flcc_monthly_grids
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Metadata:
- Identification_Information:
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- Citation:
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- Citation_Information:
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- Originator: Alicia Torregrosa
- Originator: Cindy Combs
- Originator: Jeff Peters
- Publication_Date: 20160204
- Title: flcc_monthly_grids
- Geospatial_Data_Presentation_Form: Raster Digital Data Set
- Online_Linkage: http://climate.calcommons.org/datasets/summertime-fog
- Online_Linkage: http://geography.wr.usgs.gov/fog
- Larger_Work_Citation:
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- Citation_Information:
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- Originator: Alicia Torregrosa
- Originator: Cindy Combs
- Originator: Jeff Peters
- Publication_Date: 20160204
- Title:
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GOES-derived fog and low cloud indices for coastal north and central California
- Geospatial_Data_Presentation_Form: Publication (Journal)
- Series_Information:
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- Series_Name: Earth and Space Science
- Issue_Identification: volume 3 issue 2
- Online_Linkage: http://onlinelibrary.wiley.com/doi/10.1002/2015EA000119/full
- Description:
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- Abstract:
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The raster grids in the monthly dataset contain the calculated hours per day of fog and low cloud cover (FLCC) as monthly averages for Northern and Central Coastal California. The calculations are based on a decade of summertime cloud maps derived from satellite-based measurements. The filename of each individual raster grid specifies the temporal period (month and year) for the grid. The northernmost spatial extent of the dataset is the Oregon border and the southernmost extent is Point Arguello. The digital values for each 4 km grid cell were calculated from the archive of 26,000 hourly cloud maps derived from hourly geostationary operational environmental satellite (GOES) images from 1999-2009 for June, July, August, and September. Daytime cloud maps were generated using one visible channel and two thermal channels whereas nighttime cloud maps were generated using two thermal channels.
- Purpose:
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Fog and low cloud cover (FLCC) is very important for coastal California. During the seasonally arid summer months of the northern hemisphere Mediterranean climate zones (June to September), the stratus and stratocumulus clouds that form over the ocean advect onshore. When these low clouds touch the earth they are called fog although many people will also call the higher overcast clouds fog. When fog touches needles or other surfaces the fog water droplets coalesce becoming fog drip. Overcast clouds form a shield that reflects solar radiation bringing relief from summer heat. The added water from fog and reduced temperatures from low clouds can be critical for coastal species such as endangered coho salmon that require cool flowing streams during late summer. FLCC is highly variable across the landscape and throughout the summer resulting in many different climate regimes just a short distance from each other. Precisely located fog belt zones can help natural resource managers and others quantify the impacts of FLCC on ecosystem dynamics. A summertime FLCC dataset was developed as a Pacific Coastal Fog Project partnership between the US Geological Survey and the Cooperative Institute for Research on the Atmosphere (CIRA). The project goal is to quantify coastal ecosystem response to summertime patterns of marine stratus and stratocumulus cloud. A first step toward that goal is quantifying the FLCC patterns. We used 26,000 cloud maps, generated by CIRA from hourly weather satellite imagery to generate raster grids of average summertime FLCC. The images were collected from 1999 to 2009 and were subset into several temporal periods: decadal, annual, and monthly. By compressing large quantities of FLCC data into manageable units we sought to simplify the complex FLCC meteorological phenomenon into coherent FLCC indices applicable to landscape-level analysis. For more details see the publication, GOES-derived fog and low cloud indices for coastal north and central California ecological analyses, Earth and Space Science, 3, doi:10.1002/2015EA000119. The dataset uses hours per day (h/d) as the unit of analysis. This metric, like percent cover, gives a relative measure of cover however rather than a base of 100 it uses a base of 24 hours. Either measure could be used however our use of h/d is intended to facilitate an intuitive grasp of the amount of FLCC affecting the ecological process-of-interest on a daily time-step. Other indices in the series include the nighttime and daytime patterns and two measures of variation: standard deviation and coefficient of variation.
- Time_Period_of_Content:
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- Time_Period_Information:
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- Range_of_Dates/Times:
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- Beginning_Date: 19990601
- Ending_Date: 20090930
- Currentness_Reference: observed
- Status:
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- Progress: Complete
- Maintenance_and_Update_Frequency: None planned
- Spatial_Domain:
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- Bounding_Coordinates:
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- West_Bounding_Coordinate: -128.028432
- East_Bounding_Coordinate: -120.157757
- North_Bounding_Coordinate: 42.023748
- South_Bounding_Coordinate: 33.964177
- Keywords:
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- Theme:
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- Theme_Keyword_Thesaurus: None
- Theme_Keyword: atmosphere
- Theme_Keyword: climatology
- Theme_Keyword: year
- Theme_Keyword: day
- Theme_Keyword: Meteorology
- Theme_Keyword: environment
- Theme_Keyword: night
- Theme_Keyword: summer
- Theme_Keyword: Earth Cover
- Theme_Keyword: imagery
- Theme:
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- Theme_Keyword_Thesaurus: ISO 19115 Topic Categories
- Theme_Keyword: imageryBaseMapsEarthCover
- Theme_Keyword: environment
- Theme_Keyword: climatologyMeteorologyAtmosphere
- Place:
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- Place_Keyword_Thesaurus: Common Geographic Areas
- Place_Keyword: Northern California Coastal
- Place_Keyword: Central California Coastal
- Access_Constraints: None
- Use_Constraints:
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Please use the following citation when using this dataset: Torregrosa, A., C. Combs, and J. Peters (2016), GOES-derived fog and low cloud indices for coastal north and central California ecological analyses, Earth and Space Science, 3, doi:10.1002/2015EA000119.
- Point_of_Contact:
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- Contact_Information:
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- Contact_Organization_Primary:
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- Contact_Organization: U.S. Geological Survey, PACIFIC REGION
- Contact_Person: Alicia Torregrosa
- Contact_Position: Physical Scientist
- Contact_Address:
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- Address_Type: mailing
- Address: Mail Stop 531, 345 Middlefield Road
- City: Menlo Park
- State_or_Province: CA
- Postal_Code: 94025
- Contact_Voice_Telephone: 650-329-4091
- Contact_Facsimile_Telephone: 650-329-4429
- Contact_Electronic_Mail_Address: atorregrosa@usgs.gov
- Data_Set_Credit:
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USGS Land Change Science, Cooperative Institute for Research on the Atmosphere, California Landscape Conservation Cooperative, TBC3 -Pepperwood Preserve, and Gordon and Betty Moore Foundation.
- Native_Data_Set_Environment:
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Microsoft Windows 7 Version 6.1 (Build 7601) Service Pack 1; Esri ArcGIS 10.3.1.4959
- Data_Quality_Information:
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- Attribute_Accuracy:
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- Attribute_Accuracy_Report:
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Two methods were used to ensure quality and assess attribute accuracy: 1) visual assessment of individual images-run through as movies with removal of any images that had systematic contamination such as poor image quality during dusk and dawn when extreme Sun angles impact brightness values causing the image to stand out starkly during the run-through; 2) manual calculations of statistical analysis were compared with results from the results of the python coded scripts run in ArcGIS. When the results were different from each other it triggered examination to troubleshoot and correct the code.
- Quantitative_Attribute_Accuracy_Assessment:
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- Attribute_Accuracy_Explanation: visual assessment comparison of manual versus coded results
- Logical_Consistency_Report:
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Two methods were used to assess logical accuracy: 1) expert knowledge was used to cross-check landscape level results of mapped FLCC patterns to meteorologically accepted patterns of FLCC. This assessment showed high logical accuracy. 2) regression analyses were conducted comparing airport observations of fog with point data sampled from the FLCC databse. The results of this assessment showed a high R squared value for Monterey (0.83) and a lower value for Arcata (0.32). These results are discussed and plotted as Figure 10 in Torregrosa, A., C. Combs, and J. Peters (2016), GOES-derived fog and low cloud indices for coastal north and central California ecological analyses, Earth and Space Science, 3, doi:10.1002/2015EA000119.
- Completeness_Report:
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The purpose of the data was to understand summertime coastal cloud patterns, the dataset is therefore restricted to June, July, August and September. There are data gaps in the dataset collection. Only about 72,000 of the 95,000 images that could have been potentially captured during summers of 1999-2009, from the NOAA weather satellite, also known as GOES (geostationary operational environmental satellite), from the Imager sensor channels 1 (visible), 2 (shortwave infrared), and 4 (longwave infrared), were processed into about 26,000 hourly cloud maps. Quality control removal of images and missing images gaps include all data for August 2001 and June 2006, leaving only nine full summers for interannual and decadal statistical calculations. Monthly averages from all 11 years were used when available. When an hourly dusk or dawn cloud map was removed because it had been impacted by extreme Sun angles, a substitution was made by averaging the hour before and hour after. Data set is considered complete for the information presented, as described in the abstract. Users are advised to read the rest of the metadata record carefully for additional details.
- Positional_Accuracy:
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- Horizontal_Positional_Accuracy:
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- Horizontal_Positional_Accuracy_Report:
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Horizontal accuracy was assessed using coastline basemaps. Familiarity with coastal fog patterns was used to identify images that had very obvious geopositional offset from the coast. Most data for August 2001 had error and were deleted from the collection. Practicing meteorologists with deep familiarity with coastal low cloud patterns provided technical review and closely examined the landscape level patterns that came out of the long term statistical spatial analysis (decadal averages and coefficient of variation). Known patterns such as the Petaluma Gap and deep incursion into Salinas Valley were well represented in the new outputs.
- Quantitative_Horizontal_Positional_Accuracy_Assessment:
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- Horizontal_Positional_Accuracy_Explanation: comparison with base maps
- Vertical_Positional_Accuracy:
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- Vertical_Positional_Accuracy_Report:
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The vertical positional accuracy although useful cannot be ascertained from this dataset.
- Quantitative_Vertical_Positional_Accuracy_Assessment:
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- Vertical_Positional_Accuracy_Explanation:
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High clouds were distinguished from low clouds based on temperature differences from the two thermal bands. this does not allow a true measurement of vertical position althought it does provide a relative measure of vertical position
- Lineage:
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- Source_Information:
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- Source_Citation:
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- Citation_Information:
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- Originator: NOAA
- Publication_Date: 20091001
- Title: NOAA GOES
- Geospatial_Data_Presentation_Form: Raster Digital Data Set
- Publication_Information:
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- Publication_Place: Online
- Publisher: NOAA
- Online_Linkage:
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http://www.nsof.class.noaa.gov/saa/products/search?datatype_family=GVAR_IMG
- Source_Scale_Denominator: 4000
- Type_of_Source_Media: hardcopy
- Source_Time_Period_of_Content:
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- Time_Period_Information:
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- Range_of_Dates/Times:
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- Beginning_Date: 19990601
- Ending_Date: 20090930
- Source_Currentness_Reference: observed
- Source_Citation_Abbreviation: NOAA GOES
- Source_Contribution: Satellite image data
- Process_Step:
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- Process_Description:
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1. Processed 3 GOES channel data into cloud maps. for details see Combs, C. L., R. Mazur, J. Clark, M. Norquist, and D. Molenar (2010), An effort to improve marine stratus forecasts using satellite cloudclimatologies for the Eureka, CA region, paper presented at 17th Conference on Satellite and Oceanography, Annapolis, Md, Sept. 30.[Available at https://usgs.illiad.oclc.org/illiad/GIM/illiad.dll?Action=10andForm=70Meteorology.]
- Process_Date: 20120630
- Process_Step:
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- Process_Description:
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2. Converted cloud maps into georectified raster grids and ran statistical analysis using python code in ArcGIS. For more details see Torregrosa, A., C. Combs, and J. Peters (2016), GOES-derived fog and low cloud indices for coastal north and central California ecological analyses, Earth and Space Science, 3, doi:10.1002/2015EA000119
- Process_Date: 20141130
- Process_Step:
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- Process_Description:
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3. Interpolated (bilinear) the decadal index to derive a contours for mapping purposes.
- Process_Date: 20150131
- Spatial_Data_Organization_Information:
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- Direct_Spatial_Reference_Method: Raster
- Raster_Object_Information:
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- Raster_Object_Type: Grid Cell
- Row_Count: 256
- Column_Count: 250
- Vertical_Count: 1
- Spatial_Reference_Information:
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- Horizontal_Coordinate_System_Definition:
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- Geographic:
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- Latitude_Resolution: 8.9831528411952133e-009
- Longitude_Resolution: 8.9831528411952133e-009
- Geographic_Coordinate_Units: Decimal Degrees
- Geodetic_Model:
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- Horizontal_Datum_Name: D North American 1983
- Ellipsoid_Name: GRS 1980
- Semi-major_Axis: 6378137.0
- Denominator_of_Flattening_Ratio: 298.257222101
- Entity_and_Attribute_Information:
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- Detailed_Description:
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- Entity_Type:
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- Entity_Type_Label: Attribute Table
- Entity_Type_Definition:
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Table containing attribute information associated with the data set.
- Entity_Type_Definition_Source: Producer defined
- Attribute:
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- Attribute_Label: Value
- Attribute_Definition:
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Average decadal fog and low cloud cover calculated in hours per day.
- Attribute_Definition_Source: Producer defined
- Attribute_Domain_Values:
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- Range_Domain:
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- Range_Domain_Minimum: 1.85
- Range_Domain_Maximum: 14.65
- Attribute_Units_of_Measure: hours per day
- Beginning_Date_of_Attribute_Values: 19990601
- Ending_Date_of_Attribute_Values: 20090930
- Attribute_Measurement_Frequency: 011
- Overview_Description:
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- Entity_and_Attribute_Overview:
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The entity and attribute information provided here describes the tabular data associated with the data set. Please review the detailed descriptions that are provided (the individual attribute descriptions) for information on the values that appear as fields/table entries of the data set.
- Entity_and_Attribute_Detail_Citation:
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The entity and attribute information was generated by the individual and/or agency identified as the originator of the data set. Please review the rest of the metadata record for additional details and information.
- Distribution_Information:
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- Distributor:
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- Contact_Information:
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- Contact_Organization_Primary:
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- Contact_Organization: U.S. Geological Survey, PACIFIC REGION
- Contact_Person: Alicia Torregrosa
- Contact_Position: Physical Scientist
- Contact_Address:
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- Address_Type: mailing
- Address: Mail Stop 531, 345 Middlefield Road
- City: Menlo Park
- State_or_Province: CA
- Postal_Code: 94025
- Contact_Voice_Telephone: 650-329-4091
- Contact_Facsimile_Telephone: 650-329-4429
- Contact_Electronic_Mail_Address: atorregrosa@usgs.gov
- Distribution_Liability: Distributor assumes no liability for misuse of data.
- Standard_Order_Process:
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- Digital_Form:
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- Digital_Transfer_Information:
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- Format_Name: Raster Digital Data Set
- Digital_Transfer_Option:
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- Online_Option:
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- Computer_Contact_Information:
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- Network_Address:
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- Network_Resource_Name: http://climate.calcommons.org/datasets/summertime-fog
- Fees: None. No fees are applicable for obtaining the data set.
- Metadata_Reference_Information:
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- Metadata_Date: 20160307
- Metadata_Contact:
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- Contact_Information:
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- Contact_Organization_Primary:
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- Contact_Organization: U.S. Geological Survey, PACIFIC REGION
- Contact_Person: Alicia Torregrosa
- Contact_Position: Physical Scientist
- Contact_Address:
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- Address_Type: mailing
- Address: Mail Stop 531, 345 Middlefield Road
- City: Menlo Park
- State_or_Province: CA
- Postal_Code: 94025
- Contact_Voice_Telephone: 650-329-4091
- Contact_Facsimile_Telephone: 650-329-4429
- Contact_Electronic_Mail_Address: atorregrosa@usgs.gov
- Metadata_Standard_Name: FGDC Content Standard for Digital Geospatial Metadata
- Metadata_Standard_Version: FGDC-STD-001-1998
- Metadata_Time_Convention: local time
Generated by mp version 2.9.32 on Tue Mar 8 11:34:14 2016