flcc_monthly_grids

Metadata also available as - [Questions & Answers] - [Parseable text] - [XML]

Metadata:


Identification_Information:
Citation:
Citation_Information:
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:
Citation_Information:
Originator: Alicia Torregrosa
Originator: Cindy Combs
Originator: Jeff Peters
Publication_Date: 20160204
Title:
GOES-derived fog and low cloud indices for coastal north and central California
Geospatial_Data_Presentation_Form: Publication (Journal)
Series_Information:
Series_Name: Earth and Space Science
Issue_Identification: volume 3 issue 2
Online_Linkage: http://onlinelibrary.wiley.com/doi/10.1002/2015EA000119/full
Description:
Abstract:
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:
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:
Time_Period_Information:
Range_of_Dates/Times:
Beginning_Date: 19990601
Ending_Date: 20090930
Currentness_Reference: observed
Status:
Progress: Complete
Maintenance_and_Update_Frequency: None planned
Spatial_Domain:
Bounding_Coordinates:
West_Bounding_Coordinate: -128.028432
East_Bounding_Coordinate: -120.157757
North_Bounding_Coordinate: 42.023748
South_Bounding_Coordinate: 33.964177
Keywords:
Theme:
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:
Theme_Keyword_Thesaurus: ISO 19115 Topic Categories
Theme_Keyword: imageryBaseMapsEarthCover
Theme_Keyword: environment
Theme_Keyword: climatologyMeteorologyAtmosphere
Place:
Place_Keyword_Thesaurus: Common Geographic Areas
Place_Keyword: Northern California Coastal
Place_Keyword: Central California Coastal
Access_Constraints: None
Use_Constraints:
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:
Contact_Information:
Contact_Organization_Primary:
Contact_Organization: U.S. Geological Survey, PACIFIC REGION
Contact_Person: Alicia Torregrosa
Contact_Position: Physical Scientist
Contact_Address:
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:
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:
Microsoft Windows 7 Version 6.1 (Build 7601) Service Pack 1; Esri ArcGIS 10.3.1.4959

Data_Quality_Information:
Attribute_Accuracy:
Attribute_Accuracy_Report:
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:
Attribute_Accuracy_Explanation: visual assessment comparison of manual versus coded results
Logical_Consistency_Report:
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:
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:
Horizontal_Positional_Accuracy:
Horizontal_Positional_Accuracy_Report:
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:
Horizontal_Positional_Accuracy_Explanation: comparison with base maps
Vertical_Positional_Accuracy:
Vertical_Positional_Accuracy_Report:
The vertical positional accuracy although useful cannot be ascertained from this dataset.
Quantitative_Vertical_Positional_Accuracy_Assessment:
Vertical_Positional_Accuracy_Explanation:
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:
Source_Information:
Source_Citation:
Citation_Information:
Originator: NOAA
Publication_Date: 20091001
Title: NOAA GOES
Geospatial_Data_Presentation_Form: Raster Digital Data Set
Publication_Information:
Publication_Place: Online
Publisher: NOAA
Online_Linkage:
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:
Time_Period_Information:
Range_of_Dates/Times:
Beginning_Date: 19990601
Ending_Date: 20090930
Source_Currentness_Reference: observed
Source_Citation_Abbreviation: NOAA GOES
Source_Contribution: Satellite image data
Process_Step:
Process_Description:
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:
Process_Description:
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:
Process_Description:
3. Interpolated (bilinear) the decadal index to derive a contours for mapping purposes.
Process_Date: 20150131

Spatial_Data_Organization_Information:
Direct_Spatial_Reference_Method: Raster
Raster_Object_Information:
Raster_Object_Type: Grid Cell
Row_Count: 256
Column_Count: 250
Vertical_Count: 1

Spatial_Reference_Information:
Horizontal_Coordinate_System_Definition:
Geographic:
Latitude_Resolution: 8.9831528411952133e-009
Longitude_Resolution: 8.9831528411952133e-009
Geographic_Coordinate_Units: Decimal Degrees
Geodetic_Model:
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:
Detailed_Description:
Entity_Type:
Entity_Type_Label: Attribute Table
Entity_Type_Definition:
Table containing attribute information associated with the data set.
Entity_Type_Definition_Source: Producer defined
Attribute:
Attribute_Label: Value
Attribute_Definition:
Average decadal fog and low cloud cover calculated in hours per day.
Attribute_Definition_Source: Producer defined
Attribute_Domain_Values:
Range_Domain:
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:
Entity_and_Attribute_Overview:
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:
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:
Distributor:
Contact_Information:
Contact_Organization_Primary:
Contact_Organization: U.S. Geological Survey, PACIFIC REGION
Contact_Person: Alicia Torregrosa
Contact_Position: Physical Scientist
Contact_Address:
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:
Digital_Form:
Digital_Transfer_Information:
Format_Name: Raster Digital Data Set
Digital_Transfer_Option:
Online_Option:
Computer_Contact_Information:
Network_Address:
Network_Resource_Name: http://climate.calcommons.org/datasets/summertime-fog
Fees: None. No fees are applicable for obtaining the data set.

Metadata_Reference_Information:
Metadata_Date: 20160307
Metadata_Contact:
Contact_Information:
Contact_Organization_Primary:
Contact_Organization: U.S. Geological Survey, PACIFIC REGION
Contact_Person: Alicia Torregrosa
Contact_Position: Physical Scientist
Contact_Address:
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