diff --git a/config/default/common/config/metadata/layers/modis/Chlorophyll_a.md b/config/default/common/config/metadata/layers/modis/Chlorophyll_a.md index 11e9e3c250..d705c6d071 100644 --- a/config/default/common/config/metadata/layers/modis/Chlorophyll_a.md +++ b/config/default/common/config/metadata/layers/modis/Chlorophyll_a.md @@ -1,4 +1,4 @@ ### About Chlorophyll *a* Chlorophyll is a light harvesting pigment found in most photosynthetic organisms. In the ocean, phytoplankton all contain the chlorophyll pigment, which has a greenish color. Derived from the Greek words _phyto_ (plant) and _plankton_ (made to wander or drift), _phytoplankton_ are microscopic organisms that live in watery environments, both salty and fresh. Some phytoplankton are bacteria, some are protists, and most are single-celled plants. The concentration of chlorophyll *a* is used as an index of phytoplankton biomass. Phytoplankton fix carbon through photosynthesis, taking in dissolved carbon dioxide in the sea water and producing oxygen, enabling phytoplankton to grow. Changes in the amount of phytoplankton indicate the change in productivity of the ocean and as marine phytoplankton capture almost an equal amount of carbon as does photosynthesis by land vegetation, it provides an ocean link to global climate change modeling. The MODIS Chlorophyll *a* product is therefore a useful product for assessing the “health” of the ocean. The presence of phytoplankton indicates sufficient nutrient conditions for phytoplankton to flourish, but harmful algal blooms (HABs) can result when high concentrations of phytoplankton produced toxins build up. Known as red tides, blue-green algae or cyanobacteria, harmful algal blooms have severe impacts on human health, aquatic ecosystems and the economy. Chlorophyll features can also be used to trace oceanographic currents, atmospheric jets/streams and upwelling/downwelling/river plumes. Chlorophyll concentration is also useful for studying the Earth’s climate system as it is plays an integral role in the Global Carbon Cycle. More phytoplankton in the ocean may result in a higher capture rate of carbon dioxide into the ocean and help cool the planet. -References: [OceanColor Web - Level 1&2 Browsers](https://oceancolor.gsfc.nasa.gov/cgi/browse.pl?sen=am); [OceanColor Web - Chlorophyll a](https://oceancolor.gsfc.nasa.gov/atbd/chlor_a/); [NASA Earth Observations - Chlorophyll Concentration](https://neo.gsfc.nasa.gov/view.php?datasetId=MY1DMM_CHLORA) +References: [OceanColor Web - Level 1&2 Browsers](https://oceancolor.gsfc.nasa.gov/cgi/browse.pl?sen=am); [Earthdata Algorithm Publication Tool - Chlorophyll a](https://www.earthdata.nasa.gov/apt/documents/chlor-a/v1.0); [NASA Earth Observations - Chlorophyll Concentration](https://neo.gsfc.nasa.gov/view.php?datasetId=MY1DMM_CHLORA) diff --git a/config/default/common/config/metadata/layers/modis/aqua/MODIS_Aqua_L3_SST_MidIR_4km_Night_8Day.md b/config/default/common/config/metadata/layers/modis/aqua/MODIS_Aqua_L3_SST_MidIR_4km_Night_8Day.md index 907fc99bbf..1bcf7ac7ce 100644 --- a/config/default/common/config/metadata/layers/modis/aqua/MODIS_Aqua_L3_SST_MidIR_4km_Night_8Day.md +++ b/config/default/common/config/metadata/layers/modis/aqua/MODIS_Aqua_L3_SST_MidIR_4km_Night_8Day.md @@ -1,5 +1,5 @@ The MODIS L3 SST 4km layer shows global nighttime sea surface temperature (SST) at a depth of a few micrometers with ranges from -1.8 to 32 degree Celsius. The SST is derived with a Mid-Infrared (Short–Wave) SST Algorithm that uses MODIS bands 22 and 23 at 3.959 and 4.050 μm. This Level 3 product is derived from native 1 km Level 2 SST observations that are mapped to a global 4.63 km grid. The temporal resolution of this MODIS L3 SST is 8-Day. -References: MODIS_AQUA_L3_SST_MID-IR_8DAY_4KM_NIGHTTIME_V2019.0 [doi:10.5067/MODAM-8D4N9](https://doi.org/10.5067/MODAM-8D4N9); Details of the [algorithm](https://oceancolor.gsfc.nasa.gov/atbd/sst4/) can be found at Ocean Biology Processing Group (OBPG/OB.DAAC) website. +References: MODIS_AQUA_L3_SST_MID-IR_8DAY_4KM_NIGHTTIME_V2019.0 [doi:10.5067/MODAM-8D4N9](https://doi.org/10.5067/MODAM-8D4N9); Details of the [algorithm](https://oceancolor.gsfc.nasa.gov/resources/atbd/sst4/) can be found at Ocean Biology Processing Group (OBPG/OB.DAAC) website. P. J. Minnett et al., "Sea-surface temperature measurements from the Moderate-Resolution Imaging Spectroradiometer (MODIS) on Aqua and Terra," IGARSS 2004. 2004 IEEE International Geoscience and Remote Sensing Symposium, Anchorage, AK, 2004, pp. 4576-4579 vol.7. [doi:10.1109/IGARSS.2004.1370173](https://doi.org/10.1109/IGARSS.2004.1370173). diff --git a/config/default/common/config/metadata/layers/modis/terra/MODIS_Terra_Cloud_Water_Path_PCL.md b/config/default/common/config/metadata/layers/modis/terra/MODIS_Terra_Cloud_Water_Path_PCL.md index 1a57406153..3284205447 100644 --- a/config/default/common/config/metadata/layers/modis/terra/MODIS_Terra_Cloud_Water_Path_PCL.md +++ b/config/default/common/config/metadata/layers/modis/terra/MODIS_Terra_Cloud_Water_Path_PCL.md @@ -2,4 +2,4 @@ The MODIS Cloud Water Path (PCL) indicates the amount of water in the atmosphere The MODIS Cloud Water Path layers are available from both the Terra (MOD06) and Aqua (MYD06) satellites for daytime overpasses. The sensor/algorithm resolution is 1 km, imagery resolution is 1 km, and the temporal resolution is daily. -References: [MODIS Atmosphere - Cloud (06_L2)](https://modis-atmos.gsfc.nasa.gov/products/cloud); [NCAR|UCAR Climate Date Guide: Cloud Water Path](https://climatedataguide.ucar.edu/climate-data/liquid-water-path-overview); [GES DISC: Cloud Water Path](https://disc.gsfc.nasa.gov/information/glossary?title=Cloud%20Water%20Path) +References: [MODIS Atmosphere - Cloud (06_L2)](https://modis-atmos.gsfc.nasa.gov/products/cloud); [NCAR|UCAR Climate Date Guide: Cloud Dataset Overview](https://climatedataguide.ucar.edu/climate-data/cloud-dataset-overview); [GES DISC: Cloud Water Path](https://disc.gsfc.nasa.gov/information/glossary?title=Cloud%20Water%20Path) diff --git a/config/default/common/config/metadata/layers/multi-mission/hls/HLS_MGRS_Granule_Grid.md b/config/default/common/config/metadata/layers/multi-mission/hls/HLS_MGRS_Granule_Grid.md index cbee9224fd..16ec9520ec 100644 --- a/config/default/common/config/metadata/layers/multi-mission/hls/HLS_MGRS_Granule_Grid.md +++ b/config/default/common/config/metadata/layers/multi-mission/hls/HLS_MGRS_Granule_Grid.md @@ -4,4 +4,4 @@ The UTM system divides the Earth’s surface into 60 longitude zones, each 6° o The MGRS/HLS Grid layer is a reference layer and does not change over time. -References: [Harmonized Landsat Sentinel-2 (HLS) Product User Guide](https://lpdaac.usgs.gov/documents/1326/HLS_User_Guide_V2.pdf) +References: [Harmonized Landsat Sentinel-2 (HLS) Product User Guide](https://lpdaac.usgs.gov/documents/1698/HLS_User_Guide_V2.pdf) diff --git a/config/default/common/config/metadata/layers/multi-mission/hls/Reflectance.md b/config/default/common/config/metadata/layers/multi-mission/hls/Reflectance.md index 3010e03609..765496deb4 100644 --- a/config/default/common/config/metadata/layers/multi-mission/hls/Reflectance.md +++ b/config/default/common/config/metadata/layers/multi-mission/hls/Reflectance.md @@ -1,5 +1,5 @@ ### About HLS The Harmonized Landsat and Sentinel-2 (HLS) project provides consistent surface reflectance data from the Operational Land Imager (OLI) aboard the joint NASA/USGS Landsat 8 and 9 satellites and the Multi-Spectral Instrument (MSI) aboard the European Union’s Copernicus Sentinel-2A and Sentinel-2B satellites. The combined measurements between Landsat 8, Landsat 9, Sentinel-2A, and Sentinel-2B enable global observations of the land every 2-3 days at 30 meter (m) spatial resolution. The HLS project uses a set of algorithms to obtain seamless products from OLI and MSI that include atmospheric correction, cloud and cloud-shadow masking, spatial co-registration and common gridding, illumination and view angle normalization, and spectral bandpass adjustment. -References: [Harmonized Landsat Sentinel-2 (HLS) Product User Guide](https://lpdaac.usgs.gov/documents/1326/HLS_User_Guide_V2.pdf) +References: [Harmonized Landsat Sentinel-2 (HLS) Product User Guide](https://lpdaac.usgs.gov/documents/1698/HLS_User_Guide_V2.pdf) diff --git a/config/default/common/config/metadata/layers/viirs/Chlorophyll_a.md b/config/default/common/config/metadata/layers/viirs/Chlorophyll_a.md index aa963ca78f..14c0cf1ac8 100644 --- a/config/default/common/config/metadata/layers/viirs/Chlorophyll_a.md +++ b/config/default/common/config/metadata/layers/viirs/Chlorophyll_a.md @@ -1,4 +1,4 @@ ### About Chlorophyll *a* Chlorophyll is a light harvesting pigment found in most photosynthetic organisms. In the ocean, phytoplankton all contain the chlorophyll pigment, which has a greenish color. Derived from the Greek words _phyto_ (plant) and _plankton_ (made to wander or drift), _phytoplankton_ are microscopic organisms that live in watery environments, both salty and fresh. Some phytoplankton are bacteria, some are protists, and most are single-celled plants. The concentration of chlorophyll *a* is used as an index of phytoplankton biomass. Phytoplankton fix carbon through photosynthesis, taking in dissolved carbon dioxide in the sea water and producing oxygen, enabling phytoplankton to grow. Changes in the amount of phytoplankton indicate the change in productivity of the ocean and as marine phytoplankton capture almost an equal amount of carbon as does photosynthesis by land vegetation, it provides an ocean link to global climate change modeling. The Chlorophyll *a* product is therefore a useful product for assessing the “health” of the ocean. The presence of phytoplankton indicates sufficient nutrient conditions for phytoplankton to flourish, but harmful algal blooms (HABs) can result when high concentrations of phytoplankton produced toxins build up. Known as red tides, blue-green algae or cyanobacteria, harmful algal blooms have severe impacts on human health, aquatic ecosystems and the economy. Chlorophyll features can also be used to trace oceanographic currents, atmospheric jets/streams and upwelling/downwelling/river plumes. Chlorophyll concentration is also useful for studying the Earth’s climate system as it is plays an integral role in the Global Carbon Cycle. More phytoplankton in the ocean may result in a higher capture rate of carbon dioxide into the ocean and help cool the planet. -References: [OceanColor Web - Level 1&2 Browsers](https://oceancolor.gsfc.nasa.gov/cgi/browse.pl?sen=am); [OceanColor Web - Chlorophyll a](https://oceancolor.gsfc.nasa.gov/atbd/chlor_a/); [NASA Earth Observations - Chlorophyll Concentration](https://neo.gsfc.nasa.gov/view.php?datasetId=MY1DMM_CHLORA) +References: [OceanColor Web - Level 1&2 Browsers](https://oceancolor.gsfc.nasa.gov/cgi/browse.pl?sen=am); [Earthdata Algorithm Publication Tool - Chlorophyll a](https://www.earthdata.nasa.gov/apt/documents/chlor-a/v1.0); [NASA Earth Observations - Chlorophyll Concentration](https://neo.gsfc.nasa.gov/view.php?datasetId=MY1DMM_CHLORA) diff --git a/config/default/common/config/metadata/layers/viirs/snpp/VIIRS_Black_Marble.md b/config/default/common/config/metadata/layers/viirs/snpp/VIIRS_Black_Marble.md index 6175d0cc3a..686b00dde7 100644 --- a/config/default/common/config/metadata/layers/viirs/snpp/VIIRS_Black_Marble.md +++ b/config/default/common/config/metadata/layers/viirs/snpp/VIIRS_Black_Marble.md @@ -2,4 +2,4 @@ The Black Marble layer is a nighttime view of the Earth, showing visible light e Currently, the Black Marble imagery is available only as a single snapshot in time for 2012 and 2016. The sensor resolution is 750 m and the image resolution is 500 m. The imagery can be visualized in Worldview/Global Imagery Browse Services (GIBS). -References: [Earthdata - Nighttime Lights](https://earthdata.nasa.gov/learn/backgrounders/nighttime-lights); [NASA Earth Observatory: Night Light Maps Open Up New Applications](https://earthobservatory.nasa.gov/Features/NightLights); Lee, T., S. Miller, F. Turk, C. Schueler, R. Julian, S. Deyo, P. Dills, and S. Wang, 2006: The NPOESS VIIRS Day/Night Visible Sensor. Bull. Amer. Meteor. Soc., 87, 191–199, [doi: 10.1175/BAMS-87-2-191](https://journals.ametsoc.org/doi/abs/10.1175/BAMS-87-2-191); [The Lights of London. NASA Earth Observatory](https://earthobservatory.nasa.gov/IOTD/view.php?id=78674); [Out of the Blue and Into the Black. NASA Earth Observatory](https://earthobservatory.nasa.gov/Features/IntotheBlack/); Román, M. O. and Stokes, E. C. (2015), Holidays in lights: Tracking cultural patterns in demand for energy services. Earth's Future, 3: 182–205. [doi:10.1002/2014EF000285](https://onlinelibrary.wiley.com/doi/10.1002/2014EF000285/full) +References: [Earthdata - Nighttime Lights](https://earthdata.nasa.gov/learn/backgrounders/nighttime-lights); [NASA Earth Observatory: Night Light Maps Open Up New Applications](https://earthobservatory.nasa.gov/Features/NightLights); Lee, T., S. Miller, F. Turk, C. Schueler, R. Julian, S. Deyo, P. Dills, and S. Wang, 2006: The NPOESS VIIRS Day/Night Visible Sensor. Bull. Amer. Meteor. Soc., 87, 191–199, [doi: 10.1175/BAMS-87-2-191](https://journals.ametsoc.org/doi/abs/10.1175/BAMS-87-2-191); [The Lights of London. NASA Earth Observatory](https://earthobservatory.nasa.gov/IOTD/view.php?id=78674); [Out of the Blue and Into the Black. NASA Earth Observatory](https://earthobservatory.nasa.gov/Features/IntotheBlack/); Román, M. O. and Stokes, E. C. (2015), Holidays in lights: Tracking cultural patterns in demand for energy services. Earth's Future, 3: 182–205. [doi:10.1002/2014EF000285](https://doi.org/10.1002/2014EF000285) diff --git a/config/default/common/config/metadata/layers/viirs/snpp/VIIRS_SNPP_DayNightBand_AtSensor_M15.md b/config/default/common/config/metadata/layers/viirs/snpp/VIIRS_SNPP_DayNightBand_AtSensor_M15.md index c4dfd93359..f3162f3f7b 100644 --- a/config/default/common/config/metadata/layers/viirs/snpp/VIIRS_SNPP_DayNightBand_AtSensor_M15.md +++ b/config/default/common/config/metadata/layers/viirs/snpp/VIIRS_SNPP_DayNightBand_AtSensor_M15.md @@ -6,6 +6,6 @@ References: VNP46A1 [doi:10.5067/VIIRS/VNP46A1.001](https://doi.org/10.5067/VIIR Román, M. O., Z. Wang, Q. Sun, V. Kalb, S. D. Miller, A. Molthan, L. Schultz, J. Bell, E. C. Stokes, B. Pandey, K. C. Seto, D. Hall, T. Oda, R. E. Wolfe, G. Lin, N. Golpayegani, S. Devadiga, C. Davidson, S. Sarkar, C. Praderas, J. Schmaltz, R. Boller, J. Stevens, O. M. Ramos Gonzalez, E. Padilla, J. Alonso, Y. Detrés, R. Armstrong, I. Miranda, Y. Conte, N. Marrero, K. MacManus, T. Esch, and E. J. Masuoka. 2018. "NASA’s Black Marble nighttime lights product suite." Remote Sensing of Environment 210 113-143 [doi:10.1016/j.rse.2018.03.017](https://doi.org/10.1016/j.rse.2018.03.017) -Lee, T., S. Miller, F. Turk, C. Schueler, R. Julian, S. Deyo, P. Dills, and S. Wang, 2006: The NPOESS VIIRS Day/Night Visible Sensor. Bull. Amer. Meteor. Soc., 87, 191–199, [doi: 10.1175/BAMS-87-2-191](https://journals.ametsoc.org/doi/abs/10.1175/BAMS-87-2-191) +Lee, T., S. Miller, F. Turk, C. Schueler, R. Julian, S. Deyo, P. Dills, and S. Wang, 2006: The NPOESS VIIRS Day/Night Visible Sensor. Bull. Amer. Meteor. Soc., 87, 191–199, [doi:10.1175/BAMS-87-2-191](https://doi.org/10.1175/BAMS-87-2-191) -Román, M. O. and Stokes, E. C. (2015), Holidays in lights: Tracking cultural patterns in demand for energy services. Earth's Future, 3: 182–205. [doi:10.1002/2014EF000285](https://onlinelibrary.wiley.com/doi/10.1002/2014EF000285/full) +Román, M. O. and Stokes, E. C. (2015), Holidays in lights: Tracking cultural patterns in demand for energy services. Earth's Future, 3: 182–205. [doi:10.1002/2014EF000285](https://doi.org/10.1002/2014EF000285) diff --git a/config/default/common/config/metadata/layers/viirs/snpp/VIIRS_SNPP_DayNightBand_At_Sensor_Radiance.md b/config/default/common/config/metadata/layers/viirs/snpp/VIIRS_SNPP_DayNightBand_At_Sensor_Radiance.md index 265f4742d3..f3f6a5ba14 100644 --- a/config/default/common/config/metadata/layers/viirs/snpp/VIIRS_SNPP_DayNightBand_At_Sensor_Radiance.md +++ b/config/default/common/config/metadata/layers/viirs/snpp/VIIRS_SNPP_DayNightBand_At_Sensor_Radiance.md @@ -11,6 +11,6 @@ References: VNP46A1 [doi:10.5067/VIIRS/VNP46A1.001](https://doi.org/10.5067/VIIR Román, M. O., Z. Wang, Q. Sun, V. Kalb, S. D. Miller, A. Molthan, L. Schultz, J. Bell, E. C. Stokes, B. Pandey, K. C. Seto, D. Hall, T. Oda, R. E. Wolfe, G. Lin, N. Golpayegani, S. Devadiga, C. Davidson, S. Sarkar, C. Praderas, J. Schmaltz, R. Boller, J. Stevens, O. M. Ramos Gonzalez, E. Padilla, J. Alonso, Y. Detrés, R. Armstrong, I. Miranda, Y. Conte, N. Marrero, K. MacManus, T. Esch, and E. J. Masuoka. 2018. "NASA’s Black Marble nighttime lights product suite." Remote Sensing of Environment 210 113-143 [doi:10.1016/j.rse.2018.03.017](https://doi.org/10.1016/j.rse.2018.03.017) -Lee, T., S. Miller, F. Turk, C. Schueler, R. Julian, S. Deyo, P. Dills, and S. Wang, 2006: The NPOESS VIIRS Day/Night Visible Sensor. Bull. Amer. Meteor. Soc., 87, 191–199, [doi: 10.1175/BAMS-87-2-191](https://journals.ametsoc.org/doi/abs/10.1175/BAMS-87-2-191) +Lee, T., S. Miller, F. Turk, C. Schueler, R. Julian, S. Deyo, P. Dills, and S. Wang, 2006: The NPOESS VIIRS Day/Night Visible Sensor. Bull. Amer. Meteor. Soc., 87, 191–199, [doi:10.1175/BAMS-87-2-191](https://doi.org/10.1175/BAMS-87-2-191) -Román, M. O. and Stokes, E. C. (2015), Holidays in lights: Tracking cultural patterns in demand for energy services. Earth's Future, 3: 182–205. [doi:10.1002/2014EF000285](https://onlinelibrary.wiley.com/doi/10.1002/2014EF000285/full) +Román, M. O. and Stokes, E. C. (2015), Holidays in lights: Tracking cultural patterns in demand for energy services. Earth's Future, 3: 182–205. [doi:10.1002/2014EF000285](https://doi.org/10.1002/2014EF000285) diff --git a/config/default/common/config/metadata/stories/dust_storms_overview_2019/step001.md b/config/default/common/config/metadata/stories/dust_storms_overview_2019/step001.md index f84a47bc59..80036a65e0 100644 --- a/config/default/common/config/metadata/stories/dust_storms_overview_2019/step001.md +++ b/config/default/common/config/metadata/stories/dust_storms_overview_2019/step001.md @@ -1,3 +1,3 @@ Sand and dust storms commonly occur in arid and semi-arid regions, like deserts. Strong winds pick up dust and sand from areas with dry, bare soils, lift the dust into the atmosphere, and can transport the dust many, many kilometers away. Main sources of dust are Northern Africa, the Arabian Peninsula, Central Asia and China. Areas like Australia, America and South Africa have minor contributions, yet are still important. Providing a general idea of where the major dust contributors are, this Dust Surface Mass Concentration layer from the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) shows the dust surface mass concentrations for February 2019. MERRA-2 assimilates space-based observations and model-bases analyses to produce long-term, global information on the Earth System. -References: [World Meteorological Organization: Sand and Dust Storms](https://public.wmo.int/en/our-mandate/focus-areas/environment/SDS); [Global Modeling and Assimilation Office: Modern-Era Retrospective analysis for Research and Applications, Version 2](https://gmao.gsfc.nasa.gov/reanalysis/MERRA-2/) +References: [Global Modeling and Assimilation Office: Modern-Era Retrospective analysis for Research and Applications, Version 2](https://gmao.gsfc.nasa.gov/reanalysis/MERRA-2/)