Geostationary Operational Environmental Satellite Observations Research Articles

Can We Intercalibrate Satellite Measurements by Means of Data Assimilation? An Attempt on LEO Satellites

AbstractLow Earth Orbit satellites offer extensive data of the radiation belt region, but utilizing these observations is challenging due to potential contamination and difficulty of intercalibration with spacecraft measurements at Highly Elliptic Orbit that can observe all equatorial pitch‐angles. This study introduces a new intercalibration method for satellite measurements of energetic electrons in the radiation belts using a Data assimilation (DA) approach. We demonstrate our technique by intercalibrating the electron flux measurements of the National Oceanic and Atmospheric Administration (NOAA) Polar‐orbiting Operational Environmental Satellites (POES) NOAA‐15,‐16,‐17,‐18,‐19, and MetOp‐02 against Van Allen Probes observations from October 2012 to September 2013. We use a reanalysis of the radiation belts obtained by assimilating Van Allen Probes and Geostationary Operational Environmental Satellites observations into 3‐D Versatile Electron Radiation Belt (VERB‐3D) code simulations via a standard Kalman filter. We compare the reanalysis to the POES data set and estimate the flux ratios at each time, location, and energy. From these ratios, we derive energy and L* dependent recalibration coefficients. To validate our results, we analyze on‐orbit conjunctions between POES and Van Allen Probes. The conjunction recalibration coefficients and the data‐assimilative estimated coefficients show strong agreement, indicating that the differences between POES and Van Allen Probes observations remain within a factor of two. Additionally, the use of DA allows for improved statistics, as the possible comparisons are increased 10‐fold. Data‐assimilative intercalibration of satellite observations is an efficient approach that enables intercalibration of large data sets using short periods of data.

A Statistical Analysis of the Auroral Streamer Current System

AbstractMagnetosphere‐ionosphere coupling is an important process that involves the transport of vast quantities of mass, energy, and momentum in the Earth's near‐space environment. This transport involves extended, global sheets of electrical current that flows along the magnetic field lines. Many studies have discussed the magnetosphere‐ionosphere coupling between the fast‐moving earthward flows and the north‐south oriented streamers in the ionosphere. However, only recently, the temporal evolution of the ionospheric current pattern, from the start to the end of the streamer, has been investigated through case studies, by combining the ionospheric current pattern with the magnetotail fast‐moving earthward flows. In this study, we show the statistical spatial and temporal evolution of the ionospheric current pattern associated with north‐south oriented streamers using simultaneous THEMIS (Time History of Events and Macroscale Interaction during Substorms) observations of fast‐moving earthward flows within the magnetotail, Geostationary Operational Environmental Satellite observations, auroral all‐sky images, and ionospheric equivalent current maps derived from ground magnetometer measurements. We show that the streamer related ionospheric field‐aligned currents (FACs) are statistically almost equivalent in magnitude for the 38 events that were analyzed. Results show that the streamer related ionospheric FACs are statistically approximately similar in magnitude for 38 events. The duration of these events ranges from 2 to 21 min with a median value of 9 min.

Statistical validation of ionospheric electron density profiles retrievals from GOES geosynchronous satellites

In this paper, we discuss a novel retrieval of ionospheric electron density profiles using the Radio Occultation (RO) technique applied to measurements captured by the Global Positioning System (GPS) receivers onboard two Geostationary Operational Environmental Satellites (GOES). The GOES satellites operate at ~35,800 km altitude and are primarily weather satellites that operationally contribute continuous remote-sensing data for real-time weather forecasting, as well as near-Earth environment monitoring and Sun observations. The GPS receivers onboard GOES-16 and GOES-17 satellites can track GPS signals propagated through the Earth’s atmosphere, and although the receivers are primarily designed for navigation and station-keeping maneuvers, these GPS measurements that traverse the Earth’s atmosphere can be used to retrieve the ionospheric electron density profiles. This process poses a range of technical challenges. GOES RO links are different from the traditional low Earth orbit (LEO) RO geometry since the receiver is located in an orbit that is higher in altitude than the GPS constellation of transmitters. Additionally, the GPS receivers onboard GOES satellites provide only single-frequency GPS L1 observations and have clocks much less stable than those typically used for RO measurements. The geographical distribution of the retrieved GEO-based RO profiles was found to be uniquely constrained and repeatable based on the relative geostationary fixed positions in the Earth-Centered Earth Fixed reference frame with respect to the GPS constellation orbiting at lower altitude, and significantly different from the coverage patterns of LEO-based RO missions. We demonstrate the successful application of the proposed RO profiling technique with a statistically significant set of GPS observations from GOES-16 and GOES-17 satellites over several years of data collection. This enabled us to retrieve more than 10,000 ionospheric electron density profiles with a maximum altitude of up to 1000–2000 km, much higher than any existing LEO-based RO mission. We demonstrate good performance of GEO-based RO measurements for properly specifying the vertical distribution of ionospheric plasma density by comparing the profiles dataset from the GOES RO experiment with independent reference observations – ground-based ionosondes and LEO-based RO missions, as well as model simulation results provided by the empirical International Reference Ionosphere model. Over multiple years of observations, statistical analysis of discrepancies between the ionospheric F2 layer peak parameters (peak density and height) derived from geosynchronous GOES observations and reference measurements was conducted. This analysis reveals a very good agreement between GOES RO electron density profiles and independent types of measurements in both the F2 peak and the profile shape.

Comparison of Van Allen Probes Energetic Electron Data With Corresponding GOES‐15 Measurements: 2012–2018

AbstractElectron fluxes (especially at energies E > 0.8 and 2 MeV) have been measured for many years by sensors on board the Geostationary Operational Environmental Satellite (GOES). These long‐term data (nominally at L ~ 6.6) have become a mainstay for monitoring the Earth's radiation environment. We have carried out a study directly comparing the comprehensive radiation belt particle measurements from the National Aeronautics and Space Administration dual‐spacecraft Van Allen Probes (Radiation Belt Storm Probes) sensor systems with selected GOES operational data. The Van Allen Probes have measured the properties of radiation belt electrons virtually continuously from September 2012 to 2018. We make statistical comparisons of Van Allen Probes electron data near L = 6 with concurrent daily averages of equivalent GOES‐15 flux values. We also compare Van Allen Probes data at various other L values and at a much broader range of particle energies with the more limited baseline GOES‐15 values. These comparisons inform us about the relative calibrations between the scientific and operational systems and also allow us to assess how well GOES data correlate with radiation belt behavior well away from the geostationary orbit location. We find that GOES daily average flux values can be a factor of 100 (or more) below the corresponding Van Allen Probes daily averaged fluxes at L = 6.0. This is due to the fact that GOES at stationary orbit often has excursions over large ranges of L space during a given day and strong radial gradients exist in this region of the magnetosphere. These results indicate that it is crucial to augment geosynchronous GOES observations with observations in the core of the outer belt (L ≲5.0).

Statistical Properties of Soft X-Ray Emission of Solar Flares

Abstract We present a statistical analysis of properties of Soft X-Ray (SXR) emission, plasma temperature (T), and emission measure (EM), derived from Geostationary Operational Environmental Satellite observations of flares in 2002–2017. The temperature and EMs are obtained using the Temperature and EM-based Background Subtraction algorithm, which delivers reliable results together with uncertainties even for weak B-class flare events. More than 96% of flares demonstrate a sequential appearance of T, SXR, and EM maxima, in agreement with the expected behavior of the chromospheric evaporation process. The relative number of such flares increases with increasing the SXR flux maximum. The SXR maximum is closer in time to the T maximum for B-class flares than for ≥C-class flares, while it is very close to the EM maximum for M- and X-class flares. We define flares as “T-controlled” if the time interval between the SXR and T maxima is at least two times shorter than the interval between the EM and SXR maxima, and as “EM-controlled” if the time interval between the EM and SXR maxima is at least two times shorter than the interval between the SXR and T maxima. For any considered flare class range, the T-controlled events compared to EM-controlled events have: (a) higher EM but lower T; (b) longer durations and shorter relative growth times; and (c) longer FWHM and characteristic decay times. Interpretation of these statistical results based on analysis of a single loop dynamics suggests that for flares of the same class range, the T-controlled events can be developed in longer loops than the EM-controlled events.

Global expansion of the dayside magnetopause for long‐duration radial IMF events: Statistical study on GOES observations

AbstractFor decades, unusual locations of the magnetopause under radial interplanetary magnetic field (IMF) have been reported in many studies using in situ satellite observations. These studies have shown that the magnetopause is expanded either over all magnetic local times (MLTs) on the dayside (global expansion) or just near the noon (bullet‐like expansion) during radial IMF conditions. With limited observations near the magnetopause, the type of the magnetopause expansion is still undetermined. In this study, 19 years of dayside geosynchronous magnetic field data obtained from Geostationary Operational Environmental Satellites (GOES) are statistically processed to infer the shape of the dayside magnetopause under radial IMF conditions. The MLT distributions of geosynchronous magnetic fields for radial IMF are compared with those for northward IMF with the correction of solar wind dynamic pressure distributions between two different IMF conditions. After removal of the solar wind dynamic pressure effect, we have found that the geosynchronous magnetic field for radial IMF is smaller than that for northward IMF over almost all MLTs on the dayside regardless of magnetic latitudes and seasons. The difference between geosynchronous magnetic fields for the northward and radial IMFs supports the suggestion that the dayside magnetopause is globally expanded during the radial IMF conditions.

Intercalibration of GOES Imager visible channels over the Sonoran Desert

AbstractThe Geostationary Operational Environmental Satellites (GOES) have been observing the Western Hemisphere since the late 1970s, providing valuable information for weather forecast and climate change studies. Due to the lack of an onboard calibration device for the visible channel, accurate reflectance of the visible channel data depends on vicarious calibration methods to provide postlaunch calibration coefficients to compensate for the degraded responsivity. In this study, the Sonoran Desert, which can be viewed by both GOES‐East and GOES‐West satellites, is used to intercalibrate the visible channels on board the three‐axis stabilized GOES satellite Imagers traceable to the Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6 (C6) calibration standard. It was found that when the anomalous reflectance in 2004 and 2005 are excluded, the Sonoran Desert is radiometrically, spatially, and spectrally stable at the GOES viewing geometries and thus can be considered as a pseudo‐invariant calibration site to develop long‐term GOES Imager visible data set. To characterize the desert target reflectance with the MODIS data, GOES observations over 1 year period are used to convert the MODIS reflectance to the GOES viewing and solar illumination geometries. The spectral band adjustment factor for each GOES Imager visible channel is generated with a set of clear‐sky Hyperion measurements. A trending algorithm, which consists of a polynomial function for the description of instrument degradation performance and two sine terms for the impacts of the seasonal variations of the solar zenith angle and atmospheric components, is applied to fit the time series of prelaunch calibrated reflectance. The combined calibration uncertainty of the desert calibration method is less than 4% at the Aqua MODIS C6 calibration standard. The difference of the postlaunch calibration coefficients between the desert calibration and the current GOES visible operational calibration methods is mainly within 5%.

On the interaction of Tropical Cyclone Flossie and emissions from Hawaii's Kilauea volcano

On 29 July 2013, Tropical Storm Flossie passed the Hawaiian Islands. This is the first interaction between an active, vigorously degassing volcano and a tropical cyclone captured by a vog (volcanic smog) dispersion model run over the Hawaiian Islands since operational simulations began in 2010, providing a unique opportunity to analyze the influence of robust volcanic emissions entrained into a tropical cyclone. Results from the vog dispersion model are compared with Geostationary Operational Environmental Satellite observations, lightning data from Vaisala's Global Lightning Dataset (GLD360), and the National Weather Service Weather Surveillance Radar, 1988 Dual-Polarmetric Doppler radar to investigate the effect of volcanic emissions on the storm. Observations and model results suggest that aerosol loading resulted in deep convection and glaciation which in turn enhanced charge separation and promoted active lightning.

ENERGETIC ELECTRON PROPAGATION IN THE DECAY PHASE OF NON-THERMAL FLARE EMISSION

On the basis of the trap-plus-precipitation model, the peculiarities of non-thermal emission in the decay phase of solar flares have been considered. The calculation formulas for the escape rate of trapped electrons into the loss cone in terms of time profiles of hard X-ray (HXR) and microwave (MW) emission have been obtained. It has been found that the evolution of the spectral indices of non-thermal emission depend on the regimes of the pitch angle diffusion of trapped particles into the loss cone. The properties of non-thermal electrons related to the HXR and MW emission of the solar flare on 2004 November 3 are studied with Nobeyama Radioheliograph, Nobeyama Radio Polarimeters, RHESSI, and Geostationary Operational Environmental Satellite observations. The spectral indices of non-thermal electrons related to MW and HXR emission remained constant or decreased, while the MW escape rate as distinguished from that of the HXRs increased. This may be associated with different diffusion regimes of trapped electrons into the loss cone. New arguments in favor of an important role of the superstrong diffusion for high-energy electrons in flare coronal loops have been obtained.

Toward an Operational Land Surface Temperature Algorithm for GOES

AbstractFor most land surface temperature (LST) regression algorithms, a set of optimized coefficients is determined by manual separation of the different subdivisions of atmospheric and surface conditions. In this study, a machine-learning technique, the regression tree (RT) technique, is introduced with the aim of automatically finding these subranges and the thresholds for the stratification of regression coefficients. The use of RT techniques in LST retrieval has the potential to contribute to the determination of optimal regression relationships under different conditions. Because of the lack of split-window channels for the Geostationary Operational Environmental Satellite (GOES) M–Q series (GOES-12–GOES-15, plus GOES-Q), a dual-window LST algorithm was developed by combining the infrared 11-μm channel with the shortwave-infrared (SWIR) 3.9-μm channel, which presents lower atmospheric absorption than does the infrared split-window channels (11 and 12 μm). The RT technique was introduced to derive the regression models under different conditions. The algorithms were used to derive the LST product from GOES observations and were evaluated against the 2004 Surface Radiation budget network. The results indicate that the RT technique outperforms the traditional regression method.

Improved Coastal Precipitation Forecasts with Direct Assimilation of GOES-11/12 Imager Radiances

Abstract The Geostationary Operational Environmental Satellite (GOES) imager provides observations that are of high spatial and temporal resolution and can be applied for effectively monitoring and nowcasting severe weather events. In this study, improved quantitative precipitation forecasts (QPFs) for three coastal storms over the northern Gulf of Mexico and the East Coast is demonstrated by assimilating GOES-11 and GOES-12 imager radiances into the Weather Research and Forecasting (WRF) model. Both the National Centers for Environmental Prediction (NCEP) Gridpoint Statistical Interpolation (GSI) analysis system and the Community Radiative Transfer Model (CRTM) are utilized to ingest GOES IR clear-sky data. Assimilation of GOES imager radiances during a 6–12-h time window prior to convective initiation and/or development could significantly improve the precipitation forecasts near the coast of the northern Gulf of Mexico. The 3-h accumulative precipitation threat scores are increased by about 20% after 6 h of model forecasts and more than 50% after 18–24 h of model forecasts. A detailed diagnosis of analysis fields and model forecast fields is carried out for one of the three convective precipitation events included in this study. It is shown that the assimilation of GOES data in regions of no or little clouds improved the model description of an upstream midlatitude trough and a subtropical high located in the south of the convection. The GOES observations located in the western part of land region covered by GOES within the latitude zone of 18°–37°N near 100°W contributed to a better forecast of the position of the eastward-propagating trough, while GOES observations over the Gulf of Mexico increased the amount of water vapor advection from the south into the convective region by the wind associated with the subtropical high. In the past, GOES imager radiances were not directly used in the GSI system. This study highlights the importance of satellite imagery information observed in the preconvective environment for improved cloud and precipitation forecasts. The developed data assimilation technique will prepare the NWP user community for accelerated use of advanced satellite data from the GOES-R series.

Consistency assessment of Atmospheric Infrared Sounder and Infrared Atmospheric Sounding Interferometer radiances: Double differences versus simultaneous nadir overpasses

[1] Quantifying the radiometric difference and creating a calibration link between Atmospheric Infrared Sounder (AIRS) on Aqua and Infrared Atmospheric Sounding Interferometer (IASI) on MetOp are crucial for creating fundamental climate data records and intercalibrating other narrowband or broadband satellite instruments. This study employs two different methods to assess the AIRS and IASI radiance consistency within the four Geostationary Operational Environmental Satellite (GOES) imager infrared channels (with central wavelengths at 6.7, 10.7, 12.0, and 13.3 μm) through a period of 2 years and 9 months. The first method employs the differences of AIRS and IASI relative to the GOES observations sampled in the tropics to indirectly track the AIRS and IASI radiance differences. The second approach directly compares AIRS and IASI in the polar regions through the simultaneous nadir overpass observations. Both methods reveal that AIRS and IASI radiances are in good agreement with each other both in the tropics and in the polar regions within GOES imager channels used in this study, while AIRS is found to be slightly warmer than IASI by less than 0.1 K.

A 10 year climatology of cloud fraction and vertical distribution derived from both surface and GOES observations over the DOE ARM SPG site

Analysis of one decade of radar‐lidar and Geostationary Operational Environmental Satellite (GOES) observations at the Department of Energy (DOE) Atmospheric Radiation Measurement Program (ARM) Southern Great Plains (SGP) site reveals that there is excellent agreement in the long‐term mean cloud fractions (CFs) derived from the surface and GOES data, and the CF is independent of temporal resolution and spatial scales for grid boxes of size 0.5° to 2.5°. When computed over a a 0.5 h (4 h) period, cloud frequency of occurrence (FREQ) and amount when present (AWP) derived from the point surface data agree very well with the same quantities determined from GOES for a 0.5° (2.5°) region centered on the DOE ARM SGP site. The values of FREQ (AWP) derived from the radar‐lidar observations at a given altitude increase (decrease) as the averaging period increases from 5 min to 6 h. Similarly, CF at a given altitude increases as the vertical resolution increases from 90 to 1000 m. The profiles of CF have distinct bimodal vertical distributions, with a lower peak between 1 and 2 km and a higher one between 8 and 11 km. The 10 year mean total CF, 46.9%, varies seasonally from a summer minimum of 39.8% to a maximum of 54.6% during the winter. The annual mean CF is 1%–2% less than that from previous studies, ∼48%–49%, because fewer clouds occurred during 2005 and 2006, especially during winter. The differences in single‐ and multilayered CFs between this study and an earlier analysis can be explained by the different temporal resolutions used in the two studies, where single‐layered CFs decrease but multilayered CFs increase from a 5 min resolution to a 1 h resolution. The vertical distribution of nighttime GOES high cloud tops agrees well with surface observations, but during the daytime, fewer high clouds are retrieved by the GOES analysis than seen from the surface observations. The FREQs for both daytime and nighttime GOES low cloud tops are significantly higher than surface observations, but the CFs are in good agreement.

A Calibrated, High‐Resolution GOES Satellite Solar Insolation Product for a Climatology of Florida Evapotranspiration1

Paech, Simon J., John R. Mecikalski, David M. Sumner, Chandra S. Pathak, Quinlong Wu, Shafiqul Islam, and Taiye Sangoyomi, 2009. A Calibrated, High‐Resolution GOES Satellite Solar Insolation Product for a Climatology of Florida Evapotranspiration. Journal of the American Water Resources Association (JAWRA) 45(6):1328‐1342.Abstract: Estimates of incoming solar radiation (insolation) from Geostationary Operational Environmental Satellite observations have been produced for the state of Florida over a 10‐year period (1995‐2004). These insolation estimates were developed into well‐calibrated half‐hourly and daily integrated solar insolation fields over the state at 2 km resolution, in addition to a 2‐week running minimum surface albedo product. Model results of the daily integrated insolation were compared with ground‐based pyranometers, and as a result, the entire dataset was calibrated. This calibration was accomplished through a three‐step process: (1) comparison with ground‐based pyranometer measurements on clear (noncloudy) reference days, (2) correcting for a bias related to cloudiness, and (3) deriving a monthly bias correction factor. Precalibration results indicated good model performance, with a station‐averaged model error of 2.2 MJ m−2/day (13%). Calibration reduced errors to 1.7 MJ m−2/day (10%), and also removed temporal‐related, seasonal‐related, and satellite sensor‐related biases. The calibrated insolation dataset will subsequently be used by state of Florida Water Management Districts to produce statewide, 2‐km resolution maps of estimated daily reference and potential evapotranspiration for water management‐related activities.

Estimates of surface ultraviolet radiation over north America using Geostationary Operational Environmental Satellites observations

Information on ultraviolet (UV) radiative fluxes is needed for public safety, understanding biodiversity, and for chemical transport modeling. Space‐based observations can provide homogeneous and systematic estimates of the UV flux over large regions. In the past, UV flux estimates have been made from polar orbiting satellites; such estimates lack information on diurnal variability that can result in significant errors in UV dose (diurnally integrated UV flux). An algorithm has been developed to estimate diurnally varying spectral UV flux at the surface based on information from geostationary satellites (cloud amount, surface albedo and aerosols) and from polar orbiting satellites (ozone). Algorithm evaluation is done by comparison with ground‐based observations made between January 1998 and December 2000 over eighteen stations of the United States Department of Agriculture (USDA)'s UV monitoring network. A good agreement between ground‐based observations and satellite estimates is found with a mean bias (satellite − ground) of +3.5% for all‐sky (cloudy + clear) cases. A negative mean bias of the same magnitude is found for clear‐sky cases. Root mean square (RMS) differences are 25% and 14% for all‐sky and clear‐sky cases, respectively. Using simulations, it is shown that when only one observation near noontime is used to estimate UV dose, errors in the range of −61% to 48% can result, depending on cloud conditions. The RMS difference is 9% and it increases to 13% when off‐noon hour (±2 hrs) observations are used to estimate the UV flux over Queenstown, MD.

Assimilating GOES Brightness Temperatures. Part I: Upper-Tropospheric Moisture

Abstract Imager channel 3 (at 6.7 μm) on the Geostationary Operational Environmental Satellite (GOES) is particularly sensitive to water vapor in the atmosphere. Channel-3 data from both clear and cloudy regions are used in a new assimilation scheme to improve the initial upper-tropospheric moisture fields for modeling and numerical weather prediction purposes. In this assimilation, the navigated and calibrated radiance (brightness temperature) observations from GOES are used in combination with a forward radiative transmittance model and a numerical optimization procedure to produce modifications to the upper-tropospheric moisture field. All modifications are made proportional to the contribution weighting function, which is associated with the forward radiative model. Cloudy regions are given special consideration. When processed by a forward radiative transfer model, the assimilated moisture fields are shown to correlate better with GOES observations both initially and in 24- and 48-h forecasts. Additi...

Calibration of theEighth Geostationary Observational Environmental Satellite(GOES-8) Imager Visible Sensor

Abstract The GOES-8/Imager has provided scientifically valuable imagery since its launch in April of 1994. However, without an onboard calibration source most research applications involving its data have been limited to qualitative analysis of the imagery. Presented herein is a review of previous quantitative work, including the prelaunch calibration information, and results of a new calibration effort that compares GOES-8/Imager raw counts of clear ocean scenes to theoretical satellite-detected radiance values from a radiative transfer model. Monthly averages of the calibration coefficient are presented at 6-month intervals from August 1995 through August 1999. Although the technique differs from previous calibration efforts, which compare Geostationary Operational Environmental Satellite observations to some reference instrument, the new calibration results agree well with previous results. The calibration suggests a one-time decrease of 7.6% shortly after launch, and an ongoing annual degradation of 5...

Estimation of Sea Surface Temperatures UsingGOES-8/9Radiance Measurements

Abstract Sea surface temperatures (SSTs) are derived using measurements from the new generation of imaging instruments on the Geostationary Operational Environmental Satellites (GOES). The National Environmental Satellite, Data and Information Service has been producing hourly GOES SST estimates since December 1998. This paper presents the algorithm for cloud detection and atmospheric moisture correction and shows some initial results. Several advantages of GOES SST are evident in comparison with SST from polar orbiting satellites. Frequent sampling by GOES imagers results in a more complete map of SST as clouds move away. Changes in scene temperature over a short period of time help to detect the presence of clouds. The abundance of GOES observations enables stringent screening for cloud-free observations while maintaining good spatial coverage of clear-sky inferences of SST. Diurnal variations of SST over large areas are observed for the first time and their implications for numerical weather prediction...

Modeling Topographic Solar Radiation Using GOES Data

Abstract In this paper the authors present an algorithm that combines solar radiation fields derived from Geostationary Operational Environmental Satellite (GOES) observations with digital elevation data to produce topographically varying insolation fields at fine grid spacing. Cloud-modulated irradiances are obtained using hourly 8-km resolution GOES observations. These irradiances are then spatially integrated to the grid spacing of the digital elevation data. The integration accounts for uncertainties in satellite navigation, the limited sensor resolution relative to the hemispheric field of view of a terrain element, and the mismatch between the instantaneous fluxes estimated by GOES observations and the time-integrated quantities typically used in distributed modeling, such as hourly fluxes. The integrated fields are partitioned into direct and diffuse components and then adjusted for the effects of elevation. Lastly, other topographic effects, such as slope orientation, shadowing, sky obstruction, a...