Empirical Statistical Downscaling (ESD): Analog Method · Empirical Statistical Downscaling (ESD):...

CORDEX Central America and South America

Training Workshop on Downscaling Techniques

La Paz, Bolivia, June 25-27 2018

Empirical Statistical Downscaling

(ESD): Analog Method

ESD TechniquesESD methods can be classified accordingthe type of the Statistical Technique

Transfer FunctionsBased on linear or nonlinear

regression models

Analogs and Weather Typing

Weather Generators

Wilby et al., 2004; Wilby & Fowler, 2010

Transfer FunctionsBased on linear or nonlinear

regression models

Weather Generators

The downscaling methods relate weatherclasses to local and regional weather conditions.

For instanceAnalogs and Weather

Typing

The downscaling methods relate weatherclasses to local and regional weather conditions.

SLP and Vector Wind at 1000 hPa

Analog Method In the analogue method, historical large-scale weather situations similar (according to a selected metric) to the large-scale weather situation on a given target day are identified.

Historical data

1979 2000 2018

Period of interest to be downscaled

Historical data

1979 2000 2018

23/01/2004

Target day

Historical data

1979 2000 2018

23/01/2004

Target day

Large-scale weather situation on the target day (SLP)

Historical data

1979 2000 2018

23/01/2004

Target day

Local climate associated to this situation: ???

Historical data

1979 2000 2018

23/01/2004

Target day

We look for the most similar structure in the historical data

Historical data

1979 2000 2018

23/01/2004

Target day

Historical data

1979 2000 2018

23/01/2004

Target day

Known Surface local variables

TxTnPr

Analog MethodThen, the corresponding historical local weather conditions are used to estimate local weather conditions on the target day.

Historical data

1979 2000 2018

23/01/2004

Target day

TxTnPr

ANALOGS

Analog MethodThen, the corresponding historical local weather conditions are used to estimate local weather conditions on the target day.

Historical data

1979 2000 2018

23/01/2004

Target day

TxTnPr

Analog Method In the whole process several decisions have to be made ….

Historical data

1979 2000 2018

23/01/2004

Target day

Large-scale weather situation on the target day (SLP)• What large scale variables should be considered to

define de large scale weather situation?• Which is the best domain size for those variables?• How do we get the information about those

variables? Raw data? EOF?

Analog Method

How do we look for the most similar large scale weather situation? Which is the best period of historical data to be considered?Which is the best metric? (Euclidean Distance is the most common)

Historical data

1979 2000 2018

23/01/2004

Target day

In the whole process several decisions have to be made ….

Analog Method

Historical data

1979 2000 2018

23/01/2004

Target day

TxTnPr

How do we estimate local weather conditions using the analogs?

Analog Method

Historical data

1979 2000 2018

23/01/2004

Target day

TxTnPr

The nearest neighbor: we consider the most similar large-scale situation (lowest distance), just one analog.

Analog Method

Historical data

1979 2000 2018

23/01/2004

Target day

TxTnPr

We can also consider the average of several analogs (n).

Analog Method

Historical data

1979 2000 2018

23/01/2004

Target day

TxTnPr

Or we just can pick a random analog among the n analogs

Analog Method

It is able to be applied to both normally and non-normally variables such as local temperatures and precipitation.

With a relatively simple design, the analog method has shown to perform as well as more complicated methods.

However, it is incapable of predicting new values that are outside the range of the historical data.

Our training is on Analogs ….

Analog Method We will use the Climate4R tool developed by the Santander Meteorology Grouphttps://www.meteo.unican.es/en/climate4R

Empirical Statistical Downscaling (ESD): Analog Method · Empirical Statistical Downscaling (ESD):...

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