- Are winds one minute or ten minute mean winds (or equivalents thereof)?
- How are the 3-day, weekly and monthly average data maps made?
- Why do I see data on daily maps with tomorrow's date, when tomorrow has not yet occurred?
- How can I tell when a satellite collected data over a particular spot on a daily data map?
- Who names tropical cyclones and how do they generate the names?
- What is oceanographic vs meteorological wind direction?
- Do you have an older version of the data product?
- I need brightness temperature data. Where can I get it from?
- What is LTAN?
- What are the differences between the low-frequency and medium-frequency winds?
- “I saw this plot on a denialist web site. Is this really your data?”
The satellite images are instantaneous snap-shots of a 25 km x 25 km area. This is probably more comparable to an 8 - 10 minute wind (if you consider the amount of space measured by a storm moving past a fixed point making observations for 8 minutes).
We validate satellite winds with buoy winds, most of which are temporal averages ranging from 6 minutes (TAO) to 8 minutes (NDBC), and generally obtain wind speed differences of less than 1 m/s.
The radiometer (SSM/I, TMI, and AMSR-E) and scatterometer (QuikScat, SeaWinds) data are all available as 3-day, weekly and monthly averaged data. These files are created from the earth gridded daily pass data. Each grid cell contains the average (mean) value of all valid geophysical data points in that cell for all daily passes within the averaging time period. For grid locations where no data exist within the averaging period (occasionally occurs in 3-day maps), a value of 254 (missing data) is assigned.
Ice (a value of 252) is assigned to the grid cell if ice was present more often than valid data within the averaging period.
Each daily map is for ascending or descending passes of a satellite on that date at Universal Coordinated Time (UTC) also known as Greenwich Mean Time (GMT). For example, data may be collected in the New York area at approximately 8:30 pm local time. But 8:30 pm in New York City is 1:30 am in Greenwich, England (8:30 + 5 hour time difference). If it is August 17th, local time in New York, it must be August 18th in Greenwich, England, a location with GMT (the date of the map). Thus, some data collected on Aug 17th, local time, will appear on the August 18th map.
Similar time "issues" occur for each of the satellites. The table below demonstrates another example, this time for data collected by the F13 satellite. F13 crosses the equator at approximately 5:30 am.
F13 local Time/Date
F13 GMT Time/Date
|New Guinea||0 / 133||5:30 AM 20-Sep||8:30 PM 19-Sep||19-Sep|
|Jarvis Island||0 / 203||5:30 AM 19-Sep||4:30 PM 19-Sep||19-Sep|
|Ecuador||0 / 280||5:30 AM 19-Sep||10:30 AM 19-Sep||
Here, the F13 morning pass time of 5:30 (local time) is used to determine the GMT of the map date. The corresponding GMT time and date are then used to determine the date at the given location. When the September 19th F13 morning pass was collected, it was actually September 20th in New Guinea, a location that is 8 hours ahead of Greenwich.
The best way to determine the time of observations for scientific comparisons is to use the time data in the daily binary data files. Each pixel location of an ocean parameter map has a specific GMT minute of day listed in the time array. Use of time in this manner will keep your data processing and intercomparisons in the correct order.
The time parameter can be extracted from each daily binary data file using read routines available on our FTP site (see the Data Description for each instrument). A visual method for quick approximations is discussed in: Support / Crossing Times / Swath Time Labels.
Tropical cyclones are named by a World Meteorological Organization committee. Here is a great page that describes the naming of tropical cyclones and provides current lists of names:
Worldwide Tropical Cyclone Names.
When we update to a newer version of a data product we usually make significant improvements to the data. We therefore discourage using older versions. That said, if you need access to an older version for confirmation of a previous analysis, please contact us.
Brightness temperatures are available for many of the microwave radiometers. We do not currently provide the files at RSS. They are available from some of the NASA DAACs and NOAA data centers. See the links in the Brightness Temperature Data Access Table.
Wind directions are described as either "coming from" a direction (used by meteorologists) or "blowing to" a direction (used by oceanographers). The figure shows how we report the wind directions in our data products. This oceanographic convention means a 45 degree wind blows towards the northeast.
LTAN stands for Local Time of the Ascending Node and represents the time when the satellite crosses the equator when traveling from the south pole to the north pole (ascending). This time is the time of day at that Earth location when the satellite is overhead. For sun-synchronous orbiting satellites, this time is the same for each time zone (that is, a satellite with an LTAN of 6 am will be overhead at 6 am for every location on the equator each day.
We produce two standard rain-free radiometer wind products: WSPD_LF (low-frequency) and WSPD_MF (medium frequency). The first, WSPD_LF is created using the frequency channels at 10.65 GHz and above (see tables above) and is most similar to the only wind offered in the version-5 AMSR-E data files or the first wind of the TMI files. The second, WSPD_MF, uses frequency channels at 18.7 GHz and above and is most similar to the SSM/I and SSMIS winds.
Each wind product has distinct advantages. The WSPD_LF is less affected by the atmosphere and rain, but is affected by 10.65 GHz RFI and sun glitter effects. The WSPD_MF has a higher effective spatial resolution, is less affected by ice and land contamination, and is only slightly affected by sun glitter effects and RFI. The WSPD_MF are a little noisier than the WSPD_LF.
We get this question quite a bit since many people use and look at our data to help them understand climate change. We encourage you to read more in the blog post containing a full explanation of Carl Mears' point of view on the RSS AMSU data and the differences with climate models used in the IPCC AR5 report.
If you did not find an answer to your question, please contact us. We aim to respond to support submissions within 2 - 3 business days.