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1,709 results for “Reflectivity”
TOMS Meteor-3 UV-Reflectivity Daily L3 Global 1 deg x 1.25 deg Lat/Lon Grid V008 (TOMSM3L3dref) at GES DISC
This Meteor-3 Total Ozone Mapping Spectrometer (TOMS) version 8 daily global gridded data product contains Lambertian effective surface reflectivity values (Rayleigh corrected). The data are mapped to a global grid of size 180 x 288 with a lat-long resolution of 1.00 x 1.25 degrees. These data are stored in an ASCII format.The TOMS data were produced by the Laboratory for Atmospheres at NASA Goddard Space Flight Center (Code 614).
SE-590 Landscape Reflectances (OTTER)
Bidirectional spectral reflectance factors of landscape elements (litter, scrubs and grasses, leaves) measured by the Spectron SE590 spectroradiometer.
BOREAS Level-2 MAS Surface Reflectance and Temperature Images in BSQ Format
The BOREAS Staff Science Aircraft Data Acquisition Program focused on providing the research teams with the remotely sensed aircraft data products they needed to compare and spatially extend point results. The MAS images, along with other remotely sensed data, were collected to provide spatially extensive information over the primary study areas. This information includes biophysical parameter maps such as surface reflectance and temperature. Collection of the MAS images occurred over the study areas during the 1994 field campaigns. The level-2 MAS data cover the dates of 21-Jul-1994, 24-Jul-1994, 04-Aug-1994 and 08-Aug-1994. The data are not geographically/geometrically corrected; however, files of relative X and Y coordinates for each image pixel were derived by using the C130 navigation data in a MAS scan model. The data are provided in binary image format files.
SAFARI 2000 Pre- and Post-fire Reflectance near Kaoma, Zambia, Dry Season 2000
The main goal of this study was to analyze the possibility of estimating combustion completeness based on fire-induced spectral reflectance changes of surface features by the development of relationships between combustion completeness and pre-fire to post-fire spectral reflectance changes, in the green, red, and near-infrared spectral domains (equivalent to Landsat ETM+ channels 2, 3, and 4). Experimental burns were carried out in the Western Province of Zambia in dambos (hydromorphic grasslands) and miombo woodlands during the SAFARI 2000 Third Intensive Field Campaign in August and September of 2000.This data set contains three sets of measurements: reflectance measurements from a FieldSpec UV/VNIR Spectroradiometer along burned and unburned woodland transects, in pre- and post-fire woodland and dambo plots, and for pure spectra of soil, vegetation, and charcoal; reflectance and transmittance measurements of both upper and lower leaf faces for three tree species (Julbernardia globiflora, Isoberlinia angolensis, and Brachystegia spiciformis) using an External Integrating Sphere connected to the FieldSpec Spectroradiometer; and calculations that integrate pre- and post-fire biomass measurements with pre- and post-fire reflectance in ETM+ channel 2, 3, and 4 wavelengths to estimate combustion completeness. The data files are stored as Excel spreadsheets (.csv format). Additional information about the data format, study area, instrumentation, and results is found in the companion file: ftp://daac.ornl.gov/data/safari2k/remote_sensing/pre_post_fire_refl/comp/pre_post_fire_refl_readme.pdf.
TOMS Nimbus-7 UV Reflectivity Monthly L3 Global 1 deg x 1.25 deg Lat/Lon Grid V008 (TOMSN7L3mref) at GES DISC
This Nimbus-7 Total Ozone Mapping Spectrometer (TOMS) version 8 monthly averaged global gridded data product contains Lambertian effective surface reflectivity values (Rayleigh corrected). The data are mapped to a global grid of size 180 x 288 with a lat-long resolution of 1.00 x 1.25 degrees. These data are stored in an ASCII format.The TOMS data were produced by the Laboratory for Atmospheres at NASA Goddard Space Flight Center (Code 614).
CAR Kuwait Oil Fire Spectral Reflectance L1 V1 (CAR_KUWAITOILFIRE_L1C) at GES DISC
CAR Kuwait Oil Fire mission measured bidirectional reflectance function of smoke from Kuwait oil fires during the Kuwait Oil Fire Smoke Experiment. Measurements were also taken over the Saudi Arabian desert with overlying desert dust, and Persian Gulf waters with some overlying aerosols.
SHIFT: Reflectance Measurements for Dried and Ground Leaf Materials
This dataset provides full-spectrum (350-2500 nm) reflectance measurements of dried ground leaf samples from meadow, shrub, and tree sites. Samples were collected during the period of February 23, 2022 to September 27th, 2022 for the 2022 NASA Surface Biology Geology (SBG) High Frequency Time series (SHIFT) campaign in Santa Barbara County, California, USA. The primary goal of the SHIFT campaign was to collect a repeated dense time series of airborne Visible to ShortWave Infrared (VSWIR) airborne imaging spectroscopy data with coincident field measurements in both inland terrestrial and coastal aquatic areas. Reflectance measurements were collected using a ASD FieldSpec 3 spectrometer following Serbin et al. (2014) and Wang et al. (2020). After sample collection, each leaf sample was divided into two portions: one portion with ~10 g fresh weight was oven dried and another portion with ~5 g fresh weight was flash frozen. Both samples were ground and homogenized (20-mesh, 833 micrometers). The oven dried samples were then re-dried in oven at 70 degrees C for 24 h and the flash frozen samples were dried using a Virtis Model 24DX48 specimen freeze dryer before the reflectance measurement. Data are in a comma-separated values (.csv) format.
Daily FluxSat GPP of biomass over Land, Based on MODIS Terra and Aqua adjusted reflectance Collection 6.1, on a Global 0.5 by 0.625 Degree Grid, Level 3 Version 2.2
This dataset provides global gridded daily estimates of gross primary production (GPP) and uncertainties at 0.5 deg latitude by 0.625 deg longitude resolution for the period March 2000 to present. The GPP is derived from MODerate-resolution Imaging Spectroradiometer (MODIS) instruments on NASA Terra and Aqua satellites. GPP is derived using the MODIS Nadir Bidirectional Reflectance Distribution Function (BRDF)-Adjusted Reflectances (NBAR) product, which is used as input to neural network models to globally upscale GPP estimated from selected collocated FLUXNET 2015 and OneFlux eddy covariance tower sites used for model training. Version 2.2 is the current version of the dataset.If you have any questions, please read the README document first and post your question to the NASA Earthdata Forum (forum.earthdata.nasa.gov) or email the GES DISC Help Desk (gsfc-dl-help-disc@mail.nasa.gov).
AIRS-AMSU variables-CloudSat cloud mask, radar reflectivities, and cloud classification matchups V3.2 (AIRSM_CPR_MAT) at GES DISC
This is AIRS-CloudSat collocated subset, in NetCDF 4 format. These data contain collocated: AIRS/AMSU retrievals at AMSU footprints, CloudSat radar reflectivities, and MODIS cloud mask. These data are created within the frames of the MEaSUREs project.The basic task is to bring together retrievals of water vapor and cloud properties from multiple "A-train" instruments (AIRS, AMSR-E, MODIS, AMSU, MLS, CloudSat), classify each "scene" (instrument look) using the cloud information,and develop a merged, multi-sensor climatology of atmospheric water vapor as afunction of altitude, stratified by the cloud classes. This is a large scienceanalysis project that will require the use of SciFlo technologies to discover and organize all of the datasets, move and cache datasets as required, findspace/time "matchups" between pairs of instruments, and process years ofsatellite data to produce the climate data records.The short name for this collection is AIRSM_CPR_MATParameters contained in the data files include the following:Variable Name|Description|Units CH4_total_column|Retrieved total column CH4| (molecules/cm2) CloudFraction|CloudSat/CALIPSO Cloud Fraction| (None) CloudLayers| Number of hydrometeor layers| (count) clrolr|Clear-sky Outgoing Longwave Radiation|(Watts/m**2) CO_total_column|Retrieved total column CO| (molecules/cm2) CPR_Cloud_mask| CPR Cloud Mask |(None) Data_quality| Data Quality |(None) H2OMMRSat|Water vapor saturation mass mixing ratio|(gm/kg) H2OMMRStd|Water Vapor Mass Mixing Ratio |(gm/kg dry air) MODIS_Cloud_Fraction| MODIS 250m Cloud Fraction| (None) MODIS_scene_var |MODIS scene variability| (None) nSurfStd|1-based index of the first valid level|(None) O3VMRStd|Ozone Volume Mixing Ratio|(vmr) olr|All-sky Outgoing Longwave Radiation|(Watts/m**2) Radar_Reflectivity| Radar Reflectivity Factor| (dBZe) Sigma-Zero| Sigma-Zero| (dB*100) TAirMWOnlyStd|Atmospheric Temperature retrieved using only MW|(K) TCldTopStd|Cloud top temperature|(K) totH2OStd|Total precipitable water vapor| (kg/m**2) totO3Std|Total ozone burden| (Dobson) TSurfAir|Atmospheric Temperature at Surface|(K) TSurfStd|Surface skin temperature|(K)End of parameter information
BOREAS TE-09 in situ Understory Spectral Reflectance within the NSA
Spectral reflectance of the forest understory at the ground level, in three boreal forest sites of Northern Manitoba (56 degrees N latitude and 98 degrees W longitude), were obtained and analyzed. The objective of the study was to estimate light levels inside the forest canopy and to link these estimates with airborne images taken above the canopy, in order to tie the photosynthetic experiments and models with the remotely sensed measurements. The Boreal Ecosystem-Atmospheric Study (BOREAS) Terrestrial Ecosystem (TE)-09 project contained several sub-projects designed to work together to meet this goal: a high-resolution canopy modeling component, extensive measurements of canopy architecture and structure, photometric measurements inside the canopy, and spectral measurements of both the canopy and the understory.
CLPX-Satellite: EO-1 Hyperion Surface Reflectance, Snow-Covered Area, and Grain Size, Version 1
This data set consists of apparent surface reflectance, subpixel snow-covered area, and grain size collected from the Hyperion hyperspectral imager. The Hyperion imager has a spectral range of 400-2500 nm, a spectral resolution of 10 nm, spatial resolution of 30 m, and a swath width of 7.8 km. Sampling is scene based (256 samples, 512 lines).
ASTER L2 Surface Reflectance VNIR and Crosstalk Corrected SWIR V004
The Terra Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Surface Reflectance VNIR and Crosstalk Corrected SWIR (AST_07XT) dataset contains measures of the fraction of incoming solar radiation reflected from the Earth’s surface to the ASTER instrument corrected for atmospheric effects and viewing geometry for both the Visible and Near Infrared (VNIR) and Shortwave Infrared (SWIR) sensors. Both the VNIR and SWIR data are atmospherically corrected and are generated using the bands of the corresponding ASTER [L1B](https://doi.org/10.5067/ASTER/AST_L1B.004) image. The AST_07XT product has a spatial resolution of 15 meters (m) for the VNIR bands and 30 m for the SWIR bands.Known Issues* Level 2 products that are on the international date line/anti-meridian have incorrect bounding coordinates for the UTM zone defined in the file metadata.* SWIR data acquired after April 2008 may exhibit anomalous saturation and striping. Users should consult the ASTER SWIR User Advisory for additional details.Improvements/Changes from Previous Versions* SWIR Crosstalk Correction: Applies a correction to reduce stray light effects in the SWIR bands, enhancing data quality by minimizing artifacts. Enhanced Atmospheric Correction: Version 4 uses Modern-Era Retrospective analysis for Research and Applications Version 2 (MERRA-2) data as the primary source for atmospheric parameters (ozone, water vapor, pressure, and temperature), improving the precision of emissivity calculations. Fallback Mechanisms: When MERRA-2 data are unavailable, the product employs Global Data Assimilation System (GDAS) data as a backup, with climatology data serving as a final fallback to ensure continuous processing. Radiometric Calibration Update: Version 4 applies Radiometric Calibration Coefficient Version 5 (RCC V5) to improve the radiometric accuracy of the raw DNs, based on research by [Tsuchida and others (2020)](https://doi.org/10.3390/rs12030427), published in Remote Sensing.
HLS Landsat Operational Land Imager Surface Reflectance and TOA Brightness Daily Global 30m v1.5
The HLSL30 V1.5 data product was decommissioned on January 4, 2022. Users are encouraged to use the improved [HLSL30 V2](https://doi.org/10.5067/HLS/HLSL30.002) data product.The Harmonized Landsat Sentinel-2 (HLS) project provides consistent surface reflectance (SR) and top of atmosphere (TOA) brightness data from the Operational Land Imager (OLI) aboard the joint NASA/USGS Landsat 8 satellite and the Multi-Spectral Instrument (MSI) aboard Europe’s Copernicus Sentinel-2A and Sentinel-2B satellites. The combined measurement enables global observations of the land every 2–3 days at 30-meter (m) spatial resolution. The HLS project uses a set of algorithms to obtain seamless products from OLI and MSI that include atmospheric correction, cloud and cloud-shadow masking, spatial co-registration and common gridding, illumination and view angle normalization, and spectral bandpass adjustment. The HLSL30 product provides 30-m Nadir Bidirectional Reflectance Distribution Function (BRDF)-Adjusted Reflectance (NBAR) and is derived from Landsat 8 OLI data products. The [HLSS30](https://doi.org/10.5067/HLS/HLSS30.015) and HLSL30 products are gridded to the same resolution and Military Grid Reference System ([MGRS](https://hls.gsfc.nasa.gov/products-description/tiling-system/)) tiling system and thus are “stackable” for time series analysis.The HLSL30 product is provided in Cloud Optimized GeoTIFF (COG) format, and each band is distributed as a separate file. There are 10 bands included in the HLSL30 product along with one quality assessment (QA) band and four angle bands. For a more detailed description of the individual bands provided in the HLSL30 product, please see the User Guide.Provisional HLS V1.5 data have not been validated for their science quality and should not be used in science research or applications.Known Issues* HLSL30.015 products are based on input Landsat 8 L1TP (precision terrain corrected) products, which require identification of ground control targets for precision geometric correction. Images where ground control is not available (e.g., very cloudy images) cannot be processed to L1TP and are not included in the HLSL30 dataset.* Interruptions in data service occurred during a restaging of backlogged data between June 1 and June 15, 2021 for both HLSS30 and HLSL30 version 1.5 data products. During this time period increased errors in the processing workflow resulted in a significant number of data ingestion failures and thus, significant gaps in data availability. Given the pending release of the version 2.0, science quality HLS products, these missing data will not be filled for version 1.5. Users of the provisional version 1.5 products should be aware of the significant data gap in this two week window. The version 2.0 products will incorporate these data back into the archive. If you have any feedback or questions on the data please contact [Customer Services](https://www.earthdata.nasa.gov/centers/lp-daac/contact) or join our HLS conversion on the [Earthdata Forum](https://forum.earthdata.nasa.gov/viewtopic.php?f=7&t=618&hilit=hls&sid=95750d868b6448e0f4360a1473def234).
Tundra Plant Reflectance, CO2 Exchange, PAM Fluorometry, and Pigments, AK, 2001-2002
This dataset provides measurements at tundra plots collected near Utqiagvik and Atqasuk, AK, including visible-near infrared spectral reflectance, chamber gas exchange measurements of CO2, pulse amplitude modulated (PAM) fluorometry, chlorophyll pigment contents, along with surface temperature, permafrost active layer depth, and soil temperature at 5 cm, through the growing seasons of 2001 and 2002. At all plots, spectral reflectance was measured using a portable spectrometer configured with a straight fiber optic foreoptic, surface temperatures were measured using a handheld Everest Infrared Thermometer, and thaw depth (or active layer depth) was measured using a metal rod graduated in centimeter intervals. At small plots (~15 cm) at Utqiagvik (referred to as Patch plots) chambers were constructed that enclosed an individual patch to determine photosynthetic rate and estimate respiration rate (made by covering the chamber in a dark cloth). Efficiency using PAM fluorometer, ambient yield estimations, and rapid light curve measurements were taken. Chlorophyll concentration was measured with a portable spectrometer configured as a spectrophotometer. At larger plots (approximately 1 m2) which were part of the International Tundra EXperiment (ITEX plots) at Utqiagvik (referred to as Barrow) and Atqasuk, a sub-sample of five control and five warmed plots at each site were fitted with 0.45 m diameter polyvinyl chloride collars for chamber flux measurements. To determine the total fraction of absorbed photosynthetically active radiation (fAPAR), a series of photosynthetically active radiation (PAR) measurements were made using a custom-made light bar consisting of a linear array of GaAsP sensors mounted within an aluminum U-bar under a white plastic diffuser. In addition, a visual estimate was made of the fraction of standing dead vegetation based on percent cover. The data are provided in comma-separated values (*.csv) format. In addition, photographs of plots and instruments are provided.
G-LiHT Hyperspectral Reflectance V001
Goddard’s LiDAR, Hyperspectral, and Thermal Imager ([G-LiHT](https://gliht.gsfc.nasa.gov/)) mission is a portable, airborne imaging system that aims to simultaneously map the composition, structure, and function of terrestrial ecosystems. G-LiHT primarily focuses on a broad diversity of forest communities and ecoregions in North America, mapping aerial swaths over the Conterminous United States (CONUS), Alaska, Puerto Rico, and Mexico.The purpose of G-LiHT’s Hyperspectral Reflectance data product (GLREFL) is to provide high-resolution reflectance data, ranging in wavelength from 418 to 920 nanometers across 114 spectral ranges. Reflectance data is computed as the ratio between observed upwelling radiance and downwelling hemispheric irradiance and corrected for differences in cross-track illumination and Bidirectional Reflectance Distribution Function (BRDF) using an empirically derived multiplier. At a nominal flying height of 335 m above ground level (AGL), the at-sensor reflectance is a close approximation of surface reflectance. GLREFL data are processed as a zipped raster data product (GeoTIFF) with associated header file (.hdr) at 1 meter spatial resolution over locally defined areas. A low-resolution browse is also provided with a color map applied in PNG format.
TOMS Earth Probe UV Reflectivity Daily L3 Global 1 deg x 1.25 deg Lat/Lon Grid V008 (TOMSEPL3dref) at GES DISC
This Earth Probe (EP) Total Ozone Mapping Spectrometer (TOMS) version 8 daily global gridded data product contains Lambertian effective surface reflectivity values (Rayleigh corrected). The data are mapped to a global grid of size 180 x 288 with a lat-long resolution of 1.00 x 1.25 degrees. These data are stored in an ASCII format.The TOMS data were produced by the Laboratory for Atmospheres at NASA Goddard Space Flight Center (Code 614).
VIIRS/JPSS1 BRDF/Albedo Nadir BRDF-Adjusted Reflectance Daily L3 Global 0.05Deg CMG V002
The NOAA-20 Visible Infrared Imaging Radiometer Suite (VIIRS) Bidirectional Reflectance Distribution Function (BRDF) and Albedo Nadir BRDF-Adjusted Reflectance Daily Global 0.05 Degree Climate Modeling Grid (CMG) Version 2 product (VJ143C4) is derived from the 30 arc second CMG VJ143D Version 2 product suite. VJ143C3 is generated daily from all available high-quality reflectance data over a 16-day moving window emphasizing the ninth day of the retrieval period, which is reflected in the Julian date in the filename. The VJ143 algorithm uses the RossThick/Li-Sparse-Reciprocal (RTLSR) semi-empirical kernel-driven BRDF model, with the three kernel weights from [VJ143C1](https://doi.org/10.5067/VIIRS/VJ143C1.002) to compute NBAR values for the VIIRS Day/Night band (DNB), and moderate resolution bands M1 through M5, M7, M8, M10, and M11. The algorithm removes view angle effects from directional reflectances to model the values as if they were collected from a nadir view at local solar noon. The quality and inversion status of the majority of the underlying 30 arc second pixels is provided as well as the percentage of the underlying pixels that were present or were snow covered. Users are encouraged to assess the quality information before using the BRDF/Albedo data. This 0.05 degree (5,600 meters at the equator) CMG product covers the entire globe for use in climate simulation models. The VJ143C4 product includes 10 layers containing NBAR values for VIIRS DNB and moderate resolution bands M1 through M5, M7, M8, M10, and M11. Along with the NBAR data for the 10 bands are five ancillary layers for uncertainty, quality, local solar noon, percent finer resolution inputs, and snow cover. A low-resolution browse image is also available showing NBAR bands M5, M4, and M3 as a red, green, blue (RGB) image in JPEG format.Known Issues* For complete information about known issues please refer to the [MODIS/VIIRS Land Quality Assessment website](https://landweb.modaps.eosdis.nasa.gov/knownissue?sensor=VIIRS).Improvements/Changes from Previous Version* The NOAA-20 VIIRS algorithms include the same improvements as the S-NPP VIIRS V002* Improved calibration algorithm and better coefficients for entire NOAA-20 mission* Improved geolocation accuracy and updates to fix outliers around maneuver periods and other events* Corrections to the aerosol quantity flag (low, average, high) mainly over brighter surfaces in the mid to high latitudes such as desert and tropical vegetation areas. This has an impact on the retrieval of other downstream data products such as VJ113 Vegetation Indices and VJ143 BRDF/Albedo.* Improved cloud mask input product for corrections along coastlines and artifacts from use of coarse resolution climatology data* Replaced the land/water mask input product with MODIS heritage seven class land/water mask
VIIRS/NPP Surface Reflectance Daily L2G Global 1km and 500m SIN Grid V002
The Visible Infrared Imaging Radiometer Suite (VIIRS) daily surface reflectance (VNP09GA) Version 2 product provides an estimate of land surface reflectance from the NASA/NOAA Suomi National Polar-orbiting Partnership (Suomi NPP) VIIRS sensor. Data are provided for three imagery bands (I1-I3) at nominal 500 meter resolution (~463 meter) and nine moderate resolution bands (M1-M5, M7, M8, M10, M11) at nominal 1 kilometer (~926 meter) resolution. The 500 meter and 1 kilometer datasets are derived through resampling the native 375 meter and 750 meter VIIRS resolutions, respectively, in the Level 2 input product. These bands are corrected for atmospheric conditions such as the effects of molecular gases, including ozone and water vapor, and for the effects of atmospheric aerosols. The inputs to the surface reflectance algorithm are top-of-atmosphere reflectance for the VIIRS visible bands, the VIIRS cloud mask and aerosol product, aerosol optical thickness and atmospheric data obtained from the NOAA National Centers for Environmental Prediction (NCEP) reanalysis system. Along with the twelve reflectance bands are reflectance band quality, sensor azimuth angle, solar azimuth angle, sensor zenith angle, solar zenith angle, and observations layers. The reflectance layers from the VNP09GA data product are used as input data for many of the VIIRS land products. Known Issues* For complete information about known issues please refer to the [MODIS/VIIRS Land Quality Assessment website](https://landweb.modaps.eosdis.nasa.gov/knownissue?sensor=VIIRS) and in Section 4.0 of the User Guide.Improvements/Changes from Previous Versions* Improved calibration algorithm and coefficients for entire Suomi NPP mission.* Improved geolocation accuracy and applied updates to fix outliers around maneuver periods.* Corrected the aerosol quantity flag (low, average, high) mainly over brighter surfaces in the mid- to high-latitudes such as desert and tropical vegetation areas. This has an impact on the retrieval of other downstream data products such as VNP13 Vegetation Indices and VNP43 Bidirectional Reflectance Distribution Function (BRDF)/Albedo.* Improved cloud mask input product for corrections along coastlines and artifacts from use of coarse resolution climatology data. * Replaced the land/water mask input product with the eight-class land/water mask from the VNP03 geolocation product that better aligns with MODIS.* Added secondary day-night flag to improve retrieval of Climate Modeling Grid (CMG) values over daytime pixels.* More details can be found in this [VIIRS Land V2 Changes document](https://landweb.modaps.eosdis.nasa.gov/data/userguide/VIIRS_Land_C2_Changes_09152022.pdf).
BOREAS RSS-03 Reflectance Measured from a Helicopter-Mounted Barnes MMR
The RSS-03 team acquired helicopter-based measurements of forested sites during BOREAS with a Barnes MMR. The data were collected in 1994 during the rhree BOREAS IFCs at numerous tower and auxiliary sites in both the NSA and SSA. The 15-degree FOV of the MMR yielded approximately 79 m from the 300 m altitude ground resolution. The MMR has seven spectral bands that are similar to the Landsat TM bands, ranging from the blue region to the thermal. Note:
BOREAS TE-18 Geosail Canopy Reflectance Model
The SAIL (Scattering from Arbitrarily Inclined Leaves) model was combined with the Jasinski geometric model to simulate canopy spectral reflectance and absorption of photosynthetically active radiation for discontinuous canopies. This model is called the GeoSail model. Tree shapes are described by cylinders or cones distributed over a plane. Spectral reflectance and transmittance of trees are calculated from the SAIL model to determine the reflectance of the three components used in the geometric model: illuminated canopy, illuminated background, shadowed canopy, and shadowed background. The model code is Fortran, sample input and output data are provided in ASCII text files.
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