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GHRSST Level 3C North Atlantic Regional (NAR) subskin Sea Surface Temperature from SNPP/VIIRS (GDS V2) produced by OSI SAF

A regional Group for High Resolution Sea Surface Temperature (GHRSST) Level 3 Collated (L3C) dataset for the North Atlantic Region (NAR) based on retrievals from the Visible Infrared Imaging Radiometer Suite (VIIRS). The European Organization for the Exploitation of Meteorological Satellites (EUMETSAT), Ocean and Sea Ice Satellite Application Facility (OSI SAF) is producing SST products in near real time from Metop/AVHRR and SNPP/VIIRS. Global AVHRR level 1b data are acquired at Meteo-France/Centre de Meteorologie Spatiale (CMS) through the EUMETSAT/EUMETCAST system. NAR SNPP/VIIRS level 0 data are acquired through direct readout and converted into l1b at CMS. SST is retrieved from the AVHRR and VIIRS infrared channels using a multispectral algorithm. This product is delivered as four six hourly collated files per day on a regular 2km grid. The product format is compliant with the GHRSST Data Specification (GDS) version 2.

GHRSST Level 2P Central Pacific Regional Skin Sea Surface Temperature from the Geostationary Operational Environmental Satellites (GOES) Imager on the GOES-15 satellite (GDS version 2)

The Geostationary Operational Environmental Satellites (GOES) operated by the United States National Oceanic and Atmospheric Administration (NOAA) support weather forecasting, severe storm tracking, meteorology and oceanography research. Generally there are several GOES satellites in geosynchronous orbit at any one time viewing different earth locations including the GOES-15 launched 4 March 2010. The radiometer aboard the satellite, The GOES N-P Imager, is a five channel (one visible, four infrared) imaging radiometer designed to sense radiant and solar reflected energy from sampled areas of the earth. The multi-element spectral channels simultaneously sweep east-west and west-east along a north-to-south path by means of a two-axis mirror scan system retuning telemetry in 10-bit precision. For this Group for High Resolution Sea Surface Temperature (GHRSST) dataset, skin sea surface temperature (SST) measurements are calculated from the far IR channels of GOES-15 at full resolution on a half hourly basis. In native satellite projection, vertically adjacent pixels are averaged and read out at every pixel. L2P datasets including Single Sensor Error Statistics (SSES) are then derived following the GHRSST Data Processing Specification (GDS) version 2.0. The full disk image is subsetted into granules representing distinct northern and southern regions.

GHRSST Level 4 REMO_OI_SST_5km Regional Foundation Sea Surface Temperature Analysis (GDS version 2)

A Group for High Resolution Sea Surface Temperature (GHRSST) Level 4 sea surface temperature (SST) analysis produced daily on an operational basis by the Oceanographic Modeling and Observation Network (REMO) at Applied Meteorology Laboratory/Federal University of Rio de Janeiro (LMA/UFRJ) using the Barnes sub optimal interpolation (OI) technique on a regional 0.05 degree grid. REMO uses Advanced Very High Resolution Radiometer (AVHRR) data from National Oceanic and Atmospheric Administration (NOAA) satellites series (NOAA 15, NOAA 16, NOAA 17, NOAA 18 and NOAA 19) and Microwave Imager (TMI) data from Tropical Rainfall Measuring Mission (TRMM) which is a joint mission between NASA and the Japan Aerospace Exploration Agency (JAXA) to generate 0.05 degree daily cloud free blended (infrared and microwave) SST products (approximately 5.5 km). The data lies between latitudes 45 S and 15 N and longitudes 70 W and 15 W region and are fully validated by in situ measurements from eleven buoys of Prediction and Research Moored Array in the Tropical Atlantic (PIRATA).AVHRR is a scanning radiometer capable of detecting energy from land, ocean and atmosphere. It operates with six spectral bands arranged in the regions of visible and infrared region. TRMM was launched in December, 1997, having an orbital inclination of 53 degree and altitude 350 km, an equatorial orbit that ranges from 40 N to 40 S and a spatial resolution of 0.25 degree (∼27.75 km). Although infrared AVHRR SST data have high spatial resolution, they are contaminated by cloud cover and aerosols, while lower resolution microvwave TMI data are barely influenced by these.

MISR Level 1B2 Ellipsoid Product subset for the VBBE region V003

VBEMIB2E_003 is the Multi-angle Imaging SpectroRadiometer (MISR) Level 1B2 Ellipsoid Product subset for the VBBE region version 3. It contains Ellipsoid-projected TOA Radiance, resampled at the surface and topographically corrected, as well as geometrically corrected by PGE22. MISR itself is an instrument designed to view Earth with cameras pointed in 9 different directions. As the instrument flies overhead, each piece of Earth's surface below is successively imaged by all 9 cameras, in each of 4 wavelengths (blue, green, red, and near-infrared).The MISR instrument consists of nine push-broom cameras that measure radiance in four spectral bands. Global coverage is achieved in nine days. The cameras are arranged with one camera pointing toward the nadir, four forward, and four aftward. It takes seven minutes for all nine cameras to view the same surface location. The view angles relative to the surface reference ellipsoid are 0, 26.1, 45.6, 60.0, and 70.5 degrees. The spectral band shapes are nominally Gaussian, centered at 443, 555, 670, and 865 nm.MISR is designed to view Earth with cameras in 9 different directions. As the instrument flies overhead, all nine cameras successfully imaged each piece of Earth's surface below in 4 wavelengths (blue, green, red, and near-infrared). MISR aims to improve our understanding of the effects of sunlight on Earth and distinguish different types of clouds, particles, and surfaces. Specifically, MISR monitors the monthly, seasonal, and long-term trends in three areas: 1) amount and type of atmospheric particles (aerosols), including those formed by natural sources and by human activities; 2) amounts, types, and heights of clouds, and 3) distribution of land surface cover, including vegetation canopy structure.

NOAA GHRSST Level 2P Indian Ocean Regional Skin Sea Surface Temperature v1.0 from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) on the Meteosat Second Generation-2 (MSG-2) satellite

The GHRSST L2P MSG02 SST v1.0 dataset is produced by the US National Oceanic and Atmospheric Administration (NOAA) National Environmental Satellite, Data, and Information Service (NESDIS) from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) onboard the Meteosat-9 (MSG2) satellite. It provides the full disk SEVIRI imagery covering the Indian Ocean region from its position at 45.5°E longitude. The L2P SST is produced at approximately 3 km resolution with a 15 minute duty cycle. On June 1, 2022, the Meteosat-9 (MSG2) replaced the Meteosat-8 (MSG1) (MSG01-OSPO-L2P-v1.0) and produced the L2P SST data from June 11. 2022 to the present. This dataset will be updated every 15 minutes as a forward data stream with 3-24 hours nominal latency. Be aware that the granules before Dec. 1, 2022 contain some uncorrected metadata errors. The SST measurements from SEVIRI are key parameters in study of the weather, atmosphere, climate and ocean environments. Meteosat satellites have been providing crucial data for weather forecasting since 1977. This L2P SST product which includes Single Sensor Error Statistics (i.e., uncertainty statistics) follows the GHRSST Data Processing Specification (GDS) version 2.0 format guidelines. Please refer to the user guide for more information.

GHRSST Level 3C North Atlantic Regional (NAR) subskin Sea Surface Temperature from SNPP/VIIRS and Metop-A/AVHRR (GDS V2) produced by OSI SAF

A Group for High Resolution Sea Surface Temperature (GHRSST) dataset for the North Atlantic Region (NAR) derived from the Advanced Very High Resolution Radiometer (AVHRR) on the European Meteorological Operational-A (MetOp-A) platform (launched 19 Oct 2006). The European Organization for the Exploitation of Meteorological Satellites (EUMETSAT), Ocean and Sea Ice Satellite Application Facility (OSI SAF) is producing SST products in near real time from Metop/AVHRR and SNPP/VIIRS. Global AVHRR level 1b data are acquired at Meteo-France/Centre de Meteorologie Spatiale (CMS) through the EUMETSAT/EUMETCAST system. NAR SNPP/VIIRS level 0 data are acquired through direct readout and converted into l1b at CMS. SST is retrieved from the AVHRR and VIIRS infrared channels using a multispectral algorithm.This product is delivered as four six hourly collated files per day on a regular 2km grid. The product format is compliant with the GHRSST Data Specification (GDS) version 2.

GHRSST Level 2P Regional 1m Sea Surface Temperature from the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA-19 satellite produced by NAVO

A regional Group for High Resolution Sea Surface Temperature (GHRSST) Level 2P dataset based on multi-channel sea surface temperature (SST) retrievals generated in real-time from the Advanced Very High Resolution Radiometer (AVHRR) on the NOAA-19 platform (launched 6 Feb 2009) produced and used operationally in oceanographic analyses and forecasts by the US Naval Oceanographic Office (NAVO). The AVHRR is a space-borne scanning sensor on the National Oceanic and Atmospheric Administration (NOAA) family of Polar Orbiting Environmental Satellites (POES) having a operational legacy that traces back to the Television Infrared Observation Satellite-N (TIROS-N) launched in 1978. AVHRR instruments measure the radiance of the Earth in 5 (or 6) relatively wide spectral bands. The first two are centered around the red (0.6 micrometer) and near-infrared (0.9 micrometer) regions, the third one is located around 3.5 micrometer, and the last two sample the emitted thermal radiation, around 11 and 12 micrometers, respectively. The legacy 5 band instrument is known as AVHRR/2 while the more recent version, the AVHRR/3 (first carried on the NOAA-15 platform), acquires data in a 6th channel located at 1.6 micrometer. Typically the 11 and 12 micron channels are used to derive SST sometimes in combination with the 3.5 micron channel. The NOAA platforms are sun synchronous generally viewing the same earth location twice a day (latitude dependent) due to the relatively large AVHRR swath of approximately 2400 km. The highest ground resolution that can be obtained from the current AVHRR instruments is 1.1 km at nadir. AVHRR data are acquired in three formats: High Resolution Picture Transmission (HRPT), Local Area Coverage (LAC), and Global Area Coverage (GAC). HRPT data are full resolution image data transmitted to a ground stations as they are collected. LAC are also full resolution data, but the acquisition is prescheduled and recorded with an on-board tape recorder for subsequent transmission during a station overpass. GAC data provide daily subsampled global coverage recorded on tape recorders and then transmitted to a ground station. This particular dataset is derived from LAC data. Further binning and averaging of the 1.1 km LAC pixels results in a final dataset resolution of 2.2 km. The coverage of the LAC data can vary but generally contains scenes over the oceans adjacent to Australia and the North Indian Ocean.

GHRSST Level 2P Western Pacific Regional Skin Sea Surface Temperature from the Multifunctional Transport Satellite 2 (MTSAT-2) (GDS version 2)

Multi-functional Transport Satellites (MTSAT) are a series of geostationary weather satellites operated by the Japan Meteorological Agency (JMA). MTSAT carries an aeronautical mission to assist air navigation, plus a meteorological mission to provide imagery over the Asia-Pacific region for the hemisphere centered on 140 East. The meteorological mission includes an imager giving nominal hourly full Earth disk images in five spectral bands (one visible, four infrared). MTSAT are spin stabilized satellites. With this system images are built up by scanning with a mirror that is tilted in small successive steps from the north pole to south pole at a rate such that on each rotation of the satellite an adjacent strip of the Earth is scanned. It takes about 25 minutes to scan the full Earth's disk. This builds a picture 10,000 pixels for the visible images (1.25 km resolution) and 2,500 pixels (4 km resolution) for the infrared images. The MTSAT-2 (also known as Himawari 7) and its radiometer (MTSAT-2 Imager) was successfully launched on 18 February 2006. For this Group for High Resolution Sea Surface Temperature (GHRSST) dataset, skin sea surface temperature (SST) measurements are calculated from the IR channels of the MTSAT-2 Imager full resolution data in satellite projection on a hourly basis by using Bayesian Cloud Mask algorithm at the Office of Satellite and Product Operations (OSPO). L2P datasets including Single Sensor Error Statistics (SSES) are then derived following the GHRSST Data Processing Specification (GDS) version 2.0.

GHRSST Level 2P Atlantic Regional Skin Sea Surface Temperature from the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) on the Meteosat Second Generation (MSG-3) satellite (GDS version 2)

The Meteosat Second Generation (MSG-3) satellites are spin stabilized geostationary satellites operated by the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) to provide accurate weather monitoring data through its primary instrument the Spinning Enhanced Visible and InfraRed Imager (SEVIRI), which has the capacity to observe the Earth in 12 spectral channels. Eight of these channels are in the thermal infrared, providing among other information, observations of the temperatures of clouds, land and sea surfaces at approximately 5 km resolution with a 15 minute duty cycle. This Group for High Resolution Sea Surface Temperature (GHRSST) dataset produced by the US National Oceanic and Atmospheric Administration (NOAA) National Environmental Satellite, Data, and Information Service (NESDIS) is derived from the SEVIRI instrument on the second MSG satellite (also known as Meteosat-9) that was launched on 22 December 2005. Skin sea surface temperature (SST) data are calculated from the infrared channels of SEVIRI at full resolution every 15 minutes. L2P data products with Single Sensor Error Statistics (SSES) are then derived following the GHRSST-PP Data Processing Specification (GDS) version 2.0.

openGEO-OpenMay 2024View details →

Gene expression profile at single cell level of cells from the heart region of E9.5 mouse embryos (P0) and the cultured cells from P0 in vitro (P6).

GEO Series GSE231986. Mus musculus. 2 samples. Type: Expression profiling by high throughput sequencing.

openGEO-OpenNov 2023View details →

Deficiency of Rpsa results in reduced levels of H3K4me3 in inflammatory cytokines promoter regions

GEO Series GSE204890. Mus musculus. 4 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.

openGEO-OpenJun 2015View details →

DNA methylation levels of various brain regions from HIV+ and HIV- subjects

GEO Series GSE59457. Homo sapiens. 130 samples. Type: Methylation profiling by genome tiling array.

openGEO-OpenJan 2010View details →

Cardiac Resynchronization Therapy Corrects Dyssynchrony-induced Regional Gene Expression Changes on a Genomic Level

GEO Series GSE14661. Canis lupus familiaris. 76 samples. Type: Expression profiling by array.

openGEO-OpenJan 2023View details →

Open chromatin regions at the single cell level of CD8+ T cells from the spleens of LCMV-Armstrong or LCMV-Clone 13 infected mice

GEO Series GSE213469. Mus musculus. 2 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.

opencc-by-4.0Apr 2020View details →

Data for "A Comparison on the E-change Pulses Occurring in the Bi-level Polarity-opposite Charge Regions of the Intra-Cloud Lightning Flashes"

In a manuscript entitled “A Comparison on the E-change Pulses Occurring in the Bi-level Polarity-opposite Charge Regions of the Intra-Cloud Lightning Flashes”, lightning locations and electric field can be obtained through the following attachment. These files can be opened by MATLAB 2016 (or later). The data supports the aforementioned manuscript and can be used freely for scientific purposes with appropriate citations.   Data named as “Example_IC_Flash” consists of locations and an E-change waveform. Each location data has four columns, representing x (km), y (km), z (km), and time (ms). The E-change data has two columns, namely to time (ms) and E-change amplitude (DU).   The other Data are stored using the form of ‘.fig’. Researchers can open these figures directly by using MATLAB.

opencc-by-4.0Jul 2023View details →

The best performing landslide susceptibility maps using ensemble machine learning models and precipitation data on basin and regional level in Lombardy, Italy

A selection of landslide susceptibility maps computed through ensemble machine learning models with included precipitation data for the basin of Valchiavenna, and the Lombardy region in Italy. A list of the used base machine learning methods: <ul> <li>Neural Networks.</li> </ul> A list of the precipitation data included in the models: <ul> <li>Average hourly precipitation for the year of 2020,</li> <li>90th percentile for the hourly precipitation for the year of 2020 ,</li> <li>Averaged + 90th percentile for the hourly precipitation for the year of 2020.</li> </ul> A full list of the model combinations can be found in the "Case Studies" document. The maps are in WGS 84/ UTM zone 32N (EPSG:32632). The map production process details are discussed in Xu et al. 2024. If you use the dataset, please, cite also the paper: Qiongjie Xu, Vasil Yordanov, Lorenzo Amici & Maria Antonia Brovelli (2024) Landslide susceptibility mapping using ensemble machine learning methods: a case study in Lombardy, Northern Italy, International Journal of Digital Earth, 17:1, 2346263, DOI:10.1080/17538947.2024.2346263 The maps are produced as part of the "Geoinformatics and Earth Observation for Landslide Monitoring" Italy-Vietnam. The work is partially funded by the Italian Ministry of Foreign Affairs and International Cooperation within the project “Geoinformatics and Earth Observation for Landslide Monitoring” CUP D19C21000480001.

opencc-by-4.0Jul 2023View details →

Landslide susceptibility maps using base machine learning models on basin and regional level in Lombardy, Italy

A selection of landslide susceptibility maps computed through base machine learning models for the basins of Val Tartano, Upper Valtellina and Valchiavenna, and on a regional level for the Lombardy region in Italy. A list of the used machine learning methods: <ul> <li>Bagging,</li> <li>Random Forest,</li> <li>AdaBoost,</li> <li>Gradient Tree Boosting,</li> <li>Neural Networks.</li> </ul> A full list of the model combinations can be found in the "Case Studies" document. The maps are in WGS 84/ UTM zone 32N (EPSG:32632). The map production process details are discussed in Xu et al. 2024. If you use the dataset, please, cite also the paper: Qiongjie Xu, Vasil Yordanov, Lorenzo Amici & Maria Antonia Brovelli (2024) Landslide susceptibility mapping using ensemble machine learning methods: a case study in Lombardy, Northern Italy, International Journal of Digital Earth, 17:1, 2346263, DOI:10.1080/17538947.2024.2346263 The maps are produced as part of the "Geoinformatics and Earth Observation for Landslide Monitoring" Italy-Vietnam. The work is partially funded by the Italian Ministry of Foreign Affairs and International Cooperation within the project “Geoinformatics and Earth Observation for Landslide Monitoring” CUP D19C21000480001.

restrictedcc-by-4.0Dec 2023View details →

Quantifying meridional advection in the auroral E-region for a range of geomagnetic activity levels

This repository contains the data used to reproduce the plots in the paper titled: Quantifying meridional advection in the auroral E-region for a range of geomagnetic activity levels The paper was first submitted on XX/2024 and accepted at XX/2024. A GitHub repository with the code used to produce the plots in the paper will be posted at ZZZZ.