Title: Why we are interested in QuikSCAT data
1- Why we are interested in QuikSCAT data?
- Coastal mountain chains cause unique wind
patterns - Katabatic winds
- Barrier Jets
- Strong near shore winds
- Curl and Div of wind stress
- are important for ocean/atmosphere coupling
2DATA QuikSCAT Satellite
- Operational from July 1999 to present
- Magnitude and direction of wind at 10 m height
- Twice daily measurements Ascending and
Descending gt averaged for daily - 1800 km wide band
- 25 km resolution, new algorithm 12.5 km
- Cloud coverage doesnt prevent collection
- Heavy rain affects quality
3- Orbits and Swaths
- http//ccrs.nrcan.gc.ca/resource/tutor/fundam/chap
ter2/02_e.php
- An introduction to near real-time QuikSCAT data
- http//www.opc.ncep.noaa.gov/quikscat/HofL05.pdf
- About 15 orbits per day
- 100 per week
- Covers 90 of Earths surface per day
- Data outages during Leonid meteor showers and
some holidays
4Comparison between Buoy and QuikSCAT
5- Validation Complex correlation between daily
mean buoy and daily QuikSCAT - Kundu, P. K. 1976 Ekman veering observed near
the ocean bottom. Journal of - Physical Oceanography, 6, 238-242.
- Ladd, C. and N. A. Bond, 2002 Evaluation of the
NCEP/NCAR reanalysis in the - NE Pacific and Bering Sea. Journal of Geophysical
Research, 107, 3158-3166.
6Getting the Data
- NASA Physical Oceanography DAAC
- http//podaac.jpl.nasa.gov/cgi-bin/dcatalog/fam_su
mmary.pl?ovwqscat - Level 2B (12.5 and 25 km)
- Level 3 gridded (0.25 degree)
- Can also get wind stress (Liu and Large
algorithms)
- IFREMER QuikSCAT and ERS1-2
- http//www.ifremer.fr/cersat/en/index.htm
- Level 2A swath (25 km)
- Level 4 gridded (0.5 degree)
- Can also get wind stress, curl, div, etc.
- E-mail takes around a day for them to process
the data
- Climatology of Glocal Ocean Winds
- http//cioss.coas.oregonstate.edu/cogow
7- Opendap
- http//dods.jpl.nasa.gov/
- Gets subset of netcdf data
- Might be difficult to create long timeseries
- Routines in NCL, MATLAB, IDL
8- ftp podaac.jpl.nasa.gov
- Name anonymous
- Password E-mail address
- cd ocean_wind/quikscat/L3/data/2001
- ls (copy and paste to get filenames for opendap)
- ? (to displace ftp commands)
- prompt
- mget .gz
9ftp//podaac.jpl.nasa.gov/pub/ocean_wind/quikscat/
L3/doc/
Grid Description The QuikSCAT Level 3 data
set is on a simple, rectangular grid of 1440
columns by 720 rows. Therefore, a grid element
spans 0.25 degrees in longitude (360/1440) and
latitude (180/720). Latitude and longitude
coordinates are assigned to each grid element
based on its center. To calculate the longitude
and latitude of a grid point, the following
equations can be used loni (360./XGRID)
(i0.5) for i0...XGRID-1
latj (180./YGRID) (j0.5) - 90. for
j0...YGRID-1 where XGRID grid
elements in the x-direction (1440) YGRID
grid elements in the y-direction (720) As
shown by the above formulas, the latitude and
longitude of the center of the first grid cell of
each QuikSCAT Level 3 scientific data is -89.875
North (89.875 South) and 0.125 East. The
latitude and longitude of the final grid cell of
each data set is centered at 89.875 North and
359.875 East (0.125 West).
10--Jan 19, 2006 --File to read the data using
the data from the /net/storage/isaac
directory begin filessystemfunc("ls
/net/storage/isaac/quikscat/winds/2001/QS")
filo "/workspace/thesis/wind_qk/data/qk_2001.
bin" output file do i0,360 fn
files(i) print(fn) exists
isfilepresent(fn) if(.not.exists) then
print("OPeNDAP test unsuccessful.") print("E
ither file doesn't exist, or NCL does not have
OPeNDAP capabilities on this system") else
f addfile(fn,"r") variables
getfilevarnames(f)
print(variables) will print a list of
variable names on the file end if
asc_u f-gtasc_avg_wind_vel_u(520600,720920)
asc_v f-gtasc_avg_wind_vel_v(520600,720920)
des_u f-gtdes_avg_wind_vel_u(520600,72092
0) des_v f-gtdes_avg_wind_vel_v(520600,720
920) asc_rain f-gtasc_rain_flag(520600,72
0920) des_rain f-gtdes_rain_flag(520600,7
20920) asc_time f-gtasc_time_frac(520600,
720920) des_time f-gtdes_time_frac(520600
,720920) fbinrecwrite (filo, -1,
dimsizes(asc_u) ) fbinrecwrite (filo, -1, i
) fbinrecwrite (filo, -1,
asc_u_at_scale_factorasc_uasc_u_at_add_offset)
fbinrecwrite (filo, -1, asc_v_at_scale_factorasc_va
sc_v_at_add_offset) fbinrecwrite (filo, -1,
des_u_at_scale_factordes_udes_u_at_add_offset)
fbinrecwrite (filo, -1, des_v_at_scale_factordes_vd
es_v_at_add_offset) fbinrecwrite (filo, -1,
asc_rain_at_scale_factorasc_rainasc_rain_at_add_offset
) fbinrecwrite (filo, -1,
des_rain_at_scale_factordes_raindes_rain_at_add_offset
) fbinrecwrite (filo, -1,
asc_time_at_scale_factorasc_timeasc_time_at_add_offset
) fbinrecwrite (filo, -1,
des_time_at_scale_factordes_timedes_time_at_add_offset
) end do end
11- Sources of data and spatial resolution
- The Jet Propulsion Laboratory (web-page reference
1) has swath (level 2B) and gridded (level 3)
meridional and zonal components of the wind
velocity as measured by the QuikSCAT
scatterometer. The temporal resolution is two
maps per day -- ascending and descending. The
spatial resolution is 25 km for the swath data
and 0.25 X 0.25 for the gridded data. - Tang et al (2004) used noisier data from the
QuikSCAT scatterometer along with a modified wind
retrieval algorithm to produce a 12.5 km
resolution wind velocity data set. This data is
intended for the analysis of coastal processes. - CERSAT/IFREMER (web-page reference 2) has gridded
ERS1, ERS2, NSCAT, and QuikSCAT mean surface
winds. The temporal means are weekly for all
except QuikSCAT which has daily means. The
spatial resolution is 1 X 1 for all except
QuikSCAT which has 0.5 X 0.5. - Morsel, Milliff, and Chin (web-page reference 3)
blended NCEP and QuikSCAT winds. This allows for
6-hourly maps of surface winds for July 1999 to
the present. The spatial resolution is 0.5 X
0.5. - Milliff, Large, Morzel, Danabasoglu and Chin
(web-page reference 4) blended NSCAT, ERS-2 and
NCEP winds. This allows for 4-hourly maps of
surface wind for September 1996 to July 1997. The
spatial resolution is 0.5 X 0.5.
Data Web-pages http//podaac.jpl.nasa.gov/cgi-bin/
dcatalog/summary.pl?ovw http//www.ifremer.fr/cers
at/en/data/gridded.htm http//dss.ucar.edu/dataset
s/ds744.4/ ftp//podaac.jpl.nasa.gov/pub/ocean_win
d/nscat/data/csh/millif