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At least 91 records · Page 5

Global NWP Impacts of Infrared Sounders from Geostationary Orbit

The Geostationary eXtended Observations (GeoXO) program, expected to launch in the 2030s, includes a proposed infrared (IR) sounder that would provide persistent atmospheric profile observations over much of the western hemisphere. In preparation, the National Aeronautics and Space Administration (NASA) Global Modeling and Assimilation Office (GMAO) observing system simulation experiment (OSSE) framework was used to assess the impact of such an instrument on global numerical weather prediction (NWP) as part of a global “ring” of such instruments. Building on previous preliminary studies, an evaluation of the impact of geostationary IR sounders will be presented with foci on the analysis, forecasts, and the forecast sensitivity observation impact (FSOI) metric, including an examination of the consequences for tropical cyclone representation. Overall, assimilation of geostationary IR provide a beneficial impact for NWP applications.

Erica L. Mcgrath-spangler↗

U.S. Plans for Geostationary Hyperspectral Infrared Sounders

NOAA’s Geostationary Extended Observations (GeoXO) satellite system will provide advanced hyperspectral resolution infrared observations. The first GeoXO Sounder (GXS) will fly in the mid-2030s and provide an unprecedented level of information. The plans are for the GXS to be located at a longitude over the center of the U.S. The GXS will be as much of an improvement over the legacy Geostationary Operational Environmental Satellite (GOES)broad-spectral resolution sounder as the Advanced Baseline Imager (ABI) was to the legacy imager. The GXS will be the U.S. contribution to the global ring of geostationary advanced infrared sounders. The GXS sensor will provide unique information about the vertical structure of moisture, winds, and temperature to support both Numerical Weather Prediction (NWP)and nowcasting applications.

Timothy J Schmit↗

GeoSTAR - A Synthetic Aperture Microwave Sounder for Geostationary Missions

The Geostationary Synthetic Thinned Aperture Radiometer (GeoSTAR) is a new microwave atmospheric sounder under development. It will bring capabilities similar to those now available on low-earth orbiting environmental satellites to geostationary orbit - where such capabilities have not been available. GeoSTAR will synthesize the multimeter aperture needed to achieve the required spatial resolution, which will overcome the obstacle that has prevented a GEO microwave sounder from being implemented until now. The synthetic aperture approach has until recently not been feasible, due to the high power needed to operate the on-board high-speed massively parallel processing system required for 2D-synthesis, as well as a number of system and calibration obstacles. The development effort under way at JPL, with important contributions from the Goddard Space Flight Center and the University of Michigan, is intended to demonstrate the measurement concept and retire much of the technology risk.

geostationary↗

Influence of Atmospheric Slant Path on Geostationary Hyperspectral Infrared Sounder Radiance Simulations

Accurately simulating a geostationary hyperspectral infrared sounder is critical for quantitative applications. Traditional radiation simulations of such instruments often overlook the influence of slant observation geometry by using vertical profile assumption, leading to inadequate simulation accuracy. By using global atmospheric profiles with 1 km spatial resolution, the slant-path effects on brightness temperature simulations are quantified. Experiments indicate that the slant geometry has less impact on longwave brightness temperature simulations and has a substantial impact on middle-wave brightness temperature simulations. It may introduce 0.5 K (or more) uncertainty to brightness temperatures of water vapor absorption channels when the satellite zenith angle is greater than 45°. Considering the slant profile is recommended for quantitative applications of geostationary hyperspectral sounder data, such as sounding retrieval and data assimilation.

54 ENVIRONMENTAL SCIENCES↗

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

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

aerosols↗

H31G-1596: DeepSAT's CloudCNN: A Deep Neural Network for Rapid Cloud Detection from Geostationary Satellites

Cloud and cloud shadow detection has important applications in weather and climate studies. It is even more crucial when we introduce geostationary satellites into the field of terrestrial remote sensing. With the challenges associated with data acquired in very high frequency (10-15 mins per scan), the ability to derive an accurate cloud shadow mask from geostationary satellite data is critical. The key to the success for most of the existing algorithms depends on spatially and temporally varying thresholds,which better capture local atmospheric and surface effects.However, the selection of proper threshold is difficult and may lead to erroneous results. In this work, we propose a deep neural network based approach called CloudCNN to classify cloudshadow from Himawari-8 AHI and GOES-16 ABI multispectral data. DeepSAT's CloudCNN consists of an encoderdecoder based architecture for binary-class pixel wise segmentation. We train CloudCNN on multi-GPU Nvidia Devbox cluster, and deploy the prediction pipeline on NASA Earth Exchange (NEX) Pleiades supercomputer. We achieved an overall accuracy of 93.29% on test samples. Since, the predictions take only a few seconds to segment a full multispectral GOES-16 or Himawari-8 Full Disk image, the developed framework can be used for real-time cloud detection, cyclone detection, or extreme weather event predictions.

GOES-1↗

Improved Detection of Low Stratus and Fog at Dawn from Dual Geostationary (COMS and FY-2D) Satellites

A novel method was proposed to detect low stratus and fog (LSF) at dawn during the summertime using near simultaneous observations from dual geostationary-orbit satellites (GEOs): the Korean Communication, Ocean and Meteorological Satellite (COMS; 128.2 degrees East) and the Chinese Feng-Yun-2D (FY-2D; 86.5 degrees East). The orbital positions of the GEOs provided a large difference (around 46.5 degrees) in the viewing zenith angle (VZA) in the study region (122-132 degrees East, 32.5-42.5 degrees North) and high contrast observations at dawn. Numerical simulations were carried out to derive the optical properties of the LSF and the radiative differences between the GEOs due to both the VZA and spectral response function (SRF). The conventional threshold method, which used the visible reflectance at 0.67 microns (R (sub 0.67)) and the brightness temperature difference between 3.7 microns and 11 microns (BTD (sub 3.7-11), had limitations in detecting LSF at dawn due to weak visible light and fast night-to-day transition. We utilized the observed stereo differences (delta R (sub 0.67), delta BTD (sub 3.7-11) between the two GEOs to improve LSF detection. The dual-satellite observations were verified with ground-based data from 45 stations in South Korea co-located with each GEO pixel. The delta R (sub 0.67) threshold value showed better accuracy (78 percent vs. 67 percent) than the conventional R (sub 0.67) threshold method. In addition, the delta BTD (sub 3.7-11) threshold was better (55 percent vs. 38 percent) than the BTD (sub 3.7-11) threshold. The dual-satellite method allowed more reliable LSF detection using the combination of delta R (sub 0.67) and R (sub 0.67), particularly for LSF without cumuliform or high clouds. Our method is applicable to multiple geostationary satellites for continuous LSF monitoring.

geostationary satellite↗

Land Surface Reflectances from Geostationary Sensors

GEONEX is a processing pipeline that produces a suite of satellite land surface products using data streams from the latest geostationary (GEO) sensors including the GOES016/ABI and the Himawari-8/AHI. The suite, created collaboratively by scientists from NASA and NOAA, includes top-of-atmosphere (TOA) reflectances, land surface reflectances (LSRs), vegetation indices, LAI/fPAR, and other downstream products. As a key component of the GEONEX product processing, we have adapted the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm to produce LSRs from the TOA data. Because the algorithm depends on building "stacks" of images, we first run internal geo-registration checks to ensure geo-spatial accuracy and consistency of the input (L1B) data before transferring them from the geostationary projection into a tile system in geographic grids. Scan-time is inferred from metadata and applied to calculate the sun-sensor angles for each grid cell. The MAIAC algorithm is run to detect clouds/shadows, estimate aerosol optical thickness (AOT), perform atmospheric corrections, and generate LSRs. We have processed 18-months (from 2016/04 onward) of AHI data over East Asia and Oceania at a 10-minute time step and 10-months (from 2018/01 onward) of ABI data over North and South Americas at a 15-minute time step. As a verification measure, we compare the GEONEX (AHI/ABI) surface reflectances with the standard MODIS products (MOD09GA) and the MODIS MAIAC products over pixels that have similar sun-view geometries. The results indicate general linear relationships between GEONEX and corresponding MODIS LSRs. In particular, the RMSEs between GEONEX and MOD09 data are comparable to those between MOD09 and MODIS MAIAC products, suggesting that the uncertainties of GEONEX LSRs fall into an acceptable range. However, direct comparisons of LSRs over pixels with different sun-view angles are not as straightforward and require more modeling efforts to correct the directional effects. Evaluation of such angular influences on the downstream products (e.g., vegetation indices) is also under investigation.

Geostationary satellite; Remote Sensing; Atmospher↗

Uncertainties in the Geostationary Ocean Color Imager (GOCI) Remote Sensing Reflectance for Assessing Diurnal Variability of Biogeochemical Processes

Short-term (sub-diurnal) biological and biogeochemical processes cannot be fully captured by the current suite of polar-orbiting satellite ocean color sensors, as their temporal resolution is limited to potentially one clear image per day. Geostationary sensors, such as the Geostationary Ocean Color Imager (GOCI) from the Republic of Korea, allow the study of these short-term processes because their orbit permit the collection of multiple images throughout each day for any area within the sensor’s field of regard. Assessing the capability to detect sub-diurnal changes in in-water properties caused by physical and biogeochemical processes characteristic of open ocean and coastal ocean ecosystems, however, requires an understanding of the uncertainties introduced by the instrument and/or geophysical retrieval algorithms. This work presents a study of the uncertainties during the daytime period for an ocean region with characteristically low-productivity with the assumption that only small and undetectable changes occur in the in-water properties due to biogeochemical processes during the daytime period. The complete GOCI mission data were processed using NASA’s SeaDAS/l2gen package. The assumption of homogeneity of the study region was tested using three-day sequences and diurnal statistics. This assumption was found to hold based on the minimal diurnal and day-to-day variability in GOCI data products. Relative differences with respect to the midday value were calculated for each hourly observation of the day in order to investigate what time of the day the variability is greater. Also, the influence of the solar zenith angle in the retrieval of remote sensing reflectances and derived products was examined. Finally, we determined that the uncertainties in water-leaving “remote-sensing” reflectance (Rrs) for the 412, 443, 490, 555, 660 and 680 nm bands on GOCI are 8.05 × 10−4, 5.49 × 10−4, 4.48 × 10−4, 2.51 × 10−4, 8.83 × 10−5, and 1.36 × 10−4 sr−1, respectively, and 1.09 × 10−2 mg m−3 for the chlorophyll-a concentration (Chl-a), 2.09 × 10−3 m−1 for the absorption coefficient of chromophoric dissolved organic matter at 412 nm (ag (412)), and 3.7 mg m−3 for particulate organic carbon (POC). These Rrs values can be considered the threshold values for detectable changes of the in-water properties due to biological, physical or biogeochemical processes from GOCI.

Geostationary Ocean Color Imager (GOCI)↗

First Provisional Land Surface Reflectance Product from Geostationary Satellite Himawari-8 AHI

A provisional surface reflectance (SR) product from the Advanced Himawari Imager (AHI) on-board the new generation geostationary satellite (Himawari-8) covering the period between July 2015 and December 2018 is made available to the scientific community. The Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm is used in conjunction with time series Himawari-8 AHI observations to generate 1-km gridded and tiled land SR every 10 minutes during day time. This Himawari-8 AHI SR product includes retrieved atmospheric properties (e.g., aerosol optical depth at 0.47μm and 0.51μm), spectral surface reflectance (AHI bands 1–6), parameters of the RTLS BRDF model, and quality assurance flags. Product evaluation shows that Himawari-8 AHI data on average yielded 35% more cloud-free, valid pixels in a single day when compared to available data from the low earth orbit (LEO) satellites Terra/Aqua with MODIS sensor. Comparisons of Himawari-8 AHI SR against corresponding MODIS SR products (MCD19A1) over a variety of land cover types with the similar viewing geometry show high consistency between them, with correlation coefficients (r) being 0.94 and 0.99 for red and NIR bands, respectively. The high-frequency geostationary data are expected to facilitate studies of ecosystems on daily to diurnal time scales, complementing observations from networks such as the FLUXNET.

Himawari-8 AHI↗

A Novel Atmospheric Correction Algorithm to Exploit the Diurnal Variability in Hypertemporal Geostationary Observations

This study developed a new atmospheric correction algorithm, GeoNEX-AC, that is independent from the traditional use of spectral band ratios but dedicated to exploiting information from the diurnal variability in the hypertemporal geostationary observations. The algorithm starts by evaluating smooth segments of the diurnal time series of the top-of-atmosphere (TOA) reflectance to identify clear-sky and snow-free observations. It then attempts to retrieve the Ross-Thick–Li-Sparse (RTLS) surface bi-directional reflectance distribution function (BRDF) parameters and the daily mean atmospheric optical depth (AOD) with an atmospheric radiative transfer model (RTM) to optimally simulate the observed diurnal variability in the clear-sky TOA reflectance. Once the initial RTLS parameters are retrieved after the algorithm’s burn-in period, they serve as the prior information to estimate the AOD levels for the following days and update the surface BRDF information with the new clear-sky observations. This process is iterated through the full time span of the observations, skipping only totally cloudy days or when surface snow is detected. We tested the algorithm over various Aerosol Robotic Network (AERONET) sites and the retrieved results well agree with the ground-based measurements. This study demonstrates that the high-frequency diurnal geostationary observations contain unique information that can help to address the atmospheric correction problem from new directions.

atmospheric correction↗

Spectrally Simplified Approach for Leveraging Legacy Geostationary Oceanic Observations

The use of multispectral geostationary satellites to study aquatic ecosystems improves the temporal frequency of observations and mitigates cloud obstruction, but no operational capability presently exists for the coastal and inland waters of the United States. The Advanced Baseline Imager (ABI) on the current iteration of the Geostationary Operational Environmental Satellites, termed the R Series (GOES-R), however, provides sub-hourly imagery and the opportunity to overcome this deficit and to leverage a large repository of existing GOES-R aquatic observations. The fulfillment of this opportunity is assessed herein using a spectrally simplified, two-channel aquatic algorithm consistent with ABI wave bands to estimate the diffuse attenuation coefficient for photosynthetically available radiation, K(d)(PAR). First, an in situ ABI dataset was synthesized using a globally representative dataset of above- and in-water radiometric data products. Values of K(d)(PAR) were estimated by fitting the ratio of the shortest and longest visible wave bands from the in situ ABI dataset to coincident, in situ K(d)(PAR) data products. The algorithm was evaluated based on an iterative cross-validation analysis in which 80% of the dataset was randomly partitioned for fitting and the remaining 20% was used for validation. The iteration producing the median coefficient of determination (R2) value (0.88) resulted in a root mean square difference of 0.319 m−1, or 8.5% of the range in the validation dataset. Second, coincident mid-day images of central and southern California from ABI and from the Moderate Resolution Imaging Spectroradiometer (MODIS) were compared using Google Earth Engine (GEE). GEE default ABI reflectance values were adjusted based on a near infrared signal. Matchups between the ABI and MODIS imagery indicated similar spatial variability (R2 = 0.60) between ABI adjusted blue-to-red reflectance ratio values and MODIS default diffuse attenuation coefficient for spectral downward irradiance at 490 nm, K(d)(490), values. This work demonstrates that if an operational capability to provide- ABI aquatic data products was realized, the spectral configuration of ABI would potentially support a sub-hourly, visible aquatic data product that is applicable to water-mass tracing and physical oceanography research.

Advanced Baseline Imager↗

On the remote sensing of mesoscale tropical convection intensity from a geostationary satellite.

This paper develops an objective technique for estimating the mass and energy exchange in convection systems corresponding to altocumulus cumulogenitus and cumulonimbus intensities using measurements of the area change of the cirrus outflow on a sequence of satellite cloud photographs obtained at geostationary altitude. The data clearly show that: (1) the technique is able to isolate vigorous and moderate convection regimes on the geostationary satellite cloud photos; and (2) the model-estimated mass and energy are consistent with ground-based measurements such as those of Braham and Brown.

Sikdar, D. N.↗

Preliminary analysis of the implications of natural radiations on geostationary operations

The natural radiations present at geostationary orbit are discussed. Low-level galactic cosmic rays are important for careers spending a year or more at geostationary altitude. Trapped radiation will on occasion require interruption of extravehicular activity (EVA). The spacesuit shield requirements are strongly affected by the number of interruptions allowed. EVA cannot proceed during a large solar event and maximum allowable doses are exceeded in a few hours unless a heavily shielded area is provided. A shelter of 10 g/sq cm with personal shielding for the eyes and testes would contain exposure to within the presently accepted exposure constraints. Since radiation levels can increase unexpectedly to serious levels, an onboard radiation monitoring system with rate and integration capabilities is required for both surface-dose and depth-dose monitoring.

Wilson, J. W.↗

Cost competitive space transportation system for geostationary payloads

A geostationary satellite system designer will have a number of launch vehicles to consider in the system designs for the 1980s. The Space transportation System (the shuttle orbiter plus upper stage) offers the opportunity for lower system cost in comparison with the expendable launch vehicles. An analysis of a spin stabilized solid rocket motor stage has demonstrated the feasibility of this upper stage concept. A cost competitive Space Transportation System (STS) for geostationary payloads is made possible by achievement of the STS cost goals, multiple launch from the STS orbiter, and a user-provided spin stabilized upper stage.

Jones, C. R.↗

Implications of outer-zone radiations on operations in the geostationary region utilizing the AE4 environmental model

The radiation exposure in the region of geostationary orbits is examined in search for means of optimizing human performance. It is found that the use of slightly inclined circular orbits is one means by which exposure and spacesuit thickness requirements can be reduced. Another effective technique is to limit the extravehicular activity to those days when the short term fluctuations result in low exposure. Space-suit shielding approaching 1/2 sq cm or less may be possible by utilizing work stoppages and inclined orbits. If aluminum and other low-atomic-number materials are used to construct the habitat, then excessive wall thicknesses are required. If special bremsstrahlung shielding is used, then the habitat shield may be reduced to as low as 2 g/sq cm. Numerous tables and graphs are presented for future analysis of dose in the geostationary region.

Wilson, J. W.↗

A user assessment of servicing at geostationary orbit

Orbital servicing assessed from the viewpoint of a commercial user of communications satellites at geostationary orbit. The need for servicing is emphasized by looking at the history of failures and defects occurring in communications satellites. The methods used in servicing were evaluated in terms of the needs of a communications satellite user. A system that utilizes servicing was studied, and some benefits in addition to cost savings were identified. Most of the assumptions and conclusions apply to earth observation satellites at geostationary orbit.

Gordon, G. D.↗

An application of a geostationary satellite rain estimation technique to an extratropical area

Previous studies in which geostationary-satellite images were used for estimating precipitations dealt primarily with tropical clouds. In the present study, an attempt is made to evaluate the applicability of geostationary images and techniques in the Montreal area, characterized by a variety of weather situations and variables (different types of cloud, moisture and temperature profiles, and rain rates). The large differences between the Montreal and tropical studies are shown to be reflected by Simpson and Wiggert's (1969) cloud model.

Wylie, D. P.↗