Designed to test pairs of observations. If a potential duplicate initially identified by overlapping platform-date-time information falls outside the 5 km window, it is not a duplicate. Example: When data collected at the same time, from different ships are both tagged with the SHIP call sign. Once observations and their corresponding subsurface profiles, there are several potential outcomes to consider:. If the message comes from different streams, then one would not expect the subsurface information to be the different.
If from the same stream, they should be the same. This occurs when the two observations come from different stream types, or when neither of the cases 1 or 2 are satisfied. The decision is referred to an operator, who receives a printed copy of the potential duplicates list. A technician then reviews the listing and makes the appropriate decision. The duplicates identification system runs as a batch job.
Once the technician has reviewed the list, he or she then applies the final decisions to the ISAM file used as input to the original batch run. In the above example, four potential duplicates are identified in the target observation the first BATHY. Each potential duplicate had the same:.
This group of observations were referred to the technician, because some of them have temperature differences at several depths.. For example, at the 79 meter depth, the temperature is Technicians decide which version makes the final dataset based on guidelines and prioritizations, such as selecting the version that covers the greatest range of depths or the correct call sign. Note that the first message in the group has an incomplete call sign and was included in the group through the fuzzy time-fuzzy area test.
Look at the contents of the PROF structure of the station record, and check for both temperature and salinity profiles. A new State of the Climate report confirmed that was one of the three warmest years in records dating to the mids. And just as land regions have. Several key environmental factors guide an ongoing effort to understand global changes in climate.
They are tracked as part of a. Scientists and sailors were using. Citation Sun, C. Documentation Download ncBrowse ncBrowse is a Java application that provides flexible, interactive graphical displays of data and attributes from a wide range of netCDF data file conventions.
Contains support for variable mapping and animation Warning: this is test version, please report any problems Directly access remote netCDF files using the HTTPClient library for connectivity. Background GTSPP is a cooperative international program that was developed to address the need for up-to-date, high quality ocean temperature and salinity data in the ocean science and marine operational communities researching sustainable development, climate change, and human and environmental safety.
Long-Term Archive Center LTAC : Maintains the up-to-date global temperature-salinity data, replaces near real-time records with higher quality delayed-mode records as they are received, and creates and distributes data copies. Data Product Center DPC : Performs analysis of all the GTSPP data in the region of interest to assess its data quality consistency, provide feedback to data collectors about the results of the analysis, and prepare and distribute data products on a regular basis.
Goals Provide a timely and complete data and information base of ocean temperature and salinity profile data To implement data flow monitoring system for improving the capture and timeliness of real-time and delayed-mode data To improve and implement agreed and uniform quality control and duplicates management systems To facilitate the development and provision of a wide variety of useful data analyses, data and information products, and datasets Data Access Characteristics GTSPP consolidates ocean profile data into a single format with consistent quality control and duplicates processing.
The Chair is selected by the Steering Group and will be reviewed every two sessions. Provide scientific and technical guidance for the program in the implementation and enhancement of the GTSPP including: Near real time data observations within 30 days acquisition Non real time data observations older than 30 days or data never circulated on the Global Telecommunication System acquisition Communications infrastructures Quality control and analysis procedures Continuously managed database Ocean data and metadata standards Data and information products In conjunction with user groups and data collectors, design and implement data flow monitoring systems to ensure that the data are collected, processed and distributed according to agreed schedules and responsibilities.
Includes: Location Time of the station Receipt Number of repeats of other components found in the 'Station' record Second Component Number of station profiles Duplicate flags Variable accuracy and precision Segment profiles for depth Third Component Carries information about other variables measured at the station, such as winds, air temperature, etc. Fourth Component Carries information about other variables measured at the station which are recorded as alphanumerics, including Beaufort winds, QC tests executed, etc.
Fifth Component Used to record the processing history of the station. Sample Layout with Specifications Temperature and a salinity profiles were collected at a station, with observations every meter to m depth. Component Contents 1 Station location, time and other information. First Component Always present Has a fixed number of fields Repeats the station location and time Identifies the profile type and segment of the profile Indicates depths or pressures if recorded and the number of depth-variable pairs Second Component Records the depth and measured variable Quality control flags that have been applied at each depth This component can be repeated as often as necessary Sample Layout with Specifications Component Contents 1 Station location, time, profile, and segment identifiers 2 Up to repeats of depth-variable information and associated quality control flags NetCDF Description All GTSPP data is located and represented by three spatial axes longitude, latitude, and depth and one temporal time axis.
The numeric variable code is a unique identifier for the variable or axis, and is described below under Variables Each axis needs to be defined with a numeric code for EPS library V2. The basic GISS temperature analysis scheme was defined in the late s by James Hansen when a method of estimating global temperature change was needed for comparison with one-dimensional global climate models. The analysis method was fully documented in Hansen and Lebedeff Several papers describing updates to the analysis followed over the following decades, most recently that of Hansen et al.
We also maintain a running record of modifications made to the analysis on our Updates to Analysis page. The update incorporates reports for the previous month as well as late reports and corrections for earlier months. The programs assume a Unix-like operating system and require familiarity with Python for installation and use. The following are plain-text files in tabular format of temperature anomalies, i. The following tables show anomalies based on AIRS data vs.
Corresponding L-OTI anomaly data are also provided. Missing Data Flag missing data present. Vertical Levels Surface Data Set. Data Access: Please Cite data sources, following the data providers' instructions. Key Figures Click the thumbnails to view larger sizes. Thumbnails Captions Change of mean annual surface temperatures in 5 global, gridded data sets. Calculated as the difference of means of the period and the period. Cite this page. Acknowledgement of any material taken from this page is appreciated.
Type of data product Gridded from obs. Find Help. Search Tool Search for and access past weather and climate data by station name or identifier, ZIP code, city, county, state, or country. Search Tool » Mapping Tool Find and view past weather and climate data by station name or identifier, ZIP code, city, county, state, or country.
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