Version-7 Release-01 Wind Speed CDR
This data product is constructed from Remote Sensing Systems (RSS) Version-7 microwave radiometer wind speed values. The product is updated monthly and is available at www.remss.com. One netCDF file contains all the data and is named wspd_v07r01_198801_YYYYMM.nc, where YYYY is the most recent year and MM is the most recent month of the data in the file. We will update this file monthly. The V07 signifies that the data are made from the Version-7 RSS data (this will not change until the RSS input data are a new version). The r01 signifies this is the second revision of the Wind Speed product. The changes from V00 to V01 included adding AMSR2 to the product. If we make any significant changes to the file/contents beyond adding new data, we will increment the version number. We expect to update the climatology data once per decade and will increment the version number at that time.
Introduction
We have constructed a merged, 1-degree wind speed data set using the version-7 (V7) passive microwave geophysical ocean products publicly available from Remote Sensing Systems (www.remss.com). The wind speed values come from the following satellite radiometers; SSM/I F08 through F15, SSMIS F16 and F17, WindSat, and AMSR2. These microwave radiometers have been carefully intercalibrated at the brightness temperature level and the V7 ocean products have been produced using a consistent processing methodology for all sensors. These high quality ocean data are made available to users thanks to funding from the NASA MEaSUREs project. Ocean surface winds obtained from satellite radiometers represent wind speeds at a height of 10- meters. Through comparisons with winds measured by anemometers on moored buoys we can determine that the wind speed data have an rms error of ~1.0 m/s. This document highlights the construction of the merged product which contains monthly, 1-degree wind speed means, a 12-month climatology made using 1988 to 2007 data, monthly anomaly maps, a trend map with associated global and tropical wind speed time series and trends, and a time-latitude plot. The data set was released in February 2014 in netCDF format and updated in Jan 2016. It is accessible by FTP (ftp.remss.com/wind), OpenDAP, and browse imagery. The product is updated monthly and will continue for as long as microwave satellite radiometers are in operation.
Development of the Merged Wind Speed 1-deg Data Set
This wind speed product is made using a two-step construction process. First, we make monthly 1-deg maps from the individual satellite wind speed values, keeping track of number of obs, number of ice obs and the mean day of month. We re-grid using cosine latitude weights to reduce from the 0.25 deg grid of the RSS satellite products to the 1-deg grid of this product. In the second stage of processing, we apply quality control measures, apply post hoc adjustments, and combine the wind speed values from all instruments using simple averaging. The resulting wind speed product was constructed using the following requirements: We only calculate a wind speed value for a specific 1-deg grid cell if the cell contains more than 160 observations during the month, if ice is present for <= 30 of the included observations, and if the calculated mean day of the month (derived by averaging the time of the data falling within the cell) is within 6 days of the center day of the month. Three satellite-months did not meet our requirements: F08 in Jan 1988, F08 in Oct 1990 and F10 in Dec 1991. In each case, the month values are needed for consistency of the time series so an exception was made and the data were included. These quality checks were applied in the second stage of processing. In developing our methodology, several aspects of data product construction were explored, including geographic sampling, minimal data number requirements, ice flagging, rain flagging, averaging methods, analysis of offsets and need for small bias corrections. These are further described in the following paragraphs.
The quality of the wind product produced is dependent on the number of data that are averaged into each grid cell. Land and ice proximity affects this number. Radiometers suffer from side lobe interference that prevents obtaining wind speed values near land. Due to variations in instrument resolution, look angle, geographic conditions and spatial footprints, some pixels have more observations than others. This results in varying numbers of observations for a given grid cell and poorer quality averages near coastlines and along ice edges. We tested a variety of minimum observation requirements and experimented to see how different thresholds affected resulting trends. We found little difference once a minimum threshold of 160 counts per cell was met.
Ice is likely to exist more at one end of a month than another (with the exception of floating icebergs) and ice removal is necessary. We developed a mean-day-of-month quality calculation to remove ice edge grid cells where the amount of ice increases or decreases throughout the month. To handle icebergs which move between grid cells, we used the number of ice observations within a grid cell during the month to exclude when too much ice existed (number of ice observations must be <= 30).
Rain affects radiometer wind speeds and therefore rain-affected data must be removed from the merging process. For wind, we find that we need to remove data in grid points adjacent to rain to ensure the highest quality data. We also found that exclusion of data adjacent to rain creates a geographic sampling problem by removing data from primarily rainy, tropical areas which results in lower mean wind speed values and higher global trends. We excluded data from grid points with rain.
We use only RSS Version-7 wind speed values in making this product. The data are from all SSM/I instruments, the F16 and F17 SSMIS, WindSat, and AMSR2. AMSR-E data are excluded due to the later sampling time of AMSR-E (1am/pm as opposed to 6-9 am/pm of the other radiometers). Though the AMSR2 also has the later sampling time, we have included it in the R01 version to provide more data in the most recent years. Another minor difference between the instruments involves the calibration process, AMSR-2 and WindSat were calibrated with only rain-free data as opposed to using all data (rain-free and rainy) for the intercalibration process. This slight difference in calibration may account the need of a small post-hoc correction applied to the data prior to merging. Post-hoc corrections used in the V07R01 product are those given in the Wentz, 2015 TMI paper.
Data Issues / Known Problems
3 satellite/month exceptions are needed in order to maintain time series consistency and avoid large data gaps.
|
F08 |
for |
Jan 1988 |
|
F08 |
for |
Oct 1990 |
|
F10 |
for |
Dec 1991 |
In each case, these are the only (or the best) satellite/month data available. In the case of F08, no other radiometer was in operation at that time.
This wind speed product is intended for climate study as the input data have been carefully intercalibrated and consistently processed. Strict Q/C requirements are used to omit data that are not suitable for climate study. For more information, see the description of the development of the product.
We update the product monthly, adding the data for the last month to the time series. Trends are recalculated. The 12-month climatology supplied in the file and used for anomaly calculations is calculated by averaging all observations that pass our Q/C requirements from the years 1988 to 2007 (20 years). We will recalculate the climatology every 10 years (due to be recalculated next in 2018).
Some users have had trouble reading the netCDF4 format file. Therefore, we provide both a netCDF3 file and a netCDF4 file. Both files contain identical data and information.
Data Product Format Description
This product is constructed by merging all valid wind speed data from SSM/I, SSMIS, WindSat, and AMSR2 instruments. The netCDF file contains mean wind speed values on a 1-degree grid, a 12-month wind speed climatology, monthly anomalies, a wind speed trend map, and a time-latitude (hovmoeller) plot. The product contains data for the global oceans at 1-deg spatial resolution and represents monthly means for January 1988 to the date of most recent processing. The product is updated monthly. There are no data values in regions of land, persistent ice, and coastal areas.
Wind Speed is reported in meters per second (m/s). Wind speed ranges between 0 to 50 m/s with a resolution of 0.2 m/s.
File Format and Contents:
We provide 2 netCDF files, both contain the same information, one is netCDF3 format and the other is netCDF4 format.
Temporal coverage for this data set is monthly maps from 1988 through to the present.
The product file is re-created every month by the 15th adding the previous month's value.
The number of months in the data file will continue to increase until there are no more satellite radiometer instruments in operation.
Content of the netCDF File:
1) monthly means of wind speed, grid size 360 x 180 x number of all months since Jan 1988 (increases over time)
2) a 12-month set of climatology wind speed, grid size 360 x 180, the climatology is an average calculated over the 20-year period 1988-2007
3) monthly anomalies of wind speed derived by subtracting the above climatology maps from the monthly means, grid size 360 x 180 x number of months since Jan 1988 (increases over time)
4) a wind speed trend map, grid size 360 x 180, the trend is calculated from Jan 1988 through Dec of the latest complete year of data
5) a time-latitude plot (a minimum of 10% of latitude cells is required for valid data), grid size 180 x number of months since Jan 1988 (increases over time)
In addition to the above variables, we include:
1) satellites_used:
information about which satellites were included that month in calculating the mean
the array is sized #months x 10 satellites, where 1= used, 0=not used
The satellite instruments are in the following order: 1=SSMI F08,2=SSMI F10,3=SSMI F11,4=SSMI F13,5=SSMI F14,6=SSMI F15,7=SSMIS F16,8=SSMIS F17,9=AMSRE* on AQUA,10=WindSat on Coriolis,11=AMSR2 on GCOM-W1. The AMSRE position is provided for consistency with the TPW product. We have not used AMSR-E in this wind speed product.
2) global_mean_wind speed_anomaly:
the monthly Average Near-Global Mean Wind Speed Anomaly over Ice-Free Oceans, 60S to 60N, array size = #months
3) tropical_mean_wind speed_anomaly:
the Monthly Average Tropical Mean Wind Speed Anomaly over Ice-Free Oceans, 20S to 20N, array size = #months
The file size is approximately 151 MB, and grows as each new month of data is added to the file.The remaining variables are time, latitude, longitude, climatology_time, and bounds for each of these.
File Naming Convention:
wspd_v07r##_yyyymm_yyyymm.nc, where:
|
wspd |
= |
wind speed |
|
## |
= |
file revision number |
|
yyyy |
= |
four-digit year, first value is start of data, second is end of data |
|
mm |
= |
two-digit month, first value is start of data, second is end of data |
|
nc |
netCDF file format |
Read Routines
Read routines are available in Idl, Matlab and Python at:
ftp.discover-earth.org/wind/monthly_1deg/read_routines/.
Any third party tool/software capable of reading netCDF files can be used (such as Panoply).
|
IDL: |
read_wspd_v07r01.pro |
|
|
Matlab |
read_wspd_v07r01.m |
|
|
Python |
show_rss_wspd_netcdf.py and readnetcdf.py |
Browse Images/ Graphic Image Maps
We have developed a browse environment for this data product. The environment allows the user to switch between monthly mean wind speed plots, anomaly plots, the 12-month climatology and the wind speed trend. More capability will be added to this environment at a later date. The 'Get Data' button connects to the ftp server for data file download.
Product Validation
Product validation results will be available soon.
References
Wentz, FJ, 2015,
"A 17-yr Climate Record of Environmental Parameters Derived from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager",
Journal of Climate, vol. 28, pg. 6882-6902.
Wentz, FJ, L Ricciardulli, KA Hilburn and others, 2007,
"How much more rain will global warming bring?",
Science, vol. 317, pg. 233-235.
Wentz FJ, 1997,
"A well-calibrated ocean algorithm for SSM/I",
Journal of Geophysical Research, vol. 102(C4), pg. 8703-8718.
Wentz, FJ and RW Spencer, 1998,
"SSM/I rain retrievals within a unified all-weather ocean algorithm",
Journal of the Atmospheric Sciences, vol. 55, pg. 1613-1627.
Wentz, FJ and T Meissner, 2000,
"AMSR Ocean Algorithm, Version 2",
report number 121599A-1, Remote Sensing Systems, Santa Rosa, CA, 66 pp.
Wentz, FJ and T Meissner, 2007,
"Supplement 1 Algorithm Theoretical Basis Document for AMSR-E Ocean Algorithms",
report number 051707, Remote Sensing Systems, Santa Rosa, CA, 6 pp.
Hilburn, KA, FJ Wentz, CA Mears, T Meissner, DK Smith, 2010,
"Description of Remote Sensing Systems Version-7 geophysical retrievals",
presented at 17th Conference on Satellite Meteorology and Oceanography and 17th Conference on Air-Sea Interaction, Annapolis, MD.
Mears, CA, BD Santer, FJ Wentz, KE Taylor, and MF Wehner, 2007,
"Relationship between temperature and precipitable water changes over tropical oceans",
Geophysical Research Letters, vol. 34, L24709, doi:10.1029/2007GL031936.
Contacts
Investigators:
Carl A. Mears, Kyle A. Hilburn, Deborah K. Smith, Lucrezia Ricciardulli
Remote Sensing Systems
444 Tenth St, Suite 200
Santa Rosa, CA 95401 USA
Technical Contact:
Michael Densberger and Marty Brewer
Remote Sensing Systems User Support
support@remss.com
Acknowledgement and Citation
This research was supported by National Aeronautics and Space Administration (NASA) Making Earth System data records for Use in Research Environments (MEaSUREs) Grant #NNX09AC19A. Microwave radiometer data are processed by Remote Sensing Systems with funding from the NASA Earth Science MEaSUREs Program and the NASA Earth Science Physical Oceanography Program.
Please acknowledge use of this data set when used in your work.
For example, include this citation:
Remote Sensing Systems, 2016, updated MMMYYYY [this should be the date of the file]. Monthly Mean Wind Speed Data Set on a 1 degree grid made from Remote Sensing Systems Version-7 Microwave Radiometer Data, V0701, [accessed on DATE ACCESSED]. Santa Rosa, CA, USA. Available at www.remss.com