostationary (CG) temporal interpolation methods. The CO method assumes that the cloud properties at the time of the CERES observation remain constant and that it only accounts for changes in albedo with solar zenith angle and diurnal land heating, by assuming a shape for unresolved changes in the diurnal cycle. The CG method enhances the CERES data by explicitly accounting for changes in cloud and radiation between CERES observation times using 3-hourly imager data from five geostationary (GEO) satellites. To maintain calibration traceability, GEO radiances are calibrated against Moderate Resolution Imaging Spectroradiometer (MODIS) and the derived GEO fluxes are normalized to the CERES measurements. While the regional (1 deg latitude x 1 deg longitude) monthly-mean difference between the CG and CO methods can exceed 25 W m(sub -2) over marine stratus and land convection, these regional biases nearly cancel in the global mean. The regional monthly CG shortwave (SW) and longwave (LW) flux uncertainty is reduced by 20%, whereas the daily uncertainty is reduced by 50% and 20%, respectively, over the CO method, based on comparisons with 15-min Geostationary Earth Radiation Budget (GERB) data.

Doelling, David R.↗