Page History

Table of Contents

Creation of ER-M-Climate

The ER-M-Climate is derived from a set of extended range re-forecasts created using the same calendar start dates over several years for data times either side of the time of the extended ensemble run itself.  The re-forecast runs are at the same resolution as the extended medium range run itself and run over the 46-day extended range ENS period. 

There is merit in examining the real-time performance of a forecasting system.   But the sample sizes created for one system are far too small to conclude anything about its true performance levels.  Re-forecasts are used to increase the available data to produce a model climate.   The results of forecast system may be compared with this model climate.

Re-forecasts are a fundamental component of all seasonal forecasting system; they have two applications:

• extended range forecast verification metrics are based on the re-forecasts.
  
• re-forecasts allow computation of the ER-M-climate which allows actual forecasts to be converted into an anomaly format.   Forecasts in terms of anomalies relative to a model climate (rather than relative to the observed climatology) mean that some calibration for model bias and drift into the products is incorporated.

Selection of extended range re-forecasts

The set of re-forecasts is based on using the three consecutive dates surrounding the day and month of the extended ENS run in question.  Re-forecasts are climate is used in association with Extended Range ENS forecasts, primarily to highlight significant forecast anomalies in weekly averages of 2m temperature, soil temperature and sea-surface temperature, mean sea level pressure, and precipitation from the norm for a given location and time of year.To evaluate the ER-M-climate, 3 consecutive re-forecast sets are used, based on Mondays and Thursdays, the middle one of which corresponds to the same date (i.e. day-of-month and month) as the data time of the extended ENS run itself.  These 3 re-forecast sets are each created using the same calendar start dates for each of the last 20 years.   So each ER-M-climate dataset consists of 3 sets of  

The set of re-forecasts is made up from:

• a set of re-forecasts using the same calendar start dates for each of the last 20 years.
• three consecutive re-forecasts (covering a 1 week period), the middle one of which corresponds to the preceding Monday or Thursday that is closest to the actual ensemble run date.
• each re-forecast is from an 11-member ensemble (1 control and 10 perturbed members) run over the 46-day ensemble forecast period.

In total, each set of re-forecasts consists of Extended Range ENS period.  Therefore altogether 20 years x 3 runs x 11 ENS ensemble members = 660 re-forecast values.  These are available to define the ER-M-climate for a given location and for each forecast parameter, forecast lead-time.   Note also that , calendar start date, location, at forecast intervals of 6 hours.  These are used to define the ER-M-climate re-forecast runs are at the same resolution as the extended range runs themselves (currently ~18km up to day15 and ~36km thereafter).  In fact it is essentially the same re-forecast runs that are utilised to build the M-Climate and the ER-M-Climate; the key difference is that those runs are grouped together in different ways.

ER-M-climate is updated twice a week, every Monday and Thursday, and based on 00UTC runs only (there are no 12UTC re-forecast sets).  The new files start to be used from the 00UTC run that day.  So if one compares, for the same lead-time, the ER-M-climate quantile plots (e.g. for a Thursday run, and a run the following Monday, they will be slightly different as the ER-M-climate changes).  The impact of twice-weekly updates to the ER-M-climate is similar to that for M-climate and can be significant, particularly in spring and autumn when mean temperatures are changing most rapidly day by day.  Note also that 33% of the re-forecast members making up the ER-M-Climate change each time that the ER-M-climate is updated.  For the shorter range M-Climate the equivalent change is 1/9 = 11%.  So the ER-M-climate is a little more prone to jumpiness related to sampling.

.

A lower number of re-forecasts than for evaluating M-climate is justified because the tails are less important and should not be so prone to having a reduced sample size.

The ER-M-climate is used in association with the extended range ensemble forecast:

• to present the day15 to day46 ensemble meteograms with the extended range climate (ER-M-climate).
• to highlight significant anomalies of forecast 2m temperature, wind speed, cloudiness and precipitation from the norm for a given location and time of year.  

Different reference periods for M-Climate and ER-M-Climate

ECMWF uses different reference periods but essentially the same re-forecast runs to build One might ask why ECMWF uses different length reference periods to define the M-Climate and the ER-M-Climate.   The reason key difference is that they those runs are grouped and used in different ways.  In the :  

• For shorter ranges,

...

• the priority is the best possible capture of the climatological distribution

...

• of the tails (e.g. extreme forecast index (EFI) and shift of tails (SOT)).  This can be better achieved using a re-forecast span of 5 weeks (1980 re-forecast values).  
• For longer ranges, the priority is the correct representation of seasonal cycles

...

• .  This can be better achieved by

...

• using a span of 1 week (660 re-forecast values).  The tails should not be so prone to having a reduced sample size

...

• .

Note before Cy41r1 in spring 2015, the M-climate was constructed from only 500 re-forecasts was more prone to sampling errors and as a result.