1. SAL - Structure, Ampliutde, Location
Institute for Atmospheric Physics – University of Mainz
Name of method:
SAL - Structure, Ampliutde, Location
Investigators:
Marcus Paulat, Heini Wernli – Institute for Atmospheric Physics, University of Mainz
Christoph Frei – Bundesamt für Meteorologie und Klimatologie, MeteoSwiss Zürich
Martin Hagen - Institut für Physik der Atmosphäre, DLR Oberpfaffenhofen
Literature / References: none
- presentations at workshops in Boulder (2006) and ECMWF (2007)
- manuscript in preparation (Wernli et al., MWR)
16. February 2007

2. What kind of data? only gridded data
fields: so far only precipitation, in principle also applicable to other fields with well-structures signatures (e.g. wind gusts)
presently used FC data: ECMWF and COSMO-LM precipitation forecasts (accumulated over 1 or 24 h) over Germany on rotated lon/lat grid with 7 km horizontal resolution
presently used OBS data: gridded rain gauge data set on same grid as models, based upon ~4000 stations with 24 h values; 1-h disaggregated fields through combination of rain gauge and radar data
Marcus Paulat Christoph Frei Martin Hagen Heini Wernli

3. Basic strategy (I): General concept
consider precipitation in pre-specified area (e.g. river catchment)
SAL consists of three independent components
components address quality of structure (S), amplitude (A) and location (L) of QPF in that area
according to SAL a forecast is perfect if S = A = L = 0
S requires the definition of precipitation objects, using a threshold value
but: no attribution between precipitation objects in forecast and observations!
Marcus Paulat Christoph Frei Martin Hagen Heini Wernli

4. Basic strategy (II): Definition of the components
A = (D(Rmod) - D(Robs)) / 0.5*(D(Rmod) + D(Robs))
D(…) denotes the area-mean value (e.g. catchment)
normalized amplitude error in considered area
A  [-2, …, 0, …, +2]
L = |r(Rmod) - r(Robs)| / distmax
r(…) denotes the centre of gravity of the precipitation field in the area
normalized location error in considered area
L  [0, …, 1]
A = amplitude error
L = location error
S = structure error
S = (V(Rmod*) - V(Robs*)) / 0.5*(V(Rmod*) + V(Robs*))
V(…) denotes the weighted volume average of all scaled precipitation objects in considered area
normalized structure error in considered area
S  [-2, …, 0, …, +2]
Marcus Paulat Christoph Frei Martin Hagen Heini Wernli

5. circular precipitation object
Basic strategy (III): The S component
scaling for every object: R* = R / Rmax; R*  [Rthresh/Rmax, …, 1] R R*
Rmax 1
S gives information about the size and shape of the objects in a way that is essentially independent of their amplitudes
Rthresh
Rthresh/Rmax x x
V(R)
V(R*)
circular precipitation object
Marcus Paulat Christoph Frei Martin Hagen Heini Wernli

6. Basic strategy (IV): Example 1
Rmax 1
OBS x
V(R*) x R R* 1
MOD
Rmax x
V(R*) x
A < 0
S = 0
Marcus Paulat Christoph Frei Martin Hagen Heini Wernli

7. Basic strategy (V): Example 2
Rmax 1
OBS x
V(R*) x R R* 1
MOD
Rmax x
V(R*) x
A = 0
S > 0
Marcus Paulat Christoph Frei Martin Hagen Heini Wernli

8. summer seasons 2001-2004 for catchment Rhine
S A L - statistics: 24h accumulated
A-component 1 -1 -2 2
S-component
summer seasons for catchment Rhine
aLMo
ECMWF
Marcus Paulat Christoph Frei Martin Hagen Heini Wernli

9. Kind of verification information / Verification questions
3 independent components to quantify quality of structure, amplitude and location of QPF
information is valid for a pre-specified area (e.g. river catchment, state, field campaign area, …)
questions:
- is the domain averaged precipitation amount correctly forecast? -> A
- is the centre of the precipitation distribution in the domain correctly forecast? -> L
- does the forecast capture the typical structure of the precipitation field
(e.g. large broad vs. small peaked objects)? -> S
Marcus Paulat Christoph Frei Martin Hagen Heini Wernli

10. Strength relatively intuitive
physically meaningful information about amplitude, location and structure of QPF
relatively intuitive
SAL approach is close to “subjective human judgement” (claim)
no attribution between objects is required (difficult for small objects)
computationally simple
Marcus Paulat Christoph Frei Martin Hagen Heini Wernli

11. Weaknesses and limitations
non-perfect QPFs can yield S = A = L = 0 (slight modification of L component is underway)
no consideration of orientation of objects
currently very simple definition of objects (threshold value)
S value is sensitive to choice of threshold used for object definition (tests are underway to quantify sensitivity)
so far only preliminary results for Germany have been computed
Marcus Paulat Christoph Frei Martin Hagen Heini Wernli