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NOAA Open Data Dissemination Program

Amazon Web Services has entered into a research agreement with the US National Oceanic and Atmospheric Administration (NOAA) to explore sustainable models to increase the output of open NOAA data. Publicly available NOAA data drives multi-billion dollar industries and critical research efforts. Under this agreement, AWS and its collaborators will look at ways to push more NOAA data to the cloud and build an ecosystem of innovation around it.


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NOAA Geostationary Operational Environmental Satellites (GOES) 16, 17 & 18

agriculturedisaster responseearth observationgeospatialmeteorologicalsatellite imagerysustainabilityweather

NEW GOES-18 Data!!! GOES-18 is now provisional and data has began streaming. Data files will be available between Provisional and the Operational Declaration of the satellite, however, data will have the caveat GOES-18 Preliminary, Non-Operational Data. The exception is during the interleave period when ABI Radiances and Cloud and Moisture Imagery data will be shared operationally via the NOAA Open Data Dissemination Program.

GOES satellites (GOES-16, GOES-17, & GOES-18) provide continuous weather imagery and monitoring of meteorological and space environment data across North America.
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NEXRAD on AWS

agricultureearth observationmeteorologicalnatural resourcesustainabilityweather

Real-time and archival data from the Next Generation Weather Radar (NEXRAD) network.

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NOAA Operational Forecast System (OFS)

climatecoastaldisaster responseenvironmentalmeteorologicaloceanssustainabilitywaterweather

ANNOUNCEMENTS: [NOS OFS Version Updates and Implementation of Upgraded Oceanographic Forecast Modeling Systems for Lakes Superior and Ontario; Effective October 25, 2022}(https://www.weather.gov/media/notification/pdf2/scn22-91_nos_loofs_lsofs_v3.pdf)

For decades, mariners in the United States have depended on NOAA's Tide Tables for the best estimate of expected water levels. These tables provide accurate predictions of the astronomical tide (i.e., the change in water level due to the gravitational effects of the moon and sun and the rotation of the Earth); however, they cannot predict water-level changes due to wind, atmospheric pressure, and river flow, which are often significant.

The National Ocean Service (NOS) has the mission and mandate to provide guidance and information to support navigation and coastal needs. To support this mission, NOS has been developing and implementing hydrodynamic model-based Operational Forecast Systems.

This forecast guidance provides oceanographic information that helps mariners safely navigate their local waters. This national network of hydrodynamic models provides users with operational nowcast and forecast guidance (out to 48 – 120 hours) on parameters such as water levels, water temperature, salinity, and currents. These forecast systems are implemented in critical ports, harbors, estuaries, Great Lakes and coastal waters of the United States, and form a national backbone of real-time data, tidal predictions, data management and operational modeling.

Nowcasts and forecasts are scientific predictions about the present and future states of water levels (and possibly currents and other relevant oceanographic variables, such as salinity and temperature) in a coastal area. These predictions rely on either observed data or forecasts from a numerical model. A nowcast incorporates recent (and often near real-time) observed meteorological, oceanographic, and/or river flow rate data. A nowcast covers the period from the recent past (e.g., the past few days) to the present, and it can make predictions for locations where observational data are not available. A forecast incorporates meteorological, oceanographic, and/or river flow rate forecasts and makes predictions for times where observational data will not be available. A forecast is usually initiated by the results of a nowcast.

OFS generally runs four times per day (every 6 hours) on NOAA's Weather and Climate Operational Supercomputing Systems (WCOSS) in a standard Coastal Ocean Modeling Framework (COMF) developed by the Center for Operational Oceanographic Products and Services (CO-OPS). COMF is a set...

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NOAA Joint Polar Satellite System (JPSS)

agricultureclimatemeteorologicalsustainabilityweather

Satellites in the JPSS constellation gather global measurements of atmospheric, terrestrial and oceanic conditions, including sea and land surface temperatures, vegetation, clouds, rainfall, snow and ice cover, fire locations and smoke plumes, atmospheric temperature, water vapor and ozone. JPSS delivers key observations for the Nation's essential products and services, including forecasting severe weather like hurricanes, tornadoes and blizzards days in advance, and assessing environmental hazards such as droughts, forest fires, poor air quality and harmful coastal waters. Further, JPSS w...

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NOAA Rapid Refresh Forecast System (RRFS) [Prototype]

agricultureclimatemeteorologicalsustainabilityweather

The Rapid Refresh Forecast System (RRFS) is the National Oceanic and Atmospheric Administration’s (NOAA) next generation convection-allowing, rapidly-updated ensemble prediction system, currently scheduled for operational implementation in 2024. The operational configuration will feature a 3 km grid covering North America and include deterministic forecasts every hour out to 18 hours, with deterministic and ensemble forecasts to 60 hours four times per day at 00, 06, 12, and 18 UTC.The RRFS will provide guidance to support forecast interests including, but not limited to, aviation, severe convective weather, renewable energy, heavy precipitation, and winter weather on timescales where rapidly-updated guidance is particularly useful.

The RRFS is underpinned by the Unified Forecast System (UFS), a community-based Earth modeling initiative, and benefits from collaborative development efforts across NOAA, academia, and research institutions.

This bucket provides access to real time, experimental RRFS prototype output as of October 2022. This bucket also holds output from past experimental RRFS prototypes that were evaluated as a part of NOAA testbed projects. The immediate section describes the data for the real time system. The section that follows thereafter describes outputs from three past NOAA Testbed experiments.


Real time, experimental RRFS Prototype output

The real-time RRFS prototype is experimental and evolving. It is not under 24x7 monitoring and is not operational. Output may be delayed or missing. Outputs will change. When significant changes to output take place, this description will be updated.

We currently provide hourly deterministic forecasts at 3 km grid spacing over the CONUS out to 60 hours at 00 and 12 UTC, and out to 18 hours at other times. Future enhancements will include an ensemble forecast component and expansion to the planned North American domain. All forecasts are initialized from a hybrid 3DEnVar data assimilation system with hourly updates.Output is available on the S3 bucket for every third cycle, and is organized by cycle day and time of day. For example, rrfs_a/rrfs_a.20221012/00/ contains the forecast initialized at 00 UTC on 12 October 2022. Users will find two types of output in GRIB2 format. The first is:

rrfs.t00z.natlev.f018.conus_3km.grib2

Meaning that this is the RRFS_A initialized at 00 UTC, covers the CONUS domain, and is the native level post-processed gridded data at hour 18. This output is on a Lambert Conic Conformal domain at 3 km grid spacing.

The second output file in grib2 format is:

rrfs.t00z.prslev.f018.conus_3km.grib2

Meaning that this is the pressure level post-processed gridded data.


Past output from NOAA Testbed Experiments

This bucket also provides datasets from three of the 2021 NOAA Testbed Experiments. During each of these experiments, a prototype version of RRFS under development was run. The following is a high-level overview dates and RRFS configurations for each of the Testbed Experiments.

2021 Hazardous Weather Testbed (HWT) Spring Forecast Experiment (May 3 through June 4 2021) and 2021 Hydrometeorological Testbed Annual Flash Flood and Intense Rainfall Experiment (FFaIR) (June 21 through July 23 2021, excluding the week of July 4). A 9-member multi-physics ensemble with stochastic perturbations run once per day at 3 km grid spacing covering North America out to 60 hours. Initial conditions and lateral boundary conditions are taken from the GFS and GEFS.

2021-2022 Hydrometeorological Testbed Winter Weather Experiment (WWE) (mid November through mid-March). Select cases only. Deterministic forecasts were run once per day at 00 UTC at 3 km grid spacing covering the CONUS out to 60 hours. A 36-member, 3 km ensemble Kalman filter data assimilation approach is implemented through hourly cycling starting at 18 UTC on the previous day.

For each cycle of the HWT and FFaIR experiments, the dataset is organized by cycle day, time of day, and member. For example, rrfs.20210504/00/mem01/ contains the forecast from ensemble member 1 initialized at 00 UTC on 04 May 2021. Users will find two types of output in GRIB2 format. The first is:

rrfs.t00z.mem01.naf024.grib2

Meaning that this is RRFS ensemble member 1 initialized at 00 UTC, covers the North American domain, and is the post-processed gridded data at hour 24. This output is on a rotated latitude-longitude domain at 3 km grid spacing. These are large files and users may wish to subset or re-project the grid after downloading. We recommend using the WGRIB2 application for such purposes.

The second output file in grib2 format is as follows:

rrfs.t00z.mem01.testbed.conusf020.grib2

These grids have been subset from the much larger North American domain to a CONUS domain on a Lambert Conic Conformal projection and also contain significantly fewer fields, resulting in smaller files.

Graphics for select runs are also included in a plots/ directory under each experiment day for quick, yet simple visualization.

For each cycle of the WWE, the dataset is organized by cycle day and time of day. For example, rrfs.20220306/00/ contains data for the forecast initialized at 00 UTC on 06 March 2022. The initial conditions for the 36 ensemble members are located in the ens_ics/mem??? subdirectories. Users will find two types of output in GRIB2 format in the post subdirectories. The first is:

BGDAWP.GrbF12

Meaning that this is the forecast initialized at 00 UTC, covers the CONUS domain, and is the pressure level post-processed gridded data at forecast hour 18. This output is on a Lambert Conic Conformal grid at 3 km grid spacing.

The second output file in grib2 format is as follows:

testbed.conusf030.grib2

These grids contain significantly fewer fields, resulting in smaller files.

This work is supported by the Unified Forecast System Research to Operation (UFS R2O) Project which is jointly funded by NOAA’s Office of Science and Technology Integration (OSTI) of National Weather Service (NWS) and Weather Program Office (WPO), [Joint Technology Transfer Initiative (JTTI)] of the Office of Oceanic and Atmospheric Research (OAR).

DISCLAIMER The o...

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JMA Himawari-8/9

agriculturedisaster responseearth observationgeospatialmeteorologicalsatellite imagerysustainabilityweather

Himawari-8, stationed at 140E, owned and operated by the Japan Meteorological Agency (JMA), is a geostationary meteorological satellite, with Himawari-9 as on-orbit back-up, that provides constant and uniform coverage of east Asia, and the west and central Pacific regions from around 35,800 km above the equator with an orbit corresponding to the period of the earth’s rotation. This allows JMA weather offices to perform uninterrupted observation of environmental phenomena such as typhoons, volcanoes, and general weather systems. Archive data back to July 2015 is available for Full Disk (AHI-L1...

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NOAA Global Ensemble Forecast System (GEFS) Re-forecast

agricultureclimatemeteorologicalsustainabilityweather

NOAA has generated a multi-decadal reanalysis and reforecast data set to accompany the next-generation version of its ensemble prediction system, the Global Ensemble Forecast System, version 12 (GEFSv12). Accompanying the real-time forecasts are “reforecasts” of the weather, that is, retrospective forecasts spanning the period 2000-2019. These reforecasts are not as numerous as the real-time data; they were generated only once per day, from 00 UTC initial conditions, and only 5 members were provided, with the following exception. Once weekly, an 11-member reforecast was generated, and these ex...

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NOAA Global Historical Climatology Network Daily (GHCN-D)

agricultureclimatemeteorologicalsustainabilityweather


UPDATE TO GHCN PREFIXES - The NODD team is working on improving performance and access to the GHCNd data and will be implementing an updated prefix structure. For more information on the prefix changes, please see the "READ ME on the NODD Github". If you have questions, comments, or feedback, please reach out to nodd@noaa.gov with GHCN in the subject line.

Global Historical Climatology Network - Daily is a dataset from NOAA that contains daily observations over global land areas. It contains station-based measurements f...

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NOAA High-Resolution Rapid Refresh (HRRR) Model

agricultureclimatedisaster responseenvironmentalsustainabilityweather

The HRRR is a NOAA real-time 3-km resolution, hourly updated, cloud-resolving, convection-allowing atmospheric model, initialized by 3km grids with 3km radar assimilation. Radar data is assimilated in the HRRR every 15 min over a 1-h period adding further detail to that provided by the hourly data assimilation from the 13km radar-enhanced Rapid Refresh.

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NOAA Climate Forecast System (CFS)

agricultureclimatemeteorologicalsustainabilityweather

The Climate Forecast System (CFS) is a model representing the global interaction between Earth's oceans, land, and atmosphere. Produced by several dozen scientists under guidance from the National Centers for Environmental Prediction (NCEP), this model offers hourly data with a horizontal resolution down to one-half of a degree (approximately 56 km) around Earth for many variables. CFS uses the latest scientific approaches for taking in, or assimilating, observations from data sources including surface observations, upper air balloon observations, aircraft observations, and satellite obser...

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NOAA Emergency Response Imagery

aerial imageryclimatecogdisaster responsesustainabilityweather

In order to support NOAA's homeland security and emergency response requirements, the National Geodetic Survey Remote Sensing Division (NGS/RSD) has the capability to acquire and rapidly disseminate a variety of spatially-referenced datasets to federal, state, and local government agencies, as well as the general public. Remote sensing technologies used for these projects have included lidar, high-resolution digital cameras, a film-based RC-30 aerial camera system, and hyperspectral imagers. Examples of rapid response initiatives include acquiring high resolution images with the Emerge/App...

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NOAA World Ocean Database (WOD)

climateoceanssustainability

The World Ocean Database (WOD) is the largest uniformly formatted, quality-controlled, publicly available historical subsurface ocean profile database. From Captain Cook's second voyage in 1772 to today's automated Argo floats, global aggregation of ocean variable information including temperature, salinity, oxygen, nutrients, and others vs. depth allow for study and understanding of the changing physical, chemical, and to some extent biological state of the World's Oceans. Browse the bucket via the AWS S3 explorer: https://noaa-wod-pds.s3.amazonaws.com/index.html

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  • The World Ocean Database Introduction by Tim P. Boyer, Olga K. Baranova, Carla Coleman, Hernan E. Garcia, Alexandra Grodsky, Ricardo A. Locarnini, Alexey V. Mishonov, Christopher R. Paver, James R. Reagan, Dan Seidov, Igor V. Smolyar, Katharine W. Weathers, Melissa M. Zweng
  • The World Ocean Database User's Manual by Hernan E. Garcia, Tim P. Boyer, Ricardo A. Locarnini, Olga K. Baranova, Melissa M. Zweng

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Coupled Model Intercomparison Project Phase 5 (CMIP5) University of Wisconsin-Madison Probabilistic Downscaling Dataset

climatecoastaldisaster responseenvironmentalmeteorologicaloceanssustainabilitywaterweather

The University of Wisconsin Probabilistic Downscaling (UWPD) is a statistically downscaled dataset based on the Coupled Model Intercomparison Project Phase 5 (CMIP5) climate models. UWPD consists of three variables, daily precipitation and maximum and minimum temperature. The spatial resolution is 0.1°x0.1° degree resolution for the United States and southern Canada east of the Rocky Mountains.

The downscaling methodology is not deterministic. Instead, to properly capture unexplained variability and extreme events, the methodology predicts a spatially and temporally varying Probability Density Function (PDF) for each variable. Statistics such as the mean, mean PDF and annual maximum statistics can be calculated directly from the daily PDF and these statistics are included in the dataset. In addition, “standard”, “raw” data is created by randomly sampling from the PDFs to create a “realization” of the local scale given the large-scale from the climate model. There are 3 realizations for temperature and 14 realizations for precipitation. ...

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Crowdsourced Bathymetry

earth observationoceanssustainability

Community provided bathymetry data collected in collaboration with the International Hydrographic Organization.

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NOAA Global Forecast System (GFS)

agricultureclimatedisaster responseenvironmentalmeteorologicalsustainabilityweather

NOTE - Upgrade NCEP Global Forecast System to v16.3.0 - Effective November 29, 2022 See notification HERE

The Global Forecast System (GFS) is a weather forecast model produced by the National Centers for Environmental Prediction (NCEP). Dozens of atmospheric and land-soil variables are available through this dataset, from temperatures, winds, and precipitation to soil moisture and atmospheric ozone concentration. The entire globe is covered by the GFS at a base horizontal resolution of 18 miles (28 kilometers) between grid points, which is used by the operational forecasters who predict weather out to 16 days in the future. Horizontal resolution drops to 44 miles (70 kilometers) between grid point for forecasts between one week and two weeks.

The NOAA Global Forecast Systems (GFS) Warm Start Initial Conditions are produced by the National Centers for Environmental Prediction Center (NCEP) to run operational deterministic medium-range numerical weather predictions.
The GFS is built with the GFDL Finite-Volume Cubed-Sphere Dynamical Core (FV3) and the Grid-Point Statistical Interpolation (GSI) data assimilation system.
Please visit the links below in the Documentation section to find more details about the model and the data...

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NOAA Global Surface Summary of Day

agricultureclimateenvironmentalnatural resourceregulatorysustainabilityweather

Global Surface Summary of the Day is derived from The Integrated Surface Hourly (ISH) dataset. The ISH dataset includes global data obtained from the USAF Climatology Center, located in the Federal Climate Complex with NCDC. The latest daily summary data are normally available 1-2 days after the date-time of the observations used in the daily summaries. The online data files begin with 1929 and are at the time of this writing at the Version 8 software level. Over 9000 stations' data are typically available. The daily elements included in the dataset (as available from each station) are:
Mean temperature (.1 Fahrenheit)
Mean dew point (.1 Fahrenheit)
Mean sea level pressure (.1 mb)
Mean station pressure (.1 mb)
Mean visibility (.1 miles)
Mean wind speed (.1 knots)
Maximum sustained wind speed (.1 knots)
Maximum wind gust (.1 knots)
Maximum temperature (.1 Fahrenheit)
Minimum temperature (.1 Fahrenheit)
Precipitation amount (.01 inches)
Snow depth (.1 inches)
Indicator for occurrence of: Fog, Rain or Drizzle, Snow or Ice Pellets, Hail, Thunder, Tornado/Funnel Cloud.

G
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NOAA Integrated Surface Database (ISD)

agricultureclimatemeteorologicalsustainabilityweather

The Integrated Surface Database (ISD) consists of global hourly and synoptic observations compiled from numerous sources into a gzipped fixed width format. ISD was developed as a joint activity within Asheville's Federal Climate Complex. The database includes over 35,000 stations worldwide, with some having data as far back as 1901, though the data show a substantial increase in volume in the 1940s and again in the early 1970s. Currently, there are over 14,000 "active" stations updated daily in the database. The total uncompressed data volume is around 600 gigabytes; however, it ...

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NOAA National Digital Forecast Database (NDFD)

agricultureclimatemeteorologicalsustainabilityweather

The National Digital Forecast Database (NDFD) is a suite of gridded forecasts of sensible weather elements (e.g., cloud cover, maximum temperature). Forecasts prepared by NWS field offices working in collaboration with the National Centers for Environmental Prediction (NCEP) are combined in the NDFD to create a seamless mosaic of digital forecasts from which operational NWS products are generated. The most recent data is under the opnl and expr prefixes. A copy is also placed under the wmo prefix. The wmo prefix is structured like so: wmo/<parameter>/<year>/<month>/<day&g...

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NOAA S-111 Surface Water Currents Data

oceanssustainabilitywater

S-111 is a data and metadata encoding specification that is part of the S-100 Universal Hydrographic Data Model, an international standard for hydrographic data. This collection of data contains surface water currents forecast guidance from NOAA/NOS Operational Forecast Systems, a set of operational hydrodynamic nowcast and forecast modeling systems, for various U.S. coastal waters and the great lakes. The collection also contains surface current forecast guidance output from the NCEP Global Real-Time Ocean Forecast System (GRTOFS) for some offshore areas. These datasets are encoded as HDF-5 f...

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NOAA U.S. Climate Normals

agricultureclimatemeteorologicalsustainabilityweather

The U.S. Climate Normals are a large suite of data products that provide information about typical climate conditions for thousands of locations across the United States. Normals act both as a ruler to compare today’s weather and tomorrow’s forecast, and as a predictor of conditions in the near future. The official normals are calculated for a uniform 30 year period, and consist of annual/seasonal, monthly, daily, and hourly averages and statistics of temperature, precipitation, and other climatological variables from almost 15,000 U.S. weather stations.

NCEI generates the official U.S. norma
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NOAA Wave Ensemble Reforecast

agricultureclimatemeteorologicalsustainabilityweather

This is a 20-year global wave reforecast generated by WAVEWATCH III model (https://github.com/NOAA-EMC/WW3) forced by GEFSv12 winds (https://noaa-gefs-retrospective.s3.amazonaws.com/index.html). The wave ensemble was run with one cycle per day (at 03Z), spatial resolution of 0.25°X0.25° and temporal resolution of 3 hours. There are five ensemble members (control plus four perturbed members) and, once a week (Wednesdays), the ensemble is expanded to eleven members. The forecast range is 16 days and, once a week (Wednesdays), it extends to 35 days. More information about the wave modeling, wave grids and calibration can be found in the WAVEWATCH III regtest ww3_ufs1.3 (https://github.com/NOAA-EMC/WW3/tree/develop/regtests/ww3_ufs1.3). ...

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NOAA/PMEL Ocean Climate Stations Moorings

climateenvironmentaloceanssustainabilityweather

The mission of the Ocean Climate Stations (OCS) Project is to make meteorological and oceanic measurements from autonomous platforms. Calibrated, quality-controlled, and well-documented climatological measurements are available on the OCS webpage and the OceanSITES Global Data Assembly Centers (GDACs), with near-realtime data available prior to release of the complete, downloaded datasets.

OCS measurements served through the Big Data Program come from OCS high-latitude moored buoys located in the Kuroshio Extension (32°N 145°E) and the Gulf of Alaska (50°N 145°W). Initiated in 2004 and 20
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NOAA Atmospheric Climate Data Records

agricultureclimatemeteorologicalsustainabilityweather

NOAA's Climate Data Records (CDRs) are robust, sustainable, and scientifically sound climate records that provide trustworthy information on how, where, and to what extent the land, oceans, atmosphere and ice sheets are changing. These datasets are thoroughly vetted time series measurements with the longevity, consistency, and continuity to assess and measure climate variability and change. NOAA CDRs are vetted using standards established by the National Research Council (NRC).

Climate Data Records are created by merging data from surface, atmosphere, and space-based systems across decades. NOAA’s Climate Data Records provides authoritative and traceable long-term climate records. NOAA developed CDRs by applying modern data analysis methods to historical global satellite data. This process can clarify the underlying climate trends within the data and allows researchers and other users to identify economic and scientific value in these records. NCEI maintains and extends CDRs by applying the same methods to present-day and future satellite measurements.

Atmospheric Climate Data Records are measurements of several global variables to help characterize the atmosphere
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NOAA Coastal Lidar Data

climatedisaster responseelevationgeospatiallidarsustainability

Lidar (light detection and ranging) is a technology that can measure the 3-dimentional location of objects, including the solid earth surface. The data consists of a point cloud of the positions of solid objects that reflected a laser pulse, typically from an airborne platform. In addition to the position, each point may also be attributed by the type of object it reflected from, the intensity of the reflection, and other system dependent metadata. The NOAA Coastal Lidar Data is a collection of lidar projects from many different sources and agencies, geographically focused on the coastal areas...

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NOAA Continuously Operating Reference Stations (CORS) Network (NCN)

broadcast ephemerisContinuously Operating Reference Station (CORS)earth observationgeospatialGNSSGPSmappingNOAA CORS Network (NCN)post-processingRINEXsurvey

The NOAA Continuously Operating Reference Stations (CORS) Network (NCN), managed by NOAA/National Geodetic Survey (NGS), provide Global Navigation Satellite System (GNSS) data, supporting three dimensional positioning, meteorology, space weather, and geophysical applications throughout the United States. The NCN is a multi-purpose, multi-agency cooperative endeavor, combining the efforts of hundreds of government, academic, and private organizations. The stations are independently owned and operated. Each agency shares their GNSS/GPS carrier phase and code range measurements and station metadata with NGS, which are analyzed and distributed free of charge. ...

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NOAA Fundamental Climate Data Records (FCDR)

agricultureclimatemeteorologicalsustainabilityweather

NOAA's Climate Data Records (CDRs) are robust, sustainable, and scientifically sound climate records that provide trustworthy information on how, where, and to what extent the land, oceans, atmosphere and ice sheets are changing. These datasets are thoroughly vetted time series measurements with the longevity, consistency, and continuity to assess and measure climate variability and change. NOAA CDRs are vetted using standards established by the National Research Council (NRC).

Climate Data Records are created by merging data from surface, atmosphere, and space-based systems across decades. NOAA’s Climate Data Records provides authoritative and traceable long-term climate records. NOAA developed CDRs by applying modern data analysis methods to historical global satellite data. This process can clarify the underlying climate trends within the data and allows researchers and other users to identify economic and scientific value in these records. NCEI maintains and extends CDRs by applying the same methods to present-day and future satellite measurements.

Fundamental CDRs are composed of sensor data (e.g. calibrated radiances, brightness temperatures) that have been
...

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NOAA Global Ensemble Forecast System (GEFS)

agricultureclimatemeteorologicalsustainabilityweather

The Global Ensemble Forecast System (GEFS), previously known as the GFS Global ENSemble (GENS), is a weather forecast model made up of 21 separate forecasts, or ensemble members. The National Centers for Environmental Prediction (NCEP) started the GEFS to address the nature of uncertainty in weather observations, which is used to initialize weather forecast models. The GEFS attempts to quantify the amount of uncertainty in a forecast by generating an ensemble of multiple forecasts, each minutely different, or perturbed, from the original observations. With global coverage, GEFS is produced fo...

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NOAA Global Extratropical Surge and Tide Operational Forecast System (Global ESTOFS)

climatecoastaldisaster responseenvironmentalglobalmeteorologicaloceanssustainabilitywaterweather

NOTICE - The Coast Survey Development Laboratory (CSDL) in NOAA/National Ocean Service (NOS)/Office of Coast Survey is proposing to upgrade the Surge and Tide Operational Forecast System (STOFS, formerly ESTOFS) to Version 1.0.1 in late fall of 2022. CSDL is seeking comments on this proposed upgrade through September 1, 2022. If approved, a Service Change Notice (SCN) will be issued at least 30 days before implementation of STOFS V1.0.1 with more detailed information. More details on the Public Information Statement can be found "HERE"

NOAA's Global Extratropical Surge and Tide Operational Forecast System (Global ESTOFS) provides users with nowcasts (analyses of near present conditions) and forecast guidance of water level conditions for the entire globe. Global ESTOFS has been developed to serve the marine navigation, weather forecasting, and disaster mitigation user communities. Global ESTOFS was developed in a collaborative effort between the NOAA/National Ocean Service (NOS)/Office of Coast Survey, the NOAA/National Weather Service (NWS)/National Centers for Environmental Prediction (NCEP) Central Operations (NCO), the University of Notre Dame, the University of North Carolina, and The Water Institute of the Gulf. The model generates forecasts out to 180 hours four times per day; forecast output includes water levels caused by the combined effects of storm surge and tides, by astronomical tides alone, and by sub-tidal water levels (isolated storm surge).

The hydrodynamic model employed by Global ESTOFS is the ADvanced CIRCulation (ADCIRC) finite element model. The model is forced by GFS winds, mean sea level pressure, and sea ice. The unstructured grid used by Global ESTOFS consists of 8,452,486 nodes and 16,226,163 triangular elements. Coastal resolution is up to 80 m for Hawaii and the U.S. West Coast; up to 90-120 m for the Pacific Islands including Guam, American Samoa, Marianas, Wake Island, Marshall Islands, and Palau; and up to 120 m for the U.S. East Coast, Puerto Rico, Micronesia, and Alaska. The flood plain extends overland to approximately 6 m elevation ASL for the U.S. East Coast, and up to 20 m elevation ASL for the Pacific Islands. Global ESTOFS a) reduces bias and errors due to the removal of the open ocean boundaries that were included in previous ESTOFS regional domains (ESTOFS-Atlantic, -Pacific, -Micronesia); b) includes internal tide-induced dissipation in the deep ocean; c) includes sea ice effect on wind drag, and d) incorporates a bias correction using 2-day average water level observations from CO-OPS tide stations that are interpolated spatially across the Global ESTOFS mesh.

Global ESTOFS water level forecast guidance outpu...

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NOAA Global Hydro Estimator (GHE)

agriculturemeteorologicalsustainabilitywaterweather

Global Hydro-Estimator provides a global mosaic imagery of rainfall estimates from multi-geostationary satellites, which currently includes GOES-16, GOES-15, Meteosat-8, Meteosat-11 and Himawari-8. The GHE products include: Instantaneous rain rate, 1 hour, 3 hour, 6 hour, 24 hour and also multi-day rainfall accumulation.

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NOAA Global Mosaic of Geostationary Satellite Imagery (GMGSI)

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NOAA/NESDIS Global Mosaic of Geostationary Satellite Imagery (GMGSI) visible (VIS), shortwave infrared (SIR), longwave infrared (LIR) imagery, and water vaport imagery (WV) are composited from data from several geostationary satellites orbiting the globe, including the GOES-East and GOES-West Satellites operated by U.S. NOAA/NESDIS, the Meteosat-11 and Meteosat-8 satellites from theMeteosat Second Generation (MSG) series of satellites operated by European Organization for the Exploitation of Meteorological Satellites (EUMETSAT), and the Himawari-8 satellite operated by the Japan Meteorological...

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NOAA National Bathymetric Source Data

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The National Bathymetric Source (NBS) project creates and maintains high-resolution bathymetry composed of the best available data. This project enables the creation of next-generation nautical charts while also providing support for modeling, industry, science, regulation, and public curiosity. Primary sources of bathymetry include NOAA and U.S. Army Corps of Engineers hydrographic surveys and topographic bathymetric (topo-bathy) lidar (light detection and ranging) data. Data submitted through the NOAA Office of Coast Survey’s external source data process are also included, with gaps...

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NOAA National Blend of Models (NBM)

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The National Blend of Models (NBM) is a nationally consistent and skillful suite of calibrated forecast guidance based on a blend of both NWS and non-NWS numerical weather prediction model data and post-processed model guidance. The goal of the NBM is to create a highly accurate, skillful and consistent starting point for the gridded forecast.

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NOAA National Water Model Short-Range Forecast

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The National Water Model (NWM) is a water resources model that simulates and forecasts water budget variables, including snowpack, evapotranspiration, soil moisture and streamflow, over the entire continental United States (CONUS). The model, launched in August 2016, is designed to improve the ability of NOAA to meet the needs of its stakeholders (forecasters, emergency managers, reservoir operators, first responders, recreationists, farmers, barge operators, and ecosystem and floodplain managers) by providing expanded accuracy, detail, and frequency of water information. It is operated by NOA...

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NOAA North American Mesoscale Forecast System (NAM)

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The North American Mesoscale Forecast System (NAM) is one of the National Centers For Environmental Prediction’s (NCEP) major models for producing weather forecasts. NAM generates multiple grids (or domains) of weather forecasts over the North American continent at various horizontal resolutions. Each grid contains data for dozens of weather parameters, including temperature, precipitation, lightning, and turbulent kinetic energy. NAM uses additional numerical weather models to generate high-resolution forecasts over fixed regions, and occasionally to follow significant weather events like hur...

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NOAA Oceanic Climate Data Records

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NOAA's Climate Data Records (CDRs) are robust, sustainable, and scientifically sound climate records that provide trustworthy information on how, where, and to what extent the land, oceans, atmosphere and ice sheets are changing. These datasets are thoroughly vetted time series measurements with the longevity, consistency, and continuity to assess and measure climate variability and change. NOAA CDRs are vetted using standards established by the National Research Council (NRC).

Climate Data Records are created by merging data from surface, atmosphere, and space-based systems across decades. NOAA’s Climate Data Records provides authoritative and traceable long-term climate records. NOAA developed CDRs by applying modern data analysis methods to historical global satellite data. This process can clarify the underlying climate trends within the data and allows researchers and other users to identify economic and scientific value in these records. NCEI maintains and extends CDRs by applying the same methods to present-day and future satellite measurements.

Oceanic Climate Data Records are measurements of oceans and seas both surface and subsurface as well as frozen st
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NOAA Rapid Refresh (RAP)

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The Rapid Refresh (RAP) is a NOAA/NCEP operational weather prediction system comprised primarily of a numerical forecast model and analysis/assimilation system to initialize that model. It covers North America and is run with a horizontal resolution of 13 km and 50 vertical layers. The RAP was developed to serve users needing frequently updated short-range weather forecasts, including those in the US aviation community and US severe weather forecasting community. The model is run for every hour of the day; it is integrated to 51 hours for the 03/09/15/21 UTC cycles and to 21 hours for every ot...

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NOAA Real-Time Mesoscale Analysis (RTMA)

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The Real-Time Mesoscale Analysis (RTMA) is a NOAA National Centers For Environmental Prediction (NCEP) high-spatial and temporal resolution analysis/assimilation system for near-surf ace weather conditions. Its main component is the NCEP/EMC Gridpoint Statistical Interpolation (GSI) system applied in two-dimensional variational mode to assimilate conventional and satellite-derived observations.

The RTMA was developed to support NDFD operations and provide field forecasters with high quality analyses for nowcasting, situational awareness, and forecast verification purposes. The system produces
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NOAA Severe Weather Data Inventory (SWDI)

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The Storm Events Database is an integrated database of severe weather events across the United States from 1950 to this year, with information about a storm event's location, azimuth, distance, impact, and severity, including the cost of damages to property and crops. It contains data documenting: The occurrence of storms and other significant weather phenomena having sufficient intensity to cause loss of life, injuries, significant property damage, and/or disruption to commerce. Rare, unusual, weather phenomena that generate media attention, such as snow flurries in South Florida or the S...

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NOAA Space Weather Forecast and Observation Data

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Space weather forecast and observation data is collected and disseminated by NOAA’s Space Weather Prediction Center (SWPC) in Boulder, CO. SWPC produces forecasts for multiple space weather phenomenon types and the resulting impacts to Earth and human activities. A variety of products are available that provide these forecast expectations, and their respective measurements, in formats that range from detailed technical forecast discussions to NOAA Scale values to simple bulletins that give information in laymen's terms. Forecasting is the prediction of future events, based on analysis and...

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NOAA Terrestrial Climate Data Records

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NOAA's Climate Data Records (CDRs) are robust, sustainable, and scientifically sound climate records that provide trustworthy information on how, where, and to what extent the land, oceans, atmosphere and ice sheets are changing. These datasets are thoroughly vetted time series measurements with the longevity, consistency, and continuity to assess and measure climate variability and change. NOAA CDRs are vetted using standards established by the National Research Council (NRC).

Climate Data Records are created by merging data from surface, atmosphere, and space-based systems across decades. NOAA’s Climate Data Records provides authoritative and traceable long-term climate records. NOAA developed CDRs by applying modern data analysis methods to historical global satellite data. This process can clarify the underlying climate trends within the data and allows researchers and other users to identify economic and scientific value in these records. NCEI maintains and extends CDRs by applying the same methods to present-day and future satellite measurements.

Terrestrial CDRs are composed of sensor data that have been improved and quality controlled over time, together w
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NOAA U.S. Climate Gridded Dataset (NClimGrid)

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The NOAA Monthly U.S. Climate Gridded Dataset (NClimGrid) consists of four climate variables derived from the GHCN-D dataset: maximum temperature, minimum temperature, average temperature and precipitation. Each file provides monthly values in a 5x5 lat/lon grid for the Continental United States. Data is available from 1895 to the present. On an annual basis, approximately one year of "final" nClimGrid will be submitted to replace the initially supplied "preliminary" data for the same time period. Users should be sure to ascertain which level of data is required for their research.

EpiNOAA is an analysis ready dataset that consists of a daily time-series of nClimGrid measures (maximum temperature, minimum temperature, average temperature, and precipitation) at the county scale. Each file provides daily values for the Continental United States. Data are available from 1951 to the present. Daily data are updated every 3 days with a preliminary data file and replaced with the scaled (i.e., quality controlled) data file every three months. This derivative data product is an enhancement from the original daily nClimGrid dataset in that all four weather parameters are now p
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NOAA Unified Forecast System (UFS) Marine Reanalysis: 1979-2019

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The NOAA UFS Marine Reanalysis is a global sea ice ocean coupled reanalysis product produced by the marine data assimilation team of the UFS Research-to-Operation (R2O) project. Underlying forecast and data assimilation systems are based on the UFS model prototype version-6 and the Next Generation Global Ocean Data Assimilation System (NG-GODAS) release of the Joint Effort for Data assimilation Integration (JEDI) Sea Ice Ocean Coupled Assimilation (SOCA). Covering the 40 year reanalysis time period from 1979 to 2019, the data atmosphere option of the UFS coupled global atmosphere ocean sea ice (DATM-MOM6-CICE6) model was applied with two atmospheric forcing data sets: CFSR from 1979 to 1999 and GEFS from 2000 to 2019. Assimilated observation data sets include extensive space-based marine observations and conventional direct measurements of in situ profile data sets.

This first UFS-marine interim reanalysis product is released to the broader weather and earth system modeling and analysis communities to obtain scientific feedback and applications for the development of the next generation operational numerical weather prediction system at the National Weather Service(NWS). The released file sets include two parts 1.) 1979 - 2019 UFS-DATM-MOM6-CICE6 model free runs and 2) 1979-2019 reanalysis cycle outputs (see descriptions embedded in each file set). Analyzed sea ice and ocean variables are ocean temperature, salinity, sea surface height, and sea ice conce
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NOAA Unified Forecast System Short-Range Weather (UFS SRW) Application

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The "Unified Forecast System (UFS)" is a community-based, coupled, comprehensive Earth Modeling System. It supports " multiple applications" with different forecast durations and spatial domains. The UFS Short-Range Weather (SRW) Application figures among these applications. It targets predictions of atmospheric behavior on a limited spatial domain and on time scales from minutes to several days. The SRW Application includes a prognostic atmospheric model, pre-processor, post-processor, and community workflow for running the system end-to-end. The "SRW Application Users's Guide" includes information on these components and provides detailed instructions on how to build and run the SRW Application. Users can access additional technical support via the "UFS Community Forum"

This data registry contains the data required to run the “out-of-the-box” SRW Application case. The SRW App requires numerous input files to run, including static datasets (fix files containing climatological information, terrain and land use data), initial condition data files, lateral boundary condition data files, and model configuration files (such as namelists). The SRW App experiment generation system also contains a set of workflow end-to-end (WE2E) tests that exercise various configurations of the system (e.g., different grids, physics suites). Data for running a subset of these WE2E tests are also included within this registry.

Users can generate forecasts for dates not included in this data registry by downloading and manually adding raw model files for the desired dates. Many of these model files are publicly available and can be accessed via links on the "Developmental Testbed Center&...

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NOAA Unified Forecast System Subseasonal to Seasonal Prototypes

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The Unified Forecast System Subseasonal to Seasonal prototypes consist of reforecast data from the UFS atmosphere-ocean coupled model experimental prototype version 5, 6, 7, and 8 produced by the Medium Range and Subseasonal to Seasonal Application team of the UFS-R2O project. The UFS prototypes are the first dataset released to the broader weather community for analysis and feedback as part of the development of the next generation operational numerical weather prediction system from NWS. The datasets includes all the major weather variables for atmosphere, land, ocean, sea ice, and ocean wav...

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NOAA Unified Forecast System Weather Model (UFS-WM) Regression Tests

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The Unified Forecast System (UFS) is a community-based, coupled, comprehensive Earth Modeling System. The ufs-weather-model (UFS-WM) is the model source of the UFS for NOAA’s operational numerical weather prediction applications. The UFS-WM Regression Test (RT) is the testing software to ensure that previously developed and tested capabilities in UFS-WM still work after code changes are integrated into the system. It is required that UFS-WM RTs are performed successfully on the required Tier-1 platforms whenever code changes are made to the UFS-WM. The results of the UFS-WM RTs are summarized in log files and these files will be committed to the UFS-WM repository along with the code changes. Currently, the UFS-WM RTs have been developed to support several applications targeted for operational implementations including the global weather forecast, subseasonal to seasonal forecasts, hurricane forecast, regional rapid refresh forecast, and ocean analysis.

At this time, there are 123 regression tests to support the UFS applications. The tests are evolving along with the development merged to the UFS-WM code repository. The regression test framework has been developed in the UFS-WM to run these tests on tier-1 supported systems. Each of the regression tests require a set of input data files and configuration files. The configuration files include namelist and model configuration files residing within the UFS-WM code repository. The input data includes initial conditions, climatology data, and fixed data sets such as orographic data and grid sp
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