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The NASA CERES project has provided the climate quality observed TOA and computed surface fluxes to the scientific community. CERES uses MODIS and VIIRS imagers to retrieve cloud properties needed to convert Terra, Aqua, NPP, and NOAA-20 CERES footprint radiance observations into fluxes. The imagers are also used to radiometrically scale the geostationary sensors (GEO) radiances to the imager calibration reference to ensure that the GEO derived cloud properties and broadband TOA fluxes are consistent in both space and time. Both the imager and GEO retrieved cloud properties are used to compute the surface fluxes. The CERES imager and GEO calibration team uses ray-matched radiance pairs to radiometrically scale the SNPP and NOAA-20 VIIRS sensors to the Aqua-MODIS calibration reference. The radiometric scaling is further validated using geostationary imagers as transfer radiometers. The team will rely primarily on deep convective clouds to monitor the imager channel calibration stability and to correct for short term calibration drifts. The DSCOVR satellite was launched on February 25, 2015 and orbits around the L1 Lagrange point directly between the Earth and the sun. The EPIC sensor contains no onboard calibration systems. However, multiple inter-calibration studies have shown that the EPIC imager is very stable in time. The excellent radiometric stability of EPIC allows the use of EPIC observations as a stable reference to validate both the short term drift corrections of the imagers, as well as to validate the radiometric scaling factors between them. Examples of the imager relative calibration using EPIC before and after radiometric scaling will be shown along with the results from the use of invariant targets to remove imager calibration drifts.

The CERES project relies on MODIS, VIIRS and geostationary (GEO) imager retrieved cloud properties to compute surface fluxes and convert CERES and GEO radiances into TOA fluxes. The CERES TOA and surface fluxes need to be of climate quality and any anomaly or discontinuity in the calibration of the MODIS, VIIRS, GEO radiances need to be mitigated or avoided. Otherwise the variations in the cloud properties will be improperly interpreted as climate signals. Due to the nature of the CERES instrument calibration, there is a lag time of 3 months before the processing of the CERES product. This allows the CERES team to investigate any unforeseen problems in the input datasets before processing. The CERES geostationary imager calibration team has set up a daily monitoring system of GEO, MODIS and VIIRS radiances in order to detect any day to day discontinuities as part of the CERES/GEO coincident ray-matching calibration efforts. A MODIS calibration discontinuity can be detected using five GEO sensors simultaneously, whereas a GEO discontinuity can be detected using 2 MODIS and 2 VIIRS sensors simultaneously, thus increasing the sampling greatly over a single GEO/LEO radiance pairs. This method is being automated and has already detected a GOES-16 erroneous radiometric calibration for VNIR bands that was experienced between Jan 18 to 22, 2019. It has also detected the usage of an incorrect LUT for NOAA-20 VIIRS processing for the CERES project prompting a reprocessing effort. This monitoring system is more reliable than those based on invariant Earth targets and can nearly pinpoint the GMT time of the discontinuity.

We present a fast and accurate, semi-analytical method for predicting hydrogen adsorption in nanoporous materials. For any temperature and pressure, the adsorbed amount is calculated as an integral over the energy density of adsorption sites (guest-host interactions) plus an average guest-guest term. The guest-host interaction energy is calculated using a classical force field with hydrogen modelled as a single-site probe. The guest-guest interaction energy is approximated using an average coordination number, which is regressed using Gaussian Process Regression (GPR). Local adsorption at each site is then modelled using a Langmuir isotherm, which when weighted with its probability density gives an accurate description of hydrogen adsorption. The method is tested on 933 metal-organic frameworks (MOFs) from the Computation-Ready Experimental (CoRE) MOF database at 77 K from 10−5 to 100 bar, and the results are compared against GCMC predictions. To demonstrate the utility of the method, we calculated hydrogen adsorption isotherms for 12,914 existing MOF structures, at two different temperatures at a speed about 100 times that of GCMC simulations and analyzed the results. We found 13 MOFs with predicted deliverable capacities exceeding the DOE target of 50 g/L for adsorption at 100 bar, 77 K and desorption at 5 bar, 160 K.

Tropical deep convective clouds (DCC) are proven to be an excellent invariant target for post-launch radiometric calibration of satellite visible (VIS) and near-infrared (NIR) spectral channels. The DCC technique (DCCT) is a statistical approach that collectively analyzes DCC pixels and provides a near lambertian reflectance suitable for inter-calibration. At shortwave infrared (SWIR) wavelengths, the DCC reflectance is impacted by the ice microphysical properties of particle size and optical depth, thereby increasing the temporal noise in the DCC response. The key to improving the DCCT for satellite SWIR bands calibration is proper characterization of the DCC reflectance at SWIR wavelengths. This paper will present empirical bidirectional reflectance distribution function (BRDF) models based on multiple years of NPP-VIIRS DCC measurements to mitigate the seasonal variation in the SWIR band DCC reflectance. The DCC BRDF models are wavelength-specific and are effective in reducing the temporal noise in the DCC response by up to 50%. Application of these BRDF models to the Aqua-MODIS and JPSS-1 VIIRS imagers for radiometric inter-comparison will be discussed. Another factor that impacts the stability of the SWIR band DCC reflectance is the infrared brightness temperature (IR-BT) threshold used for identifying the DCC pixels. The optimal BT threshold for achieving the most predictable DCC response for individual SWIR bands will also be addressed. The channel-specific BRDFs and BT thresholds will help to extend the use of DCCT to SWIR bands inter-calibration.

The CERES project relies on the MODIS and VIIRS sensors for cloud retrievals to convert the CERES observed radiances into fluxes. In order to produce climate quality data records, the cloud properties derived from the MODIS instruments onboard Terra and Aqua as well as from the VIIRS instruments onboard NPP and JPSS-1 must be consistent. Although MODIS and VIIRS have onboard solar diffusers to actively monitor inflight calibration, the absolute radiometric calibration may still differ between them, which could cause discontinuities between sensor records. The projected plan for the JPSS constellation is to maintain two operational satellites, which are spaced 45 minutes apart in the same 1:30 PM sun-synchronous orbit. The projected orbital configuration will provide no simultaneous nadir orbit (SNO) inter-calibration opportunities between any of the two operational VIIRS sensors. VIIRS inter-calibration approaches must then rely on Earth invariant or lunar targets. This presentation will demonstrate the use Libya-4, Dome-C, and deep convective cloud (DCC) Earth invariant targets to radiometrically scale the spectrally matching visible channels of VIIRS to MODIS. The new 3rd generation geostationary (GEO) satellites, such as GOES-16 and Himawari-8, have multiple visible bands that are spectrally similar to those of MODIS and VIIRS. A double-difference technique of inter-calibration will be presented using GOES-16 and Himawari-8 as transfer radiometers. We will also present all-sky tropical ocean (ATO) and DCC ray-matching approaches that use coincident, co-angled, and co-located MODIS and VIIRS instantaneous radiances for inter-calibration. The ATO method captures the complete earth observed radiance range and will be used to validate the Earth invariant target and GEO transfer radiometer methods. Consistency between all of the independent MODIS to VIIRS inter-calibration approaches validates all approaches.

NASA Langley Research Center; Rajendra Bhatt, Arun Gopalan, Conor Haney, Benjamin Scarino – Science Systems and Applications, Inc. (SSAI) ABSTRACT: The ISCCP project provides a 40-year geostationary (GEO) imager record of 3-hourly cloud properties and surface reflectances. ISCCP coordinated the ingestion of 3-hourly geostationary imager pixel level radiances, placing them in a common format across GEO imagers and archiving the datasets for future reprocessing efforts. The ISCCP project is currently is trying to faithfully reproduce the historical DX results in the new processing environment. Once this has been achieved, new calibration coefficients and cloud retrieval algorithms can be processed and compared to the original algorithms and validated for stability across the record. CERES is currently releasing their Edition4 data products, where the GEO imager calibration, has been referenced to the Aqua-MODIS band 1 Collection 6 calibration (https://www-pm.larc.nasa.gov/cgi-bin/site/showdoc?mnemonic=CALIB-ED4). The same calibration approach was applied to the 40-year AVHRR visible imagers record (https://www-pm.larc.nasa.gov/cgi-bin/site/showdoc?mnemonic=SATCALIB2&c=home). The pre-2000 GEO imager calibration strategy relies on deep convective cloud and invariant desert calibration targets, which have been characterized using post-2000 reference GEO imagers based on the Edition 4 calibration. Since the GEO imaging schedules do not change over time, the angular distribution of the targets repeat themselves annually. This approach will provide better stability across sensors, rather than using ray-matched AVHRR/GEO radiance pairs, since the NOAA satellite orbits drift in time, making it difficult discern GEO calibration and NOAA satellite drifts. This provides the ISCCP project another set of calibration coefficients, which are consistent across sensor platforms, in order to retrieve climate quality cloud properties.

Accurate characterization of the Earth’s radiant energy is critical for many climate monitoring and weather forecasting applications. Therefore, in order to facilitate reliable, climate-quality retrievals, it is important that consistent calibration coefficients across satellite platforms are made available to the remote sensing community, and that calibration anomalies are recognized and mitigated. One such anomaly is the infrared imager brightness temperature drift that occurs for many geostationary (GEO) satellite instruments near local midnight. This anomaly has been extensively documented, with corrections offered, for the Geostationary Operational Environmental Satellite system (GOES) series of satellites, and is thought to be caused by solar heating of the instrument. Owing to the diurnal dependency of this midnight inconsistency, the commonly referenced calibration standards, as proposed by the Global Space-Based Inter-Calibration System (GSICS) community, are insufficient. The Infrared Atmospheric Sounding Interferometer (IASI) and Atmospheric Infrared Sounder (AIRS) hyperspectral reference standards cannot be used to resolve the calibrations over all hours of the diurnal cycle given their MetOp/Aqua platforms are in late-morning/early-afternoon sun-synchronous orbits. The precessionary orbit of the Tropical Rainfall Measuring Mission (TRMM) Visible and Infrared Scanner (VIRS), however, allows for full local diurnal sampling over 46 days. Thus, VIRS has the capability of providing hourly temperature adjustments for concurrent GEO sensors in order to mitigate the midnight effect. To achieve this goal, VIRS is compared with Aqua-MODIS, thereby ensuring that VIRS IR measurements were stable between 2002 and 2012. Furthermore, VIRS IR calibration artifacts, i.e., temperature dependencies, are characterized and corrected by first calibrating with IASI. The validity of this methodology is tested through direct comparisons of GEO/VIRS diurnally adjusted temperatures with measurements from IASI.

Deep Convective Clouds (DCC) are bright, nearly isotropic earth targets extending up to the tropopause, making them favorable as pseudo invariant calibration sites (PICS). Located in all tropical domains, DCC can be observed by both geostationary (GEO) and low earth orbit (LEO) satellites, allowing for large ensemble statistical comparisons of the instrument sensors aboard the respective satellites to measure variation in sensor response. The stability of the GEO instrument can be monitored over time using monthly DCC PDF mode visible reflectances of GEO pixels over the corresponding domain. The temporal stability of DCC reflectances has been well documented. The inter-annual variability of the regional seasonal and diurnal cycle DCC reflectances are very small. The more difficult part of DCC calibration is tying the GEO DCC mode reflectance to the Aqua-MODIS 0.65 µm band calibration reference as recommended by the GSICS community. It has been shown that the DCC mode reflectance is dependent on the IR threshold temperature. If the GEO and MODIS imagers had the same IR temperature threshold, it can be assumed that the GEO and MODIS DCC monthly mode reflectance should be equal over the GEO domain during the MODIS overpass time provided they have the similar visible spectral responses. If this assumption is verified then any GEO in this GEO domain can be anchored to the MODIS calibration and therefor can be applied to historical GEOs. This assumption is verified by using GEO and MODIS ray-matched 10-km or 30-km pixel level averaged radiance pairs to transfer the MODIS calibration. In order to reduce the spectral band differences the ray-matched radiance pairs are limited over DCC. Another permutation of this method is to compare the GEO and MODIS monthly DCC mode reflectance using the same pixel-level ray-matched radiances. This will allow for a reliable transfer of a well-calibrated reference sensor calibration using DCC calibration.

The Multi-functional Transport Satellite (MTSAT)-1R is a geostationary imager located at 140°E over the tropical western pacific operated by the Japanese Meteorological Agency and was launched on February 26, 2005. It has been operational from June 2005 to June 2010 and now serves as the backup instrument when the MTSAT-2 ground segment is maintained annually during November and December. The Clouds and the Earth's Radiant Energy System (CERES) project utilizes geostationary (GEO) derived broadband fluxes to infer the regional diurnal cycle between CERES observed broadband observations. The GEO visible channels are first calibrated against Aqua-MODIS using ray-matched coincident 0.5° gridded radiance pairs, which are regressed monthly to determine the GEO calibration coefficients. Unlike other GEOs the MTSAT-1R visible channel exhibited a nonlinear sensor response. In order to ensure that the ray-matching algorithm is not introducing any systematic biases, the navigation, the MTSAT-1R and MODIS spectral band differences, and MTSAT-1R space offset are carefully examined and were determined not to be the cause. Also Terra-MODIS or TRMM-VIRS and MTSAT-1R ray-matched radiance pairs also showed similar nonlinear behavior. However, VIRS onboard the TRMM precessing satellite, revealed that the nonlinear behavior was dependent on solar zenith angle or dynamic range. No further progress could be achieved until coincident MTSAT-2 and MTSAT-1R images taken in December 2010 became available. Comparing the coincident imagery the image blurring effect was noticeable. Dark regions neighboring bright clouds within 500-km were brightened. This effect was not noticed in the IR imagery, even though both visible and IR optical paths are shared. The slight blurring effect is attributed to the mirror surface by either flawed polishing or by a dust contaminant. The dispersed light of the signal was assumed to be small and randomly distributed around the optical axis allowing the image to be deconvolved using an inverted point spread function. The PSF removed ~80% of the blurring effect and the MTSAT-1R sensor observed a linear response when ray-matched with Aqua-MODIS radiance pairs. This chain of events, emphasizes the need for coincident imagery when replacing operational GEO imagers, as part of the commissioning process. If MTSAT-2, which was launched in February 2006, provided coincident imagery with MTSAT-1R within a few months after launch, retrieval quality imagery could have been available 5-years earlier.

Tropical Deep Convective Clouds (DCC) are the brightest, nearly isotropic, tropopause-level earth invariant targets or solar diffusers, making them suitable as pseudo invariant calibration sites (PICS). DCC are observed by both low earth orbit and geostationary (GEO) satellites, since they are found over all tropical domains. DCC calibration is a statistical technique that collectively analyzes all identified DCC over a geographical domain by a simple IR threshold. After the pixel level application of a DCC Bidirectional Reflectance Distribution Function (BRDF), the DCC monthly mode statistic can accurately verify the temporal stability of the sensor response. The temporal standard error is equal to or better than other desert and polar ice PICS. Another advantage of DCC is that they are spectrally flat in the visible and near IR, since they are above the tropopause where there is little water vapor absorption. The most difficult aspect of DCC absolute calibration is the calibration transfer from a reference instrument. The GSICS community has decided on Aqua-MODIS 0.65µm as the calibration reference. As the calibration of future VIIRS or CLARREO hyper-spectral instruments improves, the superior calibration can be transferred back in time using Simultaneous Nadir Overpasses (SNO)s. Since DCC calibration is a statistical method that relies on ~100K DCC identified pixels, the feasibility of pixel-level matching between reference and target sensor is virtually impossible. It also preferable to characterize the DCC with a reference instrument so that the absolute calibration can be inferred even when there is no simultaneous GEO and MODIS data available. If the frequency histogram of the GEO and MODIS pixel level radiances are very similar and obtained over the same domain and time range with the same DCC algorithm, then the GEO and MODIS mode radiance should be similar. This assumption will be tested by transferring the Aqua-MODIS reference calibration using ray-matched coincident radiance pairs over DCC. Sensitivity to other factors such as GEO and MODIS threshold temperature and pixel resolution differences will also be examined in obtaining the histogram mode DCC radiance.

Uniform radiometric calibration of satellite sensors is vital to the scientists and researchers around the world that use the satellite retrieved properties to study the Earth’s climate. In order to consistently calibrate sensors that have varying degrees of onboard calibration over time, an invariant target approach is needed. Fortunately, all satellite sensors are able to view deep convective clouds (DCC), which are bright, nearly-isotropic solar diffusers that can be easily identified via a simple infrared (IR) brightness temperature threshold. Also, most sensors have a window channel, which are historically well-calibrated using onboard black-bodies. If the DCC reflectivity is predictable in space and time, then the DCC can be used as an absolute reference for past, present, and future operational sensors. This study focuses on analyzing and optimizing the DCC identification criteria in order to derive the most consistent DCC reflectance fields over the tropics, while maintaining the greatest regional temporal stability. The DCC reflectances were characterized using the well-calibrated Aqua-MODIS 0.65 micron channel radiances. The DCC calibration technique revealed that the Aqua-MODIS 0.65µm radiances are temporally stable to within 0.5%/decade based on 9-years of data over the entire tropics. Replacing the DCC bidirectional reflectance distribution function (BRDF) model with a Lambertian BRDF model increased the Aqua-MODIS temporally stability to 0.7%, verifying that the DCC reflectance were nearly isotropic. It is known that the seasonal and diurnal distribution of DCC varies geographically over tropics. However, the inter-annual variability of the distribution is small and very predictable. The DCC reflectance was found to be dependent on the IR threshold criteria, indicating that a comparable IR temperature threshold is necessary to transfer the absolute visible calibration across visible sensors. It was also found that the lowest DCC reflectances were found over the tropical western pacific but the brightest DCC were not always found exclusively over land. These differences can easily be accounted for when using DCC as an invariant Earth target, allowing for a uniform and consistent calibration target for visible sensors.

The goal of the Global Space-Based Inter-Calibration System (GSICS) and the future Climate Absolute Radiance and Refractivity Observatory (CLARREO) missions are to provide consistent calibration coefficients across satellite platforms in order to provide reliable, climate-quality retrievals. A calibration transfer that ties hyper-spectral radiances to an absolute, or traceable, calibration reference is preferred. Hyper-spectral data can be used to easily account for the varying spectral bands of operational sensors. Currently, GSICS uses the well-calibrated Infrared Atmospheric Sounding Interferometer (IASA) hyper-spectral radiances to calibrate geostationary satellite (GEO) IR radiances. To date, no such hyper-spectral instrument has been used as a direct GEO visible calibration reference. The ENVISAT Scanning Imaging Absorption spectroMeter for Atmospheric CartograpHY (SCIAMACHY) hyper-spectral data have the potential to function as a transfer medium for the absolute calibration reference of the MODerate-resolution Imaging Spectroradiometer (MODIS) and GEO imagers. Additionally, SCIAMACHY can be used to adjust for imager spectral response function (SRF) differences. The SCIAMACHY absolute calibration and stability are evaluated by cross-calibrating SCIAMACHY with Aqua-MODIS at the ground track intersects near the poles, thereby serving as a calibration transfer standard. Preliminary results indicate excellent calibration transfer given that direct comparisons of Aqua-MODIS and SCIAMACHY-convolved-with-Aqua-MODIS-SRF radiances have a monthly temporal uncertainty of 0.44%, and a relative trend of -0.2% per decade. The number of ray-matched, or bore-sighted, SCIAMACHY and GEO radiance pairs is limited by the size of the SCIAMACHY footprint, the number of footprints along the cross-track, and the nadir/limb view duty cycle. Relaxing the ray-matching criteria allows sufficient sampling for seasonal inter-calibration without detriment to the calibration transfer. This calibration approach reveals that the SCIAMACHY-to-Meteosat-9 0.65-µm calibration transfer is within 1% of other Meteosat-9 calibration techniques. Furthermore, this method yields one of the lowest temporal uncertainties of all approaches, most likely because no SRF adjustment is required.

An Internet transaction is a transaction that involves communication over the Internet using standard Internet protocols such as HTTPS. Such transactions are widely used in Internet-based applications such as e-commerce. With the growth of the Internet, the volume and complexity of Internet transactions are rapidly increasing. We present data versioning techniques that can reduce the complexity of managing Internet transactions and improve their scalability and reliability. These techniques have been implemented using standard database technology, without any change in database kernel. Our initial empirical results argue for the effectiveness of these techniques in practice.

Database applications such as enterprise resource planning systems and customer relationship management systems are widely used software systems. Development and testing of database applications is difficult because the program execution depends on the persistent state stored in the database. In this paper we show that how versioning of the persistent data stored in the database can solve some critical problems in the development and testing of database applications can be solved by versioning the data stored in the database. Our solution framework is based on long transaction management, a well-researched branch of database systems. We also present empirical results that show the proposed framework's effectiveness in practice.

In this paper we present a more efficient record based caching model than the conventional page (disk block) based scheme. In a record caching model, individual records are stored together in a section of shared memory to form the cache. Traditional relational database systems have individual pages that are stored together in shared memory to form the cache and records are then extracted from these pages on demand. The record cache model has better memory utilization than the page model and also helps reduce overheads like page fetches/writes, page locks and code path. In May 1996, Oracle Rdb announced a record breaking number of 14227 tpmC on a Digital AlphaServer 8400. At the time, this was the best TPC-C performance achieved on a single SMP machine. A total of 15 record caches, caching 19.5 million records, consuming almost 7 GB of memory, formed the bulk of the shared memory.