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36 results for “geopotential”
Geopotential-based Multivariate MJO Index (GMM Index)
<p>This repository contains the data of the Geopotential-based Multivariate MJO Index (GMM Index).<br> </p> <p><strong>About the GMM Index</strong></p> <ul> <li>The GMM index is an RMM-like index, derived from outgoing longwave radiation (OLR), 200hPa and 850hPa zonal wind, that can be extended to the pre-satellite era where satellite-based OLR data is unavailable.</li> <li>The short record of OLR observation limits the data length of the RMM index (<a href="https://journals.ametsoc.org/view/journals/mwre/132/8/1520-0493_2004_132_1917_aarmmi_2.0.co_2.xml">Wheeler and Hendon, 2004</a>), hindering the research of long-term variability of the Madden-Julian Oscillation (MJO) in the past century. And, the GMM index, which can be extended to the early 20th century (and even to the 19th century), is proposed to solve the problem.</li> <li>The construction method of the GMM index is the same as the RMM index, except that: <ul> <li>the OLR input is derived from upper-tropospheric geopotential data, based on the intrinsic relationship between MJO convection and upper-level geopotential (see <a href="https://doi.org/10.1007/s00382-016-3431-x">Leung and Qian, 2017</a>);</li> <li>the OLR, 200hPa and 850hPa zonal wind input of the GMM index are bandpass-filtered anomalies.</li> </ul> </li> <li>Please refer to <a href="https://doi.org/10.1007/s00382-022-06142-2">Leung et al. (2022)</a> for more detail about the calculation procedure and the theory behind it.</li> </ul> <p> </p> <p><strong>Files</strong></p> <ul> <li>GMM index derived based on the ERA-Interim reanalysis <ul> <li>Location: <a href="https://github.com/jeremychleung/Geopotential-based-Multivariate-MJO-Index/blob/main/data/gmm_index_erai.csv">data/gmm_index_erai.csv</a></li> <li>Temporal coverage: 1979–2013</li> </ul> </li> <li>GMM index derived based on the ERA-20C reanalysis <ul> <li>Location: <a href="https://github.com/jeremychleung/Geopotential-based-Multivariate-MJO-Index/blob/main/data/gmm_index_era20c.csv">data/gmm_index_era20c.csv</a></li> <li>Temporal coverage: 1900–2010</li> </ul> </li> <li>GMM index derived based on the NOAA-20CRv3 reanalysis <ul> <li>Link: (to be uploaded)</li> <li>Temporal coverage: 1836–2015</li> </ul> </li> </ul> <p> </p> <p><strong>Citation</strong></p> <p>If you use the GMM index in a publication or for any other purposes, please cite</p> <ul> <li>Leung, J.CH., Qian, W., Zhang, P. et al. Geopotential-based Multivariate MJO Index: extending RMM-like indices to pre-satellite era. Clim Dyn (2022). <a href="https://doi.org/10.1007/s00382-022-06142-2">https://doi.org/10.1007/s00382-022-06142-2</a></li> <li>Zenodo archive: <a href="https://doi.org/10.5281/zenodo.6331379">https://doi.org/10.5281/zenodo.6331379</a></li> </ul> <p> </p> <p><strong>References</strong></p> <ul> <li>Leung, J.CH., Qian, W., Zhang, P. et al. Geopotential-based Multivariate MJO Index: extending RMM-like indices to pre-satellite era. Clim Dyn (2022). <a href="https://doi.org/10.1007/s00382-022-06142-2">https://doi.org/10.1007/s00382-022-06142-2</a></li> <li>Leung, J.CH., Qian, W. Monitoring the Madden–Julian oscillation with geopotential height. Clim Dyn 49, 1981–2006 (2017). <a href="https://doi.org/10.1007/s00382-016-3431-x">https://doi.org/10.1007/s00382-016-3431-x</a></li> <li>Wheeler, M.C., Hendon, H.H. An All-Season Real-Time Multivariate MJO Index: Development of an Index for Monitoring and Prediction. Mon Weather Rev 132:1917–1932 (2004). <a href="https://journals.ametsoc.org/view/journals/mwre/132/8/1520-0493_2004_132_1917_aarmmi_2.0.co_2.xml">https://journals.ametsoc.org/view/journals/mwre/132/8/1520-0493_2004_132_1917_aarmmi_2.0.co_2.xml</a></li> </ul> <p> </p> <p><strong>Contact</strong></p> <p>If you have any questions about the data, feel free to contact Dr. Jeremy Leung (<a href="mailto:chleung@pku.edu.cn">chleung@pku.edu.cn</a> or <a href="mailto:liangzx@gd121.cn">liangzx@gd121.cn</a>).</p>
Evaluation of Upper Tropospheric Geopotential Height Anomalies over the Tropical and Subtropical Oceans in CMIP6 Models Using GNSS Radio Occultation Observations
<p>The set-up of CESM2-CAM6 sensitivity experiments for winter season (Dec-Jan-Feb: DJF), with prognostic falling ice radiative effects on (SON) and off (NOS), is an updated two-moment stratiform cloud scheme (MG2, Gettelman & Morrison, 2015) in the CESM2 atmospheric component of CAM6. CESM2-CAM6 participated in CMIP6. Both the NOS and SON simulations were configured following the same approach as the CMIP6 "historical" run spanning from 1980 to 2014.</p> <p> </p> <p>The data are:</p> <p> </p> <p>TS: skin temperature (K)</p> <p>TAUX: zonal surface wind stress</p> <p>TAUY: meridinal surface wind stress</p> <p>DTCOND: moist condensation heating rate</p> <p>QRL: long wave heating rate</p> <p>OMEGA: vertical motion</p> <p>Z3: geopotential height</p> <p> </p>
Precipitation, low-level jet, and geopotential height data for analyzing sources of predictability in the US northern Great Plains
<p>Dec 15, 2021</p> <p> </p> <p><strong>Precipitation, low-level jet, and geopotential height data for analyzing sources of predictability in the US northern Great Plains</strong></p> <p> </p> <p>Carlos M. Carrillo and Francisco Muñoz-Arriola</p> <p> </p> <p><strong>Motivation</strong></p> <p>The data presented here was used to investigate the uskills of precipitation in the US northern Great Plains, and it can be cited as described below. The original data for producing this data is from the Climate Forecast System (CFS) retrospective reanalysis and reforecast as well as precipitation data from the Climate Prediction Center (CPC) from the National Oceanic and Atmospheric Administration (NOAA). Also, gridded data is from the North American Regional Reanalysis (NARR) from the National Centers for Environmental Prediction (NCEP).</p> <p> </p> <p><strong>License </strong></p> <p>Creative Commons CC-BY</p> <p><strong>Disclaimer</strong></p> <p>The data provided in the files is provided as is. Despite our best efforts at filtering out potential issues, some information could be erroneous.</p> <p><strong>Description of the dataset</strong></p> <p>Files are provided with the following features:</p> <p><strong>List of cases: </strong></p> <p> files.0.00.dy.txt</p> <p><strong>Low-level jet (or the GP-LLJ index)</strong></p> <p>Originally located at /home/cmc542/2019/sum-pred/eof/cfs/0.35.cases/</p> <p>Master file:<strong> LLJ_pc_corr_1D_pdf_full.m</strong></p> <p>With input data</p> <p> from CFS models,</p> <p> eof1.v850.cfs.1982-2009.dy.tar</p> <p> pc1.v850.cfs.1982-2009.dy.tar</p> <p> from NARR model,</p> <p> pc1.vwnd.narr.1982-2009.tar</p> <p><strong>The geopotential height (or CGT index): </strong></p> <p>Originally located at /home/cmc542/2019/sum-pred/eof/cfs/0.35.cases/</p> <p>Master file:<strong> Z200_mode_corr_1D_pdf_full.m</strong></p> <p>With input data</p> <p> xt-reco-z200.Full.123.z200.cfs.1982-2009.12-60.tar</p> <p> xt-reco-z200.Full.z200.narr.1982-2009.bin.tar</p> <p><strong>Precipitation at the US Great Plains:</strong></p> <p>Originally located at /home/cmc542/2019/sum-pred/clim/yrcases</p> <p>Master file: <strong>prec_corr_cfs_1D_pdf_full.m</strong></p> <p>With input data:</p> <p> prec.cfs.MW.1982-2009.tar</p> <p> prec.cpc.MW.1982-2009.tar</p> <p><strong>Correlation patterns:</strong></p> <p> Precipitation: PREC.NGP.corr.txt</p> <p> LLJ: LLJ.pcs.corr.narr.pdf.txt</p> <p> Z200: Z200.pcs.corr.narr.pdf.txt</p> <p> </p> <p><strong>Disclaimer</strong></p> <p>The data provided in the files is provided as is. Despite our best efforts at filtering out potential issues, some information could be erroneous.</p> <p><strong>Description of the dataset</strong></p> <p>Files are provided with the following features:</p> <p><strong>List of cases: </strong></p> <p> files.0.00.dy.txt</p> <p><strong>Low-level jet (or the GP-LLJ index)</strong></p> <p>Originally located at /home/cmc542/2019/sum-pred/eof/cfs/0.35.cases/</p> <p>Master file:<strong> LLJ_pc_corr_1D_pdf_full.m</strong></p> <p>With input data</p> <p> from CFS models,</p> <p><strong> </strong>eof1.v850.cfs.1982-2009.dy.tar</p> <p> pc1.v850.cfs.1982-2009.dy.tar</p> <p> from NARR model,</p> <p> pc1.vwnd.narr.1982-2009.tar</p> <p><strong>The geopotential height (or CGT index): </strong></p> <p>Originally located at /home/cmc542/2019/sum-pred/eof/cfs/0.35.cases/</p> <p>Master file:<strong> Z200_mode_corr_1D_pdf_full.m</strong></p> <p>With input data</p> <p> xt-reco-z200.Full.123.z200.cfs.1982-2009.12-60.tar</p> <p> xt-reco-z200.Full.z200.narr.1982-2009.bin.tar</p> <p><strong>Precipitation at the US Great Plains:</strong></p> <p>Originally located at /home/cmc542/2019/sum-pred/clim/yrcases</p> <p>Master file: <strong>prec_corr_cfs_1D_pdf_full.m</strong></p> <p>With input data:</p> <p> prec.cfs.MW.1982-2009.tar</p> <p> prec.cpc.MW.1982-2009.tar</p> <p><strong>Correlation patterns:</strong></p> <p> Precipitation: PREC.NGP.corr.txt</p> <p> LLJ: LLJ.pcs.corr.narr.pdf.txt</p> <p> Z200: Z200.pcs.corr.narr.pdf.txt</p> <p><strong>Credit</strong></p> <p>Carlos M. Carrillo and Francisco Muñoz-Arriola, 2021: “Sources of Subseasonal Predictability of Rainfall in the Northern Great Plains”, <em>Journal of Applied Meteorology and Climatology</em>. In review.</p> <p><strong>Grant funding</strong></p> <p>This research was funded by the U.S. Geological Survey (USGS), the U.S. Department of Agriculture (USDA), the Daugherty Water for Food Global Institute (DWFI) at the University of Nebraska-Lincoln (UNL), and the UNL’s Layman Award.</p>
Dates and 500 hPa geopotential height of P90, P95 and P99 blocking days
<p>These .mat files contain the dates of blocking days over two domains around the Antarctic Peninsula: a domain located to the west (150-90ºW, 50-70ºW) and a domain located over and to the east of the Peninsula (90-30ºW, 50-70ºW). Extreme blocking on each domain occurs when the mean 500 hPa geopotential height, averaged over the domain, is larger than the 90% percentile. Very extreme blocking occurs when the mean 500 hPa geopotential height, averaged over the domain, is larger than the 95% and 99% percentiles.</p> <p>Variables included within each file:</p> <p>- date_500mb_p90</p> <p>- date_500mb_p95</p> <p>- date_500mb_p99</p> <p>They represent the dates of extreme and very extreme blocking on each domain</p> <p>- geo_h500mb_p90</p> <p>- geo_h500mb_p95</p> <p>- geo_h500mb_p99</p> <p>They represent the corresponding 500 hPa mean geopotential height averaged over each domain during extreme (values larger than 90% percentile) and very extreme (values larger than the 95% and 99% percentiles) blocking days.</p> <p>Also included on each file are variables:</p> <p>- date_500mb_p90_sor</p> <p>- date_500mb_p95_sor</p> <p>- date_500mb_p99_sor</p> <p>which are just the dates of extreme and very extreme blocking days sorted in ascending order.</p> <p>For more details on this dataset, see </p> <p><strong>J. C. Marín</strong>, D. Bozkurt, Barrett, B., 2022: Atmospheric blocking trends and seasonality around the Antarctic Peninsula. Accepted in Journal of Climate.</p>
Daily 500 hPa geopotential height from ERA5 for the period 1940-2022 for the North Atlantic domain - 2 degree resolution
<p>Data downloaded from the Copernicus Data Store from the `reanalysis-era5-pressure-levels` dataset. Data converted from hourly to daily and regridded using xarray. </p>
North American winter season (Nov-Mar) 500 mb geopotential height classification scheme, 1979-2018
<p>This dataset comes from a study that investigated the link between atmospheric circulation patterns and deep persistent slab avalanches for three study sites in the western United States: Bridger Bowl, MT; Jackson Hole, WY; and Mammoth Mountain, CA. We used Self-organizing maps to generate 20 synoptic types that summarize the primary modes of atmospheric variability for 5,899 daily 500 mb geopotential height charts on record for the North American winter season (Nov. 1 - Mar. 31) from 1979-2017. We summarize median daily precipitation totals, daily maximum, and daily minimum temperatures observed for each synoptic type, and identify circulation patterns that occur frequently during Nov.-Dec of seasons that recorded unusually high deep persistent slab avalanche activity. We also find specific synoptic types that occur more frequently in the days immediately prior to deep slab events. This work provides practitioners with a better understanding of the processes leading to deep persistent slab avalanches, thus improving our ability to anticipate these difficult to predict events. Furthermore, we provide a conceptual model to apply this study at any site faced with similar hazard, and equipped with long-term meteorological and avalanche records.</p>
North American winter season (Nov-Mar) 500 mb geopotential height classification scheme, 1979-2018
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GRACE NON-TIDAL OCEAN GEOPOTENTIAL COEFFICIENTS GFZ RELEASE 6.0 GAB
FOR EXPERT USE ONLY. This dataset contains estimates of geopotential field derived from the Gravity Recovery and Climate Experiment (GRACE) mission measurements and a non-tidal oceanic model produced by the German Research Centre for Geosciences (GFZ). The data are in spherical harmonics averaged over approximately a month. The primary objective of the GRACE mission is to obtain accurate estimates of the mean and time-variable components of the gravity field variations. This objective is achieved by making continuous measurements of the change in distance between twin spacecraft, co-orbiting in about 500 km altitude, near circular, polar orbit, spaced approximately 200 km apart, using a microwave ranging system. In addition to these range change, the non-gravitional forces are measured on each satellite using a high accuracy electrostatic, room-temperature accelerometer. The satellite orientation and position (and timing) are precisely measured using twin star cameras and a GPS receiver, respectively. Spatial and temporal variations in the gravity field affect the orbits (or trajectories) of the twin spacecraft differently. These differences are manifested as changes in the distance between the spacecraft, as they orbit the Earth. This change in distance is reflected in the time-of-flight of microwave signals transmitted and received nearly simultaneously between the two spacecraft. The change in this time of fight is continuously measured by tracking the phase of the microwave carrier signals. The so called dual-one-way range change measurements can be reconstructed from these phase measurements. This range change (or its numerically derived derivatives), along with other mission and ancillary data, is subsequently analyzed to extract the parameters of an Earth gravity field model.
GRACE-FO Level-2 Monthly Geopotential Spherical Harmonics JPL Release 6.3 (RL06.3)
FOR EXPERT USE ONLY. This dataset contains estimates of the total month-by-month geopotential of the Earth, derived from the Gravity Recovery and Climate Experiment Follow-On (GRACE-FO) mission measurements, produced by the NASA Jet Propulsion Laboratory (JPL). The data are provided as spherical harmonic coefficients, averaged over approximately a month, and available from 2018 onward. These coefficients are derived from the Microwave Instrument (MWI) measured intersatellite range changes between the twin spacecraft of the GRACE-FO (Gravity Recovery and Climate Experiment Follow-On) mission. The GRACE-FO mission, a joint partnership between NASA and the German Research Centre for Geosciences (GFZ), launched on 22 May 2018. It uses twin satellites to accurately map variations in the Earth's gravity field and surface mass distribution. It is designed as a successor to the Gravity Recovery and Climate Experiment (GRACE) mission. <br><br>This GRACE-FO RL06.3 data is an updated version of the GRACE-FO RL06.1 Level-2 data products. RL06.3 differs from RL06.1 only in the Level-1B accelerometer transplant data that is used for the GF2 satellite: Level-2 RL06.3 uses ACH1B RL04 that is contained within the ACX2 Level-1 bundle, which replaces ACH1B RL04 contained within the ACX Level-1 bundle that was used for Level-2 RL06.1 (note: ACX2-L1B is only applicable for 01/2023 onwards in wide-pointing operational mode; from 6/2018 through 12/2022, RL06.1 and RL06.3 GRACE-FO data are identical and based on ACX; ACX2 is not available for 03/2023-06/2023 as the satellites were not in wide-pointing mode during that period). All GRACE-FO RL06.3 Level-2 products are fully compatible with the GRACE RL06 level-2 fields. Refer to the mission page for more information.
GRACE FIELD GEOPOTENTIAL COEFFICIENTS GFZ RELEASE 6.0
FOR EXPERT USE ONLY. This dataset contains estimates of static field geopotential of the Earth, derived from the Gravity Recovery and Climate Experiment (GRACE) mission measurements, produced by the German Research Centre for Geosciences (GFZ). The data are in spherical harmonics averaged over approximately a month. The primary objective of the GRACE mission is to obtain accurate estimates of the mean and time-variable components of the gravity field variations. This objective is achieved by making continuous measurements of the change in distance between twin spacecraft, co-orbiting in about 500 km altitude, near circular, polar orbit, spaced approximately 200 km apart, using a microwave ranging system. In addition to these range change, the non-gravitional forces are measured on each satellite using a high accuracy electrostatic, room-temperature accelerometer. The satellite orientation and position (and timing) are precisely measured using twin star cameras and a GPS receiver, respectively. Spatial and temporal variations in the gravity field affect the orbits (or trajectories) of the twin spacecraft differently. These differences are manifested as changes in the distance between the spacecraft, as they orbit the Earth. This change in distance is reflected in the time-of-flight of microwave signals transmitted and received nearly simultaneously between the two spacecraft. The change in this time of fight is continuously measured by tracking the phase of the microwave carrier signals. The so called dual-one-way range change measurements can be reconstructed from these phase measurements. This range change (or its numerically derived derivatives), along with other mission and ancillary data, is subsequently analyzed to extract the parameters of an Earth gravity field model.
GRACE NON-TIDAL ATMOSPHERE AND OCEAN GEOPOTENTIAL COEFFICIENTS CSR RELEASE 6.0 GAC
FOR EXPERT USE ONLY. This dataset contains estimates of geopotential field derived from the Gravity Recovery and Climate Experiment (GRACE) mission measurements and a non-tidal oceanic and atmospheric model produced by the Center for Space Research (CSR) at University of Texas at Austin. The data are in spherical harmonics averaged over approximately a month. The primary objective of the GRACE mission is to obtain accurate estimates of the mean and time-variable components of the gravity field variations. This objective is achieved by making continuous measurements of the change in distance between twin spacecraft, co-orbiting in about 500 km altitude, near circular, polar orbit, spaced approximately 200 km apart, using a microwave ranging system. In addition to these range change, the non-gravitional forces are measured on each satellite using a high accuracy electrostatic, room-temperature accelerometer. The satellite orientation and position (and timing) are precisely measured using twin star cameras and a GPS receiver, respectively. Spatial and temporal variations in the gravity field affect the orbits (or trajectories) of the twin spacecraft differently. These differences are manifested as changes in the distance between the spacecraft, as they orbit the Earth. This change in distance is reflected in the time-of-flight of microwave signals transmitted and received nearly simultaneously between the two spacecraft. The change in this time of fight is continuously measured by tracking the phase of the microwave carrier signals. The so called dual-one-way range change measurements can be reconstructed from these phase measurements. This range change (or its numerically derived derivatives), along with other mission and ancillary data, is subsequently analyzed to extract the parameters of an Earth gravity field model.
MLS/Aura Level 3 Daily Binned Geopotential Height (GPH) on Zonal and Similar Grids V005 (ML3DZGPH) at GES DISC
ML3DZGPH is the EOS Aura Microwave Limb Sounder (MLS) daily binned on zonal and assorted vertical grids product for geopotential height (GPH) derived from radiances measured by the 118 and 240 GHz radiometers. The data version is 5.1. Data coverage is from August 2, 2005 to current. Spatial coverage is near-global (-82 to +82 degrees latitude) at 4 degree latitude zonal increments. The recommended useful vertical range is between 261 and 0.001 hPa, and the vertical resolution varies between ~3.6 and 6 km. Users of the ML3DZGPH data product should read chapter 4 and section 3.8 of the EOS MLS Level 2 Version 5 Quality Document for more information.The data files contain one year of data and are archived in the netCDF4 format, which is also compatible with HDF5 readers and tools. Each file contains four group objects: lat vs pressure zonal mean, lat vs "potential temperature" zonal mean, "equivalent latitude" vs "potential temperature" zonal mean, and vortex average vs "potential temperature". Each group has a set of data (average, min, max, std dev, rms) and geolocation fields, grid attributes, and metadata.
MLS/Aura Level 3 Daily Binned Geopotential Height (GPH) on Assorted Grids V005 (ML3DBGPH) at GES DISC
ML3DBGPH is the EOS Aura Microwave Limb Sounder (MLS) daily binned on various vertical grids product for geopotential height (GPH) derived from radiances measured by the 118 and 240 GHz radiometers. The data version is 5.1. Data coverage is from August 2, 2005 to current. Spatial coverage is near-global (-82 to +82 degrees latitude), with a spatial resolution of 4 degrees latitude by 5 degrees longitude. The recommended useful vertical range is between 261 and 0.001 hPa, and the vertical resolution varies between ~3.6 and 6 km. Users of the ML3DBGPH data product should read chapter 4 and section 3.8 of the EOS MLS Level 2 Version 5 Quality Document for more information.The data files are archived in the netCDF4 format, which is also compatible with HDF5 readers and tools. Each file contains two grid objects (profile and column data), each with a set of data and geolocation fields, grid attributes, and metadata.
GRACE OCEAN BOTTOM GEOPOTENTIAL COEFFICIENTS CSR RELEASE 6.0 GAD
FOR EXPERT USE ONLY. This dataset contains estimates of ocean bottom pressure derived from the Gravity Recovery and Climate Experiment (GRACE) mission measurements, produced by the Center for Space Research (CSR) at University of Texas at Austin. The data are in spherical harmonics averaged over approximately a month. The primary objective of the GRACE mission is to obtain accurate estimates of the mean and time-variable components of the gravity field variations. This objective is achieved by making continuous measurements of the change in distance between twin spacecraft, co-orbiting in about 500 km altitude, near circular, polar orbit, spaced approximately 200 km apart, using a microwave ranging system. In addition to these range change, the non-gravitional forces are measured on each satellite using a high accuracy electrostatic, room-temperature accelerometer. The satellite orientation and position (and timing) are precisely measured using twin star cameras and a GPS receiver, respectively. Spatial and temporal variations in the gravity field affect the orbits (or trajectories) of the twin spacecraft differently. These differences are manifested as changes in the distance between the spacecraft, as they orbit the Earth. This change in distance is reflected in the time-of-flight of microwave signals transmitted and received nearly simultaneously between the two spacecraft. The change in this time of fight is continuously measured by tracking the phase of the microwave carrier signals. The so called dual-one-way range change measurements can be reconstructed from these phase measurements. This range change (or its numerically derived derivatives), along with other mission and ancillary data, is subsequently analyzed to extract the parameters of an Earth gravity field model.
GRACE-FO Level-2 Monthly Geopotential Spherical Harmonics GFZ Release 6.3 (RL06.3)
FOR EXPERT USE ONLY. This dataset contains estimates of the total month-by-month geopotential of the Earth, derived from the Gravity Recovery and Climate Experiment Follow-On (GRACE-FO) mission measurements, produced by the German Research Centre for Geosciences (GFZ). The data are provided as spherical harmonic coefficients, averaged over approximately a month. These coefficients are derived from the Microwave Instrument (MWI) measured intersatellite range changes between the twin spacecraft of the GRACE-FO mission. Refer to the mission page for more information. <br><br>This GRACE-FO RL06.3 data is an updated version of the GRACE-FO RL06.1 Level-2 data products. RL06.3 differs from RL06.1 only in the Level-1B accelerometer transplant data that is used for the GF2 satellite: Level-2 RL06.3 uses ACH1B RL04 that is contained within the ACX2 Level-1 bundle, which replaces ACH1B RL04 contained within the ACX Level-1 bundle that was used for Level-2 RL06.1 (note: ACX2-L1B is only applicable for 01/2023 onwards in wide-deadband operational mode; from 6/2018 through 12/2022, RL06.1 and RL06.3 GRACE-FO data are identical). All GRACE-FO RL06.3 Level-2 products are fully compatible with the GRACE RL06 level-2 fields. Refer to the mission page for more information.
GRACE FIELD GEOPOTENTIAL COEFFICIENTS JPL RELEASE 6.0
FOR EXPERT USE ONLY. This dataset contains estimates of static field geopotential of the Earth, derived from the Gravity Recovery and Climate Experiment (GRACE) mission measurements, produced by the NASA Jet Propulsion Laboratory (JPL). The data are in spherical harmonics averaged over approximately a month. The primary objective of the GRACE mission is to obtain accurate estimates of the mean and time-variable components of the gravity field variations. This objective is achieved by making continuous measurements of the change in distance between twin spacecraft, co-orbiting in about 500 km altitude, near circular, polar orbit, spaced approximately 200 km apart, using a microwave ranging system. In addition to these range change, the non-gravitional forces are measured on each satellite using a high accuracy electrostatic, room-temperature accelerometer. The satellite orientation and position (and timing) are precisely measured using twin star cameras and a GPS receiver, respectively. Spatial and temporal variations in the gravity field affect the orbits (or trajectories) of the twin spacecraft differently. These differences are manifested as changes in the distance between the spacecraft, as they orbit the Earth. This change in distance is reflected in the time-of-flight of microwave signals transmitted and received nearly simultaneously between the two spacecraft. The change in this time of fight is continuously measured by tracking the phase of the microwave carrier signals. The so called dual-one-way range change measurements can be reconstructed from these phase measurements. This range change (or its numerically derived derivatives), along with other mission and ancillary data, is subsequently analyzed to extract the parameters of an Earth gravity field model.
GRACE FIELD GEOPOTENTIAL COEFFICIENTS CSR RELEASE 6.0
FOR EXPERT USE ONLY. This dataset contains estimates of static field geopotential of the Earth, derived from the Gravity Recovery and Climate Experiment (GRACE) mission measurements, produced by the Center for Space Research (CSR) at University of Texas at Austin. The data are in spherical harmonics averaged over approximately a month. The primary objective of the GRACE mission is to obtain accurate estimates of the mean and time-variable components of the gravity field variations. This objective is achieved by making continuous measurements of the change in distance between twin spacecraft, co-orbiting in about 500 km altitude, near circular, polar orbit, spaced approximately 200 km apart, using a microwave ranging system. In addition to these range change, the non-gravitional forces are measured on each satellite using a high accuracy electrostatic, room-temperature accelerometer. The satellite orientation and position (and timing) are precisely measured using twin star cameras and a GPS receiver, respectively. Spatial and temporal variations in the gravity field affect the orbits (or trajectories) of the twin spacecraft differently. These differences are manifested as changes in the distance between the spacecraft, as they orbit the Earth. This change in distance is reflected in the time-of-flight of microwave signals transmitted and received nearly simultaneously between the two spacecraft. The change in this time of fight is continuously measured by tracking the phase of the microwave carrier signals. The so called dual-one-way range change measurements can be reconstructed from these phase measurements. This range change (or its numerically derived derivatives), along with other mission and ancillary data, is subsequently analyzed to extract the parameters of an Earth gravity field model.
GRACE OCEAN BOTTOM GEOPOTENTIAL COEFFICIENTS JPL RELEASE 6.0 GAD
FOR EXPERT USE ONLY. This dataset contains estimates of ocean bottom pressure derived from the Gravity Recovery and Climate Experiment (GRACE) mission measurements, produced by the NASA Jet Propulsion Laboratory (JPL). The data are in spherical harmonics averaged over approximately a month. The primary objective of the GRACE mission is to obtain accurate estimates of the mean and time-variable components of the gravity field variations. This objective is achieved by making continuous measurements of the change in distance between twin spacecraft, co-orbiting in about 500 km altitude, near circular, polar orbit, spaced approximately 200 km apart, using a microwave ranging system. In addition to these range change, the non-gravitional forces are measured on each satellite using a high accuracy electrostatic, room-temperature accelerometer. The satellite orientation and position (and timing) are precisely measured using twin star cameras and a GPS receiver, respectively. Spatial and temporal variations in the gravity field affect the orbits (or trajectories) of the twin spacecraft differently. These differences are manifested as changes in the distance between the spacecraft, as they orbit the Earth. This change in distance is reflected in the time-of-flight of microwave signals transmitted and received nearly simultaneously between the two spacecraft. The change in this time of fight is continuously measured by tracking the phase of the microwave carrier signals. The so called dual-one-way range change measurements can be reconstructed from these phase measurements. This range change (or its numerically derived derivatives), along with other mission and ancillary data, is subsequently analyzed to extract the parameters of an Earth gravity field model.
HIRDLS/Aura Level 3 Geopotential Height 1deg Lat Zonal Fourier Coefficients V007 (H3ZFCGPH) at GES DISC
The "HIRDLS/Aura Level 3 Geopotential Height Zonal Fourier Coefficients" version 7 data product (H3ZFCGPH) contains the entire mission (~3 years) of HIRDLS data expressed as zonal Fourier coefficients in 1 degree latitude bands from -64 to 80 degrees at 121 pressure levels. The coefficients are computed from the HIRDLS Level 2 profiles with a Kalman filter approach using both forward and backward passes in time. Expressed as the mean and up to 7 sine and cosine coefficients (4 waves for ascending and descending, 7 waves for combined), these coefficients may be used to compute values at any longitude. The data are provided on a pressure grid with 24 levels per decade, corresponding to about 1 km vertical resolution. The useful vertical range of the data is 1000 to 0.01 hPa. The precision values are given by the root-mean square of the differences between the estimated fields and the input data.The data are stored in the version 5 Hierarchical Data Format for the Earth Observing System (HDF-EOS5), which is an extension of the HDF5 format. Each file contains a zonal object with data for the entire mission with separate data fields for ascending (daytime), descending (nighttime), and combined orbit node.
GRACE NON-TIDAL ATMOSPHERE GEOPOTENTIAL COEFFICIENTS GFZ RELEASE 6.0 GAA
FOR EXPERT USE ONLY. This dataset contains estimates of geopotential field derived from the Gravity Recovery and Climate Experiment (GRACE) mission measurements and a non-tidal atmospheric model produced by the German Research Centre for Geosciences (GFZ). The data are in spherical harmonics averaged over approximately a month. The primary objective of the GRACE mission is to obtain accurate estimates of the mean and time-variable components of the gravity field variations. This objective is achieved by making continuous measurements of the change in distance between twin spacecraft, co-orbiting in about 500 km altitude, near circular, polar orbit, spaced approximately 200 km apart, using a microwave ranging system. In addition to these range change, the non-gravitional forces are measured on each satellite using a high accuracy electrostatic, room-temperature accelerometer. The satellite orientation and position (and timing) are precisely measured using twin star cameras and a GPS receiver, respectively. Spatial and temporal variations in the gravity field affect the orbits (or trajectories) of the twin spacecraft differently. These differences are manifested as changes in the distance between the spacecraft, as they orbit the Earth. This change in distance is reflected in the time-of-flight of microwave signals transmitted and received nearly simultaneously between the two spacecraft. The change in this time of fight is continuously measured by tracking the phase of the microwave carrier signals. The so called dual-one-way range change measurements can be reconstructed from these phase measurements. This range change (or its numerically derived derivatives), along with other mission and ancillary data, is subsequently analyzed to extract the parameters of an Earth gravity field model.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.