Overview of current atmospheric reanalyses

Submitted by Cathy.Smith@noaa.gov on Thu, 10/07/2010 - 12:47

 

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Current / State-of-the-art: 

ASR | ERA-20C | ERA-20CM | ERA-Interim | JRA-55, JRA-55C, JRA-55AMIP | MERRA-2 |  NCEP CFSR | NOAA-CIRES 20CRv2c
 

Possible issues: Consider other datasets for use in new research projects: NCEP/DOE II  | NCEP/NCAR NCEP NARR 

Superseded / Caution use for new research projects: ERA-40 | ERA-15 JRA-25
 

Model Change: NCEP CFSR (2011 and after)
 

Updated in real-time for public use (days behind): NCEP/DOE II  | NCEP/NCAR NCEP NARR  | NCEP CFSR? |  JRA-55 (2 days behind from JMA suite) |
Updated in near real-time for public use (months behind)ERA-Interim | JRA-55 | MERRA-2
Updated irregularly for public use (years behind): ERA-20C | ERA-20CM | NOAA-CIRES 20CR NOAA-CIRES 20CRv2cNASA MERRA

 

Overview Comparison Table (Reanalyses.org)

Overview Comparison Table (ClimateDataGuide)

Questions and Comments

 

Arctic System Reanalysis (ASR): 2000-2012

The Arctic System Reanalysis (ASR), a high-resolution regional assimilation of model output, observations, and satellite data across the mid- and high latitudes of the Northern Hemisphere for the period 2000 – 2012 has been performed at 30 km (ASRv1) and 15 km (ASRv2) horizontal resolution using the polar version of the Weather Research and Forecasting (WRF) model and the WRF Data Assimilation (WRFDA) System.

Source: Polar Meteorology Group, Byrd Polar & Climate Research Center, The Ohio State University

Time Range: 2000-2012

Assimilation: WRFDA-3DVAR

Dataset Output Times and Time Averaging: 3-hourly for surface and upper air fields, Monthly means of selected variables

ASRv1 – 30 km
Model Resolution: 30 km, 71 sigma levels
Dataset location: http://rda.ucar.edu/datasets/ds631.4/
ASRv2 30 km is expected early 2017

ASRv2 – 15 km
Model Resolution: 15 km, 71 sigma levels
Dataset location: http://rda.ucar.edu/datasets/ds631.4/ - Will become available during second half of 2016

Data Access: Polar Meteorology Group

References | ClimateDataGuide

ECMWF ERA-20C: 1900 - 2010

ERA-20C is ECMWF's first atmospheric reanalysis of the 20th century, from 1900-2010. It is an outcome of the ERA-CLIM project.

ERA-20C was produced with the same surface and atmospheric forcings as the final version of the atmospheric model integration ERA-20CM. A coupled Atmosphere/Land-surface/Ocean-waves model is used to reanalyse the weather, by assimilating surface observations. The ERA-20C products describe the spatio-temporal evolution of the atmosphere (on 91 vertical levels, between the surface and 0.01 hPa), the land-surface (on 4 soil layers), and the ocean waves (on 25 frequencies and 12 directions). The horizontal resolution is approximately 125 km (spectral truncation T159). Note, atmospheric data are not only available on the native 91 model levels, but also on 37 pressure levels (as in ERA-Interim), 16 potential temperature levels, and the 2 PVU potential vorticity level. Monthly means, daily, and invariant data are available. The temporal resolution of the daily products is usually 3-hourly.

The assimilation methodology is 24-hour 4D-Var analysis, with variational bias correction of surface pressure observations. Analysis increments are at T95 horizontal resolution (aprox. 210 km). The analyses provide the initial conditions for subsequent forecasts that serve as backgrounds to the next analyses. A 10-member ensemble was produced initially, to estimate the spatio-temporal evolution of the background errors.

The observations assimilated in ERA-20C include surface pressures and mean sea level pressures from ISPDv3.2.6 and ICOADSv2.5.1, and surface marine winds from ICOADSv2.5.1. The observation feedback from ERA-20C is available. It includes the observations but also departures before and after assimilation and usage flags.

Data Access: ECMWF

References | ClimateDataGuide

ECMWF ERA-20CM Model integration (no data assimilation): 1900 - 2010

The ERA-20CM atmospheric model integrations were produced in the framework of the ERA-CLIM project.

There are two versions, ERA-20CM and ERA-20CMv0, each comprising of a 10-member ensemble. The first version is 'final', the second is 'experimental'. The 'experimental' version was an early production and should not be used to initiate new research.

The model integration is forced by radiative forcing from CMIP5 and also by sea-surface temperature (SST) and sea ice cover from HadISST2.

Access: ECMWF

References | ClimateDataGuide

ECMWF Interim Reanalysis (ERA-Interim): 1979-present

ERA-Interim was originally planned as an 'interim' reanalysis in preparation for the next-generation extended reanalysis to replace ERA-40. It uses a December 2006 version of the ECMWF Integrated Forecast Model (IFS Cy31r2). It originally covered dates from 1 Jan 1989 but an additional decade, from 1 January 1979, was added later. ERA-Interim is being continued in real time. The spectral resolution is T255 (about 80 km) and there are 60 vertical levels, with the model top at 0.1 hPa (about 64 km). The data assimilation is based on a 12-hourly four-dimensional variational analysis (4D-Var) with adaptive estimation of biases in satellite radiance data (VarBC). With some exceptions, ERA-Interim uses input observations prepared for ERA-40 until 2002, and data from ECMWF's operational archive thereafter. See Dee et al. (2011) in the references below for a full description of the ERA-Interim system.

Data Access: ECMWF | NCAR

References | ClimateDataGuide

ECMWF 40 Year Reanalysis (ERA-40): Sep 1957-Aug 2002

Completed in 2003, ERA-40 is a global atmospheric reanalysis of the 45-year period 1 September 1957 - 31 August 2002. It was produced using a June 2001 version of the ECMWF Integrated Forecast Model (IFS Cy28r3). The spectral resolution is T159 (about 125 km) and there are 60 vertical levels, with the model top at 0.1 hPa (about 64 km). Observations were assimilated using a 6-hourly 3D variational analysis (3D-Var). Satellite data used include Vertical Temperature Profile Radiometer radiances starting in 1972, followed by TOVS, SSM/I, ERS and ATOVS data. Cloud Motion Winds are used from 1979 onwards. Various data from past field experiments were used, such as the 1974 Atlantic Tropical Experiment of the Global Atmospheric Research Program, GATE, 1979 FGGE, 1982 Alpine Experiment, ALPEX and 1992-1993 TOGA-COARE.

Data Access: ECMWF  | NCAR

References | ClimateDataGuide

ECMWF 15 Year Reanalysis (ERA-15): Jan 1979-Dec 1993

Completed in 1996, ERA-15 is a global atmospheric reanalysis of the 15-year period 1 January 1979 - 31 December 1993. It was produced using an April 1995 version of the ECMWF Integrated Forecast Model (IFS Cy13r4). The spectral resolution is T106 (about 190 km) and there are 31 vertical levels, with the model top at 10 hPa (about 31 km altitude). Observations were assimilated using a 6-hourly Optimum Interpolation analysis (OI). Satellite data used were limited to cloud-cleared TOVS radiances and Cloud Motion Winds from GOES, GMS, and METEOSAT. Pseudo-observations of surface pressure (PAOBS) were also used, as well various data from past field experiments: 1979 FGGE, 1982 Alpine Experiment (ALPEX), TOGA, SUBDUCTION, and those found in the COADS dataset.

Data Access: ECMWF  | NCAR

References | ClimateDataGuide

Japanese 25-year Reanalysis (JRA-25): 1979-2004, JCDAS: 2005-Jan.2014

The Japanese 25-year Reanalysis (JRA-25) represents the first long-term global atmospheric reanalysis undertaken in Asia. Covering the period 1979-2004, it was completed using the Japan Meteorological Agency (JMA) numerical assimilation and forecast system and specially collected and prepared observational and satellite data from many sources including the European Center for Medium-Range Weather Forecasts (ECMWF), the National Climatic Data Center (NCDC), and the Meteorological Research Institute (MRI) of JMA. A primary goal of JRA-25 is to provide a consistent and high-quality reanalysis dataset for climate research, monitoring, and operational forecasts, especially by improving the coverage and quality of analysis in the Asian region.  JRA-25 was conducted by JMA and CRIEPI (Central Research Institute of Electric Power Industry).  It had been continued as JCDAS (JMA Climate Data Assimilation System) operated by JMA in near real time basis. The data assimilation systems of JRA-25 and JCDAS are the same.  Users can use JRA-25 and JCDAS as one continuous reanalysis dataset. JCDAS data provision was terminated in early Feburay 2014 because it was replaced with JRA-55 in operational. The available data period of JRA-25/JCDAS is for 35 years and 1 month (January 1979 to January 2014).

Data Access: NCAR

Homepage | Atlas | References | ClimateDataGuide

Japanese 55-year Reanalysis (JRA-55): 1958-2012,  and extended to present
     [JRA-55C(1972-2012) and JRA-55AMIP(1958-2012)] <-- not extended to present

JMA has carried out the second reanalysis project named the Japanese 55-year Reanalysis (JRA-55) (nicknamed JRA Go! Go!) using a more sophisticated NWP system, which is based on the operational system as of December 2009, and newly prepared past observations. The analysis period is extended to 55 years starting from 1958, when the regular radiosonde observations became operational on the global basis. Many of deficiencies in JRA-25 have been diminished or reduced in JRA-55 because many improvements achieved after JRA-25 have been introduced. JRA-55 provides a consistent climate dataset over the last half century. JRA-55 has been continued in near real time basis after 2013. If you need real time basis (2 days behind) data, please access to JMA. The real time basis data are also provided to other cooperating organizations (Note: half year behind). Note that the products for extended period after 2013 are also called JRA-55. As "JRA-55 family", there are two subproducts JRA-55C and JRA-55AMIP produced by MRI/JMA. JRA-55C assimilated conventional observations only. JRA-55C covers from 1972 to 2012. Before 1971, use JRA-55 instead because no satellite data was assimilated in JRA-55 before 1971. JRA-55AMIP (AMIP type run of JRA-55, with no observations) covers 1958 to 2012. JRA-55C and JRA-55AMIP data are available from DIAS and NCAR. Note that JRA-55C and JRA-55AMIP are not extended to present. JRA-55 Atlas (climate charts) is now available.

Data Access: JMA | DIAS (JRA-55) (JRA-55C) (JRA-55AMIP) | NCAR (JRA-55: Daily 3-Hourly and 6-Hourly DataMonthly Means and Variances) (JRA-55C: Daily(3-hourly,6-hourly), Monthly) (JRA-55AMIP: Daily(3-hourly,6-hourly), Monthly) | ESGF/NASA/WCRP | ECMWF |

Homepage | References | JRA-55 Atlas |

 

NASA Modern Era Reanalysis for Research and Applications (MERRA): 1979-2016(Feb)

MERRA is a NASA reanalysis for the satellite era using a major new version (circa 2008) of the Goddard Earth Observing System Data Assimilation System Version 5 (GEOS-5) produced by the NASA GSFC Global Modeling and Assimilation Office (GMAO). The Project focused on historical analyses of the hydrological cycle on a broad range of weather and climate time scales and placed the NASA EOS suite of observations in a climate context.

Data Access: GES MDISC | ESGF

Home Page | References | FAQ | Atlas | ClimateDataGuide | AMS Special Collection

NASA Modern Era Reanalysis for Research and Applications Version-2 (MERRA-2): 1980-present

MERRA-2 is a NASA reanalysis for the satellite era using a major new version of the Goddard Earth Observing System Data Assimilation System Version 5 (GEOS-5) produced by the NASA GSFC Global Modeling and Assimilation Office (GMAO). MERRA-2 assimilates observations not available to MERRA during the 2010s, and therefore, will continue processing in real time longer than MERRA.  There are numerous improvements and updates to the data assimilaiton, model and observing system. One notable change is the assimilation of aerosol observations, including black and organic carbon, sulfate and dust. Production began in the spring of 2014 and is presently available for access.

Data Access: GES MDISC | FTP Subsetter

Home Page | File Specification | Documentation

NCEP Climate Forecast System Reanalysis (CFSR): 1979-present

The National Centers for Environmental Prediction (NCEP) Climate Forecast System Reanalysis (CFSR) spans 1979 to present. The CFSR was designed and executed as a global, high resolution, coupled atmosphere-ocean-land surface-sea ice system to provide the best estimate of the state of these coupled domains over this period. The T382 resolution atmospheric data spans 1979 to 2010. The current T574 analysis is an extension of the CFSR as an operational, real time CFSv2 product from 2011 into the future.

Data Access: NCEP | NCDC NOMADS | NCAR (includes real time CFSv2) | ESGF

References | ClimateDataGuide

NCEP/DOE Reanalysis II: 1979-near present

NCEP produced a second version of their first reanalysis starting from the beginning of the major satellite era. More observations were added, assimilation errors were corrected and a better version of the model was used.

Data Access: NCEP NOMADS | NCAR | ESRL | KNMI | IRI

References | ClimateDataGuide

NCEP/NCAR Reanalysis I: 1948-present

This reanalysis was the first of its kind for NOAA. NCEP used the same climate model that were initialized with a wide variety of weather observations: ships, planes, RAOBS, station data, satellite observations and many more. By using the same model, scientists can examine climate/weather statistics and dynamic processes without the complication that model changes can cause. The dataset is kept current using near real-time observations.

Data access: NCEP NOMADS| NCAR | ESRL | IRI | KNMI 

References | FAQ | FGDC | ClimateDataGuide

NCEP North American Regional Reanalysis (NARR): 1979-near present

The NARR reanalysis was done to produce very high resolution output over the North American region. Observational inputs were similar to NCEP I with the addition of assimilated precipitation. The NARR model region was nested in a global, lower resolution model. Outputs are similar to the NCEP I and II models but with more snow, ice and precipitation related variables.

Data Access: NCDC and NCEP NOMADS | NCAR | ESRL

References | FAQ | ClimateDataGuide

NOAA-CIRES 20th Century Reanalysis version 2 (20CRv2): 1871-2012

The 20th Century Reanalysis version 2 (20CRv2) dataset contains global weather conditions and their uncertainty in six hour intervals from the year 1871 to 2012. Surface and sea level pressure observations are combined with a short-term forecast from an ensemble of 56 integrations of an NCEP numerical weather prediction model using the Ensemble Kalman Filter technique to produce an estimate of the complete state of the atmosphere, and the uncertainty in that estimate. The uncertainty is approximately inversely proportional to the density of observations. Additional observations and a newer version of the NCEP model that includes time-varying CO2 concentrations, solar variability, and volcanic aerosols are used in version 2. The long time range of this dataset allows scientists to examine better long time scale climate processes such as the Pacific Decadal Oscillation and the Atlantic Multidecadal Oscillation as well as looking at the dynamics of historical climate and weather events. Verification tests have shown that using only pressure creates reasonable atmospheric fields up to the tropopause. Additional tests suggest some correspondence with observed variations in the lower stratosphere.

Data Access: ESRL | KNMI | IRI | NCAR | NERSC | BADC | ESGF

Homepage | References | Related Publications | ClimateDataGuide

NOAA-CIRES 20th Century Reanalysis version 2c (20CRv2c): 1851-2012 [2013-2014]

The 20th Century Reanalysis version 2 (20CRv2c) dataset contains global weather conditions and their uncertainty in six hour intervals from the year 1851 to 2012. Surface and sea level pressure observations are combined with a short-term forecast from an ensemble of 56 integrations of an NCEP numerical weather prediction model using the Ensemble Kalman Filter technique to produce an estimate of the complete state of the atmosphere, and the uncertainty in that estimate. The uncertainty is approximately inversely proportional to the density of observations. Additional observations from ISPDv3.2.9 and new boundary conditions from the Simple Ocean Data Assimilation with sparse observational input (SODAsi.2) pentad sea surface temperature and COBE-SST2 monthly sea ice concentration are used.  For the 2013 and 2014 extension, SSTs are from the NOAA daily 1/4 degree Optimal Interpolation version 2. 2014 does not include tropical cyclone pressure observations after April. 

Data Access: ESRL |  NCAR | NERSC (every member)

Homepage | References | Related Publications ClimateDataGuide

 


Have a question or comment on a specific reanalysis dataset or in general?

Use this link to Post Notes, Questions, and Comments on specific reanalyses


 

 

Dear Gilbert, thank you very much for your answer. Following your suggestion, I made a page at reanalyses.org where a time series comparison can be seen and where I specified the details about the data. The page is https://reanalyses.org/atmosphere/slp-drops-20cr-not-present-era-interim-reanalysis Thanks again! Alba

SSA (not verified)

Thu, 05/07/2015 - 21:29

Hello all, can anyone tell me the difference between the sea ice cover and sea ice extent. can i using the sea ice cover data in era iterim to explain how much the sea ice extent from one month to other month???

Nigerian Student (not verified)

Mon, 07/13/2015 - 12:45

Hi guys. I'm pretty new to all this stuff. Can anyone please give me a simplified, step by step explanation of how to get and use data from any of these reanalysis websites? I'm a student at a University in Nigeria. I stumbled on this and I'd like to use data from this for my final dissertation. I'd really appreciate any help I can get. Thank you.

Dear Student, Please provide more information about what you are trying to accomplish. What variables? What time period? What time resolution? There is no single way to get data, and there are many possibilities. What software will be using to analyze and plot the data? Will any of the tools for subdaily, daily-average, or monthly average data available off of go.usa.gov/XTd work for you? If monthly mean data are what you are interested in, you may want to consider using the web-based reanalysis intercomparison tool or one of the other tools listed at http://reanalyses.org/atmosphere/tools. best wishes,

Mr Al (not verified)

Wed, 07/15/2015 - 10:58

Hi, I too have just started to review some reanalysis surface pressure data and was hoping if someone could clarify a particular point. The data I'm looking at is from: http://iridl.ldeo.columbia.edu/SOURCES/.NOAA/.ESRL/.PSD/.rean20thcent/.V2/.six-hourly/.monolevel/.sfc/.pres/ and is 6hrly surface pressures at 2deg grid increments. My question is whether this is likely to be the spatial mean surface pressure across a grid square (and if so, would the coordinates represent the grid square centre) or whether the dataset should be considered as point data applicable to precise coordinates? thanks, Alan

Yiyi (not verified)

Tue, 08/11/2015 - 16:29

Hello there, I found that in some reanalyses products, they would provide FORECAST and ANALYSIS products. Thus I am wondering that if forecast data is only model output and analysis data is produced by model and assimilation method. Can anyone help to explain the differences between them? Also, why some variables are only available in FORECAST but not in ANALYSIS? Thanks. Yiyi

Anonymous (not verified)

Sat, 08/29/2015 - 09:34

I am looking at long term drought in the Southern Africa region and I would like to utilise ERA-INTERIM Reanalysis data. I am just not sure of the difference between Large-scale and total precipitation and which one is better to use for such analysis. I would also like to find out if there are other rainfall parameters that are available that I could use. Miya

In ERA-Interim, the total precipitation is the sum of the large-scale precipitation and convective precipitation. There is also snowfall, large-scale snowfall and convective snowfall available. All these fields are accumulated from the beginning of the forecast and the units are "m of water" or "m of water equivalent".

Fabio (not verified)

Fri, 10/09/2015 - 08:33

Hello, Which dataset do you think has the most accurate data for tropical central africa and has a time-step of at least 6-hours? Thanks

There is a description of how CAPE is calculated (in the post processing) in ERA-Interim, in Part IV Physical processes, Chapter 5 Convection, Section 5.11, of the ERA-Interim model (IFS) documentation: https://software.ecmwf.int/wiki/display/IFS/CY31R1+Official+IFS+Documentation Also note that in ERA-Interim the CAPE at forecast step=0 is erroneously set to zero everywhere.

fry.meridith

Wed, 10/28/2015 - 15:39

Hi all,

I am currently looking for gridded datasets of evapotranspiration (daily, ideally, at national/global scale). I have derived daily potential evapotranspiration estimates for the U.S. using the Hargreaves-Samani equation and the NCEP/NCAR Reanalysis dataset. However, I would like to compare these estimates to other datasets/derivations if possible. I know that Penman-Monteith is another standard method for calculating, but I have not attempted to calculate using P-M yet because of the greater number of inputs needed.

I am interested in learning more about the potential evaporation rate (W/m2) in the NCEP/NCAR Reanalysis dataset (Kalnay et al., 1996) - Does anyone have familiarity with this particular variable and/or know how it was derived? I know that actual evapotranspiration, potential evaporation, and potential evapotranspiration are often distinguised in the literature, so I also wanted to confirm what the potential evaporation rate in this dataset represents.

I also recently asked ESRL PSD about the potential evaporation and transpiration variables in the NOAA-CIRES 20CR dataset, and Gil Compo was very helpful in providing those references (Mahrt and Ek, 1984 - eq 9; Chen et al., 1996 - eqn 11).

If there are other national (or global) gridded datasets of daily evapotranspiration that you know of (eventually I will need to have PET in mm/day), please let me know.

Thank you in advance!
Best regards,
Meridith Fry (EPA/OPP)

New student (not verified)

Sun, 11/08/2015 - 12:30

Hello,I am a student currently working on MERRA data, I need some links or detailed information for the parameters of Radiation ; SWGDN(Surface incident shortwave flux) & SWGNT(Surface net downward shortwave flux). What are the differences in both? How both can have effect on a body lying on Earth surface(probably near equator)? Your help will mean alot to me. Thanks in advance

In MERRA, there are two fundamental components of the radiation in shortwave. Downward, the solar radiation that reaches the surface through clouds and other atmospheric attenuation. Upward, the reflected radiation which depends on the downward radiation, and the albedo. The net shortwave is the downward minus the upward. It is described as net downward to provide the direction (or sign) of the data. For more information on MERRA data, you can refer to the File Specification document, and the budget appendix.
http://gmao.gsfc.nasa.gov/research/merra/file_specifications.php

For land surface modeling, it is useful to know temporal frequency of reanalysis output (hourly, 3-hourly, etc...). Some have this mentioned, others make it hard to figure out. Is there a simple list somewhere? In particular, for some of my applications, temporal frequency of surface meteorology trumps spatial resolution. Not sure if any hourly output exists. Thanks. -ankur, UW-Madison, desai@aos.wisc.edu

Ankur, For offline land modeling, the MERRA-2 data includes our lowest model level data. This is on the terrain following coordinate, so the height AGL is variable, roughly 60m (but also provided). The advantages of lowest model level to land modeling are 1) this level includes a portion of the analysis increment, so the observations that help constrain the prognostic state fields and 2) it does not include the surface layer similarity parameterization interpolation that we use to determine fluxes for our land model. This should allow your land model and surface layer to develop independently of what the reanalyses systems do. In this way you can also compare back to the 2m meteorology and even diffusion coefficients that MERRA-2 provides.

MERRA-2 and CFSR provide 1 hourly frequency data, and CFSR does have higher spatial resolutions.

Ankur, Courtesy of Suru Saha of NCEP: "CFSR has hourly output for all land surface variables at full model resolution." I see from the links http://reanalyses.org/atmosphere/overview-current-reanalyses#CFSR one to NOMADS NCDC http://nomads.ncdc.noaa.gov/data.php?name=access#cfsr . Also, the link to NCAR should be useful http://rda.ucar.edu/#!lfd?nb=y&b=proj&v=NCEP%20Climate%20Forecast%20System%20Reanalysis . best wishes, gil

Yiyi (not verified)

Mon, 03/07/2016 - 13:42

Hello, Currently I am processing the cloud water content (for entire atmosphere) data in 20CRv2c. And I am wondering if this variable include liquid water, ice water and water vapor? Thanks. Yiyi

Dear Yiyi, Happy to help. A couple of questions. From where did you obtain the data? What format is it in? If it is in netcdf, please send the output of "ncdump -h" on the file. If it is in GRIB, please send the output of "wgrib -V" and only the first message is needed. I am fairly certain that the variable is "cloud liquid water" not "cloud water content", but I would need to see your output to be sure of what you are accessing. Best wishes,

Thanks for your help! I downloaded data from ESRL-PSD 20CRv2c webpage. The data link is ftp://ftp.cdc.noaa.gov/Datasets/20thC_ReanV2c/Monthlies/monolevel/cldwtr.eatm.mon.mean.nc. The data is in netcdf format, and the output of "ncdump -h" is following: float cldwtr(time, lat, lon) ; cldwtr:cell_methods = "time: mean (monthly from 6-hourly values)" ; cldwtr:long_name = "Monthly Cloud Water for entire atmosphere" ; cldwtr:units = "kg/m^2" ; cldwtr:precision = 4s ; cldwtr:GRIB_id = 76s ; cldwtr:GRIB_name = "C WAT" ; cldwtr:var_desc = "Cloud Water Content" ; cldwtr:dataset = "NOAA-CIRES 20th Century Reanalysis version 2c Monthly Averages" ; cldwtr:level_desc = "Entire Atmosphere Considered As a Single Layer" ; cldwtr:statistic = "Ensemble Mean" ; cldwtr:parent_stat = "Individual Obs" ; cldwtr:standard_name = "atmosphere_cloud_condensed_water_content" ; cldwtr:missing_value = -9.96921e+36f ; cldwtr:valid_range = 0.f, 6.5532f ; cldwtr:statistic_method = "Ensemble mean is calculated by averaging over all 56 ensemble members at each time step and then averaging mean over all time steps in a month" ; cldwtr:GridType = "Cylindrical Equidistant Projection Grid" ; cldwtr:datum = "wgs84" ; cldwtr:actual_range = 0.f, 0.3662097f ; Thanks, Yiyi

Senya Grodsky (not verified)

Mon, 03/14/2016 - 14:49

Is snowfall included in ERA-Interim total precipitation? Yes. precipitation is the liquid equivalent of all precipitation including rain/snow etc.

Anonymous (not verified)

Tue, 03/15/2016 - 10:10

Hi everyone, I am trying to use ERA Interim and CFSR for hydrological modelling in a mesoscale catchment in Africa. I have obtained CFSR data for SWAT modelling from globalweather.tamu.edu and ERA Interim data from http://apps.ecmwf.int/datasets/. However i have a problem using ERA Interim data as I can locate elevation data which is needed by SWAT model. Can some one direct me to where i can download elevation data? Thanks in advance for you help. Nkiaka

Dear Nkiaka, I presume you require the elevation of the surface of the Earth. The invariant (ie unchanging) fields are available from http://apps.ecmwf.int/datasets/data/interim-full-invariant/ and includes the (surface) geopotential. Divide by g (9.80665) to obtain surface geopotential height. Regards, Paul Berrisford

Daniel (not verified)

Tue, 03/15/2016 - 18:19

Hello, I have been working with the ensemble mean of the 20CR. However, I know that the 20CR ensemble mean is based on 56 members. I would like to work with some of this realizations. First of all, where do I more information about them? It seems that most information deals with the ensemble mean. How do I download them? Is is possible to know before downloading which members represent more extreme climates? Many thanks for you help!

Daniel, See the link on this page https://reanalyses.org/atmosphere/overview-current-reanalyses#TWENTv2c with "NERSC (every member)". This will take you to portal.nersc.gov, which has a "Browse" button. Use 20CR version 2c. Please feel free to respond to this thread with questions.

Yiyi (not verified)

Wed, 04/13/2016 - 15:39

Hello there, Since I need to convert sea ice concentration to sea ice extent in MERRA-2 (0.625 x 0.5) and JRA-55 (1.25 x 1.25). I was wondering if these two products can provide gridded surface area information. Any help would be appreciated. Thanks, Yiyi

Hi all,

I've run across what is either a 2-day discrepancy or a misunderstanding on my part of the time coordinate in MERRA2 data accessed through OpenDAP. The description of the 'time' variable is 'days since 1-1-1 00:00:00'. However, the first element of the MERRA2 time vector, corresponding to 1980-1-1 00:00:00, is 722816 (days), whereas when I compute the difference between 1980-1-1 and 1-1-1 using Python's 'datetime', I get 722814 days. I've checked 'datetime' against test data in Appendix C of Dershowitz and Reinhold's book 'Calendrical Calculations', and it appears to be correct. Any ideas? I've appended a short iPython session demonstrating the issue below.

Thanks,

Scott Paine
Smithsonian Astrophysical Observatory

=================================
In [1]: import pydap.client

In [2]: import datetime

In [3]: dataset = pydap.client.open_url('http://goldsmr4.sci.gsfc.nasa.gov:80/dods/M2I1NXASM')

In [4]: var = dataset['time']

In [5]: var.attributes
Out[5]:
{'grads_dim': 't',
'grads_mapping': 'linear',
'grads_min': '00z01jan1980',
'grads_size': '324362',
'grads_step': '60mn',
'long_name': 'time',
'maximum': '01z01jan2017',
'minimum': '00z01jan1980',
'resolution': 0.0416666679084301,
'units': 'days since 1-1-1 00:00:0.0'}

In [6]: var[0]
Out[6]: array([ 722816.])

In [7]: d1 = datetime.date(1980, 1, 1)

In [8]: d0 = datetime.date(1, 1, 1)

In [9]: delta = d1 - d0

In [10]: delta.days
Out[10]: 722814

We've seen this 2 day error that some calendar calculations make and which I think the python and the calendar script are making.I think it is counting 2 years as leap years that are not. udunits (which we use) has the correct calculation and I believe MERRA2 does as well. Because the base date (1-1-1) is so far back, many calendar programs don't handle it correctly and we have shifted in our group to try to use a base date after the Gregorian calendar started so all calendar programs handle it correctly. I think this rule is the sticking point "The Revised Julian calendar adds an extra day to February in years that are multiples of four, except for years that are multiples of 100 that do not leave a remainder of 200 or 600 when divided by 900." .

Anonymous (not verified)

Fri, 05/20/2016 - 05:39

Good day, I want to obtain the moisture bugdet term P-E from the evapotranpiration and Total precipitation data sets, and the evaporation values are negative. any explanation. Also I may want to know the unit of evapotranspiration. thanks

Dear Keerthi, For ERA-Interim "daily" data, the units of evaporation and precipitation are "m", and these quantities are accumulated from the beginning of the forecast for step hours. To convert to mm/day (for the period of step hours) you need to multiply by 1000*24/step. However, if you want a value of evaporation over one day, you could add the values for time=00, step=12 and time=12, step=12 and then multiply by 1000. Note that vertical fluxes are defined to be positive downwards, so precipitation is positive and evaporation is usually negative (though condensation would be positive). Regards, Paul

Rocio (not verified)

Mon, 05/30/2016 - 10:29

Hi all. I'm pretty new to all this stuff. Can anyone please give me a simplified, step by step explanation of how to get and use data from any of these reanalysis websites? I'm a student at a University in Cuba. I stumbled on this and I'd like to use data from this for my final dissertation.I need temperature, preassure and relative humidity data from at lees 1985 untill nowadays, with the best resolution I can get, I'll be using python to analize and plot the data. I'd really appreciate any help I can get. Thank you.

Dear Rocio, You can click on the Data Access links above, or it may be more convenient to use some plotting web tools first. See the page http://reanalyses.org/atmosphere/how-obtainplotanalyze-data . You didn't mention at what time resolution you need the data: subdaily, daily, or monthly? The table at http://reanalyses.org/atmosphere/comparison-table may help you select some datasets to examine. As to "best", it entirely depends on your application. I am afraid you will need to experiment some and see what works for you. Best wishes,

Wenjun Cui (not verified)

Fri, 06/03/2016 - 14:10

Hello all, I have a question about CFSR precipitation data. According to Saha et al. (2010), for land-surface analysis, the model-generated precipitation is replaced by the a mix of observation-based (CMAP and CPCU) and model-generated precipitation as forcing data. So I am wondering, are the CFSR precipitation data I downloaded generated by model or generated by merging observations and model out? Thanks, Wenjun

Dear Wenjun, A little more information is needed to make a helpful reply. What "CFSR precipitation data" are you using? What is the source of this data? Where did this person download it and what is the exact name of the file you are looking at and the link to where you obtained it? There are several distributors of CFSR data. Thanks for clarifying,

Hello Dr. Compo, I downloaded CFSR monthly precipitation data from the UCAR/NCAR Research Data Archive, the link is "http://rda.ucar.edu/datasets/ds093.2/#!description". The variable I downloaded is total precipitation, and the file name is "pgbh.gdas.yyyymm.grb2.nc". Thank you for your time, Wenjun

Courtesy of Jesse Meng and Suru Saha of NCEP When you download the CFSR data, you are getting the model generated precipitation. The mixed precipitation approach is used in land analysis only, not in the product. Hope this answers the questions.

Julio Cardona (not verified)

Fri, 06/10/2016 - 10:33

Hello I am new to this reanalysis data, I would like to know where can I download data from precipitation and monthly average temperature from 1950 for the region of north central Mexico with good resolution and what software or application you recommend to view and extract data downloaded from the server because the files have .nc commonly extension. I am an engineering student at the Autonomous University of Zacatecas in Mexico and I'm doing my teisis in the analysis of drought, for which I need the data. Beforehand thank you very much

Many applications can read netCDF files. See unidata http://www.unidata.ucar.edu/software/netcdf/software.html and http://www.esrl.noaa.gov/psd/data/gridded/tools.html As far as which dataset, all reanalyses have precipitation and temperature (though precip is usually model output and not assimilated). See this table for resolution and time coverage. https://reanalyses.org/atmosphere/comparison-table There are also observed temperature and precipitation files. See http://www.esrl.noaa.gov/psd/data/gridded/tables/precipitation.html and http://www.esrl.noaa.gov/psd/data/gridded/tables/temperature.html NCAR archives many datasets, in addition. http://rda.ucar.edu Cathy

sujan ghimire (not verified)

Fri, 09/09/2016 - 04:57

I am doing solar modelling and have downloaded the data but it is at 0.00 which is UTC and our region is UTC +10. so it means that the data is for 10AM here which is not useful and next hour is 6 which is 16hrs so it means 4 PM over here. So with the 10AM data and 4 PM data how can i do the modelling?

How can i download the daily data on hourly basis? Any idea highly appreciated.

Ashwin (not verified)

Wed, 09/21/2016 - 20:27

Is the same sigma coordinate used in the reanalysis data from UCAR FNL ? 0.25 x 0.25 degree resolution ? Are the 28 levels the same ?

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