Loc Clim Local Climate Estimator Jrgen Grieser And

Loc. Clim Local Climate Estimator Jürgen Grieser And The Agromet Group And Jeroen Ticheler Environment and Natural Resources Service SDRN

Local Climate Estimator Estimates the Climate at a given location.

Why should this be important? • In order to investigate climatic constraints. • investigate deviations from „Normal“ states. • compare different locations.

Why should this be a difficult problem? • Climate is highly variable in time and space. • This variability happens to occur on all scales. - Pole/Equator - South/North of a tree

How does Loc. Clim estimate the local climate? How good does Loc. Clim estimate the local climate?

How to estimate the climate of a given location? • Nearest-Neighbor Approximation

How to estimate the climate of a given location? • Nearest-Neighbor Approximation =

How to estimate the climate of a given location? • Simple Averaging Fixed number of neighbors Fixed maximum distance

How to estimate the climate of a given location? • Weighted Averaging Observations • Inverse Distance

How to estimate the climate of a given location? • Weighted Averaging • Inverse Distance

How to estimate the climate of a given location? • Weighted Averaging • Inverse Distance • According neighborhood (shadowing)

How to estimate the climate of a given location? • Weighted Averaging • Inverse Distance • According neighborhood (shadowing) • According to altitude

How to estimate the climate of a given location? • Systematic Approximations Altitude • Altitude Functions Observations

How to estimate the climate of a given location? • Systematic Approximations Observations • Horizontal Functions Horizontal Coordinates

Which method is the best? • • Nearest Neighbor Simple Averaging Inverse Distance Weighted Averaging Shadow Controlled Averaging • Systematic Altitude Function • Systematic Horizontal Function There is no general answer!

1. Altitude Correction to reduce all obseravtions to the Altitude of the desired location. Altitude What is Loc. Clim doing? Observations

1. Altitude Correction to reduce all obseravtions to the Altitude of the desired location. Altitude What is Loc. Clim doing? Observations

1. Altitude Correction to reduce all obseravtions to the Altitude of the desired location. Altitude What is Loc. Clim doing? Observations

1. Altitude Correction to reduce all obseravtions to the Altitude of the desired location. Altitude What is Loc. Clim doing? Observations

1. Altitude Correction to reduce all obseravtions to the Altitude of the desired location. Altitude What is Loc. Clim doing? Observations

What is Loc. Clim doing? 1. Altitude Correction

What is Loc. Clim doing? Observations 1. Altitude Correction 2. Horizontal Correction Horizontal Coordinates

What is Loc. Clim doing? Observations 1. Altitude Correction 2. Horizontal Correction Horizontal Coordinates

What is Loc. Clim doing? Observations 1. Altitude Correction 2. Horizontal Correction Horizontal Coordinates

What is Loc. Clim doing? 1. Altitude Correction 2. Horizontal Correction 3. Inverse Distance Weighted Averaging

What is Loc. Clim doing? 1. 2. 3. 4. Altitude Correction Horizontal Correction Inverse Distance Weighting Shadow Controlled Weighting

How good is the estimate? • Depends on region and climate variable • LOCLIM only estimates the expectation value of the observation - not the truth.

Quality Assessment

Quality Assessment

Quality Assessment • Calculate the estimation error at every station • Average Error = Bias • Variability = Local Climate Variability

Quality Assessment Altitude Never trust extrapolated data. Observations

Quality Assessment Altitude Never trust extrapolated data. Observations

Quality Assessment Altitude Never trust extrapolated data. Observations

Quality Assessment Altitude Never trust extrapolated data. Observations

Quality Assessment Altitude Never trust extrapolated data. Observations

Quality Assessment Altitude Never trust extrapolated data. Observations

Quality Assessment Altitude Never trust extrapolated data. Observations

Are there enough data?

Global Database (maintained by Fulvia Petrassi, The Agromet Group) Variable (Monthly Values) Number of stations Max. Distance (km) if homogeneously distributed Mean Temperature 20828 49 km Minimum Temperature 11550 65 km Maximum Temperature 11544 65 km Precipitation 27375 43 km Potential Evapotranspiration 4285 107 km Windspeed 3779 114 km Vapor Pressure 3959 111 km

Let‘s try it!

Maximale Entfernung bei gleichmäßiger Verteilung:

Maximale Entfernung bei gleichmäßiger Verteilung: Variable Max. Entfernung Stationen Temp. 49 km 20828 Min. T. 65 km 11550 Max. T. 65 km 11544 Nieder. 43 km 27375 PET 107 km 4285 Wind 114 km 3779 Dampf 111 km 3959

Mögliche Fehlerquellen • • • Systematische Fehler: - Horizontalgradient der Variable - Vertikalgradient der Variable -. . . Statistische Fehler: - Durch lokale Schwankungen - Durch Ausreißer (Ort, Wert) -. . . Behandlung mit Jackknife-Verfahren

How does the climate look like at any location on Earth? • Investigate climatic constraints • Investigate deviations from normals (average conditions) • Compare different locations