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At least 289 records · Page 16

Geostationary Operational Environmental Satellite (GOES-N report). Volume 2: Technical appendix

The contents include: operation with inclinations up to 3.5 deg to extend life; earth sensor improvements to reduce noise; sensor configurations studied; momentum management system design; reaction wheel induced dynamic interaction; controller design; spacecraft motion compensation; analog filtering; GFRP servo design - modern control approach; feedforward compensation as applied to GOES-1 sounder; discussion of allocation of navigation, inframe registration and image-to-image error budget overview; and spatial response and cloud smearing study.

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Thermal and structural analysis of the GOES scan mirror's on orbit performance

The on-orbit performance of the GOES satellite's scan mirror has been predicted by means of thermal, structural, and optical models. A simpler-than-conventional thermal model was used to reduce the time required to obtain orbital predictions, and the structural model was used to predict on-earth gravity sag and on-orbit distortions. The transfer of data from the thermal model to the structural model was automated for a given set of thermal nodes and structural grids.

Zurmehly, G. E.↗

Detection of CO J = 2 goes to 1 emission from the polar rings of NGC 2685 and NGC 4650A

We report the detection of the J = 2 goes to 1 (230 GHz) line of carbon monoxide in the polar rings of the galaxies NGC 2685 and NGC 4650A, and we use the results in a simple analysis of the composition of the neutral interstellar medium therein. Only 17%-35% of the gas mass of the NGC 4650A ring is provided by molecular clouds, perhaps consistent with the conventional picture of the origin of polar rings in the capture of a dwarf galaxy or tidal mass transfer from a spiral galaxy. The polar ring of NGC 2685, however, is quite rich in molecular matter, with an H2 mass greater than the neutral atomic hydrogen mass. Such a composition may be difficult to explain with the picture that applies to NGC 4650A.

Watson, Dan M.↗

Precipitable Water Variability Using SSM/I and GOES VAS Pathfinder Data Sets

Determining moisture variability for all weather scenes is critical to understanding the earth's hydrologic cycle and global climate changes. Remote sensing from geostationary satellites provides the necessary temporal and spatial resolutions necessary for global change studies. Due to antenna size constraints imposed with the use of microwave radiometers, geostationary satellites have carried instruments passively measuring radiation at infrared wavelengths or shorter. The shortfall of using infrared instruments in moisture studies lies in its inability to sense terrestrial radiation through clouds. Microwave emissions, on the other hand, are mostly unaffected by cloudy atmospheres. Land surface emissivity at microwave frequencies exhibit both high temporal and spatial variability thus confining moisture retrievals at microwave frequencies to over marine atmospheres (a near uniform cold background). This study intercompares the total column integrated water content Precipitable Water, (PW) as derived from both the Special Sensor Microwave Imager (SSM/I) and the Geostationary Operational Environmental Satellite (GOES) VISSR Atmospheric Sounder (VAS) pathfinder data sets. PW is a bulk parameter often used to quantify moisture variability and is important to understanding the earth's hydrologic cycle and climate system. This research has been spawned in an effort to combine two different algorithms which together can lead to a more comprehensive quantification of global water vapor. The approach taken here is to intercompare two independent PW retrieval algorithms and to validate the resultant retrievals against an existing data set, namely the European Center for Medium range Weather Forecasts (ECMWF) model analysis data.

Lerner, Jeffrey A.↗

Comparison of Lidar Backscatter with Particle Distribution and GOES-7 Data in Hurricane Juliette

Measurements of calibrated backscatter, using two continuous wave Doppler lidars operating at wavelengths 9.1 and 10.6 micrometers were obtained along with cloud particle size distributions in Hurricane Juliette on 21 September 1995 at altitude approximately 11.7 km. Agreement between backscatter from the two lidars and with the cloud particle size distribution is excellent. Features in backscatter and particle number density compare well with concurrent GOES-7 infrared images.

Jarzembski, Maurice A.↗

Comparison of registration techniques for GOES visible imagery data

This paper briefly describes and then compares the effectiveness of five image registration approaches for GOES visible band imagery. The techniques compared are (1) NOAA "point" manual landmarking, (2) manual landmarking on extant feature (whole island, lake, etc.), (3) automatic phase correlation, (4) automatic spatial correlation on edge features, and (5) automatic spatial correlation of region boundaries derived from image segmentation.

Tilton, James C.↗

Iterative edge- and wavelet-based image registration of AVHRR and GOES satellite imagery

Most automatic registration methods are either correlation-based, feature-based, or a combination of both. Examples of features which can be utilized for automatic image registration are edges, regions, corners, or wavelet-extracted features. In this paper, we describe two proposed approaches, based on edge or edge-like features, which are very appropriate to highlight regions of interest such as coastlines. The two iterative methods utilize the Normalized Cross-Correlation of edge and wavelet features and are applied to such problems as image-to-map registration, landmarking, and channel-to-channel co-registration, utilizing test data, AVHRR data, as well as GOES image data.

LeMoigne, Jacqueline↗

Comparison of CO2 Lidar Backscatter with Particle Size Distribution and GOES-7 Data in Hurricane Juliette

Backscatter measurements using 9.1 and 10.6 micron continuous wave lidars were obtained along with particle size distributions in 1995 Hurricane Juliette at altitude approximately 11.7 km. Agreement between lidar backscatter and cloud particle size distribution was excellent. Measurements also correlated well with concurrent GOES-7 infrared images of cloud top height.

Jarzembski, Maurice↗

Operational Assimilation of GOES Data into a Mesoscale Model

A technique has been developed for assimilating GOES-derived skin temperature tendencies and insolation into the surface energy budget equation of a mesoscale model so that the simulated rate of temperature change closely agrees with the satellite observations. A critical assumption of the technique is that the availability of moisture (either from the soil or vegetation) is the least known term in the model's surface energy budget. Therefore, the simulated latent heat flux, which is a function of surface moisture availability, is adjusted based upon differences between the modeled and satellite- observed skin temperature tendencies. An advantage of this technique is that satellite temperature tendencies are assimilated in an energetically consistent manner that avoids energy imbalances and surface stability problems that arise from direct assimilation of surface shelter temperatures. The fact that the rate of change of the satellite skin temperature is used rather than the absolute temperature means that sensor calibration is not as critical. The technique has been employed on a semi-operational basis at the Global Hydrology and Climate Center (GHCC) within the Penn State/National Center for Atmospheric Research (PSU/NCAR) Mesoscale Model (MM5) since 1 November 1998. We performed the assimilation on a model grid centered over the Southeastern US. In addition, a control run without assimilation was performed to provide insight into the performance of the assimilation technique. Bulk verification statistics (BIAS and RMSE) of surface air temperature and relative humidity of more than 250 case days has been performed to date. Results show that assimilation of the satellite data results reduces both the bias and RMSE for simulations of surface air temperature and relative humidity. We are working with forecasters at the National Weather Service Forecast Office located in Birmingham, AL to evaluate the impact of the assimilation on precipitation forecasts. In addition, work is currently underway to determine the ability of both the assimilation technique and Early Eta to sense the significant changes that occur in both leaf expansion and soil moisture conditions during the Spring-Summer of 1999. This will be accomplished via examination of the simulated surface energy budgets from both modeling systems.

Lapenta, William↗

Comparison fo CO2 Lidar Backscatter with Particle Size Distribution and GOES-7 Data in Hurricane Juliette

Two NASA/MSFC continuous wave (CW) focused Doppler lidars obtained in-situ high resolution calibrated backscatter measurements in the upper levels of Hurricane Juliette as part of the 1995 NASA/Multicenter Airborne Coherent Atmospheric Wind Sensor (MACAWS) mission on board NASA's DC8 aircraft. These were also intercompared with in-situ cloud particle size distributions obtained from NASA/Ames Research Center's forward scattering spectrometer probe (FSSP), the DC8 aircraft infrared (IR) surface temperature radiometer data, and the Geostationary Operational Environmental Satellites (GOES-7) 11 micrometer IR emission images with their corresponding estimates of cloud top temperature and height. Two traverses of Hurricane Juliette's eye were made off the west coast of Mexico at altitude approx. 11.7 km on 21 September 1995. During this DC8 flight, late stages of eyewall decay-replacement cycles were observed, giving the appearance of an annular eye with clouds in the central region.

Jarzembski, Maurice A.↗

Cooler Deployment, GOES J on ATLAS

This NASA Kennedy Space Center video release presents footage of workcrews overseeing the cooler deployment on the GOES-J weather satellite that will be launched on the Atlas Centaur rocket from Complex 36 at the Cape Canaveral Air Station.

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EHL Transition Temperature Measurements on a Geostationary Operational Environmental Satellite (GOES) Filter Wheel Bearing

The elastohydrodynamic lubrication (EHL) transition temperature was measured for a Geostationary Operational Environmental Satellite (GOES) sounder filter wheel bearing in a vacuum tribometer. Conditions included both an 89 N (20 lb.) hard and soft load, 600 rpm, temperatures between 23 C (73 F) and 85 C (185 F), and a vacuum of approximately 1.3 x 10(exp -5) Pa. Elastohydrodynamic to mixed lubrication started to occur at approximately 70 C (158 F).

Jansen, Mark J.↗

Assimilation of GOES Land Surface Data into a Mesoscale Models

A technique has been developed for assimilating Geostationary Operational Environmental Satellite (GOES)-derived skin temperature tendencies and insolation into the surface energy budget equation of a mesoscale model so that the simulated rate of temperature change closely agrees with the satellite observations. A critical assumption of the technique is that the availability of moisture (either from the soil or vegetation) is the least known term in the model's surface energy budget. Therefore, the simulated latent heat flux, which is a function of surface moisture availability, is adjusted based upon differences between the modeled and satellite-observed skin temperature tendencies. An advantage of this technique is that satellite temperature tendencies are assimilated in an energetically consistent manner that avoids energy imbalances and surface stability problems that arise from direct assimilation of surface shelter temperatures. The fact that the rate of change of the satellite skin temperature is used rather than the absolute temperature means that sensor calibration is not as critical. The assimilation technique has been applied to the Oklahoma-Kansas region during the spring-summer 2000 time period when dynamic changes in vegetation cover occur. In April, central Oklahoma is characterized by large NDVI associated with winter wheat while surrounding areas are primarily rangeland with lower NDVI. In July the vegetation pattern reverses as the central wheat area changes to low NDVI due to harvesting and the surrounding rangeland is greener than it was in April. The goal of this study is to determine if assimilating satellite land surface data can improve simulation of the complex spatial distribution of surface energy and water fluxes across this region. The PSU/NCAR NM5 V3 system is used in this study. The grid configuration consists of a 36-km CONUS domain and a 12-km nest over the area of interest. Bulk verification statistics (BIAS and RMSE) of surface air temperature and dewpoint indicates that assimilation of the satellite data results reduces both the bias and RMSE for both state variables. In addition, comparison of model data with ARM/CART EBBR flux observations reveals that the assimilation technique adjusts the bowen ratio in a realistic fashion.

Lapenta, William M.↗

Assimilation of GOES Land Surface Data: Benefits to Numerical Weather Prediction

A technique has been developed for assimilating GOES-derived skin temperature tendencies and insolation into the surface energy budget equation of a mesoscale model so that the simulated rate of temperature change closely agrees with the satellite observations. A critical assumption of the technique is that the availability of moisture (either from the soil or vegetation) is the least known term in the model's surface energy budget. Therefore, the simulated latent heat flux, which is a function of surface moisture availability, is adjusted based upon differences between the modeled and satellite observed skin temperature tendencies. An advantage of this technique is that satellite temperature tendencies are assimilated in an energetically consistent manner that avoids energy imbalances and surface stability problems that arise from direct assimilation of surface shelter temperatures. The fact that the rate of change of the satellite skin temperature is used rather than the absolute temperature means that sensor calibration is not as critical. The technique has been employed on a semi-operational basis at the GHCC within the PSU/CAR MM5 since 1 November 1998. A one-way nested grid configuration was employed with a 75 kin CONUS domain and a 25 km grid over the southeastern United States. Initial conditions were obtained from the 12 UTC Early Eta Data Assimilation System analyses and lateral boundary conditions from the Early Eta forecast available at 3 hour intervals. The satellite-derived land surface temperature tendencies and insolation were assimilated between two and five hours (1400 and 1650 UTC) of the forecast. We performed the assimilation on the Southeastern domain only. In addition, a control run without assimilation was performed to provide insight into the performance of the assimilation technique.

Lapenta, William M.↗

A 3-Year Climatology of Cloud and Radiative Properties Derived from GOES-8 Data Over the Southern Great Plains

While the various instruments maintained at the Atmospheric Radiation Measurement (ARM) Program Southern Great Plains (SGP) Central Facility (CF) provide detailed cloud and radiation measurements for a small area, satellite cloud property retrievals provide a means of examining the large-scale properties of the surrounding region over an extended period of time. Seasonal and inter-annual climatological trends can be analyzed with such a dataset. For this purpose, monthly datasets of cloud and radiative properties from December 1996 through November 1999 over the SGP region have been derived using the layered bispectral threshold method (LBTM). The properties derived include cloud optical depths (ODs), temperatures and albedos, and are produced on two grids of lower (0.5 deg) and higher resolution (0.3 deg) centered on the ARM SGP CF. The extensive time period and high-resolution of the inner grid of this dataset allows for comparison with the suite of instruments located at the ARM CF. In particular, Whole-Sky Imager (WSI) and the Active Remote Sensing of Clouds (ARSCL) cloud products can be compared to the cloud amounts and heights of the LBTM 0.3 deg grid box encompassing the CF site. The WSI provides cloud fraction and the ARSCL computes cloud fraction, base, and top heights using the algorithms by Clothiaux et al. (2001) with a combination of Belfort Laser Ceilometer (BLC), Millimeter Wave Cloud Radar (MMCR), and Micropulse Lidar (MPL) data. This paper summarizes the results of the LBTM analysis for 3 years of GOES-8 data over the SGP and examines the differences between surface and satellite-based estimates of cloud fraction.

Khaiyer, M. M.↗

Evaluation of Temperature and Material Combinations on Several Lubricants for Use in the Geostationary Operational Environmental Satellite (GOES) Mission Filter Wheel Bearings

A bearing test apparatus was used to investigate lubricant degradation rates and elastohydrodynamic transition temperatures for several perfluoropolyether (Krytox) formulations, a pentasilahydrocarbon, and a synthetic hydrocarbon (Pennzane 2001 A) in an MPB 1219 bearing, which is used in the geostationary operational environmental satellite (GOES) mission filter wheel assembly. Test conditions were the following: 1000-hr duration, 75 C, 20 lb axial load, vacuum level less than 1 x 10(exp -6) Torr, and a 600-rpm rotational speed. Baseline tests were performed using unformulated Krytox 143AB, the heritage lubricant. Krytox additive formulations showed small reductions in degradation rate. Krytox GPL-105, a higher viscosity version, yielded the least amount of degradation products. Both the silahydrocarbon and Pennzane 2001A showed no signs of lubricant degradation and had ample amounts of free oil at test conclusion.

Jansen, Mark J.↗

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

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

Kawamoto, K.↗