tools

Web-based Reanalysis Intercomparison Tools (WRIT)

Created by Cathy.Smith@noaa.gov on - Updated on 10/28/2021 12:14

Web-based Reanalysis Intercomparison Tools  (WRIT) BAMS article: 

  http://journals.ametsoc.org/doi/abs/10.1175/BAMS-D-13-00192.1

A set of web-based reanalysis intercomparison tools (WRIT) is available from the NOAA Physical Sciences Laboratory and University of Colorado CIRES.

 

WRIT Maps WRIT Time-series WRIT Correlations WRIT Trajectories WRIT Distributions

The "WRIT" Maps tool allows users to examine 20CR, ERA-Interim, ERA-20C, JRA-55, MERRA, MERRA-2, NCEP R1, NCEP R2, and NCEP CFSR reanalyses datasets. Pressure level data are available for most reanalyses, as well as 5 single level variables including sea level pressure, 2 m air temperature, 10 m winds, precipitation. Maps and pressure-level by longitude and pressure-level by latitude can be generated for monthly means, anomalies, and climatologies. Observational datasets have been made available that can be compared to 2m air temperature and precipitation. These quantities can be differenced between datasets.

Future enhancements include different time scales.

is also available from WRIT. It allows users to examine 20CR, ERA-Interim, ERA-20C, JRA-55, MERRA, MERRA-2, NCEP R1,  NCEP R2, and NCEP-CFSR as well as some observational dataset. Users can compare timeseries from different datasets, regions, variables and levels. Distributions, scatter plots, and auto-correlation are also available. Statistics for each timeseries including means, standaed deviations, slope and correlations are provided.

The "WRIT" Trajectory Tool is a new tool available from WRIT. It allows users to plot forward and backward trajectories from different reanalyses (currently NCEP R1, NCEP R2, and 20CR with more planned). Users can plot  the trajectories of one or more levels on a single plot. The output is plotted and is available as netCDF and as KMZ files suitable for Google Earth.

Other analysis products are planned.

Feedback and suggestions are welcome. Please give comments/issues/suggestions in the Post a comment or question below.

 

Acknowledgments

The Twentieth Century Reanalysis Project (20CR) used resources of the National Energy Research Scientific Computing Center managed by Lawrence Berkeley National Laboratory and of the Oak Ridge Leadership Computing Facility at Oak Ridge National Laboratory, which are supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231 and Contract No. DE-AC05-00OR22725, respectively. Support is provided by the U.S. Department of Energy, Office of Science Innovative and Novel Computational Impact on Theory and Experiment (DOE INCITE) program, and Office of Biological and Environmental Research (BER), and by the National Oceanic and Atmospheric Administration Climate Program Office. Data are freely available from NOAA, NCAR, the IRI, KNMI, and DOE NERSC.

NASA's Modern Era Retrospective analysis for Research and Applications (MERRA) was developed by the Global Modeling and Assimilation Office (GMAO) and produced through NASA's Modeling, Analysis and Prediction (MAP) program, and is freely available from the Goddard Earth Sciences (GES) Data Information Services center (DISC).

NCEP's Climate Forecast System Reanalysis (CFSR) was developed by the Environmental Modeling Center (EMC) and was partially funded through the NOAA Climate Program Office. It is available free to the public from both NCDC and NCAR.

The ERA-Interim reanalysis is being produced by the European Centre for Medium-Range Weather Forecasts (ECMWF) in Reading, UK. ERA-Interim data with near-real time updates are freely available from the ECMWF data server and from the CISL Data Archive at NCAR. 

WRIT contributes to the Atmospheric Circulation Reconstructions over the Earth (ACRE) Initiative.

WRIT is supported in part by NOAA and by the US Department of Energy Office of Science (BER).

Annonimous (not verified)

Sun, 07/14/2024 - 02:40

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Hi,

Would you mind referring me where I can find daily temperature data from the period 2012-2022 for the the entire world?

Best wishes,

Kris

Yaren Duygu Atalay (not verified)

Wed, 01/24/2024 - 12:40

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Hello, For my master's thesis, I need the wind speed, solar radiation and sunshine hours of the city of Stuttgart in 10-minute periods for the last 5 years. Coould you direct me to access this data please?

 

Hi

Is there any source for multiyear WRIT reanalysis for water equivalence of snow depth for the Mediterranean region. I have tried your interface for ERA5, JRA55, MERRA databses and the option appears to be frozen and not allowed. I am testing a statistical ANN and Cluster analysis model that I utilized to identify possible approximate seasons for snowfall and severe weather events, it worked well for flood risk and severe weather , however i wish to trry it for snowfall/depth using multiyear analogous months or seasons . Any suggestions/solutions for analogous re-analysis for snowfall risk and depth?

 

Thank you B y all results and outcomes. 

Warmest Regards

Mohammed Alkhateeb

Anonymous (not verified)

Thu, 03/20/2014 - 16:24

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Why only 2 time series maximum? Do you plan to increase that number? Since this tool is for INTER-comparison (not just comparison), I would expect this function to be useful. It would be particularly good to allow users to choose a group of the reanalyses to plot.Whereas this is more difficult to do for 2d plots, time series should allow such intercomparison to be performed easily.

While comparing more than one timeseries would be ideal, in the current implementation of the tool, it would not be possible as the entire timeseries at all gridpoints is read in and that is very large. We would need to process the data one timestep at a time instead to have it work on the server. It is still possible this is too resource intensive for a web tool but but if we are able to get more programming resources, it would be a very nice feature and a higher priority than other new features for time series plots.--Cathy

Cathy.Smith@noaa.gov

Mon, 05/06/2013 - 14:06

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When a user selects MERRA pressure level data for time series as one or both of the variables, we now print "Note: MERRA does not interpolate pressure level variables below the surface. Your MERRA timeseries may average "missing" grids. Please check the MERRA maps of the variable to see where this may occur." MERRA maps points to the mapping WRIT page. Is this sufficient? How should we handle pressure level data below the surface? A user could pick a box that has some values below the surface and some not. We could alternatively not allow any comparisons below the surface. We may be able to report average percent of grids in each month available or something like that. Any other ideas?

MERRA 3D atmospheric data were produced without extrapolation to pressure surfaces where the pressure level would be greater than the surface pressure (in other words, under ground). The impact that this has on averaging is discussed here:

http://gmao.gsfc.nasa.gov/research/merra/pressure_surface.php

A third party routine is available to extrapolate continuous pressure levels.

https://reanalyses.org/atmosphere/extrapolation-merra-reanalyses-obtain…

This would be best applied to 3 or 6 hourly fields.

Gintautas (not verified)

Fri, 11/30/2012 - 12:50

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It is a "cool" tool for my students analysing anomalies and compositions, drawing timeseries and trajectories. And all is available without any knowledge in programming, data format or additional data visualisation software. Thanks. Gintas

Anonymous (not verified)

Thu, 08/16/2012 - 15:12

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What we could add or change to page: Ability to composite on a set of dates. Allow users to use own dates More variables (what?) Standardized anomalies. We can consider these though they may require too much time to compute. What we hope to improve. Speed! We know where some of the slowness is and hope to find ways around it. Labeling... Please list other suggestions.

Hi,

I am just starting to work with WRIT. It's proving excellent for all sorts of analyses we're doing but one aspect that I'm struggling to undertake is to extract data for specific seasons or a selected run of months. The option to chose a range of months is there on the page but I'm not having any luck getting it to work. Profuse apologies if I'm missing something obvious.

 

Thanks for providing such great software!

 

Best wishes, Chris 

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How to obtain/plot/analyze data

Created by Cathy.Smith@noaa.gov on - Updated on 08/26/2024 13:09

Data Extraction

  1. NCEI NOMADS and NCMP:  reanalysis (CFSR,NARR,R1,R2); NWP (NAM, GFS, RUC); GENS ensembles, SST
  2. NOAA PSL Search and Plot. (R1,R2,20CR, NARR)
  3. NOAA IRI (CFSR,20CR,R1,R2)
  4. ECMWF: 
    1. ERA5: access via the Climate Data Store https://cds.climate.copernicus.eu/#!/home and https://cds-beta.climate.copernicus.eu/ 
    2. Alternative: https://www.ecmwf.int/en/forecasts/datasets/search 
  5. NASA 
    1. MERRA: GES DISC Data Collections: MERRA
    2. MERRA-2: GES DISC Data Collections: MERRA-2
    3. MERRA and MERRA2 Data Subsetter  (variable list for MERRA-2)
  6. NCAR, Highest-resolution files for all reanalyses, except MERRA. GRIB parameter field extraction using cURL, and some conversion to netCDF as noted. 
    1. JRA-25: Data Access > Web File Listing > Create Your Own File List (e.g. anl_p), use cURL or wget (for files).
    2. JRA-55
    3. ERA5, ERA-Interim
    4. CFSR - (also subset with net CDF format conversion)
    5. 20CR
    6. 20CRv2c
    7. 20CRv3
  7. OpenDAP servers: 
    1. NOAA PSL (20CR,R1,R2,NARR), NCEP, MERRA2D, MERRA3D
    2. MERRA Gridded Innovations and Observations (GIO)
  8. OpenGrADS.org: GrADS software with additional user functionality, including GUI for reanalyses including NCEP and MERRA
  9. Earth System Grid Federation (CFSR, MERRA, 20CR, JRA-25, ERA-Interim) Obs4MIPS: Easy access to NetCDF reanalyses data of selected variables corresponding to the CMIP5 climate model output
  10. GOAT: Geophysical Observations Analysis Tool for MATLAB

Step-by-Step Guide to obtaining data files

Post Processing Routines and Algorithms

  1. Extrapolate MERRA pressure-level data below the surface

Webtools to plot/analyze data by Function

Basic Maps

  1. NOAA IRI (CFSR,20CR,R1,R2)
  2. NOAA PSL Search and Plot (20CR,R1,R2,NARR)
  3. NASA MERRA: Uses Giovanni to produce maps or animations of some monthly fields. Can average over successive times.
  4. NOAA NOMADS (CFSR,NARR,R1,R2)
  5. ECMWF ERA-40, ERA-Interim (Plot maps)
  6. NASA MERRA Atlas
  7. NOAA/PSL Web-based Reanalysis Intercomparison Tool for maps makes user-selected reanalysis fields for monthly data. It can also difference two reanalyses or selected observational datasets with user-selected climatologies.
  8. The Climate Reanalyzer makes user-selected reanalysis fields and differences for monthly data.
  9. MeteoCentre provides pre-generated synoptic maps of SLP, 1000-500 thickness, and 500 hPa height (20CR and R1).
  10. GOAT: Geophysical Observations Analysis Tool for MATLAB

Other Basic Geographic Plots

  1. NOAA PSL:Crossections
  2. NOAA PSL: Search and Plot
  3. MERRA: Uses Giovanni to produce hovmollers of some monthly fields.
  4. The Royal Netherlands Meteorological Institute (KNMI) Climate Explorer
  5. GOAT: Management and Analysis of Geophysical-Data Made Simple for Matlab
  6. Met Data Explorer

Hovmollers

  1. NOAA/PSL: Hovmollers (R1)
  2. IRI
  3. GOAT: Geophysical Observations Analysis Tool:Management and Analysis of Geophysical-Data Made Simple for Matlab

Advanced Plots

  1. NOAA PSL: Can plot monthly, daily and sub-daily of crossections from composite plotting pages (R1). Anomalies are available.
  2. NOAA/PSL: Hovmollers of means, anomalies of daily data. Anomalies are available (R1).
  3. GOAT: Temporal and spatial subsettting is supported via a GUI or built in function. Built-in calculation of anomalies and climatology. Superimpose or show the difference between two fields. Display land-cover or topography.

Composite Maps (Average different, possibly non-contiguous dates together)

  1. NOAA PSL: Can plot composite maps and vertical crossectons from composite plotting pages on monthly, daily and sub-daily time scales for R1. Anomalies are available.
  2. NOAA PSL: Can plot composite maps from plotting pages on monthly, daily and sub-daily timescales for 20CR. Anomalies are available. For monthly, plot composite maps of the 20CR ensemble spread (uncertainty).
  3. GCOS/WGSP: Can plot composite maps of sea level pressure from plotting pages on monthly timescales. Anomalies are available.
  4. WRIT maps: Can plot composite maps of a reanalysis or the difference of composites from two reanalyses.
  5. GOAT: Can plot composites of non-contiguous dates.

Correlation Maps

  1. NOAA PSL WRIT Correlations
  2. NOAA PSL: From monthly NCEP/NCAR R1
  3. KNMI
  4. The Climate Reanalyzer (ERA-Interim, NCEP/NCAR R1, NCEP/DOE R2, 20CR, observational datasets: PRISM precipitation, ERSSTv3b)

Timeseries Plots

  1. NOAA PSL Plot simple timeseries of NCEP/NCAR R1 and 20thC Reanalysis monthly variables
  2. IRI Data Library
  3. Met Data Explorer: Unidata
  4. Web-based Reanalysis Intercomparison Tool for timeseries (WRIT) makes user-selected reanalysis timeseries, scatter plots, cross-correlation functions, and probability density functions for monthly data. It can also difference two reanalyses or selected observational datasets.
  5. The Climate Reanalyzer makes user-selected reanalysis time series with land/ocean masking.

Timeseries Analysis

  1. KNMI: Plot, compute annual cycle, filter and other tools available for time series analysis. Provides many climate/ocean time-series.
  2. NOAA/PSL: Correlate and do some other simple analysis on pregenerated or user supplied monthly time-series
  3. NOAA/PSL: Extract daily timeseries from datasets. Can supply user criteria (e.g. top 10 temperatures in January for a point). R1,20CR
  4. NOAA/PSL: Extract monthly timeseries from datasets.  R1,20CR
  5. IRI Data Library
  6. NOAA PSL: Web-based Reanalysis Intercomparison Tool for timeseries (WRIT) makes user-selected reanalysis timeseries, scatter plots, cross-correlation functions, wavelets, and probability density functions for monthly data. It can also difference two reanalyses or selected observational datasets.

Google Earth

  1. NOAA PSL: Create in KML plots (20CR, R1)

Miscellaneous

  1. NOAA/PSL Lead/Lag for Composites
  2. NOAA\/PSL Lead/Lag for Correlations (maps)
  3. KNMI Smoothed fields, EOF, SVD and other analysis
  4. NOAA/PSL WRIT Trajectory calculator (20CR, CFSR)

 

Applications that read/plot/analyze netCDF and/or grib data (non-web)

A complete list is at Unidata

  1. NCL: NCAR Command Language (no longer updated but has full functionality)
  2. GrADS: The Grid Analysis and Display System (GrADS)
  3. IDV:  Integrated Data Viewer
  4. Ferret: Data Visualization and Analysis: From NOAA/PMEL
  5. NCO: NetCDF Operators. The NCO toolkit manipulates and analyzes data stored in netCDF-accessible formats, including DAP, HDF4, andHDF5. It exploits the geophysical expressivity of many CF (Climate & Forecast) metadata conventions, the flexible description of physical dimensions translated by UDUnits, the network transparency of OPeNDAP, the storage features (e.g., compression, chunking, groups) of HDF (the Hierarchical Data Format), and many powerful mathematical and statistical algorithms of GSL (the GNU Scientific Library). NCO is fast, powerful, and free.
  6. CDO: Climate Data operators.  A collection of command-line operators to manipulate and analyze climate and numerical weather prediction data; includes support for netCDF-3, netCDF-4 and GRIB1, GRIB2, and other formats.
  7. MATLAB
  8. IDL: Interactive Data Language
  9. CDAT Community Data Analysis Tools: CDAT: Note this will be replaced soon by xCDAT
  10. xCDAT: xCDAT is an extension of xarray for climate data analysis on structured grids. It serves as a spiritual successor to the Community Data Analysis Tools (CDAT) library.
  11. GOAT: Geophysical Observations Analysis Tool:  A MATLAB based tool that integrates with NetCDF files and OPeNDAP sources.

 

 

 

khaled Megahed (not verified)

Sun, 03/06/2022 - 12:47

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Dear Sir,

I would like to open ERA5 grid data that was downloaded from ECMWF.

Could you please send me some code to open and read with a visualize such kind of data.

I wait your reply as soon as possible.

Best wishes

Khaled

solgunta@123

Mon, 10/08/2018 - 23:15

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Please can anyone help me? I failed install NCL on my window platform, i fallowed the instruction but could not start to work. 

Moses Monday (not verified)

Fri, 08/04/2017 - 19:15

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I really need help. 

I want to download data for 

-Incoming shortwave and outgoing shortwave radiation 

-Incoming longwave and outgoing longwave radiation 

-Albedo and net radiation. 

Location: Lagos Nigeria 

These data must be hourly with good resolution. 

Please any help? 

Thanks 

 

Moses,

A couple of points. MERRA, MERRA-2 and CSFR have 1 hourly data, others may too, you should review the characteristics of these and others to see which best suits your needs. When you say resolution must be good, do you mean spatial resolution? And if so, what is good resolution?

Keep in mind that when using reanalysis data, the radiation parameters are strongly dependent on *modeled* cloud fields.  This can lead to significant uncertainty in the values. 

Once you figure out which you want, then you can start looking to see if they have tools that permit the download of point data (MERRA/MERRA-2 both do).  Their documentation is listed here.

For there ERA5

https://www.ecmwf.int/en/newsletter/147/news/era5-reanalysis-production

For CFSR

https://www.ncdc.noaa.gov/data-access/model-data/model-datasets/climate-forecast-system-version2-cfsv2#CFS%20Reanalysis%20(CFSR)

The 20CRV2c has 3 hourly data for surface fluxes. The MERRA and ERA have higher spatial resolution. 

As the others asked, what time period?

andy (not verified)

Thu, 05/04/2017 - 07:34

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Hi, 

 

Need to plot streamlines using ECMWF winds (U and V) over Asian region ...Can I have matlab code?

Cathy.Smith@noaa.gov

Fri, 05/19/2017 - 09:53

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While I don't think matlab has an email list, they do have extensive help pages. I searched and see

https://plot.ly/matlab/streamline-plots/

https://www.mathworks.com/help/matlab/ref/streamline.html

https://www.mathworks.com/help/matlab/ref/stream2.html

They also have libraries to read netCDF files.

 

Cathy S.

 

 

For GrADS, this page has an example http://www.jamstec.go.jp/frsgc/research/iprc/nona/GrADS/plot-strem-line.html You can use this plotting page http://www.esrl.noaa.gov/psd/cgi-bin/data/testdap/plot.comp.pl to plot zonal means of meridional winds (and omega) to look at the Hadley cell. NCL will also plot streamlines http://www.ncl.ucar.edu/Applications/stream.shtml Cathy Smith

I'd like to access from 20CR (ver 2c) daily rainfall for a specific lat/lon reference point. Is there a relationship between the daily pr_wtr output variable and the monthly mean prate variable? Is it valid to compare actual daily rainfall with data derived from pr_wtr?

Sebastian Krogh (not verified)

Wed, 12/02/2015 - 11:44

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Hi, I trying to extract daily incoming shortwave from ERA-I, the variable is ssrd (Surface solar radiation downwards), which I downloaded from ECMWF website (http://apps.ecmwf.int/datasets/data/interim-full-daily/levtype=sfc/). The problem is that the daily values that I obtain from ERA-I are too low. ssrd comes in J/m2 and in a daily resolution (I cannot get higher temporal resolutions), and I get values up to 7 MJ/m2/d, in which values around 20+ MJ/m2/d are expected for mid-summer in this location (lat = 68N Lon 134W). Has anyone run into these problems with radiation (not able to download subdaily radiation and getting too small values). Any answer is appreciated, thanks Sebastian

These are not daily values. If you look above "Select parameter" you will see "Select step" and "Select time". Time (and date) are the start time of the forecasts (twice daily) and step is the number of hours into the forecast. Ssrd is an accumulated field, from the beginning of the forecast to the particular step. Steps are 3 hourly, out to 12 hours. However, note that further steps, out to 240 hours are available with batch access, see "Access Public Datasets" in the left hand menu. To convert Jm-2 to Wm-2, simply divide by the number of seconds in step hours ie step*60*60.

Dear Toihir, I'm not sure what a SAGE II V7 file has to do with reanalysis, but perhaps these suggestions will help. I suggest you consult the lead author of any reference you are using for the SAGE II data, or consult with the data center from which you procured the data. From a google search on SAGE II, I see that the SAGE II home page is http://sage.nasa.gov/SAGE2/ . Read software is provided at https://eosweb.larc.nasa.gov/project/sage2/sage2_v7_table . Both Fortran and IDL code are provided there, so some modification will be necessary for matlab. I suggest you consult with a local matlab expert about how to interpret either the Fortran or IDL. best wishes

Anonymous (not verified)

Mon, 03/09/2015 - 17:17

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I have been puzzled about odd looking scales in some downloaded ERA-I netCDF files. However, I have found out about scale factors and add-offset. However, when I apply them to some datasets, e.g. temperature and mean SLP, the new "unpacked" values are quite obviously not right, and the original values were. I tried to check by downloading an equivalent grib file, converting to net CDF with cod then examining the new output values. They were the same as the packed version. This is confusing. Heat flux values on the other hand seem wrong in both packed and unpacked, as ocean values in the Arctic (Barents Sea) appear more negative than do those over the ice.

To assist you, anyone will probably need significantly more information. I suggest you start a page at reanalyses.org under Help (visible once authenticated) and describe precisely what you steps you followed and what values you are seeing. Including screen shots of the data access request and then the output of ncdump will be helpful.

I can offer some general advice, but as Gilbert Compo said, a precise answer would require more information. Firstly, beware that some software automatically unpacks netCDF data. Also note, that the scale factors and add-offset vary from variable to variable and file to file. ERA-Interim fluxes, defined to be positive downwards, are accumulated from the beginning of the forecast for +step hours, so you need to divide by the number of seconds in step to obtain units in "per second".

Hi subramanyam , In order to help, anyone looking at this would need to have a link to the data you are trying to open. Grads and opengrads are similar in their capacity to open files. You may prefer to search the grads forum, then ask this question if it hasn't already been discussed. I did a quick google search and found:

http://gradsusr.org/pipermail/gradsusr/2012-December/033787.html

Good Luck

Dear Subramanyam, It looks like bug reports for opengrads are entered at http://sourceforge.net/p/opengrads/bugs/ I suggest submitting a detailed bug report, including the particular CMIP5 file that is causing the problem, and any error messages. Additionally, try downloading the CMIP5 files that are causing problems, or demonstrate that some other software opens it correctly in your bug report. best wishes,

Camiel Severijns (not verified)

Tue, 03/04/2014 - 04:26

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I think I have found a problem with the longitude coordinate of the data files of the 20CR under http://portal.nersc.gov/archive/home/projects/incite11/www/20C_Reanalysis/everymember_grib_indi_fg_variables ncl_convert2nc fails to convert these files. CDO does convert them to NetCDF but after this the longitude coordinate values range from about -1.8 to 0 (from West to East). The latitude coordinates are correct. The CDO operator setgrid,t62 fixes this problem.

Camiel, Does your cdo returned netCDF file show grid_type = "gaussian" before you use setgrid,t62 ? When I use cdo on these files without the setgrid,t62 I see that metadata. The longitude coordinate goes from 0 to 358.125. But, we use "wgrib" to separate out each ensemble member as a separate grib file before passing to cdo. Perhaps the ensemble dimension is confusing cdo? Looks like by specifying the setgrid,t62 you have found a great workaround to a cdo problem! thanks for sharing this, best wishes, gil

Anonymous (not verified)

Fri, 02/21/2014 - 11:34

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Yeah, I agree that it is better to read every single ensemble member out from TMP.2m.1871.grb type files and convert them to be nc files. It works for me in this way. But I use "cdo -f nc copy filename.grb filename.nc" to convert grb files to be nc files. Thanks.

Camiel Severijns (not verified)

Wed, 02/19/2014 - 03:07

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To force an ensemble of ocean model experiments I would like to use (near) surface data from individual members of the 20CR. I downloaded a file 187501_sfcanl_mem01.tar which I assume contains the data I am looking for. However, the files in this tar-file are not in GRIB format. The first few bytes contain the string 'GFS SFC'. Can anyone tell me how this files are formatted?

Dear Camiel, For the GRIB formatted data from the NERSC Science Tape Gateway at http://portal.nersc.gov/archive/home/projects/incite11/www/20C_Reanalysis/everymember_full_analysis_fields you want the surface flux grib files "sflx", rather than the binary "sfcanl" files. E.g. for the first member of the 0 to 3 hour forecast 187501_sflxgrbens_fhr03_mem01.tar and the first member of the 3 to 6 hour forecast 187501_sflxgrbens_fhr06_mem01.tar These are the file types that most other groups have used. Alternatively, you may want to obtain only your variables of interest. If a variable that you need is not at http://portal.nersc.gov/archive/home/projects/incite11/www/20C_Reanalysis/everymember_grib_indi_fg_variables we can generate it if it is in the "sflx" files. Obtaining the individual variables you need, rather than the complete "sflxgrbens" file may save transfer time. Please reply if you one or the other of these solutions does not work for your purposes. best wishes, gil compo

Dear Gill, I have found the data files and tried to convert the grib files to netcdf using ncl_convert2nc (version 6.1.2). This tool stops with the following warnings (there are lots more of those preceeding) and two fatal errors: warning:./TMP.2m.1871.ens.grb->TMP_98_HTGL is missing ens: 54 it: 12/31/1871 (18:00) ft: 6 warning:./TMP.2m.1871.ens.grb->TMP_98_HTGL is missing ens: 55 it: 12/31/1870 (18:00) ft: 3 warning:./TMP.2m.1871.ens.grb->TMP_98_HTGL is missing ens: 55 it: 12/31/1871 (18:00) ft: 6 fatal:NclGRIB: Couldn't handle dimension information returned by grid decoding fatal:NclGRIB: Deleting reference to parameter because of decoding error Classic model NetCDF does not support string types, converting initial_time1 to a character array Dimension 'ncl_strlen_0' will be added Classic model NetCDF does not support string types, converting ensemble0_info to a character array Dimension 'ncl_strlen_1' will be added Do you know what might be the problem here? Thanks, Camiel

Camiel, I was able to use ncl_convert2nc 6.0.0 to convert the file sflxgrbens_fhr03_1871010100_mem01 (add .grib suffix) to netcdf. This file is contained in the tarfile accessed from http://portal.nersc.gov/archive/home/projects/incite11/www/20C_Reanalysis/everymember_full_analysis_fields/1871/187101_sflxgrbens_fhr03_mem01.tar Conversely, when I tried the file TMP.2m.1871.ens.grb accessed from http://portal.nersc.gov/archive/home/projects/incite11/www/20C_Reanalysis/everymember_grib_indi_fg_variables/TMP/TMP.2m.1871.ens.grb.tar I get ncl_convert2nc error messages very similar to yours. I access the TMP.2m.1871.ens.grb in python. I suspect that there is a bug in the ncl_convert2nc for very large files. You may want to use wgrib http://www.cpc.ncep.noaa.gov/products/wesley/wgrib.html to slice up the file into smaller pieces and see if that works. Alternatively, since the sflxgrb file does work with ncl_convert2nc, perhaps using those will be better? best wishes, gil

Camiel, You may want to see if you can enable the "large file support" in ncl_convert2nc. compo/test_ncl_convert2nc> ncl_convert2nc -h ncl_convert2nc inputFile(s) OPTIONS inputFile(s) name(s) of data file(s) [required] [valid types: GRIB1 GRIB2 HDF HDF-EOS netCDF shapefile] [-i input_directory] location of input file(s) [default: current directory] [-o output_directory] location of output file(s) [default: current directory] [-e extension] file type, defined by extension, to convert [example: grb] [-u time_name] name of the NCL-named time dimension to be UNLIMITED [-U new_time_name] if -u is specified: new name of UNLIMITED variable and dimension [-sed sed1[,...]] GRIB files only; set single element dimensions [default: none] choices are initial_time, forecast_time, level, ensemble, probability, all, none [-itime] GRIB files only; set initial time as a single element dimension (same as -sed initial_time) [-ftime] GRIB files only; set forecast time as a single element dimension (same as -sed forecast_time) [-tps] GRIB files only; remove suffix representing a time period (e.g. 2h) from statistically processed variables, leaving only type of processing as a suffix (e.g. _acc, _avg) [-v var1[,...]] user specified subset of variables [default: all variables] ncl_filedump can be used to determine desired variable names [-L] support for writing large (>2Gb) netCDF files [default: no largefile support] Note, though, from the ncl_convert2nc help page http://www.ncl.ucar.edu/Document/Tools/ncl_convert2nc.shtml -L Specifies that the resultant netCDF output file may exceed 2Gb in size on platforms that have "large file support" (LFS). However, no single variable may exceed 2Gb in the current implementation. You may need to slice out individual ensemble members for ncl_convert2nc to work on the TMP.2m.1871.grb type files. I hope that this helps. best wishes, gil

Hi Gil, After extracting the T2M data for one member only, ncl_convert2nc still fails with the same error (-L option makes no difference). CDO has no problems with converting the single member GRIB file to NetCDF. The variable name is wrong but this can be fixed. My guess now is that something is wrong with ncl_convert2nc. Regards, Camiel

Unfortunately, it is not straight forward to automate the download of ERA-Interim and ERA-40 fields. I do have automated routines for the conversion of ERA-40 and ERA-Interim to GOAT format but you need to download the NC files yourself. If you are interested in monthly means, some of these are available at the goat-geo.org site. I can add more upon request. GOAT does support automated download for NCEPI, NCEPII, 20CRenalysis, ORAS4, TRMM, CloudSatCalipso composite, ERSST, MERRA, and others.

Masatomo Fujiwara (not verified)

Fri, 12/27/2013 - 18:45

Permalink

I think you had better look at the original satellite ozone measurements for your purpose. The Stratospheric Processes and their Role in Climate (SPARC) project has been doing ozone measurement validation and evaluation for many years. Please go to http://www.sparc-climate.org/activities/ozone-profile-ii/ and contact with the activity leaders shown there, and/or check "Website for further information" at the end of the page (i.e., http://igaco-o3.fmi.fi/VDO/index.html). Actually, there are several choices for satellite ozone measurements, but the latest version SAGE data set may be most useful for you. For ozone in the reanalyses, I think we need validation and evaluation before using it for climate studies. The SPARC Reanslysis Intercomparison Project (S-RIP, http://s-rip.ees.hokudai.ac.jp/index.html) has this component. For your information, the following is my quick survey for the 9 reanalyses. Please confirm by yourself by checking the references. NCEP/NCAR & NCEP/DOE: (Kalnay et al., 1996; Kistler et al., 2001; Kanamitsu et al., 2002): - Zonally averaged seasonal climatological ozone used in the radiation computation - (In NCEP/DOE, the latitudinal orientation was reversed north to south) ERA-40: (Uppala et al., 2005; Dethof and Holm, 2004): - TOMS and SBUV ozone retrievals (not radiance) are assimilated (1978-). Ozonesondes not assimilated. - Ozone in the ECMWF model is described by a tracer transport equation including a parametrization of photochemical sources and sinks. - The ozone climatology is used in the radiation calculations of the forecast model. ERA-Interim: (Dee et al., 2011; Dragani, 2011): - TOMS, SBUV, GOME (1996-2002), MIPAS (2003-2004), SCIAMACHY (2003-), MLS (2008-), OMI (2008-) are assimilated. SAGE, HALOE, and POAM are not assimilated. – Ozone model and radiation calculations are basically the same as ERA-40. JRA-25: (Onogi et al., 2007): – Ozone observations are not assimilated directly. – Daily ozone distribution is prepared in advance using a CTM with “nudging” to the satellite total ozone measurements and provided to the forecast model (the radiative part). JRA-55 (Ebita et al., 2011): - similar to JRA-25 for 1979-; monthly climatology for -1978 MERRA: (Rienecker et al., 2011): – SBUV2 ozone (version 8 retrievals) is assimilated for Oct 1978–present. – The MERRA AGCM uses the analyzed ozone generated by the DAS. (cf. a climatology for aerosol) NCEP-CFSR: (Saha et al., 2010) – SBUV profiles and total ozone retrievals are assimilated (but not bias-adjusted; should not be used for trend detection) – Prognostic ozone with climatological production and destruction terms computed from 2D chemistry models (for radiation parameterization) 20CR: (Compo et al., 2011): – "A prognostic ozone scheme includes parametrizations of ozone production and destruction (Saha et al., 2010)."

gilbert.p.comp…

Fri, 12/27/2013 - 13:23

Permalink

Dear samudraval59, Some atmospheric reanalyses, such as NCEP/NCAR http://reanalyses.org/atmosphere/overview-current-reanalyses#NCEP1 do not provide ozone. some, such as CFSR http://reanalyses.org/atmosphere/overview-current-reanalyses#CFSR, ERA-Interim http://reanalyses.org/atmosphere/overview-current-reanalyses#ERAINT, MERRA http://reanalyses.org/atmosphere/overview-current-reanalyses#MERRA provide ozone on levels. Links to the data are provided at each overview. 20th Century Reanalysis (20CR) http://reanalyses.org/atmosphere/overview-current-reanalyses#TWENT provides only the total column ozone. Note that while ozone is prognostic in 20CR, that system assimilates only surface pressure. Please read the linked references to determine what each system is doing and what data are being assimilated, particularly related to ozone. Links to various tools are given on this page where you left this comment, i.e., http://reanalyses.org/atmosphere/how-obtainplotanalyze-data and are also http://reanalyses.org/atmosphere/tools . If those do not include ozone, you may want to leave a comment on each page or use the contact on the respective linked sites. For the Web-based Reanalysis Intercomparison Tool, you can leave comments at https://reanalyses.org/atmosphere/web-based-reanalysis-intercomparison-tools-writ best wishes, gil compo

samudralav59 (not verified)

Fri, 12/27/2013 - 11:40

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My present work of study of warming regimes and the trends require me acquire and capture data and analysis tools on open domain vis-à-vis ozone profiling, the ozone mixing ration and partial pressures.I would be very grateful if I could be given a peek to get the above in the most reliable free sources. thanking you. Samudrlav59

Luigi (not verified)

Wed, 06/12/2013 - 12:59

Permalink

Dear reanalyses.org I am trying to get daily weather data from CFSR to run an ecosystem model for a geographic area (say Italy) by using the NCDC OPENDAP server, e.g. http://nomads.ncdc.noaa.gov/thredds/dodsC/modeldata/cmd_flxf/2000/200005/20000504/flxf01.gdas.2000050400.grb2.html but with no luck so far. I was wondering whether there is a more direct way to get daily time series data (in ASCII) from CFSR that people uses routinely. Daily time series for surface parameters such as max/min temperature, solar radiation, precipitation, relative humidity, and wind, are standard for ecosystem models as life works on a circadian rhythm on Earth. Thanks for any hint and kind regards, Luigi

Easwar (not verified)

Thu, 05/30/2013 - 04:08

Permalink

Dear sir, I need historiacl /longterm wind data for a specific site in order to obtain correlation with actual data/nearby metmast data,so how can i get it ?and where from?.Kindly guide me with a procedure to download the data with an exact link. Regards, Easwar.

Dear Easwar, Happy to help, but this area is for reanalysis data. See http://reanalyses.org/ for the definition of reanalysis data. This may be what you need but your question is not clear in this respect. If you want data from a station, you should post your question in the Observations area http://reanalyses.org/observations/surface . Is your site over the ocean or over land? How close do the data need to be to your site? What is your site location? While posting at http://reanalyses.org/observations/surface, you may want to make your question a bit clearer. What do you mean by "historical/longterm" wind data? Do you want a long-term average or do you want a long time series at some temporal resolution? What is the temporal resolution you need? What is the temporal resolution you can still use (e.g., monthly averages, daily averages, once-per-day)? What is the height of the data you need? Do you want data from satellites, such as scatterometers? By providing more information in the Observations area, someone may be able to help you better. best wishes, gil compo

gilbert.p.comp…

Wed, 01/25/2012 - 10:14

Permalink

Stefan,

Adding panoply is a great idea, but Reanalyses.org is a wiki site that depends on users. You can login and add it where you feel it is appropriate. If you have any questions, please feel free to ask or add a question to the Help section.

best wishes,
gil compo

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Tools

Created by Cathy.Smith@noaa.gov on - Updated on 12/29/2020 12:06

List of web-based tools for comparing reanalysis datasets:

 

GOAT (Geophysical Observation Analysis Tool) is a free MATLAB based tool for the analysis and visualization of various types of geophysical data.

GOAT archives all geophysical data in a consistent format thereby alleviating many of the annoyances related to the inconsistency of spatial and temporal resolutions, naming, units and file formats across the ever growing number of observed and simulated geophysical datasets. 

 

Andy Barrett (not verified)

Thu, 12/20/2018 - 12:53

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Nice tool.  However, the MERRA-2 global average precipitation rate is different from that shown in figure 6 Bosilovich et al, 2017, Atmospheric Water Balance and Variability in the MERRA-2 Reanalysis, J. Clim, 30.

I can send a screen shot and the plot if you need, just email me.

The plotting options I used are:

Dataset: MERRA-2

Variable: Precipitation Rate (note selecting this variable gives an option to select a level, I assume this is irrelevant but selected 1000 hPa)

Time averaging: None

Variable statistic: mean

Grid Point: -90 to 90 N, 0 to 360 E, no mask (All)

Output type: time series

Smoothing: 12 month running mean

Cheers

Andy Barrett

NSIDC, CIRES, University of Colorado at Boulder

There are two global precipitation fields in the MERRA-2 flux data collection. PRECTOT is determined from the model physics and represents the condensation sink of water vapor out of the atmosphere. However, this field is not used for water source/forcing in the land surface.  PRECTOTCORR was developed by Reichle et al. to provide observation corrected precipitation to the land surface.  Fig 6 is PRECTOT, the modeled precipitation.  Make sure that PRECTOTCORR isnt being presented without explaining its purpose.

There is a substantial difference between these two fields over land. These need consideration in any water budget study.

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Comparison

Created by Cathy.Smith@noaa.gov on - Updated on 04/27/2017 22:53

Climate Comparisons in the MERRA Atlas

The MERRA Atlas provides monthly, annual, seasonal and climate comparisons among several of the latest atmospheric reanalyses (including ERA-Interim, CFSR, and JRA25) and various global observation datasets.

Reanalysis Comparisons on the WRIT webpages

The NOAA-CIRES Web-based Reanalysis Intercomparison Tools (WRIT) has a prototype plotting/comparison page that is available for testing and commenting by reanalyses.org users and others. To obtain a login to reanalyses.org go to Create New Account.

Observational Studies that examine reanalysis datasets and compare them and observations are described here.

Inter-reanalysis studies that intercompare reanalyses are described here.

WCRP Task Team for the Intercomparison of ReAnalyses (TIRA) - A group of reanalysis developers and users charged to develop a broad reanalysis intercomparison project.

 

SPARC Reanalysis Intercomparison Project 

A coordinated activity under the WCRP/SPARC focusing on reanalysis output in the stratosphere, upper troposphere, and lower mesosphere. 

 

Tables:

Reanalyses.org Overview Comparison

ClimateDataGuide Summary and Comparison

Ana4MIPS Data Description

 

While NCEP/NCAR is using a much older model for the first guess, and an older data assimilation system, it is still widely used around the world. The main paper on the NCEP/NCAR reanalysis, Kalnay et al. (1996) http://dx.doi.org/10.1175/1520-0477(1996)077<0437:TNYRP>2.0.CO;2. , specifically lists the expected quality of surface-related variables. For the case of southern africa, the recent paper Zhang et al (2012) http://dx.doi.org/10.1007/s00382-012-1423-z examines precipitation. You can make quick comparisons of several surface variables using the Web-based reanalysis intercomparison tool or other tools listed at https://reanalyses.org/atmosphere/tools. The other question you need to ask is what observations are included. The 2m air temperature from stations is indirectly assimilated in ERA-Interim, while it is not in NCEP/NCAR. Please let us know of other questions, or if anything can be clarified. best wishes,

ERA-Interim (like ERA-40 and the JRA reanalyses, but unlike the NCEP/NCAR reanalysis) used the 2m temperature observations to produce its 2m temperature values. Any comparisons thus have to be carried out particularly carefully. We did this recently for the Arctic (Simmons & Poli, doi: 10.1002/qj.2422), though for instantaneous temperatures not daily means. This paper and a couple of Simmons et al. papers it refers to provide details on how we analyse screen-level observations. The ERA-Interim system (which is more than nine years old) is rather limited in the feedback information it saves from its 2m temperature analysis. This will be remedied in the replacement for ERA-Interim that is currently being prepared for production.

jeff.knight

Tue, 08/19/2014 - 12:00

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I am no expert on reanalyses, so I thought I would ask this community this question.

I have been comparing 20cr to ncep/ncar reanalysis. I have computed DJF mslp anomalies wrt 1981-2010 over part of the North Atlantic (40W-5E, 45-70N). Not only do the two agree very well in the overlap period but there is very little spread in the 20cr ensemble in values going back to 1900. Perhaps to be expected, but I am very pleased by this!

For 850hPa T over part of North America (70-110W, 40-65N), however, the range in the early part of the series is larger and while the comparison with the ncep/ncar shows reasonable agreement in terms of the year-to-year variations, there are instances where the ncep/ncar data are outside the range of the 20cr ensemble, even in the most recent years.

Presumably ncep/ncar is a better estimate in recent times as it includes radiosonde/satellite observations, but would the range of the 20cr be expected to include the other reanalysis? Or is that not expected based on the biases in the underlying model?

Any guidance would be very gratefully received.

Ideally you would expect the 20CR range to cover the other reanalyses in most instances if both are unbiased and NCEP/NCAR is error free. Temperatures in 20CR have problems over the Arctic, so there might be biases in the northernmost part of your domain (and they have a seasonal cycle), and generally that region is not very well represented prior to around 1940. But other than that, I am not aware of problems so if you could name the instances that might help further. Stefan Brönnimann

I'm new to this site and have just prepared a page in my own 'area'. After some fiddling around, I seemed to get something going, though will need some fine-tuning as I re-learn Wiki. It deals with an issue regarding some trends in the US Reanalysis data sets and I've obtained some EC data for comparison. Hence it will have some focus on comparison, so I suppose the heading of this thread is apt.

My question is: If I have done the right thing by doing it in my area, how do I get it linked into the main site for others to have a read?

Sorry for troubling you but I sincerely think is an important issue for the folks here to consider.

I warmly appreciate what the site is about and look forward to helping the cause.

Dave

Dave, Happy to help. Welcome! Please be very specific when you refer to something. What is "EC data"? This could refer to Environment Canada or sometimes to the European Centre for Medium Range Weather Forecasts. When you are authenticated, look at the Help area. Directions for how to link and how to include images should be there, e.g., https://reanalyses.org/help/how-edit-site Please put Help related comments under the Help area if at all possible. Then the Help pages can themselves be updated as your questions are answered. best wishes, gil compo

To answer the question about the link, it should probably be linked from here https://reanalyses.org/atmosphere/inter-reanalysis-studies-0 On there top bar, there is a help link. If you click it, it tells you how to a) create the page and b) link to it. If you have problems, comment and we will try to help/improve directions. Cathy

Ashwini Jain (not verified)

Tue, 11/05/2013 - 12:07

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I am using wind velocity and I want to calculate it at a height of 80mtrs from the ground . So could you tell me that at what height from the ground these data have been taken????

michael.bosilovich

Tue, 11/05/2013 - 12:42

Permalink

Typically, there is meteorology produced at 2m and 10m above the surface. MERRA produces winds at 50m, and also the lowest model level. the lowest model level does not have a fixed height above the surface, but the geopotential height of the lowest model level is also provided. pressure level wind profile data is also provided, but again, not at a fixed height, geopotential height is provided. 80m is an atypical height for most reanalysis output. In the case of MERRA, you would need the 2 lowest model levels to interpolate to that height. These are available in 3D data files, but, there would be a substantial amount of work to get the interpolated winds.

Another general answer to your question is to read the documentation associated with the reanalysis system that you are using to determine which height the data are at, in case it is not obvious (such as u2m and v2m).

I hope this helps,

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analysis software

Created by Cathy.Smith@noaa.gov on - Updated on 07/18/2016 10:13

List of Plotting/Analysis Software useful for Reanalysis Datasets

  1. CDAT: Climate Data Analysis Tools (CDAT) is a software system designed to provide access to and management of gridded climate data. It uses the Python scripting language which provides a general purpose and full-featured scripting language with a variety of user interfaces including command-line interaction, stand-alone scripts (applications) and graphical user interfaces (GUI). The modular CDAT subsystems provide access to the data, to large-array numerical operations (via Numerical Python), and visualization.
  2. Ferret*: Ferret is an interactive computer visualization and analysis environment designed to meet the needs of oceanographers and meteorologists analyzing large and complex gridded data sets. It runs on most Unix systems, and on Windows XP/NT/9x using X windows for display.
  3. GrADS*: The Grid Analysis and Display System (GrADS) is an interactive desktop tool that is used for easy access, manipulation, and visualization of earth science data. GrADS has two data models for handling gridded and station data. GrADS supports many data file formats, including binary (stream or sequential), GRIB (version 1 and 2), NetCDF, HDF (version 4 and 5), and BUFR (for station data). GrADS has been implemented worldwide on a variety of commonly used operating systems and is freely distributed over the Internet.
  4. IDL*: IDL is a commercial cross platform data analysis/mapping/plotting code that is extremely customizable.
  5. IDV*: is a Java(TM)-based software framework for analyzing and visualizing geoscience data. The IDV brings together the ability to display and work with satellite imagery, gridded data, surface observations, balloon soundings, NWS WSR-88D Level II and Level III radar data, and NOAA National Profiler Network data, all within a unified interface. 
  6. Matlab: MATLAB is a high-level language and interactive environment w/extensive plotting and numerical processing available.
  7. 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.
  8. NCL*: Is an interpreted language designed specifically for data analysis and visualization.
  9. Panoply: Panoply is a cross-platform application which plots geo-gridded arrays from netCDF, HDF and GRIB datasets. You can plot data as well as do some simple data analysis. Outputs are images, postscript and kml

     

*'d are OPeNDAP enabled

Dataset Analysis Tools

  1. Excel: A desktop analysis tool. It can read netCDF files.
  2. CDO: CDO is a collection of command line Operators to manipulate and analyse Climate and forecast model Data.

    Supported data formats are GRIB, netCDF, SERVICE, EXTRA and IEG. There are more than 400 operators available.
  3. NCO: A (free) suite of programs that operate on netCDF files. Each operator is a standalone, command line program which is executed at the UNIX (or NT) shell-level like, e.g., ls or mkdir. The operators take netCDF or HDF4 files as input, then perform a set of operations (e.g., deriving new data, averaging, hyperslabbing, or metadata manipulation) and produce a netCDF file as output. The operators are primarily designed to aid manipulation and analysis of gridded scientific data. These tools are a powerful and easy way to perform simple manipulations on netCDF files without a major programming effort.

Read Files Remotely

  1. GDS: The GrADS Data Server (GDS, formerly known as GrADS-DODS Server) is a stable, secure data server that provides subsetting and analysis services across the internet.
  2. TDS: The THREDDS Data Server (TDS) is a web server that provides metadata and data access for scientific datasets, using OPeNDAP, OGC WMS and WCS, HTTP, and other remote data access protocols.

 

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