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to be peer reviewed by: Paul Berrisford, 2018-07-24

approved by CUS team leader: 2018-05-01

This article applies to the ERA5 sub-daily datasets:

  • ERA5 high resolution (HRES), containing
    • sub-daily atmospheric data (
streams oper/
    • stream oper)
    • sub-daily ocean wave data (stream wave)
  • ERA5 ensemble (EDA), containing
    • sub-daily atmospheric data (
streams enda/
    • stream enda)
    • sub-daily ocean wave data (stream ewda)
.

This article does not apply to

other

ERA5

streams, for example

monthly data.

See what

What streams are available? (Section 'Data organisation').

Before continuing with this article you might want to read:

, section 'Data organisation').

Analysis and forecast

If you access ERA5 data in the C3S Climate Data Store (CDS), you will not see the concept of type 'analysis' and 'forecast'.  However, behind the scene, ERA5 data archive has two types of data available, 'analysis' (an) and 'forecast' (fc). This article will help you understand the differences between these two types.

  • An analysis, of the atmospheric conditions, is a blend of observations with a previous forecast. An analysis can only provide instantaneous parameters (parameters valid at a specific time, e.g temperature at 12:00), but not accumulated parameters, mean rates or min/max parameters.
  • A forecast starts with an analysis at a specific time (the 'initialization time'), and a model computes the atmospheric conditions for a number of 'forecast steps', at increasing 'validity times', into the future. A forecast can provide instantaneous parameters, accumulated parameters, mean rates, and min/max parameters.

To see which parameters are available as analysis (an) and/or forecasts (fc)  see ERA5: data documentation, section 'Parameter listings'.

Instantaneous, accumulated, mean rate

See also: What is ERA5 ,

Instantaneous, accumulated

and min/max parameters

Each parameter is classed as either 'instantaneous', 'accumulated', 'mean rate' or 'min/max', depending on the temporal properties of the parameter:

  • Instantaneous parameters refer to a
particular
(Note, these parameters cannot represent time scales shorter than the model time step, 30min in ERA5, see details below.)
  • For a list of available surface and single level instantaneous parameters see ERA5: data documentation, Table 2.
  • Accumulated parameters are accumulations during a particular time period, for example precipitation between 17:00 and 18:00. For a list of available accumulated parameters see ERA5: data documentation, Table 3.
  • Mean rate parameters are temporally averaged rates over a particular time period, for example the mean snowfall rate between 17:00 and 18:00. For a list of available mean rate parameters see ERA5: data documentation, Table 4.
  • Min/max parameters are the minimum or maximum 'instantaneous' value
in
  • within a particular time period
.

See the ERA5 documentation for available instantaneous parameters (Table 2) and accumulated parameters (Table 3). There you can also see if a parameter is available from analysis (an) or from forecast (fc) or from both.

Analysis and forecast

In ERA5 two types of data are available, 'analysis' and 'forecast':

  • An analysis is a point-in-time snapshot of the atmospheric conditions at the specified time. An analysis can by definition only compute instantaneous parameters.
  • A forecast starts with the atmospheric conditions at a specific time (the 'initialization time'), and computes the atmospheric conditions in multiple iterations (steps) for 'validity times' in the future. A forecast can compute instantaneous parameters (e.g. the temperature at the validity times), and  also accumulated parameters (e.g. precipitation up to the validity times).

'time' in analyses

An ERA5 analysis is computed for each full hour (i.e. for 00:00, 01
  • , for example minimum temperature between 17:00 and 18:00. For a list of available min/max parameters see ERA5: data documentation, Table  5.

Time and Step

'time' in analyses

Each analysis has a validity time, i.e. the time the data values refer to (not the time when the analysis was computed).

All validity times are in hours UTC.

Depending on the selected stream, ERA5 daily analysis data is available hourly (i.e. for the HRES, with validity time 00:00, 01:00, 02:00, ... , 23:00)

.

or 3-hourly (i.e. for the EDA, with validity time 00:00, 03:00, 06:00,  ... , 21:00). See also the ERA5: data documentation, 'Temporal resolution' and the ERA5 Catalogue, streams.

The concept of 'step' does not apply to analyses.

'time' in forecasts

Each forecast starts with the atmospheric conditions at a specific 'initialization time'.

At the model level an analysis takes a 30-minute window around the validity time into account (+/-15 min). In the output data, 'time' specifies the validity time:

Image Removed

'time'/'step' in forecasts

In ERA5 a new forecast is

initialized every day at

computed twice a day, with initialization times of 06:00 and 18:00 UTC

. The

.

In the ERA5 data archive, for forecasts, 'time' (and date) refers to the initialization time.

'step' in forecasts

Each forecast computes the future atmospheric conditions

internally in 30-minute 'model steps'. The model output data is then aggregated to 18 one-hour intervals (steps) and archived. Hence in the ERA5 data archive each 'step' represents one hour. For example, for the daily forecast initialized at 06:00:

, and at certain "points", or "steps", during this computation the data is post-processed, and stored in the ERA5 data archive. In ERA5 there is a step every 1 or 3 hours, depending on the selected stream. Note, when downloading data from the C3S Climate Data Store (CDS), 'step' does not need to be specified because data is selected according to the valid time automatically, assuming steps from 1 to 12 hours.

Steps are referenced in hours from the forecast initialization time. This is regardless of the step interval. For example, for time=06:00, step 3 is always at 09:00 (06:00+3h).

The step interval in ERA5 is:

  • Every 1 hour in the HRES atmospheric (stream=oper), HRES wave (stream=wave) and EDA wave (stream=ewda) forecasts. Hence data is available with validity times 06:00 (step 0, initialization), 07:00 (step 1, i.e. initialization + 1h), 08:00 (step 2, i.e. initialization + 2h), and so on, and equivalent for the 18:00 initialization.
  • Every 3 hours in the EDA atmospheric (stream=enda) forecasts. Hence data is available with validity times 06:00 (step 0, initialization), 09:00 (step 3, i.e. initialization +3h), 12:00 (step 6, i.e. initialization + 6h), and so on, and equivalent for the 18:00 initialization.

'step'

Image Removed

Forecast steps

and instantaneous, accumulated and min/max parameters

When retrieving forecast data from the ERA5 archive, 'step' identifies one of the 18 forecast steps.

The interpretation of 'step' also depends on the parameter

though

:

data for instantaneous
  • Instantaneous parameters
is
  • are valid at the
end of the step, i.e. at  t + (s * 1h)
  • time indicated by time+step. For example, temperature from the forecast at time
t
  • =06:00, step
s
  • =
1
  • 3, represents the temperature at 06:00 +
(1 * 1 hour)
  • 3h, i.e. at
07
  • 09:00.
data for accumulated
  • Accumulated parameters
is
  • are aggregated up to
the end of the respective step, i.e. up to t + (s * 1h), starting at the end of the previous step, i.e. at t + ((s-1) * 1h). For example
  • a Step Y, starting at the previous Step X:

Image Added

Note that the interval between Step X and Step Y can be 1 hour or 3 hours, depending on the selected stream.

At Step 0 all accumulated values and mean rates are zero, because there is no previous data to accumulate from.

Examples:
  • In HRES atmospheric (hourly steps), precipitation at time=06:00, step=3 represents precipitation from [06:00 + 2h] to [06:00 + 3h], i.e. precipitation in the 1-hour period from 08:00 to 09:00.
  • In EDA atmospheric (3-hourly steps), precipitation at time=06:00, step=
4
  • 3 represents precipitation
up to
  • from [06:00 +
4 * 1h, starting from
  • 0h] to [06:00 +
3 * 1h
  • 3h], i.e. precipitation in the 3-hour period from 06:00 to 09:00.
  • Mean rate parameters are similar to accumulated parameters, except that the quantities are averaged, instead of accumulated, up to a Step Y , from the previous Step X, so the units include "per second". For example:
    • In HRES atmospheric (hourly steps), mean rate precipitation at time=06:00, step=3 represents the average precipitation rate in the 1-hour period from 08:00 to 09:00,.
    • In EDA atmospheric (3-hourly steps), mean rate precipitation at time=06:00
to 10:00.
    • , step=3 represents the average precipitation rate in the 3-hour period from 06:00 to 09:00.
  • Min/max parameters  (parameters named 'Minimum/Maximum ... since previous post-processing' ) are similar to accumulated parameters, except that instead of accumulating, only the min/max value during the period from Step X to Step Y is archived.

Summary

  • If you download ERA5 data hosted on the C3S Climate Data Store (CDS), you can either download the data using the web interface or CDS API. If you go for CDS API, you should use the web interface to help you build up the download script by making selections and then clicking the 'Show API request' button towards the end of a download form.
  • If you download ERA5 data hosted outside of CDS, you can download the data using CDS API. You should then use the ERA5 catalogue to help you build up your script by making selections and then clicking the 'View the MARS request' link.

The following table summarizes the different parameter types available in ERA5 from analysis and forecast:


Instantaneous

Image Removed

Summary

The following table summarizes how instantaneous and accumulated parameters, from analysis and forecast are available in ERA5:

instantaneous

parameters,

e.g. 2m temperature

accumulated

Accumulated parameters,

e.g. precipitation		Mean rate parametersMinimum/maximum parameters named 'Minimum/Maximum ... since previous post-processing'

Analysis

'date' and

Calculated from observations and previous forecasts

'time'

indicate

indicates a specific point in time for which a data analysis is carried out

('validity time')


'time' is hourly, HH:00

'step'

by definition is always 0

does not apply

For example '2 metre temperature'.

Values are valid at 'time'



n.a.
Data represents the average of a 30 minute window around the analysis time (t +/- 15min)
n.a.n.a.

Forecast

'date' and

Calculated from analysis and the forecast model

'time' indicate a specific point in time at which a forecast starts (initialization time)

.

'time' can be 06:00 or 18:00

'step' indicates

the number of forecasting steps from

hours after the initialization time.




For example '2 metre temperature'.

Values are valid at 'time'+'step'


'step'

can be 0 (effectively giving analysis), or

is in the range

1

0 to 18

Data represents the average of a 30 minute window around the valid time (t +/- 15min)

Image Removed

Data represents

(hours after initialization)

For example 'Total precipitation'.

Values represent the accumulation up to 'time'

t

+'step'

s

,

starting

from the previous

step, so the accumulation covers the period from t + sx-1 to t + sx

For example, time=06:00 and step=2 specifies the accumulation up to 06:00+2*1h (i.e. up to 08:00), starting from the previous step (s=1, i.e. at 06:00+1*1h = 07:00), so the accumulation covers the period from 07:00 to 08:00.

Image Removed

'step'


'step' is in the range 0 to 18 (hours after initialization)

At 'step' 0 all data is zero.


For example 'Mean total precipitation rate'.

Values represent the average rate up to 'time'+'step', from the previous 'step'


'step' is in the range 0 to 18 (hours after initialization)

At 'step' 0 all data is zero.

For

In ERA5 forecasts there are some parameters named '...since previous post-processing', for

example 'Maximum temperature at 2 metres since previous post-processing'.

Data represents

Examples

See also

Values represent the Min/Max

values within the forecast step.

in the period up to 'time'+'step', starting from the previous 'step'


'step' is in the range 0 to 18 (hours after initialization)

At 'step' 0 all data is zero.


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Examples

ERA5 data should preferably be downloaded from the C3S Climate Data Store (CDS). There you only need to select the desired validity times; the CDS then maps the validity times to the corresponding analysis/forecast and step.

The examples below apply to retrieving ERA5 data from the ECMWF data archive MARS. See

How to download ERA5 data via the ECMWF Web API

Example 1:  hourly data, accumulated; e.g. total precipitation and evaporation

StepYour requirement
Select from the ERA5 data catalogueSet in a WebAPI Python script
1

You are interested in HRES data, not in the ensemble

>Select Deterministic forecast, Atmospheric model'stream':'oper'
2

You need total precipitation and evaporation.

See and ECMWF parameter definitions

You find suitable parameters: 

  • Total precipitation (tp
) as hourly values for January 2015.tp is an accumulated parameter, so only available from forecasts. 
  • , paramId 228). Available from forecast (fc)
  • Evaporation (e, paramId 182). Available from forecast (fc)
>Select Forecast'type':'fc'
3Month>

Select a month, e.g. 2015, January


4Total precipitation and and evaporation are 2-dimensional fields ('surface field')>Select Surface'levtype':'sfc'
5Dates>Select dates'date':' 2015-01-01/to/2015-01-31'
6

ERA5 forecasts are initialized at 06:00 and 18:00

. Each forecast step

, and in HRES the interval between forecast steps is one hour

, so

.

Hence you need forecast steps 1 to 12, from each forecast, in order to cover a 24 hour period.

>

Select time 06:00

forecast

and

from each

18:00

forecast, tp for first the first 12 forecast steps:

Select steps 1 to 12

'time':'

  • type : fc
  • date : 2015-01-01/to/2015-01-31
    • time :

    06:00/18:00'

    'step':'1/2/3/4/5/6/7/8/9/10/11/12

    '

    7

    Specify parameters


    		>Select parameters 'Total precipitation' and 'Evaporation'

    'param':'tp/e' (short names)

    or

    'param':'228.128/182.128' (MARS parameter IDs)

    8
    		>

    Click 'View the MARS request'


    The resulting WebAPI Python script to download data:

    py

    These specifications give you hourly 'total precipitation' data from 2015-01-

    This results in hourly data from January

    01, 06:00 to

    February

    2015-02-01, 06:00

    (discard

    . 

    Discard the last 6 hours (2015-02-01, 00:01 to 06:00).

    You still need the first six hours of the first day, get these

     

    The data does not cover the period 00:00 to 06:00 of the first date.  Retrieve these 6 hours from the last forecast of the previous day

    :
  • type : fc
    • date :

    ('date':'2014-12-31

    ', 'time':'18:00

    ', 'step':'7/8/9/10/11/12')

    Example 2

    You need 2 metre temperature (2t) as daily average for January 2015.

    2t is an instantaneous parameter, available from analysis and forecasts. Since both are available, analysis is recommended.

    ERA5 analysis is available at each full hour, so you need:

    • type : an
    • date : 2015-01-01/to/2015-01-31
    • time : 00:00/01:00/02:00/03:00/04:00/05:00/06:00/07:00/08:00/09:00/10:00/11:00/12:00/13:00/14:00/15:00/16:00/17:00/18:00/19:00/20:00/21:00/22:00/23:00

    This results in hourly data for 2t. Then calculate the daily average.

    Example 3

    You need the daily minimum and maximum of 2m temperature for January 2015.

    You could obtain the hourly 2m temperature (see Example 3), and then identify the daily maximum and minimum of the hourly values.

    Alternatively you can use the parameters

    :  daily average, minimum and maximum of 2m temperature

    In ERA5 there is no daily data, so you have to download sub-daily  data and aggregate to full days yourself.

    StepYour requirement
    		Select from the ERA5 data catalogueSet in a WebAPI Python script
    1

    You are interested in HRES data, not in the ensemble

    		>Select Deterministic forecast, Atmospheric model'stream':'oper'
    2

    You need average, minimum and maximum of 2m temperature.

    See and ECMWF parameter definitions

    You find suitable parameters:  

    • '2 metre temperature' (2t, paramId 167). Available from analysis (an) and forecast (fc)
    • 'Maximum temperature at 2 metres since previous post-processing' (mx2t
    ) and
    • , paramId 201). Available from forecast (fc)
    • 'Minimum temperature at 2 metres since previous post-processing' (mn2t, paramId 202). Available from forecast (fc)

    You could retrieve the first parameter from analysis  and the other two from forecast, or all three from forecast. You choose the latter.

    		>Select Forecast'type':'fc'
    3Month>

    Select a month, e.g. 2015, January


    4All 2 metre temperatures are by definition 2-dimensional fields ('surface field')>Select Surface'levtype':

    The parameters named 'min/max since previous post-processing' are available from forecasts.

    Is this a valid use case? Why not simply use analysis?
    'sfc'
    5Dates>Select dates'date':' 2015-01-01/to/2015-01-31'
    6

    ERA5 forecasts are initialized at 06:00 and 18:00

    . Each forecast step

    , and in HRES the interval between forecast steps is one hour

    , so

    .

    Hence you need forecast steps 1 to 12, from each forecast, in order to cover a 24 hour period.

    		>

    Select time 06:00

    forecast

    and

    from each

    18:00

    forecast, mx2t and mn2t for first the first 12 forecast steps:
  • type : fc
  • date : 2015-01-01/to/2015-01-31

    • Select steps 1 to 12

    'time':'

    time :

    06:00/18:00'

    'step':'1/2/3/4/5/6/7/8/9/10/11/12

    '

    7

    Specify parameters


    		>Select parameters 
    • '2 metre temperature'
    • 'Maximum temperature at 2 metres since previous post-processing'
    • 'Minimum temperature at 2 metres since previous post-processing'

    'param':'2t/mx2t/mn2t' (short names)

    or

    'param':'167.128/201.128/202.128' (MARS parameter IDs)

    8
    		>

    Click 'View the MARS request'


    The resulting WebAPI Python script to download data:

    py

    These specifications give you hourly data from 2015-01-

    This results in hourly data from January

    01, 06:00 to

    February

    2015-02-01, 06:00

    (discard

    . 

    Discard the last 6 hours (2015-02-01, 00:01 to 06:00).

    You still need the first six hours of the first day, get these

     

    The data does not cover the period 00:00 to 06:00 of the first date.  Retrieve these 6 hours from the last forecast of the previous day

    :
  • type : fc
    • date :

    ('date':'2014-12-31

    ', 'time':'18:00

    ', 'step':'7/8/9/10/11/12

    Sample Python script for the ECMWF WebAPI:

    Code Block
    languagepy
    #!/usr/bin/env python
from ecmwfapi import ECMWFDataServer
server = ECMWFDataServer()
server.retrieve({
    "class": "ea",
    "dataset": "era5",
    "stream": "oper",
    "expver": "1",
    "date": "2015-01-01/to/2015-01-31",
    "type": "fc",
    "levtype": "sfc",
    "param": "201.128/202.128",             # 'Maximum temperature at 2 metres since previous post-processing' and 'Minimum temperature at 2 metres since previous post-processing'
    "time": "06:00:00/18:00:00",            # 2 forecasts per day, starting at 06:00 and 12:00
    "step": "1/2/3/4/5/6/7/8/9/10/11/12",   # For each forecast 18 one-hour steps are available. Here we use only steps 1 to 12.
    "grid": "0.30/0.30",
    "area": "60/-10/20/50",
    "target": "output",                     # change this to your output file name
})
    The above script retrieves Min and Max 2m temperature since previous post-processing, from 2015-01-01 06:00 to 2015-02-01 06:00, as one-hour periods. To identify

    ')

    To find the average 2 metre temperature per day, average the hourly 2t values per date.

    To find the daily max/min, find the the max/min of

    these one-hour maxima/minima

    the hourly mx2t/mn2t per date.


    See also

    What is

    The family of ERA5 datasets

    ERA5: data documentation

    How to download ERA5 data via the ECMWF Web API

    Info
    iconfalse

    This document has been produced in the context of the Copernicus Climate Change Service (C3S).

    The activities leading to these results have been contracted by the European Centre for Medium-Range Weather Forecasts, operator of C3S on behalf of the European Union (Delegation Agreement signed on 11/11/2014 and Contribution Agreement signed on 22/07/2021). All information in this document is provided "as is" and no guarantee or warranty is given that the information is fit for any particular purpose.

    The users thereof use the information at their sole risk and liability. For the avoidance of all doubt , the European Commission and the European Centre for Medium - Range Weather Forecasts have no liability in respect of this document, which is merely representing the author's view.

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