NCEP Reanalysis Plotter: Frequently Asked Questions

The following article details most of the information necessary for correctly interpreting plots:

E. Kalnay, M. Kanamitsu, R. Kistler, W. Collins, D. Deaven, L. Gandin, M. Iredell, S. Saha, G. White, J. Woollen, Y. Zhu, A. Leetmaa, B. Reynolds,
M. Chelliah, W. Ebisuzaki, W. Higgins, J. Janowiak, K.C. Mo, C. Ropelewski, J. Wang, R. Jenne, and D. Joseph, 1996: The NCEP/NCAR 40-Year Reanalysis Project. Bull. Amer. Meteor. Soc., 77, 437–471.

Further details and information appear at the CISL Research Data Archive and in an explanation of the annual reanalysis CD-ROMs.

You may purchase reanalysis data, complete with GrADS control files that make plotting exceptionally easy, through the CISL Research Data Archive.

Raw grib files are available for free from the Earth System Research Laboratory.

• Jay Trobec of KELO-TV in Sioux Falls, SD donated the annual CD-ROMs for 2002 and 2003.
• Hank de Wit and Lyndon Grimmer of the Bureau of Meteorology in Kent Town, South Australia donated the annual CD-ROMs for 1995–2001.
• Roswitha Mandix of Deutscher Wetterdienst in Hamburg, Germany donated the annual CD-ROMs for 1983 and 1984.
• Kent Johnson of the Meteorological Service of Canada in Kelowna, British Columbia donated the annual CD-ROMs for 1950–1982, 1985–1994, and 2004–2006.
• Ken Crawford of the University of Oklahoma donated the annual CD-ROMs for 2007 and 2008.
• Wesley Ebisuzaki of NOAA’s Climate Prediction Center processed and provided the data for 2009 through 2016.

Many thanks for helping to maintain the plotter!

Yes, I will consider adding variables to the plotter. I am more likely to add variables provided directly in the reanalysis data. I will evaluate those that require calculations (such as Q-vectors, static stability, etc.) as long as it makes sense to do so based on how the reanalysis data are produced.

The Climate Prediction Center offers plots and data for the NCEP/NCAR 40-Year Reanalysis Project. They also offer plots of GDAS operational analyses, climate monitoring parameters, observations, and model forecasts. The NOAA-CIRES Climate Diagnostics Center also offers a plotter for NCEP data. If you know of any other similar sites, please let me know.

Plot meridional vertical cross sections by checking the first checkbox under map options. Note that these plots display only zonal, monthly averages for each variable. Data are available in the plotter for only geopotential heights, potential vorticity, temperature, winds, and vertical velocity. Select the abscissa range by entering appropriate values in the latitude boxes. The plotter ignores the values in the longitude boxes.

Reanalysis data exist for monthly mean winds at five levels. The NOAA-CIRES Climate Diagnostics Center provides similar information at lower horizontal resolution but at all mandatory levels.

The plotter uses the 6-hourly global reanalysis data included on the NCEP/NCAR 40-Year Reanalysis annual CD-ROM. The data for the plotter are at T62 (209 km) resolution. The ESRL site provides monthly means and daily climatology on a larger grid.

You may use these plots in your article, but I ask that you give appropriate credit to Dr. Christopher Godfrey, the University of North Carolina Asheville, and to the National Centers for Environmental Prediction/National Center for Atmospheric Research 40-Year Reanalysis Project. Though I’ve done my best to check each variable for accuracy, I cannot guarantee that
any of the calculations are correct. You may do well to purchase the data and make the plots yourself. If you choose to use my plots, please send me a copy of the article when you submit it. I’d love to see it!

If you would like to make a loop of, say, five consecutive images with the first image at the time you select under date, check the checkbox next to loop and select 5 from the pull-down menu. Rather than plotting a single image, you have a movie of the five images.

Enter the same latitude or longitude into both boxes under map options. If you enter the same latitude and the same longitude in both boxes, you will get a blank plot.

Check the printer-friendly version checkbox under plot options.

The plotter draws many of the available variables directly from the reanalysis data. For those requiring calculations, explanations of my work appear by clicking on the name of the variable. Yes, these are links, but for clarity I removed the underline. GrADS scripts carry out all of the calculations. If you believe that I have made a mistake, please let me know!

Definitions are on the reanalysis CD-ROM for any particular year in the text/details directory. Some of them are fairly cryptic, but many definitions explain how the variables were calculated. Further information is available from sources listed in question #1.

Station data give information for a single point. GrADS can plot station data, but the information to do so is unavailable in the reanalysis data. Since grid values in the reanalysis data are spatially and temporally averaged, I suggest using another source of data. To estimate values for a small area through visual inspection, use the map options selections to zoom
in on an area and set a small contour interval under plot options.

See the explanation for corrected precipitation rate.

See the explanation for isentropic potential vorticity. To arrive at potential vorticity units, multiply the isentropic potential vorticity in the plot by the temperature (in Kelvin) of the isentropic
surface.

See the explanation for mean sea level pressure. Other sites or analyses very likely employ different sea level pressure reductions. The formulation used by the plotter is based on the formula used by the National Weather Service.

The reanalysis annual CD-ROM only contains data on 315K, 330K, and 450K isentropic surfaces.

The order of the variables in the script determines the order as they are plotted. If you have a compelling reason to switch the order such that a particular variable appears shaded and another appears contoured when selecting both to plot, please let me know and I will switch the order.

Your selections are fed to a CGI script written in Python. The Python script composes and executes a GrADS script, which reads the binary reanalysis data, performs any necessary calculations, and draws a hard-copy plot. Finally, the Python script writes HTML code to display a single image or a JavaScript loop of multiple images.