GHRSST Level 4 MUR Global Foundation Sea Surface Temperature Analysis (v4.1)

(MUR-JPL-L4-GLOB-v4.1)

Citation metrics available for years (2014-2021)

Publications citing GHRSST Level 4 MUR Global Foundation Sea Surface Temperature Analysis (v4.1)

Citation metrics available for years (2014-2021)

Year	Citation
2015	ANALYSIS OF OZONE PRODUCTION AND ITS SENSITIVITY IN HOUSTON USING THE DATA COLLECTED DURING DISCOVER-AQ
2015	Northward migration of Cape São Tomé rings, Brazil, Continental Shelf Research,https://doi.org/10.1016/j.csr.2015.06.010
2015	Observations of meandering and upwelling events in the AgulhasCurrent at 34° s
2017	Shelf-edge exchange in a numerical model of the Shetland shelf, PhD Thesis,http://hdl.handle.net/10044/1/52909
2017	A multi-scale high-resolution analysis of global sea surface temperature, Remote Sensing of,https://doi.org/10.1016/j.rse.2017.07.029
2017	GHRSST Level 4 MUR Global Foundation Sea Surface Temperature Analysis (v4.1). Ver. 4.1. PO.DAAC, CA,USA. Available at http://dx.doi.org/10.5067/GHGMR-4FJ04. (Accessed 21 September 2016) High-resolution modeling of thermal thresholds and multiple environmental influences on coral bleaching for regional and local reef managements, bioRxiv,https://doi.org/10.1101/211854
2017	JPL MUR MEaSUREs Project(2015).GHRSST Level 4 MUR Global Foundation Sea Surface Temperature Analysis (v4.1)In:CA, USA: PO.DAAC, DOI:https://doi.org/10.5067/GHGMR-4FJ04Ver. 4.1. Collaborations and Partnerships in NASA's Earth Science Data Systems, Data Science Journal,https://doi.org/10.5334/dsj-2017-051
2017	JPL MUR MEaSUREs Project. GHRSST Level 4 MUR Global Foundation Sea Surface Temperature Analysis (v4.1). Ver. 4.1. PO.DAAC, CA, USA.https://podaac.jpl.nasa.gov/dataset/MUR-JPL-L4-GLOB-v4.1. Accessed 10 Feb 2016. Remote sensing measurements of sea surface temperature as an indicator of Vibrio parahaemolyticus in oyster meat and human illnesses, Environmental,https://doi.org/10.1186/s12940-017-0301-x
2017	JPL MUR MEaSUREs Project. GHRSST Level 4 MUR Global Foundation Sea Surface Temperature Analysis (v4.1) (PO.DAAC, 2015). Reconciling the opposing effects of warming on phytoplankton biomass in 188 large lakes, Scientific reports,https://doi.org/10.1038/s41598-017-11167-3
2018	At-sea distribution and fine-scale habitat use patterns of zooplanktivorous Cassin's auklets during the chick-rearing period, Marine biology,https://doi.org/10.1007/s00227-018-3434-8
2018	At-sea distribution and foraging behaviour of two North Pacific seabirds revealed through GPS tracking, N/A,N/A
2018	36.Physical Oceanography Distributed Active Archive Center. JPL MUR MEaSUREs Project. 2015. GHRSST Level 4 MUR Global Foundation Sea Surface Temperature Analysis (v4.1). Version 4.1.; Physical Oceanography Distributed Active Archive Center: Pasadena, CA, USA, 2015. Coastal Upwelling Front Detection off Central Chile (36.5–37° S) and Spatio-Temporal Variability of Frontal Characteristics, Remote Sensing,https://doi.org/10.3390/rs10050690
2018	Movement, dive behavior, and habitat-use of common murres (Uria aalge) in the Northern California Current System under variable ocean conditions, N/A,N/A
2018	NASA, 2002. Jet Propulsion Laboratory, Physical Oceanography Distributed Active Archive Center (JPL PO.DAAC). GHRSST Level 4 MUR Global Foundation Sea Surface Temperature Analysis (v4.1) (GDS versions 1 and 2). National Oceanographic Data Center, NOAA. (Accessed 19 December 2017). Ocean circulation and frontal structure near the southern Kerguelen Plateau: the physical context for the Kerguelen Axis ecosystem study, Deep-Sea Research Part II: Topical Studies in Oceanography,https://doi.org/10.1016/j.dsr2.2018.07.013
2018	Does Sea Surface Temperature contribute to determining range limits and expansion of mangroves in Eastern South America (Brazil)?, Remote Sensing,https://doi.org/10.3390/rs10111787
2018	MEaSUREs Project, JPL MUR, 2015. GHRSST Level 4 MUR Global Foundation Sea Surface. Temperature Analysis (v4.1). Ver. 4.1. PO.DAAC, CA, USA. Temperature Analysis (v4.1). Ver. 4.1. PO.DAAC, CA, USA. Exploring the synergy between along-track altimetry and tracer fronts to reconstruct surface ocean currents, Remote Sensing of Environment,https://doi.org/10.1016/j.rse.2018.04.036
2018	JPL MUR MEaSUREs Project. 2015. GHRSST level 4 MUR global foundation sea surface temperature analysis (v4.1). (Version 4.1). PO.DAAC, CA, USA. Available at http://dx.doi.org/10.5067/GHGMR-4FJ04 (accessed 21 September 2016). High-resolution modeling of thermal thresholds and environmental influences on coral bleaching for local and regional reef management, PeerJ,https://doi.org/10.7717/peerj.4382
2018	Salinity Simulation in Florida Bay with the Regional Oceanic Modeling System (ROMS), N/A,https://doi.org/10.13140/RG.2.2.24828.23683
2018	The Impacts of Anthropogenic Global Change and Local Human Activities on Reef-Building Corals on the Belize Mesoamerican Barrier Reef System, N/A,N/A
2019	Whales in warming water: Assessing breeding habitat diversity and adaptability in Oceania's changing climate, Global Change Biology,https://doi.org/10.1111/gcb.14563
2019	Crown-of-thorns starfish impede the recovery potential of coral reefs following bleaching, Marine Biology,https://doi.org/10.1007/s00227-019-3543-z
2019	MUR MEaSUREs Project, J.P.L., 2015. GHRSST Level 4 MUR Global Foundation Sea Surface Temperature Analysis (v4.1). Ver. 4.1. PO, DAAC, CA, USA. https://doi.org/10.5067/GHGMR-4FJ04, Accessed date: 10 June 2017. Proteomic changes across a natural temperature gradient in a marine gastropod, Marine Environmental Research,https://doi.org/10.1016/j.marenvres.2019.06.002
2019	Environmental representativity in marine protected area networks over large and partly unexplored seascapes, Global ecology and Conservation,https://doi.org/10.1016/j.gecco.2019.e00545
2019	Extreme reduction in nutritional value of a key forage fish during the Pacific marine heatwave of 2014-2016, Marine Ecology Progress Series,https://doi.org/10.3354/meps12891
2019	MUR MEaSUREs Project, J.P.L., 2015. GHRSST Level 4 MUR Global Foundation Sea Surface Temperature Analysis V4, vol. 1 PO.DAAC, CA, USA Last access March/2018. https://doi.org/10.5067/GHGMR-4FJ04, Ver. 4.1. https://doi.org/10.5067/GHGMR-4FJ04, Ver. 4.1. First measurements of the ocean-atmosphere CO2 fluxes at the Cabo Frio upwelling system region, Southwestern Atlantic Ocean, Continental Shelf Research,https://doi.org/10.1016/j.csr.2019.05.008
2019	Fluctuating reproductive rates in Hawaii's humpback whales, Megaptera novaeangliae, reflect recent climate anomalies in the North Pacific, Royal Society Open Science,https://doi.org/10.1098/rsos.181463
2019	Sensitivity of the near‐shore oceanic circulation off Central Chile to coastal wind profiles characteristics, Journal of Geophysical Research: Oceans,https://doi.org/10.1029/2018JC014051
2019	Sixty years since the creation of Lake Kariba: Thermal and oxygen dynamics in the riverine and lacustrine sub-basins, PloS one,https://doi.org/10.1371/journal.pone.0224679
2019	Jet Propulsion Laboratory MUR MEaSUREs Project (2015). GHRSST level 4 MUR global foundation sea surface temperature analysis (v4.1). Ver. 4.1. PO.DAAC, CA, USA. Dataset accessed [YYYY‐MM‐DD] at https://doi.org/10.5067/GHGMR‐4FJ04. High Rates of N2 Fixation in Temperate, Western North Atlantic Coastal Waters Expand the Realm of Marine Diazotrophy, Global Biogeochemical Cycles,https://doi.org/10.1029/2018GB006130
2019	JPL MUR MEaSUREs Project. 2015. GHRSST Level 4 MUR Global Foundation Sea Surface Temperature Analysis (v4.1). Ver. 4.1. PO.DAAC, CA, USA. Dataset accessed [2018-05] at http://dx.doi.org/10.5067/GHGMR-4FJ04. Spatial and temporal visualizations of satellite-derived sea surface temperatures for Alaska fishery management areas, Pacific States E-Journal of Scientific Visualizations,https://doi.org/10.28966/PSESV.2019.003
2019	Saildrone. Saildrone Baja Field Campaign Surface and ADCP Measurements. Ver. 1.0. PO.DAAC, CA, USA, 2018. Available online: http://dx.doi.org/10.5067/SDRON-SURF0 (accessed on 19 December 2018). Using saildrones to validate satellite-derived sea surface salinity and sea surface temperature along the California/Baja Coast, Remote Sensing,https://doi.org/10.3390/rs11171964
2020	B. Beckley, R. Ray, S. Holmes, N. Zelensky, F. Lemoine, X. Yang, S. Brown, S. Desai, G. Mitchum, and J. Hausman, “Integrated multi- mission ocean altimeter data for climate research topex/poseidon, jason- 1 and ostm/jason-2 user’s handbook version 3.0, 61 pp., california institute of technology,” California Institute of Technology, ftp://podaac.jpl.nasa.gov/allData/merged alt L, vol. 2, p. 61, 2018. Super-Resolution of Sea Surface Temperature Satellite Images, Global Oceans 2020: Singapore – U.S. Gulf Coast,https://doi.org/10.1109/IEEECONF38699.2020.9389030
2020	Horizontal and vertical movements of humpback whales inform the use of critical pelagic habitats in the western South Pacific, Scientific Reports,https://doi.org/10.1038/s41598-020-61771-z
2020	JPL MUR MEaSUREs Project (2015). GHRSST Level 4 MUR Global Foundation Sea Surface Temperature Analysis (v4.1). Version 4.1, https://doi.org/10.5067/GHGMR-4FJ04. PO.DAAC, CA, USA. Variability of physicochemical and biological parameters in the Sado Estuary: integration of in situ observations and satellite data, N/A,http://hdl.handle.net/10451/45253
2020	Variational Based Estimation of Sea Surface Temperature from Split-Window Observations of INSAT-3D/3DR Imager, Remote Sensing,https://doi.org/10.3390/rs12193142
2020	9. JPL MUR MEaSUREs Project. 2015. GHRSST Level 4 MUR Global Foundation Sea Surface Temperature Analy‐ sis (v4.1). Ver. 4.1. PO.DAAC, CA, USA Available at: https://podaac.jpl.nasa.gov/dataset/MUR‐JPL‐L4‐GLOB‐ v4.1 (accessed 10.02.2020). DOI 10.5067/GHGMR‐4FJ04 Выявление температурных аномалий на западном Каспии за 2017 г. по данным дистанционного зондирования, Юг России: экология, развитие,https://doi.org/10.18470/1992‐1098‐2020‐4‐63‐74
2020	JPL MUR MEaSUREs Project. GHRSST Level 4 MUR Global Foundation Sea Surface Temperature Analysis Ver. 4.1, PO.DAAC, CA, USA, 2015. doi 10.5067/GHGMR-4FJ04. Стандартизация уловов на усилие минтая в северной части Охотского моря с учетом некоторых факторов среды, Известия ТИНРО …,https://doi.org/10.26428/1606-9919-2020-200-819-836
2020	Modelling the effects of large dams on water quality in tropical rivers, N/A,https://doi.org/10.3929/ethz-b-000476521
2020	Accuracy of empirical satellite algorithms for mapping phytoplankton diagnostic pigments in the open ocean: A supervised learning perspective, Frontiers in Marine Science,https://doi.org/10.3389/fmars.2020.00599
2020	Monitoring pearl farming lagoon temperature with global high resolution satellite-derived products: An evaluation using Raroia Atoll, French Polynesia, Marine Pollution Bulletin,https://doi.org/10.1016/j.marpolbul.2020.111576
2020	MUR MEaSUREs Project, J.P.L. (2015) GHRSST Level 4 MUR Global Foundation Sea Surface Temperature Analysis V4, vol. 1 PO.DAAC, CA, USA. Last access March 2018. Ver. 4.1. Available at: https://doi.org/10.5067/GHGMR-4FJ04. Observations of air–sea heat fluxes in the southwestern Atlantic under high‐frequency ocean and atmospheric perturbations, Quarterly Journal of the Royal Metereological Society,https://doi.org/10.1002/qj.3905
2020	Open Data, Collaborative Working Platforms, and Interdisciplinary Collaboration: Building an Early Career Scientist Community of Practice to Leverage Ocean …, Frontiers in Marine ,https://doi.org/10.3389/fmars.2020.593512
2020	JPL MUR MEaSUREs Project, 2015. GHRSST level 4 MUR global foundation sea surface temperature analysis (v4.1). Ver. 4.1. PO.DAAC, CA, USA. Available at: https://doi.org/10.5067/GHGMR-4FJ04. Phytoplankton community dynamics in a coastal bay under upwelling influence (Central Chile), Estuarine, Coastal and Shelf Science,https://doi.org/10.1016/j.ecss.2020.106968
2020	Characterizing phytoplankton biomass seasonal cycles in two NE Atlantic coastal bays, Continental Shelf Research,https://doi.org/10.1016/j.csr.2020.104200
2020	JPL MUR MEaSUREs Project (2015). GHRSST Level 4 MUR Global Foundation Sea Surface Temperature Analysis (v4.1). NASA PO.DAAC. Available online at: http://podaac.jpl.nasa.gov/dataset/MUR-JPL-L4-GLOB-v4.1 (accessed October 29, 2019). Climate extreme seeds a new domoic acid hotspot on the US west coast, Frontiers in Climate,https://doi.org/10.3389/fclim.2020.571836
2020	Remote Sensing of Phytoplankton Size Classes on the Northeast US Continental Shelf, N/A,https://digitalcommons.uri.edu/theses/1913
2020	Response of near-inertial energy to a supercritical tropical cyclone and jet in the South China Sea: modelling study, Ocean Science,https://doi.org/10.5194/os-16-1095-2020
2020	Comparison of Satellite-Derived Sea Surface Temperature and Sea Surface Salinity Gradients Using the Saildrone California/Baja and North Atlantic Gulf Stream Deployments, Remote Sensing,https://doi.org/10.3390/rs12111839
2020	JPL MUR MEaSUREs Project (2015). GHRSST Level 4 MUR Global Foundation Sea Surface Temperature Analysis (v4.1). Ver. 4.1. PO.DAAC, Caifornia. doi: 10.5067/GHGMR-4FJ04. Complementary tools for aquaculture management: remote sensing and in situ approaches for Sines, N/A,http://hdl.handle.net/10451/45301
2020	JPL Mur MEaSUREs Project (2015). JPL MUR MEaSUREs Project, GHRSST Level 4 MUR Global Foundation Sea Surface Temperature Analysis. , Pasadena, CA: PO.DAAC. Contemporary climate change hinders hybrid performance of ecologically dominant marine invertebrates, Journal of evolutionary …,https://doi.org/10.1111/jeb.13609
2020	JPL MUR MEaSUREs Project, 2015. GHRSST Level 4 MUR Global Foundation Sea Surface Temperature Analysis (v4.1). Ver. 4.1. PO.DAAC, CA, USA. Dataset accessed [2018-09-10]. http://dx.doi.org/10.5067/GHGMR-4FJ04 Sea surface temperature trends and the influence of ENSO on the southwest sea of Vietnam using remote sensing data and GIS, Vietnam Journal of Marine Sciene and Technology,https://doi.org/10.15625/1859-3097/20/2/14173
2020	Discrepancies between satellite-derived and in situ SST data in the Cape Frio Upwelling System, Southeastern Brazil (23˚ S), Remote Sensing Letters,https://doi.org/10.1080/2150704X.2020.1742941
2020	SMART drumlines at Réunion Island do not attract bull sharks Carcharhinus leucas into nearshore waters: Evidence from acoustic monitoring, Fisheries Research,https://doi.org/10.1016/j.fishres.2019.105480
2020	JPL MUR MEaSUREs Project. GHRSST Level 4 MUR global foundation sea surface temperature analysis (v4.1).PO.DAAC. https://doi.org/10.5067/GHGMR-4FJ04 (2015). Effects of intense storm events on dolphin occurrence and foraging behavior, Scientific Reports,https://doi.org/10.1038/s41598-020-76077-3
2021	Ocean front detection with glider and satellite-derived sst data in the southern california current system, Journal,10.3390/rs13245032
2021	Jpl Mur MEaSUREs Project, 2015. GHRSST level 4 MUR global foundation Sea Surface temperature analysis (v4.1). Ver. 4.1. PO.DAAC, CA, USA. Dataset accessed [2019- 03-25] at. https://doi.org/10.5067/GHGMR-4FJ04. Variability of mackerel fish catch and remotely-sensed biophysical controls in the eastern Pemba Channel, Journal,10.1016/j.ocecoaman.2021.105593
2021	JPL MUR MEaSUREs Project. GHRSST Level 4 MUR Global Foundation Sea Surface Temperature Analysis (v4.1). PO.DAAC, CA, USA; 2015 [2019/04/13]. Available from: https://podaac.jpl.nasa.gov/dataset/MUR-JPL-L4 -GLOB-v4.1 Oceanic primary production trend patterns along coast of Ecuador, Journal,10.1080/23766808.2021.1964915
2021	JPL MUR MEaSUREs Project, 2010: GHRSST level 4 MUR global foundation sea surface temperature analysis, version 2. PO.DAAC, accessed 24 January 2019, https://doi.org/10.5067/ GHGMR-4FJ01 On the hyperbolicity of the bulk air-sea heat flux functions: insights into the efficiency of air-sea moisture disequilibrium for tropical cyclone intensification, Journal,10.1175/MWR-D-20-0324.1
2021	Optimization and assessment of phytoplankton size class algorithms for ocean color data on the Northeast US continental shelf, Journal,10.1016/j.rse.2021.112729
2021	JPL MUR MEaSUREs Project: GHRSST Level 4 MUR Global Foundation Sea Surface Temperature Analysis (v4.1), Ver. 4.1. PO.DAAC, CA, USA, https://doi.org/10.5067/GHGMR-4FJ04, 2015 Performance of the Adriatic Sea and Coast (AdriSC) climate componentâ€“a COAWST V3. 3-based one-way coupled atmosphereâ€“ocean modelling suite â€¦, Journal,10.5194/gmd-14-5927-2021
2021	Effects of competitive pressure and habitat heterogeneity on niche partitioning between Arctic and boreal congeners, Journal,10.1038/s41598-021-01506-w
2021	Persistent meanders and eddies lead to quasi-steady Lagrangian transport patterns in a weak western boundary current, Journal,10.1038/s41598-020-79386-9
2021	(Acknowledgements) The Group for High Resolution Sea Surface Temperature(GHRSST) Multi-scale Ultra-high Resolution (MUR) SST data were ob-tained from the NASA EOSDIS Physical Oceanography DistributedActive Archive Center (PO.DAAC) at the Jet Propulsion Laboratory,Pasadena, CA (https://doi.org/10.5067/GHGMR-4FJ04). Phytoplankton communities in two wide-open bays in the Iberian upwelling system, Journal,10.1016/j.seares.2020.101982
2021	JPL (2015). JPL Mur Measures Project. Ghrsst Level 4 MUR Global Foundation Sea Surface Temperature Analysis. Ver. 4.1. PO.DAAC, CA, USA. Available online at: https://doi.org/10.5067/GHGMR-4FJ04. (Accessed October, 1, 2020). Environmental Factors Affecting Spatial Dinoflagellate Cyst Distribution in Surface Sediments Off Aveiro-Figueira da Foz (Atlantic Iberian Margin), Journal,10.3389/fmars.2021.699483
2021	NASA/JPL (2015) GHRSST Level 4 MUR Global Foundation Sea Surface Temperature Analysis (v4.1). https://podaac. jpl.nasa.gov/dataset/MUR-JPL-L4-GLOB-v4.1 Environmental forcing on zooplankton distribution in the coastal waters of the GalÃ¡pagos Islands: spatial and seasonal patterns in the copepod community structure, Journal,10.3354/meps13617
2021	GHRSST, 2019: The Group for High Resolution Sea Surface Temperature (GHRSST) Multiscale Ultrahigh Resolution (MUR) SST data. JPL MUR MEaSUREs Project, accessed 5 June 2019, https://podaac-opendap.jpl.nasa.gov/opendap/ allData/ghrsst/data/GDS2/L4/GLOB/JPL/MUR/v4.1/ Equatorial waves triggering extreme rainfall and floods in southwest Sulawesi, Indonesia, Journal,10.1175/MWR-D-20-0262.1
2021	Rapid Warming Events in a Small Coastal Upwelling Embayment, Dissertation,N/A
2021	JPL MUR MEaSUREs Project: GHRSST Level 4 MUR Global Foundation Sea Surface Temperature Analy- sis, Version 4.1, PO.DAAC [data set], CA, USA, at https://doi.org/10.5067/GHGMR-4FJ04 (last access: 10 Febru- ary 2020), 2015. Evaluating high-frequency radar data assimilation impact in coastal ocean operational modelling, Journal,10.5194/os-17-1157-2021
2021	Research and Development of a Supporting Information System for Optimization of Salmon Release Operations and Monitoring the Coastal Environment on the â€¦, Report,N/A
2021	Experimental assessment of vulnerability to warming in tropical shallow-water marine organisms, Journal,10.3389/fmars.2021.767628
2021	FISH larvae distribution and transport on the thermal fronts in the Midriff Archipelago region, Gulf of California, Journal,10.1016/j.csr.2021.104384
2021	JPL MUR MEaSUREs Project. (2015). GHRSST Level 4 MUR Global Foundation Sea Surface Temperature Analysis (v4.1) . Ver. 4.1. (Publication no. https://doi.org/10.5067/GHGMR-4FJ04). Retrieved 2020-01-17, from PO.DAAC, CA, USA https://doi. org/10.5067/GHGMR-4FJ04 Genotype-Environment mismatch of kelp forests under climate change, Journal,10.1111/mec.15993
2021	Available online: Https://Podaac.Jpl.Nasa.Gov/Dataset/MUR-JPL-L4-GLOB-v4.1 (accessed on 7 October 2019). Satellite sea surface temperature product comparison for the Southern African marine region, Journal,10.3390/rs13071244
2021	JPL MUR MEaSUREs Project. GHRSST Level 4 MUR Global Foundation Sea Surface Temperature Analysis. Ver. 4.1. PO.DAAC, CA, USA, 2015. Available online: https://doi.org/10.5067/GHGMR-4FJ04 (accessed on 25 October 2021) High Chlorophyll-a Areas along the Western Coast of South Sulawesi-Indonesia during the Rainy Season Revealed by Satellite Data, Journal,10.3390/rs13234833
2021	Seasonal instability of the Western Equatorial Indian Ocean, Journal,10.1029/2021JC017875
2021	JPL MUR MEaSUREs Project. 2015. GHRSST Level 4 MUR Global Foundation Sea Surface Temperature Analysis (v4.1). Ver. 4.1. PO.DAAC, CA, USA. Dataset accessed [2016-10-30] at https://doi.org/10.5067/ GHGMR-4FJ04 Hydroclimatic changes in Alaska portrayed by a high-resolution regional climate simulation, Journal,10.1007/s10584-021-02956-x
2021	Seasonal Variability of SST Fronts in the Inner Sea of ChiloÃ© and Its Adjacent Coastal Ocean, Northern Patagonia, Journal,10.3390/rs13020181
2021	Sensitivity of photosynthesis to warming in two similar species of the aquatic angiosperm Ruppia from tropical and temperate habitats, Journal,10.3390/su13169433
2021	Impacts of the Kuroshio intrusion through the luzon strait on the local precipitation anomaly, Journal,10.3390/rs13061113
2021	Surface Current Variations and Oceanic Fronts in the Southern East China Sea: Drifter Experiments, Coastal Radar Applications, and Satellite Observations, Journal,10.1029/2021JC017373
2021	JPL MUR MEaSUREs Project (2015). GHRSST Level 4 MUR Global Foundation Sea Surface Temperature Analysis (v4.1). Ver. 4.1. PO.DAAC, CA, USA. Available online at: https://doi.org/10.5067/GHGMR-4FJ04 (accessed August, 2020) Temperature and Patterns of Occurrence and Abundance of Key Copepod Taxa in the Northeast Pacific, Journal,10.3389/fmars.2021.670795
2021	JPL MUR Measures Project (2015). GHRSST Level 4 MUR Global Foundation Sea Surface Temperature Analysis.Ver. 4.1. Pasadena, CA: PO.DAAC. Temporal Variability of Thermohaline Fine-Structure Associated With the Subtropical Front Off the Southeast Coast of New Zealand in High-Frequency Short-Streamer â€¦, Journal,10.3389/fmars.2021.751385
2021	NASA/JPL (2015) GHRSST Level 4 MUR Global Foundation Sea Surface Temperature Analysis (v4.1). NASA PO. DAAC. https://podaac.jpl.nasa.gov/dataset/MUR-JPL-L4- GLOB-v4.1 Influence of land-derived stressors and environmental variability on compositional turnover and diversity of estuarine benthic communities, Journal,10.3354/meps13714
2021	PL MUR MEaSUREs Project. GHRSST Level 4 MUR Global Foundation Sea Surface Temperature Analysis (v4.1) [Internet]. PO.DAAC, CA, USA: NASA; 2015 [cited 2018 Dec 11]. http://podaac.jpl.nasa.gov/dataset/ MUR-JPL-L4-GLOB-v4.1 Influence of thermal stratification and storms on acoustic telemetry detection efficiency: a year-long test in the US Southern Mid-Atlantic Bight, Journal,10.1186/s40317-021-00233-3
2021	PL MUR MEaSUREs Project. 2010. GHRSST Level 4 G1SST Global Foundation Sea Surface Temperature Analysis. Ver. 1. PO.DAAC, CA, USA. Dataset accessed [2020-02-03] at https://doi.org/10.5067/GHGMR-4FJ04 Assessing spatial segregation of beluga whales (Delphinapterus leucas) in Western Hudson Bay estuaries, Preprint,10.1101/2021.08.05.455325
2021	JPL MUR MEaSUREs Project: GHRSST Level 4 MUR Global Foundation Sea Surface Temperature Analy- sis (v4.1), Ver. 4.1. PO.DAAC [data set], CA, USA, https://doi.org/10.5067/GHGMR-4FJ04, 2015 The COTUR project: remote sensing of offshore turbulence for wind energy application, Journal,10.5194/amt-14-6137-2021
2021	Cascading weather events amplify the coastal thermal conditions prior to the shelf transit of Hurricane Sally (2020), Journal,10.1029/2021JC017957
2021	Catastrophic loss of tropical seagrass habitats at the Cocos (Keeling) Islands due to multiple stressors, Journal,10.1016/j.marpolbul.2021.112602
2021	The South Atlantic Meridional Overturning Circulation and Mesoscale Eddies in the First GOâ€SHIP Section at 34.5Â° S, Journal,10.1029/2020JC016962
2021	Cephalopod paralarval species richness, abundance and size structure during the 2014â€“2017 anomalous warm period in the southern Gulf of California, Journal,10.1093/plankt/fbab010
2021	MUR MEaSUREs Project, J.P.L., 2015. GHRSST Level 4 MUR Global Foundation Sea Surface Temperature Analysis. PO.DAAC, CA, USA. https://doi.org/10.5067/ GHGMR-4FJ04 (v4.1). Ver. 4.1 Changes in rocky intertidal communities after the 2015 and 2017 El NiÃ±o events along the Peruvian coast, Journal,10.1016/j.ecss.2020.107142
2021	MUR MEaSUREs Project, JPL (2015). GHRSST level 4 MUR global foundation sea surface temperature analysis (v4.1). Ver. 4.1 (Vol. 1). CA, USA: PO.DAAC. Dataset accessed [2020-03-31] at https://doi.org/10.5067/GHGMR-4FJ04 Circulation over the Southâ€East Greenland Shelf and potential for liquid freshwater export: a drifter study, Journal,10.1029/2020GL091948
2021	JPL MUR MEaSUREs Project: GHRSST Level 4 MUR Global Foundation Sea Surface Temperature Analysis. Ver. 4.1. PO.DAAC, JPL NASA, https://doi.org/10.5067/GHGMR- 4FJ04, 2015 Coupled and decoupled stratocumulus-topped boundary layers: turbulence properties, Journal,10.5194/acp-21-10965-2021
2021	JPL MUR MEaSUREs Project: GHRSST Level 4 MUR Global Foundation Sea Surface Temperature Analysis. Ver. 4.1. PO.DAAC, CA, USA, http://doi.org/10.5067/GHGMR-4FJ04, 2015. Nutrients attenuate the negative effect of ocean acidification on reef coral calcification in the Arabian Sea upwelling zone (Masirah Island, Oman), Preprint,10.5194/bg-2021-213
2021	JPL MUR MEaSUREs Project 2015. GHRSST level 4 MUR global foundation sea surface temperature analysis (4.1). doi: 10.5067/GHGMR-4FJ04 Nutritional quality of giant kelp declines due to warming ocean temperatures, Journal,10.1111/oik.08619
2021	JPL MUR MEaSUREs Project, “GHRSST Level 4 MUR Global Foun- dation Sea Surface Temperature Analysis,” Ver. 4.1. PO.DAAC, CA, USA; https://doi.org/10.5067/GHGMR-4FJ04, 2015, online; accessed March, 2021 Decentralized nested Gaussian processes for multi-robot systems, Conference Paper,10.1109/ICRA48506.2021.9561566
2021	JPL MUR MEaSUREs Project, 2015. GHRSST Level 4 MUR Global Foundation Sea Surface Temperature Analysis, vol. 1. https://doi.org/10.5067/GHGMR-4FJ04. Ver. 4.1. PO. DAAC, CA, USA. Dataset accessed [2020-04-21] at. Observations of northeastward flow on a narrow shelf dominated by the Agulhas Current, Journal,10.1016/j.ecss.2021.107197
2021	Ocean and Sea Ice Retrievals From an Endâ€Toâ€End Simulation of the Copernicus Imaging Microwave Radiometer (CIMR) 1.4â€“36.5 GHz Measurements, Journal,10.1029/2021JC017610

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Version	4.1
Processing Level	4
Start/Stop Date	2002-May-31 to Present
Short Name	MUR-JPL-L4-GLOB-v4.1
Description	A Group for High Resolution Sea Surface Temperature (GHRSST) Level 4 sea surface temperature analysis produced as a retrospective dataset (four day latency) and near-real-time dataset (one day latency) at the JPL Physical Oceanography DAAC using wavelets as basis functions in an optimal interpolation approach on a global 0.01 degree grid. The version 4 Multiscale Ultrahigh Resolution (MUR) L4 analysis is based upon nighttime GHRSST L2P skin and subskin SST observations from several instruments including the NASA Advanced Microwave Scanning Radiometer-EOS (AMSR-E), the JAXA Advanced Microwave Scanning Radiometer 2 on GCOM-W1, the Moderate Resolution Imaging Spectroradiometers (MODIS) on the NASA Aqua and Terra platforms, the US Navy microwave WindSat radiometer, the Advanced Very High Resolution Radiometer (AVHRR) on several NOAA satellites, and in situ SST observations from the NOAA iQuam project. The ice concentration data are from the archives at the EUMETSAT Ocean and Sea Ice Satellite Application Facility (OSI SAF) High Latitude Processing Center and are also used for an improved SST parameterization for the high-latitudes. The dataset also contains additional variables for some granules including a SST anomaly derived from a MUR climatology and the temporal distance to the nearest IR measurement for each pixel.This dataset is funded by the NASA MEaSUREs program ( http://earthdata.nasa.gov/our-community/community-data-system-programs/measures-projects ), and created by a team led by Dr. Toshio M. Chin from JPL. It adheres to the GHRSST Data Processing Specification (GDS) version 2 format specifications. Use the file global metadata "history:" attribute to determine if a granule is near-realtime or retrospective.
DOI	10.5067/GHGMR-4FJ04
Measurement	OCEANS > OCEAN TEMPERATURE > SEA SURFACE TEMPERATURE
Platform/Sensor	Aqua Platform Name: Earth Observing System, Aqua (Aqua) Orbit Period: 98.4 minutes Inclination Angle: 98.1 degrees / MODIS SENSOR Name: Moderate-Resolution Imaging Spectroradiometer (MODIS) Swath Width: 2330.0 kilometers Description: Spacecraft angular distance from orbital plane relative to the Equator. Aqua Platform Name: Earth Observing System, Aqua (Aqua) Orbit Period: 98.4 minutes Inclination Angle: 98.1 degrees / AMSR-E SENSOR Name: Advanced Microwave Scanning Radiometer-EOS (AMSR-E) Swath Width: 1450.0 kilometers Description: Spacecraft angular distance from orbital plane relative to the Equator. CORIOLIS Platform Name: Coriolis (CORIOLIS) Orbit Period: 101.6 minutes Inclination Angle: 98.7 degrees / WINDSAT SENSOR Name: WindSat (WINDSAT) Swath Width: 1200.0 kilometers Description: Spacecraft angular distance from orbital plane relative to the Equator. Terra Platform Name: Earth Observing System, Terra (AM-1) (Terra) Orbit Period: 98.8 minutes Inclination Angle: 98.2 degrees / MODIS SENSOR Name: Moderate-Resolution Imaging Spectroradiometer (MODIS) Swath Width: 2330.0 kilometers Description: Spacecraft angular distance from orbital plane relative to the Equator. NOAA-19 Platform Name: National Oceanic & Atmospheric Administration-19 (NOAA-19) Orbit Period: 102.12 minutes Inclination Angle: 98.74 degrees / AVHRR-3 SENSOR Name: Advanced Very High Resolution Radiometer-3 (AVHRR-3) Swath Width: 2400.0 kilometers Description: Spacecraft angular distance from orbital plane relative to the Equator. GCOM-W1 Platform Name: Global Change Observation Mission 1st-Water (GCOM-W1) Orbit Period: 100.0 minutes Inclination Angle: 98.19 degrees / AMSR2 SENSOR Name: Advanced Microwave Scanning Radiometer 2 (AMSR2) Swath Width: 1450.0 kilometers Description: Spacecraft angular distance from orbital plane relative to the Equator. BUOYS Platform Name: Global Change Observation Mission 1st-Water (BUOYS) / DRIFTING BUOYS SENSOR Name: DRIFTING BUOYS (DRIFTING BUOYS) Show More
Project	Group for High Resolution Sea Surface Temperature (GHRSST)
Data Provider	Publisher: JPL NASA Creator: JPL MUR MEaSUREs Project Release Place: Jet Propulsion Laboratory Release Date: 2015-Mar-11 Resource: https://podaac.jpl.nasa.gov/MEaSUREs-MUR
Format	netCDF-4
Keyword(s)	GHRSST, sea surface temperature, Level 4, SST, surface temperature, MUR, foundation SST, SST anomaly, anomaly

Questions related to this dataset? Contact podaac@podaac.jpl.nasa.gov

Resolution Spatial Resolution: 0.01 Decimal Degrees x 0.01 Decimal Degrees Temporal Resolution: Hourly - < Daily Coverage Region: GLOBAL North Bounding Coordinate: 90 degrees South Bounding Coordinate: -90 degrees West Bounding Coordinate: -180 degrees East Bounding Coordinate: 180 degrees Time Span: 2002-May-31 to Present Granule Time Span: 2002-Jun-01 to 2023-May-31 Projection Projection Type: Cylindrical Lat-Lon Projection Detail: Geolocation information included for each pixel Ellipsoid: WGS 84

DIRECT ACCESS
HTTPS endpoint for data browse and download
https://cmr.earthdata.nasa.gov/virtual-directory/collections/C1996881146-POCLOUD
Search Granules
https://search.earthdata.nasa.gov/search/granules?p=C1996881146-POCLOUD
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us-west-2
Bucket/Object Prefix: Protected buckets contain the data files for a given collection. Protected simply means users must log in to Earthdata Login before gaining access to contents within that S3 Bucket. Please use the S3Credential endpoint to gain an Earthdata login token for use in S3 Access. Public buckets, in contrast, house metadata such as checksums, imagery, and metadata files and the like. A user can access public buckets and these types of files without logging in to Earthdata Login. Most of the time, you'll want to access the protected bucket Information
podaac-ops-cumulus-public/MUR-JPL-L4-GLOB-v4.1/
podaac-ops-cumulus-protected/MUR-JPL-L4-GLOB-v4.1/
AWS S3 Credentials
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TOOLS AND SERVICES
MUR formatted in ZARR for Amazon Web Services

GENERAL DOCUMENTATION
https://ghrsst.jpl.nasa.gov Group for High Resolution Sea Surface Temperature Information
https://earthdata.nasa.gov/esds/competitive-programs/measures/mur-sst Homepage for the NASA MEaSUREs projects
http://www.ghrsst.org GHRSST Project website
https://podaac.jpl.nasa.gov/MEaSUREs-MUR MUR Project homepage
PUBLICATIONS
http://journals.ametsoc.org/doi/abs/10.1175/1520-0426%281998%29015%3C0741:BSHWSS%3E2.0.CO;2 Chin T.M., Milliff R.F., Large W.G. (1998). Basin-scale, high-wavenumber sea surface wind fields from a multiresolution analysis of scatterometer data. Journal of Atmospheric and Oceanic Technology, 15: 741-763
https://doi.org/10.1016/j.rse.2017.07.029 Chin, Toshio Michael, Jorge Vazquez-Cuervo, and Edward M. Armstrong. A multi-scale high-resolution analysis of global sea surface temperature. Remote sensing of environment 200 (2017): 154-169.
USER'S GUIDE
https://archive.podaac.earthdata.nasa.gov/podaac-ops-cumulus-docs/ghrsst/open/docs/GDS20r5.pdf Documentation on the GDS version 2 format specification
DATA RECIPE
https://github.com/podaac/data-readers Generic data readers
https://github.com/podaac/tutorials/blob/master/notebooks/SWOT-EA-2021/Colocate_satellite_insitu_ocean.ipynb Jupyter python notebook to co-locate MUR and MODIS L2P satellite data with Argo in-situ data for cross-validation
DATA CITATION POLICY
https://podaac.jpl.nasa.gov/CitingPODAAC Data Use and Citation Policy

Citation is critically important for dataset documentation and discovery. Please cite the data as follows, and cite the reference papers when it is appropriate.

Citation

JPL MUR MEaSUREs Project. 2015. GHRSST Level 4 MUR Global Foundation Sea Surface Temperature Analysis. Ver. 4.1. PO.DAAC, CA, USA. Dataset accessed [YYYY-MM-DD] at https://doi.org/10.5067/GHGMR-4FJ04

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Journal Reference

Chin, T.M, J. Vazquez-Cuervo, and E.M. Armstrong. 2017. A multi-scale high-resolution analysis of global sea surface temperature, Remote Sensing of Environment , 200 . https://doi.org/10.1016/j.rse.2017.07.029

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Short Name:

MUR-JPL-L4-GLOB-v4.1

Collection Concept ID:

C1996881146-POCLOUD

Spatial Coverage:

N: 90°

S: -90°

E: 180°

W: -180°

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GHRSST Level 4 MUR Global Foundation Sea Surface Temperature Analysis (v4.1)

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