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Utilisation of satellite data

in the verification of HIRLAM cloud

forecasts

Christoph Zingerle and Pertti Nurmi

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● verification, the task

● the forecasting system HIRLAM

● observations = satellite data

● making forecast and observation comparable

● an example

● summary

● future

Contents

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Task

● Verification of the HIRLAM cloud forecast

- detection of deficiencies in the cloud forecast scheme

- feasibility of different approaches to verification using satellite data

- methodology of verifying cloud forecasts and its operational implementation

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HIRLAM at FMI

- FMI is running the reference HIRLAM (RCR) operationally

- resolution 0.2 deg horizontal (438x336 grid points, ~ 22 km)

40 levels vertical (up to 10 hPa)

- semi-lagrangian advection

- 3D–Var analysis (no satellite data)

- lateral boundary conditions from ECMWF

- Denmark, Finland, Iceland, Ireland, Netherlands, Norway,

Spain and Sweden (France)

● HIgh Resolution Limited Area Model

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HIRLAM RCR domain

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Satellite Observations

● satellite data at FMI from:

- METEOSAT 7/8:

high resolution (temporal and spatial)

coarse resolution at the edges - like Finland - with limb darkening

- NOAA polar orbiting satellites

high spatial resolution

coarse temporal resolution

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Observation – Forecast

● Model to Satellite: ● Satellite to Model:

- transferring the parameters

forecasted by the model to

observations

- Radiative Transfer Model

uses model data to simulate

observed radiances and Tb’s

- transferring the observations

to parameters forecasted by

the model

- Cloud classification scheme

generally thresholding methods

based on typical cloud properties

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Model to Satellite

● Radiative Transfer Model (RTM)- RTTOV 7

- a fast RTM for the assimilation of satellite data

calculates radiances (and Tb's) as seen by a satellite instrument

uses profiles of temperature

humidity

cloud fraction

cloud liquid water

cloud ice water

ozone

surface properties

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Model to Satellite

● 'synthetic' NOAA AVHRR image (10.8µ)

- 24 h forecast from HIRLAM

- AVHRR because of the

high resolution provided

even at the poles

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Observation Re-sampling

● NOAA AVHRR satellite image

- re-sampling needed

- preprocessed (AAPP) AVHRR image (calibrated and navigated) pixel center in the grid-box corresponding to the HIRLAM grid pixel assigned to this grid-box

- Assumptions:

HIRLAM grid value represents average over all the values in box

neighbouring pixels don't differ much from each other

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full resolution, 30.4.2004 (10.8µ) after re-sampling, 30.4.2004 (10.8µ)

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simulated, 30.4.2004 (10.8µ) observed, 30.4.2004 (10.8µ)

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Difference:observed - simulated

Difference > 40 K:Model error?

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observed / simulated Tbrelative frequency of Tb

observedsimulated

Summary distributions

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Summary

● RTTOV - a tool to simulate satellite measurements as close as possible- surface parameters and transmission (clouds) dependent

● observations - simple re-sampling of NOAA AVHRR data is sufficient- re-sampling will be more sophisticated for other instruments

● verification of HIRLAM- cloud forecast scheme not yet verified extensively- approach to verification looks promising

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Future

● examine approaches to verification- satellite to observation approach (SAFNWC software)- pattern recognition methods

● expand to other satellite data (instruments)

- Meteosat data over Europe- polar orbiting satellites over Scandinavia and Nordic Countries

● operational verification- refine methodology to verify cloud forecasts- improve the operational verification package of FMI